SHIMMER (1.0): a novel mathematical model for microbial and biogeochemical dynamics in glacier forefield ecosystems

NASA Astrophysics Data System (ADS)

Bradley, J. A.; Anesio, A. M.; Singarayer, J. S.; Heath, M. R.; Arndt, S.

2015-10-01

SHIMMER (Soil biogeocHemIcal Model for Microbial Ecosystem Response) is a new numerical modelling framework designed to simulate microbial dynamics and biogeochemical cycling during initial ecosystem development in glacier forefield soils. However, it is also transferable to other extreme ecosystem types (such as desert soils or the surface of glaciers). The rationale for model development arises from decades of empirical observations in glacier forefields, and enables a quantitative and process focussed approach. Here, we provide a detailed description of SHIMMER, test its performance in two case study forefields: the Damma Glacier (Switzerland) and the Athabasca Glacier (Canada) and analyse sensitivity to identify the most sensitive and unconstrained model parameters. Results show that the accumulation of microbial biomass is highly dependent on variation in microbial growth and death rate constants, Q10 values, the active fraction of microbial biomass and the reactivity of organic matter. The model correctly predicts the rapid accumulation of microbial biomass observed during the initial stages of succession in the forefields of both the case study systems. Primary production is responsible for the initial build-up of labile substrate that subsequently supports heterotrophic growth. However, allochthonous contributions of organic matter, and nitrogen fixation, are important in sustaining this productivity. The development and application of SHIMMER also highlights aspects of these systems that require further empirical research: quantifying nutrient budgets and biogeochemical rates, exploring seasonality and microbial growth and cell death. This will lead to increased understanding of how glacier forefields contribute to global biogeochemical cycling and climate under future ice retreat.

Direct coupling of a genome-scale microbial in silico model and a groundwater reactive transport model.

PubMed

Fang, Yilin; Scheibe, Timothy D; Mahadevan, Radhakrishnan; Garg, Srinath; Long, Philip E; Lovley, Derek R

2011-03-25

The activity of microorganisms often plays an important role in dynamic natural attenuation or engineered bioremediation of subsurface contaminants, such as chlorinated solvents, metals, and radionuclides. To evaluate and/or design bioremediated systems, quantitative reactive transport models are needed. State-of-the-art reactive transport models often ignore the microbial effects or simulate the microbial effects with static growth yield and constant reaction rate parameters over simulated conditions, while in reality microorganisms can dynamically modify their functionality (such as utilization of alternative respiratory pathways) in response to spatial and temporal variations in environmental conditions. Constraint-based genome-scale microbial in silico models, using genomic data and multiple-pathway reaction networks, have been shown to be able to simulate transient metabolism of some well studied microorganisms and identify growth rate, substrate uptake rates, and byproduct rates under different growth conditions. These rates can be identified and used to replace specific microbially-mediated reaction rates in a reactive transport model using local geochemical conditions as constraints. We previously demonstrated the potential utility of integrating a constraint-based microbial metabolism model with a reactive transport simulator as applied to bioremediation of uranium in groundwater. However, that work relied on an indirect coupling approach that was effective for initial demonstration but may not be extensible to more complex problems that are of significant interest (e.g., communities of microbial species and multiple constraining variables). Here, we extend that work by presenting and demonstrating a method of directly integrating a reactive transport model (FORTRAN code) with constraint-based in silico models solved with IBM ILOG CPLEX linear optimizer base system (C library). The models were integrated with BABEL, a language interoperability tool. The modeling system is designed in such a way that constraint-based models targeting different microorganisms or competing organism communities can be easily plugged into the system. Constraint-based modeling is very costly given the size of a genome-scale reaction network. To save computation time, a binary tree is traversed to examine the concentration and solution pool generated during the simulation in order to decide whether the constraint-based model should be called. We also show preliminary results from the integrated model including a comparison of the direct and indirect coupling approaches and evaluated the ability of the approach to simulate field experiment. Published by Elsevier B.V.

Insights from intercomparison of microbial and conventional soil models

NASA Astrophysics Data System (ADS)

Allison, S. D.; Li, J.; Luo, Y.; Mayes, M. A.; Wang, G.

2014-12-01

Changing the structure of soil biogeochemical models to represent coupling between microbial biomass and carbon substrate pools could improve predictions of carbon-climate feedbacks. So-called "microbial models" with this structure make very different predictions from conventional models based on first-order decay of carbon substrate pools. Still, the value of microbial models is uncertain because microbial physiological parameters are poorly constrained and model behaviors have not been fully explored. To address these issues, we developed an approach for inter-comparing microbial and conventional models. We initially focused on soil carbon responses to microbial carbon use efficiency (CUE) and temperature. Three scenarios were implemented in all models at a common reference temperature (20°C): constant CUE (held at 0.31), varied CUE (-0.016°C-1), and 50% acclimated CUE (-0.008°C-1). Whereas the conventional model always showed soil carbon losses with increasing temperature, the microbial models each predicted a temperature threshold above which warming led to soil carbon gain. The location of this threshold depended on CUE scenario, with higher temperature thresholds under the acclimated and constant scenarios. This result suggests that the temperature sensitivity of CUE and the structure of the soil carbon model together regulate the long-term soil carbon response to warming. Compared to the conventional model, all microbial models showed oscillatory behavior in response to perturbations and were much less sensitive to changing inputs. Oscillations were weakest in the most complex model with explicit enzyme pools, suggesting that multi-pool coupling might be a more realistic representation of the soil system. This study suggests that model structure and CUE parameterization should be carefully evaluated when scaling up microbial models to ecosystems and the globe.

Human Immune Function and Microbial Pathogenesis in Human Spaceflight

NASA Technical Reports Server (NTRS)

Pierson, Duane J.; Ott, M.

2006-01-01

This oral presentation was requested by Conference conveners. The requested subject is microbial risk assessment considering changes in the human immune system during flight and microbial diversity of environmental samples aboard the International Space Station (ISS). The presentation will begin with an introduction discussing the goals and limitations of microbial risk assessment during flight. The main portion of the presentation will include changes in the immune system that have been published, historical data from microbial analyses, and initial modeling of the environmental flora aboard ISS. The presentation will conclude with future goals and techniques to enhance our ability to perform microbial risk assessment on long duration missions.

Representing life in the Earth system with soil microbial functional traits in the MIMICS model

NASA Astrophysics Data System (ADS)

Wieder, W. R.; Grandy, A. S.; Kallenbach, C. M.; Taylor, P. G.; Bonan, G. B.

2015-02-01

Projecting biogeochemical responses to global environmental change requires multi-scaled perspectives that consider organismal diversity, ecosystem processes and global fluxes. However, microbes, the drivers of soil organic matter decomposition and stabilization, remain notably absent from models used to project carbon cycle-climate feedbacks. We used a microbial trait-based soil carbon (C) model, with two physiologically distinct microbial communities to improve current estimates of soil C storage and their likely response to perturbations. Drawing from the application of functional traits used to model other ecosystems, we incorporate copiotrophic and oligotrophic microbial functional groups in the MIcrobial-MIneral Carbon Stabilization (MIMICS) model, which incorporates oligotrophic and copiotrophic functional groups, akin to "gleaner" vs. "opportunist" plankton in the ocean, or r vs. K strategists in plant and animals communities. Here we compare MIMICS to a conventional soil C model, DAYCENT, in cross-site comparisons of nitrogen (N) enrichment effects on soil C dynamics. MIMICS more accurately simulates C responses to N enrichment; moreover, it raises important hypotheses involving the roles of substrate availability, community-level enzyme induction, and microbial physiological responses in explaining various soil biogeochemical responses to N enrichment. In global-scale analyses, we show that current projections from Earth system models likely overestimate the strength of the land C sink in response to increasing C inputs with elevated carbon dioxide (CO2). Our findings illustrate that tradeoffs between theory and utility can be overcome to develop soil biogeochemistry models that evaluate and advance our theoretical understanding of microbial dynamics and soil biogeochemical responses to environmental change.

Noninvasive methods for dynamic mapping of microbial populations across the landscape

NASA Astrophysics Data System (ADS)

Meredith, L. K.; Sengupta, A.; Troch, P. A.; Volkmann, T. H. M.

2017-12-01

Soil microorganisms drive key ecosystem processes, and yet characterizing their distribution and activity in soil has been notoriously difficult. This is due, in part, to the heterogeneous nature of their response to changing environmental and nutrient conditions across time and space. These dynamics are challenging to constrain in both natural and experimental systems because of sampling difficulty and constraints. For example, soil microbial sampling at the Landscape Evolution Observatory (LEO) infrastructure in Biosphere 2 is limited in efforts to minimize soil disruption to the long term experiment that aims to characterize the interacting biological, hydrological, and geochemical processes driving soil evolution. In this and other systems, new methods are needed to monitor soil microbial communities and their genetic potential over time. In this study, we take advantage of the well-defined boundary conditions on hydrological flow at LEO to develop a new method to nondestructively characterize in situ microbial populations. In our approach, we sample microbes from the seepage flow at the base of each of three replicate LEO hillslopes and use hydrological models to `map back' in situ microbial populations. Over the course of a 3-month periodic rainfall experiment we collected samples from the LEO outflow for DNA and extraction and microbial community composition analysis. These data will be used to describe changes in microbial community composition over the course of the experiment. In addition, we will use hydrological flow models to identify the changing source region of discharge water over the course of periodic rainfall pulses, thereby mapping back microbial populations onto their geographic origin in the slope. These predictions of in situ microbial populations will be ground-truthed against those derived from destructive soil sampling at the beginning and end of the rainfall experiment. Our results will show the suitability of this method for long-term, non-destructive monitoring of the microbial communities that contribute to soil evolution in this large-scale model system. Furthermore, this method may be useful for other study systems with limitations to destructive sampling including other model infrastructures and natural landscapes.

Quantitative analysis of transverse bacterial migration induced by chemotaxis in a packed column with structured physical heterogeneity.

PubMed

Wang, Meng; Ford, Roseanne M

2010-01-15

A two-dimensional mathematical model was developed to simulate transport phenomena of chemotactic bacteria in a sand-packed column designed with structured physical heterogeneity in the presence of a localized chemical source. In contrast to mathematical models in previous research work, in which bacteria were typically treated as immobile colloids, this model incorporated a convective-like chemotaxis term to represent chemotactic migration. Consistency between experimental observation and model prediction supported the assertions that (1) dispersion-induced microbial transfer between adjacent conductive zones occurred at the interface and had little influence on bacterial transport in the bulk flow of the permeable layers and (2) the enhanced transverse bacterial migration in chemotactic experiments relative to nonchemotactic controls was mainly due to directed migration toward the chemical source zone. On the basis of parameter sensitivity analysis, chemotactic parameters determined in bulk aqueous fluid were adequate to predict the microbial transport in our intermediate-scale porous media system. Additionally, the analysis of adsorption coefficient values supported the observation of a previous study that microbial deposition to the surface of porous media might be decreased under the effect of chemoattractant gradients. By quantitatively describing bacterial transport and distribution in a heterogeneous system, this mathematical model serves to advance our understanding of chemotaxis and motility effects in granular media systems and provides insights for modeling microbial transport in in situ microbial processes.

Monitoring and modeling of microbial and biological water quality

USDA-ARS?s Scientific Manuscript database

Microbial and biological water quality informs on the health of water systems and their suitability for uses in irrigation, recreation, aquaculture, and other activities. Indicators of microbial and biological water quality demonstrate high spatial and temporal variability. Therefore, monitoring str...

Biofilm community succession: a neutral perspective.

PubMed

Woodcock, Stephen; Sloan, William T

2017-05-22

Although biofilms represent one of the dominant forms of life in aqueous environments, our understanding of the assembly and development of their microbial communities remains relatively poor. In recent years, several studies have addressed this and have extended the concepts of succession theory in classical ecology into microbial systems. From these datasets, niche-based conceptual models have been developed explaining observed biodiversity patterns and their dynamics. These models have not, however, been formulated mathematically and so remain untested. Here, we further develop spatially resolved neutral community models and demonstrate that these can also explain these patterns and offer alternative explanations of microbial succession. The success of neutral models suggests that stochastic effects alone may have a much greater influence on microbial community succession than previously acknowledged. Furthermore, such models are much more readily parameterised and can be used as the foundation of more complex and realistic models of microbial community succession.

Reply to 'Comment on kinetic modeling of microbially-driven redox chemistry of subsurface environments: coupling transport, microbial metabolism and geochemistry' by J. Griffioen

NASA Astrophysics Data System (ADS)

Hunter, K. S.; Van Cappellen, P.

2000-01-01

Our paper, 'Kinetic modeling of microbially-driven redox chemistry of subsurface environments: coupling transport, microbial metabolism and geochemistry' (Hunter et al., 1998), presents a theoretical exploration of biogeochemical reaction networks and their importance to the biogeochemistry of groundwater systems. As with any other model, the kinetic reaction-transport model developed in our paper includes only a subset of all physically, biologically and chemically relevant processes in subsurface environments. It considers aquifer systems where the primary energy source driving microbial activity is the degradation of organic matter. In addition to the primary biodegradation pathways of organic matter (i.e. respiration and fermentation), the redox chemistry of groundwaters is also affected by reactions not directly involving organic matter oxidation. We refer to the latter as secondary reactions. By including secondary redox reactions which consume reduced reaction products (e.g., Mn2+, FeS, H2S), and in the process compete with microbial heterotrophic populations for available oxidants (i.e. O2, NO3-, Mn(IV), Fe(III), SO42-), we predict spatio-temporal distributions of microbial activity which differ significantly from those of models which consider only the biodegradation reactions. That is, the secondary reactions have a significant impact on the distributions of the rates of heterotrophic and chemolithotrophic metabolic pathways. We further show that secondary redox reactions, as well as non-redox reactions, significantly influence the acid-base chemistry of groundwaters. The distributions of dissolved inorganic redox species along flowpaths, however, are similar in simulations with and without secondary reactions (see Figs. 3(b) and 7(b) in Hunter et al., 1998), indicating that very different biogeochemical reaction dynamics may lead to essentially the same chemical redox zonation of a groundwater system.

Representing life in the Earth system with soil microbial functional traits in the MIMICS model

NASA Astrophysics Data System (ADS)

Wieder, W. R.; Grandy, A. S.; Kallenbach, C. M.; Taylor, P. G.; Bonan, G. B.

2015-06-01

Projecting biogeochemical responses to global environmental change requires multi-scaled perspectives that consider organismal diversity, ecosystem processes, and global fluxes. However, microbes, the drivers of soil organic matter decomposition and stabilization, remain notably absent from models used to project carbon (C) cycle-climate feedbacks. We used a microbial trait-based soil C model with two physiologically distinct microbial communities, and evaluate how this model represents soil C storage and response to perturbations. Drawing from the application of functional traits used to model other ecosystems, we incorporate copiotrophic and oligotrophic microbial functional groups in the MIcrobial-MIneral Carbon Stabilization (MIMICS) model; these functional groups are akin to "gleaner" vs. "opportunist" plankton in the ocean, or r- vs. K-strategists in plant and animal communities. Here we compare MIMICS to a conventional soil C model, DAYCENT (the daily time-step version of the CENTURY model), in cross-site comparisons of nitrogen (N) enrichment effects on soil C dynamics. MIMICS more accurately simulates C responses to N enrichment; moreover, it raises important hypotheses involving the roles of substrate availability, community-level enzyme induction, and microbial physiological responses in explaining various soil biogeochemical responses to N enrichment. In global-scale analyses, we show that MIMICS projects much slower rates of soil C accumulation than a conventional soil biogeochemistry in response to increasing C inputs with elevated carbon dioxide (CO2) - a finding that would reduce the size of the land C sink estimated by the Earth system. Our findings illustrate that tradeoffs between theory and utility can be overcome to develop soil biogeochemistry models that evaluate and advance our theoretical understanding of microbial dynamics and soil biogeochemical responses to environmental change.

Metabolic Reconstruction and Modeling Microbial Electrosynthesis.

PubMed

Marshall, Christopher W; Ross, Daniel E; Handley, Kim M; Weisenhorn, Pamela B; Edirisinghe, Janaka N; Henry, Christopher S; Gilbert, Jack A; May, Harold D; Norman, R Sean

2017-08-21

Microbial electrosynthesis is a renewable energy and chemical production platform that relies on microbial cells to capture electrons from a cathode and fix carbon. Yet despite the promise of this technology, the metabolic capacity of the microbes that inhabit the electrode surface and catalyze electron transfer in these systems remains largely unknown. We assembled thirteen draft genomes from a microbial electrosynthesis system producing primarily acetate from carbon dioxide, and their transcriptional activity was mapped to genomes from cells on the electrode surface and in the supernatant. This allowed us to create a metabolic model of the predominant community members belonging to Acetobacterium, Sulfurospirillum, and Desulfovibrio. According to the model, the Acetobacterium was the primary carbon fixer, and a keystone member of the community. Transcripts of soluble hydrogenases and ferredoxins from Acetobacterium and hydrogenases, formate dehydrogenase, and cytochromes of Desulfovibrio were found in high abundance near the electrode surface. Cytochrome c oxidases of facultative members of the community were highly expressed in the supernatant despite completely sealed reactors and constant flushing with anaerobic gases. These molecular discoveries and metabolic modeling now serve as a foundation for future examination and development of electrosynthetic microbial communities.

Cheese rind communities provide tractable systems for in situ and in vitro studies of microbial diversity

PubMed Central

Wolfe, Benjamin E.; Button, Julie E.; Santarelli, Marcela; Dutton, Rachel J.

2014-01-01

SUMMARY Tractable microbial communities are needed to bridge the gap between observations of patterns of microbial diversity and mechanisms that can explain these patterns. We developed cheese rinds as model microbial communities by characterizing in situ patterns of diversity and by developing an in vitro system for community reconstruction. Sequencing of 137 different rind communities across 10 countries revealed 24 widely distributed and culturable genera of bacteria and fungi as dominant community members. Reproducible community types formed independent of geographic location of production. Intensive temporal sampling demonstrated that assembly of these communities is highly reproducible. Patterns of community composition and succession observed in situ can be recapitulated in a simple in vitro system. Widespread positive and negative interactions were identified between bacterial and fungal community members. Cheese rind microbial communities represent an experimentally tractable system for defining mechanisms that influence microbial community assembly and function. PMID:25036636

Rate dependent fractionation of sulfur isotopes in through-flowing systems

NASA Astrophysics Data System (ADS)

Giannetta, M.; Sanford, R. A.; Druhan, J. L.

2017-12-01

The fidelity of reactive transport models in quantifying microbial activity in the subsurface is often improved through the use stable isotopes. However, the accuracy of current predictions for microbially mediated isotope fractionations within open through-flowing systems typically depends on nutrient availability. This disparity arises from the common application of a single `effective' fractionation factor assigned to a given system, despite extensive evidence for variability in the fractionation factor between eutrophic environments and many naturally occurring, nutrient-limited environments. Here, we demonstrate a reactive transport model with the capacity to simulate a variable fractionation factor over a range of microbially mediated reduction rates and constrain the model with experimental data for nutrient limited conditions. Two coupled isotope-specific Monod rate laws for 32S and 34S, constructed to quantify microbial sulfate reduction and predict associated S isotope partitioning, were parameterized using a series of batch reactor experiments designed to minimize microbial growth. In the current study, we implement these parameterized isotope-specific rate laws within an open, through-flowing system to predict variable fractionation with distance as a function of sulfate reduction rate. These predictions are tested through a supporting laboratory experiment consisting of a flow-through column packed with homogenous porous media inoculated with the same species of sulfate reducing bacteria used in the previous batch reactors, Desulfovibrio vulgaris. The collective results of batch reactor and flow-through column experiments support a significant improvement for S isotope predictions in isotope-sensitive multi-component reactive transport models through treatment of rate-dependent fractionation. Such an update to the model will better equip reactive transport software for isotope informed characterization of microbial activity within energy and nutrient limited environments.

Bifurcations of a periodically forced microbial continuous culture model with restrained growth rate

NASA Astrophysics Data System (ADS)

Ren, Jingli; Yuan, Qigang

2017-08-01

A three dimensional microbial continuous culture model with a restrained microbial growth rate is studied in this paper. Two types of dilution rates are considered to investigate the dynamic behaviors of the model. For the unforced system, fold bifurcation and Hopf bifurcation are detected, and numerical simulations reveal that the system undergoes degenerate Hopf bifurcation. When the system is periodically forced, bifurcation diagrams for periodic solutions of period-one and period-two are given by researching the Poincaré map, corresponding to different bifurcation cases in the unforced system. Stable and unstable quasiperiodic solutions are obtained by Neimark-Sacker bifurcation with different parameter values. Periodic solutions of various periods can occur or disappear and even change their stability, when the Poincaré map of the forced system undergoes Neimark-Sacker bifurcation, flip bifurcation, and fold bifurcation. Chaotic attractors generated by a cascade of period doublings and some phase portraits are given at last.

A microbial clock provides an accurate estimate of the postmortem interval in a mouse model system

PubMed Central

Metcalf, Jessica L; Wegener Parfrey, Laura; Gonzalez, Antonio; Lauber, Christian L; Knights, Dan; Ackermann, Gail; Humphrey, Gregory C; Gebert, Matthew J; Van Treuren, Will; Berg-Lyons, Donna; Keepers, Kyle; Guo, Yan; Bullard, James; Fierer, Noah; Carter, David O; Knight, Rob

2013-01-01

Establishing the time since death is critical in every death investigation, yet existing techniques are susceptible to a range of errors and biases. For example, forensic entomology is widely used to assess the postmortem interval (PMI), but errors can range from days to months. Microbes may provide a novel method for estimating PMI that avoids many of these limitations. Here we show that postmortem microbial community changes are dramatic, measurable, and repeatable in a mouse model system, allowing PMI to be estimated within approximately 3 days over 48 days. Our results provide a detailed understanding of bacterial and microbial eukaryotic ecology within a decomposing corpse system and suggest that microbial community data can be developed into a forensic tool for estimating PMI. DOI: http://dx.doi.org/10.7554/eLife.01104.001 PMID:24137541

Using integrated environmental modeling to automate a process-based Quantitative Microbial Risk Assessment

EPA Science Inventory

Integrated Environmental Modeling (IEM) organizes multidisciplinary knowledge that explains and predicts environmental-system response to stressors. A Quantitative Microbial Risk Assessment (QMRA) is an approach integrating a range of disparate data (fate/transport, exposure, an...

Using Integrated Environmental Modeling to Automate a Process-Based Quantitative Microbial Risk Assessment (presentation)

EPA Science Inventory

Integrated Environmental Modeling (IEM) organizes multidisciplinary knowledge that explains and predicts environmental-system response to stressors. A Quantitative Microbial Risk Assessment (QMRA) is an approach integrating a range of disparate data (fate/transport, exposure, and...

Density-dependent microbial turnover improves soil carbon model predictions of long-term litter manipulations

NASA Astrophysics Data System (ADS)

Georgiou, Katerina; Abramoff, Rose; Harte, John; Riley, William; Torn, Margaret

2017-04-01

Climatic, atmospheric, and land-use changes all have the potential to alter soil microbial activity via abiotic effects on soil or mediated by changes in plant inputs. Recently, many promising microbial models of soil organic carbon (SOC) decomposition have been proposed to advance understanding and prediction of climate and carbon (C) feedbacks. Most of these models, however, exhibit unrealistic oscillatory behavior and SOC insensitivity to long-term changes in C inputs. Here we diagnose the sources of instability in four models that span the range of complexity of these recent microbial models, by sequentially adding complexity to a simple model to include microbial physiology, a mineral sorption isotherm, and enzyme dynamics. We propose a formulation that introduces density-dependence of microbial turnover, which acts to limit population sizes and reduce oscillations. We compare these models to results from 24 long-term C-input field manipulations, including the Detritus Input and Removal Treatment (DIRT) experiments, to show that there are clear metrics that can be used to distinguish and validate the inherent dynamics of each model structure. We find that widely used first-order models and microbial models without density-dependence cannot readily capture the range of long-term responses observed across the DIRT experiments as a direct consequence of their model structures. The proposed formulation improves predictions of long-term C-input changes, and implies greater SOC storage associated with CO2-fertilization-driven increases in C inputs over the coming century compared to common microbial models. Finally, we discuss our findings in the context of improving microbial model behavior for inclusion in Earth System Models.

Chlorine stress mediates microbial surface attachment in drinking water systems.

PubMed

Liu, Li; Le, Yang; Jin, Juliang; Zhou, Yuliang; Chen, Guowei

2015-03-01

Microbial attachment to drinking water pipe surfaces facilitates pathogen survival and deteriorates disinfection performance, directly threatening the safety of drinking water. Notwithstanding that the formation of biofilm has been studied for decades, the underlying mechanisms for the origins of microbial surface attachment in biofilm development in drinking water pipelines remain largely elusive. We combined experimental and mathematical methods to investigate the role of environmental stress-mediated cell motility on microbial surface attachment in chlorination-stressed drinking water distribution systems. Results show that at low levels of disinfectant (0.0-1.0 mg/L), the presence of chlorine promotes initiation of microbial surface attachment, while higher amounts of disinfectant (>1.0 mg/L) inhibit microbial attachment. The proposed mathematical model further demonstrates that chlorination stress (0.0-5.0 mg/L)-mediated microbial cell motility regulates the frequency of cell-wall collision and thereby controls initial microbial surface attachment. The results reveal that transport processes and decay patterns of chlorine in drinking water pipelines regulate microbial cell motility and, thus, control initial surface cell attachment. It provides a mechanistic understanding of microbial attachment shaped by environmental disinfection stress and leads to new insights into microbial safety protocols in water distribution systems.

Using integrated environmental modeling to automate a process-based Quantitative Microbial Risk Assessment

USDA-ARS?s Scientific Manuscript database

Integrated Environmental Modeling (IEM) organizes multidisciplinary knowledge that explains and predicts environmental-system response to stressors. A Quantitative Microbial Risk Assessment (QMRA) is an approach integrating a range of disparate data (fate/transport, exposure, and human health effect...

A Workflow to Model Microbial Loadings in Watersheds ...

EPA Pesticide Factsheets

Many watershed models simulate overland and instream microbial fate and transport, but few actually provide loading rates on land surfaces and point sources to the water body network. This paper describes the underlying general equations for microbial loading rates associated with 1) land-applied manure on undeveloped areas from domestic animals; 2) direct shedding on undeveloped lands by domestic animals and wildlife; 3) urban or engineered areas; and 4) point sources that directly discharge to streams from septic systems and shedding by domestic animals. A microbial source module, which houses these formulations, is linked within a workflow containing eight models and a set of databases that form a loosely configured modeling infrastructure which supports watershed-scale microbial source-to-receptor modeling by focusing on animal-impacted catchments. A hypothetical example application – accessing, retrieving, and using real-world data – demonstrates the ability of the infrastructure to automate many of the manual steps associated with a standard watershed assessment, culminating with calibrated flow and microbial densities at the pour point of a watershed. Presented at 2016 Biennial Conference, International Environmental Modelling & Software Society.

Data-driven integration of genome-scale regulatory and metabolic network models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Imam, Saheed; Schauble, Sascha; Brooks, Aaron N.

Microbes are diverse and extremely versatile organisms that play vital roles in all ecological niches. Understanding and harnessing microbial systems will be key to the sustainability of our planet. One approach to improving our knowledge of microbial processes is through data-driven and mechanism-informed computational modeling. Individual models of biological networks (such as metabolism, transcription, and signaling) have played pivotal roles in driving microbial research through the years. These networks, however, are highly interconnected and function in concert a fact that has led to the development of a variety of approaches aimed at simulating the integrated functions of two or moremore » network types. Though the task of integrating these different models is fraught with new challenges, the large amounts of high-throughput data sets being generated, and algorithms being developed, means that the time is at hand for concerted efforts to build integrated regulatory-metabolic networks in a data-driven fashion. Lastly, in this perspective, we review current approaches for constructing integrated regulatory-metabolic models and outline new strategies for future development of these network models for any microbial system.« less

Data-driven integration of genome-scale regulatory and metabolic network models

DOE PAGES

Imam, Saheed; Schauble, Sascha; Brooks, Aaron N.; ...

2015-05-05

Microbes are diverse and extremely versatile organisms that play vital roles in all ecological niches. Understanding and harnessing microbial systems will be key to the sustainability of our planet. One approach to improving our knowledge of microbial processes is through data-driven and mechanism-informed computational modeling. Individual models of biological networks (such as metabolism, transcription, and signaling) have played pivotal roles in driving microbial research through the years. These networks, however, are highly interconnected and function in concert a fact that has led to the development of a variety of approaches aimed at simulating the integrated functions of two or moremore » network types. Though the task of integrating these different models is fraught with new challenges, the large amounts of high-throughput data sets being generated, and algorithms being developed, means that the time is at hand for concerted efforts to build integrated regulatory-metabolic networks in a data-driven fashion. Lastly, in this perspective, we review current approaches for constructing integrated regulatory-metabolic models and outline new strategies for future development of these network models for any microbial system.« less

Modeling Global Soil Carbon and Soil Microbial Carbon by Integrating Microbial Processes into the Ecosystem Process Model TRIPLEX-GHG

DOE PAGES

Wang, Kefeng; Peng, Changhui; Zhu, Qiuan; ...

2017-09-28

Microbial physiology plays a critical role in the biogeochemical cycles of the Earth system. However, most traditional soil carbon models are lacking in terms of the representation of key microbial processes that control the soil carbon response to global climate change. In this study, the improved process-based model TRIPLEX-GHG was developed by coupling it with the new MEND (Microbial-ENzyme-mediated Decomposition) model to estimate total global soil organic carbon (SOC) and global soil microbial carbon. The new model (TRIPLEX-MICROBE) shows considerable improvement over the previous version (TRIPLEX-GHG) in simulating SOC. We estimated the global soil carbon stock to be approximately 1195more » Pg C, with 348 Pg C located in the high northern latitudes, which is in good agreement with the well-regarded Harmonized World Soil Database (HWSD) and the Northern Circumpolar Soil Carbon Database (NCSCD). We also estimated the global soil microbial carbon to be 21 Pg C, similar to the 23 Pg C estimated. We found that the microbial carbon quantity in the latitudinal direction showed reversions at approximately 30°N, near the equator and at 25°S. A sensitivity analysis suggested that the tundra ecosystem exhibited the highest sensitivity to a 1°C increase or decrease in temperature in terms of dissolved organic carbon (DOC), microbial biomass carbon (MBC) and mineral-associated organic carbon (MOC). Furthermore, our work represents the first step towards a new generation of ecosystem process models capable of integrating key microbial processes into soil carbon cycles.« less

Modeling Global Soil Carbon and Soil Microbial Carbon by Integrating Microbial Processes into the Ecosystem Process Model TRIPLEX-GHG

NASA Astrophysics Data System (ADS)

Wang, Kefeng; Peng, Changhui; Zhu, Qiuan; Zhou, Xiaolu; Wang, Meng; Zhang, Kerou; Wang, Gangsheng

2017-10-01

Microbial physiology plays a critical role in the biogeochemical cycles of the Earth system. However, most traditional soil carbon models are lacking in terms of the representation of key microbial processes that control the soil carbon response to global climate change. In this study, the improved process-based model TRIPLEX-GHG was developed by coupling it with the new MEND (Microbial-ENzyme-mediated Decomposition) model to estimate total global soil organic carbon (SOC) and global soil microbial carbon. The new model (TRIPLEX-MICROBE) shows considerable improvement over the previous version (TRIPLEX-GHG) in simulating SOC. We estimated the global soil carbon stock to be approximately 1195 Pg C, with 348 Pg C located in the high northern latitudes, which is in good agreement with the well-regarded Harmonized World Soil Database (HWSD) and the Northern Circumpolar Soil Carbon Database (NCSCD). We also estimated the global soil microbial carbon to be 21 Pg C, similar to the 23 Pg C estimated by Xu et al. (2014). We found that the microbial carbon quantity in the latitudinal direction showed reversions at approximately 30°N, near the equator and at 25°S. A sensitivity analysis suggested that the tundra ecosystem exhibited the highest sensitivity to a 1°C increase or decrease in temperature in terms of dissolved organic carbon (DOC), microbial biomass carbon (MBC), and mineral-associated organic carbon (MOC). However, our work represents the first step toward a new generation of ecosystem process models capable of integrating key microbial processes into soil carbon cycles.

Modeling Global Soil Carbon and Soil Microbial Carbon by Integrating Microbial Processes into the Ecosystem Process Model TRIPLEX-GHG

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Kefeng; Peng, Changhui; Zhu, Qiuan

Microbial physiology plays a critical role in the biogeochemical cycles of the Earth system. However, most traditional soil carbon models are lacking in terms of the representation of key microbial processes that control the soil carbon response to global climate change. In this study, the improved process-based model TRIPLEX-GHG was developed by coupling it with the new MEND (Microbial-ENzyme-mediated Decomposition) model to estimate total global soil organic carbon (SOC) and global soil microbial carbon. The new model (TRIPLEX-MICROBE) shows considerable improvement over the previous version (TRIPLEX-GHG) in simulating SOC. We estimated the global soil carbon stock to be approximately 1195more » Pg C, with 348 Pg C located in the high northern latitudes, which is in good agreement with the well-regarded Harmonized World Soil Database (HWSD) and the Northern Circumpolar Soil Carbon Database (NCSCD). We also estimated the global soil microbial carbon to be 21 Pg C, similar to the 23 Pg C estimated. We found that the microbial carbon quantity in the latitudinal direction showed reversions at approximately 30°N, near the equator and at 25°S. A sensitivity analysis suggested that the tundra ecosystem exhibited the highest sensitivity to a 1°C increase or decrease in temperature in terms of dissolved organic carbon (DOC), microbial biomass carbon (MBC) and mineral-associated organic carbon (MOC). Furthermore, our work represents the first step towards a new generation of ecosystem process models capable of integrating key microbial processes into soil carbon cycles.« less

Characterizing Feedback Control Mechanisms in Nonlinear Microbial Models of Soil Organic Matter Decomposition by Stability Analysis

NASA Astrophysics Data System (ADS)

Georgiou, K.; Tang, J.; Riley, W. J.; Torn, M. S.

2014-12-01

Soil organic matter (SOM) decomposition is regulated by biotic and abiotic processes. Feedback interactions between such processes may act to dampen oscillatory responses to perturbations from equilibrium. Indeed, although biological oscillations have been observed in small-scale laboratory incubations, the overlying behavior at the plot-scale exhibits a relatively stable response to disturbances in input rates and temperature. Recent studies have demonstrated the ability of microbial models to capture nonlinear feedbacks in SOM decomposition that linear Century-type models are unable to reproduce, such as soil priming in response to increased carbon input. However, these microbial models often exhibit strong oscillatory behavior that is deemed unrealistic. The inherently nonlinear dynamics of SOM decomposition have important implications for global climate-carbon and carbon-concentration feedbacks. It is therefore imperative to represent these dynamics in Earth System Models (ESMs) by introducing sub-models that accurately represent microbial and abiotic processes. In the present study we explore, both analytically and numerically, four microbe-enabled model structures of varying levels of complexity. The most complex model combines microbial physiology, a non-linear mineral sorption isotherm, and enzyme dynamics. Based on detailed stability analysis of the nonlinear dynamics, we calculate the system modes as functions of model parameters. This dependence provides insight into the source of state oscillations. We find that feedback mechanisms that emerge from careful representation of enzyme and mineral interactions, with parameter values in a prescribed range, are critical for both maintaining system stability and capturing realistic responses to disturbances. Corroborating and expanding upon the results of recent studies, we explain the emergence of oscillatory responses and discuss the appropriate microbe-enabled model structure for inclusion in ESMs.

Quantitative analysis of microbial biomass yield in aerobic bioreactor.

PubMed

Watanabe, Osamu; Isoda, Satoru

2013-12-01

We have studied the integrated model of reaction rate equations with thermal energy balance in aerobic bioreactor for food waste decomposition and showed that the integrated model has the capability both of monitoring microbial activity in real time and of analyzing biodegradation kinetics and thermal-hydrodynamic properties. On the other hand, concerning microbial metabolism, it was known that balancing catabolic reactions with anabolic reactions in terms of energy and electron flow provides stoichiometric metabolic reactions and enables the estimation of microbial biomass yield (stoichiometric reaction model). We have studied a method for estimating real-time microbial biomass yield in the bioreactor during food waste decomposition by combining the integrated model with the stoichiometric reaction model. As a result, it was found that the time course of microbial biomass yield in the bioreactor during decomposition can be evaluated using the operational data of the bioreactor (weight of input food waste and bed temperature) by the combined model. The combined model can be applied to manage a food waste decomposition not only for controlling system operation to keep microbial activity stable, but also for producing value-added products such as compost on optimum condition. Copyright © 2013 The Research Centre for Eco-Environmental Sciences, Chinese Academy of Sciences. Published by Elsevier B.V. All rights reserved.

Investigating the role of biofilms in trihalomethane formation in water distribution systems with a multicomponent model.

PubMed

Abokifa, Ahmed A; Yang, Y Jeffrey; Lo, Cynthia S; Biswas, Pratim

2016-11-01

Biofilms are ubiquitous in the pipes of drinking water distribution systems (DWDSs), and recent experimental studies revealed that the chlorination of the microbial carbon associated with the biofilm contributes to the total disinfection by-products (DBPs) formation with distinct mechanisms from those formed from precursors derived from natural organic matter (NOM). A multiple species reactive-transport model was developed to explain the role of biofilms in DBPs formation by accounting for the simultaneous transport and interactions of disinfectants, organic compounds, and biomass. Using parameter values from experimental studies in the literature, the model equations were solved to predict chlorine decay and microbial regrowth dynamics in an actual DWDS, and trihalomethanes (THMs) formation in a pilot-scale distribution system simulator. The model's capability of reproducing the measured concentrations of free chlorine, suspended biomass, and THMs under different hydrodynamic and temperature conditions was demonstrated. The contribution of bacteria-derived precursors to the total THMs production was found to have a significant dependence on the system's hydraulics, seasonal variables, and the quality of the treated drinking water. Under system conditions that promoted fast bacterial re-growth, the transformation of non-microbial into microbial carbon DBP precursors by the biofilms showed a noticeable effect on the kinetics of THMs formation, especially when a high initial chlorine dose was applied. These conditions included elevated water temperature and high concentrations of nutrients in the influent water. The fraction of THMs formed from microbial sources was found to reach a peak of 12% of the total produced THMs under the investigated scenarios. The results demonstrated the importance of integrating bacterial regrowth dynamics in predictive DBPs formation models. Copyright © 2016 Elsevier Ltd. All rights reserved.

Biotic Interactions in Microbial Communities as Modulators of Biogeochemical Processes: Methanotrophy as a Model System

PubMed Central

Ho, Adrian; Angel, Roey; Veraart, Annelies J.; Daebeler, Anne; Jia, Zhongjun; Kim, Sang Yoon; Kerckhof, Frederiek-Maarten; Boon, Nico; Bodelier, Paul L. E.

2016-01-01

Microbial interaction is an integral component of microbial ecology studies, yet the role, extent, and relevance of microbial interaction in community functioning remains unclear, particularly in the context of global biogeochemical cycles. While many studies have shed light on the physico-chemical cues affecting specific processes, (micro)biotic controls and interactions potentially steering microbial communities leading to altered functioning are less known. Yet, recent accumulating evidence suggests that the concerted actions of a community can be significantly different from the combined effects of individual microorganisms, giving rise to emergent properties. Here, we exemplify the importance of microbial interaction for ecosystem processes by analysis of a reasonably well-understood microbial guild, namely, aerobic methane-oxidizing bacteria (MOB). We reviewed the literature which provided compelling evidence for the relevance of microbial interaction in modulating methane oxidation. Support for microbial associations within methane-fed communities is sought by a re-analysis of literature data derived from stable isotope probing studies of various complex environmental settings. Putative positive interactions between active MOB and other microbes were assessed by a correlation network-based analysis with datasets covering diverse environments where closely interacting members of a consortium can potentially alter the methane oxidation activity. Although, methanotrophy is used as a model system, the fundamentals of our postulations may be applicable to other microbial guilds mediating other biogeochemical processes. PMID:27602021

Metabolic Reconstruction and Modeling Microbial Electrosynthesis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Marshall, Christopher W.; Ross, Daniel E.; Handley, Kim M.

Microbial electrosynthesis is a renewable energy and chemical production platform that relies on microbial cells to capture electrons from a cathode and fix carbon. Yet despite the promise of this technology, the metabolic capacity of the microbes that inhabit the electrode surface and catalyze electron transfer in these systems remains largely unknown. Here, we assembled thirteen draft genomes from a microbial electrosynthesis system producing primarily acetate from carbon dioxide, and their transcriptional activity was mapped to genomes from cells on the electrode surface and in the supernatant. This allowed us to create a metabolic model of the predominant community membersmore » belonging to Acetobacterium, Sulfurospirillum, and Desulfovibrio. According to the model, the Acetobacterium was the primary carbon fixer, and a keystone member of the community. Transcripts of soluble hydrogenases and ferredoxins from Acetobacterium and hydrogenases, formate dehydrogenase, and cytochromes of Desulfovibrio were found in high abundance near the electrode surface. Cytochrome c oxidases of facultative members of the community were highly expressed in the supernatant despite completely sealed reactors and constant flushing with anaerobic gases. The resulting molecular discoveries and metabolic modeling now serve as a foundation for future examination and development of electrosynthetic microbial communities.« less

Metabolic Reconstruction and Modeling Microbial Electrosynthesis

DOE PAGES

Marshall, Christopher W.; Ross, Daniel E.; Handley, Kim M.; ...

2017-08-21

Microbial electrosynthesis is a renewable energy and chemical production platform that relies on microbial cells to capture electrons from a cathode and fix carbon. Yet despite the promise of this technology, the metabolic capacity of the microbes that inhabit the electrode surface and catalyze electron transfer in these systems remains largely unknown. Here, we assembled thirteen draft genomes from a microbial electrosynthesis system producing primarily acetate from carbon dioxide, and their transcriptional activity was mapped to genomes from cells on the electrode surface and in the supernatant. This allowed us to create a metabolic model of the predominant community membersmore » belonging to Acetobacterium, Sulfurospirillum, and Desulfovibrio. According to the model, the Acetobacterium was the primary carbon fixer, and a keystone member of the community. Transcripts of soluble hydrogenases and ferredoxins from Acetobacterium and hydrogenases, formate dehydrogenase, and cytochromes of Desulfovibrio were found in high abundance near the electrode surface. Cytochrome c oxidases of facultative members of the community were highly expressed in the supernatant despite completely sealed reactors and constant flushing with anaerobic gases. The resulting molecular discoveries and metabolic modeling now serve as a foundation for future examination and development of electrosynthetic microbial communities.« less

Development of a Model, Metal-reducing Microbial Community for a System Biology Level Assessment of Desulfovibrio vulgaris as part of a Community

DOE Office of Scientific and Technical Information (OSTI.GOV)

Elias, Dwayne; Schadt, Christopher; Miller, Lance

2010-05-17

One of the largest experimental gaps is between the simplicity of pure cultures and the complexity of open environmental systems, particularly in metal-contaminated areas. These microbial communities form ecosystem foundations, drive biogeochemical processes, and are relevant for biotechnology and bioremediation. A model, metal-reducing microbial community was constructed as either syntrophic or competitive to study microbial cell to cell interactions, cell signaling and competition for resources. The microbial community was comprised of the metal-reducing Desulfovibrio vulgaris Hildenborough and Geobacter sulfurreducens PCA. Additionally, Methanococcus maripaludis S2 was added to study complete carbon reduction and maintain a low hydrogen partial pressure for syntrophismmore » to occur. Further, considerable work has been published on D. vulgaris and the D. vulgaris/ Mc. maripaludis co-culture both with and without stress. We are extending this work by conducting the same stress conditions on the model community. Additionally, this comprehensive investigation includes physiological and metabolic analyses as well as specially designed mRNA microarrays with the genes for all three organisms on one slide so as to follow gene expression changes in the various cultivation conditions as well as being comparable to the co- and individual cultures. Further, state-of -the-art comprehensive AMT tag proteomics allows for these comparisons at the protein level for a systems biology assessment of a model, metal-reducing microbial community. Preliminary data revealed that lactate oxidation by D. vulgaris was sufficient to support both G. sulfurreducens and M. maripaludis via the excretion of H2 and acetate. Fumarate was utilized by G. sulfurreducens and reduced to succinate since neither of the other two organisms can reduce fumarate. Methane was quantified, suggesting acetate and H2 concentrations were sufficient for M. maripaludis. Steady state community cultivation will allow for a comprehensive, system biology level analysis of a metal-reducing microbial community.« less

A Workflow to Model Microbial Loadings in Watersheds ...

EPA Pesticide Factsheets

Many watershed models simulate overland and instream microbial fate and transport, but few actually provide loading rates on land surfaces and point sources to the water body network. This paper describes the underlying general equations for microbial loading rates associated with 1) land-applied manure on undeveloped areas from domestic animals; 2) direct shedding on undeveloped lands by domestic animals and wildlife; 3) urban or engineered areas; and 4) point sources that directly discharge to streams from septic systems and shedding by domestic animals. A microbial source module, which houses these formulations, is linked within a workflow containing eight models and a set of databases that form a loosely configured modeling infrastructure which supports watershed-scale microbial source-to-receptor modeling by focusing on animal-impacted catchments. A hypothetical example application – accessing, retrieving, and using real-world data – demonstrates the ability of the infrastructure to automate many of the manual steps associated with a standard watershed assessment, culminating with calibrated flow and microbial densities at the pour point of a watershed. In the Proceedings of the International Environmental Modelling and Software Society (iEMSs), 8th International Congress on Environmental Modelling and Software, Toulouse, France

Microbial load monitor

NASA Technical Reports Server (NTRS)

Caplin, R. S.; Royer, E. R.

1977-01-01

Design analysis of a microbial load monitor system flight engineering model was presented. Checkout of the card taper and media pump system was fabricated as well as the final two incubating reading heads, the sample receiving and card loading device assembly, related sterility testing, and software. Progress in these areas was summarized.

(A)biotic processes control soil carbon dynamics: quantitative assessment of model complexity, stability and response to perturbations for improving ESMs

NASA Astrophysics Data System (ADS)

Georgiou, K.; Abramoff, R. Z.; Harte, J.; Riley, W. J.; Torn, M. S.

2016-12-01

As global temperatures and atmospheric CO2 concentrations continue to increase, soil microbial activity and decomposition of soil organic matter (SOM) are expected to follow suit, potentially limiting soil carbon storage. Traditional global- and ecosystem-scale models simulate SOM decomposition using linear kinetics, which are inherently unable to reproduce carbon-concentration feedbacks, such as priming of native SOM at elevated CO2 concentrations. Recent studies using nonlinear microbial models of SOM decomposition seek to capture these interactions, and several groups are currently integrating these microbial models into Earth System Models (ESMs). However, despite their widespread ability to exhibit nonlinear responses, these models vary tremendously in complexity and, consequently, dynamics. In this study, we explore, both analytically and numerically, the emergent oscillatory behavior and insensitivity of SOM stocks to carbon inputs that have been deemed `unrealistic' in recent microbial models. We discuss the sources of instability in four models of varying complexity, by sequentially reducing complexity of a detailed model that includes microbial physiology, a mineral sorption isotherm, and enzyme dynamics. We also present an alternative representation of microbial turnover that limits population sizes and, thus, reduces oscillations. We compare these models to several long-term carbon input manipulations, including the Detritus Input and Removal Treatment (DIRT) experiments, to show that there are clear metrics that can be used to distinguish and validate the inherent dynamics of each model structure. We find that traditional linear and nonlinear models cannot readily capture the range of long-term responses observed across the DIRT experiments as a direct consequence of their model structures, and that modifying microbial turnover results in more realistic predictions. Finally, we discuss our findings in the context of improving microbial model behavior for inclusion in ESMs.

Exploring a microbial ecosystem approach to modeling deep ocean biogeochemical cycles

NASA Astrophysics Data System (ADS)

Zakem, E.; Follows, M. J.

2014-12-01

Though microbial respiration of organic matter in the deep ocean governs ocean and atmosphere biogeochemistry, it is not represented mechanistically in current global biogeochemical models. We seek approaches that are feasible for a global resolution, yet still reflect the enormous biodiversity of the deep microbial community and its associated metabolic pathways. We present a modeling framework grounded in thermodynamics and redox reaction stoichiometry that represents diverse microbial metabolisms explicitly. We describe a bacterial/archaeal functional type with two parameters: a growth efficiency representing the chemistry underlying a bacterial metabolism, and a rate limitation given by the rate of uptake of each of the necessary substrates for that metabolism. We then apply this approach to answer questions about microbial ecology. As a start, we resolve two dominant heterotrophic respiratory pathways- reduction of oxygen and nitrate- and associated microbial functional types. We combine these into an ecological model and a two-dimensional ocean circulation model to explore the organization, biogeochemistry, and ecology of oxygen minimum zones. Intensified upwelling and lateral transport conspire to produce an oxygen minimum at mid-depth, populated by anaerobic denitrifiers. This modeling approach should ultimately allow for the emergence of bacterial biogeography from competition of metabolisms and for the incorporation of microbial feedbacks to the climate system.

Metabolic Network Modeling of Microbial Interactions in Natural and Engineered Environmental Systems

PubMed Central

Perez-Garcia, Octavio; Lear, Gavin; Singhal, Naresh

2016-01-01

We review approaches to characterize metabolic interactions within microbial communities using Stoichiometric Metabolic Network (SMN) models for applications in environmental and industrial biotechnology. SMN models are computational tools used to evaluate the metabolic engineering potential of various organisms. They have successfully been applied to design and optimize the microbial production of antibiotics, alcohols and amino acids by single strains. To date however, such models have been rarely applied to analyze and control the metabolism of more complex microbial communities. This is largely attributed to the diversity of microbial community functions, metabolisms, and interactions. Here, we firstly review different types of microbial interaction and describe their relevance for natural and engineered environmental processes. Next, we provide a general description of the essential methods of the SMN modeling workflow including the steps of network reconstruction, simulation through Flux Balance Analysis (FBA), experimental data gathering, and model calibration. Then we broadly describe and compare four approaches to model microbial interactions using metabolic networks, i.e., (i) lumped networks, (ii) compartment per guild networks, (iii) bi-level optimization simulations, and (iv) dynamic-SMN methods. These approaches can be used to integrate and analyze diverse microbial physiology, ecology and molecular community data. All of them (except the lumped approach) are suitable for incorporating species abundance data but so far they have been used only to model simple communities of two to eight different species. Interactions based on substrate exchange and competition can be directly modeled using the above approaches. However, interactions based on metabolic feedbacks, such as product inhibition and synthropy require extensions to current models, incorporating gene regulation and compounding accumulation mechanisms. SMN models of microbial interactions can be used to analyze complex “omics” data and to infer and optimize metabolic processes. Thereby, SMN models are suitable to capitalize on advances in high-throughput molecular and metabolic data generation. SMN models are starting to be applied to describe microbial interactions during wastewater treatment, in-situ bioremediation, microalgae blooms methanogenic fermentation, and bioplastic production. Despite their current challenges, we envisage that SMN models have future potential for the design and development of novel growth media, biochemical pathways and synthetic microbial associations. PMID:27242701

When everything is not everywhere but species evolve: an alternative method to model adaptive properties of marine ecosystems

PubMed Central

Sauterey, Boris; Ward, Ben A.; Follows, Michael J.; Bowler, Chris; Claessen, David

2015-01-01

The functional and taxonomic biogeography of marine microbial systems reflects the current state of an evolving system. Current models of marine microbial systems and biogeochemical cycles do not reflect this fundamental organizing principle. Here, we investigate the evolutionary adaptive potential of marine microbial systems under environmental change and introduce explicit Darwinian adaptation into an ocean modelling framework, simulating evolving phytoplankton communities in space and time. To this end, we adopt tools from adaptive dynamics theory, evaluating the fitness of invading mutants over annual timescales, replacing the resident if a fitter mutant arises. Using the evolutionary framework, we examine how community assembly, specifically the emergence of phytoplankton cell size diversity, reflects the combined effects of bottom-up and top-down controls. When compared with a species-selection approach, based on the paradigm that “Everything is everywhere, but the environment selects”, we show that (i) the selected optimal trait values are similar; (ii) the patterns emerging from the adaptive model are more robust, but (iii) the two methods lead to different predictions in terms of emergent diversity. We demonstrate that explicitly evolutionary approaches to modelling marine microbial populations and functionality are feasible and practical in time-varying, space-resolving settings and provide a new tool for exploring evolutionary interactions on a range of timescales in the ocean. PMID:25852217

When everything is not everywhere but species evolve: an alternative method to model adaptive properties of marine ecosystems.

PubMed

Sauterey, Boris; Ward, Ben A; Follows, Michael J; Bowler, Chris; Claessen, David

2015-01-01

The functional and taxonomic biogeography of marine microbial systems reflects the current state of an evolving system. Current models of marine microbial systems and biogeochemical cycles do not reflect this fundamental organizing principle. Here, we investigate the evolutionary adaptive potential of marine microbial systems under environmental change and introduce explicit Darwinian adaptation into an ocean modelling framework, simulating evolving phytoplankton communities in space and time. To this end, we adopt tools from adaptive dynamics theory, evaluating the fitness of invading mutants over annual timescales, replacing the resident if a fitter mutant arises. Using the evolutionary framework, we examine how community assembly, specifically the emergence of phytoplankton cell size diversity, reflects the combined effects of bottom-up and top-down controls. When compared with a species-selection approach, based on the paradigm that "Everything is everywhere, but the environment selects", we show that (i) the selected optimal trait values are similar; (ii) the patterns emerging from the adaptive model are more robust, but (iii) the two methods lead to different predictions in terms of emergent diversity. We demonstrate that explicitly evolutionary approaches to modelling marine microbial populations and functionality are feasible and practical in time-varying, space-resolving settings and provide a new tool for exploring evolutionary interactions on a range of timescales in the ocean.

Microbial Risk Assessment

NASA Technical Reports Server (NTRS)

Ott, C. M.; Mena, K. D.; Nickerson, C.A.; Pierson, D. L.

2009-01-01

Historically, microbiological spaceflight requirements have been established in a subjective manner based upon expert opinion of both environmental and clinical monitoring results and the incidence of disease. The limited amount of data, especially from long-duration missions, has created very conservative requirements based primarily on the concentration of microorganisms. Periodic reevaluations of new data from later missions have allowed some relaxation of these stringent requirements. However, the requirements remain very conservative and subjective in nature, and the risk of crew illness due to infectious microorganisms is not well defined. The use of modeling techniques for microbial risk has been applied in the food and potable water industries and has exceptional potential for spaceflight applications. From a productivity standpoint, this type of modeling can (1) decrease unnecessary costs and resource usage and (2) prevent inadequate or inappropriate data for health assessment. In addition, a quantitative model has several advantages for risk management and communication. By identifying the variable components of the model and the knowledge associated with each component, this type of modeling can: (1) Systematically identify and close knowledge gaps, (2) Systematically identify acceptable and unacceptable risks, (3) Improve communication with stakeholders as to the reasons for resource use, and (4) Facilitate external scientific approval of the NASA requirements. The modeling of microbial risk involves the evaluation of several key factors including hazard identification, crew exposure assessment, dose-response assessment, and risk characterization. Many of these factors are similar to conditions found on Earth; however, the spaceflight environment is very specialized as the inhabitants live in a small, semi-closed environment that is often dependent on regenerative life support systems. To further complicate modeling efforts, microbial dose-response characteristics may be affected by a potentially dysfunctional crew immune system during a mission. In addition, microbial virulence has been shown to change under certain conditions during spaceflight, further complicating dose-response characterization. An initial study of the applicability of microbial risk assessment techniques was performed using Crew Health Care System (CHeCS) operational data from the International Space Station potable water systems. The risk of infection from potable water was selected as the flight systems and microbial ecology are well defined. This initial study confirmed the feasibility of using microbial risk assessment modeling for spaceflight systems. While no immediate threat was detected, the study identified several medically significant microorganisms that could pose a health risk if uncontrolled. The study also identified several specific knowledge gaps in making a risk assessment and noted that filling these knowledge gaps is essential as the risk estimates may change by orders of magnitude depending on the answers. The current phase of the microbial risk assessment studies focuses on the dose-response relationship of specific infectious agents, focusing on Salmonella enterica Typhimurium, Pseudomonas spp., and Escherichia coli, as their evaluation will provide a better baseline for determining the overall hazard characterization. The organisms were chosen as they either have been isolated on spacecraft or have an identified route of infection during a mission. The characterization will utilize dose-response models selected either from the peer-reviewed literature and/or by using statistical approaches. Development of these modeling and risk assessment techniques will help to optimize flight requirements and to protect the safety, health, and performance of the crew.

Different Mechanisms of Soil Microbial Response to Global Change Result in Different Outcomes in the MIMICS-CN Model

NASA Astrophysics Data System (ADS)

Kyker-Snowman, E.; Wieder, W. R.; Grandy, S.

2017-12-01

Microbial-explicit models of soil carbon (C) and nitrogen (N) cycling have improved upon simulations of C and N stocks and flows at site-to-global scales relative to traditional first-order linear models. However, the response of microbial-explicit soil models to global change factors depends upon which parameters and processes in a model are altered by those factors. We used the MIcrobial-MIneral Carbon Stabilization Model with coupled N cycling (MIMICS-CN) to compare modeled responses to changes in temperature and plant inputs at two previously-modeled sites (Harvard Forest and Kellogg Biological Station). We spun the model up to equilibrium, applied each perturbation, and evaluated 15 years of post-perturbation C and N pools and fluxes. To model the effect of increasing temperatures, we independently examined the impact of decreasing microbial C use efficiency (CUE), increasing the rate of microbial turnover, and increasing Michaelis-Menten kinetic rates of litter decomposition, plus several combinations of the three. For plant inputs, we ran simulations with stepwise increases in metabolic litter, structural litter, whole litter (structural and metabolic), or labile soil C. The cumulative change in soil C or N varied in both sign and magnitude across simulations. For example, increasing kinetic rates of litter decomposition resulted in net releases of both C and N from soil pools, while decreasing CUE produced short-term increases in respiration but long-term accumulation of C in litter pools and shifts in soil C:N as microbial demand for C increased and biomass declined. Given that soil N cycling constrains the response of plant productivity to global change and that soils generate a large amount of uncertainty in current earth system models, microbial-explicit models are a critical opportunity to advance the modeled representation of soils. However, microbial-explicit models must be improved by experiments to isolate the physiological and stoichiometric parameters of soil microbes that shift under global change.

IMGMD: A platform for the integration and standardisation of In silico Microbial Genome-scale Metabolic Models.

PubMed

Ye, Chao; Xu, Nan; Dong, Chuan; Ye, Yuannong; Zou, Xuan; Chen, Xiulai; Guo, Fengbiao; Liu, Liming

2017-04-07

Genome-scale metabolic models (GSMMs) constitute a platform that combines genome sequences and detailed biochemical information to quantify microbial physiology at the system level. To improve the unity, integrity, correctness, and format of data in published GSMMs, a consensus IMGMD database was built in the LAMP (Linux + Apache + MySQL + PHP) system by integrating and standardizing 328 GSMMs constructed for 139 microorganisms. The IMGMD database can help microbial researchers download manually curated GSMMs, rapidly reconstruct standard GSMMs, design pathways, and identify metabolic targets for strategies on strain improvement. Moreover, the IMGMD database facilitates the integration of wet-lab and in silico data to gain an additional insight into microbial physiology. The IMGMD database is freely available, without any registration requirements, at http://imgmd.jiangnan.edu.cn/database.

Modelling coupled microbial processes in the subsurface: Model development, verification, evaluation and application

NASA Astrophysics Data System (ADS)

Masum, Shakil A.; Thomas, Hywel R.

2018-06-01

To study subsurface microbial processes, a coupled model which has been developed within a Thermal-Hydraulic-Chemical-Mechanical (THCM) framework is presented. The work presented here, focuses on microbial transport, growth and decay mechanisms under the influence of multiphase flow and bio-geochemical reactions. In this paper, theoretical formulations and numerical implementations of the microbial model are presented. The model has been verified and also evaluated against relevant experimental results. Simulated results show that the microbial processes have been accurately implemented and their impacts on porous media properties can be predicted either qualitatively or quantitatively or both. The model has been applied to investigate biofilm growth in a sandstone core that is subjected to a two-phase flow and variable pH conditions. The results indicate that biofilm growth (if not limited by substrates) in a multiphase system largely depends on the hydraulic properties of the medium. When the change in porewater pH which occurred due to dissolution of carbon dioxide gas is considered, growth processes are affected. For the given parameter regime, it has been shown that the net biofilm growth is favoured by higher pH; whilst the processes are considerably retarded at lower pH values. The capabilities of the model to predict microbial respiration in a fully coupled multiphase flow condition and microbial fermentation leading to production of a gas phase are also demonstrated.

In-Drift Microbial Communities

DOE Office of Scientific and Technical Information (OSTI.GOV)

D. Jolley

2000-11-09

As directed by written work direction (CRWMS M and O 1999f), Performance Assessment (PA) developed a model for microbial communities in the engineered barrier system (EBS) as documented here. The purpose of this model is to assist Performance Assessment and its Engineered Barrier Performance Section in modeling the geochemical environment within a potential repository drift for TSPA-SR/LA, thus allowing PA to provide a more detailed and complete near-field geochemical model and to answer the key technical issues (KTI) raised in the NRC Issue Resolution Status Report (IRSR) for the Evolution of the Near Field Environment (NFE) Revision 2 (NRC 1999).more » This model and its predecessor (the in-drift microbial communities model as documented in Chapter 4 of the TSPA-VA Technical Basis Document, CRWMS M and O 1998a) was developed to respond to the applicable KTIs. Additionally, because of the previous development of the in-drift microbial communities model as documented in Chapter 4 of the TSPA-VA Technical Basis Document (CRWMS M and O 1998a), the M and O was effectively able to resolve a previous KTI concern regarding the effects of microbial processes on seepage and flow (NRC 1998). This document supercedes the in-drift microbial communities model as documented in Chapter 4 of the TSPA-VA Technical Basis Document (CRWMS M and O 1998a). This document provides the conceptual framework of the revised in-drift microbial communities model to be used in subsequent performance assessment (PA) analyses.« less

Actual measurement, hygrothermal response experiment and growth prediction analysis of microbial contamination of central air conditioning system in Dalian, China

PubMed Central

Lv, Yang; Hu, Guangyao; Wang, Chunyang; Yuan, Wenjie; Wei, Shanshan; Gao, Jiaoqi; Wang, Boyuan; Song, Fangchao

2017-01-01

The microbial contamination of central air conditioning system is one of the important factors that affect the indoor air quality. Actual measurement and analysis were carried out on microbial contamination in central air conditioning system at a venue in Dalian, China. Illumina miseq method was used and three fungal samples of two units were analysed by high throughput sequencing. Results showed that the predominant fungus in air conditioning unit A and B were Candida spp. and Cladosporium spp., and two fungus were further used in the hygrothermal response experiment. Based on the data of Cladosporium in hygrothermal response experiment, this paper used the logistic equation and the Gompertz equation to fit the growth predictive model of Cladosporium genera in different temperature and relative humidity conditions, and the square root model was fitted based on the two environmental factors. In addition, the models were carried on the analysis to verify the accuracy and feasibility of the established model equation. PMID:28367963

Actual measurement, hygrothermal response experiment and growth prediction analysis of microbial contamination of central air conditioning system in Dalian, China.

PubMed

Lv, Yang; Hu, Guangyao; Wang, Chunyang; Yuan, Wenjie; Wei, Shanshan; Gao, Jiaoqi; Wang, Boyuan; Song, Fangchao

2017-04-03

The microbial contamination of central air conditioning system is one of the important factors that affect the indoor air quality. Actual measurement and analysis were carried out on microbial contamination in central air conditioning system at a venue in Dalian, China. Illumina miseq method was used and three fungal samples of two units were analysed by high throughput sequencing. Results showed that the predominant fungus in air conditioning unit A and B were Candida spp. and Cladosporium spp., and two fungus were further used in the hygrothermal response experiment. Based on the data of Cladosporium in hygrothermal response experiment, this paper used the logistic equation and the Gompertz equation to fit the growth predictive model of Cladosporium genera in different temperature and relative humidity conditions, and the square root model was fitted based on the two environmental factors. In addition, the models were carried on the analysis to verify the accuracy and feasibility of the established model equation.

The Study of Microbial Environmental Processes Related to the Natural Attenuation of Uranium at the Rifle Site using Systems-level Biology

DOE Office of Scientific and Technical Information (OSTI.GOV)

Methe, Barbara; Lipton, Mary; Mahadevan, Krishna

Microbes exist in communities in the environment where they are fundamental drivers of global carbon, nutrient and metal cycles. In subsurface environments, they possess significant metabolic potential to affect these global cycles including the transformation of radionuclides. This study examined the influence of microbial communities in sediment zones undergoing biogeochemical cycling of carbon, nutrients and metals including natural attenuation of uranium. This study examined the relationship of both the microbiota (taxonomy) and their metabolic capacity (function) in driving carbon, nutrient and metal cycles including uranium reduction at the Department of Energy (DOE) Rifle Integrated Field Research Challenge (RIFRC). Objectives ofmore » this project were: 1) to apply systems-level biology through application of ‘metaomics’ approaches (collective analyses of whole microbial community DNA, RNA and protein) to the study of microbial environmental processes and their relationship to C, N and metals including the influence of microbial communities on uranium contaminant mobility in subsurface settings undergoing natural attenuation, 2) improve methodologies for data generation using metaomics (collectively metagenomics, metatranscriptomics and proteomics) technologies and analysis and interpretation of that data and 3) use the data generated from these studies towards microbial community-scale metabolic modeling. The strategy for examining these subsurface microbial communities was to generate sequence reads from microbial community DNA (metagenomics or whole genome shotgun sequencing (WGS)) and RNA (metatranscriptomcs or RNAseq) and protein information using proteomics. Results were analyzed independently and through computational modeling. Overall, the community model generated information on the microbial community structure that was observed using metaomic approaches at RIFRC sites and thus provides an important framework for continued community modeling development. The model as created is capable of predicting the response of the community structure in changing environments such as anoxic/oxic conditions or limitations by carbon or nutrients. The ability to more accurately model these responses is critical to understanding carbon and energy flows in an ecosystem is critical towards improving our ability to make predictions that can be used to design more efficient remediation and management strategies, and better understand the implications of environmental perturbations on these ecosystems.« less

Diflerent formulations of microbial respiratory losses and microbial efficiency have pronounced short and long term consequences for soil C dynamics and soil respiration

NASA Astrophysics Data System (ADS)

Ballantyne, F.; Billings, S. A.

2016-12-01

Much of the variability in projections of Earth's future C balance derives from uncertainty in how to formulate and parameterize models of biologically mediated transformations of soil organic C (SOC). Over the past decade, models of belowground decomposition have incorporated more realism, namely microbial biomass and exoenzyme pools, but it remains unclear whether microbially mediated decomposition is accurately formulated. Different models and different assumptions about how microbial efficiency, defined in terms of respiratory losses, varies with temperature exert great influence on SOC and CO2 flux projections for the future. Here, we incorporate a physiologically realistic formulation of CO2 loss from microbes, distinct from extant formulations and logically consistent with microbial C uptake and losses, into belowground dynamics and contrast its projections for SOC pools and CO2 flux from soils to those from the phenomenological formulations of efficiency in current models. We quantitatively describe how short and long term SOC dynamics are influenced by different mathematical formulations of efficiency, and that our lack of knowledge regarding loss rates from SOC and microbial biomass pools, specific respiration rate and maximum substrate uptake rate severely constrains our ability to confidently parameterize microbial SOC modules in Earth System Models. Both steady-state SOC and microbial biomass C pools, as well as transient responses to perturbations, can differ substantially depending on how microbial efficiency is derived. In particular, the discrepancy between SOC stocks for different formulations of efficiency varies from negligible to more than two orders of magnitude, depending on the relative values of respiratory versus non-respiratory losses from microbial biomass. Mass-specific respiration and proportional loss rates from soil microbes emerge as key determinants of the consequences of different formulations of efficiency for C flux in soils.

Elevated temperature alters carbon cycling in a model microbial community

NASA Astrophysics Data System (ADS)

Mosier, A.; Li, Z.; Thomas, B. C.; Hettich, R. L.; Pan, C.; Banfield, J. F.

2013-12-01

Earth's climate is regulated by biogeochemical carbon exchanges between the land, oceans and atmosphere that are chiefly driven by microorganisms. Microbial communities are therefore indispensible to the study of carbon cycling and its impacts on the global climate system. In spite of the critical role of microbial communities in carbon cycling processes, microbial activity is currently minimally represented or altogether absent from most Earth System Models. Method development and hypothesis-driven experimentation on tractable model ecosystems of reduced complexity, as presented here, are essential for building molecularly resolved, benchmarked carbon-climate models. Here, we use chemoautotropic acid mine drainage biofilms as a model community to determine how elevated temperature, a key parameter of global climate change, regulates the flow of carbon through microbial-based ecosystems. This study represents the first community proteomics analysis using tandem mass tags (TMT), which enable accurate, precise, and reproducible quantification of proteins. We compare protein expression levels of biofilms growing over a narrow temperature range expected to occur with predicted climate changes. We show that elevated temperature leads to up-regulation of proteins involved in amino acid metabolism and protein modification, and down-regulation of proteins involved in growth and reproduction. Closely related bacterial genotypes differ in their response to temperature: Elevated temperature represses carbon fixation by two Leptospirillum genotypes, whereas carbon fixation is significantly up-regulated at higher temperature by a third closely related genotypic group. Leptospirillum group III bacteria are more susceptible to viral stress at elevated temperature, which may lead to greater carbon turnover in the microbial food web through the release of viral lysate. Overall, this proteogenomics approach revealed the effects of climate change on carbon cycling pathways and other microbial activities. When scaled to more complex ecosystems and integrated into Earth System Models, this approach could significantly improve predictions of global carbon-climate feedbacks. Experiments such as these are a critical first step designed at understanding climate change impacts in order to better predict ecosystem adaptations, assess the viability of mitigation strategies, and inform relevant policy decisions.

The shift of microbial communities and their roles in sulfur and iron cycling in a copper ore bioleaching system.

PubMed

Niu, Jiaojiao; Deng, Jie; Xiao, Yunhua; He, Zhili; Zhang, Xian; Van Nostrand, J D; Liang, Yili; Deng, Ye; Liu, Xueduan; Yin, Huaqun

2016-10-04

Bioleaching has been employed commercially to recover metals from low grade ores, but the production efficiency remains to be improved due to limited understanding of the system. This study examined the shift of microbial communities and S&Fe cycling in three subsystems within a copper ore bioleaching system: leaching heap (LH), leaching solution (LS) and sediment under LS. Results showed that both LH and LS had higher relative abundance of S and Fe oxidizing bacteria, while S and Fe reducing bacteria were more abundant in the Sediment. GeoChip analysis showed a stronger functional potential for S 0 oxidation in LH microbial communities. These findings were consistent with measured oxidation activities to S 0 and Fe 2+ , which were highest by microbial communities from LH, lower by those from LS and lowest form Sediment. Moreover, phylogenetic molecular ecological network analysis indicated that these differences might be related to interactions among microbial taxa. Last but not the least, a conceptual model was proposed, linking the S&Fe cycling with responsible microbial populations in the bioleaching systems. Collectively, this study revealed the microbial community and functional structures in all three subsystems of the copper ore, and advanced a holistic understanding of the whole bioleaching system.

The shift of microbial communities and their roles in sulfur and iron cycling in a copper ore bioleaching system

NASA Astrophysics Data System (ADS)

Niu, Jiaojiao; Deng, Jie; Xiao, Yunhua; He, Zhili; Zhang, Xian; van Nostrand, J. D.; Liang, Yili; Deng, Ye; Liu, Xueduan; Yin, Huaqun

2016-10-01

Bioleaching has been employed commercially to recover metals from low grade ores, but the production efficiency remains to be improved due to limited understanding of the system. This study examined the shift of microbial communities and S&Fe cycling in three subsystems within a copper ore bioleaching system: leaching heap (LH), leaching solution (LS) and sediment under LS. Results showed that both LH and LS had higher relative abundance of S and Fe oxidizing bacteria, while S and Fe reducing bacteria were more abundant in the Sediment. GeoChip analysis showed a stronger functional potential for S0 oxidation in LH microbial communities. These findings were consistent with measured oxidation activities to S0 and Fe2+, which were highest by microbial communities from LH, lower by those from LS and lowest form Sediment. Moreover, phylogenetic molecular ecological network analysis indicated that these differences might be related to interactions among microbial taxa. Last but not the least, a conceptual model was proposed, linking the S&Fe cycling with responsible microbial populations in the bioleaching systems. Collectively, this study revealed the microbial community and functional structures in all three subsystems of the copper ore, and advanced a holistic understanding of the whole bioleaching system.

The shift of microbial communities and their roles in sulfur and iron cycling in a copper ore bioleaching system

PubMed Central

Niu, Jiaojiao; Deng, Jie; Xiao, Yunhua; He, Zhili; Zhang, Xian; Van Nostrand, J. D.; Liang, Yili; Deng, Ye; Liu, Xueduan; Yin, Huaqun

2016-01-01

Bioleaching has been employed commercially to recover metals from low grade ores, but the production efficiency remains to be improved due to limited understanding of the system. This study examined the shift of microbial communities and S&Fe cycling in three subsystems within a copper ore bioleaching system: leaching heap (LH), leaching solution (LS) and sediment under LS. Results showed that both LH and LS had higher relative abundance of S and Fe oxidizing bacteria, while S and Fe reducing bacteria were more abundant in the Sediment. GeoChip analysis showed a stronger functional potential for S0 oxidation in LH microbial communities. These findings were consistent with measured oxidation activities to S0 and Fe2+, which were highest by microbial communities from LH, lower by those from LS and lowest form Sediment. Moreover, phylogenetic molecular ecological network analysis indicated that these differences might be related to interactions among microbial taxa. Last but not the least, a conceptual model was proposed, linking the S&Fe cycling with responsible microbial populations in the bioleaching systems. Collectively, this study revealed the microbial community and functional structures in all three subsystems of the copper ore, and advanced a holistic understanding of the whole bioleaching system. PMID:27698381

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wieder, William R.; Allison, Steven D.; Davidson, Eric A.

Microbes influence soil organic matter (SOM) decomposition and the long-term stabilization of carbon (C) in soils. We contend that by revising the representation of microbial processes and their interactions with the physicochemical soil environment, Earth system models (ESMs) may make more realistic global C cycle projections. Explicit representation of microbial processes presents considerable challenges due to the scale at which these processes occur. Thus, applying microbial theory in ESMs requires a framework to link micro-scale process-level understanding and measurements to macro-scale models used to make decadal- to century-long projections. Here, we review the diversity, advantages, and pitfalls of simulating soilmore » biogeochemical cycles using microbial-explicit modeling approaches. We present a roadmap for how to begin building, applying, and evaluating reliable microbial-explicit model formulations that can be applied in ESMs. Drawing from experience with traditional decomposition models we suggest: (1) guidelines for common model parameters and output that can facilitate future model intercomparisons; (2) development of benchmarking and model-data integration frameworks that can be used to effectively guide, inform, and evaluate model parameterizations with data from well-curated repositories; and (3) the application of scaling methods to integrate microbial-explicit soil biogeochemistry modules within ESMs. With contributions across scientific disciplines, we feel this roadmap can advance our fundamental understanding of soil biogeochemical dynamics and more realistically project likely soil C response to environmental change at global scales.« less

SHIMMER (1.0): a novel mathematical model for microbial and biogeochemical dynamics in glacier forefield ecosystems

NASA Astrophysics Data System (ADS)

Bradley, J. A.; Anesio, A. M.; Singarayer, J. S.; Heath, M. R.; Arndt, S.

2015-08-01

SHIMMER (Soil biogeocHemIcal Model for Microbial Ecosystem Response) is a new numerical modelling framework which is developed as part of an interdisciplinary, iterative, model-data based approach fully integrating fieldwork and laboratory experiments with model development, testing, and application. SHIMMER is designed to simulate the establishment of microbial biomass and associated biogeochemical cycling during the initial stages of ecosystem development in glacier forefield soils. However, it is also transferable to other extreme ecosystem types (such as desert soils or the surface of glaciers). The model mechanistically describes and predicts transformations in carbon, nitrogen and phosphorus through aggregated components of the microbial community as a set of coupled ordinary differential equations. The rationale for development of the model arises from decades of empirical observation on the initial stages of soil development in glacier forefields. SHIMMER enables a quantitative and process focussed approach to synthesising the existing empirical data and advancing understanding of microbial and biogeochemical dynamics. Here, we provide a detailed description of SHIMMER. The performance of SHIMMER is then tested in two case studies using published data from the Damma Glacier forefield in Switzerland and the Athabasca Glacier in Canada. In addition, a sensitivity analysis helps identify the most sensitive and unconstrained model parameters. Results show that the accumulation of microbial biomass is highly dependent on variation in microbial growth and death rate constants, Q10 values, the active fraction of microbial biomass, and the reactivity of organic matter. The model correctly predicts the rapid accumulation of microbial biomass observed during the initial stages of succession in the forefields of both the case study systems. Simulation results indicate that primary production is responsible for the initial build-up of substrate that subsequently supports heterotrophic growth. However, allochthonous contributions of organic matter are identified as important in sustaining this productivity. Microbial production in young soils is supported by labile organic matter, whereas carbon stocks in older soils are more refractory. Nitrogen fixing bacteria are responsible for the initial accumulation of available nitrates in the soil. Biogeochemical rates are highly seasonal, as observed in experimental data. The development and application of SHIMMER not only provides important new insights into forefield dynamics, but also highlights aspects of these systems that require further field and laboratory research. The most pressing advances need to come in quantifying nutrient budgets and biogeochemical rates, in exploring seasonality, the fate of allochthonous deposition in relation to autochthonous production, and empirical studies of microbial growth and cell death, to increase understanding of how glacier forefield development contributes to the global biogeochemical cycling and climate in the future.

Linking microbial community structure to function in representative simulated systems.

PubMed

Marcus, Ian M; Wilder, Hailey A; Quazi, Shanin J; Walker, Sharon L

2013-04-01

Pathogenic bacteria are generally studied as a single strain under ideal growing conditions, although these conditions are not the norm in the environments in which pathogens typically proliferate. In this investigation, a representative microbial community along with Escherichia coli O157:H7, a model pathogen, was studied in three environments in which such a pathogen could be found: a human colon, a septic tank, and groundwater. Each of these systems was built in the lab in order to retain the physical/chemical and microbial complexity of the environments while maintaining control of the feed into the models. The microbial community in the colon was found to have a high percentage of bacteriodetes and firmicutes, while the septic tank and groundwater systems were composed mostly of proteobacteria. The introduction of E. coli O157:H7 into the simulated systems elicited a shift in the structures and phenotypic cell characteristics of the microbial communities. The fate and transport of the microbial community with E. coli O157:H7 were found to be significantly different from those of E. coli O157:H7 studied as a single isolate, suggesting that the behavior of the organism in the environment was different from that previously conceived. The findings in this study clearly suggest that to gain insight into the fate of pathogens, cells should be grown and analyzed under conditions simulating those of the environment in which the pathogens are present.

Linking Microbial Community Structure to Function in Representative Simulated Systems

PubMed Central

Marcus, Ian M.; Wilder, Hailey A.; Quazi, Shanin J.

2013-01-01

Pathogenic bacteria are generally studied as a single strain under ideal growing conditions, although these conditions are not the norm in the environments in which pathogens typically proliferate. In this investigation, a representative microbial community along with Escherichia coli O157:H7, a model pathogen, was studied in three environments in which such a pathogen could be found: a human colon, a septic tank, and groundwater. Each of these systems was built in the lab in order to retain the physical/chemical and microbial complexity of the environments while maintaining control of the feed into the models. The microbial community in the colon was found to have a high percentage of bacteriodetes and firmicutes, while the septic tank and groundwater systems were composed mostly of proteobacteria. The introduction of E. coli O157:H7 into the simulated systems elicited a shift in the structures and phenotypic cell characteristics of the microbial communities. The fate and transport of the microbial community with E. coli O157:H7 were found to be significantly different from those of E. coli O157:H7 studied as a single isolate, suggesting that the behavior of the organism in the environment was different from that previously conceived. The findings in this study clearly suggest that to gain insight into the fate of pathogens, cells should be grown and analyzed under conditions simulating those of the environment in which the pathogens are present. PMID:23396331

Eco-evolutionary Red Queen dynamics regulate biodiversity in a metabolite-driven microbial system.

PubMed

Bonachela, Juan A; Wortel, Meike T; Stenseth, Nils Chr

2017-12-15

The Red Queen Hypothesis proposes that perpetual co-evolution among organisms can result from purely biotic drivers. After more than four decades, there is no satisfactory understanding as to which mechanisms trigger Red Queen dynamics or their implications for ecosystem features such as biodiversity. One reason for such a knowledge gap is that typical models are complicated theories where limit cycles represent an idealized Red Queen, and therefore cannot be used to devise experimental setups. Here, we bridge this gap by introducing a simple model for microbial systems able to show Red Queen dynamics. We explore diverse biotic sources that can drive the emergence of the Red Queen and that have the potential to be found in nature or to be replicated in the laboratory. Our model enables an analytical understanding of how Red Queen dynamics emerge in our setup, and the translation of model terms and phenomenology into general underlying mechanisms. We observe, for example, that in our system the Red Queen offers opportunities for the increase of biodiversity by facilitating challenging conditions for intraspecific dominance, whereas stasis tends to homogenize the system. Our results can be used to design and engineer experimental microbial systems showing Red Queen dynamics.

High definition for systems biology of microbial communities: metagenomics gets genome-centric and strain-resolved.

PubMed

Turaev, Dmitrij; Rattei, Thomas

2016-06-01

The systems biology of microbial communities, organismal communities inhabiting all ecological niches on earth, has in recent years been strongly facilitated by the rapid development of experimental, sequencing and data analysis methods. Novel experimental approaches and binning methods in metagenomics render the semi-automatic reconstructions of near-complete genomes of uncultivable bacteria possible, while advances in high-resolution amplicon analysis allow for efficient and less biased taxonomic community characterization. This will also facilitate predictive modeling approaches, hitherto limited by the low resolution of metagenomic data. In this review, we pinpoint the most promising current developments in metagenomics. They facilitate microbial systems biology towards a systemic understanding of mechanisms in microbial communities with scopes of application in many areas of our daily life. Copyright © 2016 Elsevier Ltd. All rights reserved.

The ECLSS Advanced Automation Project Evolution and Technology Assessment

NASA Technical Reports Server (NTRS)

Dewberry, Brandon S.; Carnes, James R.; Lukefahr, Brenda D.; Rogers, John S.; Rochowiak, Daniel M.; Mckee, James W.; Benson, Brian L.

1990-01-01

Viewgraphs on Environmental Control and Life Support System (ECLSS) advanced automation project evolution and technology assessment are presented. Topics covered include: the ECLSS advanced automation project; automatic fault diagnosis of ECLSS subsystems descriptions; in-line, real-time chemical and microbial fluid analysis; and object-oriented, distributed chemical and microbial modeling of regenerative environmental control systems description.

Modeling environmental risk factors of autism in mice induces IBD-related gut microbial dysbiosis and hyperserotonemia.

PubMed

Lim, Joon Seo; Lim, Mi Young; Choi, Yongbin; Ko, GwangPyo

2017-04-20

Autism spectrum disorder (ASD) is a range of neurodevelopmental conditions that are sharply increasing in prevalence worldwide. Intriguingly, ASD is often accompanied by an array of systemic aberrations including (1) increased serotonin, (2) various modes of gastrointestinal disorders, and (3) inflammatory bowel disease (IBD), albeit the underlying cause for such comorbidities remains uncertain. Also, accumulating number of studies report that the gut microbial composition is significantly altered in children with ASD or patients with IBD. Surprisingly, when we analyzed the gut microbiota of poly I:C and VPA-induced mouse models of ASD, we found a distinct pattern of microbial dysbiosis that highly recapitulated those reported in clinical cases of ASD and IBD. Moreover, we report that such microbial dysbiosis led to notable perturbations in microbial metabolic pathways that are known to negatively affect the host, especially with regards to the pathogenesis of ASD and IBD. Lastly, we found that serum level of serotonin is significantly increased in both poly I:C and VPA mice, and that it correlates with increases of a bacterial genus and a metabolic pathway that are implicated in stimulation of host serotonin production. Our results using animal model identify prenatal environmental risk factors of autism as possible causative agents of IBD-related gut microbial dysbiosis in ASD, and suggest a multifaceted role of gut microbiota in the systemic pathogenesis of ASD and hyperserotonemia.

Emergence of microbial diversity due to cross-feeding interactions in a spatial model of gut microbial metabolism.

PubMed

Hoek, Milan J A van; Merks, Roeland M H

2017-05-16

The human gut contains approximately 10 14 bacteria, belonging to hundreds of different species. Together, these microbial species form a complex food web that can break down nutrient sources that our own digestive enzymes cannot handle, including complex polysaccharides, producing short chain fatty acids and additional metabolites, e.g., vitamin K. Microbial diversity is important for colonic health: Changes in the composition of the microbiota have been associated with inflammatory bowel disease, diabetes, obesity and Crohn's disease, and make the microbiota more vulnerable to infestation by harmful species, e.g., Clostridium difficile. To get a grip on the controlling factors of microbial diversity in the gut, we here propose a multi-scale, spatiotemporal dynamic flux-balance analysis model to study the emergence of metabolic diversity in a spatial gut-like, tubular environment. The model features genome-scale metabolic models (GEM) of microbial populations, resource sharing via extracellular metabolites, and spatial population dynamics and evolution. In this model, cross-feeding interactions emerge readily, despite the species' ability to metabolize sugars autonomously. Interestingly, the community requires cross-feeding for producing a realistic set of short-chain fatty acids from an input of glucose, If we let the composition of the microbial subpopulations change during invasion of adjacent space, a complex and stratified microbiota evolves, with subspecies specializing on cross-feeding interactions via a mechanism of compensated trait loss. The microbial diversity and stratification collapse if the flux through the gut is enhanced to mimic diarrhea. In conclusion, this in silico model is a helpful tool in systems biology to predict and explain the controlling factors of microbial diversity in the gut. It can be extended to include, e.g., complex nutrient sources, and host-microbiota interactions via the intestinal wall.

Microbial Ecology and Evolution in the Acid Mine Drainage Model System.

PubMed

Huang, Li-Nan; Kuang, Jia-Liang; Shu, Wen-Sheng

2016-07-01

Acid mine drainage (AMD) is a unique ecological niche for acid- and toxic-metals-adapted microorganisms. These low-complexity systems offer a special opportunity for the ecological and evolutionary analyses of natural microbial assemblages. The last decade has witnessed an unprecedented interest in the study of AMD communities using 16S rRNA high-throughput sequencing and community genomic and postgenomic methodologies, significantly advancing our understanding of microbial diversity, community function, and evolution in acidic environments. This review describes new data on AMD microbial ecology and evolution, especially dynamics of microbial diversity, community functions, and population genomes, and further identifies gaps in our current knowledge that future research, with integrated applications of meta-omics technologies, will fill. Copyright © 2016 Elsevier Ltd. All rights reserved.

OCCURRENCE AND EXPOSURE ASSESSMENT FOR THE ...

EPA Pesticide Factsheets

Describes the occurrence of Cryptosporidium and other pathogens in the raw and finished water of public water systems (PWS) based on modeling of source water survey data. Analysis of microbial occurrence data to support LT2ESWTR microbial risk assessment

Fundamental CRISPR-Cas9 tools and current applications in microbial systems.

PubMed

Tian, Pingfang; Wang, Jia; Shen, Xiaolin; Rey, Justin Forrest; Yuan, Qipeng; Yan, Yajun

2017-09-01

Derived from the bacterial adaptive immune system, CRISPR technology has revolutionized conventional genetic engineering methods and unprecedentedly facilitated strain engineering. In this review, we outline the fundamental CRISPR tools that have been employed for strain optimization. These tools include CRISPR editing, CRISPR interference, CRISPR activation and protein imaging. To further characterize the CRISPR technology, we present current applications of these tools in microbial systems, including model- and non-model industrial microorganisms. Specially, we point out the major challenges of the CRISPR tools when utilized for multiplex genome editing and sophisticated expression regulation. To address these challenges, we came up with strategies that place emphasis on the amelioration of DNA repair efficiency through CRISPR-Cas9-assisted recombineering. Lastly, multiple promising research directions were proposed, mainly focusing on CRISPR-based construction of microbial ecosystems toward high production of desired chemicals.

In silico approaches to study mass and energy flows in microbial consortia: a syntrophic case study

PubMed Central

2009-01-01

Background Three methods were developed for the application of stoichiometry-based network analysis approaches including elementary mode analysis to the study of mass and energy flows in microbial communities. Each has distinct advantages and disadvantages suitable for analyzing systems with different degrees of complexity and a priori knowledge. These approaches were tested and compared using data from the thermophilic, phototrophic mat communities from Octopus and Mushroom Springs in Yellowstone National Park (USA). The models were based on three distinct microbial guilds: oxygenic phototrophs, filamentous anoxygenic phototrophs, and sulfate-reducing bacteria. Two phases, day and night, were modeled to account for differences in the sources of mass and energy and the routes available for their exchange. Results The in silico models were used to explore fundamental questions in ecology including the prediction of and explanation for measured relative abundances of primary producers in the mat, theoretical tradeoffs between overall productivity and the generation of toxic by-products, and the relative robustness of various guild interactions. Conclusion The three modeling approaches represent a flexible toolbox for creating cellular metabolic networks to study microbial communities on scales ranging from cells to ecosystems. A comparison of the three methods highlights considerations for selecting the one most appropriate for a given microbial system. For instance, communities represented only by metagenomic data can be modeled using the pooled method which analyzes a community's total metabolic potential without attempting to partition enzymes to different organisms. Systems with extensive a priori information on microbial guilds can be represented using the compartmentalized technique, employing distinct control volumes to separate guild-appropriate enzymes and metabolites. If the complexity of a compartmentalized network creates an unacceptable computational burden, the nested analysis approach permits greater scalability at the cost of more user intervention through multiple rounds of pathway analysis. PMID:20003240

A quasi-chemical model for the growth and death of microorganisms in foods by non-thermal and high-pressure processing.

PubMed

Doona, Christopher J; Feeherry, Florence E; Ross, Edward W

2005-04-15

Predictive microbial models generally rely on the growth of bacteria in laboratory broth to approximate the microbial growth kinetics expected to take place in actual foods under identical environmental conditions. Sigmoidal functions such as the Gompertz or logistics equation accurately model the typical microbial growth curve from the lag to the stationary phase and provide the mathematical basis for estimating parameters such as the maximum growth rate (MGR). Stationary phase data can begin to show a decline and make it difficult to discern which data to include in the analysis of the growth curve, a factor that influences the calculated values of the growth parameters. In contradistinction, the quasi-chemical kinetics model provides additional capabilities in microbial modelling and fits growth-death kinetics (all four phases of the microbial lifecycle continuously) for a general set of microorganisms in a variety of actual food substrates. The quasi-chemical model is differential equations (ODEs) that derives from a hypothetical four-step chemical mechanism involving an antagonistic metabolite (quorum sensing) and successfully fits the kinetics of pathogens (Staphylococcus aureus, Escherichia coli and Listeria monocytogenes) in various foods (bread, turkey meat, ham and cheese) as functions of different hurdles (a(w), pH, temperature and anti-microbial lactate). The calculated value of the MGR depends on whether growth-death data or only growth data are used in the fitting procedure. The quasi-chemical kinetics model is also exploited for use with the novel food processing technology of high-pressure processing. The high-pressure inactivation kinetics of E. coli are explored in a model food system over the pressure (P) range of 207-345 MPa (30,000-50,000 psi) and the temperature (T) range of 30-50 degrees C. In relatively low combinations of P and T, the inactivation curves are non-linear and exhibit a shoulder prior to a more rapid rate of microbial destruction. In the higher P, T regime, the inactivation plots tend to be linear. In all cases, the quasi-chemical model successfully fit the linear and curvi-linear inactivation plots for E. coli in model food systems. The experimental data and the quasi-chemical mathematical model described herein are candidates for inclusion in ComBase, the developing database that combines data and models from the USDA Pathogen Modeling Program and the UK Food MicroModel.

Population-reaction model and microbial experimental ecosystems for understanding hierarchical dynamics of ecosystems.

PubMed

Hosoda, Kazufumi; Tsuda, Soichiro; Kadowaki, Kohmei; Nakamura, Yutaka; Nakano, Tadashi; Ishii, Kojiro

2016-02-01

Understanding ecosystem dynamics is crucial as contemporary human societies face ecosystem degradation. One of the challenges that needs to be recognized is the complex hierarchical dynamics. Conventional dynamic models in ecology often represent only the population level and have yet to include the dynamics of the sub-organism level, which makes an ecosystem a complex adaptive system that shows characteristic behaviors such as resilience and regime shifts. The neglect of the sub-organism level in the conventional dynamic models would be because integrating multiple hierarchical levels makes the models unnecessarily complex unless supporting experimental data are present. Now that large amounts of molecular and ecological data are increasingly accessible in microbial experimental ecosystems, it is worthwhile to tackle the questions of their complex hierarchical dynamics. Here, we propose an approach that combines microbial experimental ecosystems and a hierarchical dynamic model named population-reaction model. We present a simple microbial experimental ecosystem as an example and show how the system can be analyzed by a population-reaction model. We also show that population-reaction models can be applied to various ecological concepts, such as predator-prey interactions, climate change, evolution, and stability of diversity. Our approach will reveal a path to the general understanding of various ecosystems and organisms. Copyright © 2015 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

Accounting for microbial habitats in modeling soil organic matter dynamics

NASA Astrophysics Data System (ADS)

Chenu, Claire; Garnier, Patricia; Nunan, Naoise; Pot, Valérie; Raynaud, Xavier; Vieublé, Laure; Otten, Wilfred; Falconer, Ruth; Monga, Olivier

2017-04-01

The extreme heterogeneity of soils constituents, architecture and inhabitants at the microscopic scale is increasingly recognized. Microbial communities exist and are active in a complex 3-D physical framework of mineral and organic particles defining pores of various sizes, more or less inter-connected. This results in a frequent spatial disconnection between soil carbon, energy sources and the decomposer organisms and a variety of microhabitats that are more or less suitable for microbial growth and activity. However, current biogeochemical models account for C dynamics at the macroscale (cm, m) and consider time- and spatially averaged relationships between microbial activity and soil characteristics. Different modelling approaches have intended to account for this microscale heterogeneity, based either on considering aggregates as surrogates for microbial habitats, or pores. Innovative modelling approaches are based on an explicit representation of soil structure at the fine scale, i.e. at µm to mm scales: pore architecture and their saturation with water, localization of organic resources and of microorganisms. Three recent models are presented here, that describe the heterotrophic activity of either bacteria or fungi and are based upon different strategies to represent the complex soil pore system (Mosaic, LBios and µFun). These models allow to hierarchize factors of microbial activity in soil's heterogeneous architecture. Present limits of these approaches and challenges are presented, regarding the extensive information required on soils at the microscale and to up-scale microbial functioning from the pore to the core scale.

Coupling Spatiotemporal Community Assembly Processes to Changes in Microbial Metabolism.

PubMed

Graham, Emily B; Crump, Alex R; Resch, Charles T; Fansler, Sarah; Arntzen, Evan; Kennedy, David W; Fredrickson, Jim K; Stegen, James C

2016-01-01

Community assembly processes generate shifts in species abundances that influence ecosystem cycling of carbon and nutrients, yet our understanding of assembly remains largely separate from ecosystem-level functioning. Here, we investigate relationships between assembly and changes in microbial metabolism across space and time in hyporheic microbial communities. We pair sampling of two habitat types (i.e., attached and planktonic) through seasonal and sub-hourly hydrologic fluctuation with null modeling and temporally explicit multivariate statistics. We demonstrate that multiple selective pressures-imposed by sediment and porewater physicochemistry-integrate to generate changes in microbial community composition at distinct timescales among habitat types. These changes in composition are reflective of contrasting associations of Betaproteobacteria and Thaumarchaeota with ecological selection and with seasonal changes in microbial metabolism. We present a conceptual model based on our results in which metabolism increases when oscillating selective pressures oppose temporally stable selective pressures. Our conceptual model is pertinent to both macrobial and microbial systems experiencing multiple selective pressures and presents an avenue for assimilating community assembly processes into predictions of ecosystem-level functioning.

Weaker soil carbon-climate feedbacks resulting from microbial and abiotic interactions

NASA Astrophysics Data System (ADS)

Tang, Jinyun; Riley, William J.

2015-01-01

The large uncertainty in soil carbon-climate feedback predictions has been attributed to the incorrect parameterization of decomposition temperature sensitivity (Q10; ref. ) and microbial carbon use efficiency. Empirical experiments have found that these parameters vary spatiotemporally, but such variability is not included in current ecosystem models. Here we use a thermodynamically based decomposition model to test the hypothesis that this observed variability arises from interactions between temperature, microbial biogeochemistry, and mineral surface sorptive reactions. We show that because mineral surfaces interact with substrates, enzymes and microbes, both Q10 and microbial carbon use efficiency are hysteretic (so that neither can be represented by a single static function) and the conventional labile and recalcitrant substrate characterization with static temperature sensitivity is flawed. In a 4-K temperature perturbation experiment, our fully dynamic model predicted more variable but weaker soil carbon-climate feedbacks than did the static Q10 and static carbon use efficiency model when forced with yearly, daily and hourly variable temperatures. These results imply that current Earth system models probably overestimate the response of soil carbon stocks to global warming. Future ecosystem models should therefore consider the dynamic interactions between sorptive mineral surfaces, substrates and microbial processes.

Evaluation on the Nanoscale Zero Valent Iron Based Microbial Denitrification for Nitrate Removal from Groundwater

NASA Astrophysics Data System (ADS)

Peng, Lai; Liu, Yiwen; Gao, Shu-Hong; Chen, Xueming; Xin, Pei; Dai, Xiaohu; Ni, Bing-Jie

2015-07-01

Nanoscale zero valent iron (NZVI) based microbial denitrification has been demonstrated to be a promising technology for nitrate removal from groundwater. In this work, a mathematical model is developed to evaluate the performance of this new technology and to provide insights into the chemical and microbial interactions in the system in terms of nitrate reduction, ammonium accumulation and hydrogen turnover. The developed model integrates NZVI-based abiotic reduction of nitrate, NZVI corrosion for hydrogen production and hydrogen-based microbial denitrification and satisfactorily describes all of the nitrate and ammonium dynamics from two systems with highly different conditions. The high NZVI corrosion rate revealed by the model indicates the high reaction rate of NZVI with water due to their large specific surface area and high surface reactivity, leading to an effective microbial nitrate reduction by utilizing the produced hydrogen. The simulation results further suggest a NZVI dosing strategy (3-6 mmol/L in temperature range of 30-40 °C, 6-10 mmol/L in temperature range of 15-30 °C and 10-14 mmol/L in temperature range of 5-15 °C) during groundwater remediation to make sure a low ammonium yield and a high nitrogen removal efficiency.

Evaluation on the Nanoscale Zero Valent Iron Based Microbial Denitrification for Nitrate Removal from Groundwater

PubMed Central

Peng, Lai; Liu, Yiwen; Gao, Shu-Hong; Chen, Xueming; Xin, Pei; Dai, Xiaohu; Ni, Bing-Jie

2015-01-01

Nanoscale zero valent iron (NZVI) based microbial denitrification has been demonstrated to be a promising technology for nitrate removal from groundwater. In this work, a mathematical model is developed to evaluate the performance of this new technology and to provide insights into the chemical and microbial interactions in the system in terms of nitrate reduction, ammonium accumulation and hydrogen turnover. The developed model integrates NZVI-based abiotic reduction of nitrate, NZVI corrosion for hydrogen production and hydrogen-based microbial denitrification and satisfactorily describes all of the nitrate and ammonium dynamics from two systems with highly different conditions. The high NZVI corrosion rate revealed by the model indicates the high reaction rate of NZVI with water due to their large specific surface area and high surface reactivity, leading to an effective microbial nitrate reduction by utilizing the produced hydrogen. The simulation results further suggest a NZVI dosing strategy (3–6 mmol/L in temperature range of 30–40 °C, 6–10 mmol/L in temperature range of 15–30 °C and 10–14 mmol/L in temperature range of 5–15 °C) during groundwater remediation to make sure a low ammonium yield and a high nitrogen removal efficiency. PMID:26199053

Contrasting response to nutrient manipulation in Arctic mesocosms are reproduced by a minimum microbial food web model.

PubMed

Larsen, Aud; Egge, Jorun K; Nejstgaard, Jens C; Di Capua, Iole; Thyrhaug, Runar; Bratbak, Gunnar; Thingstad, T Frede

2015-03-01

A minimum mathematical model of the marine pelagic microbial food web has previously shown to be able to reproduce central aspects of observed system response to different bottom-up manipulations in a mesocosm experiment Microbial Ecosystem Dynamics (MEDEA) in Danish waters. In this study, we apply this model to two mesocosm experiments (Polar Aquatic Microbial Ecology (PAME)-I and PAME-II) conducted at the Arctic location Kongsfjorden, Svalbard. The different responses of the microbial community to similar nutrient manipulation in the three mesocosm experiments may be described as diatom-dominated (MEDEA), bacteria-dominated (PAME-I), and flagellated-dominated (PAME-II). When allowing ciliates to be able to feed on small diatoms, the model describing the diatom-dominated MEDEA experiment give a bacteria-dominated response as observed in PAME I in which the diatom community comprised almost exclusively small-sized cells. Introducing a high initial mesozooplankton stock as observed in PAME-II, the model gives a flagellate-dominated response in accordance with the observed response also of this experiment. The ability of the model originally developed for temperate waters to reproduce population dynamics in a 10°C colder Arctic fjord, does not support the existence of important shifts in population balances over this temperature range. Rather, it suggests a quite resilient microbial food web when adapted to in situ temperature. The sensitivity of the model response to its mesozooplankton component suggests, however, that the seasonal vertical migration of Arctic copepods may be a strong forcing factor on Arctic microbial food webs.

Contrasting response to nutrient manipulation in Arctic mesocosms are reproduced by a minimum microbial food web model

PubMed Central

Larsen, Aud; Egge, Jorun K; Nejstgaard, Jens C; Di Capua, Iole; Thyrhaug, Runar; Bratbak, Gunnar; Thingstad, T Frede

2015-01-01

A minimum mathematical model of the marine pelagic microbial food web has previously shown to be able to reproduce central aspects of observed system response to different bottom-up manipulations in a mesocosm experiment Microbial Ecosystem Dynamics (MEDEA) in Danish waters. In this study, we apply this model to two mesocosm experiments (Polar Aquatic Microbial Ecology (PAME)-I and PAME-II) conducted at the Arctic location Kongsfjorden, Svalbard. The different responses of the microbial community to similar nutrient manipulation in the three mesocosm experiments may be described as diatom-dominated (MEDEA), bacteria-dominated (PAME-I), and flagellated-dominated (PAME-II). When allowing ciliates to be able to feed on small diatoms, the model describing the diatom-dominated MEDEA experiment give a bacteria-dominated response as observed in PAME I in which the diatom community comprised almost exclusively small-sized cells. Introducing a high initial mesozooplankton stock as observed in PAME-II, the model gives a flagellate-dominated response in accordance with the observed response also of this experiment. The ability of the model originally developed for temperate waters to reproduce population dynamics in a 10°C colder Arctic fjord, does not support the existence of important shifts in population balances over this temperature range. Rather, it suggests a quite resilient microbial food web when adapted to in situ temperature. The sensitivity of the model response to its mesozooplankton component suggests, however, that the seasonal vertical migration of Arctic copepods may be a strong forcing factor on Arctic microbial food webs. PMID:26074626

Living microorganisms change the information (Shannon) content of a geophysical system.

PubMed

Tang, Fiona H M; Maggi, Federico

2017-06-12

The detection of microbial colonization in geophysical systems is becoming of interest in various disciplines of Earth and planetary sciences, including microbial ecology, biogeochemistry, geomicrobiology, and astrobiology. Microorganisms are often observed to colonize mineral surfaces, modify the reactivity of minerals either through the attachment of their own biomass or the glueing of mineral particles with their mucilaginous metabolites, and alter both the physical and chemical components of a geophysical system. Here, we hypothesise that microorganisms engineer their habitat, causing a substantial change to the information content embedded in geophysical measures (e.g., particle size and space-filling capacity). After proving this hypothesis, we introduce and test a systematic method that exploits this change in information content to detect microbial colonization in geophysical systems. Effectiveness and robustness of this method are tested using a mineral sediment suspension as a model geophysical system; tests are carried out against 105 experiments conducted with different suspension types (i.e., pure mineral and microbially-colonized) subject to different abiotic conditions, including various nutrient and mineral concentrations, and different background entropy production rates. Results reveal that this method can systematically detect microbial colonization with less than 10% error in geophysical systems with low-entropy background production rate.

Ecological and soil hydraulic implications of microbial responses to stress - A modeling analysis

NASA Astrophysics Data System (ADS)

Brangarí, Albert C.; Fernàndez-Garcia, Daniel; Sanchez-Vila, Xavier; Manzoni, Stefano

2018-06-01

A better understanding of microbial dynamics in porous media may lead to improvements in the design and management of a number of technological applications, ranging from the degradation of contaminants to the optimization of agricultural systems. To this aim, there is a recognized need for predicting the proliferation of soil microbial biomass (often organized in biofilms) under different environments and stresses. We present a general multi-compartment model to account for physiological responses that have been extensively reported in the literature. The model is used as an explorative tool to elucidate the ecological and soil hydraulic consequences of microbial responses, including the production of extracellular polymeric substances (EPS), the induction of cells into dormancy, and the allocation and reuse of resources between biofilm compartments. The mechanistic model is equipped with indicators allowing the microorganisms to monitor environmental and biological factors and react according to the current stress pressures. The feedbacks of biofilm accumulation on the soil water retention are also described. Model runs simulating different degrees of substrate and water shortage show that adaptive responses to the intensity and type of stress provide a clear benefit to microbial colonies. Results also demonstrate that the model may effectively predict qualitative patterns in microbial dynamics supported by empirical evidence, thereby improving our understanding of the effects of pore-scale physiological mechanisms on the soil macroscale phenomena.

Determination of volumetric gas-liquid mass transfer coefficient of carbon monoxide in a batch cultivation system using kinetic simulations.

PubMed

Jang, Nulee; Yasin, Muhammad; Park, Shinyoung; Lovitt, Robert W; Chang, In Seop

2017-09-01

A mathematical model of microbial kinetics was introduced to predict the overall volumetric gas-liquid mass transfer coefficient (k L a) of carbon monoxide (CO) in a batch cultivation system. The cell concentration (X), acetate concentration (C ace ), headspace gas (N co and [Formula: see text] ), dissolved CO concentration in the fermentation medium (C co ), and mass transfer rate (R) were simulated using a variety of k L a values. The simulated results showed excellent agreement with the experimental data for a k L a of 13/hr. The C co values decreased with increase in cultivation times, whereas the maximum mass transfer rate was achieved at the mid-log phase due to vigorous microbial CO consumption rate higher than R. The model suggested in this study may be applied to a variety of microbial systems involving gaseous substrates. Copyright © 2017 Elsevier Ltd. All rights reserved.

Trophic interactions induce spatial self-organization of microbial consortia on rough surfaces.

PubMed

Wang, Gang; Or, Dani

2014-10-24

The spatial context of microbial interactions common in natural systems is largely absent in traditional pure culture-based microbiology. The understanding of how interdependent microbial communities assemble and coexist in limited spatial domains remains sketchy. A mechanistic model of cell-level interactions among multispecies microbial populations grown on hydrated rough surfaces facilitated systematic evaluation of how trophic dependencies shape spatial self-organization of microbial consortia in complex diffusion fields. The emerging patterns were persistent irrespective of initial conditions and resilient to spatial and temporal perturbations. Surprisingly, the hydration conditions conducive for self-assembly are extremely narrow and last only while microbial cells remain motile within thin aqueous films. The resulting self-organized microbial consortia patterns could represent optimal ecological templates for the architecture that underlie sessile microbial colonies on natural surfaces. Understanding microbial spatial self-organization offers new insights into mechanisms that sustain small-scale soil microbial diversity; and may guide the engineering of functional artificial microbial consortia.

Synthetic Ecology of Microbes: Mathematical Models and Applications

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zomorrodi, Ali R.; Segre, Daniel

As the indispensable role of natural microbial communities in many aspects of life on Earth is uncovered, the bottom-up engineering of synthetic microbial consortia with novel functions is becoming an attractive alternative to engineering single-species systems. Here, we summarize recent work on synthetic microbial communities with a particular emphasis on open challenges and opportunities in environmental sustainability and human health. We next provide a critical overview of mathematical approaches, ranging from phenomenological to mechanistic, to decipher the principles that govern the function, dynamics and evolution of microbial ecosystems. Lastly, we present our outlook on key aspects of microbial ecosystems andmore » synthetic ecology that require further developments, including the need for more efficient computational algorithms, a better integration of empirical methods and model-driven analysis, the importance of improving gene function annotation, and the value of a standardized library of well-characterized organisms to be used as building blocks of synthetic communities.« less

Synthetic Ecology of Microbes: Mathematical Models and Applications

DOE PAGES

Zomorrodi, Ali R.; Segre, Daniel

2015-11-11

As the indispensable role of natural microbial communities in many aspects of life on Earth is uncovered, the bottom-up engineering of synthetic microbial consortia with novel functions is becoming an attractive alternative to engineering single-species systems. Here, we summarize recent work on synthetic microbial communities with a particular emphasis on open challenges and opportunities in environmental sustainability and human health. We next provide a critical overview of mathematical approaches, ranging from phenomenological to mechanistic, to decipher the principles that govern the function, dynamics and evolution of microbial ecosystems. Lastly, we present our outlook on key aspects of microbial ecosystems andmore » synthetic ecology that require further developments, including the need for more efficient computational algorithms, a better integration of empirical methods and model-driven analysis, the importance of improving gene function annotation, and the value of a standardized library of well-characterized organisms to be used as building blocks of synthetic communities.« less

Microbial ecology of the closed artificial ecosystem MELiSSA (Micro-Ecological Life Support System Alternative): reinventing and compartmentalizing the Earth's food and oxygen regeneration system for long-haul space exploration missions.

PubMed

Hendrickx, Larissa; De Wever, Heleen; Hermans, Veronik; Mastroleo, Felice; Morin, Nicolas; Wilmotte, Annick; Janssen, Paul; Mergeay, Max

2006-01-01

MELiSSA is a bioregenerative life support system designed by the European Space Agency (ESA) for the complete recycling of gas, liquid and solid wastes during long distance space exploration. The system uses the combined activity of different living organisms: microbial cultures in bioreactors, a plant compartment and a human crew. In this minireview, the development of a short-cut ecological system for the biotransformation of organic waste is discussed from a microorganism's perspective. The artificial ecological model--still in full development--that is inspired by Earth's own geomicrobiological ecosystem serves as an ideal study object on microbial ecology and will become an indispensable travel companion in manned space exploration.

Linking the development and functioning of a carnivorous pitcher plant's microbial digestive community.

PubMed

Armitage, David W

2017-11-01

Ecosystem development theory predicts that successional turnover in community composition can influence ecosystem functioning. However, tests of this theory in natural systems are made difficult by a lack of replicable and tractable model systems. Using the microbial digestive associates of a carnivorous pitcher plant, I tested hypotheses linking host age-driven microbial community development to host functioning. Monitoring the yearlong development of independent microbial digestive communities in two pitcher plant populations revealed a number of trends in community succession matching theoretical predictions. These included mid-successional peaks in bacterial diversity and metabolic substrate use, predictable and parallel successional trajectories among microbial communities, and convergence giving way to divergence in community composition and carbon substrate use. Bacterial composition, biomass, and diversity positively influenced the rate of prey decomposition, which was in turn positively associated with a host leaf's nitrogen uptake efficiency. Overall digestive performance was greatest during late summer. These results highlight links between community succession and ecosystem functioning and extend succession theory to host-associated microbial communities.

Development of constraint-based system-level models of microbial metabolism.

PubMed

Navid, Ali

2012-01-01

Genome-scale models of metabolism are valuable tools for using genomic information to predict microbial phenotypes. System-level mathematical models of metabolic networks have been developed for a number of microbes and have been used to gain new insights into the biochemical conversions that occur within organisms and permit their survival and proliferation. Utilizing these models, computational biologists can (1) examine network structures, (2) predict metabolic capabilities and resolve unexplained experimental observations, (3) generate and test new hypotheses, (4) assess the nutritional requirements of the organism and approximate its environmental niche, (5) identify missing enzymatic functions in the annotated genome, and (6) engineer desired metabolic capabilities in model organisms. This chapter details the protocol for developing genome-scale models of metabolism in microbes as well as tips for accelerating the model building process.

An integrative view of microbiome-host interactions in inflammatory bowel diseases

PubMed Central

Wlodarska, Marta; Kostic, Aleksandar D.; Xavier, Ramnik J.

2015-01-01

Summary The intestinal microbiota, which is composed of bacteria, viruses, and micro-eukaryotes, acts as an accessory organ system with distinct functions along the intestinal tract that are critical for health. This review focuses on how the microbiota drives intestinal disease through alterations in microbial community architecture, disruption of the mucosal barrier, modulation of innate and adaptive immunity, and dysfunction of the enteric nervous system. Inflammatory bowel disease is used as a model system to understand these microbial-driven pathologies, but the knowledge gained in this space is extended to less well studied intestinal diseases that may also have an important microbial component, including environmental enteropathy and chronic colitis-associated colorectal cancer. PMID:25974300

Toward quantitative understanding on microbial community structure and functioning: a modeling-centered approach using degradation of marine oil spills as example

PubMed Central

Röling, Wilfred F. M.; van Bodegom, Peter M.

2014-01-01

Molecular ecology approaches are rapidly advancing our insights into the microorganisms involved in the degradation of marine oil spills and their metabolic potentials. Yet, many questions remain open: how do oil-degrading microbial communities assemble in terms of functional diversity, species abundances and organization and what are the drivers? How do the functional properties of microorganisms scale to processes at the ecosystem level? How does mass flow among species, and which factors and species control and regulate fluxes, stability and other ecosystem functions? Can generic rules on oil-degradation be derived, and what drivers underlie these rules? How can we engineer oil-degrading microbial communities such that toxic polycyclic aromatic hydrocarbons are degraded faster? These types of questions apply to the field of microbial ecology in general. We outline how recent advances in single-species systems biology might be extended to help answer these questions. We argue that bottom-up mechanistic modeling allows deciphering the respective roles and interactions among microorganisms. In particular constraint-based, metagenome-derived community-scale flux balance analysis appears suited for this goal as it allows calculating degradation-related fluxes based on physiological constraints and growth strategies, without needing detailed kinetic information. We subsequently discuss what is required to make these approaches successful, and identify a need to better understand microbial physiology in order to advance microbial ecology. We advocate the development of databases containing microbial physiological data. Answering the posed questions is far from trivial. Oil-degrading communities are, however, an attractive setting to start testing systems biology-derived models and hypotheses as they are relatively simple in diversity and key activities, with several key players being isolated and a high availability of experimental data and approaches. PMID:24723922

Toward quantitative understanding on microbial community structure and functioning: a modeling-centered approach using degradation of marine oil spills as example.

PubMed

Röling, Wilfred F M; van Bodegom, Peter M

2014-01-01

Molecular ecology approaches are rapidly advancing our insights into the microorganisms involved in the degradation of marine oil spills and their metabolic potentials. Yet, many questions remain open: how do oil-degrading microbial communities assemble in terms of functional diversity, species abundances and organization and what are the drivers? How do the functional properties of microorganisms scale to processes at the ecosystem level? How does mass flow among species, and which factors and species control and regulate fluxes, stability and other ecosystem functions? Can generic rules on oil-degradation be derived, and what drivers underlie these rules? How can we engineer oil-degrading microbial communities such that toxic polycyclic aromatic hydrocarbons are degraded faster? These types of questions apply to the field of microbial ecology in general. We outline how recent advances in single-species systems biology might be extended to help answer these questions. We argue that bottom-up mechanistic modeling allows deciphering the respective roles and interactions among microorganisms. In particular constraint-based, metagenome-derived community-scale flux balance analysis appears suited for this goal as it allows calculating degradation-related fluxes based on physiological constraints and growth strategies, without needing detailed kinetic information. We subsequently discuss what is required to make these approaches successful, and identify a need to better understand microbial physiology in order to advance microbial ecology. We advocate the development of databases containing microbial physiological data. Answering the posed questions is far from trivial. Oil-degrading communities are, however, an attractive setting to start testing systems biology-derived models and hypotheses as they are relatively simple in diversity and key activities, with several key players being isolated and a high availability of experimental data and approaches.

A microbial functional group-based module for simulating methane production and consumption: Application to an incubated permafrost soil

DOE PAGES

Xu, Xiaofeng; Elias, Dwayne A.; Graham, David E.; ...

2015-07-23

In this study, accurately estimating methane (CH 4) flux is critically important for investigating and predicting the biogeochemistry-climate feedback. Better simulating CH 4 flux requires explicit representations of microbial processes on CH 4 dynamics because all processes for CH 4 production and consumption are actually carried out by microbes. A microbial functional group based module was developed and tested against an incubation experiment. The module considers four key mechanisms for CH 4 production and consumption: methanogenesis from acetate or single-carbon compounds and CH 4 oxidation using molecular oxygen or other inorganic electron acceptors. These four processes were carried out bymore » four microbial functional groups: acetoclastic methanogens, hydrogenotrophic methanogens, aerobic methanotrophs, and anaerobic methanotrophs. This module was then linked with the decomposition subroutine of the Community Land Model, and was further used to simulate dynamics of carbon dioxide (CO 2) and CH 4 concentrations from an incubation experiment with permafrost soils. The results show that the model could capture the dynamics of CO 2 and CH 4 concentrations in microcosms with top soils, mineral layer soils and permafrost soils under natural and saturated moisture conditions and a temperature gradient of -2°C, 3°C, and 5°C. Sensitivity analysis confirmed the importance of acetic acid's direct contribution as substrate and indirect effects through pH feedback on CO 2 and CH 4 production and consumption. This study suggests that representing the microbial mechanisms is critical for modeling CH 4 production and consumption; it is urgent to incorporate microbial mechanisms into Earth system models for better predicting the behavior of the climate system.« less

Functional Enzyme-Based Approach for Linking Microbial Community Functions with Biogeochemical Process Kinetics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Li, Minjing; Qian, Wei-jun; Gao, Yuqian

The kinetics of biogeochemical processes in natural and engineered environmental systems are typically described using Monod-type or modified Monod-type models. These models rely on biomass as surrogates for functional enzymes in microbial community that catalyze biogeochemical reactions. A major challenge to apply such models is the difficulty to quantitatively measure functional biomass for constraining and validating the models. On the other hand, omics-based approaches have been increasingly used to characterize microbial community structure, functions, and metabolites. Here we proposed an enzyme-based model that can incorporate omics-data to link microbial community functions with biogeochemical process kinetics. The model treats enzymes asmore » time-variable catalysts for biogeochemical reactions and applies biogeochemical reaction network to incorporate intermediate metabolites. The sequences of genes and proteins from metagenomes, as well as those from the UniProt database, were used for targeted enzyme quantification and to provide insights into the dynamic linkage among functional genes, enzymes, and metabolites that are necessary to be incorporated in the model. The application of the model was demonstrated using denitrification as an example by comparing model-simulated with measured functional enzymes, genes, denitrification substrates and intermediates« less

Constraint-based stoichiometric modelling from single organisms to microbial communities

PubMed Central

Olivier, Brett G.; Bruggeman, Frank J.; Teusink, Bas

2016-01-01

Microbial communities are ubiquitously found in Nature and have direct implications for the environment, human health and biotechnology. The species composition and overall function of microbial communities are largely shaped by metabolic interactions such as competition for resources and cross-feeding. Although considerable scientific progress has been made towards mapping and modelling species-level metabolism, elucidating the metabolic exchanges between microorganisms and steering the community dynamics remain an enormous scientific challenge. In view of the complexity, computational models of microbial communities are essential to obtain systems-level understanding of ecosystem functioning. This review discusses the applications and limitations of constraint-based stoichiometric modelling tools, and in particular flux balance analysis (FBA). We explain this approach from first principles and identify the challenges one faces when extending it to communities, and discuss the approaches used in the field in view of these challenges. We distinguish between steady-state and dynamic FBA approaches extended to communities. We conclude that much progress has been made, but many of the challenges are still open. PMID:28334697

Mathematical Modeling of Microbial Community Dynamics: A Methodological Review

DOE Office of Scientific and Technical Information (OSTI.GOV)

Song, Hyun-Seob; Cannon, William R.; Beliaev, Alex S.

Microorganisms in nature form diverse communities that dynamically change in structure and function in response to environmental variations. As a complex adaptive system, microbial communities show higher-order properties that are not present in individual microbes, but arise from their interactions. Predictive mathematical models not only help to understand the underlying principles of the dynamics and emergent properties of natural and synthetic microbial communities, but also provide key knowledge required for engineering them. In this article, we provide an overview of mathematical tools that include not only current mainstream approaches, but also less traditional approaches that, in our opinion, can bemore » potentially useful. We discuss a broad range of methods ranging from low-resolution supra-organismal to high-resolution individual-based modeling. Particularly, we highlight the integrative approaches that synergistically combine disparate methods. In conclusion, we provide our outlook for the key aspects that should be further developed to move microbial community modeling towards greater predictive power.« less

Spatial pattern formation of microbes at the soil microscale affect soil C and N turnover in an individual-based microbial community model

NASA Astrophysics Data System (ADS)

Kaiser, Christina; Evans, Sarah; Dieckmann, Ulf; Widder, Stefanie

2016-04-01

At the μm-scale, soil is a highly structured and complex environment, both in physical as well as in biological terms, characterized by non-linear interactions between microbes, substrates and minerals. As known from mathematics and theoretical ecology, spatial structure significantly affects the system's behaviour by enabling synergistic dynamics, facilitating diversity, and leading to emergent phenomena such as self-organisation and self-regulation. Such phenomena, however, are rarely considered when investigating mechanisms of microbial soil organic matter turnover. Soil organic matter is the largest terrestrial reservoir for organic carbon (C) and nitrogen (N) and plays a pivotal role in global biogeochemical cycles. Still, the underlying mechanisms of microbial soil organic matter buildup and turnover remain elusive. We explored mechanisms of microbial soil organic matter turnover using an individual-based, stoichiometrically and spatially explicit computer model, which simulates the microbial de-composer system at the soil microscale (i.e. on a grid of 100 x 100 soil microsites). Soil organic matter dynamics in our model emerge as the result of interactions among individual microbes with certain functional traits (f.e. enzyme production rates, growth rates, cell stoichiometry) at the microscale. By degrading complex substrates, and releasing labile substances microbes in our model continusly shape their environment, which in turn feeds back to spatiotemporal dynamics of the microbial community. In order to test the effect of microbial functional traits and organic matter input rate on soil organic matter turnover and C and N storage, we ran the model into steady state using continuous inputs of fresh organic material. Surprisingly, certain parameter settings that induce resource limitation of microbes lead to regular spatial pattern formation (f.e. moving spiral waves) of microbes and substrate at the μm-scale at steady-state. The occurrence of these pattern can be explained by the Turing mechanism. These pattern formation had strong consequences for process rates, as well as for C and N storage in the soil at the steady state: Scenarios that exhibited pattern formation were generally associated with higher C storage at steady state compared to those without pattern formation (i.e. at non-limiting conditions for microbes). Moreover, pattern formation lead to a spatial decoupling of C and N turnover processes, and to a spatial decoupling of microbial N mineralization and N immobilization. Taken together, our theoretical analysis shows that self-organisation may be a feature of the soil decomposer system, with consequences for process rates of microbial C and N turnover. Pattern formation through spatial self-organization, which has been observed on larger spatial scales in other resource-limited communities (e.g., vegetation patterns in arid or wetland eco-systems), may also occur at the soil microscale, leaving its mark on the soil's storage capacity for C and N.

Data-model integration to interpret connectivity between biogeochemical cycling, and vegetation phenology and productivity in mountainous ecosystems under changing hydrologic regimes

NASA Astrophysics Data System (ADS)

Brodie, E.; Arora, B.; Beller, H. R.; Bill, M.; Bouskill, N.; Chakraborty, R.; Conrad, M. E.; Dafflon, B.; Enquist, B. J.; Falco, N.; Henderson, A.; Karaoz, U.; Polussa, A.; Sorensen, P.; Steltzer, H.; Wainwright, H. M.; Wang, S.; Williams, K. H.; Wilmer, C.; Wu, Y.

2017-12-01

In mountainous systems, snow-melt is associated with a large pulse of nutrients that originates from under-snow microbial mineralization of organic matter and microbial biomass turnover. Vegetation phenology in these systems is regulated by environmental cues such as air temperature ranges and photoperiod, such that, under typical conditions, vegetation greening and nutrient uptake occur in sync with microbial biomass turnover and nutrient release, closing nutrient cycles and enhancing nutrient retention. However, early snow-melt has been observed with increasing frequency in the mountainous west and is hypothesized to disrupt coupled plant-microbial behavior, potentially resulting in a temporal discontinuity between microbial nutrient release and vegetation greening. As part of the Watershed Function Scientific Focus Area (SFA) at Berkeley Lab we are quantifying below-ground biogeochemistry and above-ground phenology and vegetation chemistry and their relationships to hydrologic events at a lower montane hillslope in the East River catchment, Crested Butte, CO. This presentation will focus on data-model integration to interpret connectivity between biogeochemical cycling of nitrogen and vegetation nitrogen demand. Initial model results suggest that early snow-melt will result in an earlier accumulation and leaching loss of nitrate from the upper soil depths but that vegetation productivity may not decline as traits such as greater rooting depth and resource allocation to stems are favored.

Systems Reliability Framework for Surface Water Sustainability and Risk Management

NASA Astrophysics Data System (ADS)

Myers, J. R.; Yeghiazarian, L.

2016-12-01

With microbial contamination posing a serious threat to the availability of clean water across the world, it is necessary to develop a framework that evaluates the safety and sustainability of water systems in respect to non-point source fecal microbial contamination. The concept of water safety is closely related to the concept of failure in reliability theory. In water quality problems, the event of failure can be defined as the concentration of microbial contamination exceeding a certain standard for usability of water. It is pertinent in watershed management to know the likelihood of such an event of failure occurring at a particular point in space and time. Microbial fate and transport are driven by environmental processes taking place in complex, multi-component, interdependent environmental systems that are dynamic and spatially heterogeneous, which means these processes and therefore their influences upon microbial transport must be considered stochastic and variable through space and time. A physics-based stochastic model of microbial dynamics is presented that propagates uncertainty using a unique sampling method based on artificial neural networks to produce a correlation between watershed characteristics and spatial-temporal probabilistic patterns of microbial contamination. These results are used to address the question of water safety through several sustainability metrics: reliability, vulnerability, resilience and a composite sustainability index. System reliability is described uniquely though the temporal evolution of risk along watershed points or pathways. Probabilistic resilience describes how long the system is above a certain probability of failure, and the vulnerability metric describes how the temporal evolution of risk changes throughout a hierarchy of failure levels. Additionally our approach allows for the identification of contributions in microbial contamination and uncertainty from specific pathways and sources. We expect that this framework will significantly improve the efficiency and precision of sustainable watershed management strategies through providing a better understanding of how watershed characteristics and environmental parameters affect surface water quality and sustainability. With microbial contamination posing a serious threat to the availability of clean water across the world, it is necessary to develop a framework that evaluates the safety and sustainability of water systems in respect to non-point source fecal microbial contamination. The concept of water safety is closely related to the concept of failure in reliability theory. In water quality problems, the event of failure can be defined as the concentration of microbial contamination exceeding a certain standard for usability of water. It is pertinent in watershed management to know the likelihood of such an event of failure occurring at a particular point in space and time. Microbial fate and transport are driven by environmental processes taking place in complex, multi-component, interdependent environmental systems that are dynamic and spatially heterogeneous, which means these processes and therefore their influences upon microbial transport must be considered stochastic and variable through space and time. A physics-based stochastic model of microbial dynamics is presented that propagates uncertainty using a unique sampling method based on artificial neural networks to produce a correlation between watershed characteristics and spatial-temporal probabilistic patterns of microbial contamination. These results are used to address the question of water safety through several sustainability metrics: reliability, vulnerability, resilience and a composite sustainability index. System reliability is described uniquely though the temporal evolution of risk along watershed points or pathways. Probabilistic resilience describes how long the system is above a certain probability of failure, and the vulnerability metric describes how the temporal evolution of risk changes throughout a hierarchy of failure levels. Additionally our approach allows for the identification of contributions in microbial contamination and uncertainty from specific pathways and sources. We expect that this framework will significantly improve the efficiency and precision of sustainable watershed management strategies through providing a better understanding of how watershed characteristics and environmental parameters affect surface water quality and sustainability.

Interactions Between Mineral Surfaces, Substrates, Enzymes, and Microbes Result in Hysteretic Temperature Sensitivities and Microbial Carbon Use Efficiencies and Weaker Predicted Carbon-Climate Feedbacks

NASA Astrophysics Data System (ADS)

Riley, W. J.; Tang, J.

2014-12-01

We hypothesize that the large observed variability in decomposition temperature sensitivity and carbon use efficiency arises from interactions between temperature, microbial biogeochemistry, and mineral surface sorptive reactions. To test this hypothesis, we developed a numerical model that integrates the Dynamic Energy Budget concept for microbial physiology, microbial trait-based community structure and competition, process-specific thermodynamically ­­based temperature sensitivity, a non-linear mineral sorption isotherm, and enzyme dynamics. We show, because mineral surfaces interact with substrates, enzymes, and microbes, both temperature sensitivity and microbial carbon use efficiency are hysteretic and highly variable. Further, by mimicking the traditional approach to interpreting soil incubation observations, we demonstrate that the conventional labile and recalcitrant substrate characterization for temperature sensitivity is flawed. In a 4 K temperature perturbation experiment, our fully dynamic model predicted more variable but weaker carbon-climate feedbacks than did the static temperature sensitivity and carbon use efficiency model when forced with yearly, daily, and hourly variable temperatures. These results imply that current earth system models likely over-estimate the response of soil carbon stocks to global warming.

Final Report Systems Level Analysis of the Function and Adaptive Responses of Methanogenic Consortia

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lovley, Derek R.

The purpose of this research was to determine whether the syntrophic microbial associations that are central to the functioning of methane-producing terrestrial wetlands can be predictively modeled with coupled multi-species genome-scale metabolic models. Such models are important because methane is an important greenhouse gas and there is a need to predictively model how the methane-producing microbial communities will respond to environmental perturbations, such as global climate change. The research discovered that the most prodigious methane-producing microorganisms on earth participate in a previously unrecognized form of energy exchange. The methane-producers Methanosaeta and Methanosarcina forge biological electrical connections with other microbes inmore » order to obtain electrons to reduce carbon dioxide to methane. This direct interspecies electron transfer (DIET) was demonstrated in complex microbial communities as well as in defined co-cultures. For example, metatranscriptomic analysis of gene expression in both natural communities and defined co-cultures demonstrated that Methanosaeta species highly expressed genes for the enzymes for the reduction of carbon dioxide to methane. Furthermore, Methanosaeta’s electron-donating partners highly expressed genes for the biological electrical connections known as microbial nanowires. A series of studies involving transcriptomics, genome resequencing, and analysis of the metabolism of a series of strains with targeted gene deletions, further elucidated the mechanisms and energetics of DIET in methane-producing co-cultures, as well as in a co-culture of Geobacter metallireducens and Geobacter sulfurreducens, which provided a system for studying DIET with two genetically tractable partners. Genome-scale modeling of DIET in the G. metallireducens/G. sulfurreducens co-culture suggested that DIET provides more energy to the electron-donating partner that electron exchange via interspecies hydrogen transfer, but that the performance of DIET may be strongly influenced by environmental factors. These studies have significantly modified conceptual models for carbon and electron flow in methane-producing environments and have developed a computational framework for predictive modeling the influence of environmental perturbations on methane-producing microbial communities. The results have important implications for modeling the response of methane-producing microbial communities to climate change as well as for the bioenergy strategy of converting wastes and biomass to methane.« less

Stability characterization and modeling of robust distributed benthic microbial fuel cell (DBMFC) system.

PubMed

Karra, Udayarka; Huang, Guoxian; Umaz, Ridvan; Tenaglier, Christopher; Wang, Lei; Li, Baikun

2013-09-01

A novel and robust distributed benthic microbial fuel cell (DBMFC) was developed to address the energy supply issues for oceanographic sensor network applications, especially under scouring and bioturbation by aquatic life. Multi-anode/cathode configuration was employed in the DBMFC system for enhanced robustness and stability in the harsh ocean environment. The results showed that the DBMFC system achieved peak power and current densities of 190mW/m(2) and 125mA/m(2) respectively. Stability characterization tests indicated the DBMFC with multiple anodes achieved higher power generation over the systems with single anode. A computational model that integrated physical, electrochemical and biological factors of MFCs was developed to validate the overall performance of the DBMFC system. The model simulation well corresponded with the experimental results, and confirmed the hypothesis that using a multi anode/cathode MFC configuration results in reliable and robust power generation. Published by Elsevier Ltd.

Use of an uncertainty analysis for genome-scale models as a prediction tool for microbial growth processes in subsurface environments.

PubMed

Klier, Christine

2012-03-06

The integration of genome-scale, constraint-based models of microbial cell function into simulations of contaminant transport and fate in complex groundwater systems is a promising approach to help characterize the metabolic activities of microorganisms in natural environments. In constraint-based modeling, the specific uptake flux rates of external metabolites are usually determined by Michaelis-Menten kinetic theory. However, extensive data sets based on experimentally measured values are not always available. In this study, a genome-scale model of Pseudomonas putida was used to study the key issue of uncertainty arising from the parametrization of the influx of two growth-limiting substrates: oxygen and toluene. The results showed that simulated growth rates are highly sensitive to substrate affinity constants and that uncertainties in specific substrate uptake rates have a significant influence on the variability of simulated microbial growth. Michaelis-Menten kinetic theory does not, therefore, seem to be appropriate for descriptions of substrate uptake processes in the genome-scale model of P. putida. Microbial growth rates of P. putida in subsurface environments can only be accurately predicted if the processes of complex substrate transport and microbial uptake regulation are sufficiently understood in natural environments and if data-driven uptake flux constraints can be applied.

Proteogenemic Approaches for the Molecular Characterization of Natural Microbial Communities

DOE Office of Scientific and Technical Information (OSTI.GOV)

Banfield, Jillian F.

2014-04-25

Microbial biofilms involved in acid mine drainage formation have served as a model systems for the study of microbial communities. Over the grant period we developed community metagenomic methods for recovery of genomes of uncultivated bacteria, archaea, viruses/phage, and plasmids from natural systems. We leveraged highly curated metagenomic datasets to develop methods to monitor microbial function in situ. Beyond new insight into extremophilic microbial ecosystems, we have shown that our strain-resolved proteogenomic methods can be applied to other systems. Our studies have uncovered new patters of inter-species recombination that likely lead to fine-scale environmental adaptation, defined the importance of inter-speciesmore » vs. intra-species recombination in archaea, and evaluated the processes shaping fine-scale sequence variation. The project was the subject of study for six Ph.D. students, two of whom are now Associate Professors, the others are post docs; for M.S. or undergraduate researchers, and thirteen post docs, ten of which are now Assistant or Associate professors. The research generated 53 publications, five of which appeard in Science or Nature.« less

Customizing laboratory mice by modifying gut microbiota and host immunity in an early "window of opportunity".

PubMed

Hansen, Camilla H F; Metzdorff, Stine B; Hansen, Axel K

2013-01-01

We recently investigated how post-natal microbial gut colonization is important for the development of the immune system, especially in the systemic compartments. This addendum presents additional data which in accordance with our previous findings show that early life microbial colonization is critical for a fine-tuned immune homeostasis to develop also in the intestinal environment. A generalized reduction in the expression of immune signaling related genes in the small intestine may explain previously shown increased systemic adaptive immune reactivity, if the regulatory cross-talk between intra- and extra-intestinal immune cells is immature following a neonatal germ-free period. These findings are furthermore discussed in the context of recently published results on how lack of microbial exposure in the neonatal life modifies disease expression in rodents used as models mimicking human inflammatory diseases. In particular, with a focus on how these interesting findings could be used to optimize the use of rodent models.

Effect of food microstructure on growth dynamics of Listeria monocytogenes in fish-based model systems.

PubMed

Verheyen, Davy; Bolívar, Araceli; Pérez-Rodríguez, Fernando; Baka, Maria; Skåra, Torstein; Van Impe, Jan F

2018-06-01

Traditionally, predictive growth models for food pathogens are developed based on experiments in broth media, resulting in models which do not incorporate the influence of food microstructure. The use of model systems with various microstructures is a promising concept to get more insight into the influence of food microstructure on microbial dynamics. By means of minimal variation of compositional and physicochemical factors, these model systems can be used to study the isolated effect of certain microstructural aspects on microbial growth, survival and inactivation. In this study, the isolated effect on microbial growth dynamics of Listeria monocytogenes of two food microstructural aspects and one aspect influenced by food microstructure were investigated, i.e., the nature of the food matrix, the presence of fat droplets, and microorganism growth morphology, respectively. To this extent, fish-based model systems with various microstructures were used, i.e., a liquid, a second more viscous liquid system containing xanthan gum, an emulsion, an aqueous gel, and a gelled emulsion. Growth experiments were conducted at 4 and 10 °C, both using homogeneous and surface inoculation (only for the gelled systems). Results regarding the influence of the growth morphology indicated that the lag phase of planktonic cells in the liquid system was similar to the lag phase of submerged colonies in the xanthan system. The lag phase of submerged colonies in each gelled system was considerably longer than the lag phase of surface colonies on these respective systems. The maximum specific growth rate of planktonic cells in the liquid system was significantly lower than for submerged colonies in the xanthan system at 10 °C, while no significant differences were observed at 4 °C. The maximum cell density was higher for submerged colonies than for surface colonies. The nature of the food matrix only exerted an influence on the maximum specific growth rate, which was significantly higher in the viscous systems than in the gelled systems. The presence of a small amount of fat droplets improved the growth of L. monocytogenes at 4 °C, resulting in a shorter lag phase and a higher maximum specific growth rate. The obtained results could be useful in the determination of a set of suitable microstructural parameters for future predictive models that incorporate the influence of food microstructure on microbial dynamics. Copyright © 2018. Published by Elsevier B.V.

Hydrological modelling in a drinking water catchment area as a means of evaluating pathogen risk reduction

NASA Astrophysics Data System (ADS)

Bergion, Viktor; Sokolova, Ekaterina; Åström, Johan; Lindhe, Andreas; Sörén, Kaisa; Rosén, Lars

2017-01-01

Waterborne outbreaks of gastrointestinal diseases are of great concern to drinking water producers and can give rise to substantial costs to the society. The World Health Organisation promotes an approach where the emphasis is on mitigating risks close to the contamination source. In order to handle microbial risks efficiently, there is a need for systematic risk management. In this paper we present a framework for microbial risk management of drinking water systems. The framework incorporates cost-benefit analysis as a decision support method. The hydrological Soil and Water Assessment Tool (SWAT) model, which was set up for the Stäket catchment area in Sweden, was used to simulate the effects of four different mitigation measures on microbial concentrations. The modelling results showed that the two mitigation measures that resulted in a significant (p < 0.05) reduction of Cryptosporidium spp. and Escherichia coli concentrations were a vegetative filter strip linked to cropland and improved treatment (by one Log10 unit) at the wastewater treatment plants. The mitigation measure with a vegetative filter strip linked to grazing areas resulted in a significant reduction of Cryptosporidium spp., but not of E. coli concentrations. The mitigation measure with enhancing the removal efficiency of all on-site wastewater treatment systems (total removal of 2 Log10 units) did not achieve any significant reduction of E. coli or Cryptosporidium spp. concentrations. The SWAT model was useful when characterising the effect of different mitigation measures on microbial concentrations. Hydrological modelling implemented within an appropriate risk management framework is a key decision support element as it identifies the most efficient alternative for microbial risk reduction.

Information transmission in microbial and fungal communication: from classical to quantum.

PubMed

Majumdar, Sarangam; Pal, Sukla

2018-06-01

Microbes have their own communication systems. Secretion and reception of chemical signaling molecules and ion-channels mediated electrical signaling mechanism are yet observed two special ways of information transmission in microbial community. In this article, we address the aspects of various crucial machineries which set the backbone of microbial cell-to-cell communication process such as quorum sensing mechanism (bacterial and fungal), quorum sensing regulated biofilm formation, gene expression, virulence, swarming, quorum quenching, role of noise in quorum sensing, mathematical models (therapy model, evolutionary model, molecular mechanism model and many more), synthetic bacterial communication, bacterial ion-channels, bacterial nanowires and electrical communication. In particular, we highlight bacterial collective behavior with classical and quantum mechanical approaches (including quantum information). Moreover, we shed a new light to introduce the concept of quantum synthetic biology and possible cellular quantum Turing test.

Developing and using artificial soils to analyze soil microbial processes

NASA Astrophysics Data System (ADS)

Gao, X.; Cheng, H. Y.; Boynton, L.; Masiello, C. A.; Silberg, J. J.

2017-12-01

Microbial diversity and function in soils are governed by soil characteristics such as mineral composition, particles size and aggregations, soil organic matter (SOM), and availability of nutrients and H2O. The spatial and temporal heterogeneity of soils creates a range of niches (hotspots) differing in the availability of O2, H2O, and nutrients, which shapes microbial activities at scales ranging from nanometer to landscape. Synthetic biologists often examine microbial response trigged by their environment conditions in nutrient-rich aqueous media using single strain microbes. While these studies provided useful insight in the role of soil microbes in important soil biogeochemical processes (e.g., C cycling, N cycling, etc.), the results obtained from the over-simplified model systems are often not applicable natural soil systems. On the contrary, soil microbiologists examine microbial processes in natural soils using longer incubation time. However, due to its physical, chemical and biological complexity of natural soils, it is often difficult to examine soil characteristics independently and understand how each characteristic influences soil microbial activities and their corresponding soil functioning. Therefore, it is necessary to bridge the gap and develop a model matrix to exclude unpredictable influences from the environment while still reliably mimicking real environmental conditions. The objective of this study is to design a range of ecologically-relevant artificial soils with varying texture (particle size distribution), structure, mineralogy, SOM content, and nutrient heterogeneity. We thoroughly characterize the artificial soils for pH, active surface area and surface morphology, cation exchange capacity (CEC), and water retention curve. We demonstrate the effectiveness of the artificial soils as useful matrix for microbial processes, such as microbial growth and horizontal gene transfer (HGT), using the gas-reporting biosensors recently developed in our lab.

Microbial Fingerprints of Community Structure Correlate with Changes in Ecosystem Function Induced by Perturbing the Redox Environment

NASA Astrophysics Data System (ADS)

Mills, A. L.; Ford, R. M.; Vallino, J. J.; Herman, J. S.; Hornberger, G. M.

2001-12-01

Restoration of high-quality groundwater has been an elusive engineering goal. Consequently, natural microbially-mediated reactions are increasingly relied upon to degrade organic contaminants, including hydrocarbons and many synthetic compounds. Of concern is how the introduction of an organic chemical contaminant affects the indigenous microbial communities, the geochemistry of the aquifer, and the function of the ecosystem. The presence of functional redundancy in microbial communities suggests that recovery of the community after a disturbance such as a contamination event could easily result in a community that is similar in function to that which existed prior to the contamination, but which is compositionally quite different. To investigate the relationship between community structure and function we observed the response of a diverse microbial community obtained from raw sewage to a dynamic redox environment using an aerobic/anaerobic/aerobic cycle. To evaluate changes in community function CO2, pH, ammonium and nitrate levels were monitored. A phylogenetically-based DNA technique (tRFLP) was used to assess changes in microbial community structure. Principal component analysis of the tRFLP data revealed significant changes in the composition of the microbial community that correlated well with changes in community function. Results from our experiments will be discussed in the context of a metabolic model based the biogeochemistry of the system. The governing philosophy of this thermodynamically constrained metabolic model is that living systems synthesize and allocate cellular machinery in such a way as to "optimally" utilize available resources in the environment. The robustness of this optimization-based approach provides a powerful tool for studying relationships between microbial diversity and ecosystem function.

Microbial Internal Storage Alters the Carbon Transformation in Dynamic Anaerobic Fermentation.

PubMed

Ni, Bing-Jie; Batstone, Damien; Zhao, Bai-Hang; Yu, Han-Qing

2015-08-04

Microbial internal storage processes have been demonstrated to occur and play an important role in activated sludge systems under both aerobic and anoxic conditions when operating under dynamic conditions. High-rate anaerobic reactors are often operated at a high volumetric organic loading and a relatively dynamic profile, with large amounts of fermentable substrates. These dynamic operating conditions and high catabolic energy availability might also facilitate the formation of internal storage polymers by anaerobic microorganisms. However, so far information about storage under anaerobic conditions (e.g., anaerobic fermentation) as well as its consideration in anaerobic process modeling (e.g., IWA Anaerobic Digestion Model No. 1, ADM1) is still sparse. In this work, the accumulation of storage polymers during anaerobic fermentation was evaluated by batch experiments using anaerobic methanogenic sludge and based on mass balance analysis of carbon transformation. A new mathematical model was developed to describe microbial storage in anaerobic systems. The model was calibrated and validated by using independent data sets from two different anaerobic systems, with significant storage observed, and effectively simulated in both systems. The inclusion of the new anaerobic storage processes in the developed model allows for more successful simulation of transients due to lower accumulation of volatile fatty acids (correction for the overestimation of volatile fatty acids), which mitigates pH fluctuations. Current models such as the ADM1 cannot effectively simulate these dynamics due to a lack of anaerobic storage mechanisms.

Immunity in Drosophila melanogaster--from microbial recognition to whole-organism physiology.

PubMed

Buchon, Nicolas; Silverman, Neal; Cherry, Sara

2014-12-01

Since the discovery of antimicrobial peptide responses 40 years ago, the fruit fly Drosophila melanogaster has proven to be a powerful model for the study of innate immunity. Early work focused on innate immune mechanisms of microbial recognition and subsequent nuclear factor-κB signal transduction. More recently, D. melanogaster has been used to understand how the immune response is regulated and coordinated at the level of the whole organism. For example, researchers have used this model in studies investigating interactions between the microbiota and the immune system at barrier epithelial surfaces that ensure proper nutritional and immune homeostasis both locally and systemically. In addition, studies in D. melanogaster have been pivotal in uncovering how the immune response is regulated by both endocrine and metabolic signalling systems, and how the immune response modifies these systems as part of a homeostatic circuit. In this Review, we briefly summarize microbial recognition and antiviral immunity in D. melanogaster, and we highlight recent studies that have explored the effects of organism-wide regulation of the immune response and, conversely, the effects of the immune response on organism physiology.

Predicting taxonomic and functional structure of microbial communities in acid mine drainage

PubMed Central

Kuang, Jialiang; Huang, Linan; He, Zhili; Chen, Linxing; Hua, Zhengshuang; Jia, Pu; Li, Shengjin; Liu, Jun; Li, Jintian; Zhou, Jizhong; Shu, Wensheng

2016-01-01

Predicting the dynamics of community composition and functional attributes responding to environmental changes is an essential goal in community ecology but remains a major challenge, particularly in microbial ecology. Here, by targeting a model system with low species richness, we explore the spatial distribution of taxonomic and functional structure of 40 acid mine drainage (AMD) microbial communities across Southeast China profiled by 16S ribosomal RNA pyrosequencing and a comprehensive microarray (GeoChip). Similar environmentally dependent patterns of dominant microbial lineages and key functional genes were observed regardless of the large-scale geographical isolation. Functional and phylogenetic β-diversities were significantly correlated, whereas functional metabolic potentials were strongly influenced by environmental conditions and community taxonomic structure. Using advanced modeling approaches based on artificial neural networks, we successfully predicted the taxonomic and functional dynamics with significantly higher prediction accuracies of metabolic potentials (average Bray–Curtis similarity 87.8) as compared with relative microbial abundances (similarity 66.8), implying that natural AMD microbial assemblages may be better predicted at the functional genes level rather than at taxonomic level. Furthermore, relative metabolic potentials of genes involved in many key ecological functions (for example, nitrogen and phosphate utilization, metals resistance and stress response) were extrapolated to increase under more acidic and metal-rich conditions, indicating a critical strategy of stress adaptation in these extraordinary communities. Collectively, our findings indicate that natural selection rather than geographic distance has a more crucial role in shaping the taxonomic and functional patterns of AMD microbial community that readily predicted by modeling methods and suggest that the model-based approach is essential to better understand natural acidophilic microbial communities. PMID:26943622

Predicting taxonomic and functional structure of microbial communities in acid mine drainage.

PubMed

Kuang, Jialiang; Huang, Linan; He, Zhili; Chen, Linxing; Hua, Zhengshuang; Jia, Pu; Li, Shengjin; Liu, Jun; Li, Jintian; Zhou, Jizhong; Shu, Wensheng

2016-06-01

Predicting the dynamics of community composition and functional attributes responding to environmental changes is an essential goal in community ecology but remains a major challenge, particularly in microbial ecology. Here, by targeting a model system with low species richness, we explore the spatial distribution of taxonomic and functional structure of 40 acid mine drainage (AMD) microbial communities across Southeast China profiled by 16S ribosomal RNA pyrosequencing and a comprehensive microarray (GeoChip). Similar environmentally dependent patterns of dominant microbial lineages and key functional genes were observed regardless of the large-scale geographical isolation. Functional and phylogenetic β-diversities were significantly correlated, whereas functional metabolic potentials were strongly influenced by environmental conditions and community taxonomic structure. Using advanced modeling approaches based on artificial neural networks, we successfully predicted the taxonomic and functional dynamics with significantly higher prediction accuracies of metabolic potentials (average Bray-Curtis similarity 87.8) as compared with relative microbial abundances (similarity 66.8), implying that natural AMD microbial assemblages may be better predicted at the functional genes level rather than at taxonomic level. Furthermore, relative metabolic potentials of genes involved in many key ecological functions (for example, nitrogen and phosphate utilization, metals resistance and stress response) were extrapolated to increase under more acidic and metal-rich conditions, indicating a critical strategy of stress adaptation in these extraordinary communities. Collectively, our findings indicate that natural selection rather than geographic distance has a more crucial role in shaping the taxonomic and functional patterns of AMD microbial community that readily predicted by modeling methods and suggest that the model-based approach is essential to better understand natural acidophilic microbial communities.

Groundwater–surface water mixing shifts ecological assembly processes and stimulates organic carbon turnover

DOE PAGES

Stegen, James C.; Fredrickson, James K.; Wilkins, Michael J.; ...

2016-04-07

Environmental transition zones are associated with geochemical gradients that overcome energy limitations to microbial metabolism, resulting in biogeochemical hot spots and moments. Riverine systems where groundwater mixes with surface water (the hyporheic zone) are spatially complex and temporally dynamic, making development of predictive models challenging. Spatial and temporal variations in hyporheic zone microbial communities are a key, but understudied, component of riverine biogeochemical function. To investigate the coupling among groundwater-surface water mixing, microbial communities, and biogeochemistry we applied ecological theory, aqueous biogeochemistry, DNA sequencing, and ultra-high resolution organic carbon profiling to field samples collected across times and locations representing amore » broad range of mixing conditions. Mixing of groundwater and surface water resulted in a shift from transport-driven stochastic dynamics to a deterministic microbial structure associated with elevated biogeochemical rates. While the dynamics of the hyporheic make predictive modeling a challenge, we provide new knowledge that can improve the tractability of such models.« less

Microbial dispersal in unsaturated porous media: Characteristics of motile bacterial cell motions in unsaturated angular pore networks

NASA Astrophysics Data System (ADS)

Ebrahimi, Ali N.; Or, Dani

2014-09-01

The dispersal rates of self-propelled microorganisms affect their spatial interactions and the ecological functioning of microbial communities. Microbial dispersal rates affect risk of contamination of water resources by soil-borne pathogens, the inoculation of plant roots, or the rates of spoilage of food products. In contrast with the wealth of information on microbial dispersal in water replete systems, very little is known about their dispersal rates in unsaturated porous media. The fragmented aqueous phase occupying complex soil pore spaces suppress motility and limits dispersal ranges in unsaturated soil. The primary objective of this study was to systematically evaluate key factors that shape microbial dispersal in model unsaturated porous media to quantify effects of saturation, pore space geometry, and chemotaxis on characteristics of principles that govern motile microbial dispersion in unsaturated soil. We constructed a novel 3-D angular pore network model (PNM) to mimic aqueous pathways in soil for different hydration conditions; within the PNM, we employed an individual-based model that considers physiological and biophysical properties of motile and chemotactic bacteria. The effects of hydration conditions on first passage times in different pore networks were studied showing that fragmentation of aquatic habitats under dry conditions sharply suppresses nutrient transport and microbial dispersal rates in good agreement with limited experimental data. Chemotactically biased mean travel speed of microbial cells across 9 mm saturated PNM was ˜3 mm/h decreasing exponentially to 0.45 mm/h for the PNM at matric potential of -15 kPa (for -35 kPa, dispersal practically ceases and the mean travel time to traverse the 9 mm PNM exceeds 1 year). Results indicate that chemotaxis enhances dispersal rates by orders of magnitude relative to random (diffusive) motions. Model predictions considering microbial cell sizes relative to available liquid pathways sizes were in good agreement with experimental results for unsaturated soils. The new modeling platform enables quantitative consideration of key biophysical factors (e.g., pore space heterogeneities and hydration conditions) governing microbial interactions in 3-D soil pore spaces.

C. botulinum inactivation kinetics implemented in a computational model of a high-pressure sterilization process.

PubMed

Juliano, Pablo; Knoerzer, Kai; Fryer, Peter J; Versteeg, Cornelis

2009-01-01

High-pressure, high-temperature (HPHT) processing is effective for microbial spore inactivation using mild preheating, followed by rapid volumetric compression heating and cooling on pressure release, enabling much shorter processing times than conventional thermal processing for many food products. A computational thermal fluid dynamic (CTFD) model has been developed to model all processing steps, including the vertical pressure vessel, an internal polymeric carrier, and food packages in an axis-symmetric geometry. Heat transfer and fluid dynamic equations were coupled to four selected kinetic models for the inactivation of C. botulinum; the traditional first-order kinetic model, the Weibull model, an nth-order model, and a combined discrete log-linear nth-order model. The models were solved to compare the resulting microbial inactivation distributions. The initial temperature of the system was set to 90 degrees C and pressure was selected at 600 MPa, holding for 220 s, with a target temperature of 121 degrees C. A representation of the extent of microbial inactivation throughout all processing steps was obtained for each microbial model. Comparison of the models showed that the conventional thermal processing kinetics (not accounting for pressure) required shorter holding times to achieve a 12D reduction of C. botulinum spores than the other models. The temperature distribution inside the vessel resulted in a more uniform inactivation distribution when using a Weibull or an nth-order kinetics model than when using log-linear kinetics. The CTFD platform could illustrate the inactivation extent and uniformity provided by the microbial models. The platform is expected to be useful to evaluate models fitted into new C. botulinum inactivation data at varying conditions of pressure and temperature, as an aid for regulatory filing of the technology as well as in process and equipment design.

Development of fish-based model systems with various microstructures.

PubMed

Verheyen, Davy; Baka, Maria; Glorieux, Seline; Duquenne, Barbara; Fraeye, Ilse; Skåra, Torstein; Van Impe, Jan F

2018-04-01

The effectiveness of predictive microbiology is limited by the lack of knowledge concerning the influence of food microstructure on microbial dynamics. Therefore, future modelling attempts should be based on experiments in structured food model systems as well as liquid systems. In this study, fish-based model systems with various microstructures were developed, i.e., two liquid systems (with and without xanthan gum), an emulsion, an aqueous gel, and a gelled emulsion. The microstructural effect was isolated by minimising compositional and physico-chemical changes among the different model systems. The systems were suitable for common growth and mild thermal inactivation experiments involving both homogeneous and surface inoculation. Average pH of the model systems was 6.36±0.03 and average a w was 0.988±0.002. The liquid system without xanthan gum behaved like a Newtonian fluid, while the emulsion and the liquid containing xanthan gum exhibited (non-Newtonian) pseudo-plastic behaviour. Both the aqueous gel and gelled emulsion were classified as strong gels, with a hardness of 1.35±0.07N and 1.25±0.05N, respectively. Fat droplet size of the emulsion and gelled emulsion model systems was evenly distributed around 1μm. In general, the set of model systems was proven to be suitable to study the influence of important aspects of food microstructure on microbial dynamics. Copyright © 2017. Published by Elsevier Ltd.

Microbial Communities as Experimental Units

PubMed Central

DAY, MITCH D.; BECK, DANIEL; FOSTER, JAMES A.

2011-01-01

Artificial ecosystem selection is an experimental technique that treats microbial communities as though they were discrete units by applying selection on community-level properties. Highly diverse microbial communities associated with humans and other organisms can have significant impacts on the health of the host. It is difficult to find correlations between microbial community composition and community-associated diseases, in part because it may be impossible to define a universal and robust species concept for microbes. Microbial communities are composed of potentially thousands of unique populations that evolved in intimate contact, so it is appropriate in many situations to view the community as the unit of analysis. This perspective is supported by recent discoveries using metagenomics and pangenomics. Artificial ecosystem selection experiments can be costly, but they bring the logical rigor of biological model systems to the emerging field of microbial community analysis. PMID:21731083

Strain- and Substrate-Dependent Redox Mediator and Electricity Production by Pseudomonas aeruginosa.

PubMed

Bosire, Erick M; Blank, Lars M; Rosenbaum, Miriam A

2016-08-15

Pseudomonas aeruginosa is an important, thriving member of microbial communities of microbial bioelectrochemical systems (BES) through the production of versatile phenazine redox mediators. Pure culture experiments with a model strain revealed synergistic interactions of P. aeruginosa with fermenting microorganisms whereby the synergism was mediated through the shared fermentation product 2,3-butanediol. Our work here shows that the behavior and efficiency of P. aeruginosa in mediated current production is strongly dependent on the strain of P. aeruginosa We compared levels of phenazine production by the previously investigated model strain P. aeruginosa PA14, the alternative model strain P. aeruginosa PAO1, and the BES isolate Pseudomonas sp. strain KRP1 with glucose and the fermentation products 2,3-butanediol and ethanol as carbon substrates. We found significant differences in substrate-dependent phenazine production and resulting anodic current generation for the three strains, with the BES isolate KRP1 being overall the best current producer and showing the highest electrochemical activity with glucose as a substrate (19 μA cm(-2) with ∼150 μg ml(-1) phenazine carboxylic acid as a redox mediator). Surprisingly, P. aeruginosa PAO1 showed very low phenazine production and electrochemical activity under all tested conditions. Microbial fuel cells and other microbial bioelectrochemical systems hold great promise for environmental technologies such as wastewater treatment and bioremediation. While there is much emphasis on the development of materials and devices to realize such systems, the investigation and a deeper understanding of the underlying microbiology and ecology are lagging behind. Physiological investigations focus on microorganisms exhibiting direct electron transfer in pure culture systems. Meanwhile, mediated electron transfer with natural redox compounds produced by, for example, Pseudomonas aeruginosa might enable an entire microbial community to access a solid electrode as an alternative electron acceptor. To better understand the ecological relationships between mediator producers and mediator utilizers, we here present a comparison of the phenazine-dependent electroactivities of three Pseudomonas strains. This work forms the foundation for more complex coculture investigations of mediated electron transfer in microbial fuel cells. Copyright © 2016, American Society for Microbiology. All Rights Reserved.

Strain- and Substrate-Dependent Redox Mediator and Electricity Production by Pseudomonas aeruginosa

PubMed Central

Bosire, Erick M.; Blank, Lars M.

2016-01-01

ABSTRACT Pseudomonas aeruginosa is an important, thriving member of microbial communities of microbial bioelectrochemical systems (BES) through the production of versatile phenazine redox mediators. Pure culture experiments with a model strain revealed synergistic interactions of P. aeruginosa with fermenting microorganisms whereby the synergism was mediated through the shared fermentation product 2,3-butanediol. Our work here shows that the behavior and efficiency of P. aeruginosa in mediated current production is strongly dependent on the strain of P. aeruginosa. We compared levels of phenazine production by the previously investigated model strain P. aeruginosa PA14, the alternative model strain P. aeruginosa PAO1, and the BES isolate Pseudomonas sp. strain KRP1 with glucose and the fermentation products 2,3-butanediol and ethanol as carbon substrates. We found significant differences in substrate-dependent phenazine production and resulting anodic current generation for the three strains, with the BES isolate KRP1 being overall the best current producer and showing the highest electrochemical activity with glucose as a substrate (19 μA cm−2 with ∼150 μg ml−1 phenazine carboxylic acid as a redox mediator). Surprisingly, P. aeruginosa PAO1 showed very low phenazine production and electrochemical activity under all tested conditions. IMPORTANCE Microbial fuel cells and other microbial bioelectrochemical systems hold great promise for environmental technologies such as wastewater treatment and bioremediation. While there is much emphasis on the development of materials and devices to realize such systems, the investigation and a deeper understanding of the underlying microbiology and ecology are lagging behind. Physiological investigations focus on microorganisms exhibiting direct electron transfer in pure culture systems. Meanwhile, mediated electron transfer with natural redox compounds produced by, for example, Pseudomonas aeruginosa might enable an entire microbial community to access a solid electrode as an alternative electron acceptor. To better understand the ecological relationships between mediator producers and mediator utilizers, we here present a comparison of the phenazine-dependent electroactivities of three Pseudomonas strains. This work forms the foundation for more complex coculture investigations of mediated electron transfer in microbial fuel cells. PMID:27287325

The effects of mixotrophy on the stability and dynamics of a simple planktonic food web

USGS Publications Warehouse

Jost, Christian; Lawrence, Cathryn A.; Campolongo, Francesca; Wouter, van de Bund; Hill, Sheryl; DeAngelis, Donald L.

2004-01-01

Recognition of the microbial loop as an important part of aquatic ecosystems disrupted the notion of simple linear food chains. However, current research suggests that even the microbial loop paradigm is a gross simplification of microbial interactions due to the presence of mixotrophs—organisms that both photosynthesize and graze. We present a simple food web model with four trophic species, three of them arranged in a food chain (nutrients–autotrophs–herbivores) and the fourth as a mixotroph with links to both the nutrients and the autotrophs. This model is used to study the general implications of inclusion of the mixotrophic link in microbial food webs and the specific predictions for a parameterization that describes open ocean mixed layer plankton dynamics. The analysis indicates that the system parameters reside in a region of the parameter space where the dynamics converge to a stable equilibrium rather than displaying periodic or chaotic solutions. However, convergence requires weeks to months, suggesting that the system would never reach equilibrium in the ocean due to alteration of the physical forcing regime. Most importantly, the mixotrophic grazing link seems to stabilize the system in this region of the parameter space, particularly when nutrient recycling feedback loops are included.

Ecological perspectives on synthetic biology: insights from microbial population biology

PubMed Central

Escalante, Ana E.; Rebolleda-Gómez, María; Benítez, Mariana; Travisano, Michael

2015-01-01

The metabolic capabilities of microbes are the basis for many major biotechnological advances, exploiting microbial diversity by selection or engineering of single strains. However, there are limits to the advances that can be achieved with single strains, and attention has turned toward the metabolic potential of consortia and the field of synthetic ecology. The main challenge for the synthetic ecology is that consortia are frequently unstable, largely because evolution by constituent members affects their interactions, which are the basis of collective metabolic functionality. Current practices in modeling consortia largely consider interactions as fixed circuits of chemical reactions, which greatly increases their tractability. This simplification comes at the cost of essential biological realism, stripping out the ecological context in which the metabolic actions occur and the potential for evolutionary change. In other words, evolutionary stability is not engineered into the system. This realization highlights the necessity to better identify the key components that influence the stable coexistence of microorganisms. Inclusion of ecological and evolutionary principles, in addition to biophysical variables and stoichiometric modeling of metabolism, is critical for microbial consortia design. This review aims to bring ecological and evolutionary concepts to the discussion on the stability of microbial consortia. In particular, we focus on the combined effect of spatial structure (connectivity of molecules and cells within the system) and ecological interactions (reciprocal and non-reciprocal) on the persistence of microbial consortia. We discuss exemplary cases to illustrate these ideas from published studies in evolutionary biology and biotechnology. We conclude by making clear the relevance of incorporating evolutionary and ecological principles to the design of microbial consortia, as a way of achieving evolutionarily stable and sustainable systems. PMID:25767468

Immunity by equilibrium.

PubMed

Eberl, Gérard

2016-08-01

The classical model of immunity posits that the immune system reacts to pathogens and injury and restores homeostasis. Indeed, a century of research has uncovered the means and mechanisms by which the immune system recognizes danger and regulates its own activity. However, this classical model does not fully explain complex phenomena, such as tolerance, allergy, the increased prevalence of inflammatory pathologies in industrialized nations and immunity to multiple infections. In this Essay, I propose a model of immunity that is based on equilibrium, in which the healthy immune system is always active and in a state of dynamic equilibrium between antagonistic types of response. This equilibrium is regulated both by the internal milieu and by the microbial environment. As a result, alteration of the internal milieu or microbial environment leads to immune disequilibrium, which determines tolerance, protective immunity and inflammatory pathology.

Utilization of subsurface microbial electrochemical systems to elucidate the mechanisms of competition between methanogenesis and microbial iron(III)/humic acid reduction in Arctic peat soils

NASA Astrophysics Data System (ADS)

Friedman, E. S.; Miller, K.; Lipson, D.; Angenent, L. T.

2012-12-01

High-latitude peat soils are a major carbon reservoir, and there is growing concern that previously dormant carbon from this reservoir could be released to the atmosphere as a result of continued climate change. Microbial processes, such as methanogenesis and carbon dioxide production via iron(III) or humic acid reduction, are at the heart of the carbon cycle in Arctic peat soils [1]. A deeper understanding of the factors governing microbial dominance in these soils is crucial for predicting the effects of continued climate change. In previous years, we have demonstrated the viability of a potentiostatically-controlled subsurface microbial electrochemical system-based biosensor that measures microbial respiration via exocellular electron transfer [2]. This system utilizes a graphite working electrode poised at 0.1 V NHE to mimic ferric iron and humic acid compounds. Microbes that would normally utilize these compounds as electron acceptors donate electrons to the electrode instead. The resulting current is a measure of microbial respiration with the electrode and is recorded with respect to time. Here, we examine the mechanistic relationship between methanogenesis and iron(III)- or humic acid-reduction by using these same microbial-three electrode systems to provide an inexhaustible source of alternate electron acceptor to microbes in these soils. Chamber-based carbon dioxide and methane fluxes were measured from soil collars with and without microbial three-electrode systems over a period of four weeks. In addition, in some collars we simulated increased fermentation by applying acetate treatments to understand possible effects of continued climate change on microbial processes in these carbon-rich soils. The results from this work aim to increase our fundamental understanding of competition between electron acceptors, and will provide valuable data for climate modeling scenarios. 1. Lipson, D.A., et al., Reduction of iron (III) and humic substances plays a major role in anaerobic respiration in an Arctic peat soil. Journal of Geophysical Research-Biogeosciences, 2010. 115. 2. Friedman, E.S., et al., A cost-effective and field-ready potentiostat that poises subsurface electrodes to monitor bacterial respiration. Biosensors and Bioelectronics, 2012. 32(1): p. 309-313.

An experimental-computational platform for investigating microbial interactions and dynamics in communities with two codependent species

NASA Astrophysics Data System (ADS)

Fuentes-Cabrera, Miguel; Anderson, John D.; Wilmoth, Jared; Ginovart, Marta; Prats, Clara; Portell-Canal, Xavier; Retterer, Scott

Microbial interactions are critical for governing community behavior and structure in natural environments. Examination of microbial interactions in the lab involves growth under ideal conditions in batch culture; conditions that occur in nature are, however, characterized by disequilibrium. Of particular interest is the role that system variables play in shaping cell-to-cell interactions and organization at ultrafine spatial scales. We seek to use experiments and agent-based modeling to help discover mechanisms relevant to microbial dynamics and interactions in the environment. Currently, we are using an agent-based model to simulate microbial growth, dynamics and interactions that occur on a microwell-array device developed in our lab. Bacterial cells growing in the microwells of this platform can be studied with high-throughput and high-content image analyses using brightfield and fluorescence microscopy. The agent-based model is written in the language Netlogo, which in turn is ''plugged into'' a computational framework that allows submitting many calculations in parallel for different initial parameters; visualizing the outcomes in an interactive phase-like diagram; and searching, with a genetic algorithm, for the parameters that lead to the most optimal simulation outcome.

Multi-variable mathematical models for the air-cathode microbial fuel cell system

NASA Astrophysics Data System (ADS)

Ou, Shiqi; Kashima, Hiroyuki; Aaron, Douglas S.; Regan, John M.; Mench, Matthew M.

2016-05-01

This research adopted the version control system into the model construction for the single chamber air-cathode microbial fuel cell (MFC) system, to understand the interrelation of biological, chemical, and electrochemical reactions. The anodic steady state model was used to consider the chemical species diffusion and electric migration influence to the MFC performance. In the cathodic steady state model, the mass transport and reactions in a multi-layer, abiotic cathode and multi-bacteria cathode biofilm were simulated. Transport of hydroxide was assumed for cathodic pH change. This assumption is an alternative to the typical notion of proton consumption during oxygen reduction to explain elevated cathode pH. The cathodic steady state model provided the power density and polarization curve performance results that can be compared to an experimental MFC system. Another aspect considered was the relative contributions of platinum catalyst and microbes on the cathode to the oxygen reduction reaction (ORR). Simulation results showed that the biocatalyst in a cathode that includes a Pt/C catalyst likely plays a minor role in ORR, contributing up to 8% of the total power calculated by the models.

Coupling Spatiotemporal Community Assembly Processes to Changes in Microbial Metabolism

DOE Office of Scientific and Technical Information (OSTI.GOV)

Graham, Emily B.; Crump, Alex R.; Resch, Charles T.

Community assembly processes govern shifts in species abundances in response to environmental change, yet our understanding of assembly remains largely decoupled from ecosystem function. Here, we test hypotheses regarding assembly and function across space and time using hyporheic microbial communities as a model system. We pair sampling of two habitat types through hydrologic fluctuation with null modeling and multivariate statistics. We demonstrate that dual selective pressures assimilate to generate compositional changes at distinct timescales among habitat types, resulting in contrasting associations of Betaproteobacteria and Thaumarchaeota with selection and with seasonal changes in aerobic metabolism. Our results culminate in a conceptualmore » model in which selection from contrasting environments regulates taxon abundance and ecosystem function through time, with increases in function when oscillating selection opposes stable selective pressures. Our model is applicable within both macrobial and microbial ecology and presents an avenue for assimilating community assembly processes into predictions of ecosystem function.« less

Data-Driven Microbial Modeling for Soil Carbon Decomposition and Stabilization

NASA Astrophysics Data System (ADS)

Luo, Yiqi; Chen, Ji; Chen, Yizhao; Feng, Wenting

2017-04-01

Microorganisms have long been known to catalyze almost all the soil organic carbon (SOC) transformation processes (e.g., decomposition, stabilization, and mineralization). Representing microbial processes in Earth system models (ESMs) has the potential to improve projections of SOC dynamics. We have recently examined (1) relationships of microbial functions with environmental factors and (2) microbial regulations of decomposition and other key soil processes. According to three lines of evidence, we have developed a data-driven enzyme (DENZY) model to simulate soil microbial decomposition and stabilization. First, our meta-analysis of 64 published field studies showed that field experimental warming significantly increased soil microbial communities abundance, which is negatively correlated with the mean annual temperature. The negative correlation indicates that warming had stronger effects in colder than warmer regions. Second, we found that the SOC decomposition, especially the transfer between labile SOC and protected SOC, is nonlinearly regulated by soil texture parameters, such as sand and silt contents. Third, we conducted a global analysis of the C-degrading enzyme activities, soil respiration, and SOC content under N addition. Our results show that N addition has contrasting effects on cellulase (hydrolytic C-degrading enzymes) and ligninase (oxidative C-degrading enzymes) activities. N-enhanced cellulase activity contributes to the minor stimulation of soil respiration whereas N-induced repression on ligninase activity drives soil C sequestration. Our analysis links the microbial extracellular C-degrading enzymes to the SOC dynamics at ecosystem scales across scores of experimental sites around the world. It offers direct evidence that N-induced changes in microbial community and physiology play fundamental roles in controlling the soil C cycle. Built upon those three lines of empirical evidence, the DENZY model includes two enzyme pools and explicitly characterizes two classes of extracellular enzyme activities: one that degrades organic molecules containing both C and N (e.g., chitin or protein) and another that degrades only C (e.g., cellulose). The DENZY model assumes that the microbes allocate resources to different enzyme pools so as to exactly satisfy microbial CN ratio stoichiometry in response to changes in climate conditions and soil attributes. The DENZY model can simulate differential effects of nitrogen fertilization on the two groups of enzymes and thus soil respiration and SOC dynamics. We will select field experimental sites to test the DENZY model. With increasing amounts of available observations and data synthesis, this DENZY model will be better parameterized and have a potential to reveal how responses of microbial enzymes to environmental changes regulate soil carbon decomposition and stabilization.

Microbial communities from different subsystems in biological heap leaching system play different roles in iron and sulfur metabolisms.

PubMed

Xiao, Yunhua; Liu, Xueduan; Ma, Liyuan; Liang, Yili; Niu, Jiaojiao; Gu, Yabing; Zhang, Xian; Hao, Xiaodong; Dong, Weiling; She, Siyuan; Yin, Huaqun

2016-08-01

The microbial communities are important for minerals decomposition in biological heap leaching system. However, the differentiation and relationship of composition and function of microbial communities between leaching heap (LH) and leaching solution (LS) are still unclear. In this study, 16S rRNA gene sequencing was used to assess the microbial communities from the two subsystems in ZiJinShan copper mine (Fujian province, China). Results of PCoA and dissimilarity test showed that microbial communities in LH samples were significantly different from those in LS samples. The dominant genera of LH was Acidithiobacillus (57.2 ∼ 87.9 %), while Leptospirillum (48.6 ∼ 73.7 %) was predominant in LS. Environmental parameters (especially pH) were the major factors to influence the composition and structure of microbial community by analysis of Mantel tests. Results of functional test showed that microbial communities in LH utilized sodium thiosulfate more quickly and utilized ferrous sulfate more slowly than those in LS, which further indicated that the most sulfur-oxidizing processes of bioleaching took place in LH and the most iron-oxidizing processes were in LS. Further study found that microbial communities in LH had stronger pyrite leaching ability, and iron extraction efficiency was significantly positively correlated with Acidithiobacillus (dominated in LH), which suggested that higher abundance ratio of sulfur-oxidizing microbes might in favor of minerals decomposition. Finally, a conceptual model was designed through the above results to better exhibit the sulfur and iron metabolism in bioleaching systems.

Microbial response to environmental gradients in a ceramic-based diffusion system.

PubMed

Wolfaardt, G M; Hendry, M J; Birkham, T; Bressel, A; Gardner, M N; Sousa, A J; Korber, D R; Pilaski, M

2008-05-01

A solid, porous matrix was used to establish steady-state concentration profiles upon which microbial responses to concentration gradients of nutrients or antimicrobial agents could be quantified. This technique relies on the development of spatially defined concentration gradients across a ceramic plate resulting from the diffusion of solutes through the porous ceramic matrix. A two-dimensional, finite-element numerical transport model was used to predict the establishment of concentration profiles, after which concentration profiles of conservative tracers were quantified fluorometrically and chemically at the solid-liquid interface to verify the simulated profiles. Microbial growth responses to nutrient, hypochloride, and antimicrobial concentration gradients were then quantified using epifluorescent or scanning confocal laser microscopy. The observed microbial response verified the establishment and maintenance of stable concentration gradients along the solid-liquid interface. These results indicate the ceramic diffusion system has potential for the isolation of heterogeneous microbial communities as well as for testing the efficacy of antimicrobial agents. In addition, the durability of the solid matrix allowed long-term investigations, making this approach preferable to conventional gel-stabilized systems that are impeded by erosion as well as expansion or shrinkage of the gel. Copyright 2008 Wiley Periodicals, Inc.

Disturbance Regimes Predictably Alter Diversity in an Ecologically Complex Bacterial System

PubMed Central

Scholz, Monika; Hutchison, Alan L.; Dinner, Aaron R.; Gilbert, Jack A.; Coleman, Maureen L.

2016-01-01

ABSTRACT Diversity is often associated with the functional stability of ecological communities from microbes to macroorganisms. Understanding how diversity responds to environmental perturbations and the consequences of this relationship for ecosystem function are thus central challenges in microbial ecology. Unimodal diversity-disturbance relationships, in which maximum diversity occurs at intermediate levels of disturbance, have been predicted for ecosystems where life history tradeoffs separate organisms along a disturbance gradient. However, empirical support for such peaked relationships in macrosystems is mixed, and few studies have explored these relationships in microbial systems. Here we use complex microbial microcosm communities to systematically determine diversity-disturbance relationships over a range of disturbance regimes. We observed a reproducible switch between community states, which gave rise to transient diversity maxima when community states were forced to mix. Communities showed reduced compositional stability when diversity was highest. To further explore these dynamics, we formulated a simple model that reveals specific regimes under which diversity maxima are stable. Together, our results show how both unimodal and non-unimodal diversity-disturbance relationships can be observed as a system switches between two distinct microbial community states; this process likely occurs across a wide range of spatially and temporally heterogeneous microbial ecosystems. PMID:27999158

Ruminal acidosis in beef cattle: the current microbiological and nutritional outlook.

PubMed

Nagaraja, T G; Titgemeyer, E C

2007-06-01

Ruminal acidosis continues to be a common ruminal digestive disorder in beef cattle and can lead to marked reductions in cattle performance. Ruminal acidosis or increased accumulation of organic acids in the rumen reflects imbalance between microbial production, microbial utilization, and ruminal absorption of organic acids. The severity of acidosis, generally related to the amount, frequency, and duration of grain feeding, varies from acute acidosis due to lactic acid accumulation, to subacute acidosis due to accumulation of volatile fatty acids in the rumen. Ruminal microbial changes associated with acidosis are reflective of increased availability of fermentable substrates and subsequent accumulation of organic acids. Microbial changes in the rumen associated with acute acidosis have been well documented. Microbial changes in subacute acidosis resemble those observed during adaptation to grain feeding and have not been well documented. The decrease in ciliated protozoal population is a common feature of both forms of acidosis and may be a good microbial indicator of an acidotic rumen. Other microbial factors, such as endotoxin and histamine, are thought to contribute to the systemic effects of acidosis. Various models have been developed to assess the effects of variation in feed intake, dietary roughage amount and source, dietary grain amount and processing, step-up regimen, dietary addition of fibrous byproducts, and feed additives. Models have been developed to study effects of management considerations on acidosis in cattle previously adapted to grain-based diets. Although these models have provided useful information related to ruminal acidosis, many are inadequate for detecting responses to treatment due to inadequate replication, low feed intakes by the experimental cattle that can limit the expression of acidosis, and the feeding of cattle individually, which reduces experimental variation but limits the ability of researchers to extrapolate the data to cattle performing at industry standards. Optimal model systems for assessing effects of various management and nutritional strategies on ruminal acidosis will require technologies that allow feed intake patterns, ruminal conditions, and animal health and performance to be measured simultaneously in a large number of cattle managed under conditions similar to commercial feed yards. Such data could provide valuable insight into the true extent to which acidosis affects cattle performance.

Aerobic Toluene Degraders in the Rhizosphere of a Constructed Wetland Model Show Diurnal Polyhydroxyalkanoate Metabolism.

PubMed

Lünsmann, Vanessa; Kappelmeyer, Uwe; Taubert, Anja; Nijenhuis, Ivonne; von Bergen, Martin; Heipieper, Hermann J; Müller, Jochen A; Jehmlich, Nico

2016-07-15

Constructed wetlands (CWs) are successfully applied for the treatment of waters contaminated with aromatic compounds. In these systems, plants provide oxygen and root exudates to the rhizosphere and thereby stimulate microbial degradation processes. Root exudation of oxygen and organic compounds depends on photosynthetic activity and thus may show day-night fluctuations. While diurnal changes in CW effluent composition have been observed, information on respective fluctuations of bacterial activity are scarce. We investigated microbial processes in a CW model system treating toluene-contaminated water which showed diurnal oscillations of oxygen concentrations using metaproteomics. Quantitative real-time PCR was applied to assess diurnal expression patterns of genes involved in aerobic and anaerobic toluene degradation. We observed stable aerobic toluene turnover by Burkholderiales during the day and night. Polyhydroxyalkanoate synthesis was upregulated in these bacteria during the day, suggesting that they additionally feed on organic root exudates while reutilizing the stored carbon compounds during the night via the glyoxylate cycle. Although mRNA copies encoding the anaerobic enzyme benzylsuccinate synthase (bssA) were relatively abundant and increased slightly at night, the corresponding protein could not be detected in the CW model system. Our study provides insights into diurnal patterns of microbial processes occurring in the rhizosphere of an aquatic ecosystem. Constructed wetlands are a well-established and cost-efficient option for the bioremediation of contaminated waters. While it is commonly accepted knowledge that the function of CWs is determined by the interplay of plants and microorganisms, the detailed molecular processes are considered a black box. Here, we used a well-characterized CW model system treating toluene-contaminated water to investigate the microbial processes influenced by diurnal plant root exudation. Our results indicated stable aerobic toluene degradation by members of the Burkholderiales during the day and night. Polyhydroxyalkanoate synthesis in these bacteria was higher during the day, suggesting that they additionally fed on organic root exudates and reutilized the stored carbon compounds during the night. Our study illuminates microbial processes occurring in the rhizosphere of an aquatic ecosystem. Copyright © 2016, American Society for Microbiology. All Rights Reserved.

Aerobic Toluene Degraders in the Rhizosphere of a Constructed Wetland Model Show Diurnal Polyhydroxyalkanoate Metabolism

PubMed Central

Lünsmann, Vanessa; Kappelmeyer, Uwe; Taubert, Anja; Nijenhuis, Ivonne; von Bergen, Martin; Müller, Jochen A.; Jehmlich, Nico

2016-01-01

ABSTRACT Constructed wetlands (CWs) are successfully applied for the treatment of waters contaminated with aromatic compounds. In these systems, plants provide oxygen and root exudates to the rhizosphere and thereby stimulate microbial degradation processes. Root exudation of oxygen and organic compounds depends on photosynthetic activity and thus may show day-night fluctuations. While diurnal changes in CW effluent composition have been observed, information on respective fluctuations of bacterial activity are scarce. We investigated microbial processes in a CW model system treating toluene-contaminated water which showed diurnal oscillations of oxygen concentrations using metaproteomics. Quantitative real-time PCR was applied to assess diurnal expression patterns of genes involved in aerobic and anaerobic toluene degradation. We observed stable aerobic toluene turnover by Burkholderiales during the day and night. Polyhydroxyalkanoate synthesis was upregulated in these bacteria during the day, suggesting that they additionally feed on organic root exudates while reutilizing the stored carbon compounds during the night via the glyoxylate cycle. Although mRNA copies encoding the anaerobic enzyme benzylsuccinate synthase (bssA) were relatively abundant and increased slightly at night, the corresponding protein could not be detected in the CW model system. Our study provides insights into diurnal patterns of microbial processes occurring in the rhizosphere of an aquatic ecosystem. IMPORTANCE Constructed wetlands are a well-established and cost-efficient option for the bioremediation of contaminated waters. While it is commonly accepted knowledge that the function of CWs is determined by the interplay of plants and microorganisms, the detailed molecular processes are considered a black box. Here, we used a well-characterized CW model system treating toluene-contaminated water to investigate the microbial processes influenced by diurnal plant root exudation. Our results indicated stable aerobic toluene degradation by members of the Burkholderiales during the day and night. Polyhydroxyalkanoate synthesis in these bacteria was higher during the day, suggesting that they additionally fed on organic root exudates and reutilized the stored carbon compounds during the night. Our study illuminates microbial processes occurring in the rhizosphere of an aquatic ecosystem. PMID:27129963

Influence of food intrinsic complexity on Listeria monocytogenes growth in/on vacuum-packed model systems at suboptimal temperatures.

PubMed

Baka, Maria; Noriega, Estefanía; Van Langendonck, Kristof; Van Impe, Jan F

2016-10-17

Food intrinsic factors e.g., food (micro)structure, compositional and physicochemical aspects, which are mutually dependent, influence microbial growth. While the effect of composition and physicochemical properties on microbial growth has been thoroughly assessed and characterised, the role of food (micro)structure still remains unravelled. Most studies on food (micro)structure focus on comparing planktonic growth in liquid (microbiological) media with colonial growth in/on solid-like systems or on real food surfaces. However, foods are not only liquids or solids; they can also be emulsions or gelled emulsions and have complex compositions. In this study, Listeria monocytogenes growth was studied on the whole spectrum of (micro)structure, in terms of food (model) systems. The model systems varied not only in (micro)structure, which was the target of the study, but also in compositional and physicochemical characteristics, which was an inevitable consequence of the (micro)structural variability. The compositional and physicochemical differences were mainly due to the presence or absence of fat and gelling agents. The targeted (micro)structures were: i) liquids, ii) aqueous gels, iii) emulsions and iv) gelled emulsions. Furthermore, the microbial dynamics were studied and compared in/on all these model systems, as well as on a compositionally predefined canned meat, developed in order to have equal compositional level to the gelled emulsion model system and represent a real food system. Frankfurter sausages were the targeted real foods, selected as a case study, to which the canned meat had similar compositional characteristics. All systems were vacuum packed and incubated at 4, 8 and 12°C. The most appropriate protocol for the preparation of the model systems was developed. The pH, water activity and resistance to penetration of the model systems were characterised. Results indicated that low temperature contributes to growth variations among the model systems. Additionally, the firmer the solid system, the faster L. monocytogenes grew on it. Finally, it was found that L. monocytogenes grows faster on canned meat and real Frankfurters, as found in a previous study, followed by liquids, aqueous gels, emulsions and gelled emulsions. This observation indicates that all model systems, developed in this study, underestimated L. monocytogenes growth. Despite some limitations, model systems are overall advantageous and therefore, their validation is always recommended prior to further use. Copyright © 2016. Published by Elsevier B.V.

Teaching the Methodology of Science: The Utilization of Microbial Model Systems for Biometric Analysis.

ERIC Educational Resources Information Center

Adamo, Joseph A.

Students set in their ways are usually reluctant, as a general rule, to deal with open-ended investigative scenarios. In order to acquaint the student with the physical method and philosophical thought process of the discipline, the tone of the course must be set early on. The present study was conducted to develop scenarios and microbial model…

Evaluation of the relevance of the glassy state as stability criterion for freeze-dried bacteria by application of the Arrhenius and WLF model.

PubMed

Aschenbrenner, Mathias; Kulozik, Ulrich; Foerst, Petra

2012-12-01

The aim of this work was to describe the temperature dependence of microbial inactivation for several storage conditions and protective systems (lactose, trehalose and dextran) in relation to the physical state of the sample, i.e. the glassy or non-glassy state. The resulting inactivation rates k were described by applying two models, Arrhenius and Williams-Landel-Ferry (WLF), in order to evaluate the relevance of diffusional limitation as a protective mechanism. The application of the Arrhenius model revealed a significant decrease in activation energy E(a) for storage conditions close to T(g). This finding is an indication that the protective effect of a surrounding glassy matrix can, at least, partly be ascribed to its inherent restricted diffusion and mobility. The application of the WLF model revealed that the temperature dependence of microbial inactivation above T(g) is significantly weaker than predicted by the universal coefficients. Thus, it can be concluded that microbial inactivation is not directly linked with the mechanical relaxation behavior of the surrounding matrix as it was reported for viscosity and crystallization phenomena in case of disaccharide systems. Copyright © 2012. Published by Elsevier Inc.

Modelling the transport and decay processes of microbial tracers in a macro-tidal estuary.

PubMed

Abu-Bakar, Amyrhul; Ahmadian, Reza; Falconer, Roger A

2017-10-15

The Loughor Estuary is a macro-tidal coastal basin, located along the Bristol Channel, in the South West of the U.K. The maximum spring tidal range in the estuary is up to 7.5 m, near Burry Port Harbour. This estuarine region can experience severe coastal flooding during high spring tides, including extreme flooding of the intertidal saltmarshes at Llanrhidian, as well as the lower industrial and residential areas at Llanelli and Gowerton. The water quality of this estuarine basin needs to comply with the designated standards for safe recreational bathing and shellfish harvesting industries. The waterbody however, potentially receives overloading of bacterial inputs that enter the estuarine system from both point and diffuse sources. Therefore, a microbial tracer study was carried out to get a better understanding of the faecal bacteria sources and to enable a hydro-environmental model to be refined and calibrated for both advection and dispersion transport. A two-dimensional hydro-environmental model has been refined and extended to predict the highest water level covering the intertidal floodplains of the Loughor Estuary. The validated hydrodynamic model for both water levels and currents, was included with the injected mass of microbial tracer, i.e. MS2 coliphage from upstream of the estuary, and modelled as a non-conservative tracer over several tidal cycles through the system. The calibration and validation of the transport and decay of microbial tracer was undertaken, by comparing the model results and the measured data at two different sampling locations. The refined model developed as a part of this study, was used to acquire a better understanding of the water quality processes and the potential sources of bacterial pollution in the estuary. Copyright © 2017 Elsevier Ltd. All rights reserved.

Engineering Ecosystems and Synthetic Ecologies#

PubMed Central

Mee, Michael T; Wang, Harris H

2012-01-01

Microbial ecosystems play an important role in nature. Engineering these systems for industrial, medical, or biotechnological purposes are important pursuits for synthetic biologists and biological engineers moving forward. Here, we provide a review of recent progress in engineering natural and synthetic microbial ecosystems. We highlight important forward engineering design principles, theoretical and quantitative models, new experimental and manipulation tools, and possible applications of microbial ecosystem engineering. We argue that simply engineering individual microbes will lead to fragile homogenous populations that are difficult to sustain, especially in highly heterogeneous and unpredictable environments. Instead, engineered microbial ecosystems are likely to be more robust and able to achieve complex tasks at the spatial and temporal resolution needed for truly programmable biology. PMID:22722235

Ecosystems Biology Approaches To Determine Key Fitness Traits of Soil Microorganisms

NASA Astrophysics Data System (ADS)

Brodie, E.; Zhalnina, K.; Karaoz, U.; Cho, H.; Nuccio, E. E.; Shi, S.; Lipton, M. S.; Zhou, J.; Pett-Ridge, J.; Northen, T.; Firestone, M.

2014-12-01

The application of theoretical approaches such as trait-based modeling represent powerful tools to explain and perhaps predict complex patterns in microbial distribution and function across environmental gradients in space and time. These models are mostly deterministic and where available are built upon a detailed understanding of microbial physiology and response to environmental factors. However as most soil microorganisms have not been cultivated, for the majority our understanding is limited to insights from environmental 'omic information. Information gleaned from 'omic studies of complex systems should be regarded as providing hypotheses, and these hypotheses should be tested under controlled laboratory conditions if they are to be propagated into deterministic models. In a semi-arid Mediterranean grassland system we are attempting to dissect microbial communities into functional guilds with defined physiological traits and are using a range of 'omics approaches to characterize their metabolic potential and niche preference. Initially, two physiologically relevant time points (peak plant activity and prior to wet-up) were sampled and metagenomes sequenced deeply (600-900 Gbp). Following assembly, differential coverage and nucleotide frequency binning were carried out to yield draft genomes. In addition, using a range of cultivation media we have isolated a broad range of bacteria representing abundant bacterial genotypes and with genome sequences of almost 40 isolates are testing genomic predictions regarding growth rate, temperature and substrate utilization in vitro. This presentation will discuss the opportunities and challenges in parameterizing microbial functional guilds from environmental 'omic information for use in trait-based models.

Synthetic microbial ecosystems for biotechnology.

PubMed

Pandhal, Jagroop; Noirel, Josselin

2014-06-01

Most highly controlled and specific applications of microorganisms in biotechnology involve pure cultures. Maintaining single strain cultures is important for industry as contaminants can reduce productivity and lead to longer "down-times" during sterilisation. However, microbes working together provide distinct advantages over pure cultures. They can undertake more metabolically complex tasks, improve efficiency and even expand applications to open systems. By combining rapidly advancing technologies with ecological theory, the use of microbial ecosystems in biotechnology will inevitably increase. This review provides insight into the use of synthetic microbial communities in biotechnology by applying the engineering paradigm of measure, model, manipulate and manufacture, and illustrate the emerging wider potential of the synthetic ecology field. Systems to improve biofuel production using microalgae are also discussed.

A microbial biogeochemistry network for soil carbon and nitrogen cycling and methane flux: model structure and application to Asia

NASA Astrophysics Data System (ADS)

Xu, X.; Song, C.; Wang, Y.; Ricciuto, D. M.; Lipson, D.; Shi, X.; Zona, D.; Song, X.; Yuan, F.; Oechel, W. C.; Thornton, P. E.

2017-12-01

A microbial model is introduced for simulating microbial mechanisms controlling soil carbon and nitrogen biogeochemical cycling and methane fluxes. The model is built within the CN (carbon-nitrogen) framework of Community Land Model 4.5, named as CLM-Microbe to emphasize its explicit representation of microbial mechanisms to biogeochemistry. Based on the CLM4.5, three new pools were added: bacteria, fungi, and dissolved organic matter. It has 11 pools and 34 transitional processes, compared with 8 pools and 9 transitional flow in the CLM4.5. The dissolve organic carbon was linked with a new microbial functional group based methane module to explicitly simulate methane production, oxidation, transport and their microbial controls. Comparing with CLM4.5-CN, the CLM-Microbe model has a number of new features, (1) microbial control on carbon and nitrogen flows between soil carbon/nitrogen pools; (2) an implicit representation of microbial community structure as bacteria and fungi; (3) a microbial functional-group based methane module. The model sensitivity analysis suggests the importance of microbial carbon allocation parameters on soil biogeochemistry and microbial controls on methane dynamics. Preliminary simulations validate the model's capability for simulating carbon and nitrogen dynamics and methane at a number of sites across the globe. The regional application to Asia has verified the model in simulating microbial mechanisms in controlling methane dynamics at multiple scales.

Phototrophic Biofilm Assembly in Microbial-Mat-Derived Unicyanobacterial Consortia: Model Systems for the Study of Autotroph-Heterotroph Interactions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cole, Jessica K.; Hutchison, Janine R.; Renslow, Ryan S.

2014-04-07

Though microbial autotroph-heterotroph interactions influence biogeochemical cycles on a global scale, the diversity and complexity of natural systems and their intractability to in situ environmental manipulation makes elucidation of the principles governing these interactions challenging. Examination of primary succession during phototrophic biofilm assembly provides a robust means by which to elucidate the dynamics of such interactions and determine their influence upon recruitment and maintenance of phylogenetic and functional diversity in microbial communities. We isolated and characterized two unicyanobacterial consortia from the Hot Lake phototrophic mat, quantifying the structural and community composition of their assembling biofilms. The same heterotrophs were retainedmore » in both consortia and included members of Alphaproteobacteria, Gammaproteobacteria, and Bacteroidetes, taxa frequently reported as consorts of microbial photoautotrophs. Cyanobacteria led biofilm assembly, eventually giving way to a late heterotrophic bloom. The consortial biofilms exhibited similar patterns of assembly, with the relative abundances of members of Bacteroidetes and Alphaproteobacteria increasing and members of Gammaproteobacteria decreasing as colonization progressed. Despite similar trends in assembly at higher taxa, the consortia exhibited substantial differences in community structure at the species level. These similar patterns of assembly with divergent community structures suggest that, while similar niches are created by the metabolism of the cyanobacteria, the resultant webs of autotroph-heterotroph and heterotroph-heterotroph interactions driving metabolic exchange are specific to each primary producer. Altogether, our data support these Hot Lake unicyanobacterial consortia as generalizable model systems whose simplicity and tractability permit the deciphering of community assembly principles relevant to natural microbial communities.« less

Representing Microbial Dormancy in Soil Decomposition Models Improves Model Performance and Reveals Key Ecosystem Controls on Microbial Activity

NASA Astrophysics Data System (ADS)

He, Y.; Yang, J.; Zhuang, Q.; Wang, G.; Liu, Y.

2014-12-01

Climate feedbacks from soils can result from environmental change and subsequent responses of plant and microbial communities and nutrient cycling. Explicit consideration of microbial life history traits and strategy may be necessary to predict climate feedbacks due to microbial physiology and community changes and their associated effect on carbon cycling. In this study, we developed an explicit microbial-enzyme decomposition model and examined model performance with and without representation of dormancy at six temperate forest sites with observed soil efflux ranged from 4 to 10 years across different forest types. We then extrapolated the model to all temperate forests in the Northern Hemisphere (25-50°N) to investigate spatial controls on microbial and soil C dynamics. Both models captured the observed soil heterotrophic respiration (RH), yet no-dormancy model consistently exhibited large seasonal amplitude and overestimation in microbial biomass. Spatially, the total RH from temperate forests based on dormancy model amounts to 6.88PgC/yr, and 7.99PgC/yr based on no-dormancy model. However, no-dormancy model notably overestimated the ratio of microbial biomass to SOC. Spatial correlation analysis revealed key controls of soil C:N ratio on the active proportion of microbial biomass, whereas local dormancy is primarily controlled by soil moisture and temperature, indicating scale-dependent environmental and biotic controls on microbial and SOC dynamics. These developments should provide essential support to modeling future soil carbon dynamics and enhance the avenue for collaboration between empirical soil experiment and modeling in the sense that more microbial physiological measurements are needed to better constrain and evaluate the models.

Rejuvenation of Spent Media via Supported Emulsion Liquid Membranes

NASA Technical Reports Server (NTRS)

Wiencek, John M.

2002-01-01

The overall goal of this project was to maximize the reuseability of spent fermentation media. Supported emulsion liquid membrane separation, a highly efficient extraction technique, was used to remove inhibitory byproducts during fermentation; thus, improve the yield while reducing the need for fresh water. The key objectives of this study were: (1) Develop an emulsion liquid membrane system targeting low molecular weight organic acids which has minimal toxicity on a variety of microbial systems. (2) Conduct mass transfer studies to allow proper modeling and design of a supported emulsion liquid membrane system. (3) Investigate the effect of gravity on emulsion coalescence within the membrane unit. (4) Access the effect of water re-use on fermentation yields in a model microbial system. and (5) Develop a perfusion-type fermentor utilizing a supported emulsion liquid membrane system to control inhibitory fermentation byproducts (not completed due to lack of funds)

Carbon dioxide evolution rate as a method to monitor and control an aerobic biological waste treatment system

NASA Technical Reports Server (NTRS)

Lee, S. S.; Shuler, M. L.

1986-01-01

An experimental system was developed to study the microbial growth kinetic of an undefined mixed culture in an erobic biological waste treatment process. The experimental results were used to develop a mathematical model that can predict the performance of a bioreactor. The bioreactor will be used to regeneratively treat waste material which is expected to be generated during a long term manned space mission. Since the presence of insoluble particles in the chemically undefined complex media made estimating biomass very difficult in the real system, a clean system was devised to study the microbial growth from the soluble substrate.

Multilevel selection analysis of a microbial social trait

PubMed Central

de Vargas Roditi, Laura; Boyle, Kerry E; Xavier, Joao B

2013-01-01

The study of microbial communities often leads to arguments for the evolution of cooperation due to group benefits. However, multilevel selection models caution against the uncritical assumption that group benefits will lead to the evolution of cooperation. We analyze a microbial social trait to precisely define the conditions favoring cooperation. We combine the multilevel partition of the Price equation with a laboratory model system: swarming in Pseudomonas aeruginosa. We parameterize a population dynamics model using competition experiments where we manipulate expression, and therefore the cost-to-benefit ratio of swarming cooperation. Our analysis shows that multilevel selection can favor costly swarming cooperation because it causes population expansion. However, due to high costs and diminishing returns constitutive cooperation can only be favored by natural selection when relatedness is high. Regulated expression of cooperative genes is a more robust strategy because it provides the benefits of swarming expansion without the high cost or the diminishing returns. Our analysis supports the key prediction that strong group selection does not necessarily mean that microbial cooperation will always emerge. PMID:23959025

Elucidating the effects of river fluctuation on microbial removal during riverbank filtration

NASA Astrophysics Data System (ADS)

Derx, J.; Sommer, R.; Farnleitner, A. H.; Blaschke, A. P.

2010-12-01

The transfer of microbial pathogens from surface or waste water can have adverse effects on groundwater quality at riverbank filtration sites. Previous studies on groundwater protection in sandy unconfined aquifers with the focus on virus transport and health based water quality targets, such as done in the Netherlands, revealed larger protection zones than zones limited by 60 days of groundwater travel time. The 60 days of travel time are the design criterion in Austria for drinking water protection. However, in gravel aquifers, microbial transport processes differ significantly to those in sandy aquifers. Preferential flow and aquifer heterogeneities dominate microbial transport in sandy gravels and gravel aquifers. Microbial mass transfer and dual domain transport models were used previously to reproduce these effects. Furthermore, microbial transport has mainly been studied in the field during steady state groundwater flow situations. Hence, previous microbial transport models have seldom accounted for transient groundwater flow conditions. These dynamic flow conditions could have immense effects on the fate of microorganisms because of the variations in flow velocities, which are dominating microbial transport. In the current study, we used a variably saturated, three-dimensional groundwater flow and transport model coupled to a hydrodynamic surface water model at a riverbank filtration site. With this model, we estimated the required groundwater protection zones based on 8 log10 viral reductions and compared them to the 60 days travel time zones. The 8 log10 removal steps were based on a preliminary microbial risk assessment scheme for enteroviruses at the riverbank infiltration sites. The groundwater protection zones were estimated for a set of well withdrawal rates, river fluctuation ranges and frequencies, river gradients and bank slopes. The river flow dynamics and the morphology of the riverbed and banks are potentially important factors affecting microbial transport processes during riverbank filtration, which were previously not accounted for. Acknowledgments We would like to thank the Austrian Science Funds FWF for financial support as part of the Doctoral program DK-plus W1219-N22 on Water Resource Systems and the Vienna Waterworks (MA31) as part of the GWRS-Vienna project. We would also like to thank the MA39 (IFUM) for helping at the preliminary risk assessment.

Risk-based cost-benefit analysis for evaluating microbial risk mitigation in a drinking water system.

PubMed

Bergion, Viktor; Lindhe, Andreas; Sokolova, Ekaterina; Rosén, Lars

2018-04-01

Waterborne outbreaks of gastrointestinal diseases can cause large costs to society. Risk management needs to be holistic and transparent in order to reduce these risks in an effective manner. Microbial risk mitigation measures in a drinking water system were investigated using a novel approach combining probabilistic risk assessment and cost-benefit analysis. Lake Vomb in Sweden was used to exemplify and illustrate the risk-based decision model. Four mitigation alternatives were compared, where the first three alternatives, A1-A3, represented connecting 25, 50 and 75%, respectively, of on-site wastewater treatment systems in the catchment to the municipal wastewater treatment plant. The fourth alternative, A4, represented installing a UV-disinfection unit in the drinking water treatment plant. Quantitative microbial risk assessment was used to estimate the positive health effects in terms of quality adjusted life years (QALYs), resulting from the four mitigation alternatives. The health benefits were monetised using a unit cost per QALY. For each mitigation alternative, the net present value of health and environmental benefits and investment, maintenance and running costs was calculated. The results showed that only A4 can reduce the risk (probability of infection) below the World Health Organization guidelines of 10 -4 infections per person per year (looking at the 95th percentile). Furthermore, all alternatives resulted in a negative net present value. However, the net present value would be positive (looking at the 50 th percentile using a 1% discount rate) if non-monetised benefits (e.g. increased property value divided evenly over the studied time horizon and reduced microbial risks posed to animals), estimated at 800-1200 SEK (€100-150) per connected on-site wastewater treatment system per year, were included. This risk-based decision model creates a robust and transparent decision support tool. It is flexible enough to be tailored and applied to local settings of drinking water systems. The model provides a clear and holistic structure for decisions related to microbial risk mitigation. To improve the decision model, we suggest to further develop the valuation and monetisation of health effects and to refine the propagation of uncertainties and variabilities between the included methods. Copyright © 2018 Elsevier Ltd. All rights reserved.

CRISPR-enabled tools for engineering microbial genomes and phenotypes.

PubMed

Tarasava, Katia; Oh, Eun Joong; Eckert, Carrie A; Gill, Ryan T

2018-06-19

In recent years CRISPR-Cas technologies have revolutionized microbial engineering approaches. Genome editing and non-editing applications of various CRISPR-Cas systems have expanded the throughput and scale of engineering efforts, as well as opened up new avenues for manipulating genomes of non-model organisms. As we expand the range of organisms used for biotechnological applications, we need to develop better, more versatile tools for manipulation of these systems. Here we summarize the current advances in microbial gene editing using CRISPR-Cas based tools, and highlight state-of-the-art methods for high-throughput, efficient genome-scale engineering in model organisms Escherichia coli and Saccharomyces cerevisiae. We also review non-editing CRISPR-Cas applications available for gene expression manipulation, epigenetic remodeling, RNA editing, labeling and synthetic gene circuit design. Finally, we point out the areas of research that need further development in order to expand the range of applications and increase the utility of these new methods. This article is protected by copyright. All rights reserved.

Developing Model Benchtop Systems for Microbial Experimental Evolution

NASA Astrophysics Data System (ADS)

Gentry, D.; Wang, J.; Arismendi, D.; Alvarez, J.; Ouandji, C.; Blaich, J.

2017-12-01

Understanding how microbes impact an ecosystem has improved through advances of molecular and genetic tools, but creating complex systems that emulate natural biology goes beyond current technology. In fact, many chemical, biological, and metabolic pathways of even model organisms are still poorly characterized. Even then, standard laboratory techniques for testing microbial impact on environmental change can have many drawbacks; they are time-consuming, labor intensive, and are at risk of contamination. By having an automated process, many of these problems can be reduced or even eliminated. We are developing a benchtop system that can run for long periods of time without the need for human intervention, involve multiple environmental stressors at once, perform real-time adjustments of stressor exposure based on current state of the population, and minimize contamination risks. Our prototype device allows operators to generate an analogue of real world micro-scale ecosystems that can be used to model the effects of disruptive environmental change on microbial ecosystems. It comprises of electronics, mechatronics, and fluidics based systems to control, measure, and evaluate the before and after state of microbial cultures from exposure to environmental stressors. Currently, it uses four parallel growth chambers to perform tests on liquid cultures. To measure the population state, optical sensors (LED/photodiode) are used. Its primary selection pressure is UV-C radiation, a well-studied stressor known for its cell- and DNA- damaging effects and as a mutagen. Future work will involve improving the current growth chambers, as well as implementing additional sensors and environmental stressors into the system. Full integration of multiple culture testing will allow inter-culture comparisons. Besides the temperature and OD sensors, other types of sensors can be integrated such as conductivity, biomass, pH, and dissolved gasses such as CO2 and O2. Additional environmental stressor systems like temperature (extreme heat or cold), metal toxicity, and other forms of radiation will increase the scale and testing range.

Developing Model Benchtop Systems for Microbial Experimental Evolution

NASA Technical Reports Server (NTRS)

Wang, Jonathan; Arismendi, Dillon; Alvarez, Jennifer; Ouandji, Cynthia; Blaich, Justin; Gentry, Diana

2017-01-01

Understanding how microbes impact an ecosystem has improved through advances of molecular and genetic tools, but creating complex systems that emulate natural biology goes beyond current technology. In fact, many chemical, biological, and metabolic pathways of even model organisms are still poorly characterized. Even then, standard laboratory techniques for testing microbial impact on environmental change can have many drawbacks; they are time-consuming, labor intensive, and are at risk of contamination. By having an automated process, many of these problems can be reduced or even eliminated. We are developing a benchtop system that can run for long periods of time without the need for human intervention, involve multiple environmental stressors at once, perform real-time adjustments of stressor exposure based on current state of the population, and minimize contamination risks. Our prototype device allows operators to generate an analogue of real world micro-scale ecosystems that can be used to model the effects of disruptive environmental change on microbial ecosystems. It comprises of electronics, mechatronics, and fluidics based systems to control, measure, and evaluate the before and after state of microbial cultures from exposure to environmental stressors. Currently, it uses four parallel growth chambers to perform tests on liquid cultures. To measure the population state, optical sensors (LED/photodiode) are used. Its primary selection pressure is UV-C radiation, a well-studied stressor known for its cell- and DNA-damaging effects and as a mutagen. Future work will involve improving the current growth chambers, as well as implementing additional sensors and environmental stressors into the system. Full integration of multiple culture testing will allow inter-culture comparisons. Besides the temperature and OD sensors, other types of sensors can be integrated such as conductivity, biomass, pH, and dissolved gasses such as CO and O. Additional environmental stressor systems like temperature (extreme heat or cold), metal toxicity, and other forms of radiation will increase the scale and testing range.

The implications of microbial and substrate limitation for the fates of carbon in different organic soil horizon types of boreal forest ecosystems: a mechanistically based model analysis

USGS Publications Warehouse

He, Y.; Zhuang, Q.; Harden, Jennifer W.; McGuire, A. David; Fan, Z.; Liu, Y.; Wickland, Kimberly P.

2014-01-01

The large amount of soil carbon in boreal forest ecosystems has the potential to influence the climate system if released in large quantities in response to warming. Thus, there is a need to better understand and represent the environmental sensitivity of soil carbon decomposition. Most soil carbon decomposition models rely on empirical relationships omitting key biogeochemical mechanisms and their response to climate change is highly uncertain. In this study, we developed a multi-layer microbial explicit soil decomposition model framework for boreal forest ecosystems. A thorough sensitivity analysis was conducted to identify dominating biogeochemical processes and to highlight structural limitations. Our results indicate that substrate availability (limited by soil water diffusion and substrate quality) is likely to be a major constraint on soil decomposition in the fibrous horizon (40–60% of soil organic carbon (SOC) pool size variation), while energy limited microbial activity in the amorphous horizon exerts a predominant control on soil decomposition (>70% of SOC pool size variation). Elevated temperature alleviated the energy constraint of microbial activity most notably in amorphous soils, whereas moisture only exhibited a marginal effect on dissolved substrate supply and microbial activity. Our study highlights the different decomposition properties and underlying mechanisms of soil dynamics between fibrous and amorphous soil horizons. Soil decomposition models should consider explicitly representing different boreal soil horizons and soil–microbial interactions to better characterize biogeochemical processes in boreal forest ecosystems. A more comprehensive representation of critical biogeochemical mechanisms of soil moisture effects may be required to improve the performance of the soil model we analyzed in this study.

Predictive microbiology in a dynamic environment: a system theory approach.

PubMed

Van Impe, J F; Nicolaï, B M; Schellekens, M; Martens, T; De Baerdemaeker, J

1995-05-01

The main factors influencing the microbial stability of chilled prepared food products for which there is an increased consumer interest-are temperature, pH, and water activity. Unlike the pH and the water activity, the temperature may vary extensively throughout the complete production and distribution chain. The shelf life of this kind of foods is usually limited due to spoilage by common microorganisms, and the increased risk for food pathogens. In predicting the shelf life, mathematical models are a powerful tool to increase the insight in the different subprocesses and their interactions. However, the predictive value of the sigmoidal functions reported in the literature to describe a bacterial growth curve as an explicit function of time is only guaranteed at a constant temperature within the temperature range of microbial growth. As a result, they are less appropriate in optimization studies of a whole production and distribution chain. In this paper a more general modeling approach, inspired by system theory concepts, is presented if for instance time varying temperature profiles are to be taken into account. As a case study, we discuss a recently proposed dynamic model to predict microbial growth and inactivation under time varying temperature conditions from a system theory point of view. Further, the validity of this methodology is illustrated with experimental data of Brochothrix thermosphacta and Lactobacillus plantarum. Finally, we propose some possible refinements of this model inspired by experimental results.

Investigating the initial stages of soil formation in glacier forefields using the new biogeochemical model: SHIMMER

NASA Astrophysics Data System (ADS)

Bradley, James; Anesio, Alexandre; Arndt, Sandra; Sabacka, Marie; Barker, Gary; Benning, Liane; Blacker, Joshua; Singarayer, Joy; Tranter, Martyn; Yallop, Marian

2016-04-01

Glaciers and ice sheets in Polar and alpine regions are retreating in response to recent climate warming, exposing terrestrial ecosystems that have been locked under the ice for thousands of years. Exposed soils exhibit successional characteristics that can be characterised using a chronosequence approach. Decades of empirical research in glacier forefields has shown that soils are quickly colonised by microbes which drive biogeochemical cycling of elements and affect soil properties including nutrient concentrations, carbon fluxes and soil stability (Bradley et al, 2014). The characterisation of these soils is important for our understanding of the cycling of organic matter under extreme environmental and nutrient limiting conditions, and their potential contribution to global biogeochemical cycles. This is particularly important as these new areas will become more geographically expansive with continued ice retreat. SHIMMER (Soil biogeocHemIcal Model of Microbial Ecosystem Response) (Bradley et al, 2015) is a new mathematical model that simulates biogeochemical and microbial dynamics in glacier forefields. The model captures, explores and predicts the growth of different microbial groups (classified by function), and the associated cycling of carbon, nitrogen and phosphorus along a chronosequence. SHIMMER improves typical soil model formulations by including explicit representation of microbial dynamics, and those processes which are shown to be important for glacier forefields. For example, we categorise microbial groups by function to represent the diversity of soil microbial communities, and include the different metabolic needs and physiological pathways of microbial organisms commonly found in glacier forefields (e.g. microbes derived from underneath the glacier, typical soil bacteria, and microbes that can fix atmospheric nitrogen and assimilate soil nitrogen). Here, we present data from a study where we integrated modelling using SHIMMER with empirical observations from chronosequences from the forefield of Midtre Lovénbreen, Svalbard (78°N), to investigate the first 120 years of soil development. We carried out an in depth analysis of the model dynamics and determined the most sensitive parameters. We then used laboratory measurements to derive values for those parameters: bacterial growth rate, growth efficiency and temperature dependency. By applying the model to the High-Arctic forefield and integrating the measured parameter values, we could refine the model and easily predict the rapid accumulation of microbial biomass that was observed in our field data. Furthermore, we show that the bacterial production is dominated by autotrophy (rather than heterotrophy). Heterotrophic production in young soils (0-20 years) is supported by labile substrate, whereas carbon stocks in older soils (60-120 years) are more refractory. Nitrogen fixing organisms are responsible for the initial accumulation of available nitrates in the soil. However, microbial processes alone do not explain the build-up of organic matter observed in the field data record. Consequently, the model infers that allochthonous deposition of organic material may play a significant contributory role that could accelerate or facilitate further microbial growth. SHIMMER provides a quantitative evaluation on the dynamics of glacier forefield systems that have previously largely been explored through qualitative interpretation of datasets. References Bradley J.A., Singarayer J.S., Anesio A.M. (2014) Microbial community dynamics in the forefield of glaciers. Proceedings Biological sciences / The Royal Society 281(1795), 2793-2802. (doi:10.1098/rspb.2014.0882). Bradley J.A., Anesio A.M., Singarayer J.S., Heath M.R., Arndt S. (2015) SHIMMER (1.0): a novel mathematical model for microbial and biogeochemical dynamics in glacier forefield ecosystems. Geosci Model Dev 8(10), 3441-3470. (doi:10.5194/gmd-8-3441-2015).

Self-sustained reduction of multiple metals in a microbial fuel cell-microbial electrolysis cell hybrid system.

PubMed

Li, Yan; Wu, Yining; Liu, Bingchuan; Luan, Hongwei; Vadas, Timothy; Guo, Wanqian; Ding, Jie; Li, Baikun

2015-09-01

A self-sustained hybrid bioelectrochemical system consisting of microbial fuel cell (MFC) and microbial electrolysis cell (MEC) was developed to reduce multiple metals simultaneously by utilizing different reaction potentials. Three heavy metals representing spontaneous reaction (chromium, Cr) and unspontaneous reaction (lead, Pb and nickel, Ni) were selected in this batch-mode study. The maximum power density of the MFC achieved 189.4 mW m(-2), and the energy recovery relative to the energy storage circuit (ESC) was ∼ 450%. At the initial concentration of 100 mg L(-1), the average reduction rate of Cr(VI) was 30.0 mg L(-1) d(-1), Pb(II) 32.7 mg L(-1) d(-1), and Ni(II) 8.9 mg L(-1) d(-1). An electrochemical model was developed to predict the change of metal concentration over time. The power output of the MFC was sufficient to meet the requirement of the ESC and MEC, and the "self-sustained metal reduction" was achieved in this hybrid system. Published by Elsevier Ltd.

Effect of red blood cells on the growth of Porphyromonas endodontalis and microbial community development.

PubMed

Zerr, M A; Cox, C D; Johnson, W T; Drake, D R

1998-04-01

Establishment of a microbial community in the root canal system depends on numerous factors, of which nutrient availability may be one of the most important. We hypothesized that the presence of red blood cells or hemoglobin in this environment could cause shifts in microbial composition of communities, resulting in organisms such as Porphyromonas endodontalis becoming more dominant. An in vitro model system using mixed, batch cultures was performed with the bacteria P. endodontalis, Fusobacterium nucleatum, Peptostreptococcus micros and Campylobacter rectus. Bacteria were cultured in media with or without the addition of washed red blood cells, hemoglobin, or serum. Cyclic growth studies revealed that P. endodontalis was lost from the community of organisms after three cycles. However, inclusion of red blood cells resulted in establishment of this organism. Moreover, red blood cells added to pure cultures of P. endodontalis substantially enhanced growth and protected the organisms from oxygen. We conclude that the presence of red blood cells could result in shifts of microbial communities of organisms within the root canal system.

Multi-variable mathematical models for the air-cathode microbial fuel cell system

DOE PAGES

Ou, Shiqi; Kashima, Hiroyuki; Aaron, Douglas S.; ...

2016-03-10

This research adopted the version control system into the model construction for the single chamber air-cathode microbial fuel cell (MFC) system, to understand the interrelation of biological, chemical, and electrochemical reactions. The anodic steady state model was used to consider the chemical species diffusion and electric migration influence to the MFC performance. In the cathodic steady state model, the mass transport and reactions in a multi-layer, abiotic cathode and multi-bacteria cathode biofilm were simulated. Transport of hydroxide was assumed for cathodic pH change. This assumption is an alternative to the typical notion of proton consumption during oxygen reduction to explainmore » elevated cathode pH. The cathodic steady state model provided the power density and polarization curve performance results that can be compared to an experimental MFC system. Another aspect we considered was the relative contributions of platinum catalyst and microbes on the cathode to the oxygen reduction reaction (ORR). We found simulation results showed that the biocatalyst in a cathode that includes a Pt/C catalyst likely plays a minor role in ORR, contributing up to 8% of the total power calculated by the models.« less

Bioprocess scale-up/down as integrative enabling technology: from fluid mechanics to systems biology and beyond.

PubMed

Delvigne, Frank; Takors, Ralf; Mudde, Rob; van Gulik, Walter; Noorman, Henk

2017-09-01

Efficient optimization of microbial processes is a critical issue for achieving a number of sustainable development goals, considering the impact of microbial biotechnology in agrofood, environment, biopharmaceutical and chemical industries. Many of these applications require scale-up after proof of concept. However, the behaviour of microbial systems remains unpredictable (at least partially) when shifting from laboratory-scale to industrial conditions. The need for robust microbial systems is thus highly needed in this context, as well as a better understanding of the interactions between fluid mechanics and cell physiology. For that purpose, a full scale-up/down computational framework is already available. This framework links computational fluid dynamics (CFD), metabolic flux analysis and agent-based modelling (ABM) for a better understanding of the cell lifelines in a heterogeneous environment. Ultimately, this framework can be used for the design of scale-down simulators and/or metabolically engineered cells able to cope with environmental fluctuations typically found in large-scale bioreactors. However, this framework still needs some refinements, such as a better integration of gas-liquid flows in CFD, and taking into account intrinsic biological noise in ABM. © 2017 The Authors. Microbial Biotechnology published by John Wiley & Sons Ltd and Society for Applied Microbiology.

Contaminant concentration versus flow velocity: drivers of biodegradation and microbial growth in groundwater model systems.

PubMed

Grösbacher, Michael; Eckert, Dominik; Cirpka, Olaf A; Griebler, Christian

2018-06-01

Aromatic hydrocarbons belong to the most abundant contaminants in groundwater systems. They can serve as carbon and energy source for a multitude of indigenous microorganisms. Predictions of contaminant biodegradation and microbial growth in contaminated aquifers are often vague because the parameters of microbial activity in the mathematical models used for predictions are typically derived from batch experiments, which don't represent conditions in the field. In order to improve our understanding of key drivers of natural attenuation and the accuracy of predictive models, we conducted comparative experiments in batch and sediment flow-through systems with varying concentrations of contaminant in the inflow and flow velocities applying the aerobic Pseudomonas putida strain F1 and the denitrifying Aromatoleum aromaticum strain EbN1. We followed toluene degradation and bacterial growth by measuring toluene and oxygen concentrations and by direct cell counts. In the sediment columns, the total amount of toluene degraded by P. putida F1 increased with increasing source concentration and flow velocity, while toluene removal efficiency gradually decreased. Results point at mass transfer limitation being an important process controlling toluene biodegradation that cannot be assessed with batch experiments. We also observed a decrease in the maximum specific growth rate with increasing source concentration and flow velocity. At low toluene concentrations, the efficiencies in carbon assimilation within the flow-through systems exceeded those in the batch systems. In all column experiments the number of attached cells plateaued after an initial growth phase indicating a specific "carrying capacity" depending on contaminant concentration and flow velocity. Moreover, in all cases, cells attached to the sediment dominated over those in suspension, and toluene degradation was performed practically by attached cells only. The observed effects of varying contaminant inflow concentration and flow velocity on biodegradation could be captured by a reactive-transport model. By monitoring both attached and suspended cells we could quantify the release of new-grown cells from the sediments to the mobile aqueous phase. Studying flow velocity and contaminant concentrations as key drivers of contaminant transformation in sediment flow-through microcosms improves our system understanding and eventually the prediction of microbial biodegradation at contaminated sites.

Using data to inform soil microbial carbon model structure and parameters

NASA Astrophysics Data System (ADS)

Hagerty, S. B.; Schimel, J.

2016-12-01

There is increasing consensus that explicitly representing microbial mechanisms in soil carbon models can improve model predictions of future soil carbon stocks. However, which microbial mechanisms must be represented in these new models and how remains under debate. One of the major challenges in developing microbially explicit soil carbon models is that there is little data available to validate model structure. Empirical studies of microbial mechanisms often fail to capture the full range of microbial processes; from the cellular processes that occur within minutes to hours of substrate consumption to community turnover which may occur over weeks or longer. We added isotopically labeled 14C-glucose to soil incubated in the lab and traced its movement into the microbial biomass, carbon dioxide, and K2SO4 extractable carbon pool. We measured the concentration of 14C in each of these pools at 1, 3, 6, 24, and 72 hours and at 7, 14, and 21 days. We used this data to compare data fits among models that match our conceptual understanding of microbial carbon transformations and to estimate microbial parameters that control the fate of soil carbon. Over 90% of the added glucose was consumed within the first hour after it was added and concentration of the label was highest in biomass at this time. After the first hour, the label in biomass declined, with the rate that the label moved from the biomass slowing after 24hours, because of this models representing the microbial biomass as two pools fit best. Recovery of the label decreased with incubation time, from nearly 80% in the first hour to 67% after three weeks, indicating that carbon is moving into unextractable pools in the soil likely as microbial products and necromass sorb to soil particles and that these mechanisms must be represented in microbial models. This data fitting exercise demonstrates how isotopic data can be useful in validating model structure and estimating microbial model parameters. Future studies can apply this inverse modeling approach to compare the response of microbial parameters to changes in environmental conditions.

Marine Protists Are Not Just Big Bacteria.

PubMed

Keeling, Patrick J; Campo, Javier Del

2017-06-05

The study of marine microbial ecology has been completely transformed by molecular and genomic data: after centuries of relative neglect, genomics has revealed the surprising extent of microbial diversity and how microbial processes transform ocean and global ecosystems. But the revolution is not complete: major gaps in our understanding remain, and one obvious example is that microbial eukaryotes, or protists, are still largely neglected. Here we examine various ways in which protists might be better integrated into models of marine microbial ecology, what challenges this will present, and why understanding the limitations of our tools is a significant concern. In part this is a technical challenge - eukaryotic genomes are more difficult to characterize - but eukaryotic adaptations are also more dependent on morphology and behaviour than they are on the metabolic diversity that typifies bacteria, and these cannot be inferred from genomic data as readily as metabolism can be. We therefore cannot simply follow in the methodological footsteps of bacterial ecology and hope for similar success. Understanding microbial eukaryotes will require different approaches, including greater emphasis on taxonomically and trophically diverse model systems. Molecular sequencing will continue to play a role, and advances in environmental sequence tag studies and single-cell methods for genomic and transcriptomics offer particular promise. Copyright © 2017 Elsevier Ltd. All rights reserved.

Integrating plant-microbe interactions to understand soil C stabilization with the MIcrobial-MIneral Carbon Stabilization model (MIMICS)

NASA Astrophysics Data System (ADS)

Grandy, Stuart; Wieder, Will; Kallenbach, Cynthia; Tiemann, Lisa

2014-05-01

If soil organic matter is predominantly microbial biomass, plant inputs that build biomass should also increase SOM. This seems obvious, but the implications fundamentally change how we think about the relationships between plants, microbes and SOM. Plant residues that build microbial biomass are typically characterized by low C/N ratios and high lignin contents. However, plants with high lignin contents and high C/N ratios are believed to increase SOM, an entrenched idea that still strongly motivates agricultural soil management practices. Here we use a combination of meta-analysis with a new microbial-explicit soil biogeochemistry model to explore the relationships between plant litter chemistry, microbial communities, and SOM stabilization in different soil types. We use the MIcrobial-MIneral Carbon Stabilization (MIMICS) model, newly built upon the Community Land Model (CLM) platform, to enhance our understanding of biology in earth system processes. The turnover of litter and SOM in MIMICS are governed by the activity of r- and k-selected microbial groups and temperature sensitive Michaelis-Menten kinetics. Plant and microbial residues are stabilized short-term by chemical recalcitrance or long-term by physical protection. Fast-turnover litter inputs increase SOM by >10% depending on temperature in clay soils, and it's only in sandy soils devoid of physical protection mechanisms that recalcitrant inputs build SOM. These results challenge centuries of lay knowledge as well as conventional ideas of SOM formation, but are they realistic? To test this, we conducted a meta-analysis of the relationships between the chemistry of plant liter inputs and SOM concentrations. We find globally that the highest SOM concentrations are associated with plant inputs containing low C/N ratios. These results are confirmed by individual tracer studies pointing to greater stabilization of low C/N ratio inputs, particularly in clay soils. Our model and meta-analysis results suggest that current ideas about plant-microbe-SOM relationships are unraveling. If so, our reconsideration of the mechanisms stabilizing SOM will also challenge long-held views about how to optimize plant community management to increase SOM.

Genome-driven evolutionary game theory helps understand the rise of metabolic interdependencies in microbial communities.

PubMed

Zomorrodi, Ali R; Segrè, Daniel

2017-11-16

Metabolite exchanges in microbial communities give rise to ecological interactions that govern ecosystem diversity and stability. It is unclear, however, how the rise of these interactions varies across metabolites and organisms. Here we address this question by integrating genome-scale models of metabolism with evolutionary game theory. Specifically, we use microbial fitness values estimated by metabolic models to infer evolutionarily stable interactions in multi-species microbial "games". We first validate our approach using a well-characterized yeast cheater-cooperator system. We next perform over 80,000 in silico experiments to infer how metabolic interdependencies mediated by amino acid leakage in Escherichia coli vary across 189 amino acid pairs. While most pairs display shared patterns of inter-species interactions, multiple deviations are caused by pleiotropy and epistasis in metabolism. Furthermore, simulated invasion experiments reveal possible paths to obligate cross-feeding. Our study provides genomically driven insight into the rise of ecological interactions, with implications for microbiome research and synthetic ecology.

Microbial Adhesion and Biofilm Formation on Microfiltration Membranes: A Detailed Characterization Using Model Organisms with Increasing Complexity

PubMed Central

Vanysacker, L.; Denis, C.; Declerck, P.; Piasecka, A.; Vankelecom, I. F. J.

2013-01-01

Since many years, membrane biofouling has been described as the Achilles heel of membrane fouling. In the present study, an ecological assay was performed using model systems with increasing complexity: a monospecies assay using Pseudomonas aeruginosa or Escherichia coli separately, a duospecies assay using both microorganisms, and a multispecies assay using activated sludge with or without spiked P. aeruginosa. The microbial adhesion and biofilm formation were evaluated in terms of bacterial cell densities, species richness, and bacterial community composition on polyvinyldifluoride, polyethylene, and polysulfone membranes. The data show that biofouling formation was strongly influenced by the kind of microorganism, the interactions between the organisms, and the changes in environmental conditions whereas the membrane effect was less important. The findings obtained in this study suggest that more knowledge in species composition and microbial interactions is needed in order to understand the complex biofouling process. This is the first report describing the microbial interactions with a membrane during the biofouling development. PMID:23986906

Prokaryotic communities differ along a geothermal soil photic gradient.

PubMed

Meadow, James F; Zabinski, Catherine A

2013-01-01

Geothermal influenced soils exert unique physical and chemical limitations on resident microbial communities but have received little attention in microbial ecology research. These environments offer a model system in which to investigate microbial community heterogeneity and a range of soil ecological concepts. We conducted a 16S bar-coded pyrosequencing survey of the prokaryotic communities in a diatomaceous geothermal soil system and compared communities across soil types and along a conspicuous photic depth gradient. We found significant differences between the communities of the two different soils and also predictable differences between samples taken at different depths. Additionally, we targeted three ecologically relevant bacterial phyla, Cyanobacteria, Planctomycetes, and Verrucomicrobia, for clade-wise comparisons with these variables and found strong differences in their abundances, consistent with the autecology of these groups.

Using an Integrated, Multi-disciplinary Framework to Support Quantitative Microbial Risk Assessments

EPA Science Inventory

The Framework for Risk Analysis in Multimedia Environmental Systems (FRAMES) provides the infrastructure to link disparate models and databases seamlessly, giving an assessor the ability to construct an appropriate conceptual site model from a host of modeling choices, so a numbe...

Differential Microbial Diversity in Drosophila melanogaster: Are Fruit Flies Potential Vectors of Opportunistic Pathogens?

PubMed Central

Maldonado-Morales, Génesis; Bayman, Paul

2017-01-01

Drosophila melanogaster has become a model system to study interactions between innate immunity and microbial pathogens, yet many aspects regarding its microbial community and interactions with pathogens remain unclear. In this study wild D. melanogaster were collected from tropical fruits in Puerto Rico to test how the microbiota is distributed and to compare the culturable diversity of fungi and bacteria. Additionally, we investigated whether flies are potential vectors of human and plant pathogens. Eighteen species of fungi and twelve species of bacteria were isolated from wild flies. The most abundant microorganisms identified were the yeast Candida inconspicua and the bacterium Klebsiella sp. The yeast Issatchenkia hanoiensis was significantly more common internally than externally in flies. Species richness was higher in fungi than in bacteria, but diversity was lower in fungi than in bacteria. The microbial composition of flies was similar internally and externally. We identified a variety of opportunistic human and plant pathogens in flies such as Alcaligenes faecalis, Aspergillus flavus, A. fumigatus, A. niger, Fusarium equiseti/oxysporum, Geotrichum candidum, Klebsiella oxytoca, Microbacterium oxydans, and Stenotrophomonas maltophilia. Despite its utility as a model system, D. melanogaster can be a vector of microorganisms that represent a potential risk to plant and public health. PMID:29234354

Microbially Mediated Kinetic Sulfur Isotope Fractionation: Reactive Transport Modeling Benchmark

NASA Astrophysics Data System (ADS)

Wanner, C.; Druhan, J. L.; Cheng, Y.; Amos, R. T.; Steefel, C. I.; Ajo Franklin, J. B.

2014-12-01

Microbially mediated sulfate reduction is a ubiquitous process in many subsurface systems. Isotopic fractionation is characteristic of this anaerobic process, since sulfate reducing bacteria (SRB) favor the reduction of the lighter sulfate isotopologue (S32O42-) over the heavier isotopologue (S34O42-). Detection of isotopic shifts have been utilized as a proxy for the onset of sulfate reduction in subsurface systems such as oil reservoirs and aquifers undergoing uranium bioremediation. Reactive transport modeling (RTM) of kinetic sulfur isotope fractionation has been applied to field and laboratory studies. These RTM approaches employ different mathematical formulations in the representation of kinetic sulfur isotope fractionation. In order to test the various formulations, we propose a benchmark problem set for the simulation of kinetic sulfur isotope fractionation during microbially mediated sulfate reduction. The benchmark problem set is comprised of four problem levels and is based on a recent laboratory column experimental study of sulfur isotope fractionation. Pertinent processes impacting sulfur isotopic composition such as microbial sulfate reduction and dispersion are included in the problem set. To date, participating RTM codes are: CRUNCHTOPE, TOUGHREACT, MIN3P and THE GEOCHEMIST'S WORKBENCH. Preliminary results from various codes show reasonable agreement for the problem levels simulating sulfur isotope fractionation in 1D.

Incorporating microbial dormancy dynamics into soil decomposition models to improve quantification of soil carbon dynamics of northern temperate forests

NASA Astrophysics Data System (ADS)

He, Yujie; Yang, Jinyan; Zhuang, Qianlai; Harden, Jennifer W.; McGuire, Anthony D.; Liu, Yaling; Wang, Gangsheng; Gu, Lianhong

2015-12-01

Soil carbon dynamics of terrestrial ecosystems play a significant role in the global carbon cycle. Microbial-based decomposition models have seen much growth recently for quantifying this role, yet dormancy as a common strategy used by microorganisms has not usually been represented and tested in these models against field observations. Here we developed an explicit microbial-enzyme decomposition model and examined model performance with and without representation of microbial dormancy at six temperate forest sites of different forest types. We then extrapolated the model to global temperate forest ecosystems to investigate biogeochemical controls on soil heterotrophic respiration and microbial dormancy dynamics at different temporal-spatial scales. The dormancy model consistently produced better match with field-observed heterotrophic soil CO2 efflux (RH) than the no dormancy model. Our regional modeling results further indicated that models with dormancy were able to produce more realistic magnitude of microbial biomass (<2% of soil organic carbon) and soil RH (7.5 ± 2.4 Pg C yr-1). Spatial correlation analysis showed that soil organic carbon content was the dominating factor (correlation coefficient = 0.4-0.6) in the simulated spatial pattern of soil RH with both models. In contrast to strong temporal and local controls of soil temperature and moisture on microbial dormancy, our modeling results showed that soil carbon-to-nitrogen ratio (C:N) was a major regulating factor at regional scales (correlation coefficient = -0.43 to -0.58), indicating scale-dependent biogeochemical controls on microbial dynamics. Our findings suggest that incorporating microbial dormancy could improve the realism of microbial-based decomposition models and enhance the integration of soil experiments and mechanistically based modeling.

Incorporating microbial dormancy dynamics into soil decomposition models to improve quantification of soil carbon dynamics of northern temperate forests

USGS Publications Warehouse

He, Yujie; Yang, Jinyan; Zhuang, Qianlai; Harden, Jennifer W.; McGuire, A. David; Liu, Yaling; Wang, Gangsheng; Gu, Lianhong

2015-01-01

Soil carbon dynamics of terrestrial ecosystems play a significant role in the global carbon cycle. Microbial-based decomposition models have seen much growth recently for quantifying this role, yet dormancy as a common strategy used by microorganisms has not usually been represented and tested in these models against field observations. Here we developed an explicit microbial-enzyme decomposition model and examined model performance with and without representation of microbial dormancy at six temperate forest sites of different forest types. We then extrapolated the model to global temperate forest ecosystems to investigate biogeochemical controls on soil heterotrophic respiration and microbial dormancy dynamics at different temporal-spatial scales. The dormancy model consistently produced better match with field-observed heterotrophic soil CO2 efflux (RH) than the no dormancy model. Our regional modeling results further indicated that models with dormancy were able to produce more realistic magnitude of microbial biomass (<2% of soil organic carbon) and soil RH (7.5 ± 2.4 Pg C yr−1). Spatial correlation analysis showed that soil organic carbon content was the dominating factor (correlation coefficient = 0.4–0.6) in the simulated spatial pattern of soil RHwith both models. In contrast to strong temporal and local controls of soil temperature and moisture on microbial dormancy, our modeling results showed that soil carbon-to-nitrogen ratio (C:N) was a major regulating factor at regional scales (correlation coefficient = −0.43 to −0.58), indicating scale-dependent biogeochemical controls on microbial dynamics. Our findings suggest that incorporating microbial dormancy could improve the realism of microbial-based decomposition models and enhance the integration of soil experiments and mechanistically based modeling.

A simple microbial fuel cell model for improvement of biomedical device powering times.

PubMed

Roxby, Daniel N; Tran, Nham; Nguyen, Hung T

2014-01-01

This study describes a Matlab based Microbial Fuel Cell (MFC) model for a suspended microbial population, in the anode chamber for the use of the MFC in powering biomedical devices. The model contains three main sections including microbial growth, microbial chemical uptake and secretion and electrochemical modeling. The microbial growth portion is based on a Continuously Stirred Tank Reactor (CSTR) model for the microbial growth with substrate and electron acceptors. Microbial stoichiometry is used to determine chemical concentrations and their rates of change and transfer within the MFC. These parameters are then used in the electrochemical modeling for calculating current, voltage and power. The model was tested for typically exhibited MFC characteristics including increased electrode distances and surface areas, overpotentials and operating temperatures. Implantable biomedical devices require long term powering which is the main objective for MFCs. Towards this end, our model was tested with different initial substrate and electron acceptor concentrations, revealing a four-fold increase in concentrations decreased the power output time by 50%. Additionally, the model also predicts that for a 35.7% decrease in specific growth rate, a 50% increase in power longevity is possible.

INNOVATIVE MIOR PROCESS UTILIZING INDIGENOUS RESERVOIR CONSTITUENTS

DOE Office of Scientific and Technical Information (OSTI.GOV)

D.O. Hitzman; A.K. Stepp; D.M. Dennis

This research program was directed at improving the knowledge of reservoir ecology and developing practical microbial solutions and technologies for improving oil production. The goal was to identify and utilize indigenous microbial populations which can produce beneficial metabolic products and develop a methodology to stimulate those select microbes with nutrient amendments to increase oil recovery. This microbial technology has the capability of producing multiple oil-releasing agents. Experimental laboratory work in model sandpack cores was conducted using microbial cultures isolated from produced water samples. Comparative laboratory studies demonstrating in situ production of microbial products as oil recovery agents were conducted inmore » sand packs with natural field waters using cultures and conditions representative of oil reservoirs. Increased oil recovery in multiple model sandpack systems was achieved and the technology and results were verified by successful field studies. Direct application of the research results has lead to the development of a feasible, practical, successful, and cost-effective technology which increases oil recovery. This technology is now being commercialized and applied in numerous field projects to increase oil recovery. Two field applications of the developed technology reported production increases of 21% and 24% in oil recovery.« less

Microbial models with data-driven parameters predict stronger soil carbon responses to climate change.

PubMed

Hararuk, Oleksandra; Smith, Matthew J; Luo, Yiqi

2015-06-01

Long-term carbon (C) cycle feedbacks to climate depend on the future dynamics of soil organic carbon (SOC). Current models show low predictive accuracy at simulating contemporary SOC pools, which can be improved through parameter estimation. However, major uncertainty remains in global soil responses to climate change, particularly uncertainty in how the activity of soil microbial communities will respond. To date, the role of microbes in SOC dynamics has been implicitly described by decay rate constants in most conventional global carbon cycle models. Explicitly including microbial biomass dynamics into C cycle model formulations has shown potential to improve model predictive performance when assessed against global SOC databases. This study aimed to data-constrained parameters of two soil microbial models, evaluate the improvements in performance of those calibrated models in predicting contemporary carbon stocks, and compare the SOC responses to climate change and their uncertainties between microbial and conventional models. Microbial models with calibrated parameters explained 51% of variability in the observed total SOC, whereas a calibrated conventional model explained 41%. The microbial models, when forced with climate and soil carbon input predictions from the 5th Coupled Model Intercomparison Project (CMIP5), produced stronger soil C responses to 95 years of climate change than any of the 11 CMIP5 models. The calibrated microbial models predicted between 8% (2-pool model) and 11% (4-pool model) soil C losses compared with CMIP5 model projections which ranged from a 7% loss to a 22.6% gain. Lastly, we observed unrealistic oscillatory SOC dynamics in the 2-pool microbial model. The 4-pool model also produced oscillations, but they were less prominent and could be avoided, depending on the parameter values. © 2014 John Wiley & Sons Ltd.

The Genome-Based Metabolic Systems Engineering to Boost Levan Production in a Halophilic Bacterial Model.

PubMed

Aydin, Busra; Ozer, Tugba; Oner, Ebru Toksoy; Arga, Kazim Yalcin

2018-03-01

Metabolic systems engineering is being used to redirect microbial metabolism for the overproduction of chemicals of interest with the aim of transforming microbial hosts into cellular factories. In this study, a genome-based metabolic systems engineering approach was designed and performed to improve biopolymer biosynthesis capability of a moderately halophilic bacterium Halomonas smyrnensis AAD6 T producing levan, which is a fructose homopolymer with many potential uses in various industries and medicine. For this purpose, the genome-scale metabolic model for AAD6 T was used to characterize the metabolic resource allocation, specifically to design metabolic engineering strategies for engineered bacteria with enhanced levan production capability. Simulations were performed in silico to determine optimal gene knockout strategies to develop new strains with enhanced levan production capability. The majority of the gene knockout strategies emphasized the vital role of the fructose uptake mechanism, and pointed out the fructose-specific phosphotransferase system (PTS fru ) as the most promising target for further metabolic engineering studies. Therefore, the PTS fru of AAD6 T was restructured with insertional mutagenesis and triparental mating techniques to construct a novel, engineered H. smyrnensis strain, BMA14. Fermentation experiments were carried out to demonstrate the high efficiency of the mutant strain BMA14 in terms of final levan concentration, sucrose consumption rate, and sucrose conversion efficiency, when compared to the AAD6 T . The genome-based metabolic systems engineering approach presented in this study might be considered an efficient framework to redirect microbial metabolism for the overproduction of chemicals of interest, and the novel strain BMA14 might be considered a potential microbial cell factory for further studies aimed to design levan production processes with lower production costs.

Activity-Based Protein Profiling of Microbes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sadler, Natalie C.; Wright, Aaron T.

Activity-Based Protein Profiling (ABPP) in conjunction with multimodal characterization techniques has yielded impactful findings in microbiology, particularly in pathogen, bioenergy, drug discovery, and environmental research. Using small molecule chemical probes that react irreversibly with specific proteins or protein families in complex systems has provided insights in enzyme functions in central metabolic pathways, drug-protein interactions, and regulatory protein redox, for systems ranging from photoautotrophic cyanobacteria to mycobacteria, and combining live cell or cell extract ABPP with proteomics, molecular biology, modeling, and other techniques has greatly expanded our understanding of these systems. New opportunities for application of ABPP to microbial systems include:more » enhancing protein annotation, characterizing protein activities in myriad environments, and reveal signal transduction and regulatory mechanisms in microbial systems.« less

Microbial Priming and Protected Carbon Responses to Elevated CO2 at Local to Global Scales: a New Modeling Approach

NASA Astrophysics Data System (ADS)

Sulman, B. N.; Oishi, C.; Shevliakova, E.; Pacala, S. W.

2013-12-01

The soil carbon formulations commonly used in global carbon cycle models and Earth System models (ESMs) are based on first-order decomposition equations, where turnover of carbon is determined only by the size of the carbon pool and empirical functions of responses to temperature and moisture. These models do not include microbial dynamics or protection of carbon in microaggregates and mineral complexes, making them incapable of simulating important soil processes like priming and the influence of soil physical structure on carbon turnover. We present a new soil carbon dynamics model - Carbon, Organisms, Respiration, and Protection in the Soil Environment (CORPSE) - that explicitly represents microbial biomass and protected carbon pools. The model includes multiple types of carbon with different chemically determined turnover rates that interact with a single dynamic microbial biomass pool, allowing the model to simulate priming effects. The model also includes the formation and turnover of protected carbon that is inaccessible to microbial decomposers. The rate of protected carbon formation increases with microbial biomass. CORPSE has been implemented both as a stand-alone model and as a component of the NOAA Geophysical Fluid Dynamics Laboratory (GFDL) ESM. We calibrated the model against measured soil carbon stocks from the Duke FACE experiment. The model successfully simulated the seasonal pattern of heterotrophic CO2 production. We investigated the roles of priming and protection in soil carbon accumulation by running the model using measured inputs of leaf litter, fine roots, and root exudates from the ambient and elevated CO2 plots at the Duke FACE experiment. Measurements from the experiment showed that elevated CO2 caused enhanced root exudation, increasing soil carbon turnover in the rhizosphere due to priming effects. We tested the impact of increased root exudation on soil carbon accumulation by comparing model simulations of carbon accumulation under elevated CO2 with and without increased root exudation. Increased root exudation stimulated microbial activity in the model, resulting in reduced accumulation of chemically recalcitrant carbon, but increasing the formation of protected carbon. This indicates that elevated CO2 could cause decreases in soil carbon storage despite increases in productivity in ecosystems where protection of soil carbon is limited. These effects have important implications for simulations of soil carbon response to elevated CO2 in current terrestrial carbon cycle models. The CORPSE model has been implemented in LM3, the terrestrial component of the GFDL ESM. In addition to the functionality described above, this model adds vertically resolved carbon pools and vertical transfers of carbon, leading to a decrease in carbon turnover rates with depth due to leaching of priming agents from the surface. We present preliminary global simulations using this model, including the variation of microbial activity and protected carbon with latitude and the resulting impacts on the sensitivity of soil carbon to climatic warming.

Repertoire comparison of the B-cell receptor encoding loci in humans and rhesus macaques by next generation sequencing

USDA-ARS?s Scientific Manuscript database

Rhesus macaques are a widely used model system for the study of vaccines, infectious diseases, and microbial pathogenesis. Their value as a model lies in their close evolutionary relationship to humans, which, in theory, allows them to serve as a close approximation of the human immune system. Howev...

Phylogenetic and Evolutionary Patterns in Microbial Carotenoid Biosynthesis Are Revealed by Comparative Genomics

PubMed Central

Klassen, Jonathan L.

2010-01-01

Background Carotenoids are multifunctional, taxonomically widespread and biotechnologically important pigments. Their biosynthesis serves as a model system for understanding the evolution of secondary metabolism. Microbial carotenoid diversity and evolution has hitherto been analyzed primarily from structural and biosynthetic perspectives, with the few phylogenetic analyses of microbial carotenoid biosynthetic proteins using either used limited datasets or lacking methodological rigor. Given the recent accumulation of microbial genome sequences, a reappraisal of microbial carotenoid biosynthetic diversity and evolution from the perspective of comparative genomics is warranted to validate and complement models of microbial carotenoid diversity and evolution based upon structural and biosynthetic data. Methodology/Principal Findings Comparative genomics were used to identify and analyze in silico microbial carotenoid biosynthetic pathways. Four major phylogenetic lineages of carotenoid biosynthesis are suggested composed of: (i) Proteobacteria; (ii) Firmicutes; (iii) Chlorobi, Cyanobacteria and photosynthetic eukaryotes; and (iv) Archaea, Bacteroidetes and two separate sub-lineages of Actinobacteria. Using this phylogenetic framework, specific evolutionary mechanisms are proposed for carotenoid desaturase CrtI-family enzymes and carotenoid cyclases. Several phylogenetic lineage-specific evolutionary mechanisms are also suggested, including: (i) horizontal gene transfer; (ii) gene acquisition followed by differential gene loss; (iii) co-evolution with other biochemical structures such as proteorhodopsins; and (iv) positive selection. Conclusions/Significance Comparative genomics analyses of microbial carotenoid biosynthetic proteins indicate a much greater taxonomic diversity then that identified based on structural and biosynthetic data, and divides microbial carotenoid biosynthesis into several, well-supported phylogenetic lineages not evident previously. This phylogenetic framework is applicable to understanding the evolution of specific carotenoid biosynthetic proteins or the unique characteristics of carotenoid biosynthetic evolution in a specific phylogenetic lineage. Together, these analyses suggest a “bramble” model for microbial carotenoid biosynthesis whereby later biosynthetic steps exhibit greater evolutionary plasticity and reticulation compared to those closer to the biosynthetic “root”. Structural diversification may be constrained (“trimmed”) where selection is strong, but less so where selection is weaker. These analyses also highlight likely productive avenues for future research and bioprospecting by identifying both gaps in current knowledge and taxa which may particularly facilitate carotenoid diversification. PMID:20582313

Beyond The Blueprint: Development Of Genome-Informed Trait-Based Models For Prediction Of Microbial Dynamics And Biogeochemical Rates

NASA Astrophysics Data System (ADS)

Brodie, E.; King, E.; Molins, S.; Karaoz, U.; Johnson, J. N.; Bouskill, N.; Hug, L. A.; Thomas, B. C.; Castelle, C. J.; Beller, H. R.; Banfield, J. F.; Steefel, C. I.

2014-12-01

In soils and sediments microorganisms perform essential ecosystem services through their roles in regulating the stability of carbon and the flux of nutrients, and the purification of water. But these are complex systems with the physical, chemical and biological components all intimately connected. Components of this complexity are gradually being uncovered and our understanding of the extent of microbial functional diversity in particular has been enhanced greatly with the development of cultivation independent approaches. However we have not moved far beyond a descriptive and correlative use of this powerful resource. As the ability to reconstruct thousands of genomes from microbial populations using metagenomic techniques gains momentum, the challenge will be to develop an understanding of how these metabolic blueprints serve to influence the fitness of organisms within these complex systems and how populations emerge and impact the physical and chemical properties of their environment. In the presentation we will discuss the development of a trait-based model of microbial activity that simulates coupled guilds of microorganisms that are parameterized including traits extracted from large-scale metagenomic data. Using a reactive transport framework we simulate the thermodynamics of coupled electron donor and acceptor reactions to predict the energy available for respiration, biomass development and exo-enzyme production. Each group within a functional guild is parameterized with a unique combination of traits governing organism fitness under dynamic environmental conditions. This presentation will address our latest developments in the estimation of trait values related to growth rate and the identification and linkage of key fitness traits associated with respiratory and fermentative pathways, macromolecule depolymerization enzymes and nitrogen fixation from metagenomic data. We are testing model sensitivity to initial microbial composition and intra-guild trait variability amongst other parameters and are using this model to explore abiotic controls on community emergence and impact on rates of reactions that contribute to the cycling of carbon across biogeochemical gradients from the soil to the subsurface.

Microbial P450 Enzymes in Bioremediation and Drug Discovery: Emerging Potentials and Challenges.

PubMed

Bhattacharya, Sukanta S; Yadav, Jagjit S

2018-01-01

Cytochrome P450 enzymes are a structurally conserved but functionally diverse group of heme-containing mixed function oxidases found across both prokaryotic and eukaryotic forms of the microbial world. Microbial P450s are known to perform diverse functions ranging from the synthesis of cell wall components to xenobiotic/drug metabolism to biodegradation of environmental chemicals. Conventionally, many microbial systems have been reported to mimic mammalian P450-like activation of drugs and were proposed as the in-vitro models of mammalian drug metabolism. Recent reports suggest that native or engineered forms of specific microbial P450s from these and other microbial systems could be employed for desired specific biotransformation reactions toward natural and synthetic (drug) compounds underscoring their emerging potential in drug improvement and discovery. On the other hand, microorganisms particularly fungi and actinomycetes have been shown to possess catabolic P450s with unusual potential to degrade toxic environmental chemicals including persistent organic pollutants (POPs). Wood-rotting basidiomycete fungi in particular have revealed the presence of exceptionally large P450 repertoire (P450ome) in their genomes, majority of which are however orphan (with no known function). Our pre- and post-genomic studies have led to functional characterization of several fungal P450s inducible in response to exposure to several environmental toxicants and demonstration of their potential in bioremediation of these chemicals. This review is an attempt to summarize the postgenomic unveiling of this versatile enzyme superfamily in microbial systems and investigation of their potential to synthesize new drugs and degrade persistent pollutants, among other biotechnological applications. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

A Versatile Strategy for Characterization and Imaging of Drip Flow Microbial Biofilms.

PubMed

Li, Bin; Dunham, Sage J B; Ellis, Joseph F; Lange, Justin D; Smith, Justin R; Yang, Ning; King, Travis L; Amaya, Kensey R; Arnett, Clint M; Sweedler, Jonathan V

2018-06-05

The inherent architectural and chemical complexities of microbial biofilms mask our understanding of how these communities form, survive, propagate, and influence their surrounding environment. Here we describe a simple and versatile workflow for the cultivation and characterization of model flow-cell-based microbial ecosystems. A customized low-shear drip flow reactor was designed and employed to cultivate single and coculture flow-cell biofilms at the air-liquid interface of several metal surfaces. Pseudomonas putida F1 and Shewanella oneidensis MR-1 were selected as model organisms for this study. The utility and versatility of this platform was demonstrated via the application of several chemical and morphological imaging techniques-including matrix-assisted laser desorption/ionization mass spectrometry imaging, secondary ion mass spectrometry imaging, and scanning electron microscopy-and through the examination of model systems grown on iron substrates of varying compositions. Implementation of these techniques in combination with tandem mass spectrometry and a two-step imaging principal component analysis strategy resulted in the identification and characterization of 23 lipids and 3 oligosaccharides in P. putida F1 biofilms, the discovery of interaction-specific analytes, and the observation of several variations in cell and substrate morphology present during microbially influenced corrosion. The presented workflow is well-suited for examination of both single and multispecies drip flow biofilms and offers a platform for fundamental inquiries into biofilm formation, microbe-microbe interactions, and microbially influenced corrosion.

Convergence of microbial assimilations of soil carbon, nitrogen, phosphorus, and sulfur in terrestrial ecosystems

DOE PAGES

Xu, Xiaofeng; Hui, Dafeng; King, Anthony Wayne; ...

2015-11-27

How soil microbes assimilate carbon-C, nitrogen-N, phosphorus-P, and sulfur-S is fundamental for understanding nutrient cycling in terrestrial ecosystems. We compiled a global database of C, N, P, and S concentrations in soils and microbes and developed relationships between them by using a power function model. The C:N:P:S was estimated to be 287:17:1:0.8 for soils, and 42:6:1:0.4 for microbes. We found a convergence of the relationships between elements in soils and in soil microbial biomass across C, N, P, and S. The element concentrations in soil microbial biomass follow a homeostatic regulation curve with soil element concentrations across C, N, Pmore » and S, implying a unifying mechanism of microbial assimilating soil elements. This correlation explains the well-constrained C:N:P:S stoichiometry with a slightly larger variation in soils than in microbial biomass. Meanwhile, it is estimated that the minimum requirements of soil elements for soil microbes are 0.8 mmol C Kg –1 dry soil, 0.1 mmol N Kg –1 dry soil, 0.1 mmol P Kg –1 dry soil, and 0.1 mmol S Kg –1 dry soil, respectively. Lastly, these findings provide a mathematical explanation of element imbalance in soils and soil microbial biomass, and offer insights for incorporating microbial contribution to nutrient cycling into Earth system models.« less

Perfluoroalkyl Acids Shift Microbial Community Structure Across Experimental Scales

NASA Astrophysics Data System (ADS)

Weathers, T. S.; Sharp, J.

2016-12-01

Perfluoroalkyl acids (PFAAs) are contaminants of emerging concern that have increasingly been found in groundwater and drinking water systems. Previously, we demonstrated that PFAAs significantly alter the abundance of specific microbial clades in batch reductive dechlorinating systems, resulting in decreased chlorinated solvent attenuation capabilities. To further understand the impacts of PFAA exposure on subsurface microbial processes and PFAA transport, we investigated changes in microbial community structure as a function of PFAA presence in flow-through columns simulating aquifer transport. Phylogenetic analysis using high throughput, next generation sequencing performed after exposure to 250 pore volumes of source zone concentrations of PFAAs (10 mg/L each of 11 analytes including PFOS and PFOA) resulted in patterns that mirrored those observed in batch systems, demonstrating a conservation of community dynamics across experimental scales. Of the nine clades observed in both batch and flow-through systems, six were similarly impacted as a function of PFAA exposure, regardless of the experimental differences in transport and redox state. Specifically, the presence of PFAAs enhanced the relative abundance of Archaea, Bacteroidetes (phylum), and the family Veillonellaceae in both systems. Repressed clades include the genus Sedimentibacter, Ruminococcaceae (family), and the Anaerolineales, which contains Dehalococcoides, a genus known for its ability to fully dechlorinate TCE. As PFAAs are often co-located with TCE and BTEX, changes in microbial community structure can result in hindered bioremediation of these co-contaminants. Consideration of community shifts and corresponding changes in behavior, such as repressed reductive dechlorination or increased biofilm formation, will aid in the development of conceptual site models that account for co-contaminant bioremediation potential and PFAA transport.

Rejuvenation of Spent Media via Supported Emulsion Liquid Membranes

NASA Technical Reports Server (NTRS)

Wiencek, John M.

2002-01-01

The overall goal of this project is to maximize the reuseability of spent fermentation media. Supported emulsion liquid membrane separation, a highly efficient extraction technique, is used to remove inhibitory byproducts during fermentation; thus, improving the yield while reducing the need for fresh water. The key objectives of this study are: Develop an emulsion liquid membrane system targeting low molecular weight organic acids which has minimal toxicity on a variety of microbial systems; Conduct mass transfer studies to allow proper modeling and design of a supported emulsion liquid membrane system; Investigate the effect of gravity on emulsion coalescence within the membrane unit; Access the effect of water re-use on fermentation yields in a model microbial system; Develop a perfusion-type fermentor utilizing a supported emulsion liquid membrane system to control inhibitory fermentation byproducts; Work for the coming year will focus on the determination of toxicity of various solvents, selection of the emulsifying agents, as well as characterizing the mass transfer of hollow-fiber contactors.

Mathematical modelling methodologies in predictive food microbiology: a SWOT analysis.

PubMed

Ferrer, Jordi; Prats, Clara; López, Daniel; Vives-Rego, Josep

2009-08-31

Predictive microbiology is the area of food microbiology that attempts to forecast the quantitative evolution of microbial populations over time. This is achieved to a great extent through models that include the mechanisms governing population dynamics. Traditionally, the models used in predictive microbiology are whole-system continuous models that describe population dynamics by means of equations applied to extensive or averaged variables of the whole system. Many existing models can be classified by specific criteria. We can distinguish between survival and growth models by seeing whether they tackle mortality or cell duplication. We can distinguish between empirical (phenomenological) models, which mathematically describe specific behaviour, and theoretical (mechanistic) models with a biological basis, which search for the underlying mechanisms driving already observed phenomena. We can also distinguish between primary, secondary and tertiary models, by examining their treatment of the effects of external factors and constraints on the microbial community. Recently, the use of spatially explicit Individual-based Models (IbMs) has spread through predictive microbiology, due to the current technological capacity of performing measurements on single individual cells and thanks to the consolidation of computational modelling. Spatially explicit IbMs are bottom-up approaches to microbial communities that build bridges between the description of micro-organisms at the cell level and macroscopic observations at the population level. They provide greater insight into the mesoscale phenomena that link unicellular and population levels. Every model is built in response to a particular question and with different aims. Even so, in this research we conducted a SWOT (Strength, Weaknesses, Opportunities and Threats) analysis of the different approaches (population continuous modelling and Individual-based Modelling), which we hope will be helpful for current and future researchers.

Microbial Consortia Engineering for Cellular Factories: in vitro to in silico systems

PubMed Central

Bernstein, Hans C; Carlson, Ross P

2012-01-01

This mini-review discusses the current state of experimental and computational microbial consortia engineering with a focus on cellular factories. A discussion of promising ecological theories central to community resource usage is presented to facilitate interpretation of consortial designs. Recent case studies exemplifying different resource usage motifs and consortial assembly templates are presented. The review also highlights in silico approaches to design and to analyze consortia with an emphasis on stoichiometric modeling methods. The discipline of microbial consortia engineering possesses a widely accepted potential to generate highly novel and effective bio-catalysts for applications from biofuels to specialty chemicals to enhanced mineral recovery. PMID:24688677

Microbial community in a precursory scenario of growing Tagetes patula in a lunar greenhouse

NASA Astrophysics Data System (ADS)

Kozyrovska, N. O.; Korniichuk, O. S.; Voznyuk, T. M.; Kovalchuk, M. V.; Lytvynenko, T. L.; Rogutskyy, I. S.; Mytrokhyn, O. V.; Estrella-Liopis, V. R.; Borodinova, T. I.; Mashkovska, S. P.; Foing, B. H.; Kordyum, V. A.

A confined prototype plant-microbial system is elaborated for demonstration of growing pioneer plants in a lunar greenhouse. A precursory scenario of growing Tagetes patula L. in a substrate anorthosite which is similar mineralogically and chemically to lunar silicate rocks includes the use of a microbial community. Microorganisms served for preventive substrate colonization to avoid infection by deleterious microorganisms as well as for bioleaching and delivering of nutritional elements from anorthosite to plants. A model consortium of a siliceous bacterium, biocontrol agents, and arbuscular mycorrhizal fungi provided an acceptable growth and blossoming of Tagetes patula L. under growth limiting factors in terrestrial conditions.

Sustainable wastewater treatment: how might microbial fuel cells contribute.

PubMed

Oh, Sung T; Kim, Jung Rae; Premier, Giuliano C; Lee, Tae Ho; Kim, Changwon; Sloan, William T

2010-01-01

The need for cost-effective low-energy wastewater treatment has never been greater. Clean water for our expanding and predominantly urban global population will be expensive to deliver, eats into our diminishing carbon-based energy reserves and consequently contributes to green house gases in the atmosphere and climate change. Thus every potential cost and energy cutting measure for wastewater treatment should be explored. Microbial fuel cells (MFCs) could potentially yield such savings but, to achieve this, requires significant advances in our understanding in a few critical areas and in our designs of the overall systems. Here we review the research which might accelerate our progress towards sustainable wastewater treatment using MFCs: system control and modelling and the understanding of the ecology of the microbial communities that catalyse the generation of electricity. Copyright © 2010 Elsevier Inc. All rights reserved.

The rhizosphere microbiota of plant invaders: an overview of recent advances in the microbiomics of invasive plants

PubMed Central

Coats, Vanessa C.; Rumpho, Mary E.

2014-01-01

Plants in terrestrial systems have evolved in direct association with microbes functioning as both agonists and antagonists of plant fitness and adaptability. As such, investigations that segregate plants and microbes provide only a limited scope of the biotic interactions that dictate plant community structure and composition in natural systems. Invasive plants provide an excellent working model to compare and contrast the effects of microbial communities associated with natural plant populations on plant fitness, adaptation, and fecundity. The last decade of DNA sequencing technology advancements opened the door to microbial community analysis, which has led to an increased awareness of the importance of an organism’s microbiome and the disease states associated with microbiome shifts. Employing microbiome analysis to study the symbiotic networks associated with invasive plants will help us to understand what microorganisms contribute to plant fitness in natural systems, how different soil microbial communities impact plant fitness and adaptability, specificity of host–microbe interactions in natural plant populations, and the selective pressures that dictate the structure of above-ground and below-ground biotic communities. This review discusses recent advances in invasive plant biology that have resulted from microbiome analyses as well as the microbial factors that direct plant fitness and adaptability in natural systems. PMID:25101069

Microbial processing of carbon in hydrothermal systems (Invited)

NASA Astrophysics Data System (ADS)

LaRowe, D.; Amend, J. P.

2013-12-01

Microorganisms are known to be active in hydrothermal systems. They catalyze reactions that consume and produce carbon compounds as a result of their efforts to gain energy, grow and replace biomass. However, the rates of these processes, as well as the size of the active component of microbial populations, are poorly constrained in hydrothermal environments. In order to better characterize biogeochemical processes in these settings, a quantitative relationship between rates of microbial catalysis, energy supply and demand and population size is presented. Within this formulation, rates of biomass change are determined as a function of the proportion of catabolic power that is converted into biomass - either new microorganisms or the replacement of existing cell components - and the amount of energy that is required to synthesize biomass. The constraints that hydrothermal conditions place on power supply and demand are explicitly taken into account. The chemical composition, including the concentrations of organic compounds, of diffuse and focused flow hydrothermal fluids, hydrothermally influenced sediment pore water and fluids from the oceanic lithosphere are used in conjunction with cell count data and the model described above to constrain the rates of microbial processes that influence the carbon cycle in the Juan de Fuca hydrothermal system.

The Microbiota, the Immune System and the Allograft

PubMed Central

Alegre, Maria-Luisa; Mannon, Roslyn B.; Mannon, Peter J.

2015-01-01

The microbiota represents the complex collections of microbial communities that colonize a host. In health, the microbiota is essential for metabolism, protection against pathogens and maturation of the immune system. In return, the immune system determines the composition of the microbiota. Altered microbial composition (dysbiosis) has been correlated with a number of diseases in humans. The tight reciprocal immune/microbial interactions complicate determining whether dysbiosis is a cause and/or a consequence of immune dysregulation and disease initiation or progression. However, a number of studies in germ-free and antibiotic-treated animal models support causal roles for intestinal bacteria in disease susceptibility. The role of the microbiota in transplant recipients is only starting to be investigated and its study is further complicated by putative contributions of both recipient and donor microbiota. Moreover, both flora may be affected directly or indirectly by immunosuppressive drugs and anti-microbial prophylaxis taken by transplant patients, as well as by inflammatory processes secondary to ischemia/reperfusion and allorecognition, and the underlying cause of end-organ failure. Whether the ensuing dysbiosis affects alloresponses and whether therapies aimed at correcting dysbiosis should be considered in transplant patients constitutes an exciting new field of research. PMID:24840316

Quorum sensing and microbial drug resistance.

PubMed

Chen, Yu-fan; Liu, Shi-yin; Liang, Zhi-bin; Lv, Ming-fa; Zhou, Jia-nuan; Zhang, Lian-hui

2016-10-20

Microbial drug resistance has become a serious problem of global concern, and the evolution and regulatory mechanisms of microbial drug resistance has become a hotspot of research in recent years. Recent studies showed that certain microbial resistance mechanisms are regulated by quorum sensing system. Quorum sensing is a ubiquitous cell-cell communication system in the microbial world, which associates with cell density. High-density microbial cells produce sufficient amount of small signal molecules, activating a range of downstream cellular processes including virulence and drug resistance mechanisms, which increases bacterial drug tolerance and causes infections on host organisms. In this review, the general mechanisms of microbial drug resistance and quorum-sensing systems are summarized with a focus on the association of quorum sensing and chemical signaling systems with microbial drug resistance mechanisms, including biofilm formation and drug efflux pump. The potential use of quorum quenching as a new strategy to control microbial resistance is also discussed.

Concepts and tools for predictive modeling of microbial dynamics.

PubMed

Bernaerts, Kristel; Dens, Els; Vereecken, Karen; Geeraerd, Annemie H; Standaert, Arnout R; Devlieghere, Frank; Debevere, Johan; Van Impe, Jan F

2004-09-01

Description of microbial cell (population) behavior as influenced by dynamically changing environmental conditions intrinsically needs dynamic mathematical models. In the past, major effort has been put into the modeling of microbial growth and inactivation within a constant environment (static models). In the early 1990s, differential equation models (dynamic models) were introduced in the field of predictive microbiology. Here, we present a general dynamic model-building concept describing microbial evolution under dynamic conditions. Starting from an elementary model building block, the model structure can be gradually complexified to incorporate increasing numbers of influencing factors. Based on two case studies, the fundamentals of both macroscopic (population) and microscopic (individual) modeling approaches are revisited. These illustrations deal with the modeling of (i) microbial lag under variable temperature conditions and (ii) interspecies microbial interactions mediated by lactic acid production (product inhibition). Current and future research trends should address the need for (i) more specific measurements at the cell and/or population level, (ii) measurements under dynamic conditions, and (iii) more comprehensive (mechanistically inspired) model structures. In the context of quantitative microbial risk assessment, complexity of the mathematical model must be kept under control. An important challenge for the future is determination of a satisfactory trade-off between predictive power and manageability of predictive microbiology models.

Microbial Diversity of a Brazilian Coastal Region Influenced by an Upwelling System and Anthropogenic Activity

PubMed Central

Cury, Juliano C.; Araujo, Fabio V.; Coelho-Souza, Sergio A.; Peixoto, Raquel S.; Oliveira, Joana A. L.; Santos, Henrique F.; Dávila, Alberto M. R.; Rosado, Alexandre S.

2011-01-01

Background Upwelling systems are characterised by an intense primary biomass production in the surface (warmest) water after the outcrop of the bottom (coldest) water, which is rich in nutrients. Although it is known that the microbial assemblage plays an important role in the food chain of marine systems and that the upwelling systems that occur in southwest Brazil drive the complex dynamics of the food chain, little is known about the microbial composition present in this region. Methodology/Principal Findings We carried out a molecular survey based on SSU rRNA gene from the three domains of the phylogenetic tree of life present in a tropical upwelling region (Arraial do Cabo, Rio de Janeiro, Brazil). The aim was to analyse the horizontal and vertical variations of the microbial composition in two geographically close areas influenced by anthropogenic activity (sewage disposal/port activity) and upwelling phenomena, respectively. A lower estimated diversity of microorganisms of the three domains of the phylogenetic tree of life was found in the water of the area influenced by anthropogenic activity compared to the area influenced by upwelling phenomena. We observed a heterogenic distribution of the relative abundance of taxonomic groups, especially in the Archaea and Eukarya domains. The bacterial community was dominated by Proteobacteria, Cyanobacteria and Bacteroidetes phyla, whereas the microeukaryotic community was dominated by Metazoa, Fungi, Alveolata and Stramenopile. The estimated archaeal diversity was the lowest of the three domains and was dominated by uncharacterised marine Crenarchaeota that were most closely related to Marine Group I. Conclusions/Significance The variety of conditions and the presence of different microbial assemblages indicated that the area of Arraial do Cabo can be used as a model for detailed studies that contemplate the correlation between pollution-indicating parameters and the depletion of microbial diversity in areas close to anthropogenic activity; functional roles and geochemical processes; phylogeny of the uncharacterised diversity; and seasonal variations of the microbial assemblages. PMID:21304582

The impact of resource dependence of the mechanisms of life on the spatial population dynamics of an in silico microbial community

NASA Astrophysics Data System (ADS)

Daly, Aisling J.; Baetens, Jan M.; De Baets, Bernard

2016-12-01

Biodiversity has a critical impact on ecosystem functionality and stability, and thus the current biodiversity crisis has motivated many studies of the mechanisms that sustain biodiversity, a notable example being non-transitive or cyclic competition. We therefore extend existing microscopic models of communities with cyclic competition by incorporating resource dependence in demographic processes, characteristics of natural systems often oversimplified or overlooked by modellers. The spatially explicit nature of our individual-based model of three interacting species results in the formation of stable spatial structures, which have significant effects on community functioning, in agreement with experimental observations of pattern formation in microbial communities.

Incorporating microbial dormancy dynamics into soil decomposition models to improve quantification of soil carbon dynamics of northern temperate forests

DOE Office of Scientific and Technical Information (OSTI.GOV)

He, Yujie; Yang, Jinyan; Zhuang, Qianlai

Soil carbon dynamics of terrestrial ecosystems play a significant role in the global carbon cycle. Microbial-based decomposition models have seen much growth recently for quantifying this role, yet dormancy as a common strategy used by microorganisms has not usually been represented and tested in these models against field observations. Here in this study we developed an explicit microbial-enzyme decomposition model and examined model performance with and without representation of microbial dormancy at six temperate forest sites of different forest types. We then extrapolated the model to global temperate forest ecosystems to investigate biogeochemical controls on soil heterotrophic respiration and microbialmore » dormancy dynamics at different temporal-spatial scales. The dormancy model consistently produced better match with field-observed heterotrophic soil CO 2 efflux (R H) than the no dormancy model. Our regional modeling results further indicated that models with dormancy were able to produce more realistic magnitude of microbial biomass (<2% of soil organic carbon) and soil R H (7.5 ± 2.4 PgCyr -1). Spatial correlation analysis showed that soil organic carbon content was the dominating factor (correlation coefficient = 0.4-0.6) in the simulated spatial pattern of soil R H with both models. In contrast to strong temporal and local controls of soil temperature and moisture on microbial dormancy, our modeling results showed that soil carbon-to-nitrogen ratio (C:N) was a major regulating factor at regional scales (correlation coefficient = -0.43 to -0.58), indicating scale-dependent biogeochemical controls on microbial dynamics. Our findings suggest that incorporating microbial dormancy could improve the realism of microbial-based decomposition models and enhance the integration of soil experiments and mechanistically based modeling.« less

Wastewater disinfection by peracetic acid: assessment of models for tracking residual measurements and inactivation.

PubMed

Santoro, Domenico; Gehr, Ronald; Bartrand, Timothy A; Liberti, Lorenzo; Notarnicola, Michele; Dell'Erba, Adele; Falsanisi, Dario; Haas, Charles N

2007-07-01

With its potential for low (if any) disinfection byproduct formation and easy retrofit for chlorine contactors, peracetic acid (PAA) or use of PAA in combination with other disinfectant technologies may be an attractive alternative to chlorine-based disinfection. Examples of systems that might benefit from use of PAA are water reuse schemes or plants discharging to sensitive receiving water bodies. Though PAA is in use in numerous wastewater treatment plants in Europe, its chemical kinetics, microbial inactivation rates, and mode of action against microorganisms are not thoroughly understood. This paper presents results from experimental studies of PAA demand, PAA decay, and microbial inactivation, with a complementary modeling analysis. Model results are used to evaluate techniques for measurement of PAA concentration and to develop hypotheses regarding the mode of action of PAA in bacterial inactivation. Kinetic and microbial inactivation rate data were collected for typical wastewaters and may be useful for engineers in evaluating whether to convert from chlorine to PAA disinfection.

Disease Suppressive Soils: New Insights from the Soil Microbiome

USDA-ARS?s Scientific Manuscript database

In this review, we will present three currently-studied model systems with features representative of specific and general suppressiveness. Based on these systems, we will consider hypotheses about the fundamental nature of specific and general disease-suppressive soil microbial communities, explore...

A Generalized Spatial Measure for Resilience of Microbial Systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Renslow, Ryan S.; Lindemann, Stephen R.; Song, Hyun-Seob

2016-04-07

The emergent property of resilience is the ability of a system to return to an original state after a disturbance. Resilience may be used as an early warning system for significant or irreversible community transition, i.e., a community with diminishing or low resilience may be close to catastrophic shift in function or an irreversible collapse. Typically, resilience is quantified using recovery time, which may be difficult or impossible to directly measure in microbial systems. A recent study in the literature showed that under certain conditions, a set of spatial-based metrics termed recovery length, can be correlated to recovery time, andmore » thus may be a reasonable alternative measure of resilience. As a limitation, however, this spatial metric of resilience is useful only for step-change perturbations. Building upon the concept of recovery length, we propose a more general form of the spatial metric of resilience that can be applied to any shape of perturbation profiles (i.e., a sharp or smooth gradient). We termed this new spatial measure “perturbation-adjusted spatial metric of resilience” (PASMORE). We demonstrate the applicability of the proposed metric using a mathematical model of a microbial mat. PASMORE can help identify when a system, such as a microbial community, is on the verge of collapse or nearing an irreversible transition across a tipping point.« less

Alignment of microbial fitness with engineered product formation: obligatory coupling between acetate production and photoautotrophic growth.

PubMed

Du, Wei; Jongbloets, Joeri A; van Boxtel, Coco; Pineda Hernández, Hugo; Lips, David; Oliver, Brett G; Hellingwerf, Klaas J; Branco Dos Santos, Filipe

2018-01-01

Microbial bioengineering has the potential to become a key contributor to the future development of human society by providing sustainable, novel, and cost-effective production pipelines. However, the sustained productivity of genetically engineered strains is often a challenge, as spontaneous non-producing mutants tend to grow faster and take over the population. Novel strategies to prevent this issue of strain instability are urgently needed. In this study, we propose a novel strategy applicable to all microbial production systems for which a genome-scale metabolic model is available that aligns the production of native metabolites to the formation of biomass. Based on well-established constraint-based analysis techniques such as OptKnock and FVA, we developed an in silico pipeline-FRUITS-that specifically 'Finds Reactions Usable in Tapping Side-products'. It analyses a metabolic network to identify compounds produced in anabolism that are suitable to be coupled to growth by deletion of their re-utilization pathway(s), and computes their respective biomass and product formation rates. When applied to Synechocystis sp. PCC6803, a model cyanobacterium explored for sustainable bioproduction, a total of nine target metabolites were identified. We tested our approach for one of these compounds, acetate, which is used in a wide range of industrial applications. The model-guided engineered strain shows an obligatory coupling between acetate production and photoautotrophic growth as predicted. Furthermore, the stability of acetate productivity in this strain was confirmed by performing prolonged turbidostat cultivations. This work demonstrates a novel approach to stabilize the production of target compounds in cyanobacteria that culminated in the first report of a photoautotrophic growth-coupled cell factory. The method developed is generic and can easily be extended to any other modeled microbial production system.

Hydrodynamic modelling of recreational water quality using Escherichia coli as an indicator of microbial contamination

NASA Astrophysics Data System (ADS)

Eregno, Fasil Ejigu; Tryland, Ingun; Tjomsland, Torulv; Kempa, Magdalena; Heistad, Arve

2018-06-01

Microbial contamination of recreational beaches is often at its worst after heavy rainfall events due to storm floods that carry fecal matter and other pollutants from the watershed. Similarly, overflows of untreated sewage from combined sewerage systems may discharge directly into coastal water or via rivers and streams. In order to understand the effect of rainfall events, wind-directions and tides on the recreational water quality, GEMSS, an integrated 3D hydrodynamic model was applied to assess the spreading of Escherichia coli (E. coli) at the Sandvika beaches, located in the Oslo fjord. The model was also used to theoretically investigate the effect of discharges from septic tanks from boats on the water quality at local beaches. The model make use of microbial decay rate as the main input representing the survival of microbial pathogens in the ocean, which vary widely depending on the type of pathogen and environmental stress. The predicted beach water quality was validated against observed data after a heavy rainfall event using Nash-Sutcliffe coefficient (E) and the overall result indicated that the model performed quite well and the simulation was in - good agreement with the observed E. coli concentrations for all beaches. The result of this study indicated that: 1) the bathing water quality was poor according to the EU bathing water directive up to two days after the heavy rainfall event depending on the location of the beach site. 2) The discharge from a boat at 300-meter distance to the beaches slightly increased the E. coli levels at the beaches. 3) The spreading of microbial pathogens from its source to the different beaches depended on the wind speed and the wind direction.

Modeling of Nonlinear Dynamics and Synchronized Oscillations of Microbial Populations, Carbon and Oxygen Concentrations, Induced by Root Exudation in the Rhizosphere

NASA Astrophysics Data System (ADS)

Molz, F. J.; Faybishenko, B.; Jenkins, E. W.

2012-12-01

Mass and energy fluxes within the soil-plant-atmosphere continuum are highly coupled and inherently nonlinear. The main focus of this presentation is to demonstrate the results of numerical modeling of a system of 4 coupled, nonlinear ordinary differential equations (ODEs), which are used to describe the long-term, rhizosphere processes of soil microbial dynamics, including the competition between nitrogen-fixing bacteria and those unable to fix nitrogen, along with substrate concentration (nutrient supply) and oxygen concentration. Modeling results demonstrate the synchronized patterns of temporal oscillations of competing microbial populations, which are affected by carbon and oxygen concentrations. The temporal dynamics and amplitude of the root exudation process serve as a driving force for microbial and geochemical phenomena, and lead to the development of the Gompetzian dynamics, synchronized oscillations, and phase-space attractors of microbial populations and carbon and oxygen concentrations. The nonlinear dynamic analysis of time series concentrations from the solution of the ODEs was used to identify several types of phase-space attractors, which appear to be dependent on the parameters of the exudation function and Monod kinetic parameters. This phase space analysis was conducted by means of assessing the global and local embedding dimensions, correlation time, capacity and correlation dimensions, and Lyapunov exponents of the calculated model variables defining the phase space. Such results can be used for planning experimental and theoretical studies of biogeochemical processes in the fields of plant nutrition, phyto- and bio-remediation, and other ecological areas.

Effects of Resource Chemistry on the Composition and Function of Stream Hyporheic Biofilms

PubMed Central

Hall, E. K.; Besemer, K.; Kohl, L.; Preiler, C.; Riedel, K.; Schneider, T.; Wanek, W.; Battin, T. J.

2012-01-01

Fluvial ecosystems process large quantities of dissolved organic matter as it moves from the headwater streams to the sea. In particular, hyporheic sediments are centers of high biogeochemical reactivity due to their elevated residence time and high microbial biomass and activity. However, the interaction between organic matter and microbial dynamics in the hyporheic zone remains poorly understood. We evaluated how variance in resource chemistry affected the microbial community and its associated activity in experimentally grown hyporheic biofilms. To do this we fed beech leaf leachates that differed in chemical composition to a series of bioreactors filled with sediment from a sub-alpine stream. Differences in resource chemistry resulted in differences in diversity and phylogenetic origin of microbial proteins, enzyme activity, and microbial biomass stoichiometry. Specifically, increased lignin, phenolics, and manganese in a single leachate resulted in increased phenoloxidase and peroxidase activity, elevated microbial biomass carbon:nitrogen ratio, and a greater proportion of proteins of Betaproteobacteria origin. We used this model system to attempt to link microbial form (community composition and metaproteome) with function (enzyme activity) in order to better understand the mechanisms that link resource heterogeneity to ecosystem function in stream ecosystems. PMID:22347877

Effects of resource chemistry on the composition and function of stream hyporheic biofilms.

USGS Publications Warehouse

Hall, E.K.; Besemer, K.; Kohl, L.; Preiler, C.; Reidel, K.; Schneider, T.; Wanek, W.; Battin, T.J.

2012-01-01

Fluvial ecosystems process large quantities of dissolved organic matter as it moves from the headwater streams to the sea. In particular, hyporheic sediments are centers of high biogeochemical reactivity due to their elevated residence time and high microbial biomass and activity. However, the interaction between organic matter and microbial dynamics in the hyporheic zone remains poorly understood. We evaluated how variance in resource chemistry affected the microbial community and its associated activity in experimentally grown hyporheic biofilms. To do this we fed beech leaf leachates that differed in chemical composition to a series of bioreactors filled with sediment from a sub-alpine stream. Differences in resource chemistry resulted in differences in diversity and phylogenetic origin of microbial proteins, enzyme activity, and microbial biomass stoichiometry. Specifically, increased lignin, phenolics, and manganese in a single leachate resulted in increased phenoloxidase and peroxidase activity, elevated microbial biomass carbon:nitrogen ratio, and a greater proportion of proteins of Betaproteobacteria origin. We used this model system to attempt to link microbial form (community composition and metaproteome) with function (enzyme activity) in order to better understand the mechanisms that link resource heterogeneity to ecosystem function in stream ecosystems.

A Modification of the Levich Model to Flux at a Rotating Disk in the presence of Planktonic Bacteria

NASA Astrophysics Data System (ADS)

Jones, Akhenaton-Andrew; Buie, Cullen

2015-11-01

The Levich model of flow at a rotating disk describes convective mass transport to a disk when edge effects and wall effects can be neglected. It is used to interpret electrochemical reaction kinetics and electrochemical impedance of flow systems. The solution has been shown to be invalid for high densities (~ 1 % v/v) of inert, non-motile nano-sized particles (<0.1 μm) and macro-particles (>1.5 μm), yet little work has been done for motile bacteria and bacterial sized particles. The influence of planktonic bacteria on rotating disk experiments is crucial for the evaluation of electrochemically active biofilms. In this work, we show that the presence of bacteria creates significant deviation from the ideal Levich model not shared by inert particles. We also study the impact of dead (fixed) bacteria on deviation form the Levich model. This work has implications for studies of microbial induced corrosion, microbial adhesion, and antibiotic transport to adhered biofilms preformed in rotating disk systems.

Recovery of microbial communities and carbon cycling processes following drought manipulation in southern California

NASA Astrophysics Data System (ADS)

Allison, S. D.; Martiny, J. B. H.; Martiny, A.; Berlemont, R.; Treseder, K. K.; Goulden, M.; Brodie, E.

2016-12-01

Predicting the functioning of microbial communities under changing environmental conditions remains a key challenge in Earth system science. Metagenomics and other high-throughput molecular approaches can help address this challenge by revealing the functional potential of microbial communities. We coupled metagenomics with models and experimental manipulations to address microbial responses to drought in a California grassland ecosystem along with the consequences for carbon cycling. We developed an approach for extracting trait information from metagenomic data and asked: 1) What is the phylogenetic structure of drought response traits? 2) What is the relationship between these traits and those involved in carbohydrate degradation? 3) How do both classes of traits vary seasonally and with precipitation manipulation? 4) How resilient are these traits in the face of perturbation? We found that drought response traits are phylogenetically conserved at an equivalent of 5-8% ribosomal RNA gene sequence dissimilarity. Experimental drought treatment selected for the genetic potential to degrade starch, xylan, and mixed polysaccharides, suggesting a link between drought response and carbon cycling traits. In addition, microbial communities exposed to experimental drought showed a reduced potential to degrade plant biomass. Particularly among bacteria, seasonal drought had a larger impact on microbial composition, abundance, and carbohydrate-degrading genes compared to experimental drought. Bacterial communities were also more resilient to drought perturbation than fungal communities, which showed legacies of drought perturbation for up to three years. Altogether, these findings imply that microbial communities exhibit trait diversity that facilitates resilience but with substantial time lags and consequences for carbon turnover. This information is being used to inform new trait-based models that address the challenge of predicting microbial functioning under precipitation change.

Process design for microbial plastic factories: metabolic engineering of polyhydroxyalkanoates.

PubMed

Aldor, Ilana S; Keasling, Jay D

2003-10-01

Implementing several metabolic engineering strategies, either individually or in combination, it is possible to construct microbial plastic factories to produce a variety of polyhydroxyalkanoate (PHA) biopolymers with desirable structures and material properties. Approaches include external substrate manipulation, inhibitor addition, recombinant gene expression, host cell genome manipulation and, most recently, protein engineering of PHA biosynthetic enzymes. In addition, mathematical models and molecular methods can be used to elucidate metabolically engineered systems and to identify targets for performance improvement.

Engineering microbial consortia for controllable outputs

PubMed Central

Lindemann, Stephen R; Bernstein, Hans C; Song, Hyun-Seob; Fredrickson, Jim K; Fields, Matthew W; Shou, Wenying; Johnson, David R; Beliaev, Alexander S

2016-01-01

Much research has been invested into engineering microorganisms to perform desired biotransformations; nonetheless, these efforts frequently fall short of expected results due to the unforeseen effects of biofeedback regulation and functional incompatibility. In nature, metabolic function is compartmentalized into diverse organisms assembled into robust consortia, in which the division of labor is thought to lead to increased community efficiency and productivity. Here we consider whether and how consortia can be designed to perform bioprocesses of interest beyond the metabolic flexibility limitations of a single organism. Advances in post-genomic analysis of microbial consortia and application of high-resolution global measurements now offer the promise of systems-level understanding of how microbial consortia adapt to changes in environmental variables and inputs of carbon and energy. We argue that, when combined with appropriate modeling frameworks, systems-level knowledge can markedly improve our ability to predict the fate and functioning of consortia. Here we articulate our collective perspective on the current and future state of microbial community engineering and control while placing specific emphasis on ecological principles that promote control over community function and emergent properties. PMID:26967105

Engineering microbial consortia for controllable outputs

DOE PAGES

Lindemann, Stephen R.; Bernstein, Hans C.; Song, Hyun -Seob; ...

2016-03-11

In this study, much research has been invested into engineering microorganisms to perform desired biotransformations; nonetheless, these efforts frequently fall short of expected results due to the unforeseen effects of biofeedback regulation and functional incompatibility. In nature, metabolic function is compartmentalized into diverse organisms assembled into robust consortia, in which the division of labor is thought to lead to increased community efficiency and productivity. Here we consider whether and how consortia can be designed to perform bioprocesses of interest beyond the metabolic flexibility limitations of a single organism. Advances in post-genomic analysis of microbial consortia and application of high-resolution globalmore » measurements now offer the promise of systems-level understanding of how microbial consortia adapt to changes in environmental variables and inputs of carbon and energy. We argue that, when combined with appropriate modeling frameworks, systems-level knowledge can markedly improve our ability to predict the fate and functioning of consortia. Here we articulate our collective perspective on the current and future state of microbial community engineering and control while placing specific emphasis on ecological principles that promote control over community function and emergent properties.« less

A multi-perspective review of microbial fuel-cells for wastewater treatment: Bio-electro-chemical, microbiologic and modeling aspects

DOE Office of Scientific and Technical Information (OSTI.GOV)

Capodaglio, Andrea G., E-mail: capo@unipv.it; Molognoni, Daniele; Pons, Anna Vilajeliu

Microbial Fuel Cells (MFCs) represent a still novel technology for the recovery of energy and resources through wastewater treatment. Although the technology is quite appealing, due its potential benefits, its practical application is still hampered by several drawbacks, such as systems instability (especially when attempting to scale-up reactors from laboratory prototype), internally competing microbial reactions, and limited power generation. This paper is an attempt to address several of the operational issues related to MFCs application to wastewater treatment, in particular when dealing with simultaneous organic matter and nitrogen pollution control. Reactor configuration, operational schemes, electrochemical and microbiological characterization, optimization methodsmore » and modelling strategies are reviewed and discussed with a multidisciplinary, multi-perspective approach. The conclusions drawn herein can be of practical interest for all MFC researchers dealing with domestic or industrial wastewater treatment..« less

Standing variation in spatially growing populations

NASA Astrophysics Data System (ADS)

Fusco, Diana; Gralka, Matti; Kayser, Jona; Hallatschek, Oskar

Patterns of genetic diversity not only reflect the evolutionary history of a species but they can also determine the evolutionary response to environmental change. For instance, the standing genetic diversity of a microbial population can be key to rescue in the face of an antibiotic attack. While genetic diversity is in general shaped by both demography and evolution, very little is understood when both factors matter, as e.g. for biofilms with pronounced spatial organization. Here, we quantitatively explore patterns of genetic diversity by using microbial colonies and well-mixed test tube populations as antipodal model systems with extreme and very little spatial structure, respectively. We find that Eden model simulations and KPZ theory can remarkably reproduce the genetic diversity in microbial colonies obtained via population sequencing. The excellent agreement allows to draw conclusions on the resilience of spatially-organized populations and to uncover new strategies to contain antibiotic resistance.

Modelling potential/current distribution in microbial electrochemical systems shows how the optimal bioanode architecture depends on electrolyte conductivity.

PubMed

Lacroix, Rémy; Da Silva, Serge; Gaig, Monica Viaplana; Rousseau, Raphael; Délia, Marie-Line; Bergel, Alain

2014-11-07

The theoretical bases for modelling the distribution of the electrostatic potential in microbial electrochemical systems are described. The secondary potential distribution (i.e. without mass transport limitation of the substrate) is shown to be sufficient to validly address microbial electrolysis cells (MECs). MECs are modelled with two different ionic conductivities of the solution (1 and 5.3 S m(-1)) and two bioanode kinetics (jmax = 5.8 or 34 A m(-2)). A conventional reactor configuration, with the anode and the cathode face to face, is compared with a configuration where the bioanode perpendicular to the cathode implements the electrochemical reaction on its two sides. The low solution conductivity is shown to have a crucial impact, which cancels out the advantages obtained by setting the bioanode perpendicular to the cathode. For the same reason, when the surface area of the anode is increased by multiplying the number of plates, care must be taken not to create too dense anode architecture. Actually, the advantages of increasing the surface area by multiplying the number of plates can be lost through worsening of the electrochemical conditions in the multi-layered anode, because of the increase of the electrostatic potential of the solution inside the anode structure. The model gives the first theoretical bases for scaling up MECs in a rather simple but rigorous way.

Acute Gastrointestinal Illness Risks in North Carolina Community Water Systems: A Methodological Comparison.

PubMed

DeFelice, Nicholas B; Johnston, Jill E; Gibson, Jacqueline MacDonald

2015-08-18

The magnitude and spatial variability of acute gastrointestinal illness (AGI) cases attributable to microbial contamination of U.S. community drinking water systems are not well characterized. We compared three approaches (drinking water attributable risk, quantitative microbial risk assessment, and population intervention model) to estimate the annual number of emergency department visits for AGI attributable to microorganisms in North Carolina community water systems. All three methods used 2007-2013 water monitoring and emergency department data obtained from state agencies. The drinking water attributable risk method, which was the basis for previous U.S. Environmental Protection Agency national risk assessments, estimated that 7.9% of annual emergency department visits for AGI are attributable to microbial contamination of community water systems. However, the other methods' estimates were more than 2 orders of magnitude lower, each attributing 0.047% of annual emergency department visits for AGI to community water system contamination. The differences in results between the drinking water attributable risk method, which has been the main basis for previous national risk estimates, and the other two approaches highlight the need to improve methods for estimating endemic waterborne disease risks, in order to prioritize investments to improve community drinking water systems.

Depth dependent microbial carbon use efficiency in the capillary fringe as affected by water table fluctuations in a column incubation experiment

NASA Astrophysics Data System (ADS)

Pronk, G. J.; Mellage, A.; Milojevic, T.; Smeaton, C. M.; Rezanezhad, F.; Van Cappellen, P.

2017-12-01

Microbial growth and turnover of soil organic carbon (SOC) depend on the availability of electron donors and acceptors. The steep geochemical gradients in the capillary fringe between the saturated and unsaturated zones provide hotspots of soil microbial activity. Water table fluctuations and the associated drying and wetting cycles within these zones have been observed to lead to enhanced turnover of SOC and adaptation of the local microbial communities. To improve our understanding of SOC degradation under changing moisture conditions, we carried out an automated soil column experiment with integrated of hydro-bio-geophysical monitoring under both constant and oscillating water table conditions. An artificial soil mixture composed of quartz sand, montmorillonite, goethite and humus was used to provide a well-defined system. This material was inoculated with a microbial community extracted from a forested riparian zone. The soils were packed into 6 columns (60 cm length and 7.5 cm inner diameter) to a height of 45 cm; and three replicate columns were incubated under constant water table while another three were saturated and drained monthly. The initial soil development, carbon cycling and microbial community development were then characterized during 10 months of incubation. This system provides an ideal artificial gradient from the saturated to the unsaturated zone to study soil development from initially homogeneous materials and the same microbial community composition under controlled conditions. Depth profiles of SOC and microbial biomass after 329 days of incubation showed a depletion of carbon in the transition drying and wetting zone that was not associated with higher accumulation of microbial biomass, indicating a lower carbon use efficiency of the microbial community established within the water table fluctuation zone. This was supported by a higher ATP to microbial biomass carbon ratio within the same zone. The findings from this study highlight the importance of considering the effects of transient soil moisture and oxygen availability on microbial mediated SOC transformations. The effects of these changes in carbon use efficiency need to be included in soil models in order to accurately predict SOC turnover.

Modelling highly variable environmental factors to assess potential microbial respiration in complex floodplain landscapes

PubMed Central

Tritthart, Michael; Welti, Nina; Bondar-Kunze, Elisabeth; Pinay, Gilles; Hein, Thomas; Habersack, Helmut

2011-01-01

The hydrological exchange conditions strongly determine the biogeochemical dynamics in river systems. More specifically, the connectivity of surface waters between main channels and floodplains is directly controlling the delivery of organic matter and nutrients into the floodplains, where biogeochemical processes recycle them with high rates of activity. Hence, an in-depth understanding of the connectivity patterns between main channel and floodplains is important for the modelling of potential gas emissions in floodplain landscapes. A modelling framework that combines steady-state hydrodynamic simulations with long-term discharge hydrographs was developed to calculate water depths as well as statistical probabilities and event durations for every node of a computation mesh being connected to the main river. The modelling framework was applied to two study sites in the floodplains of the Austrian Danube River, East of Vienna. Validation of modelled flood events showed good agreement with gauge readings. Together with measured sediment properties, results of the validated connectivity model were used as basis for a predictive model yielding patterns of potential microbial respiration based on the best fit between characteristics of a number of sampling sites and the corresponding modelled parameters. Hot spots of potential microbial respiration were found in areas of lower connectivity if connected during higher discharges and areas of high water depths. PMID:27667961

Experimental and numerical studies on the treatment of wet astronaut trash by forced-convection drying

NASA Astrophysics Data System (ADS)

Arquiza, J. M. R. Apollo; Morrow, Robert; Remiker, Ross; Hunter, Jean B.

2017-09-01

During long-term space missions, astronauts generate wet trash, including food containers with uneaten portions, moist hygiene wipes and wet paper towels. This waste produces two problems: the loss of water and the generation of odors and health hazards by microbial growth. These problems are solved by a closed-loop, forced-convection, heat-pump drying system which stops microbial activity by both pasteurization and desiccation, and recovers water in a gravity-independent porous media condensing heat exchanger. A transient, pseudo-homogeneous continuum model for the drying of wet ersatz trash was formulated for this system. The model is based on the conservation equations for energy and moisture applied to the air and solid phases and includes the unique trash characteristic of having both dry and wet solids. Experimentally determined heat and mass transfer coefficients, together with the moisture sorption equilibrium relationship for the wet material are used in the model. The resulting system of differential equations is solved by the finite-volume method as implemented by the commercial software COMSOL. Model simulations agreed well with experimental data under certain conditions. The validated model will be used in the optimization of the entire closed-loop system consisting of fan, air heater, dryer vessel, heat-pump condenser, and heat-recovery modules.

To what extent do food preferences explain the trophic position of heterotrophic and mixotrophic microbial consumers in a Sphagnum peatland?

PubMed

Jassey, Vincent E J; Meyer, Caroline; Dupuy, Christine; Bernard, Nadine; Mitchell, Edward A D; Toussaint, Marie-Laure; Metian, Marc; Chatelain, Auriel P; Gilbert, Daniel

2013-10-01

Although microorganisms are the primary drivers of biogeochemical cycles, the structure and functioning of microbial food webs are poorly studied. This is the case in Sphagnum peatlands, where microbial communities play a key role in the global carbon cycle. Here, we explored the structure of the microbial food web from a Sphagnum peatland by analyzing (1) the density and biomass of different microbial functional groups, (2) the natural stable isotope (δ(13)C and δ(15)N) signatures of key microbial consumers (testate amoebae), and (3) the digestive vacuole contents of Hyalosphenia papilio, the dominant testate amoeba species in our system. Our results showed that the feeding type of testate amoeba species (bacterivory, algivory, or both) translates into their trophic position as assessed by isotopic signatures. Our study further demonstrates, for H. papilio, the energetic benefits of mixotrophy when the density of its preferential prey is low. Overall, our results show that testate amoebae occupy different trophic levels within the microbial food web, depending on their feeding behavior, the density of their food resources, and their metabolism (i.e., mixotrophy vs. heterotrophy). Combined analyses of predation, community structure, and stable isotopes now allow the structure of microbial food webs to be more completely described, which should lead to improved models of microbial community function.

Molecular Ecology of Hypersaline Microbial Mats: Current Insights and New Directions.

PubMed

Wong, Hon Lun; Ahmed-Cox, Aria; Burns, Brendan Paul

2016-01-05

Microbial mats are unique geobiological ecosystems that form as a result of complex communities of microorganisms interacting with each other and their physical environment. Both the microorganisms present and the network of metabolic interactions govern ecosystem function therein. These systems are often found in a range of extreme environments, and those found in elevated salinity have been particularly well studied. The purpose of this review is to briefly describe the molecular ecology of select model hypersaline mat systems (Guerrero Negro, Shark Bay, S'Avall, and Kiritimati Atoll), and any potentially modulating effects caused by salinity to community structure. In addition, we discuss several emerging issues in the field (linking function to newly discovered phyla and microbial dark matter), which illustrate the changing paradigm that is seen as technology has rapidly advanced in the study of these extreme and evolutionally significant ecosystems.

Genome-based microbial ecology of anammox granules in a full-scale wastewater treatment system.

PubMed

Speth, Daan R; In 't Zandt, Michiel H; Guerrero-Cruz, Simon; Dutilh, Bas E; Jetten, Mike S M

2016-03-31

Partial-nitritation anammox (PNA) is a novel wastewater treatment procedure for energy-efficient ammonium removal. Here we use genome-resolved metagenomics to build a genome-based ecological model of the microbial community in a full-scale PNA reactor. Sludge from the bioreactor examined here is used to seed reactors in wastewater treatment plants around the world; however, the role of most of its microbial community in ammonium removal remains unknown. Our analysis yielded 23 near-complete draft genomes that together represent the majority of the microbial community. We assign these genomes to distinct anaerobic and aerobic microbial communities. In the aerobic community, nitrifying organisms and heterotrophs predominate. In the anaerobic community, widespread potential for partial denitrification suggests a nitrite loop increases treatment efficiency. Of our genomes, 19 have no previously cultivated or sequenced close relatives and six belong to bacterial phyla without any cultivated members, including the most complete Omnitrophica (formerly OP3) genome to date.

Genome-based microbial ecology of anammox granules in a full-scale wastewater treatment system

PubMed Central

Speth, Daan R.; in 't Zandt, Michiel H.; Guerrero-Cruz, Simon; Dutilh, Bas E.; Jetten, Mike S. M.

2016-01-01

Partial-nitritation anammox (PNA) is a novel wastewater treatment procedure for energy-efficient ammonium removal. Here we use genome-resolved metagenomics to build a genome-based ecological model of the microbial community in a full-scale PNA reactor. Sludge from the bioreactor examined here is used to seed reactors in wastewater treatment plants around the world; however, the role of most of its microbial community in ammonium removal remains unknown. Our analysis yielded 23 near-complete draft genomes that together represent the majority of the microbial community. We assign these genomes to distinct anaerobic and aerobic microbial communities. In the aerobic community, nitrifying organisms and heterotrophs predominate. In the anaerobic community, widespread potential for partial denitrification suggests a nitrite loop increases treatment efficiency. Of our genomes, 19 have no previously cultivated or sequenced close relatives and six belong to bacterial phyla without any cultivated members, including the most complete Omnitrophica (formerly OP3) genome to date. PMID:27029554

Real-time evaluation of two light delivery systems for photodynamic disinfection of Candida albicans biofilm in curved root canals.

PubMed

Sabino, C P; Garcez, A S; Núñez, S C; Ribeiro, M S; Hamblin, M R

2015-08-01

Antimicrobial photodynamic therapy (APDT) combined with endodontic treatment has been recognized as an alternative approach to complement conventional root canal disinfection methods on bacterial biofilms. We developed an in  vitro model of bioluminescent Candida albicans biofilm inside curved dental root canals and investigated the microbial reduction produced when different light delivery methods are employed. Each light delivery method was evaluated in respect to the light distribution provided inside curved root canals. After conventional endodontic preparation, teeth were sterilized before canals were contaminated by a bioluminescent strain of C. albicans (CEC789). Methylene blue (90 μM) was introduced into the canals and then irradiated (λ = 660 nm, P = 100 mW, beam diameter = 2 mm) with laser tip either in contact with pulp chamber or within the canal using an optical diffuser fiber. Light distribution was evaluated by CCD camera, and microbial reduction was monitored through bioluminescence imaging. Our findings demonstrated that the bioluminescent C. albicans biofilm model had good reproducibility and uniformity. Light distribution in dental tissue was markedly dependent on the light delivery system, and this strategy was directly related to microbial destruction. Both light delivery systems performed significant fungal inactivation. However, when irradiation was performed with optical diffuser fiber, microbial burden reduction was nearly 100 times more effective. Bioluminescence is an interesting real-time analysis to endodontic C. albicans biofilm inactivation. APDT showed to be an effective way to inactivate C. albicans biofilms. Diffuser fibers provided optimized light distribution inside curved root canals and significantly increased APDT efficiency.

Phototrophic biofilm assembly in microbial-mat-derived unicyanobacterial consortia: model systems for the study of autotroph-heterotroph interactions

PubMed Central

Cole, Jessica K.; Hutchison, Janine R.; Renslow, Ryan S.; Kim, Young-Mo; Chrisler, William B.; Engelmann, Heather E.; Dohnalkova, Alice C.; Hu, Dehong; Metz, Thomas O.; Fredrickson, Jim K.; Lindemann, Stephen R.

2014-01-01

Microbial autotroph-heterotroph interactions influence biogeochemical cycles on a global scale, but the diversity and complexity of natural systems and their intractability to in situ manipulation make it challenging to elucidate the principles governing these interactions. The study of assembling phototrophic biofilm communities provides a robust means to identify such interactions and evaluate their contributions to the recruitment and maintenance of phylogenetic and functional diversity over time. To examine primary succession in phototrophic communities, we isolated two unicyanobacterial consortia from the microbial mat in Hot Lake, Washington, characterizing the membership and metabolic function of each consortium. We then analyzed the spatial structures and quantified the community compositions of their assembling biofilms. The consortia retained the same suite of heterotrophic species, identified as abundant members of the mat and assigned to Alphaproteobacteria, Gammaproteobacteria, and Bacteroidetes. Autotroph growth rates dominated early in assembly, yielding to increasing heterotroph growth rates late in succession. The two consortia exhibited similar assembly patterns, with increasing relative abundances of members from Bacteroidetes and Alphaproteobacteria concurrent with decreasing relative abundances of those from Gammaproteobacteria. Despite these similarities at higher taxonomic levels, the relative abundances of individual heterotrophic species were substantially different in the developing consortial biofilms. This suggests that, although similar niches are created by the cyanobacterial metabolisms, the resulting webs of autotroph-heterotroph and heterotroph-heterotroph interactions are specific to each primary producer. The relative simplicity and tractability of the Hot Lake unicyanobacterial consortia make them useful model systems for deciphering interspecies interactions and assembly principles relevant to natural microbial communities. PMID:24778628

Real-time evaluation of two light delivery systems for photodynamic disinfection of Candida albicans biofilm in curved root canals

PubMed Central

Sabino, C. P.; Garcez, A. S.; Núñez, S. C.; Ribeiro, M. S.; Hamblin, M. R.

2014-01-01

Antimicrobial photodynamic therapy (APDT) combined with endodontic treatment has been recognized as an alternative approach to complement conventional root canal disinfection methods on bacterial biofilms. We developed an in vitro model of bioluminescent Candida albicans biofilm inside curved dental root canals and investigated the microbial reduction produced when different light delivery methods are employed. Each light delivery method was evaluated in respect to the light distribution provided inside curved root canals. After conventional endodontic preparation, teeth were sterilized before canals were contaminated by a bioluminescent strain of C. albicans (CEC789). Methylene blue (90 µM) was introduced into the canals and then irradiated (λ=660 nm, P=100 mW, beam diameter=2 mm) with laser tip either in contact with pulp chamber or within the canal using an optical diffuser fiber. Light distribution was evaluated by CCD camera, and microbial reduction was monitored through bioluminescence imaging. Our findings demonstrated that the bioluminescent C. albicans biofilm model had good reproducibility and uniformity. Light distribution in dental tissue was markedly dependent on the light delivery system, and this strategy was directly related to microbial destruction. Both light delivery systems performed significant fungal inactivation. However, when irradiation was performed with optical diffuser fiber, microbial burden reduction was nearly 100 times more effective. Bioluminescence is an interesting real-time analysis to endodontic C. albicans biofilm inactivation. APDT showed to be an effective way to inactivate C. albicans biofilms. Diffuser fibers provided optimized light distribution inside curved root canals and significantly increased APDT efficiency. PMID:25060900

A Theoretical Reassessment of Microbial Maintenance and Implications for Microbial Ecology Modeling

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Gangsheng; Post, Wilfred M

We attempted to reconcile three microbial maintenance models (Herbert, Pirt, and Compromise) through a critical reassessment. We provided a rigorous proof that the true growth yield coefficient (YG) is the ratio of the specific maintenance rate (a in Herbert) to the maintenance coefficient (m in Pirt). Other findings from this study include: (1) the Compromise model is identical to the Herbert for computing microbial growth and substrate consumption, but it expresses the dependence of maintenance on both microbial biomass and substrate; (2) the maximum specific growth rate in the Herbert ( max,H) is higher than those in the other twomore » models ( max,P and max,C), and the difference is the physiological maintenance factor (mq = a); and (3) the overall maintenance coefficient (mT) is more sensitive to mq than to the specific growth rate ( G) and YG. Our critical reassessment of microbial maintenance provides a new approach for quantifying some important components in soil microbial ecology models.« less

Modeling the Response of Soil Organic Matter Decomposition to Warming: Effects of Dynamical Enzyme Productivity and Nuanced Representation of Respiration.

NASA Astrophysics Data System (ADS)

Sihi, D.; Gerber, S.; Inglett, K. S.; Inglett, P.

2014-12-01

Recent development in modeling soil organic carbon (SOC) decomposition includes the explicit incorporation of enzyme and microbial dynamics. A characteristic of these models is a feedback between substrate and consumers which is absent in traditional first order decay models. Second, microbial decomposition models incorporate carbon use efficiency (CUE) as a function of temperature which proved to be critical to prediction of SOC with warming. Our main goal is to explore microbial decomposition models with respect to responses of microbes to enzyme activity, costs to enzyme production, and to incorporation of growth vs. maintenance respiration. In order to simplify the modeling setup we assumed quick adjustment of enzyme activity and depolymerized carbon to microbial and SOC pools. Enzyme activity plays an important role to decomposition if its production is scaled to microbial biomass. In fact if microbes are allowed to optimize enzyme productivity the microbial enzyme model becomes unstable. Thus if the assumption of enzyme productivity is relaxed, other limiting factors must come into play. To stabilize the model, we account for two feedbacks that include cost of enzyme production and diminishing return of depolymerization with increasing enzyme concentration and activity. These feedback mechanisms caused the model to behave in a similar way to traditional, first order decay models. Most importantly, we found, that under warming, the changes in SOC carbon were more severe in enzyme synthesis is costly. In turn, carbon use efficiency (CUE) and its dynamical response to temperature is mainly determined by 1) the rate of turnover of microbes 2) the partitioning of dead microbial matter into different quality pools, and 3) and whether growth, maintenance respiration and microbial death rate have distinct responses to changes in temperature. Abbreviations: p: decay of enzyme, g: coefficient for growth respiration, : fraction of material from microbial turnover that enters the DOC pool, loss of C scaled to microbial mass, half saturation constant.

Effects of Land Use Change on C-N cycling: Microbes Matter.

NASA Astrophysics Data System (ADS)

Hofmockel, K.

2012-12-01

Large swaths of the terrestrial landscape have been altered by human actions on Earth's biophysical systems, resulting in the homogenization of Earth's biota, while simultaneously increasing greenhouse gases and reactive nitrogen (N). This is especially poignant in grasslands that have been largely replaced by managed agricultural systems with substantial N inputs, or by unmanaged grasslands that are dominated by exotic species. Impacted ecosystems may be important for global C models, because they comprise a major portion of the global land area, terrestrial NPP and the world's soil C stocks. This research investigates how anthropogenic changes in plant community composition and agricultural management systems influence the composition and function of microbial communities that mediate key aspects of belowground C and N cycling and storage. Data from agroecology and grassland climate change experiments are used to illustrate how microbial responses can have important implications for large scale coupling of C and N cycles. In this study exotic plant species significantly decreased root inputs, causing shifts in microbial community composition, including both specific taxa and functional guilds of bacteria. By contrast, climate change (precipitation manipulation) caused functional responses (increased carbon and phosphorus cycling) that were not detected in the microbial community composition. Mycorrhizal fungi in managed systems were responsive to both root biomass and nitrogen inputs, significantly altering hydrolytic enzyme activity and aggregate turnover. Collectively small-scale processes can alter the ecosystem biogeochemical cycles. Together theses results suggest that linking microbial communities to coupled C-N cycles may have important implications for terrestrial C cycling feedbacks that are an integral part of the anthropocene era.

Effects of copper particles on a model septic system's function and microbial community.

PubMed

Taylor, Alicia A; Walker, Sharon L

2016-03-15

There is concern surrounding the addition of nanoparticles into consumer products due to toxicity potential and the increased risk of human and environmental exposures to these particles. Copper nanoparticles are found in many common consumer goods; therefore, the disposal and subsequent interactions between potentially toxic Cu-based nanoparticles and microbial communities may have detrimental impacts on wastewater treatment processes. This study investigates the effects of three copper particles (micron- and nano-scale Cu particles, and a nano-scale Cu(OH)2-based fungicide) on the function and operation of a model septic tank. Septic system analyses included water quality evaluations and microbial community characterizations to detect changes in and relationships between the septic tank function and microbial community phenotype/genotype. As would be expected for optimal wastewater treatment, biological oxygen demand (BOD5) was reduced by at least 63% during nano-scale Cu exposure, indicating normal function. pH was reduced to below the optimum anaerobic fermentation range during the micro Cu exposure, suggesting incomplete degradation of organic waste may have occurred. The copper fungicide, Cu(OH)2, caused a 57% increase in total organic carbon (TOC), which is well above the typical range for septic systems and also corresponded to increased BOD5 during the majority of the Cu(OH)2 exposure. The changes in TOC and BOD5 demonstrate that the system was improperly treating waste. Overall, results imply individual exposures to the three Cu particles caused distinct disruptions in septic tank function. However, it was observed that the system was able to recover to typical operating conditions after three weeks post-exposure. These results imply that during periods of Cu introduction, there are likely pulses of improper removal of total organic carbon and significant changes in pH not in the optimal range for the system. Copyright © 2016 Elsevier Ltd. All rights reserved.

The Basics of Bacteriuria: Strategies of Microbes for Persistence in Urine

PubMed Central

Ipe, Deepak S.; Horton, Ella; Ulett, Glen C.

2016-01-01

Bacteriuria, the presence of bacteria in urine, is associated with asymptomatic, as well as symptomatic, urinary tract infection (UTI). Bacteriuria underpins some of the dynamics of microbial colonization of the urinary tract, and probably impacts the progression and persistence of infection in some individuals. Recent molecular discoveries in vitro have elucidated how some key bacterial traits can enable organisms to survive and grow in human urine as a means of microbial fitness adaptation for UTI. Several microbial characteristics that confer bacteruric potential have been identified including de novo synthesis of guanine, relative resistance to D-serine, and catabolism of malic acid. Microbial characteristics such as these are increasingly being defined through the use of synthetic human urine (SHU) in vitro as a model to mimic the in vivo environment that bacteria encounter in the bladder. There is considerable variation in the SHU model systems that have been used to study bacteriuria to date, and this influences the utility of these models. In this review, we discuss recent advances in our understanding of bacteruric potential with a focus on the specific mechanisms underlying traits that promote the growth of bacteria in urine. We also review the application of SHU in research studies modeling UTI and discuss the chemical makeup, and benefits and limitations that are encountered in utilizing SHU to study bacterial growth in urine in vitro. PMID:26904513

The Basics of Bacteriuria: Strategies of Microbes for Persistence in Urine.

PubMed

Ipe, Deepak S; Horton, Ella; Ulett, Glen C

2016-01-01

Bacteriuria, the presence of bacteria in urine, is associated with asymptomatic, as well as symptomatic, urinary tract infection (UTI). Bacteriuria underpins some of the dynamics of microbial colonization of the urinary tract, and probably impacts the progression and persistence of infection in some individuals. Recent molecular discoveries in vitro have elucidated how some key bacterial traits can enable organisms to survive and grow in human urine as a means of microbial fitness adaptation for UTI. Several microbial characteristics that confer bacteruric potential have been identified including de novo synthesis of guanine, relative resistance to D-serine, and catabolism of malic acid. Microbial characteristics such as these are increasingly being defined through the use of synthetic human urine (SHU) in vitro as a model to mimic the in vivo environment that bacteria encounter in the bladder. There is considerable variation in the SHU model systems that have been used to study bacteriuria to date, and this influences the utility of these models. In this review, we discuss recent advances in our understanding of bacteruric potential with a focus on the specific mechanisms underlying traits that promote the growth of bacteria in urine. We also review the application of SHU in research studies modeling UTI and discuss the chemical makeup, and benefits and limitations that are encountered in utilizing SHU to study bacterial growth in urine in vitro.

Satellite remote sensing data can be used to model marine microbial metabolite turnover

PubMed Central

Larsen, Peter E; Scott, Nicole; Post, Anton F; Field, Dawn; Knight, Rob; Hamada, Yuki; Gilbert, Jack A

2015-01-01

Sampling ecosystems, even at a local scale, at the temporal and spatial resolution necessary to capture natural variability in microbial communities are prohibitively expensive. We extrapolated marine surface microbial community structure and metabolic potential from 72 16S rRNA amplicon and 8 metagenomic observations using remotely sensed environmental parameters to create a system-scale model of marine microbial metabolism for 5904 grid cells (49 km2) in the Western English Chanel, across 3 years of weekly averages. Thirteen environmental variables predicted the relative abundance of 24 bacterial Orders and 1715 unique enzyme-encoding genes that encode turnover of 2893 metabolites. The genes' predicted relative abundance was highly correlated (Pearson Correlation 0.72, P-value <10−6) with their observed relative abundance in sequenced metagenomes. Predictions of the relative turnover (synthesis or consumption) of CO2 were significantly correlated with observed surface CO2 fugacity. The spatial and temporal variation in the predicted relative abundances of genes coding for cyanase, carbon monoxide and malate dehydrogenase were investigated along with the predicted inter-annual variation in relative consumption or production of ∼3000 metabolites forming six significant temporal clusters. These spatiotemporal distributions could possibly be explained by the co-occurrence of anaerobic and aerobic metabolisms associated with localized plankton blooms or sediment resuspension, which facilitate the presence of anaerobic micro-niches. This predictive model provides a general framework for focusing future sampling and experimental design to relate biogeochemical turnover to microbial ecology. PMID:25072414

Satellite remote sensing data can be used to model marine microbial metabolite turnover

DOE Office of Scientific and Technical Information (OSTI.GOV)

Larsen, Peter E.; Scott, Nicole; Post, Anton F.

Sampling ecosystems, even at a local scale, at the temporal and spatial resolution necessary to capture natural variability in microbial communities are prohibitively expensive. We extrapolated marine surface microbial community structure and metabolic potential from 72 16S rRNA amplicon and 8 metagenomic observations using remotely sensed environmental parameters to create a system-scale model of marine microbial metabolism for 5904 grid cells (49 km2) in the Western English Chanel, across 3 years of weekly averages. Thirteen environmental variables predicted the relative abundance of 24 bacterial Orders and 1715 unique enzyme-encoding genes that encode turnover of 2893 metabolites. The genes’ predicted relativemore » abundance was highly correlated (Pearson Correlation 0.72, P-value <10-6) with their observed relative abundance in sequenced metagenomes. Predictions of the relative turnover (synthesis or consumption) of CO2 were significantly correlated with observed surface CO2 fugacity. The spatial and temporal variation in the predicted relative abundances of genes coding for cyanase, carbon monoxide and malate dehydrogenase were investigated along with the predicted inter-annual variation in relative consumption or production of ~3000 metabolites forming six significant temporal clusters. These spatiotemporal distributions could possibly be explained by the co-occurrence of anaerobic and aerobic metabolisms associated with localized plankton blooms or sediment resuspension, which facilitate the presence of anaerobic micro-niches. This predictive model provides a general framework for focusing future sampling and experimental design to relate biogeochemical turnover to microbial ecology.« less

Final Report for Project "A high-throughput pipeline for mapping inter-species interactions and metabolic synergy relevant to next-generation biofuel production"

DOE Office of Scientific and Technical Information (OSTI.GOV)

Segre, Daniel; Marx, Christopher J.; Northen, Trent

The goal of our project was to implement a pipeline for the systematic, computationally-driven study and optimization of microbial interactions and their effect on lignocellulose degradation and biofuel production. We specifically sought to design and construct artificial microbial consortia that could collectively degrade lignocellulose from plant biomass, and produce precursors of energy-rich biofuels. This project fits into the bigger picture goal of helping identify a sustainable strategy for the production of energy-rich biofuels that would satisfy the existing energy constraints and demand of our society. Based on the observation that complex natural microbial communities tend to be metabolically efficient andmore » ecologically robust, we pursued the study of a microbial system in which the desired engineering function is achieved through division of labor across multiple microbial species. Our approach was aimed at bypassing the complexity of natural communities by establishing a rational approach to design small synthetic microbial consortia. Towards this goal, we combined multiple approaches, including computer modeling of ecosystem-level microbial metabolism, mass spectrometry of metabolites, genetic engineering, and experimental evolution. The microbial production of biofuels from lignocellulose is a complex, multi-step process. Microbial consortia are an ideal approach to consolidated bioprocessing: a community of microorganisms performs a wide variety of functions more efficiently and is more resilient to environmental perturbations than a microbial monoculture. Each organism we chose for this project addresses a specific challenge: lignin degradation (Pseudomonas putida); (hemi)cellulose degradation (Cellulomonas fimi); lignin degradation product demethoxylation (Methylobacterium spp); generation of biofuel lipid precursors (Yarrowia lipolytica). These organisms are genetically tractable, aerobic, and have been used in biotechnological applications. Throughout the project, we have used mass spectrometry to characterize and measure the metabolic inputs and outputs of each of these consortium members, providing valuable information for model refinement, and enabling the establishment of metabolism-mediated interactions. In addition to lignocellulose degradation, we have started addressing the challenge of removing metabolites (e.g. formaldehyde) produced by the demethoxylation of lignin monomers, which can otherwise inhibit microbial growth due to their toxicity. On the computational side, we have implemented genome-scale models for all consortium members, based on KBase reconstructions and literature curation, and we studied small consortia and their properties. Overall, our project has identified a complex landscape of interactions types and metabolic processes relevant to community-level functions, illustrating the challenges and opportunities of microbial community engineering for the transformation of biomass into bioproducts.« less

Perspective for Aquaponic Systems: "Omic" Technologies for Microbial Community Analysis.

PubMed

Munguia-Fragozo, Perla; Alatorre-Jacome, Oscar; Rico-Garcia, Enrique; Torres-Pacheco, Irineo; Cruz-Hernandez, Andres; Ocampo-Velazquez, Rosalia V; Garcia-Trejo, Juan F; Guevara-Gonzalez, Ramon G

2015-01-01

Aquaponics is the combined production of aquaculture and hydroponics, connected by a water recirculation system. In this productive system, the microbial community is responsible for carrying out the nutrient dynamics between the components. The nutrimental transformations mainly consist in the transformation of chemical species from toxic compounds into available nutrients. In this particular field, the microbial research, the "Omic" technologies will allow a broader scope of studies about a current microbial profile inside aquaponics community, even in those species that currently are unculturable. This approach can also be useful to understand complex interactions of living components in the system. Until now, the analog studies were made to set up the microbial characterization on recirculation aquaculture systems (RAS). However, microbial community composition of aquaponics is still unknown. "Omic" technologies like metagenomic can help to reveal taxonomic diversity. The perspectives are also to begin the first attempts to sketch the functional diversity inside aquaponic systems and its ecological relationships. The knowledge of the emergent properties inside the microbial community, as well as the understanding of the biosynthesis pathways, can derive in future biotechnological applications. Thus, the aim of this review is to show potential applications of current "Omic" tools to characterize the microbial community in aquaponic systems.

Agent-based model of fecal microbial transplant effect on bile acid metabolism on suppressing Clostridium difficile infection: an example of agent-based modeling of intestinal bacterial infection.

PubMed

Peer, Xavier; An, Gary

2014-10-01

Agent-based modeling is a computational modeling method that represents system-level behavior as arising from multiple interactions between the multiple components that make up a system. Biological systems are thus readily described using agent-based models (ABMs), as multi-cellular organisms can be viewed as populations of interacting cells, and microbial systems manifest as colonies of individual microbes. Intersections between these two domains underlie an increasing number of pathophysiological processes, and the intestinal tract represents one of the most significant locations for these inter-domain interactions, so much so that it can be considered an internal ecology of varying robustness and function. Intestinal infections represent significant disturbances of this internal ecology, and one of the most clinically relevant intestinal infections is Clostridium difficile infection (CDI). CDI is precipitated by the use of broad-spectrum antibiotics, involves the depletion of commensal microbiota, and alterations in bile acid composition in the intestinal lumen. We present an example ABM of CDI (the C. difficile Infection ABM, or CDIABM) to examine fundamental dynamics of the pathogenesis of CDI and its response to treatment with anti-CDI antibiotics and a newer treatment therapy, fecal microbial transplant. The CDIABM focuses on one specific mechanism of potential CDI suppression: commensal modulation of bile acid composition. Even given its abstraction, the CDIABM reproduces essential dynamics of CDI and its response to therapy, and identifies a paradoxical zone of behavior that provides insight into the role of intestinal nutritional status and the efficacy of anti-CDI therapies. It is hoped that this use case example of the CDIABM can demonstrate the usefulness of both agent-based modeling and the application of abstract functional representation as the biomedical community seeks to address the challenges of increasingly complex diseases with the goal of personalized medicine.

Agent-based model of Fecal Microbial Transplant effect on Bile Acid Metabolism on suppressing Clostridium difficile infection: an example of agent-based modeling of intestinal bacterial infection

PubMed Central

Peer, Xavier; An, Gary

2014-01-01

Agent-based modeling is a computational modeling method that represents system-level behavior as arising from multiple interactions between the multiple components that make up a system. Biological systems are thus readily described using agent-based models (ABMs), as multi-cellular organisms can be viewed as populations of interacting cells, and microbial systems manifest as colonies of individual microbes. Intersections between these two domains underlie an increasing number of pathophysiological processes, and the intestinal tract represents one of the most significant locations for these inter-domain interactions, so much so that it can be considered an internal ecology of varying robustness and function. Intestinal infections represent significant disturbances of this internal ecology, and one of the most clinically relevant intestinal infections is Clostridium difficile infection (CDI). CDI is precipitated by the use of broad-spectrum antibiotics, involves the depletion of commensal microbiota, and alterations in bile acid composition in the intestinal lumen. We present an example ABM of CDI (the Clostridium difficile Infection ABM, or CDIABM) to examine fundamental dynamics of the pathogenesis of CDI and its response to treatment with anti-CDI antibiotics and a newer treatment therapy, Fecal Microbial Transplant (FMT). The CDIABM focuses on one specific mechanism of potential CDI suppression: commensal modulation of bile acid composition. Even given its abstraction, the CDIABM reproduces essential dynamics of CDI and its response to therapy, and identifies a paradoxical zone of behavior that provides insight into the role of intestinal nutritional status and the efficacy of anti-CDI therapies. It is hoped that this use case example of the CDIABM can demonstrate the usefulness of both agent-based modeling and the application of abstract functional representation as the biomedical community seeks to address the challenges of increasingly complex diseases with the goal of personalized medicine. PMID:25168489

Systematic discovery of antiphage defense systems in the microbial pangenome.

PubMed

Doron, Shany; Melamed, Sarah; Ofir, Gal; Leavitt, Azita; Lopatina, Anna; Keren, Mai; Amitai, Gil; Sorek, Rotem

2018-03-02

The arms race between bacteria and phages led to the development of sophisticated antiphage defense systems, including CRISPR-Cas and restriction-modification systems. Evidence suggests that known and unknown defense systems are located in "defense islands" in microbial genomes. Here, we comprehensively characterized the bacterial defensive arsenal by examining gene families that are clustered next to known defense genes in prokaryotic genomes. Candidate defense systems were systematically engineered and validated in model bacteria for their antiphage activities. We report nine previously unknown antiphage systems and one antiplasmid system that are widespread in microbes and strongly protect against foreign invaders. These include systems that adopted components of the bacterial flagella and condensin complexes. Our data also suggest a common, ancient ancestry of innate immunity components shared between animals, plants, and bacteria. Copyright © 2018 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.

Microbes as engines of ecosystem function: When does community structure enhance predictions of ecosystem processes?

DOE PAGES

Graham, Emily B.; Knelman, Joseph E.; Schindlbacher, Andreas; ...

2016-02-24

In this study, microorganisms are vital in mediating the earth’s biogeochemical cycles; yet, despite our rapidly increasing ability to explore complex environmental microbial communities, the relationship between microbial community structure and ecosystem processes remains poorly understood. Here, we address a fundamental and unanswered question in microbial ecology: ‘When do we need to understand microbial community structure to accurately predict function?’ We present a statistical analysis investigating the value of environmental data and microbial community structure independently and in combination for explaining rates of carbon and nitrogen cycling processes within 82 global datasets. Environmental variables were the strongest predictors of processmore » rates but left 44% of variation unexplained on average, suggesting the potential for microbial data to increase model accuracy. Although only 29% of our datasets were significantly improved by adding information on microbial community structure, we observed improvement in models of processes mediated by narrow phylogenetic guilds via functional gene data, and conversely, improvement in models of facultative microbial processes via community diversity metrics. Our results also suggest that microbial diversity can strengthen predictions of respiration rates beyond microbial biomass parameters, as 53% of models were improved by incorporating both sets of predictors compared to 35% by microbial biomass alone. Our analysis represents the first comprehensive analysis of research examining links between microbial community structure and ecosystem function. Taken together, our results indicate that a greater understanding of microbial communities informed by ecological principles may enhance our ability to predict ecosystem process rates relative to assessments based on environmental variables and microbial physiology.« less

Microbes as engines of ecosystem function: When does community structure enhance predictions of ecosystem processes?

DOE Office of Scientific and Technical Information (OSTI.GOV)

Graham, Emily B.; Knelman, Joseph E.; Schindlbacher, Andreas

In this study, microorganisms are vital in mediating the earth’s biogeochemical cycles; yet, despite our rapidly increasing ability to explore complex environmental microbial communities, the relationship between microbial community structure and ecosystem processes remains poorly understood. Here, we address a fundamental and unanswered question in microbial ecology: ‘When do we need to understand microbial community structure to accurately predict function?’ We present a statistical analysis investigating the value of environmental data and microbial community structure independently and in combination for explaining rates of carbon and nitrogen cycling processes within 82 global datasets. Environmental variables were the strongest predictors of processmore » rates but left 44% of variation unexplained on average, suggesting the potential for microbial data to increase model accuracy. Although only 29% of our datasets were significantly improved by adding information on microbial community structure, we observed improvement in models of processes mediated by narrow phylogenetic guilds via functional gene data, and conversely, improvement in models of facultative microbial processes via community diversity metrics. Our results also suggest that microbial diversity can strengthen predictions of respiration rates beyond microbial biomass parameters, as 53% of models were improved by incorporating both sets of predictors compared to 35% by microbial biomass alone. Our analysis represents the first comprehensive analysis of research examining links between microbial community structure and ecosystem function. Taken together, our results indicate that a greater understanding of microbial communities informed by ecological principles may enhance our ability to predict ecosystem process rates relative to assessments based on environmental variables and microbial physiology.« less

Microbes as Engines of Ecosystem Function: When Does Community Structure Enhance Predictions of Ecosystem Processes?

PubMed Central

Graham, Emily B.; Knelman, Joseph E.; Schindlbacher, Andreas; Siciliano, Steven; Breulmann, Marc; Yannarell, Anthony; Beman, J. M.; Abell, Guy; Philippot, Laurent; Prosser, James; Foulquier, Arnaud; Yuste, Jorge C.; Glanville, Helen C.; Jones, Davey L.; Angel, Roey; Salminen, Janne; Newton, Ryan J.; Bürgmann, Helmut; Ingram, Lachlan J.; Hamer, Ute; Siljanen, Henri M. P.; Peltoniemi, Krista; Potthast, Karin; Bañeras, Lluís; Hartmann, Martin; Banerjee, Samiran; Yu, Ri-Qing; Nogaro, Geraldine; Richter, Andreas; Koranda, Marianne; Castle, Sarah C.; Goberna, Marta; Song, Bongkeun; Chatterjee, Amitava; Nunes, Olga C.; Lopes, Ana R.; Cao, Yiping; Kaisermann, Aurore; Hallin, Sara; Strickland, Michael S.; Garcia-Pausas, Jordi; Barba, Josep; Kang, Hojeong; Isobe, Kazuo; Papaspyrou, Sokratis; Pastorelli, Roberta; Lagomarsino, Alessandra; Lindström, Eva S.; Basiliko, Nathan; Nemergut, Diana R.

2016-01-01

Microorganisms are vital in mediating the earth’s biogeochemical cycles; yet, despite our rapidly increasing ability to explore complex environmental microbial communities, the relationship between microbial community structure and ecosystem processes remains poorly understood. Here, we address a fundamental and unanswered question in microbial ecology: ‘When do we need to understand microbial community structure to accurately predict function?’ We present a statistical analysis investigating the value of environmental data and microbial community structure independently and in combination for explaining rates of carbon and nitrogen cycling processes within 82 global datasets. Environmental variables were the strongest predictors of process rates but left 44% of variation unexplained on average, suggesting the potential for microbial data to increase model accuracy. Although only 29% of our datasets were significantly improved by adding information on microbial community structure, we observed improvement in models of processes mediated by narrow phylogenetic guilds via functional gene data, and conversely, improvement in models of facultative microbial processes via community diversity metrics. Our results also suggest that microbial diversity can strengthen predictions of respiration rates beyond microbial biomass parameters, as 53% of models were improved by incorporating both sets of predictors compared to 35% by microbial biomass alone. Our analysis represents the first comprehensive analysis of research examining links between microbial community structure and ecosystem function. Taken together, our results indicate that a greater understanding of microbial communities informed by ecological principles may enhance our ability to predict ecosystem process rates relative to assessments based on environmental variables and microbial physiology. PMID:26941732

Microbes as Engines of Ecosystem Function: When Does Community Structure Enhance Predictions of Ecosystem Processes?

PubMed

Graham, Emily B; Knelman, Joseph E; Schindlbacher, Andreas; Siciliano, Steven; Breulmann, Marc; Yannarell, Anthony; Beman, J M; Abell, Guy; Philippot, Laurent; Prosser, James; Foulquier, Arnaud; Yuste, Jorge C; Glanville, Helen C; Jones, Davey L; Angel, Roey; Salminen, Janne; Newton, Ryan J; Bürgmann, Helmut; Ingram, Lachlan J; Hamer, Ute; Siljanen, Henri M P; Peltoniemi, Krista; Potthast, Karin; Bañeras, Lluís; Hartmann, Martin; Banerjee, Samiran; Yu, Ri-Qing; Nogaro, Geraldine; Richter, Andreas; Koranda, Marianne; Castle, Sarah C; Goberna, Marta; Song, Bongkeun; Chatterjee, Amitava; Nunes, Olga C; Lopes, Ana R; Cao, Yiping; Kaisermann, Aurore; Hallin, Sara; Strickland, Michael S; Garcia-Pausas, Jordi; Barba, Josep; Kang, Hojeong; Isobe, Kazuo; Papaspyrou, Sokratis; Pastorelli, Roberta; Lagomarsino, Alessandra; Lindström, Eva S; Basiliko, Nathan; Nemergut, Diana R

2016-01-01

Microorganisms are vital in mediating the earth's biogeochemical cycles; yet, despite our rapidly increasing ability to explore complex environmental microbial communities, the relationship between microbial community structure and ecosystem processes remains poorly understood. Here, we address a fundamental and unanswered question in microbial ecology: 'When do we need to understand microbial community structure to accurately predict function?' We present a statistical analysis investigating the value of environmental data and microbial community structure independently and in combination for explaining rates of carbon and nitrogen cycling processes within 82 global datasets. Environmental variables were the strongest predictors of process rates but left 44% of variation unexplained on average, suggesting the potential for microbial data to increase model accuracy. Although only 29% of our datasets were significantly improved by adding information on microbial community structure, we observed improvement in models of processes mediated by narrow phylogenetic guilds via functional gene data, and conversely, improvement in models of facultative microbial processes via community diversity metrics. Our results also suggest that microbial diversity can strengthen predictions of respiration rates beyond microbial biomass parameters, as 53% of models were improved by incorporating both sets of predictors compared to 35% by microbial biomass alone. Our analysis represents the first comprehensive analysis of research examining links between microbial community structure and ecosystem function. Taken together, our results indicate that a greater understanding of microbial communities informed by ecological principles may enhance our ability to predict ecosystem process rates relative to assessments based on environmental variables and microbial physiology.

Reduction of Microbial Contaminants in Drinking Water by Ultraviolet Light Technology: ETS UV MODEL UVL-200-4 (Report and Statement)

EPA Science Inventory

Final technical report provides test methods used and verification results to be published on ETV web sites. The ETS UV System Model UVL-200-4 was tested to validate the UV dose delivered by the system using biodosimetry and a set line approach. The set line for 40 mJ/cm2 Red...

The Earth Microbiome Project and modeling the planets microbial potential (Invited)

NASA Astrophysics Data System (ADS)

Gilbert, J. A.

2013-12-01

The understanding of Earth's climate and ecology requires multiscale observations of the biosphere, of which microbial life are a major component. However, to acquire and process physical samples of soil, water and air that comprise the appropriate spatial and temporal resolution to capture the immense variation in microbial dynamics, would require a herculean effort and immense financial resources dwarfing even the most ambitious projects to date. To overcome this hurdle we created the Earth Microbiome Project, a crowd-sourced effort to acquire physical samples from researchers around the world that are, importantly, contextualized with physical, chemical and biological data detailing the environmental properties of that sample in the location and time it was acquired. The EMP leverages these existing efforts to target a systematic analysis of microbial taxonomic and functional dynamics across a vast array of environmental parameter gradients. The EMP captures the environmental gradients, location, time and sampling protocol information about every sample donated by our valued collaborators. Physical samples are then processed using a standardized DNA extraction, PCR, and shotgun sequencing protocol to generate comparable data regarding the microbial community structure and function in each sample. To date we have processed >17,000 samples from 40 different biomes. One of the key goals of the EMP is to map the spatiotemporal variability of microbial communities to capture the changes in important functional processes that need to be appropriately expressed in models to provide reliable forecasts of ecosystem phenotype across our changing planet. This is essential if we are to develop economically sound strategies to be good stewards of our Earth. The EMP recognizes that environments are comprised of complex sets of interdependent parameters and that the development of useful predictive computational models of both terrestrial and atmospheric systems requires recognition and accommodation of sources of uncertainty.

PhyloChip microarray analysis reveals altered gastrointestinal microbial communities in a rat model of colonic hypersensitivity

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nelson, T.A.; Holmes, S.; Alekseyenko, A.V.

Irritable bowel syndrome (IBS) is a chronic, episodic gastrointestinal disorder that is prevalent in a significant fraction of western human populations; and changes in the microbiota of the large bowel have been implicated in the pathology of the disease. Using a novel comprehensive, high-density DNA microarray (PhyloChip) we performed a phylogenetic analysis of the microbial community of the large bowel in a rat model in which intracolonic acetic acid in neonates was used to induce long lasting colonic hypersensitivity and decreased stool water content and frequency, representing the equivalent of human constipation-predominant IBS. Our results revealed a significantly increased compositionalmore » difference in the microbial communities in rats with neonatal irritation as compared with controls. Even more striking was the dramatic change in the ratio of Firmicutes relative to Bacteroidetes, where neonatally irritated rats were enriched more with Bacteroidetes and also contained a different composition of species within this phylum. Our study also revealed differences at the level of bacterial families and species. The PhyloChip is a useful and convenient method to study enteric microflora. Further, this rat model system may be a useful experimental platform to study the causes and consequences of changes in microbial community composition associated with IBS.« less

Colors of the Yellowstone thermal pools for teaching optics

NASA Astrophysics Data System (ADS)

Shaw, J. A.; Nugent, P. W.; Vollmer, M.

2015-10-01

Nature provides many beautiful optical phenomena that can be used to teach optical principles. Here we describe an interdisciplinary education project based on a simple computer model of the colors observed in the famous thermal pools of Yellowstone National Park in the northwestern United States. The primary wavelength-dependent parameters that determine the widely varying pool colors are the reflectance of the rocks or the microbial mats growing on the rocks beneath the water (the microbial mat color depends on water temperature) and optical absorption and scattering in the water. This paper introduces a teaching module based on a one-dimensional computer model that starts with measured reflectance spectra of the microbial mats and modifies the spectra with depth-dependent absorption and scattering in the water. This module is designed to be incorporated into a graduate course on remote sensing systems, in a section covering the propagation of light through air and water, although it could be adapted to a general university optics course. The module presents the basic 1-D radiative transfer equation relevant to this problem, and allows them to build their own simple model. Students can then simulate the colors that would be observed for different variations of the microbial mat reflectance spectrum, skylight spectrum, and water depth.

Persistence of Soil Organic Carbon can be Explained as an Emergent Property of Microbial Ecology and Population Dynamics

NASA Astrophysics Data System (ADS)

Woolf, D.; Lehmann, J.

2016-12-01

The exchange of carbon between soils and the atmosphere represents an important uncertainty in climate predictions. Current Earth system models apply soil organic matter (SOM) models based on independent carbon pools with 1st order decomposition dynamics. It has been widely argued over the last decade that such models do not accurately describe soil processes and mechanisms. For example, the long term persistence of soil organic carbon (SOC) is only adequately described by such models by the post hoc assumption of passive or inert carbon pools. Further, such 1st order models also fail to account for microbially-mediated dynamics such as priming interactions. These shortcomings may limit their applicability to long term predictions under conditions of global environmental change. In addition to incorporating recent conceptual advances in the mechanisms of SOM decomposition and protection, next-generation SOM models intended for use in Earth system models need to meet further quality criteria. Namely, that they should (a) accurately describe historical data from long term trials and the current global distribution of soil organic carbon, (b) be computationally efficient for large number of iterations involved in climate modeling, and (c) have sufficiently simple parameterization that they can be run on spatially-explicit data available at global scale under varying conditions of global change over long time scales. Here we show that linking fundamental ecological principles and microbial population dynamics to SOC turnover rates results in a dynamic model that meets all of these quality criteria. This approach simultaneously eliminates the need to postulate biogeochemically-implausible passive or inert pools, instead showing how SOM persistence emerges from ecological principles, while also reproducing observed priming interactions.

Kinetic models for nitrogen inhibition in ANAMMOX process on deammonification system

USDA-ARS?s Scientific Manuscript database

The performance of the deammonification process depends on the microbial activity of ammonia oxidizing bacteria (AOB) and ANAMMOX bacteria, and the autotrophic organisms involved in this process have different preferences for substrate, that may cause inhibition or imbalance of the system. The aim o...

Microbial Fuel Cells and Microbial Ecology: Applications in Ruminant Health and Production Research

PubMed Central

Osterstock, Jason B.; Pinchak, William E.; Ishii, Shun’ichi; Nelson, Karen E.

2009-01-01

Microbial fuel cell (MFC) systems employ the catalytic activity of microbes to produce electricity from the oxidation of organic, and in some cases inorganic, substrates. MFC systems have been primarily explored for their use in bioremediation and bioenergy applications; however, these systems also offer a unique strategy for the cultivation of synergistic microbial communities. It has been hypothesized that the mechanism(s) of microbial electron transfer that enable electricity production in MFCs may be a cooperative strategy within mixed microbial consortia that is associated with, or is an alternative to, interspecies hydrogen (H2) transfer. Microbial fermentation processes and methanogenesis in ruminant animals are highly dependent on the consumption and production of H2in the rumen. Given the crucial role that H2 plays in ruminant digestion, it is desirable to understand the microbial relationships that control H2 partial pressures within the rumen; MFCs may serve as unique tools for studying this complex ecological system. Further, MFC systems offer a novel approach to studying biofilms that form under different redox conditions and may be applied to achieve a greater understanding of how microbial biofilms impact animal health. Here, we present a brief summary of the efforts made towards understanding rumen microbial ecology, microbial biofilms related to animal health, and how MFCs may be further applied in ruminant research. PMID:20024685

A Natural View of Microbial Biodiversity within Hot Spring Cyanobacterial Mat Communities

PubMed Central

Ward, David M.; Ferris, Michael J.; Nold, Stephen C.; Bateson, Mary M.

1998-01-01

This review summarizes a decade of research in which we have used molecular methods, in conjunction with more traditional approaches, to study hot spring cyanobacterial mats as models for understanding principles of microbial community ecology. Molecular methods reveal that the composition of these communities is grossly oversimplified by microscopic and cultivation methods. For example, none of 31 unique 16S rRNA sequences detected in the Octopus Spring mat, Yellowstone National Park, matches that of any prokaryote previously cultivated from geothermal systems; 11 are contributed by genetically diverse cyanobacteria, even though a single cyanobacterial species was suspected based on morphologic and culture analysis. By studying the basis for the incongruity between culture and molecular samplings of community composition, we are beginning to cultivate isolates whose 16S rRNA sequences are readily detected. By placing the genetic diversity detected in context with the well-defined natural environmental gradients typical of hot spring mat systems, the relationship between gene and species diversity is clarified and ecological patterns of species occurrence emerge. By combining these ecological patterns with the evolutionary patterns inherently revealed by phylogenetic analysis of gene sequence data, we find that it may be possible to understand microbial biodiversity within these systems by using principles similar to those developed by evolutionary ecologists to understand biodiversity of larger species. We hope that such an approach guides microbial ecologists to a more realistic and predictive understanding of microbial species occurrence and responsiveness in both natural and disturbed habitats. PMID:9841675

A natural view of microbial biodiversity within hot spring cyanobacterial mat communities

NASA Technical Reports Server (NTRS)

Ward, D. M.; Ferris, M. J.; Nold, S. C.; Bateson, M. M.

1998-01-01

This review summarizes a decade of research in which we have used molecular methods, in conjunction with more traditional approaches, to study hot spring cyanobacterial mats as models for understanding principles of microbial community ecology. Molecular methods reveal that the composition of these communities is grossly oversimplified by microscopic and cultivation methods. For example, none of 31 unique 16S rRNA sequences detected in the Octopus Spring mat, Yellowstone National Park, matches that of any prokaryote previously cultivated from geothermal systems; 11 are contributed by genetically diverse cyanobacteria, even though a single cyanobacterial species was suspected based on morphologic and culture analysis. By studying the basis for the incongruity between culture and molecular samplings of community composition, we are beginning to cultivate isolates whose 16S rRNA sequences are readily detected. By placing the genetic diversity detected in context with the well-defined natural environmental gradients typical of hot spring mat systems, the relationship between gene and species diversity is clarified and ecological patterns of species occurrence emerge. By combining these ecological patterns with the evolutionary patterns inherently revealed by phylogenetic analysis of gene sequence data, we find that it may be possible to understand microbial biodiversity within these systems by using principles similar to those developed by evolutionary ecologists to understand biodiversity of larger species. We hope that such an approach guides microbial ecologists to a more realistic and predictive understanding of microbial species occurrence and responsiveness in both natural and disturbed habitats.

A methodology for a quantitative interpretation of DGGE with the help of mathematical modelling: application in biohydrogen production.

PubMed

Tapia, Estela; Donoso-Bravo, Andres; Cabrol, Léa; Alves, Madalena; Pereira, Alcina; Rapaport, Alain; Ruiz-Filippi, Gonzalo

2014-01-01

Molecular biology techniques provide valuable insights in the investigation of microbial dynamics and evolution. Denaturing gradient gel electrophoresis (DGGE) analysis is one of the most popular methods which have been used in bioprocess assessment. Most of the anaerobic digestion models consider several microbial populations as state variables. However, the difficulty of measuring individual species concentrations may cause inaccurate model predictions. The integration of microbial data and ecosystem modelling is currently a challenging issue for improved system control. A novel procedure that combines common experimental measurements, DGGE, and image analysis is presented in this study in order to provide a preliminary estimation of the actual concentration of the dominant bacterial ribotypes in a bioreactor, for further use as a variable in mathematical modelling of the bioprocess. This approach was applied during the start-up of a continuous anaerobic bioreactor for hydrogen production. The experimental concentration data were used for determining the kinetic parameters of each species, by using a multi-species chemostat-model. The model was able to reproduce the global trend of substrate and biomass concentrations during the reactor start-up, and predicted in an acceptable way the evolution of each ribotype concentration, depicting properly specific ribotype selection and extinction.

Systems biology solutions for biochemical production challenges.

PubMed

Hansen, Anne Sofie Lærke; Lennen, Rebecca M; Sonnenschein, Nikolaus; Herrgård, Markus J

2017-06-01

There is an urgent need to significantly accelerate the development of microbial cell factories to produce fuels and chemicals from renewable feedstocks in order to facilitate the transition to a biobased society. Methods commonly used within the field of systems biology including omics characterization, genome-scale metabolic modeling, and adaptive laboratory evolution can be readily deployed in metabolic engineering projects. However, high performance strains usually carry tens of genetic modifications and need to operate in challenging environmental conditions. This additional complexity compared to basic science research requires pushing systems biology strategies to their limits and often spurs innovative developments that benefit fields outside metabolic engineering. Here we survey recent advanced applications of systems biology methods in engineering microbial production strains for biofuels and -chemicals. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Biological activity of the non-microbial fraction of kefir: antagonism against intestinal pathogens.

PubMed

Iraporda, Carolina; Abatemarco Júnior, Mário; Neumann, Elisabeth; Nunes, Álvaro Cantini; Nicoli, Jacques R; Abraham, Analía G; Garrote, Graciela L

2017-08-01

Kefir is a fermented milk obtained by the activity of kefir grains which are composed of lactic and acetic acid bacteria, and yeasts. Many beneficial health effects have been associated with kefir consumption such as stimulation of the immune system and inhibition of pathogenic microorganisms. The biological activity of kefir may be attributed to the presence of a complex microbiota as well as the microbial metabolites that are released during fermentation. The aim of this work was to characterise the non-microbial fraction of kefir and to study its antagonism against Escherichia coli, Salmonella spp. and Bacillus cereus. During milk fermentation there was a production of organic acids, mainly lactic and acetic acid, with a consequent decrease in pH and lactose content. The non-microbial fraction of kefir added to nutrient broth at concentrations above 75% v/v induced a complete inhibition of pathogenic growth that could be ascribed to the presence of un-dissociated lactic acid. In vitro assays using an intestinal epithelial cell model indicated that pre-incubation of cells with the non-microbial fraction of kefir did not modify the association/invasion of Salmonella whereas pre-incubation of Salmonella with this fraction under conditions that did not affect their viability significantly decreased the pathogen's ability to invade epithelial cells. Lactate exerted a protective effect against Salmonella in a mouse model, demonstrating the relevance of metabolites present in the non-microbial fraction of kefir produced during milk fermentation.

C, N and P stoichiometric mismatch between resources and consumers influence the dynamics of a marine microbial food web model and its response to atmospheric N and P inputs

NASA Astrophysics Data System (ADS)

Pondaven, P.; Pivière, P.; Ridame, C.; Guien, C.

2014-02-01

Results from the DUNE experiments reported in this issue have shown that nutrient input from dust deposition in large mesocosms deployed in the western Mediterranean induced a response of the microbial food web, with an increase of primary production rates (PP), bacterial respiration rates (BR), as well as autotrophic and heterotrophic biomasses. Additionally, it was found that nutrient inputs strengthened the net heterotrophy of the system, with NPP : BR ratios < 1. In this study we used a simple microbial food web model, inspired from previous modelling studies, to explore how C, N and P stoichiometric mismatch between producers and consumers along the food chain can influence the dynamics and the trophic status of the ecosystem. Attention was paid to the mechanisms involved in the balance between net autotrophy vs. net heterotrophy. Although the model was kept simple, predicted changes in biomass and PP were qualitatively consistent with observations from DUNE experiments. Additionally, the model shed light on how ecological stoichiometric mismatch between producers and consumers can control food web dynamics and drive the system toward net heterotrophy. In the model, net heterotrophy was notably driven by the parameterisation of the production and excretion of extra DOC from phytoplankton under nutrient-limited conditions. This mechanism yielded to high C : P and C : N ratios of the DOM pool, and subsequent postabsorptive respiration of C by bacteria. The model also predicted that nutrient inputs from dust strengthened the net heterotrophy of the system; a pattern also observed during two of the three DUNE experiments (P and Q). However, the model was not able to account for the low NPP : BR ratios (down to 0.1) recorded during the DUNE experiments. Possible mechanisms involved in this discrepancy were discussed.

Microbial Community and Functional Structure Significantly Varied among Distinct Types of Paddy Soils But Responded Differently along Gradients of Soil Depth Layers

PubMed Central

Bai, Ren; Wang, Jun-Tao; Deng, Ye; He, Ji-Zheng; Feng, Kai; Zhang, Li-Mei

2017-01-01

Paddy rice fields occupy broad agricultural area in China and cover diverse soil types. Microbial community in paddy soils is of great interest since many microorganisms are involved in soil functional processes. In the present study, Illumina Mi-Seq sequencing and functional gene array (GeoChip 4.2) techniques were combined to investigate soil microbial communities and functional gene patterns across the three soil types including an Inceptisol (Binhai), an Oxisol (Leizhou), and an Ultisol (Taoyuan) along four profile depths (up to 70 cm in depth) in mesocosm incubation columns. Detrended correspondence analysis revealed that distinctly differentiation in microbial community existed among soil types and profile depths, while the manifest variance in functional structure was only observed among soil types and two rice growth stages, but not across profile depths. Along the profile depth within each soil type, Acidobacteria, Chloroflexi, and Firmicutes increased whereas Cyanobacteria, β-proteobacteria, and Verrucomicrobia declined, suggesting their specific ecophysiological properties. Compared to bacterial community, the archaeal community showed a more contrasting pattern with the predominant groups within phyla Euryarchaeota, Thaumarchaeota, and Crenarchaeota largely varying among soil types and depths. Phylogenetic molecular ecological network (pMEN) analysis further indicated that the pattern of bacterial and archaeal communities interactions changed with soil depth and the highest modularity of microbial community occurred in top soils, implying a relatively higher system resistance to environmental change compared to communities in deeper soil layers. Meanwhile, microbial communities had higher connectivity in deeper soils in comparison with upper soils, suggesting less microbial interaction in surface soils. Structure equation models were developed and the models indicated that pH was the most representative characteristics of soil type and identified as the key driver in shaping both bacterial and archaeal community structure, but did not directly affect microbial functional structure. The distinctive pattern of microbial taxonomic and functional composition along soil profiles implied functional redundancy within these paddy soils. PMID:28611747

Microbial Community and Functional Structure Significantly Varied among Distinct Types of Paddy Soils But Responded Differently along Gradients of Soil Depth Layers.

PubMed

Bai, Ren; Wang, Jun-Tao; Deng, Ye; He, Ji-Zheng; Feng, Kai; Zhang, Li-Mei

2017-01-01

Paddy rice fields occupy broad agricultural area in China and cover diverse soil types. Microbial community in paddy soils is of great interest since many microorganisms are involved in soil functional processes. In the present study, Illumina Mi-Seq sequencing and functional gene array (GeoChip 4.2) techniques were combined to investigate soil microbial communities and functional gene patterns across the three soil types including an Inceptisol (Binhai), an Oxisol (Leizhou), and an Ultisol (Taoyuan) along four profile depths (up to 70 cm in depth) in mesocosm incubation columns. Detrended correspondence analysis revealed that distinctly differentiation in microbial community existed among soil types and profile depths, while the manifest variance in functional structure was only observed among soil types and two rice growth stages, but not across profile depths. Along the profile depth within each soil type, Acidobacteria , Chloroflexi , and Firmicutes increased whereas Cyanobacteria , β -proteobacteria , and Verrucomicrobia declined, suggesting their specific ecophysiological properties. Compared to bacterial community, the archaeal community showed a more contrasting pattern with the predominant groups within phyla Euryarchaeota , Thaumarchaeota , and Crenarchaeota largely varying among soil types and depths. Phylogenetic molecular ecological network (pMEN) analysis further indicated that the pattern of bacterial and archaeal communities interactions changed with soil depth and the highest modularity of microbial community occurred in top soils, implying a relatively higher system resistance to environmental change compared to communities in deeper soil layers. Meanwhile, microbial communities had higher connectivity in deeper soils in comparison with upper soils, suggesting less microbial interaction in surface soils. Structure equation models were developed and the models indicated that pH was the most representative characteristics of soil type and identified as the key driver in shaping both bacterial and archaeal community structure, but did not directly affect microbial functional structure. The distinctive pattern of microbial taxonomic and functional composition along soil profiles implied functional redundancy within these paddy soils.

Systems metabolic engineering of microorganisms to achieve large-scale production of flavonoid scaffolds.

PubMed

Wu, Junjun; Du, Guocheng; Zhou, Jingwen; Chen, Jian

2014-10-20

Flavonoids possess pharmaceutical potential due to their health-promoting activities. The complex structures of these products make extraction from plants difficult, and chemical synthesis is limited because of the use of many toxic solvents. Microbial production offers an alternate way to produce these compounds on an industrial scale in a more economical and environment-friendly manner. However, at present microbial production has been achieved only on a laboratory scale and improvements and scale-up of these processes remain challenging. Naringenin and pinocembrin, which are flavonoid scaffolds and precursors for most of the flavonoids, are the model molecules that are key to solving the current issues restricting industrial production of these chemicals. The emergence of systems metabolic engineering, which combines systems biology with synthetic biology and evolutionary engineering at the systems level, offers new perspectives on strain and process optimization. In this review, current challenges in large-scale fermentation processes involving flavonoid scaffolds and the strategies and tools of systems metabolic engineering used to overcome these challenges are summarized. This will offer insights into overcoming the limitations and challenges of large-scale microbial production of these important pharmaceutical compounds. Copyright © 2014 Elsevier B.V. All rights reserved.

Zero-valent iron/biotic treatment system for perchlorate-contaminated water: lab-scale performance, modeling, and full-scale implications

EPA Science Inventory

The computer program AQUASIM was used to model biological treatment of perchlorate-contaminated water using zero-valent iron corrosion as the hydrogen gas source. The laboratory-scale column was seeded with an autohydrogenotrophic microbial consortium previously shown to degrade ...

Tracing biosignatures from the Recent to the Jurassic in sabkha-associated microbial mats

NASA Astrophysics Data System (ADS)

van der Land, Cees; Dutton, Kirsten; Andrade, Luiza; Paul, Andreas; Sherry, Angela; Fender, Tom; Hewett, Guy; Jones, Martin; Lokier, Stephen W.; Head, Ian M.

2017-04-01

Microbial mat ecosystems have been operating at the sediment-fluid interface for over 3400 million years, influencing the flux, transformation and preservation of carbon from the biosphere to the physical environment. These ecosystems are excellent recorders of rapid and profound changes in earth surface environments and biota as they often survive crisis-induced extreme paleoenvironmental conditions. Their biosignatures, captured in the preserved organic matter and the biominerals that form the microbialite rock, constitute a significant tool in understanding geobiological processes and the interactions of the microbial communities with sediments and with the prevailing physical chemical parameters, as well as the environmental conditions at a local and global scale. Nevertheless, the exact pathways of diagenetic organic matter transformation and early-lithification, essential for the accretion and preservation in the geological record as microbialites, are not well understood. The Abu Dhabi coastal sabkha system contains a vast microbial mat belt that is dominated by continuous polygonal and internally-laminated microbial mats across the upper and middle intertidal zones. This modern system is believed to be the best analogue for the Upper Jurassic Arab Formation, which is both a prolific hydrocarbon reservoir and source rock facies in the United Arab Emirates and in neighbouring countries. In order to characterise the processes that lead to the formation of microbialites we investigated the modern and Jurassic system using a multidisciplinary approach, including growth of field-sampled microbial mats under controlled conditions in the laboratory and field-based analysis of microbial communities, mat mineralogy and organic biomarker analysis. In this study, we focus on hydrocarbon biomarker data obtained from the surface of microbial mats actively growing in the intertidal zone of the modern system. By comparing these findings to data obtained from recently-buried, unlithified mats and fully lithified Jurassic mats we are able to identify those biochemical signatures of organic matter preserved in microbialites which survived diagenetic disintegration and represent the primary microbial production. Biomarkers, in the form of alkanes, mono-, di- and trimethylalkanes (MMA, DMA, TMA) were identified in surface and buried mats. Previous studies reported a bimodal distribution of n-Alkanes in the buried mats due to the relatively rapid decline in the abundance of MMAs and DMAs in the C16-C22 range with C24-C45 exclusively found in buried mats, however, this bimodal distribution was not found in our samples. Furthermore, we were able to improve the subsurface facies model for the Jurassic microbialites with our biomarker data as it shows that microbial mats growing in tidal pools or lagoons within the sabkha system form the most prolific hydrocarbon source rocks.

2010 MICROBIAL STRESS RESPONSE GORDON RESEARCH CONFERENCE, JULY 18-23, 2010

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sarah Ades

2011-07-23

The 2010 Gordon Research Conference on Microbial Stress Responses provides an open and exciting forum for the exchange of scientific discoveries on the remarkable mechanisms used by microbes to survive in nearly every niche on the planet. Understanding these stress responses is critical for our ability to control microbial survival, whether in the context of biotechnology, ecology, or pathogenesis. From its inception in 1994, this conference has traditionally employed a very broad definition of stress in microbial systems. Sessions will cover the major steps of stress responses from signal sensing to transcriptional regulation to the effectors that mediate responses. Amore » wide range of stresses will be represented. Some examples include (but are not limited to) oxidative stress, protein quality control, antibiotic-induced stress and survival, envelope stress, DNA damage, and nutritional stress. The 2010 meeting will also focus on the role of stress responses in microbial communities, applied and environmental microbiology, and microbial development. This conference brings together researchers from both the biological and physical sciences investigating stress responses in medically- and environmentally relevant microbes, as well as model organisms, using cutting-edge techniques. Computational, systems-level, and biophysical approaches to exploring stress responsive circuits will be integrated throughout the sessions alongside the more traditional molecular, physiological, and genetic approaches. The broad range of excellent speakers and topics, together with the intimate and pleasant setting at Mount Holyoke College, provide a fertile ground for the exchange of new ideas and approaches.« less

Accelerated rates of in situ microbial activity after permafrost collapse estimated from a porewater isotope model

NASA Astrophysics Data System (ADS)

Waldrop, M. P.; Neumann, R. B.; Jones, M.; Manies, K.; Mcfarland, J. W.; Blazewicz, S.; Turetsky, M. R.

2016-12-01

Permafrost thaw is expected to become widespread in interior Alaska over the coming century, resulting in increased CO2 and CH4 fluxes from soils and a positive feedback to global warming. However much of our understanding of the microbial response to thaw is predicated on simple laboratory incubations that preclude the multitude of interactions occurring in soils under field situations. Here, we utilize a time series of 13CO2 and 13CH4 measured in porewater collected from thermokarst bogs of different ages to estimate in-situ reaction rates of microbial respiration, methanogenesis from acetate, methanogenesis from CO2, homoacetogenesis, and methane oxidation from porewater concentrations and 13CO2 and 13CH4. We utilized this modeling technique to test the hypothesis that microbial activities are stimulated soon after permafrost thaw and this effect declines over time. Our field site is a chronosequence of thermokarst bogs at the Alaska Peatland Experiment (APEX) in interior AK where we have observed significant losses of peatland carbon since permafrost collapse over the last half century. Concentrations of dissolved CO2 and CH4 in porewater increased with depth, and were higher in the youngest bog compared to the older bogs. With increasing depth 13CH4 became more depleted while 13CO2 became more enriched. Preliminary modeling results, based upon these porewater gas concentrations and isotope values, indicate that microbial activities are higher in the youngest bogs compared to the older bogs, supporting the hypothesis that accelerated rates of microbial activities in young thermokarst features are responsible for high rates of C losses from these systems. Additionally, model results will be compared to variation in the abundance of methanogens, methane oxidizers, and acetogens as well as process rates measured in lab incubations, providing insights into the mechanisms responsible for these losses.

Modeling microbial reaction rates in a submarine hydrothermal vent chimney wall

NASA Astrophysics Data System (ADS)

LaRowe, Douglas E.; Dale, Andrew W.; Aguilera, David R.; L'Heureux, Ivan; Amend, Jan P.; Regnier, Pierre

2014-01-01

The fluids emanating from active submarine hydrothermal vent chimneys provide a window into subseafloor processes and, through mixing with seawater, are responsible for steep thermal and compositional gradients that provide the energetic basis for diverse biological communities. Although several models have been developed to better understand the dynamic interplay of seawater, hydrothermal fluid, minerals and microorganisms inside chimney walls, none provide a fully integrated approach to quantifying the biogeochemistry of these hydrothermal systems. In an effort to remedy this, a fully coupled biogeochemical reaction-transport model of a hydrothermal vent chimney has been developed that explicitly quantifies the rates of microbial catalysis while taking into account geochemical processes such as fluid flow, solute transport and oxidation-reduction reactions associated with fluid mixing as a function of temperature. The metabolisms included in the reaction network are methanogenesis, aerobic oxidation of hydrogen, sulfide and methane and sulfate reduction by hydrogen and methane. Model results indicate that microbial catalysis is generally fastest in the hottest habitable portion of the vent chimney (77-102 °C), and methane and sulfide oxidation peak near the seawater-side of the chimney. The fastest metabolisms are aerobic oxidation of H2 and sulfide and reduction of sulfate by H2 with maximum rates of 140, 900 and 800 pmol cm-3 d-1, respectively. The maximum rate of hydrogenotrophic methanogenesis is just under 0.03 pmol cm-3 d-1, the slowest of the metabolisms considered. Due to thermodynamic inhibition, there is no anaerobic oxidation of methane by sulfate (AOM). These simulations are consistent with vent chimney metabolic activity inferred from phylogenetic data reported in the literature. The model developed here provides a quantitative approach to describing the rates of biogeochemical transformations in hydrothermal systems and can be used to constrain the role of microbial activity in the deep subsurface.

Hydraulic redistribution affects modeled carbon cycling via soil microbial activity and suppressed fire.

PubMed

Fu, Congsheng; Wang, Guiling; Bible, Kenneth; Goulden, Michael L; Saleska, Scott R; Scott, Russell L; Cardon, Zoe G

2018-04-13

Hydraulic redistribution (HR) of water from moist to drier soils, through plant roots, occurs world-wide in seasonally dry ecosystems. Although the influence of HR on landscape hydrology and plant water use has been amply demonstrated, HR's effects on microbe-controlled processes sensitive to soil moisture, including carbon and nutrient cycling at ecosystem scales, remain difficult to observe in the field and have not been integrated into a predictive framework. We incorporated a representation of HR into the Community Land Model (CLM4.5) and found the new model improved predictions of water, energy, and system-scale carbon fluxes observed by eddy covariance at four seasonally dry yet ecologically diverse temperate and tropical AmeriFlux sites. Modeled plant productivity and microbial activities were differentially stimulated by upward HR, resulting at times in increased plant demand outstripping increased nutrient supply. Modeled plant productivity and microbial activities were diminished by downward HR. Overall, inclusion of HR tended to increase modeled annual ecosystem uptake of CO 2 (or reduce annual CO 2 release to the atmosphere). Moreover, engagement of CLM4.5's ground-truthed fire module indicated that though HR increased modeled fuel load at all four sites, upward HR also moistened surface soil and hydrated vegetation sufficiently to limit the modeled spread of dry season fire and concomitant very large CO 2 emissions to the atmosphere. Historically, fire has been a dominant ecological force in many seasonally dry ecosystems, and intensification of soil drought and altered precipitation regimes are expected for seasonally dry ecosystems in the future. HR may play an increasingly important role mitigating development of extreme soil water potential gradients and associated limitations on plant and soil microbial activities, and may inhibit the spread of fire in seasonally dry ecosystems. © 2018 John Wiley & Sons Ltd.

Groundwater–surface water mixing shifts ecological assembly processes and stimulates organic carbon turnover

PubMed Central

Stegen, James C.; Fredrickson, James K.; Wilkins, Michael J.; Konopka, Allan E.; Nelson, William C.; Arntzen, Evan V.; Chrisler, William B.; Chu, Rosalie K.; Danczak, Robert E.; Fansler, Sarah J.; Kennedy, David W.; Resch, Charles T.; Tfaily, Malak

2016-01-01

Environmental transitions often result in resource mixtures that overcome limitations to microbial metabolism, resulting in biogeochemical hotspots and moments. Riverine systems, where groundwater mixes with surface water (the hyporheic zone), are spatially complex and temporally dynamic, making development of predictive models challenging. Spatial and temporal variations in hyporheic zone microbial communities are a key, but understudied, component of riverine biogeochemical function. Here, to investigate the coupling among groundwater–surface water mixing, microbial communities and biogeochemistry, we apply ecological theory, aqueous biogeochemistry, DNA sequencing and ultra-high-resolution organic carbon profiling to field samples collected across times and locations representing a broad range of mixing conditions. Our results indicate that groundwater–surface water mixing in the hyporheic zone stimulates heterotrophic respiration, alters organic carbon composition, causes ecological processes to shift from stochastic to deterministic and is associated with elevated abundances of microbial taxa that may degrade a broad suite of organic compounds. PMID:27052662

Groundwater-surface water mixing shifts ecological assembly processes and stimulates organic carbon turnover.

PubMed

Stegen, James C; Fredrickson, James K; Wilkins, Michael J; Konopka, Allan E; Nelson, William C; Arntzen, Evan V; Chrisler, William B; Chu, Rosalie K; Danczak, Robert E; Fansler, Sarah J; Kennedy, David W; Resch, Charles T; Tfaily, Malak

2016-04-07

Environmental transitions often result in resource mixtures that overcome limitations to microbial metabolism, resulting in biogeochemical hotspots and moments. Riverine systems, where groundwater mixes with surface water (the hyporheic zone), are spatially complex and temporally dynamic, making development of predictive models challenging. Spatial and temporal variations in hyporheic zone microbial communities are a key, but understudied, component of riverine biogeochemical function. Here, to investigate the coupling among groundwater-surface water mixing, microbial communities and biogeochemistry, we apply ecological theory, aqueous biogeochemistry, DNA sequencing and ultra-high-resolution organic carbon profiling to field samples collected across times and locations representing a broad range of mixing conditions. Our results indicate that groundwater-surface water mixing in the hyporheic zone stimulates heterotrophic respiration, alters organic carbon composition, causes ecological processes to shift from stochastic to deterministic and is associated with elevated abundances of microbial taxa that may degrade a broad suite of organic compounds.

Adaptation of Aquatic Microbial Communities to Hg2+ Stress †

PubMed Central

Barkay, Tamar

1987-01-01

The mechanism of adaptation to Hg2+ in four aquatic habitats was studied by correlating microbially mediated Hg2+ volatilization with the adaptive state of the exposed communities. Community diversity, heterotrophic activity, and Hg2+ resistance measurements indicated that adaptation of all four communities was stimulated by preexposure to Hg2+. In saline water communities, adaptation was associated with rapid volatilization after an initial lag period. This mechanism, however, did not promote adaptation in a freshwater sample, in which Hg2+ was volatilized slowly, regardless of the resistance level of the microbial community. Distribution of the mer operon among representative colonies of the communities was not related to adaptation to Hg2+. Thus, although volatilization enabled some microbial communities to sustain their functions in Hg2+-stressed environments, it was not mediated by the genes that serve as a model system in molecular studies of bacterial resistance to mercurials. PMID:16347488

Reconstructing a hydrogen-driven microbial metabolic network in Opalinus Clay rock.

PubMed

Bagnoud, Alexandre; Chourey, Karuna; Hettich, Robert L; de Bruijn, Ino; Andersson, Anders F; Leupin, Olivier X; Schwyn, Bernhard; Bernier-Latmani, Rizlan

2016-10-14

The Opalinus Clay formation will host geological nuclear waste repositories in Switzerland. It is expected that gas pressure will build-up due to hydrogen production from steel corrosion, jeopardizing the integrity of the engineered barriers. In an in situ experiment located in the Mont Terri Underground Rock Laboratory, we demonstrate that hydrogen is consumed by microorganisms, fuelling a microbial community. Metagenomic binning and metaproteomic analysis of this deep subsurface community reveals a carbon cycle driven by autotrophic hydrogen oxidizers belonging to novel genera. Necromass is then processed by fermenters, followed by complete oxidation to carbon dioxide by heterotrophic sulfate-reducing bacteria, which closes the cycle. This microbial metabolic web can be integrated in the design of geological repositories to reduce pressure build-up. This study shows that Opalinus Clay harbours the potential for chemolithoautotrophic-based system, and provides a model of microbial carbon cycle in deep subsurface environments where hydrogen and sulfate are present.

Reconstructing a hydrogen-driven microbial metabolic network in Opalinus Clay rock

PubMed Central

Bagnoud, Alexandre; Chourey, Karuna; Hettich, Robert L.; de Bruijn, Ino; Andersson, Anders F.; Leupin, Olivier X.; Schwyn, Bernhard; Bernier-Latmani, Rizlan

2016-01-01

The Opalinus Clay formation will host geological nuclear waste repositories in Switzerland. It is expected that gas pressure will build-up due to hydrogen production from steel corrosion, jeopardizing the integrity of the engineered barriers. In an in situ experiment located in the Mont Terri Underground Rock Laboratory, we demonstrate that hydrogen is consumed by microorganisms, fuelling a microbial community. Metagenomic binning and metaproteomic analysis of this deep subsurface community reveals a carbon cycle driven by autotrophic hydrogen oxidizers belonging to novel genera. Necromass is then processed by fermenters, followed by complete oxidation to carbon dioxide by heterotrophic sulfate-reducing bacteria, which closes the cycle. This microbial metabolic web can be integrated in the design of geological repositories to reduce pressure build-up. This study shows that Opalinus Clay harbours the potential for chemolithoautotrophic-based system, and provides a model of microbial carbon cycle in deep subsurface environments where hydrogen and sulfate are present. PMID:27739431

The evolution of cooperation within the gut microbiota.

PubMed

Rakoff-Nahoum, Seth; Foster, Kevin R; Comstock, Laurie E

2016-05-12

Cooperative phenotypes are considered central to the functioning of microbial communities in many contexts, including communication via quorum sensing, biofilm formation, antibiotic resistance, and pathogenesis. The human intestine houses a dense and diverse microbial community critical to health, yet we know little about cooperation within this important ecosystem. Here we test experimentally for evolved cooperation within the Bacteroidales, the dominant Gram-negative bacteria of the human intestine. We show that during growth on certain dietary polysaccharides, the model member Bacteroides thetaiotaomicron exhibits only limited cooperation. Although this organism digests these polysaccharides extracellularly, mutants lacking this ability are outcompeted. In contrast, we discovered a dedicated cross-feeding enzyme system in the prominent gut symbiont Bacteroides ovatus, which digests polysaccharide at a cost to itself but at a benefit to another species. Using in vitro systems and gnotobiotic mouse colonization models, we find that extracellular digestion of inulin increases the fitness of B. ovatus owing to reciprocal benefits when it feeds other gut species such as Bacteroides vulgatus. This is a rare example of naturally-evolved cooperation between microbial species. Our study reveals both the complexity and importance of cooperative phenotypes within the mammalian intestinal microbiota.

Carbon availability structures microbial community composition and function in soil aggregate fractions

NASA Astrophysics Data System (ADS)

Hofmockel, K. S.; Bach, E.; Williams, R.; Howe, A.

2014-12-01

Identifying the microbial metabolic pathways that most strongly influence ecosystem carbon (C) cycling requires a deeper understanding of the availability and accessibility of microbial substrates. A first step towards this goal is characterizing the relationships between microbial community function and soil C chemistry in a field context. For this perspective, soil aggregate fractions can be used as model systems that scale between microbe-substrate interactions and ecosystem C cycling and storage. The present study addresses how physicochemical variation among soil aggregate fractions influences the composition and functional potential of C cycling microbial communities. We report variation across soil aggregates using plot scale biological replicates from biofuel agroecosystems (fertilized, reconstructed, tallgrass prairie). Our results suggest that C and nitrogen (N) chemistry significantly differ among aggregate fractions. This leads to variation in microbial community composition, which was better characterized among aggregates than by using the whole soil. In fact by considering soil aggregation, we were able to characterize almost 2000 more taxa than whole soil alone, resulting in 65% greater community richness. Availability of C and N strongly influenced the composition of microbial communities among soil aggregate fractions. The normalized abundance of microbial functional guilds among aggregate fractions correlated with C and N chemistry, as did functional potential, measured by extracellular enzyme activity. Metagenomic results suggest that soil aggregate fractions select for functionally distinct microbial communities, which may significantly influence decomposition and soil C storage. Our study provides support for the premise that integration of soil aggregate chemistry, especially microaggregates that have greater microbial richness and occur at spatial scales relevant to microbial community functioning, may be necessary to understand the role of microbial communities on terrestrial C and N cycling.

Perspective for Aquaponic Systems: “Omic” Technologies for Microbial Community Analysis

PubMed Central

Munguia-Fragozo, Perla; Alatorre-Jacome, Oscar; Rico-Garcia, Enrique; Cruz-Hernandez, Andres; Ocampo-Velazquez, Rosalia V.; Garcia-Trejo, Juan F.; Guevara-Gonzalez, Ramon G.

2015-01-01

Aquaponics is the combined production of aquaculture and hydroponics, connected by a water recirculation system. In this productive system, the microbial community is responsible for carrying out the nutrient dynamics between the components. The nutrimental transformations mainly consist in the transformation of chemical species from toxic compounds into available nutrients. In this particular field, the microbial research, the “Omic” technologies will allow a broader scope of studies about a current microbial profile inside aquaponics community, even in those species that currently are unculturable. This approach can also be useful to understand complex interactions of living components in the system. Until now, the analog studies were made to set up the microbial characterization on recirculation aquaculture systems (RAS). However, microbial community composition of aquaponics is still unknown. “Omic” technologies like metagenomic can help to reveal taxonomic diversity. The perspectives are also to begin the first attempts to sketch the functional diversity inside aquaponic systems and its ecological relationships. The knowledge of the emergent properties inside the microbial community, as well as the understanding of the biosynthesis pathways, can derive in future biotechnological applications. Thus, the aim of this review is to show potential applications of current “Omic” tools to characterize the microbial community in aquaponic systems. PMID:26509157

SteadyCom: Predicting microbial abundances while ensuring community stability

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chan, Siu Hung Joshua; Simons, Margaret N.; Maranas, Costas D.

Genome-scale metabolic modeling has become widespread for analyzing microbial metabolism. Extending this established paradigm to more complex microbial communities is emerging as a promising way to unravel the interactions and biochemical repertoire of these omnipresent systems. While several modeling techniques have been developed for microbial communities, little emphasis has been placed on the need to impose a time-averaged constant growth rate across all members for a community to ensure co-existence and stability. In the absence of this constraint, the faster growing organism will ultimately displace all other microbes in the community. This is particularly important for predicting steady-state microbiota compositionmore » as it imposes significant restrictions on the allowable community membership, composition and phenotypes. In this study, we introduce the SteadyCom optimization framework for predicting metabolic flux distributions consistent with the steady-state requirement. SteadyCom can be rapidly converged by iteratively solving linear programming (LP) problem and the number of iterations is independent of the number of organisms. A significant advantage of SteadyCom is compatibility with flux variability analysis. SteadyCom is first demonstrated for a community of four E. coli double auxotrophic mutants and is then applied to a gut microbiota model consisting of nine species, with representatives from the phyla Bacteroidetes, Firmicutes, Actinobacteria and Proteobacteria. In contrast to the direct use of FBA, SteadyCom is able to predict the change in species abundance in response to changes in diets with minimal additional imposed constraints on the model. Furthermore, by randomizing the uptake rates of microbes, an abundance profile with a good agreement to experimental gut microbiota is inferred. SteadyCom provides an important step towards the cross-cutting task of predicting the composition of a microbial community in a given environment.« less

SteadyCom: Predicting microbial abundances while ensuring community stability

DOE PAGES

Chan, Siu Hung Joshua; Simons, Margaret N.; Maranas, Costas D.; ...

2017-05-15

Genome-scale metabolic modeling has become widespread for analyzing microbial metabolism. Extending this established paradigm to more complex microbial communities is emerging as a promising way to unravel the interactions and biochemical repertoire of these omnipresent systems. While several modeling techniques have been developed for microbial communities, little emphasis has been placed on the need to impose a time-averaged constant growth rate across all members for a community to ensure co-existence and stability. In the absence of this constraint, the faster growing organism will ultimately displace all other microbes in the community. This is particularly important for predicting steady-state microbiota compositionmore » as it imposes significant restrictions on the allowable community membership, composition and phenotypes. In this study, we introduce the SteadyCom optimization framework for predicting metabolic flux distributions consistent with the steady-state requirement. SteadyCom can be rapidly converged by iteratively solving linear programming (LP) problem and the number of iterations is independent of the number of organisms. A significant advantage of SteadyCom is compatibility with flux variability analysis. SteadyCom is first demonstrated for a community of four E. coli double auxotrophic mutants and is then applied to a gut microbiota model consisting of nine species, with representatives from the phyla Bacteroidetes, Firmicutes, Actinobacteria and Proteobacteria. In contrast to the direct use of FBA, SteadyCom is able to predict the change in species abundance in response to changes in diets with minimal additional imposed constraints on the model. Furthermore, by randomizing the uptake rates of microbes, an abundance profile with a good agreement to experimental gut microbiota is inferred. SteadyCom provides an important step towards the cross-cutting task of predicting the composition of a microbial community in a given environment.« less

A New Approach to Predict Microbial Community Assembly and Function Using a Stochastic, Genome-Enabled Modeling Framework

NASA Astrophysics Data System (ADS)

King, E.; Brodie, E.; Anantharaman, K.; Karaoz, U.; Bouskill, N.; Banfield, J. F.; Steefel, C. I.; Molins, S.

2016-12-01

Characterizing and predicting the microbial and chemical compositions of subsurface aquatic systems necessitates an understanding of the metabolism and physiology of organisms that are often uncultured or studied under conditions not relevant for one's environment of interest. Cultivation-independent approaches are therefore important and have greatly enhanced our ability to characterize functional microbial diversity. The capability to reconstruct genomes representing thousands of populations from microbial communities using metagenomic techniques provides a foundation for development of predictive models for community structure and function. Here, we discuss a genome-informed stochastic trait-based model incorporated into a reactive transport framework to represent the activities of coupled guilds of hypothetical microorganisms. Metabolic pathways for each microbe within a functional guild are parameterized from metagenomic data with a unique combination of traits governing organism fitness under dynamic environmental conditions. We simulate the thermodynamics of coupled electron donor and acceptor reactions to predict the energy available for cellular maintenance, respiration, biomass development, and enzyme production. While `omics analyses can now characterize the metabolic potential of microbial communities, it is functionally redundant as well as computationally prohibitive to explicitly include the thousands of recovered organisms into biogeochemical models. However, one can derive potential metabolic pathways from genomes along with trait-linkages to build probability distributions of traits. These distributions are used to assemble groups of microbes that couple one or more of these pathways. From the initial ensemble of microbes, only a subset will persist based on the interaction of their physiological and metabolic traits with environmental conditions, competing organisms, etc. Here, we analyze the predicted niches of these hypothetical microbes and assess the ability of a stochastically assembled community of organisms to predict subsurface biogeochemical dynamics.

Microbial Performance of Food Safety Control and Assurance Activities in a Fresh Produce Processing Sector Measured Using a Microbial Assessment Scheme and Statistical Modeling.

PubMed

Njage, Patrick Murigu Kamau; Sawe, Chemutai Tonui; Onyango, Cecilia Moraa; Habib, I; Njagi, Edmund Njeru; Aerts, Marc; Molenberghs, Geert

2017-01-01

Current approaches such as inspections, audits, and end product testing cannot detect the distribution and dynamics of microbial contamination. Despite the implementation of current food safety management systems, foodborne outbreaks linked to fresh produce continue to be reported. A microbial assessment scheme and statistical modeling were used to systematically assess the microbial performance of core control and assurance activities in five Kenyan fresh produce processing and export companies. Generalized linear mixed models and correlated random-effects joint models for multivariate clustered data followed by empirical Bayes estimates enabled the analysis of the probability of contamination across critical sampling locations (CSLs) and factories as a random effect. Salmonella spp. and Listeria monocytogenes were not detected in the final products. However, none of the processors attained the maximum safety level for environmental samples. Escherichia coli was detected in five of the six CSLs, including the final product. Among the processing-environment samples, the hand or glove swabs of personnel revealed a higher level of predicted contamination with E. coli , and 80% of the factories were E. coli positive at this CSL. End products showed higher predicted probabilities of having the lowest level of food safety compared with raw materials. The final products were E. coli positive despite the raw materials being E. coli negative for 60% of the processors. There was a higher probability of contamination with coliforms in water at the inlet than in the final rinse water. Four (80%) of the five assessed processors had poor to unacceptable counts of Enterobacteriaceae on processing surfaces. Personnel-, equipment-, and product-related hygiene measures to improve the performance of preventive and intervention measures are recommended.

A theoretical reassessment of microbial maintenance and implications for microbial ecology modeling.

PubMed

Wang, Gangsheng; Post, Wilfred M

2012-09-01

We attempted to reconcile three microbial maintenance models (Herbert, Pirt, and Compromise) through a theoretical reassessment. We provided a rigorous proof that the true growth yield coefficient (Y(G)) is the ratio of the specific maintenance rate (a in Herbert) to the maintenance coefficient (m in Pirt). Other findings from this study include: (1) the Compromise model is identical to the Herbert for computing microbial growth and substrate consumption, but it expresses the dependence of maintenance on both microbial biomass and substrate; (2) the maximum specific growth rate in the Herbert (μ(max,H)) is higher than those in the other two models (μ(max,P) and μ(max,C)), and the difference is the physiological maintenance factor (m(q) = a); and (3) the overall maintenance coefficient (m(T)) is more sensitive to m(q) than to the specific growth rate (μ(G)) and Y(G). Our critical reassessment of microbial maintenance provides a new approach for quantifying some important components in soil microbial ecology models. © This article is a US government work and is in the public domain in the USA.

Development and application of the microbial fate and transport module for the Agricultural Policy/Environmental eXtender (APEX) model

NASA Astrophysics Data System (ADS)

Hong, E.; Park, Y.; Muirhead, R.; Jeong, J.; Pachepsky, Y. A.

2017-12-01

Pathogenic microorganisms in recreational and irrigation waters remain the subject of concern. Water quality models are used to estimate microbial quality of water sources, to evaluate microbial contamination-related risks, to guide the microbial water quality monitoring, and to evaluate the effect of agricultural management on the microbial water quality. The Agricultural Policy/Environmental eXtender (APEX) is the watershed-scale water quality model that includes highly detailed representation of agricultural management. The APEX currently does not have microbial fate and transport simulation capabilities. The objective of this work was to develop the first APEX microbial fate and transport module that could use the APEX conceptual model of manure removal together with recently introduced conceptualizations of the in-stream microbial fate and transport. The module utilizes manure erosion rates found in the APEX. Bacteria survival in soil-manure mixing layer was simulated with the two-stage survival model. Individual survival patterns were simulated for each manure application date. Simulated in-stream microbial fate and transport processes included the reach-scale passive release of bacteria with resuspended bottom sediment during high flow events, the transport of bacteria from bottom sediment due to the hyporheic exchange during low flow periods, the deposition with settling sediment, and the two-stage survival. Default parameter values were available from recently published databases. The APEX model with the newly developed microbial fate and transport module was applied to simulate seven years of monitoring data for the Toenepi watershed in New Zealand. Based on calibration and testing results, the APEX with the microbe module reproduced well the monitored pattern of E. coli concentrations at the watershed outlet. The APEX with the microbial fate and transport module will be utilized for predicting microbial quality of water under various agricultural practices, evaluating monitoring protocols, and supporting the selection of management practices based on regulations that rely on fecal indicator bacteria concentrations.

Amino acid catabolism-directed biofuel production in Clostridium sticklandii: An insight into model-driven systems engineering.

PubMed

Sangavai, C; Chellapandi, P

2017-12-01

Model-driven systems engineering has been more fascinating process for the microbial production of biofuel and bio-refineries in chemical and pharmaceutical industries. Genome-scale modeling and simulations have been guided for metabolic engineering of Clostridium species for the production of organic solvents and organic acids. Among them, Clostridium sticklandii is one of the potential organisms to be exploited as a microbial cell factory for biofuel production. It is a hyper-ammonia producing bacterium and is able to catabolize amino acids as important carbon and energy sources via Stickland reactions and the development of the specific pathways. Current genomic and metabolic aspects of this bacterium are comprehensively reviewed herein, which provided information for learning about protein catabolism-directed biofuel production. It has a metabolic potential to drive energy and direct solventogenesis as well as acidogenesis from protein catabolism. It produces by-products such as ethanol, acetate, n -butanol, n -butyrate and hydrogen from amino acid catabolism. Model-driven systems engineering of this organism would improve the performance of the industrial sectors and enhance the industrial economy by using protein-based waste in environment-friendly ways.

A mathematical model of microbial enhanced oil recovery (MEOR) method for mixed type rock

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sitnikov, A.A.; Eremin, N.A.; Ibattulin, R.R.

1994-12-31

This paper deals with the microbial enhanced oil recovery method. It covers: (1) Mechanism of microbial influence on the reservoir was analyzed; (2) The main groups of metabolites affected by the hydrodynamic characteristics of the reservoir were determined; (3) The criterions of use of microbial influence method on the reservoir are defined. The mathematical model of microbial influence on the reservoir was made on this basis. The injection of molasse water solution with Clostridium bacterias into the mixed type of rock was used in this model. And the results of calculations were compared with experimental data.

Assessment of Heterotrophic Growth Supported by Soluble Microbial Products in Anammox Biofilm using Multidimensional Modeling

PubMed Central

Liu, Yiwen; Sun, Jing; Peng, Lai; Wang, Dongbo; Dai, Xiaohu; Ni, Bing-Jie

2016-01-01

Anaerobic ammonium oxidation (anammox) is known to autotrophically convert ammonium to dinitrogen gas with nitrite as the electron acceptor, but little is known about their released microbial products and how these are relative to heterotrophic growth in anammox system. In this work, we applied a mathematical model to assess the heterotrophic growth supported by three key microbial products produced by bacteria in anammox biofilm (utilization associated products (UAP), biomass associated products (BAP), and decay released substrate). Both One-dimensional and two-dimensional numerical biofilm models were developed to describe the development of anammox biofilm as a function of the multiple bacteria–substrate interactions. Model simulations show that UAP of anammox is the main organic carbon source for heterotrophs. Heterotrophs are mainly dominant at the surface of the anammox biofilm with small fraction inside the biofilm. 1-D model is sufficient to describe the main substrate concentrations/fluxes within the anammox biofilm, while the 2-D model can give a more detailed biomass distribution. The heterotrophic growth on UAP is mainly present at the outside of anammox biofilm, their growth on BAP (HetB) are present throughout the biofilm, while the growth on decay released substrate (HetD) is mainly located in the inner layers of the biofilm. PMID:27273460

Space Station Freedom ECLSS: A step toward autonomous regenerative life support systems

NASA Technical Reports Server (NTRS)

Dewberry, Brandon S.

1990-01-01

The Environmental Control and Life Support System (ECLSS) is a Freedom Station distributed system with inherent applicability to extensive automation primarily due to its comparatively long control system latencies. These allow longer contemplation times in which to form a more intelligent control strategy and to prevent and diagnose faults. The regenerative nature of the Space Station Freedom ECLSS will contribute closed loop complexities never before encountered in life support systems. A study to determine ECLSS automation approaches has been completed. The ECLSS baseline software and system processes could be augmented with more advanced fault management and regenerative control systems for a more autonomous evolutionary system, as well as serving as a firm foundation for future regenerative life support systems. Emerging advanced software technology and tools can be successfully applied to fault management, but a fully automated life support system will require research and development of regenerative control systems and models. The baseline Environmental Control and Life Support System utilizes ground tests in development of batch chemical and microbial control processes. Long duration regenerative life support systems will require more active chemical and microbial feedback control systems which, in turn, will require advancements in regenerative life support models and tools. These models can be verified using ground and on orbit life support test and operational data, and used in the engineering analysis of proposed intelligent instrumentation feedback and flexible process control technologies for future autonomous regenerative life support systems, including the evolutionary Space Station Freedom ECLSS.

Development of a program to fit data to a new logistic model for microbial growth.

PubMed

Fujikawa, Hiroshi; Kano, Yoshihiro

2009-06-01

Recently we developed a mathematical model for microbial growth in food. The model successfully predicted microbial growth at various patterns of temperature. In this study, we developed a program to fit data to the model with a spread sheet program, Microsoft Excel. Users can instantly get curves fitted to the model by inputting growth data and choosing the slope portion of a curve. The program also could estimate growth parameters including the rate constant of growth and the lag period. This program would be a useful tool for analyzing growth data and further predicting microbial growth.

Evidence of a dynamic microbial community structure and predation through combined microbiological and stable isotope characterization

NASA Astrophysics Data System (ADS)

Druhan, J. L.; Bill, M.; Lim, H. C.; Wu, C.; Conrad, M. E.; Williams, K. H.; DePaolo, D. J.; Brodie, E.

2014-12-01

The speciation, reactivity and mobility of carbon in the near surface environment is intimately linked to the prevalence, diversity and dynamics of native microbial populations. We utilize this relationship by introducing 13C-labeled acetate to sediments recovered from a shallow aquifer system to track both the cycling of carbon through multiple redox pathways and the associated spatial and temporal evolution of bacterial communities in response to this nutrient source. Results demonstrate a net loss of sediment organic carbon over the course of the amendment experiment. Furthermore, these data demonstrated a source of isotopically labeled inorganic carbon that was not attributable to primary metabolism by acetate-oxidizing microorganisms. Fluid samples analyzed weekly for microbial composition by pyrosequencing of ribosomal RNA genes showed a transient microbial community structure, with distinct occurrences of Azoarcus, Geobacter and multiple sulfate reducing species over the course of the experiment. In combination with DNA sequencing data, the anomalous carbon cycling process is shown to occur exclusively during the period of predominant Geobacter species growth. Pyrosequencing indicated, and targeted cloning and sequencing confirmed the presence of several bacteriovorous protozoa, including species of the Breviata, Planococcus and Euplotes genera. Cloning and qPCR analysis demonstrated that Euplotes species were most abundant and displayed a growth trajectory that closely followed that of the Geobacter population. These results suggest a previously undocumented secondary turnover of biomass carbon related to protozoan grazing that was not sufficiently prevalent to be observed in bulk concentrations of carbon species in the system, but was clearly identifiable in the partitioning of carbon isotopes. The impact of predator-prey relationships on subsurface microbial community dynamics and therefore the flux of carbon through a system via the microbial biomass pool suggests a diversity of processes that should be considered for inclusion in reactive transport models that aim to predict carbon turnover, nutrient flux, and redox reactions in natural and stimulated subsurface systems.

Top-down systems biology integration of conditional prebiotic modulated transgenomic interactions in a humanized microbiome mouse model

PubMed Central

Martin, Francois-Pierre J; Wang, Yulan; Sprenger, Norbert; Yap, Ivan K S; Rezzi, Serge; Ramadan, Ziad; Peré-Trepat, Emma; Rochat, Florence; Cherbut, Christine; van Bladeren, Peter; Fay, Laurent B; Kochhar, Sunil; Lindon, John C; Holmes, Elaine; Nicholson, Jeremy K

2008-01-01

Gut microbiome–host metabolic interactions affect human health and can be modified by probiotic and prebiotic supplementation. Here, we have assessed the effects of consumption of a combination of probiotics (Lactobacillus paracasei or L. rhamnosus) and two galactosyl-oligosaccharide prebiotics on the symbiotic microbiome–mammalian supersystem using integrative metabolic profiling and modeling of multiple compartments in germ-free mice inoculated with a model of human baby microbiota. We have shown specific impacts of two prebiotics on the microbial populations of HBM mice when co-administered with two probiotics. We observed an increase in the populations of Bifidobacterium longum and B. breve, and a reduction in Clostridium perfringens, which were more marked when combining prebiotics with L. rhamnosus. In turn, these microbial effects were associated with modulation of a range of host metabolic pathways observed via changes in lipid profiles, gluconeogenesis, and amino-acid and methylamine metabolism associated to fermentation of carbohydrates by different bacterial strains. These results provide evidence for the potential use of prebiotics for beneficially modifying the gut microbial balance as well as host energy and lipid homeostasis. PMID:18628745

Frequency-dependent selection at rough expanding fronts

NASA Astrophysics Data System (ADS)

Kuhr, Jan-Timm; Stark, Holger

2015-10-01

Microbial colonies are experimental model systems for studying the colonization of new territory by biological species through range expansion. We study a generalization of the two-species Eden model, which incorporates local frequency-dependent selection, in order to analyze how social interactions between two species influence surface roughness of growing microbial colonies. The model includes several classical scenarios from game theory. We then concentrate on an expanding public goods game, where either cooperators or defectors take over the front depending on the system parameters. We analyze in detail the critical behavior of the nonequilibrium phase transition between global cooperation and defection and thereby identify a new universality class of phase transitions dealing with absorbing states. At the transition, the number of boundaries separating sectors decays with a novel power law in time and their superdiffusive motion crosses over from Eden scaling to a nearly ballistic regime. In parallel, the width of the front initially obeys Eden roughening and, at later times, passes over to selective roughening.

Uniformitarianism and its Discontents: Microbial Evolution and Co-evolution of Life and Earth

NASA Astrophysics Data System (ADS)

Wing, B. A.

2016-12-01

For the first ≈4 billion years of Earth history, life was microscopic. There are ≈5x1030 bacteria and archaea on Earth today. Mean turnover times of natural microbial populations are days to millennia (10-2 to 103 years). Assuming that a similar-sized microbial biosphere has been maintained since ≈4 billion years ago, the number of microbes that have ever lived on Earth is awesome: >1037 to 1042. In broad brush, these numbers represent the individual microbial evolution experiments run by Nature. They are many, many orders of magnitude greater than the number of stars in the universe. Despite this numerical hurdle, the geological record is read with the assumption that microbes in the geological past were doing exactly what microbes do today. In this presentation, I will discuss evolutionary impacts on a critical microbial phentypic trait - sulfur isotope fractionation - that has played a critical role in our interpretations of the the evolution of the Earth system. The discussion will range from microbial evolution experiments to models of metabolic evolution, with an eye toward understanding the evolutionary weaknesses and strengths in our uniformiatrian world view.

Microbial community dynamics in Inferno Crater Lake, a thermally fluctuating geothermal spring

PubMed Central

Ward, Laura; Taylor, Michael W; Power, Jean F; Scott, Bradley J; McDonald, Ian R; Stott, Matthew B

2017-01-01

Understanding how microbial communities respond and adjust to ecosystem perturbation is often difficult to interpret due to multiple and often simultaneous variations in observed conditions. In this research, we investigated the microbial community dynamics of Inferno Crater Lake, an acidic geothermal spring in New Zealand with a unique thermal cycle that varies between 30 and 80 °C over a period of 40–60 days. Using a combination of next-generation sequencing, geochemical analysis and quantitative PCR we found that the microbial community composition was predominantly chemolithotrophic and strongly associated with the thermal cycle. At temperatures >65 °C, the microbial community was dominated almost exclusively by sulphur-oxidising archaea (Sulfolobus-like spp.). By contrast, at mesophilic temperatures the community structure was more mixed, comprising both archaea and bacteria but dominated primarily by chemolithotrophic sulphur and hydrogen oxidisers. Multivariate analysis of physicochemical data confirmed that temperature was the only significant variable associated with community turnover. This research contributes to our understanding of microbial community dynamics in variable environments, using a naturally alternating system as a model and extends our limited knowledge of acidophile ecology in geothermal habitats. PMID:28072418

Microbial community dynamics in Inferno Crater Lake, a thermally fluctuating geothermal spring.

PubMed

Ward, Laura; Taylor, Michael W; Power, Jean F; Scott, Bradley J; McDonald, Ian R; Stott, Matthew B

2017-05-01

Understanding how microbial communities respond and adjust to ecosystem perturbation is often difficult to interpret due to multiple and often simultaneous variations in observed conditions. In this research, we investigated the microbial community dynamics of Inferno Crater Lake, an acidic geothermal spring in New Zealand with a unique thermal cycle that varies between 30 and 80 °C over a period of 40-60 days. Using a combination of next-generation sequencing, geochemical analysis and quantitative PCR we found that the microbial community composition was predominantly chemolithotrophic and strongly associated with the thermal cycle. At temperatures >65 °C, the microbial community was dominated almost exclusively by sulphur-oxidising archaea (Sulfolobus-like spp.). By contrast, at mesophilic temperatures the community structure was more mixed, comprising both archaea and bacteria but dominated primarily by chemolithotrophic sulphur and hydrogen oxidisers. Multivariate analysis of physicochemical data confirmed that temperature was the only significant variable associated with community turnover. This research contributes to our understanding of microbial community dynamics in variable environments, using a naturally alternating system as a model and extends our limited knowledge of acidophile ecology in geothermal habitats.

A Hydroponic Co-cultivation System for Simultaneous and Systematic Analysis of Plant/Microbe Molecular Interactions and Signaling.

PubMed

Nathoo, Naeem; Bernards, Mark A; MacDonald, Jacqueline; Yuan, Ze-Chun

2017-07-22

An experimental design mimicking natural plant-microbe interactions is very important to delineate the complex plant-microbe signaling processes. Arabidopsis thaliana-Agrobacterium tumefaciens provides an excellent model system to study bacterial pathogenesis and plant interactions. Previous studies of plant-Agrobacterium interactions have largely relied on plant cell suspension cultures, the artificial wounding of plants, or the artificial induction of microbial virulence factors or plant defenses by synthetic chemicals. However, these methods are distinct from the natural signaling in planta, where plants and microbes recognize and respond in spatial and temporal manners. This work presents a hydroponic cocultivation system where intact plants are supported by metal mesh screens and cocultivated with Agrobacterium. In this cocultivation system, no synthetic phytohormone or chemical that induces microbial virulence or plant defense is supplemented. The hydroponic cocultivation system closely resembles natural plant-microbe interactions and signaling homeostasis in planta. Plant roots can be separated from the medium containing Agrobacterium, and the signaling and responses of both the plant hosts and the interacting microbes can be investigated simultaneously and systematically. At any given timepoint/interval, plant tissues or bacteria can be harvested separately for various "omics" analyses, demonstrating the power and efficacy of this system. The hydroponic cocultivation system can be easily adapted to study: 1) the reciprocal signaling of diverse plant-microbe systems, 2) signaling between a plant host and multiple microbial species (i.e. microbial consortia or microbiomes), 3) how nutrients and chemicals are implicated in plant-microbe signaling, and 4) how microbes interact with plant hosts and contribute to plant tolerance to biotic or abiotic stresses.

Toward Engineering Synthetic Microbial Metabolism

PubMed Central

McArthur, George H.; Fong, Stephen S.

2010-01-01

The generation of well-characterized parts and the formulation of biological design principles in synthetic biology are laying the foundation for more complex and advanced microbial metabolic engineering. Improvements in de novo DNA synthesis and codon-optimization alone are already contributing to the manufacturing of pathway enzymes with improved or novel function. Further development of analytical and computer-aided design tools should accelerate the forward engineering of precisely regulated synthetic pathways by providing a standard framework for the predictable design of biological systems from well-characterized parts. In this review we discuss the current state of synthetic biology within a four-stage framework (design, modeling, synthesis, analysis) and highlight areas requiring further advancement to facilitate true engineering of synthetic microbial metabolism. PMID:20037734

An Energy Balance Model to Predict Chemical Partitioning in a Photosynthetic Microbial Mat

NASA Technical Reports Server (NTRS)

Hoehler, Tori M.; Albert, Daniel B.; DesMarais, David J.

2006-01-01

Studies of biosignature formation in photosynthetic microbial mat communities offer potentially useful insights with regards to both solar and extrasolar astrobiology. Biosignature formation in such systems results from the chemical transformation of photosynthetically fixed carbon by accessory microorganisms. This fixed carbon represents a source not only of reducing power, but also energy, to these organisms, so that chemical and energy budgets should be coupled. We tested this hypothesis by applying an energy balance model to predict the fate of photosynthetic productivity under dark, anoxic conditions. Fermentation of photosynthetically fixed carbon is taken to be the only source of energy available to cyanobacteria in the absence of light and oxygen, and nitrogen fixation is the principal energy demand. The alternate fate for fixed carbon is to build cyanobacterial biomass with Redfield C:N ratio. The model predicts that, under completely nitrogen-limited conditions, growth is optimized when 78% of fixed carbon stores are directed into fermentative energy generation, with the remainder allocated to growth. These predictions were compared to measurements made on microbial mats that are known to be both nitrogen-limited and populated by actively nitrogen-fixing cyanobacteria. In these mats, under dark, anoxic conditions, 82% of fixed carbon stores were diverted into fermentation. The close agreement between these independent approaches suggests that energy balance models may provide a quantitative means of predicting chemical partitioning within such systems - an important step towards understanding how biological productivity is ultimately partitioned into biosignature compounds.

Stoichiometry constrains microbial response to root exudation - insights from a model and a field experiment in a temperate forest

NASA Astrophysics Data System (ADS)

Drake, J. E.; Darby, B. A.; Giasson, M.-A.; Kramer, M. A.; Phillips, R. P.; Finzi, A. C.

2012-06-01

Healthy plant roots release a wide range of chemicals into soils. This process, termed root exudation, is thought to increase the activity of microbes and the exo-enzymes they synthesize, leading to accelerated rates of carbon (C) mineralization and nutrient cycling in rhizosphere soils relative to bulk soils. The causal role of exudation, however, is difficult to isolate with in-situ observations, given the complex nature of the rhizosphere environment. We investigated the potential effects of root exudation on microbial and exo-enzyme activity using a theoretical model of decomposition and a field experiment, with a specific focus on the stoichiometric constraint of nitrogen (N) availability. The field experiment isolated the effect of exudation by pumping solutions of exudate mimics through microlysimeter "root simulators" into intact forest soils over two 50-day periods. Using a combined model-experiment approach, we tested two hypotheses: (1) exudation alone is sufficient to stimulate microbial and exo-enzyme activity in rhizosphere soils, and (2) microbial response to C-exudates (carbohydrates and organic acids) is constrained by N-limitation. Experimental delivery of exudate mimics containing C and N significantly increased microbial respiration, microbial biomass, and the activity of exo-enzymes that decompose labile components of soil organic matter (SOM, e.g., cellulose, amino sugars), while decreasing the activity of exo-enzymes that degrade recalcitrant SOM (e.g., polyphenols, lignin). However, delivery of C-only exudates had no effect on microbial biomass or overall exo-enzyme activity, and only increased microbial respiration. The theoretical decomposition model produced complementary results; the modeled microbial response to C-only exudates was constrained by limited N supply to support the synthesis of N-rich microbial biomass and exo-enzymes, while exuding C and N together elicited an increase in modeled microbial biomass, exo-enzyme activity, and decomposition. Thus, hypothesis (2) was supported, while hypothesis (1) was only supported when C and N compounds were exuded together. This study supports a cause-and-effect relationship between root exudation and enhanced microbial activity, and suggests that exudate stoichiometry is an important and underappreciated driver of microbial activity in rhizosphere soils.

Modeling the impact of the indigenous microbial population on the maximum population density of Salmonella on alfalfa.

PubMed

Rijgersberg, Hajo; Franz, Eelco; Nierop Groot, Masja; Tromp, Seth-Oscar

2013-07-01

Within a microbial risk assessment framework, modeling the maximum population density (MPD) of a pathogenic microorganism is important but often not considered. This paper describes a model predicting the MPD of Salmonella on alfalfa as a function of the initial contamination level, the total count of the indigenous microbial population, the maximum pathogen growth rate and the maximum population density of the indigenous microbial population. The model is parameterized by experimental data describing growth of Salmonella on sprouting alfalfa seeds at inoculum size, native microbial load and Pseudomonas fluorescens 2-79. The obtained model fits well to the experimental data, with standard errors less than ten percent of the fitted average values. The results show that the MPD of Salmonella is not only dictated by performance characteristics of Salmonella but depends on the characteristics of the indigenous microbial population like total number of cells and its growth rate. The model can improve the predictions of microbiological growth in quantitative microbial risk assessments. Using this model, the effects of preventive measures to reduce pathogenic load and a concurrent effect on the background population can be better evaluated. If competing microorganisms are more sensitive to a particular decontamination method, a pathogenic microorganism may grow faster and reach a higher level. More knowledge regarding the effect of the indigenous microbial population (size, diversity, composition) of food products on pathogen dynamics is needed in order to make adequate predictions of pathogen dynamics on various food products.

Modeling the unmeasurable: scaling soil physiology from microns to meters and seconds to centuries (Invited)

NASA Astrophysics Data System (ADS)

Schimel, J.; Xu, X.; Lawrence, C. R.

2013-12-01

Models are essential tools for linking microbial dynamics to their manifestations at large scales. Yet, developing mechanistically accurate models requires data that we often don't have and may not be able to get, such as the functional life-span of an extracellular enzyme. Yet there are approaches to condense complex microbial dynamics into 'workable' models. One example is in describing soil responses to moisture pulses. We developed a family of five separate models to capture microbial dynamics through dry/wet cycles. The simplest was a straight multi-pool, 1st-order decomposition model, with versions adding levels of microbial mechanism, culminating in one that included exoenzyme-breakdown of detritus. However, this identified the critical mechanism, not as exoenzymes, but as the production of a bioavailable C pool that accumulates in dry soil and is rapidly metabolized on rewetting. A final version of the model therefore stripped out explicit enzymes but retained separate polymer breakdown and substrate use; this model was the most robust. A second pervasive question in soil biology has been what controls the size of the microbial biomass across biomes? We approached this through a physiological model that regulated microbial C assimilation into biomass by two processes: initial assimilation followed by ongoing maintenance. Assimilation is a function of substrate quality, while maintenance is regulated by climate--notably the period of the year during which microbes are active. This model was tested against a global dataset of microbial biomass. It explains why, for example, deserts and tundra have relatively high proportions of their organic matter in microbial biomass, while the low substrate quality and long active periods common in temperate conifer forests lead to low biomass levels.

Representation of Dormant and Active Microbial Dynamics for Ecosystem Modeling

NASA Astrophysics Data System (ADS)

Wang, G.; Mayes, M. A.; Gu, L.; Schadt, C. W.

2013-12-01

Experimental observations and modeling efforts have shown that dormancy is likely a common strategy for microorganisms to contend with environmental stress. We review the state-of-the-art in modeling approaches for microbial dormancy and discuss the rationales of these models. We proved that the physiological state index model is not appropriate for describing transformation between active and dormant states. Based on the generally accepted assumptions summarized from ten existing models, we postulated a new synthetic microbial physiology component within the Microbial-ENzyme-mediated Decomposition (MEND) model. Both the steady state active fraction (rss) and substrate saturation level (Øss) positively depend on two physiological indices: α and β. The index α = mR /(μG+ mR), where μG and mR represent the maximum specific growth and maintenance rates, respectively, for active microbes. β denotes the ratio of dormant to active maintenance rate. The rss equals to Øss only under the condition of β→0, and they are identical to α. When substrate availability is the only limiting factor, the maximum rss is ca. 0.5 with α≤0.5 and β ≤0.01. This threshold value (0.5) of rss (not dynamic r) can explain the low active microbial fractions observed in undisturbed soils. The applications of the improved model to a 14C-labeled glucose induced respiration dataset and a batch experimental dataset show satisfactory model performance. We found that the exponential growth respiration rates can only be used to determine μG and initial active microbial biomass (Ba0), thus we suggest using respiration data representing both exponential growth and non-accelerating phases to robustly determine other important parameters such as initial total live microbial biomass (B0), initial active fraction (r0), μG, α, and the half-saturation constant (Ks). Similar improved representations of microbial physiology should be incorporated into existing ecosystem models in order to account for the significance of dormancy in microbially-mediated processes.

Integrated Environmental Modeling: Quantitative Microbial Risk Assessment

EPA Science Inventory

The presentation discusses the need for microbial assessments and presents a road map associated with quantitative microbial risk assessments, through an integrated environmental modeling approach. A brief introduction and the strengths of the current knowledge are illustrated. W...

Inferring Microbial Interactions in the Gut of the Hong Kong Whipping Frog (Polypedates megacephalus) and a Validation Using Probiotics

PubMed Central

Weng, Francis Cheng-Hsuan; Shaw, Grace Tzun-Wen; Weng, Chieh-Yin; Yang, Yi-Ju; Wang, Daryi

2017-01-01

The concerted activity of intestinal microbes is crucial to the health and development of their host organisms. Investigation of microbial interactions in the gut should deepen our understanding of how these micro-ecosystems function. Due to advances in Next Generation Sequencing (NGS) technologies, various bioinformatic strategies have been proposed to investigate these microbial interactions. However, due to the complexity of the intestinal microbial community and difficulties in monitoring their interactions, at present there is a gap between the theory and biological application. In order to construct and validate microbial relationships, we first induce a community shift from simple to complex by manipulating artificial hibernation (AH) in the treefrog Polypedates megacephalus. To monitor community growth and microbial interactions, we further performed a time-course screen using a 16S rRNA amplicon approach and a Lotka-Volterra model. Lotka-Volterra models, also known as predator–prey equations, predict the dynamics of microbial communities and how communities are structured and sustained. An interaction network of gut microbiota at the genus level in the treefrog was constructed using Metagenomic Microbial Interaction Simulator (MetaMIS) package. The interaction network obtained had 1,568 commensal, 1,737 amensal, 3,777 mutual, and 3,232 competitive relationships, e.g., Lactococcus garvieae has a commensal relationship with Corynebacterium variabile. To validate the interacting relationships, the gut microbe composition was analyzed after probiotic trials using single strain (L. garvieae, C. variabile, and Bacillus coagulans, respectively) and a combination of L. garvieae, C. variabile, and B. coagulans, because of the cooperative relationship among their respective genera identified in the interaction network. After a 2 week trial, we found via 16S rRNA amplicon analysis that the combination of cooperative microbes yielded significantly higher probiotic concentrations than single strains, and the immune response (interleukin-10 expression) also significantly changed in a manner consistent with improved probiotic effects. By taking advantage of microbial community shift from simple to complex, we thus constructed a reliable microbial interaction network, and validated it using probiotic strains as a test system. PMID:28424669

Microbial communities and soil fertility in flood irrigated orchards under different management systems in eastern spain

NASA Astrophysics Data System (ADS)

Morugán-Coronado, Alicia; García-Orenes, Fuensanta; Caravaca, Fuensanta; Roldán, Antonio

2016-04-01

Unsuitable land management such as the excessive use of herbicides can lead to a loss of soil fertility and a drastic reduction in the abundance of microbial populations and their functions related to nutrient cycling. Microbial communities are the most sensitive and rapid indicators of perturbations in agroecosystems. A field experiment was performed in an orange-trees orchard (Citrus sinensis) to assess the long-term effect of three different management systems on the soil microbial community biomass, structure and composition (phospholipid fatty acids (PLFAs) total, pattern, and abundance). The three agricultural systems assayed were established 30 years ago: herbicides (Glyphosate (N-(phosphonomethyl)glycine) with inorganic fertilizers (H), intensive ploughing and inorganic fertilizers (NPK 15%) (P) and organic farming (chipped pruned branches and weeds, manure from sheep and goats) (O). Nine soil samples were taken from each system. The results showed that the management practices including herbicides and intensive ploughing had similar results on soil microbial properties, while organic fertilization significantly increased microbial biomass, shifted the structure and composition of the soil microbial community, and stimulated microbial activity, when compared to inorganic fertilization systems; thus, enhancing the sustainability of this agroecosystem under semiarid conditions.

Survival of a microbial soil community under Martian conditions

NASA Astrophysics Data System (ADS)

Hansen, A. A.; Noernberg, P.; Merrison, J.; Lomstein, B. Aa.; Finster, K. W.

2003-04-01

Because of the similarities between Earth and Mars early history the hypothesis was forwarded that Mars is a site where extraterrestrial life might have and/or may still occur(red). Sample-return missions are planned by NASA and ESA to test this hypothesis. The enormous economic costs and the logistic challenges of these missions make earth-based model facilities inevitable. The Mars simulation system at University of Aarhus, Denmark allows microbiological experiments under Mars analogue conditions. Thus detailed studies on the effect of Mars environmental conditions on the survival and the activity of a natural microbial soil community were carried out. Changes in the soil community were determined with a suite of different approaches: 1) total microbial respiration activity was investigated with 14C-glucose, 2) the physiological profile was investigated by the EcoLog-system, 3) colony forming units were determined by plate counts and 4) the microbial diversity on the molecular level was accessed with Denaturing Gradient Gel Electrophoresis. The simulation experiments showed that a part of the bacterial community survived Martian conditions corresponding to 9 Sol. These and future simulation experiments will contribute to our understanding of the possibility for extraterrestrial and terrestrial life on Mars.

Magnitude and Mechanism of Siderophore-Mediated Competition at Low Iron Solubility in the Pseudomonas aeruginosa Pyochelin System.

PubMed

Schiessl, Konstanze T; Janssen, Elisabeth M-L; Kraemer, Stephan M; McNeill, Kristopher; Ackermann, Martin

2017-01-01

A central question in microbial ecology is whether microbial interactions are predominantly cooperative or competitive. The secretion of siderophores, microbial iron chelators, is a model system for cooperative interactions. However, siderophores have also been shown to mediate competition by sequestering available iron and making it unavailable to competitors. The details of how siderophores mediate competition are not well understood, especially considering the complex distribution of iron phases in the environment. One pertinent question is whether sequestering iron through siderophores can indeed be effective in natural conditions; many natural environments are characterized by large pools of precipitated iron, and it is conceivable that any soluble iron that is sequestered by siderophores is replenished by the dissolution of these precipitated iron sources. Our goal here was to address this issue, and investigate the magnitude and mechanism of siderophore-mediated competition in the presence of precipitated iron. We combined experimental work with thermodynamic modeling, using Pseudomonas aeruginosa as a model system and ferrihydrite precipitates as the iron source with low solubility. Our experiments show that competitive growth inhibition by the siderophore pyochelin is indeed efficient, and that inhibition of a competitor can even have a stronger growth-promoting effect than solubilization of precipitated iron. Based on the results of our thermodynamic models we conclude that the observed inhibition of a competitor is effective because sequestered iron is only very slowly replenished by the dissolution of precipitated iron. Our research highlights the importance of competitive benefits mediated by siderophores, and underlines that the dynamics of siderophore production and uptake in environmental communities could be a signature of competitive, not just cooperative, dynamics.

Biogeochemical cycling at the aquatic-terrestrial interface is linked to parafluvial hyporheic zone inundation history

NASA Astrophysics Data System (ADS)

Goldman, Amy E.; Graham, Emily B.; Crump, Alex R.; Kennedy, David W.; Romero, Elvira B.; Anderson, Carolyn G.; Dana, Karl L.; Resch, Charles T.; Fredrickson, Jim K.; Stegen, James C.

2017-09-01

The parafluvial hyporheic zone combines the heightened biogeochemical and microbial interactions indicative of a hyporheic region with direct atmospheric/terrestrial inputs and the effects of wet-dry cycles. Therefore, understanding biogeochemical cycling and microbial interactions in this ecotone is fundamental to understanding biogeochemical cycling at the aquatic-terrestrial interface and to creating robust hydrobiogeochemical models of dynamic river corridors. We aimed to (i) characterize biogeochemical and microbial differences in the parafluvial hyporheic zone across a small spatial domain (6 lateral meters) that spans a breadth of inundation histories and (ii) examine how parafluvial hyporheic sediments respond to laboratory-simulated re-inundation. Surface sediment was collected at four elevations along transects perpendicular to flow of the Columbia River, eastern WA, USA. The sediments were inundated by the river 0, 13, 127, and 398 days prior to sampling. Spatial variation in environmental variables (organic matter, moisture, nitrate, glucose, % C, % N) and microbial communities (16S and internal transcribed spacer (ITS) rRNA gene sequencing, qPCR) were driven by differences in inundation history. Microbial respiration did not differ significantly across inundation histories prior to forced inundation in laboratory incubations. Forced inundation suppressed microbial respiration across all histories, but the degree of suppression was dramatically different between the sediments saturated and unsaturated at the time of sample collection, indicating a binary threshold response to re-inundation. We present a conceptual model in which irregular hydrologic fluctuations facilitate microbial communities adapted to local conditions and a relatively high flux of CO2. Upon rewetting, microbial communities are initially suppressed metabolically, which results in lower CO2 flux rates primarily due to suppression of fungal respiration. Following prolonged inundation, the microbial community adapts to saturation by shifting composition, and the CO2 flux rebounds to prior levels due to the subsequent change in respiration. Our results indicate that the time between inundation events can push the system into alternate states: we suggest (i) that, above some threshold of inundation interval, re-inundation suppresses respiration to a consistent, low rate and (ii) that, below some inundation interval, re-inundation has a minor effect on respiration. Extending reactive transport models to capture processes that govern such dynamics will provide more robust predictions of river corridor biogeochemical function under altered surface water flow regimes in both managed and natural watersheds.

Microbial load monitor

NASA Technical Reports Server (NTRS)

Caplin, R. S.; Royer, E. R.

1978-01-01

Attempts are made to provide a total design of a Microbial Load Monitor (MLM) system flight engineering model. Activities include assembly and testing of Sample Receiving and Card Loading Devices (SRCLDs), operator related software, and testing of biological samples in the MLM. Progress was made in assembling SRCLDs with minimal leaks and which operate reliably in the Sample Loading System. Seven operator commands are used to control various aspects of the MLM such as calibrating and reading the incubating reading head, setting the clock and reading time, and status of Card. Testing of the instrument, both in hardware and biologically, was performed. Hardware testing concentrated on SRCLDs. Biological testing covered 66 clinical and seeded samples. Tentative thresholds were set and media performance listed.

Microbial and metabolic multi-omic correlations in systemic sclerosis patients.

PubMed

Bellocchi, Chiara; Fernández-Ochoa, Álvaro; Montanelli, Gaia; Vigone, Barbara; Santaniello, Alessandro; Milani, Christian; Quirantes-Piné, Rosa; Borrás-Linares, Isabel; Ventura, Marco; Segura-Carrettero, Antonio; Alarcón-Riquelme, Marta Eugenia; Beretta, Lorenzo

2018-06-01

Intestinal microbiota has been associated with systemic autoimmune diseases, yet the functional consequences of these associations are elusive. We characterized the fecal microbiota (16S rRNA gene amplification and sequencing) and the plasma metabolome (high-performance liquid chromatography coupled to mass spectrometry) in 59 patients with systemic sclerosis (SSc) and 28 healthy controls (HCs). Microbial and metabolic data were cross-correlated to find meaningful associations after extensive data mining analysis and internal validation. Our data show that a reduced model of nine bacteria is capable of differentiating HCs from SSc patients. SSc gut microbiota is characterized by a reduction in protective butyrate-producing bacteria and by an increase in proinflammatory noxious genera, especially Desulfovibrio. From the metabolic point of view, a multivariate model with 17 metabolite intermediates well distinguished cases from controls. The most interesting peaks we found were identified as glycerophospholipid metabolites and benzene derivatives. The microbial and metabolic data showed significant interactions between Desulfovibrio and alpha-N-phenylacetyl-l-glutamine and 2,4-dinitrobenzenesulfonic acid. Our data suggest that in SSc, intestinal microbiota is characterized by proinflammatory alterations subtly entwined with the metabolic state. Desulfovibrio is a relevant actor in gut dysbiosis that may promote intestinal damage and influence amino acid metabolism. © 2018 The Authors. Annals of the New York Academy of Sciences published by Wiley Periodicals Inc. on behalf of The New York Academy of Sciences.

Microbial Toluene Removal in Hypoxic Model Constructed Wetlands Occurs Predominantly via the Ring Monooxygenation Pathway.

PubMed

Martínez-Lavanchy, P M; Chen, Z; Lünsmann, V; Marin-Cevada, V; Vilchez-Vargas, R; Pieper, D H; Reiche, N; Kappelmeyer, U; Imparato, V; Junca, H; Nijenhuis, I; Müller, J A; Kuschk, P; Heipieper, H J

2015-09-01

In the present study, microbial toluene degradation in controlled constructed wetland model systems, planted fixed-bed reactors (PFRs), was queried with DNA-based methods in combination with stable isotope fractionation analysis and characterization of toluene-degrading microbial isolates. Two PFR replicates were operated with toluene as the sole external carbon and electron source for 2 years. The bulk redox conditions in these systems were hypoxic to anoxic. The autochthonous bacterial communities, as analyzed by Illumina sequencing of 16S rRNA gene amplicons, were mainly comprised of the families Xanthomonadaceae, Comamonadaceae, and Burkholderiaceae, plus Rhodospirillaceae in one of the PFR replicates. DNA microarray analyses of the catabolic potentials for aromatic compound degradation suggested the presence of the ring monooxygenation pathway in both systems, as well as the anaerobic toluene pathway in the PFR replicate with a high abundance of Rhodospirillaceae. The presence of catabolic genes encoding the ring monooxygenation pathway was verified by quantitative PCR analysis, utilizing the obtained toluene-degrading isolates as references. Stable isotope fractionation analysis showed low-level of carbon fractionation and only minimal hydrogen fractionation in both PFRs, which matches the fractionation signatures of monooxygenation and dioxygenation. In combination with the results of the DNA-based analyses, this suggests that toluene degradation occurs predominantly via ring monooxygenation in the PFRs. Copyright © 2015, American Society for Microbiology. All Rights Reserved.

Microbial community dynamics in soil aggregates shape biogeochemical gas fluxes from soil profiles - upscaling an aggregate biophysical model.

PubMed

Ebrahimi, Ali; Or, Dani

2016-09-01

Microbial communities inhabiting soil aggregates dynamically adjust their activity and composition in response to variations in hydration and other external conditions. These rapid dynamics shape signatures of biogeochemical activity and gas fluxes emitted from soil profiles. Recent mechanistic models of microbial processes in unsaturated aggregate-like pore networks revealed a highly dynamic interplay between oxic and anoxic microsites jointly shaped by hydration conditions and by aerobic and anaerobic microbial community abundance and self-organization. The spatial extent of anoxic niches (hotspots) flicker in time (hot moments) and support substantial anaerobic microbial activity even in aerated soil profiles. We employed an individual-based model for microbial community life in soil aggregate assemblies represented by 3D angular pore networks. Model aggregates of different sizes were subjected to variable water, carbon and oxygen contents that varied with soil depth as boundary conditions. The study integrates microbial activity within aggregates of different sizes and soil depth to obtain estimates of biogeochemical fluxes from the soil profile. The results quantify impacts of dynamic shifts in microbial community composition on CO2 and N2 O production rates in soil profiles in good agreement with experimental data. Aggregate size distribution and the shape of resource profiles in a soil determine how hydration dynamics shape denitrification and carbon utilization rates. Results from the mechanistic model for microbial activity in aggregates of different sizes were used to derive parameters for analytical representation of soil biogeochemical processes across large scales of practical interest for hydrological and climate models. © 2016 John Wiley & Sons Ltd.

Intelligibility in microbial complex systems: Wittgenstein and the score of life.

PubMed

Baquero, Fernando; Moya, Andrés

2012-01-01

Knowledge in microbiology is reaching an extreme level of diversification and complexity, which paradoxically results in a strong reduction in the intelligibility of microbial life. In our days, the "score of life" metaphor is more accurate to express the complexity of living systems than the classic "book of life." Music and life can be represented at lower hierarchical levels by music scores and genomic sequences, and such representations have a generational influence in the reproduction of music and life. If music can be considered as a representation of life, such representation remains as unthinkable as life itself. The analysis of scores and genomic sequences might provide mechanistic, phylogenetic, and evolutionary insights into music and life, but not about their real dynamics and nature, which is still maintained unthinkable, as was proposed by Wittgenstein. As complex systems, life or music is composed by thinkable and only showable parts, and a strategy of half-thinking, half-seeing is needed to expand knowledge. Complex models for complex systems, based on experiences on trans-hierarchical integrations, should be developed in order to provide a mixture of legibility and imageability of biological processes, which should lead to higher levels of intelligibility of microbial life.

Physiological actions of preservative agents: prospective of use of modern microbiological techniques in assessing microbial behaviour in food preservation.

PubMed

Brul, Stanley; Coote, Peter; Oomes, Suus; Mensonides, Femke; Hellingwerf, Klaas; Klis, Frans

2002-11-15

In this mini-review, various aspects of homeostasis of microbial cells and its perturbation by antimicrobial agents will be discussed. First, outlining the position that the physiological studies on microbial behaviour using the modern molecular tools should have in food science sets the scene for the studies. Subsequently, the advent of functional genomics is discussed that allows full coverage of cellular reactions at unprecedented levels. Examples of weak organic acid resistance, the stress response against natural antimicrobial agents and responses against physicochemical factors show how we can now "open the black box" that microbes are, look inside and begin to understand how different cellular signalling cables are wired together. Using the analogy with machines, it will be indicated how the use of various signalling systems depends on the availability of substrates "fuel" to let the systems act in the context of the minimum energetic requirement cells have to let their housekeeping systems run. The outlook illustrates how new insights might be used to device knowledge-based rather than empirical combinations of preservation systems and how risk assessment models might be deviced that link the mechanistic insight to risk distributions of events in food manufacturing.

Intelligibility in microbial complex systems: Wittgenstein and the score of life

PubMed Central

Baquero, Fernando; Moya, Andrés

2012-01-01

Knowledge in microbiology is reaching an extreme level of diversification and complexity, which paradoxically results in a strong reduction in the intelligibility of microbial life. In our days, the “score of life” metaphor is more accurate to express the complexity of living systems than the classic “book of life.” Music and life can be represented at lower hierarchical levels by music scores and genomic sequences, and such representations have a generational influence in the reproduction of music and life. If music can be considered as a representation of life, such representation remains as unthinkable as life itself. The analysis of scores and genomic sequences might provide mechanistic, phylogenetic, and evolutionary insights into music and life, but not about their real dynamics and nature, which is still maintained unthinkable, as was proposed by Wittgenstein. As complex systems, life or music is composed by thinkable and only showable parts, and a strategy of half-thinking, half-seeing is needed to expand knowledge. Complex models for complex systems, based on experiences on trans-hierarchical integrations, should be developed in order to provide a mixture of legibility and imageability of biological processes, which should lead to higher levels of intelligibility of microbial life. PMID:22919679

Rate-limiting step analysis of the microbial desulfurization of dibenzothiophene in a model oil system

PubMed Central

Abin-Fuentes, Andres; Leung, James C.; Mohamed, Magdy El-Said; Wang, Daniel IC; Prather, Kristala LJ

2014-01-01

A mechanistic analysis of the various mass transport and kinetic steps in the microbial desulfurization of dibenzothiophene (DBT) by Rhodococcus erythropolis IGTS8 in a model biphasic (oil-water), small-scale system was performed. The biocatalyst was distributed into three populations, free cells in the aqueous phase, cell aggregates and oil-adhered cells, and the fraction of cells in each population was measured. The power input per volume (P/V) and the impeller tip speed (vtip) were identified as key operating parameters in determining whether the system is mass transport controlled or kinetically controlled. Oil-water DBT mass transport was found to not be limiting under the conditions tested. Experimental results at both the 100 mL and 4L (bioreactor) scales suggest that agitation leading to P/V greater than 10,000 W/ m3 and/or vtip greater than 0.67 m/s is sufficient to overcome the major mass transport limitation in the system, which was the diffusion of DBT within the biocatalyst aggregates. PMID:24284557

Effect of Nisin's Controlled Release on Microbial Growth as Modeled for Micrococcus luteus.

PubMed

Balasubramanian, Aishwarya; Lee, Dong Sun; Chikindas, Michael L; Yam, Kit L

2011-06-01

The need for safe food products has motivated food scientists and industry to find novel technologies for antimicrobial delivery for improving food safety and quality. Controlled release packaging is a novel technology that uses the package to deliver antimicrobials in a controlled manner and sustain antimicrobial stress on the targeted microorganism over the required shelf life. This work studied the effect of controlled release of nisin to inhibit growth of Micrococcus luteus (a model microorganism) using a computerized syringe pump system to mimic the release of nisin from packaging films which was characterized by an initially fast rate and a slower rate as time progressed. The results show that controlled release of nisin was strikingly more effective than instantly added ("formulated") nisin. While instant addition experiments achieved microbial inhibition only at the beginning, controlled release experiments achieved complete microbial inhibition for a longer time, even when as little as 15% of the amount of nisin was used as compared to instant addition.

Historical precipitation predictably alters the shape and magnitude of microbial functional response to soil moisture.

PubMed

Averill, Colin; Waring, Bonnie G; Hawkes, Christine V

2016-05-01

Soil moisture constrains the activity of decomposer soil microorganisms, and in turn the rate at which soil carbon returns to the atmosphere. While increases in soil moisture are generally associated with increased microbial activity, historical climate may constrain current microbial responses to moisture. However, it is not known if variation in the shape and magnitude of microbial functional responses to soil moisture can be predicted from historical climate at regional scales. To address this problem, we measured soil enzyme activity at 12 sites across a broad climate gradient spanning 442-887 mm mean annual precipitation. Measurements were made eight times over 21 months to maximize sampling during different moisture conditions. We then fit saturating functions of enzyme activity to soil moisture and extracted half saturation and maximum activity parameter values from model fits. We found that 50% of the variation in maximum activity parameters across sites could be predicted by 30-year mean annual precipitation, an indicator of historical climate, and that the effect is independent of variation in temperature, soil texture, or soil carbon concentration. Based on this finding, we suggest that variation in the shape and magnitude of soil microbial response to soil moisture due to historical climate may be remarkably predictable at regional scales, and this approach may extend to other systems. If historical contingencies on microbial activities prove to be persistent in the face of environmental change, this approach also provides a framework for incorporating historical climate effects into biogeochemical models simulating future global change scenarios. © 2016 John Wiley & Sons Ltd.

Possibilities for extremophilic microorganisms in microbial electrochemical systems

PubMed Central

Dopson, Mark; Ni, Gaofeng; Sleutels, Tom HJA

2015-01-01

Microbial electrochemical systems exploit the metabolism of microorganisms to generate electrical energy or a useful product. In the past couple of decades, the application of microbial electrochemical systems has increased from the use of wastewaters to produce electricity to a versatile technology that can use numerous sources for the extraction of electrons on the one hand, while on the other hand these electrons can be used to serve an ever increasing number of functions. Extremophilic microorganisms grow in environments that are hostile to most forms of life and their utilization in microbial electrochemical systems has opened new possibilities to oxidize substrates in the anode and produce novel products in the cathode. For example, extremophiles can be used to oxidize sulfur compounds in acidic pH to remediate wastewaters, generate electrical energy from marine sediment microbial fuel cells at low temperatures, desalinate wastewaters and act as biosensors of low amounts of organic carbon. In this review, we will discuss the recent advances that have been made in using microbial catalysts under extreme conditions and show possible new routes that extremophilic microorganisms open for microbial electrochemical systems. PMID:26474966

Microbiologic evaluation of microfiber mops for surface disinfection.

PubMed

Rutala, William A; Gergen, Maria F; Weber, David J

2007-11-01

Recently, health care facilities have started to use a microfiber mopping technique rather than a conventional, cotton string mop to clean floors. The effectiveness of microfiber mops to reduce microbial levels on floors was investigated. We compared the efficacy of microfiber mops with that of conventional, cotton string mops in 3 test conditions (cotton mop and standard wringer bucket, microfiber mop and standard wringer bucket, microfiber system). Twenty-four rooms were evaluated for each test condition. RODAC plates containing D/E Neutralizing Agar were used to assess "precleaning" and "postcleaning" microbial levels. The microfiber system demonstrated superior microbial removal compared with cotton string mops when used with a detergent cleaner (95% vs 68%, respectively). The use of a disinfectant did not improve the microbial elimination demonstrated by the microfiber system (95% vs 95%, respectively). However, use of disinfectant did significantly improve microbial removal when a cotton string mop was used (95% vs 68%, respectively). The microfiber system demonstrated superior microbial removal compared with cotton string mops when used with a detergent cleaner. The use of a disinfectant did not improve the microbial elimination demonstrated by the microfiber system.

Is DOM driver of the microbial carrying capacity in pristine porous groundwater ecosystems? - lab-scale experiments in 2D sediment flow-through microcosms

NASA Astrophysics Data System (ADS)

Hofmann, Roland; Griebler, Christian

2017-04-01

Groundwater ecosystems are an essential resource for drinking water and at the same time constitute fascinating habitats subject to increasing (anthropogenic) disturbances. In our research, we look for ways to qualitatively and quantitatively access, and predict the resistance and resilience (potential) of groundwater ecosystems in consequence of selected disturbances. As a central goal we hope to identify and quantify the underlying biological and ecological key drivers of the microbial Carrying Capacity (mCC) - an ecological concept established in macro-ecology - we assume directly connected to the ecosystem's productivity and the resistance and resilience of aquifers. We further hypothesize, that the ecosystems' mCC is a result of available energy and constitutes a promising proxy for the potential of groundwater ecosystems to withstand impacts and recover from it. In a first approach we studied the dynamics of the microbial standing stock (biomass) and growth (productivity) productivity of a natural groundwater microbial community in parallel 2-D sediment flow-through systems. Selected zones of the model aquifers were disturbed by elevated DOM concentrations. Both the 'mobile' (free floating) and 'sessile' (sediment attached) microbial components were followed over time in terms of biomass, growth, and specific activities (ATP, carbon use efficiency) and taxonomic composition. Sediment regions supplied with elevated concentrations of natural DOM showed increased biomass, activities and taxonomic richness with the sediment community, while differences in the mobile microbial were marginal. Specifically, the carbon use efficiency was significantly increased in the DOM amended sediment zones. In contrast, the microbial community that received the mainly refractory natural background DOM was able to metabolize polymers more efficiently in substrate use tests (ECOLOG), seen as an adaptation to the energy-poor subsurface. Quasi-stationary conditions were reached in the model aquifers only after several weeks. The quantitative link between microbial productivity and mCC is currently evaluated.

Integrating microbial diversity in soil carbon dynamic models parameters

NASA Astrophysics Data System (ADS)

Louis, Benjamin; Menasseri-Aubry, Safya; Leterme, Philippe; Maron, Pierre-Alain; Viaud, Valérie

2015-04-01

Faced with the numerous concerns about soil carbon dynamic, a large quantity of carbon dynamic models has been developed during the last century. These models are mainly in the form of deterministic compartment models with carbon fluxes between compartments represented by ordinary differential equations. Nowadays, lots of them consider the microbial biomass as a compartment of the soil organic matter (carbon quantity). But the amount of microbial carbon is rarely used in the differential equations of the models as a limiting factor. Additionally, microbial diversity and community composition are mostly missing, although last advances in soil microbial analytical methods during the two past decades have shown that these characteristics play also a significant role in soil carbon dynamic. As soil microorganisms are essential drivers of soil carbon dynamic, the question about explicitly integrating their role have become a key issue in soil carbon dynamic models development. Some interesting attempts can be found and are dominated by the incorporation of several compartments of different groups of microbial biomass in terms of functional traits and/or biogeochemical compositions to integrate microbial diversity. However, these models are basically heuristic models in the sense that they are used to test hypotheses through simulations. They have rarely been confronted to real data and thus cannot be used to predict realistic situations. The objective of this work was to empirically integrate microbial diversity in a simple model of carbon dynamic through statistical modelling of the model parameters. This work is based on available experimental results coming from a French National Research Agency program called DIMIMOS. Briefly, 13C-labelled wheat residue has been incorporated into soils with different pedological characteristics and land use history. Then, the soils have been incubated during 104 days and labelled and non-labelled CO2 fluxes have been measured at ten sampling time in order to follow the dynamic of residue and soil organic matter mineralization. Diversity, structure and composition of microbial communities have been characterized before incubation time. The dynamic of carbon fluxes through CO2 emissions has been modelled through a simple model. Using statistical tools, relations between parameters of the model and microbial diversity indexes and/or pedological characteristics have been developed and integrated to the model. First results show that global diversity has an impact on the models parameters. Moreover, larger fungi diversity seems to lead to larger parameters representing decomposition rates and/or carbon use efficiencies than bacterial diversity. Classically, pedological factors such as soil pH and texture must also be taken into account.

A Workflow to Model Microbial Loadings in Watersheds

EPA Science Inventory

Many watershed models simulate overland and instream microbial fate and transport, but few actually provide loading rates on land surfaces and point sources to the water body network. This paper describes the underlying general equations for microbial loading rates associated wit...

Why fruit rots: theoretical support for Janzen's theory of microbe-macrobe competition.

PubMed

Ruxton, Graeme D; Wilkinson, David M; Schaefer, H Martin; Sherratt, Thomas N

2014-05-07

We present a formal model of Janzen's influential theory that competition for resources between microbes and vertebrates causes microbes to be selected to make these resources unpalatable to vertebrates. That is, fruit rots, seeds mould and meat spoils, in part, because microbes gain a selective advantage if they can alter the properties of these resources to avoid losing the resources to vertebrate consumers. A previous model had failed to find circumstances in which such a costly spoilage trait could flourish; here, we present a simple analytic model of a general situation where costly microbial spoilage is selected and persists. We argue that the key difference between the two models lies in their treatments of microbial dispersal. If microbial dispersal is sufficiently spatially constrained that different resource items can have differing microbial communities, then spoilage will be selected; however, if microbial dispersal has a strong homogenizing effect on the microbial community then spoilage will not be selected. We suspect that both regimes will exist in the natural world, and suggest how future empirical studies could explore the influence of microbial dispersal on spoilage.

Modelling the competition of planktonic and sessile aerobic heterotrophs for complementary nutrients in biofilm reactor.

PubMed

Lu, T; Saikaly, P E; Oerther, D B

2007-01-01

A comprehensive, simplified microbial biofilm model was developed to evaluate the impact of bioreactor operating parameters on changes in microbial population abundance. Biofilm simulations were conducted using three special cases: fully penetrated, internal mass transfer resistance and external mass transfer resistance. The results of model simulations showed that for certain operating conditions, competition for growth limiting nutrients generated oscillations in the abundance of planktonic and sessile microbial populations. These oscillations resulted in the violation of the competitive exclusion principle where the number of microbial populations was greater than the number of growth limiting nutrients. However, the operating conditions which impacted microbial community diversity were different for the three special cases. Comparing the results of model simulations for dispersed-growth, biofilms and bioflocs showed that oscillations and microbial community diversity were a function of competition as well as other key features of the ecosystem. The significance of the current study is that it is the first to examine competition as a mechanism for controlling microbial community diversity in biofilm reactors.

Mineral solubility and free energy controls on microbial reaction kinetics: Application to contaminant transport in the subsurface

DOE Office of Scientific and Technical Information (OSTI.GOV)

Taillefert, Martial; Van Cappellen, Philippe

Recent developments in the theoretical treatment of geomicrobial reaction processes have resulted in the formulation of kinetic models that directly link the rates of microbial respiration and growth to the corresponding thermodynamic driving forces. The overall objective of this project was to verify and calibrate these kinetic models for the microbial reduction of uranium(VI) in geochemical conditions that mimic as much as possible field conditions. The approach combined modeling of bacterial processes using new bioenergetic rate laws, laboratory experiments to determine the bioavailability of uranium during uranium bioreduction, evaluation of microbial growth yield under energy-limited conditions using bioreactor experiments, competitionmore » experiments between metabolic processes in environmentally relevant conditions, and model applications at the field scale. The new kinetic descriptions of microbial U(VI) and Fe(III) reduction should replace those currently used in reactive transport models that couple catabolic energy generation and growth of microbial populations to the rates of biogeochemical redox processes. The above work was carried out in collaboration between the groups of Taillefert (batch reactor experiments and reaction modeling) at Georgia Tech and Van Cappellen (retentostat experiments and reactive transport modeling) at University of Waterloo (Canada).« less

Quantitative analysis of microbial contamination in private drinking water supply systems.

PubMed

Allevi, Richard P; Krometis, Leigh-Anne H; Hagedorn, Charles; Benham, Brian; Lawrence, Annie H; Ling, Erin J; Ziegler, Peter E

2013-06-01

Over one million households rely on private water supplies (e.g. well, spring, cistern) in the Commonwealth of Virginia, USA. The present study tested 538 private wells and springs in 20 Virginia counties for total coliforms (TCs) and Escherichia coli along with a suite of chemical contaminants. A logistic regression analysis was used to investigate potential correlations between TC contamination and chemical parameters (e.g. NO3(-), turbidity), as well as homeowner-provided survey data describing system characteristics and perceived water quality. Of the 538 samples collected, 41% (n = 221) were positive for TCs and 10% (n = 53) for E. coli. Chemical parameters were not statistically predictive of microbial contamination. Well depth, water treatment, and farm location proximate to the water supply were factors in a regression model that predicted presence/absence of TCs with 74% accuracy. Microbial and chemical source tracking techniques (Bacteroides gene Bac32F and HF183 detection via polymerase chain reaction and optical brightener detection via fluorometry) identified four samples as likely contaminated with human wastewater.

Deciphering the Counterplay of Aspergillus fumigatus Infection and Host Inflammation by Evolutionary Games on Graphs

NASA Astrophysics Data System (ADS)

Pollmächer, Johannes; Timme, Sandra; Schuster, Stefan; Brakhage, Axel A.; Zipfel, Peter F.; Figge, Marc Thilo

2016-06-01

Microbial invaders are ubiquitously present and pose the constant risk of infections that are opposed by various defence mechanisms of the human immune system. A tight regulation of the immune response ensures clearance of microbial invaders and concomitantly limits host damage that is crucial for host viability. To investigate the counterplay of infection and inflammation, we simulated the invasion of the human-pathogenic fungus Aspergillus fumigatus in lung alveoli by evolutionary games on graphs. The layered structure of the innate immune system is represented by a sequence of games in the virtual model. We show that the inflammatory cascade of the immune response is essential for microbial clearance and that the inflammation level correlates with the infection-dose. At low infection-doses, corresponding to daily inhalation of conidia, the resident alveolar macrophages may be sufficient to clear infections, however, at higher infection-doses their primary task shifts towards recruitment of neutrophils to infection sites.

Deciphering the Counterplay of Aspergillus fumigatus Infection and Host Inflammation by Evolutionary Games on Graphs

PubMed Central

Pollmächer, Johannes; Timme, Sandra; Schuster, Stefan; Brakhage, Axel A.; Zipfel, Peter F.; Figge, Marc Thilo

2016-01-01

Microbial invaders are ubiquitously present and pose the constant risk of infections that are opposed by various defence mechanisms of the human immune system. A tight regulation of the immune response ensures clearance of microbial invaders and concomitantly limits host damage that is crucial for host viability. To investigate the counterplay of infection and inflammation, we simulated the invasion of the human-pathogenic fungus Aspergillus fumigatus in lung alveoli by evolutionary games on graphs. The layered structure of the innate immune system is represented by a sequence of games in the virtual model. We show that the inflammatory cascade of the immune response is essential for microbial clearance and that the inflammation level correlates with the infection-dose. At low infection-doses, corresponding to daily inhalation of conidia, the resident alveolar macrophages may be sufficient to clear infections, however, at higher infection-doses their primary task shifts towards recruitment of neutrophils to infection sites. PMID:27291424

New multi-scale perspectives on the stromatolites of Shark Bay, Western Australia.

PubMed

Suosaari, E P; Reid, R P; Playford, P E; Foster, J S; Stolz, J F; Casaburi, G; Hagan, P D; Chirayath, V; Macintyre, I G; Planavsky, N J; Eberli, G P

2016-02-03

A recent field-intensive program in Shark Bay, Western Australia provides new multi-scale perspectives on the world's most extensive modern stromatolite system. Mapping revealed a unique geographic distribution of morphologically distinct stromatolite structures, many of them previously undocumented. These distinctive structures combined with characteristic shelf physiography define eight 'Stromatolite Provinces'. Morphological and molecular studies of microbial mat composition resulted in a revised growth model where coccoid cyanobacteria predominate in mat communities forming lithified discrete stromatolite buildups. This contradicts traditional views that stromatolites with the best lamination in Hamelin Pool are formed by filamentous cyanobacterial mats. Finally, analysis of internal fabrics of stromatolites revealed pervasive precipitation of microcrystalline carbonate (i.e. micrite) in microbial mats forming framework and cement that may be analogous to the micritic microstructures typical of Precambrian stromatolites. These discoveries represent fundamental advances in our knowledge of the Shark Bay microbial system, laying a foundation for detailed studies of stromatolite morphogenesis that will advance our understanding of benthic ecosystems on the early Earth.

The Microbiota, Chemical Symbiosis, and Human Disease

PubMed Central

Redinbo, Matthew R.

2014-01-01

Our understanding of mammalian-microbial mutualism has expanded by combing microbial sequencing with evolving molecular and cellular methods, and unique model systems. Here, the recent literature linking the microbiota to diseases of three of the key mammalian mucosal epithelial compartments – nasal, lung and gastrointestinal (GI) tract – is reviewed with a focus on new knowledge about the taxa, species, proteins and chemistry that promote health and impact progression toward disease. The information presented is further organized by specific diseases now associated with the microbiota:, Staphylococcus aureus infection and rhinosinusitis in the nasal-sinus mucosa; cystic fibrosis (CF), chronic obstructive pulmonary disorder (COPD), and asthma in the pulmonary tissues. For the vast and microbially dynamic GI compartment, several disorders are considered, including obesity, atherosclerosis, Crohn’s disease, ulcerative colitis, drug toxicity, and even autism. Our appreciation of the chemical symbiosis ongoing between human systems and the microbiota continues to grow, and suggest new opportunities for modulating this symbiosis using designed interventions. PMID:25305474

Direct evidence for microbial-derived soil organic matter formation and its ecophysiological controls

DOE PAGES

Kallenbach, Cynthia M.; Frey, Serita D.; Grandy, A. Stuart

2016-11-28

Soil organic matter (SOM) and the carbon and nutrients therein drive fundamental submicron- to global-scale biogeochemical processes and influence carbon-climate feedbacks. Consensus is emerging that microbial materials are an important constituent of stable SOM, and new conceptual and quantitative SOM models are rapidly incorporating this view. However, direct evidence demonstrating that microbial residues account for the chemistry, stability and abundance of SOM is still lacking. Further, emerging models emphasize the stabilization of microbial-derived SOM by abiotic mechanisms, while the effects of microbial physiology on microbial residue production remain unclear. Here we provide the first direct evidence that soil microbes producemore » chemically diverse, stable SOM. As a result, we show that SOM accumulation is driven by distinct microbial communities more so than clay mineralogy, where microbial-derived SOM accumulation is greatest in soils with higher fungal abundances and more efficient microbial biomass production.« less

Direct evidence for microbial-derived soil organic matter formation and its ecophysiological controls

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kallenbach, Cynthia M.; Frey, Serita D.; Grandy, A. Stuart

Soil organic matter (SOM) and the carbon and nutrients therein drive fundamental submicron- to global-scale biogeochemical processes and influence carbon-climate feedbacks. Consensus is emerging that microbial materials are an important constituent of stable SOM, and new conceptual and quantitative SOM models are rapidly incorporating this view. However, direct evidence demonstrating that microbial residues account for the chemistry, stability and abundance of SOM is still lacking. Further, emerging models emphasize the stabilization of microbial-derived SOM by abiotic mechanisms, while the effects of microbial physiology on microbial residue production remain unclear. Here we provide the first direct evidence that soil microbes producemore » chemically diverse, stable SOM. As a result, we show that SOM accumulation is driven by distinct microbial communities more so than clay mineralogy, where microbial-derived SOM accumulation is greatest in soils with higher fungal abundances and more efficient microbial biomass production.« less

Direct evidence for microbial-derived soil organic matter formation and its ecophysiological controls

NASA Astrophysics Data System (ADS)

Kallenbach, Cynthia M.; Frey, Serita D.; Grandy, A. Stuart

2016-11-01

Soil organic matter (SOM) and the carbon and nutrients therein drive fundamental submicron- to global-scale biogeochemical processes and influence carbon-climate feedbacks. Consensus is emerging that microbial materials are an important constituent of stable SOM, and new conceptual and quantitative SOM models are rapidly incorporating this view. However, direct evidence demonstrating that microbial residues account for the chemistry, stability and abundance of SOM is still lacking. Further, emerging models emphasize the stabilization of microbial-derived SOM by abiotic mechanisms, while the effects of microbial physiology on microbial residue production remain unclear. Here we provide the first direct evidence that soil microbes produce chemically diverse, stable SOM. We show that SOM accumulation is driven by distinct microbial communities more so than clay mineralogy, where microbial-derived SOM accumulation is greatest in soils with higher fungal abundances and more efficient microbial biomass production.

Direct evidence for microbial-derived soil organic matter formation and its ecophysiological controls.

PubMed

Kallenbach, Cynthia M; Frey, Serita D; Grandy, A Stuart

2016-11-28

Soil organic matter (SOM) and the carbon and nutrients therein drive fundamental submicron- to global-scale biogeochemical processes and influence carbon-climate feedbacks. Consensus is emerging that microbial materials are an important constituent of stable SOM, and new conceptual and quantitative SOM models are rapidly incorporating this view. However, direct evidence demonstrating that microbial residues account for the chemistry, stability and abundance of SOM is still lacking. Further, emerging models emphasize the stabilization of microbial-derived SOM by abiotic mechanisms, while the effects of microbial physiology on microbial residue production remain unclear. Here we provide the first direct evidence that soil microbes produce chemically diverse, stable SOM. We show that SOM accumulation is driven by distinct microbial communities more so than clay mineralogy, where microbial-derived SOM accumulation is greatest in soils with higher fungal abundances and more efficient microbial biomass production.

From Genes to Ecosystems in Microbiology: Modeling Approaches and the Importance of Individuality

PubMed Central

Kreft, Jan-Ulrich; Plugge, Caroline M.; Prats, Clara; Leveau, Johan H. J.; Zhang, Weiwen; Hellweger, Ferdi L.

2017-01-01

Models are important tools in microbial ecology. They can be used to advance understanding by helping to interpret observations and test hypotheses, and to predict the effects of ecosystem management actions or a different climate. Over the past decades, biological knowledge and ecosystem observations have advanced to the molecular and in particular gene level. However, microbial ecology models have changed less and a current challenge is to make them utilize the knowledge and observations at the genetic level. We review published models that explicitly consider genes and make predictions at the population or ecosystem level. The models can be grouped into three general approaches, i.e., metabolic flux, gene-centric and agent-based. We describe and contrast these approaches by applying them to a hypothetical ecosystem and discuss their strengths and weaknesses. An important distinguishing feature is how variation between individual cells (individuality) is handled. In microbial ecosystems, individual heterogeneity is generated by a number of mechanisms including stochastic interactions of molecules (e.g., gene expression), stochastic and deterministic cell division asymmetry, small-scale environmental heterogeneity, and differential transport in a heterogeneous environment. This heterogeneity can then be amplified and transferred to other cell properties by several mechanisms, including nutrient uptake, metabolism and growth, cell cycle asynchronicity and the effects of age and damage. For example, stochastic gene expression may lead to heterogeneity in nutrient uptake enzyme levels, which in turn results in heterogeneity in intracellular nutrient levels. Individuality can have important ecological consequences, including division of labor, bet hedging, aging and sub-optimality. Understanding the importance of individuality and the mechanism(s) underlying it for the specific microbial system and question investigated is essential for selecting the optimal modeling strategy. PMID:29230200

Effect Of Spaceflight On Microbial Gene Expression And Virulence: Preliminary Results From Microbe Payload Flown On-Board STS-115

NASA Technical Reports Server (NTRS)

Wilson, J. W.; HonerzuBentrup, K,; Schurr, M. J.; Buchanan, K.; Morici, L.; Hammond, T.; Allen, P.; Baker, C.; Ott, C. M.; Nelman-Gonzalez M.;

Microbial community assembly patterns under incipient conditions in a basaltic soil system

NASA Astrophysics Data System (ADS)

Sengupta, A.; Stegen, J.; Alves Meira Neto, A.; Wang, Y.; Chorover, J.; Troch, P. A. A.; Maier, R. M.

2017-12-01

In sub-surface environments, the biotic components are critically linked to the abiotic processes. However, there is limited understanding of community establishment, functional associations, and community assembly processes of such microbes in sub-surface environments. This study presents the first analysis of microbial signatures in an incipient terrestrial basalt soil system conducted under controlled conditions. A sub-meter scale sampling of a soil mesocosm revealed the contrasting distribution patterns of simple soil parameters such as bulk density and electrical conductivity. Phylogenetic analysis of 16S rRNA gene indicated the presence of a total 40 bacterial and archaeal phyla, with high relative abundance of Actinobacteria on the surface and highest abundance of Proteobacteria throughout the system. Community diversity patterns were inferred to be dependent on depth profile and average water content in the system. Predicted functional gene analysis suggested mixotrophy lifestyles with both autotrophic and heterotrophic metabolisms, likelihood of a unique salt tolerant methanogenic pathway with links to novel Euryarchea, signatures of an incomplete nitrogen cycle, and predicted enzymes of extracellular iron (II) to iron (III) conversion followed by intracellular uptake, transport and regulation. Null modeling revealed microbial community assembly was predominantly governed by variable selection, but the influence of the variable selection did not show systematic spatial structure. The presence of significant heterogeneity in predicted functions and ecologically deterministic shifts in community composition in a homogeneous incipient basalt highlights the complexity exhibited by microorganisms even in the simplest of environmental systems. This presents an opportunity to further develop our understanding of how microbial communities establish, evolve, impact, and respond in sub-surface environments.

Microbial Heat Recovery Cell (MHRC) System Concept

DOE Office of Scientific and Technical Information (OSTI.GOV)

None

This factsheet describes a project that aimed to develop a microbial heat recovery cell (MHRC) system that combines a microbial reverse electrodialysis technology with waste heat recovery to convert industrial effluents into electricity and hydrogen.

Organic farming enhances soil microbial abundance and activity—A meta-analysis and meta-regression

PubMed Central

Symnaczik, Sarah; Mäder, Paul; De Deyn, Gerlinde; Gattinger, Andreas

2017-01-01

Population growth and climate change challenge our food and farming systems and provide arguments for an increased intensification of agriculture. A promising option is eco-functional intensification through organic farming, an approach based on using and enhancing internal natural resources and processes to secure and improve agricultural productivity, while minimizing negative environmental impacts. In this concept an active soil microbiota plays an important role for various soil based ecosystem services such as nutrient cycling, erosion control and pest and disease regulation. Several studies have reported a positive effect of organic farming on soil health and quality including microbial community traits. However, so far no systematic quantification of whether organic farming systems comprise larger and more active soil microbial communities compared to conventional farming systems was performed on a global scale. Therefore, we conducted a meta-analysis on current literature to quantify possible differences in key indicators for soil microbial abundance and activity in organic and conventional cropping systems. All together we integrated data from 56 mainly peer-reviewed papers into our analysis, including 149 pairwise comparisons originating from different climatic zones and experimental duration ranging from 3 to more than 100 years. Overall, we found that organic systems had 32% to 84% greater microbial biomass carbon, microbial biomass nitrogen, total phospholipid fatty-acids, and dehydrogenase, urease and protease activities than conventional systems. Exclusively the metabolic quotient as an indicator for stresses on microbial communities remained unaffected by the farming systems. Categorical subgroup analysis revealed that crop rotation, the inclusion of legumes in the crop rotation and organic inputs are important farming practices affecting soil microbial community size and activity. Furthermore, we show that differences in microbial size and activity between organic and conventional farming systems vary as a function of land use (arable, orchards, and grassland), plant life cycle (annual and perennial) and climatic zone. In summary, this study shows that overall organic farming enhances total microbial abundance and activity in agricultural soils on a global scale. PMID:28700609

A Workflow to Model Microbial Loadings in Watersheds (proceedings)

EPA Science Inventory

Many watershed models simulate overland and instream microbial fate and transport, but few actually provide loading rates on land surfaces and point sources to the water body network. This paper describes the underlying general equations for microbial loading rates associated wit...

The effect of D123 wheat as a companion crop on soil enzyme activities, microbial biomass and microbial communities in the rhizosphere of watermelon.

PubMed

Xu, Weihui; Wang, Zhigang; Wu, Fengzhi

2015-01-01

The growth of watermelon is often threatened by Fusarium oxysporum f. sp. niveum (Fon) in successively monocultured soil, which results in economic loss. The objective of this study was to investigate the effect of D123 wheat as a companion crop on soil enzyme activities, microbial biomass and microbial communities in the rhizosphere of watermelon and to explore the relationship between the effect and the incidence of wilt caused by Fon. The results showed that the activities of soil polyphenol oxidase, urease and invertase were increased, the microbial biomass nitrogen (MBN) and microbial biomass phosphorus (MBP) were significantly increased, and the ratio of MBC/MBN was decreased (P < 0.05). Real-time PCR analysis showed that the Fon population declined significantly in the watermelon/wheat companion system compared with the monoculture system (P < 0.05). The analysis of microbial communities showed that the relative abundance of microbial communities was changed in the rhizosphere of watermelon. Compared with the monoculture system, the relative abundances of Alphaproteobacteria, Actinobacteria, Gemmatimonadetes and Sordariomycetes were increased, and the relative abundances of Gammaproteobacteria, Sphingobacteria, Cytophagia, Pezizomycetes, and Eurotiomycetes were decreased in the rhizosphere of watermelon in the watermelon/wheat companion system; importantly, the incidence of Fusarium wilt was also decreased in the watermelon/wheat companion system. In conclusion, this study indicated that D123 wheat as a companion crop increased soil enzyme activities and microbial biomass, decreased the Fon population, and changed the relative abundance of microbial communities in the rhizosphere of watermelon, which may be related to the reduction of Fusarium wilt in the watermelon/wheat companion system.

Microbial Life in Soil - Linking Biophysical Models with Observations

NASA Astrophysics Data System (ADS)

Or, Dani; Tecon, Robin; Ebrahimi, Ali; Kleyer, Hannah; Ilie, Olga; Wang, Gang

2015-04-01

Microbial life in soil occurs within fragmented aquatic habitats formed in complex pore spaces where motility is restricted to short hydration windows (e.g., following rainfall). The limited range of self-dispersion and physical confinement promote spatial association among trophically interdepended microbial species. Competition and preferences for different nutrient resources and byproducts and their diffusion require high level of spatial organization to sustain the functioning of multispecies communities. We report mechanistic modeling studies of competing multispecies microbial communities grown on hydrated surfaces and within artificial soil aggregates (represented by 3-D pore network). Results show how trophic dependencies and cell-level interactions within patchy diffusion fields promote spatial self-organization of motile microbial cells. The spontaneously forming patterns of segregated, yet coexisting species were robust to spatial heterogeneities and to temporal perturbations (hydration dynamics), and respond primarily to the type of trophic dependencies. Such spatially self-organized consortia may reflect ecological templates that optimize substrate utilization and could form the basic architecture for more permanent surface-attached microbial colonies. Hydration dynamics affect structure and spatial arrangement of aerobic and anaerobic microbial communities and their biogeochemical functions. Experiments with well-characterized artificial soil microbial assemblies grown on porous surfaces provide access to community dynamics during wetting and drying cycles detected through genetic fingerprinting. Experiments for visual observations of spatial associations of tagged bacterial species with known trophic dependencies on model porous surfaces are underway. Biophysical modeling provide a means for predicting hydration-mediated critical separation distances for activation of spatial self-organization. The study provides new modeling and observational tools that enable new mechanistic insights into how differences in substrate affinities among microbial species and soil micro-hydrological conditions may give rise to a remarkable spatial and functional order in an extremely heterogeneous soil microbial world

Microbial Life in Soil - Linking Biophysical Models with Observations

NASA Astrophysics Data System (ADS)

Or, D.; Tecon, R.; Ebrahimi, A.; Kleyer, H.; Ilie, O.; Wang, G.

2014-12-01

Microbial life in soil occurs within fragmented aquatic habitats in complex pore spaces where motility is restricted to short hydration windows (e.g., following rainfall). The limited range of self-dispersion and physical confinement promote spatial association among trophically interdepended microbial species. Competition and preferences for different nutrient resources and byproducts and their diffusion require high level of spatial organization to sustain the functioning of multispecies communities. We report mechanistic modeling studies of competing multispecies microbial communities grown on hydrated surfaces and within artificial soil aggregates (represented by 3-D pore network). Results show how trophic dependencies and cell-level interactions within patchy diffusion fields promote spatial self-organization of motile microbial cells. The spontaneously forming patterns of segregated, yet coexisting species were robust to spatial heterogeneities and to temporal perturbations (hydration dynamics), and respond primarily to the type of trophic dependencies. Such spatially self-organized consortia may reflect ecological templates that optimize substrate utilization and could form the basic architecture for more permanent surface-attached microbial colonies. Hydration dynamics affect structure and spatial arrangement of aerobic and anaerobic microbial communities and their biogeochemical functions. Experiments with well-characterized artificial soil microbial assemblies grown on porous surfaces provide access to community dynamics during wetting and drying cycles detected through genetic fingerprinting. Experiments for visual observations of spatial associations of tagged bacterial species with known trophic dependencies on model porous surfaces are underway. Biophysical modeling provide a means for predicting hydration-mediated critical separation distances for activation of spatial self-organization. The study provides new modeling and observational tools that enable new mechanistic insights into how differences in substrate affinities among microbial species and soil micro-hydrological conditions may give rise to a remarkable spatial and functional order in an extremely heterogeneous soil microbial world.

Calibration and analysis of genome-based models for microbial ecology.

PubMed

Louca, Stilianos; Doebeli, Michael

2015-10-16

Microbial ecosystem modeling is complicated by the large number of unknown parameters and the lack of appropriate calibration tools. Here we present a novel computational framework for modeling microbial ecosystems, which combines genome-based model construction with statistical analysis and calibration to experimental data. Using this framework, we examined the dynamics of a community of Escherichia coli strains that emerged in laboratory evolution experiments, during which an ancestral strain diversified into two coexisting ecotypes. We constructed a microbial community model comprising the ancestral and the evolved strains, which we calibrated using separate monoculture experiments. Simulations reproduced the successional dynamics in the evolution experiments, and pathway activation patterns observed in microarray transcript profiles. Our approach yielded detailed insights into the metabolic processes that drove bacterial diversification, involving acetate cross-feeding and competition for organic carbon and oxygen. Our framework provides a missing link towards a data-driven mechanistic microbial ecology.

Development and evaluation of the microbial fate and transport module for the Agricultural Policy/Environmental eXtender (APEX) model

NASA Astrophysics Data System (ADS)

Hong, Eun-Mi; Park, Yongeun; Muirhead, Richard; Pachepsky, Yakov

2017-04-01

Pathogenic microorganisms in recreational and irrigation waters remain the subject of concern. Water quality models are used to estimate microbial quality of water sources, to evaluate microbial contamination-related risks, to guide the microbial water quality monitoring, and to evaluate the effect of agricultural management on the microbial water quality. The Agricultural Policy/Environmental eXtender (APEX) is the watershed-scale water quality model that includes highly detailed representation of agricultural management. The APEX currently does not have microbial fate and transport simulation capabilities. The objective of this work was to develop the first APEX microbial fate and transport module that could use the APEX conceptual model of manure removal together with recently introduced conceptualizations of the in-stream microbial fate and transport. The module utilizes manure erosion rates found in the APEX. The total number of removed bacteria was set to the concentrations of bacteria in soil-manure mixing layer and eroded manure amount. Bacteria survival in soil-manure mixing layer was simulated with the two-stage survival model. Individual survival patterns were simulated for each manure application date. Simulated in-stream microbial fate and transport processes included the reach-scale passive release of bacteria with resuspended bottom sediment during high flow events, the transport of bacteria from bottom sediment due to the hyporheic exchange during low flow periods, the deposition with settling sediment, and the two-stage survival. Default parameter values were available from recently published databases. The APEX model with the newly developed microbial fate and transport module was applied to simulate seven years of monitoring data for the Toenepi watershed in New Zealand. The stream network of the watershed ran through grazing lands with the daily bovine waste deposition. Based on calibration and testing results, the APEX with the microbe module reproduced well the monitored pattern of E. coli concentrations at the watershed outlet. The APEX with the microbial fate and transport module will be utilized for predicting microbial quality of water under various agricultural practices (grazing, cropping, and manure application), evaluating monitoring protocols, and supporting the selection of management practices based on regulations that rely on fecal indicator bacteria concentrations. Future development should include modeling contributions of wildlife, manure weathering, and weather effects on manure-borne microorganism survival and release.

Interplay Between Innate Immunity and the Plant Microbiota.

PubMed

Hacquard, Stéphane; Spaepen, Stijn; Garrido-Oter, Ruben; Schulze-Lefert, Paul

2017-08-04

The innate immune system of plants recognizes microbial pathogens and terminates their growth. However, recent findings suggest that at least one layer of this system is also engaged in cooperative plant-microbe interactions and influences host colonization by beneficial microbial communities. This immune layer involves sensing of microbe-associated molecular patterns (MAMPs) by pattern recognition receptors (PRRs) that initiate quantitative immune responses to control host-microbial load, whereas diversification of MAMPs and PRRs emerges as a mechanism that locally sculpts microbial assemblages in plant populations. This suggests a more complex microbial management role of the innate immune system for controlled accommodation of beneficial microbes and in pathogen elimination. The finding that similar molecular strategies are deployed by symbionts and pathogens to dampen immune responses is consistent with this hypothesis but implies different selective pressures on the immune system due to contrasting outcomes on plant fitness. The reciprocal interplay between microbiota and the immune system likely plays a critical role in shaping beneficial plant-microbiota combinations and maintaining microbial homeostasis.

Accumulation of metals by microorganisms — processes and importance for soil systems

NASA Astrophysics Data System (ADS)

Ledin, Maria

2000-08-01

Metal accumulation by solid substances can counteract metal mobilization in the environment if the solid substance is immobile. Microorganisms have a high surface area-to-volume ratio because of their small size and therefore provide a large contact area that can interact with metals in the surrounding environment. Microbial metal accumulation has received much attention in the last years due to the potential use of microorganisms for cleaning metal-polluted water. However, considerably less attention has been paid to the role of microorganisms for metal mobility in soil even though the same processes may occur there. Therefore, this paper highlights this area. The different accumulation processes that microorganisms perform are analyzed and their potential significance in soil systems is discussed. Different kinds of mechanisms can be involved in the accumulation of metals by microorganisms, e.g. adsorption, precipitation, complexation and active transport into the cell. Physicochemical parameters like pH and ionic composition, as well as biological factors are of importance for the magnitude of accumulation. Often large amounts of metals can be accumulated with varying specificity, and microorganisms may provide nucleation sites for mineral formation. Several studies of microbial metal accumulation have been made with different methods and aims. Most of these studies concern single-component systems with one organism at a time. Data from accumulation experiments with pure cultures of microorganisms have been used to model the overall metal retention in soil. A further development is experimental model systems using various solid soil components in salt medium. Microbial metal accumulation is difficult to study in situ, but some experimental methods have been applied as tools for studying real soil systems, e.g. litter bags buried in soil containing microorganisms, a method where discs with microorganisms have been put onto agar plates with soil extracts, and comparison of sterilized and non-sterilized soils or soils with or without nutrient amendment. Different aspects of microbial metal accumulation are emphasized with the different methods applied. Single-component systems have the advantage of providing excellent information of the metal binding properties of microorganisms but cannot directly be applied to metal behavior in the heterogenous systems that real soils constitute. Studies focused on the behavior of metals in real soils can, in contrast, provide information on the overall metal distribution but less insight into the processes involved. Obviously, a combination of approaches is needed to describe metal distribution and mobility in polluted soil such as areas around mines. Different kinds of multi-component systems as well as modelling may bridge the gap between these two types of studies. Several experimental methods, complementary to each other and designed to allow for comparison, may emphasize different aspects of metal accumulation and should therefore be considered. To summarize, there are studies that indicate that microorganisms may also accumulate metals in soil and that the amounts may be considerable. However, much work remains to be done, with the focus of microorganisms in soil. It is also important to put microbial metal accumulation in relation to other microbial processes in soil, which can influence metal mobility, to determine the overall influence of soil microorganisms on metal mobility, and to be able to quantify these processes.

Kinetics of microbial degradation of deicing chemicals in percolated porous media - the modeling perspective

NASA Astrophysics Data System (ADS)

Wehrer, Markus; Lissner, Heidi; Totsche, Kai

2013-04-01

A quantitative knowledge of the fate of deicing chemicals in the subsurface can be provided by analysis of laboratory and field experiments with numerical simulation models. In the present study, experimental data of microbial degradation of the deicing chemical propylene glycol (PG) under flow conditions in soil columns and field lysimeters were simulated to analyze the process conditions of degradation and to obtain the according parameters. Results from the column experiment were evaluated applying different scenarios of an advection-dispersion model using HYDRUS-1D. To reconstruct the data, different competing degradation models were included, i.e., zero order, first order and inclusion of a growing and decaying biomass. The general breakthrough behavior of propylene glycol in soil columns can be simulated well using a coupled model of solute transport and degradation with growth and decay of biomass. The susceptibility of the model to non-unique solutions was investigated using systematical forward and inverse simulations. We found that the model tends to equifinal solutions under certain conditions. Complex experimental boundary conditions can help to avoid this. Under field conditions, the situation is far more complex than in the laboratory. Studying the fate of PG with undisturbed lysimeters we found that aerobic and anaerobic degradation occurs simultaneously. We attribute this to the physical structure and the aggregated nature of the undisturbed soil material . This results in the presence of spatially disjoint oxidative and reductive regions of microbial activity and requires, but is not fully reflected by a dual porosity model. Currently, the numerical simulation of this system is in progress, considering several flow and transport models. A stochastic global search algorithm (DREAM-ZS) is used in conjuction with HYDRUS-1D to avoid local minima in the inverse simulations. The study shows the current limitations and potentials of modeling degradation in an aggregated and structured system under flow conditions.

Genomes of diverse isolates of the marine cyanobacterium Prochlorococcus

PubMed Central

Biller, Steven J.; Berube, Paul M.; Berta-Thompson, Jessie W.; Kelly, Libusha; Roggensack, Sara E.; Awad, Lana; Roache-Johnson, Kathryn H.; Ding, Huiming; Giovannoni, Stephen J.; Rocap, Gabrielle; Moore, Lisa R.; Chisholm, Sallie W.

2014-01-01

The marine cyanobacterium Prochlorococcus is the numerically dominant photosynthetic organism in the oligotrophic oceans, and a model system in marine microbial ecology. Here we report 27 new whole genome sequences (2 complete and closed; 25 of draft quality) of cultured isolates, representing five major phylogenetic clades of Prochlorococcus. The sequenced strains were isolated from diverse regions of the oceans, facilitating studies of the drivers of microbial diversity—both in the lab and in the field. To improve the utility of these genomes for comparative genomics, we also define pre-computed clusters of orthologous groups of proteins (COGs), indicating how genes are distributed among these and other publicly available Prochlorococcus genomes. These data represent a significant expansion of Prochlorococcus reference genomes that are useful for numerous applications in microbial ecology, evolution and oceanography. PMID:25977791

Habitat Fragmentation can Modulate Drought Effects on the Plant-soil-microbial System in Mediterranean Holm Oak (Quercus ilex) Forests.

PubMed

Flores-Rentería, Dulce; Curiel Yuste, Jorge; Rincón, Ana; Brearley, Francis Q; García-Gil, Juan Carlos; Valladares, Fernando

2015-05-01

Ecological transformations derived from habitat fragmentation have led to increased threats to above-ground biodiversity. However, the impacts of forest fragmentation on soils and their microbial communities are not well understood. We examined the effects of contrasting fragment sizes on the structure and functioning of soil microbial communities from holm oak forest patches in two bioclimatically different regions of Spain. We used a microcosm approach to simulate the annual summer drought cycle and first autumn rainfall (rewetting), evaluating the functional response of a plant-soil-microbial system. Forest fragment size had a significant effect on physicochemical characteristics and microbial functioning of soils, although the diversity and structure of microbial communities were not affected. The response of our plant-soil-microbial systems to drought was strongly modulated by the bioclimatic conditions and the fragment size from where the soils were obtained. Decreasing fragment size modulated the effects of drought by improving local environmental conditions with higher water and nutrient availability. However, this modulation was stronger for plant-soil-microbial systems built with soils from the northern region (colder and wetter) than for those built with soils from the southern region (warmer and drier) suggesting that the responsiveness of the soil-plant-microbial system to habitat fragmentation was strongly dependent on both the physicochemical characteristics of soils and the historical adaptation of soil microbial communities to specific bioclimatic conditions. This interaction challenges our understanding of future global change scenarios in Mediterranean ecosystems involving drier conditions and increased frequency of forest fragmentation.

Quantitative Microbial Risk Assessment Tutorial: Installation of Software for Watershed Modeling in Support of QMRA

EPA Science Inventory

This tutorial provides instructions for accessing, retrieving, and downloading the following software to install on a host computer in support of Quantitative Microbial Risk Assessment (QMRA) modeling:• SDMProjectBuilder (which includes the Microbial Source Module as part...

Soil Microbiome Is More Heterogeneous in Organic Than in Conventional Farming System

PubMed Central

Lupatini, Manoeli; Korthals, Gerard W.; de Hollander, Mattias; Janssens, Thierry K. S.; Kuramae, Eiko E.

2017-01-01

Organic farming system and sustainable management of soil pathogens aim at reducing the use of agricultural chemicals in order to improve ecosystem health. Despite the essential role of microbial communities in agro-ecosystems, we still have limited understanding of the complex response of microbial diversity and composition to organic and conventional farming systems and to alternative methods for controlling plant pathogens. In this study we assessed the microbial community structure, diversity and richness using 16S rRNA gene next generation sequences and report that conventional and organic farming systems had major influence on soil microbial diversity and community composition while the effects of the soil health treatments (sustainable alternatives for chemical control) in both farming systems were of smaller magnitude. Organically managed system increased taxonomic and phylogenetic richness, diversity and heterogeneity of the soil microbiota when compared with conventional farming system. The composition of microbial communities, but not the diversity nor heterogeneity, were altered by soil health treatments. Soil health treatments exhibited an overrepresentation of specific microbial taxa which are known to be involved in soil suppressiveness to pathogens (plant-parasitic nematodes and soil-borne fungi). Our results provide a comprehensive survey on the response of microbial communities to different agricultural systems and to soil treatments for controlling plant pathogens and give novel insights to improve the sustainability of agro-ecosystems by means of beneficial microorganisms. PMID:28101080

Is the whole the sum of its parts? Agent-based modelling of wastewater treatment systems.

PubMed

Schuler, A J; Majed, N; Bucci, V; Hellweger, F L; Tu, Y; Gu, A Z

2011-01-01

Agent-based models (ABMS) simulate individual units within a system, such as the bacteria in a biological wastewater treatment system. This paper outlines past, current and potential future applications of ABMs to wastewater treatment. ABMs track heterogeneities within microbial populations, and this has been demonstrated to yield different predictions of bulk behaviors than the conventional, "lumped" approaches for enhanced biological phosphorus removal (EBPR) completely mixed reactors systems. Current work included the application of the ABM approach to bacterial adaptation/evolution, using the model system of individual EBPR bacteria that are allowed to evolve a kinetic parameter (maximum glycogen storage) in a competitive environment. The ABM approach was successfully implemented to a simple anaerobic-aerobic system and it was found the differing initial states converged to the same optimal solution under uncertain hydraulic residence times associated with completely mixed hydraulics. In another study, an ABM was developed and applied to simulate the heterogeneity in intracellular polymer storage compounds, including polyphosphate (PP), in functional microbial populations in enhanced biological phosphorus removal (EBPR) process. The simulation results were compared to the experimental measurements of single-cell abundance of PP in polyphosphate accumulating organisms (PAOs), performed using Raman microscopy. The model-predicted heterogeneity was generally consistent with observations, and it was used to investigate the relative contribution of external (different life histories) and internal (biological) mechanisms leading to heterogeneity. In the future, ABMs could be combined with computational fluid dynamics (CFD) models to understand incomplete mixing, more intracellular states and mechanisms can be incorporated, and additional experimental verification is needed.

Microbial Energy Conversion

DOE Office of Scientific and Technical Information (OSTI.GOV)

Buckley, Merry; Wall, Judy D.

2006-10-01

The American Academy of Microbiology convened a colloquium March 10-12, 2006, in San Francisco, California, to discuss the production of energy fuels by microbial conversions. The status of research into various microbial energy technologies, the advantages and disadvantages of each of these approaches, research needs in the field, and education and training issues were examined, with the goal of identifying routes for producing biofuels that would both decrease the need for fossil fuels and reduce greenhouse gas emissions. Currently, the choices for providing energy are limited. Policy makers and the research community must begin to pursue a broader array ofmore » potential energy technologies. A diverse energy portfolio that includes an assortment of microbial energy choices will allow communities and consumers to select the best energy solution for their own particular needs. Funding agencies and governments alike need to prepare for future energy needs by investing both in the microbial energy technologies that work today and in the untested technologies that will serve the world’s needs tomorrow. More mature bioprocesses, such as ethanol production from starchy materials and methane from waste digestors, will find applications in the short term. However, innovative techniques for liquid fuel or biohydrogen production are among the longer term possibilities that should also be vigorously explored, starting now. Microorganisms can help meet human energy needs in any of a number of ways. In their most obvious role in energy conversion, microorganisms can generate fuels, including ethanol, hydrogen, methane, lipids, and butanol, which can be burned to produce energy. Alternatively, bacteria can be put to use in microbial fuel cells, where they carry out the direct conversion of biomass into electricity. Microorganisms may also be used some day to make oil and natural gas technologies more efficient by sequestering carbon or by assisting in the recovery of oil and natural gas from the subsurface. The participants discussed--key microbial conversion paths; overarching research issues; current funding models and microbial energy research; education, training, interdisciplinary cooperation and communication. Their recommendations are--Cellulose and lignocellulose are the preferred substrates for producing liquid transportation fuels, of which ethanol is the most commonly considered example. Generating fuels from these materials is still difficult and costly. A number of challenges need to be met in order to make the conversion of cellulose and lignocellulose to transportation fuels more cost-competitive. The design of hydrogen-producing bioreactors must be improved in order to more effectively manage hydrogen removal, oxygen exclusion, and, in the case of photobioreactors, to capture light energy more efficiently. Methane production may be optimized by fine-tuning methanogenic microbial communities. The ability to transfer electrons to an anode in a microbial fuel cell is probably very broadly distributed in the bacterial world. The scientific community needs a larger inventory of cultivated microorganisms from which to draw for energy conversion development. New and unusual organisms for manufacturing fuels and for use in fuel cells can be discovered using bioprospecting techniques. Particular emphasis should be placed on finding microbes, microbial communities, and enzymes that can enhance the conversion of lignocellulosic biomass to usable sugars. Many of the microbial processes critical to energy conversion are carried out by complex communities of organisms, and there is a need to better understand the community interactions that make these transformations possible. Better understanding of microbial community structure, robustness, networks, homeostasis, and cell-to-cell signaling is also needed. A better understanding of the basic enzymology of microorganisms is needed in order to move forward more quickly with microbial energy production. Research should focus on the actions of enzymes and enzyme complexes within the context of the whole cell, how they’re regulated, where they’re placed, and what they interact with. Better modeling tools are needed to facilitate progress in microbial energy transformations. Models of metabolic dynamics, including levels of reductants and regulation of electron flow need to be improved. Global techno-economic models of microbial energy conversion systems, which seek to simultaneously describe the resource flows into and out of a system as well as its economics, are needed and should be made publicly available on the internet. Finally, more emphasis needs to be placed on multidisciplinary education and training and on cooperation between disciplines in order to make the most of microbial energy conversion technologies and to meet the research needs of the future.« less

Bacterial Quorum Sensing and Microbial Community Interactions

PubMed Central

2018-01-01

ABSTRACT Many bacteria use a cell-cell communication system called quorum sensing to coordinate population density-dependent changes in behavior. Quorum sensing involves production of and response to diffusible or secreted signals, which can vary substantially across different types of bacteria. In many species, quorum sensing modulates virulence functions and is important for pathogenesis. Over the past half-century, there has been a significant accumulation of knowledge of the molecular mechanisms, signal structures, gene regulons, and behavioral responses associated with quorum-sensing systems in diverse bacteria. More recent studies have focused on understanding quorum sensing in the context of bacterial sociality. Studies of the role of quorum sensing in cooperative and competitive microbial interactions have revealed how quorum sensing coordinates interactions both within a species and between species. Such studies of quorum sensing as a social behavior have relied on the development of “synthetic ecological” models that use nonclonal bacterial populations. In this review, we discuss some of these models and recent advances in understanding how microbes might interact with one another using quorum sensing. The knowledge gained from these lines of investigation has the potential to guide studies of microbial sociality in natural settings and the design of new medicines and therapies to treat bacterial infections. PMID:29789364

A mechanistic Individual-based Model of microbial communities.

PubMed

Jayathilake, Pahala Gedara; Gupta, Prashant; Li, Bowen; Madsen, Curtis; Oyebamiji, Oluwole; González-Cabaleiro, Rebeca; Rushton, Steve; Bridgens, Ben; Swailes, David; Allen, Ben; McGough, A Stephen; Zuliani, Paolo; Ofiteru, Irina Dana; Wilkinson, Darren; Chen, Jinju; Curtis, Tom

2017-01-01

Accurate predictive modelling of the growth of microbial communities requires the credible representation of the interactions of biological, chemical and mechanical processes. However, although biological and chemical processes are represented in a number of Individual-based Models (IbMs) the interaction of growth and mechanics is limited. Conversely, there are mechanically sophisticated IbMs with only elementary biology and chemistry. This study focuses on addressing these limitations by developing a flexible IbM that can robustly combine the biological, chemical and physical processes that dictate the emergent properties of a wide range of bacterial communities. This IbM is developed by creating a microbiological adaptation of the open source Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS). This innovation should provide the basis for "bottom up" prediction of the emergent behaviour of entire microbial systems. In the model presented here, bacterial growth, division, decay, mechanical contact among bacterial cells, and adhesion between the bacteria and extracellular polymeric substances are incorporated. In addition, fluid-bacteria interaction is implemented to simulate biofilm deformation and erosion. The model predicts that the surface morphology of biofilms becomes smoother with increased nutrient concentration, which agrees well with previous literature. In addition, the results show that increased shear rate results in smoother and more compact biofilms. The model can also predict shear rate dependent biofilm deformation, erosion, streamer formation and breakup.

A mechanistic Individual-based Model of microbial communities

PubMed Central

Gupta, Prashant; Li, Bowen; Madsen, Curtis; Oyebamiji, Oluwole; González-Cabaleiro, Rebeca; Rushton, Steve; Bridgens, Ben; Swailes, David; Allen, Ben; McGough, A. Stephen; Zuliani, Paolo; Ofiteru, Irina Dana; Wilkinson, Darren; Chen, Jinju; Curtis, Tom

2017-01-01

Accurate predictive modelling of the growth of microbial communities requires the credible representation of the interactions of biological, chemical and mechanical processes. However, although biological and chemical processes are represented in a number of Individual-based Models (IbMs) the interaction of growth and mechanics is limited. Conversely, there are mechanically sophisticated IbMs with only elementary biology and chemistry. This study focuses on addressing these limitations by developing a flexible IbM that can robustly combine the biological, chemical and physical processes that dictate the emergent properties of a wide range of bacterial communities. This IbM is developed by creating a microbiological adaptation of the open source Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS). This innovation should provide the basis for “bottom up” prediction of the emergent behaviour of entire microbial systems. In the model presented here, bacterial growth, division, decay, mechanical contact among bacterial cells, and adhesion between the bacteria and extracellular polymeric substances are incorporated. In addition, fluid-bacteria interaction is implemented to simulate biofilm deformation and erosion. The model predicts that the surface morphology of biofilms becomes smoother with increased nutrient concentration, which agrees well with previous literature. In addition, the results show that increased shear rate results in smoother and more compact biofilms. The model can also predict shear rate dependent biofilm deformation, erosion, streamer formation and breakup. PMID:28771505

Location of Microbial Ecology Evaluation Device in Apollo Command Module

NASA Technical Reports Server (NTRS)

1971-01-01

The location of the Microbial Ecology Evaluation Device (MEED) installed on the open hatch of the Apollo Command Module is illustrated in this photograph. The MEED, equipment of the Microbial Response in Space Environment experiment, will house a selection of microbial systems. The MEED will be deployed during the extravehicular activity on the transearth coast phase of the Aopllo 16 lunar landing mission. The purpose of the experiment will be to measure the effects of certain space environmental parameters on the microbial test systems.

Priming effect and microbial diversity in ecosystem functioning and response to global change: a modeling approach using the SYMPHONY model.

PubMed

Perveen, Nazia; Barot, Sébastien; Alvarez, Gaël; Klumpp, Katja; Martin, Raphael; Rapaport, Alain; Herfurth, Damien; Louault, Frédérique; Fontaine, Sébastien

2014-04-01

Integration of the priming effect (PE) in ecosystem models is crucial to better predict the consequences of global change on ecosystem carbon (C) dynamics and its feedbacks on climate. Over the last decade, many attempts have been made to model PE in soil. However, PE has not yet been incorporated into any ecosystem models. Here, we build plant/soil models to explore how PE and microbial diversity influence soil/plant interactions and ecosystem C and nitrogen (N) dynamics in response to global change (elevated CO2 and atmospheric N depositions). Our results show that plant persistence, soil organic matter (SOM) accumulation, and low N leaching in undisturbed ecosystems relies on a fine adjustment of microbial N mineralization to plant N uptake. This adjustment can be modeled in the SYMPHONY model by considering the destruction of SOM through PE, and the interactions between two microbial functional groups: SOM decomposers and SOM builders. After estimation of parameters, SYMPHONY provided realistic predictions on forage production, soil C storage and N leaching for a permanent grassland. Consistent with recent observations, SYMPHONY predicted a CO2 -induced modification of soil microbial communities leading to an intensification of SOM mineralization and a decrease in the soil C stock. SYMPHONY also indicated that atmospheric N deposition may promote SOM accumulation via changes in the structure and metabolic activities of microbial communities. Collectively, these results suggest that the PE and functional role of microbial diversity may be incorporated in ecosystem models with a few additional parameters, improving accuracy of predictions. © 2013 John Wiley & Sons Ltd.

Scaling Soil Microbe-Water Interactions from Pores to Ecosystems

NASA Astrophysics Data System (ADS)

Manzoni, S.; Katul, G. G.

2014-12-01

The spatial scales relevant to soil microbial activity are much finer than scales relevant to whole-ecosystem function and biogeochemical cycling. On the one hand, how to link such different scales and develop scale-aware biogeochemical and ecohydrological models remains a major challenge. On the other hand, resolving these linkages is becoming necessary for testing ecological hypotheses and resolving data-theory inconsistencies. Here, the relation between microbial respiration and soil moisture expressed in water potential is explored. Such relation mediates the water availability effects on ecosystem-level heterotrophic respiration and is of paramount importance for understanding CO2 emissions under increasingly variable rainfall regimes. Respiration has been shown to decline as the soil dries in a remarkably consistent way across climates and soil types (open triangles in Figure). Empirical models based on these respiration-moisture relations are routinely used in Earth System Models to predict moisture effects on ecosystem respiration. It has been hypothesized that this consistency in microbial respiration decline is due to breakage of water film continuity causing in turn solute diffusion limitations in dry conditions. However, this hypothesis appears to be at odds with what is known about soil hydraulic properties. Water film continuity estimated from soil water retention (SWR) measurements at the 'Darcy' scale breaks at far less negative water potential (<-0.1 MPa) levels than where microbial respiration ceases (approximately -15 MPa) as shown in the Figure (violet frequency distribution). Also, this threshold point inferred from SWR shows strong texture dependence, in contrast to the respiration curves. Employing theoretical tools from percolation theory, it is demonstrated that hydrological measurements can be spatially downscaled at a micro-level relevant to microbial activity. Such downscaling resolves the inconsistency between respiration thresholds and hydrological thresholds. This result, together with observations of residual microbial activity well below -15 MPa (dashed back curve in Figure), lends support to the hypothesis that soil microbes are substrate-limited in dry conditions.

Seamount Hydrothermal Systems as Analogies for Ocean Worlds: Reaction Paths Throughout the Lo'ihi Seamount (Hawaii Archipelago)

NASA Astrophysics Data System (ADS)

Milesi, V.; Shock, E.

2018-05-01

Thermodynamic modeling is performed to investigate the possible reaction paths of sea water throughout the Lo'ihi seamount and the associated geochemical supplies of energy that can support autotrophic microbial communities.

KINETIC MODEL OF BIOSURFACTANT ENHANCED HEXADECANE BIODEGRADATION BY PSEUDOMONAS AERUGINOSA. (R827132)

EPA Science Inventory

Many sites of environmental concern contain groundwater contaminated with nonaqueous phase liquids (NAPL). In such sites interfacial processes may affect both the equilibrium and kinetic behavior of the system. In particular, insoluble hydrocarbon partitioning and microbial biode...

Real-time monitoring of a microbial electrolysis cell using an electrical equivalent circuit model.

PubMed

Hussain, S A; Perrier, M; Tartakovsky, B

2018-04-01

Efforts in developing microbial electrolysis cells (MECs) resulted in several novel approaches for wastewater treatment and bioelectrosynthesis. Practical implementation of these approaches necessitates the development of an adequate system for real-time (on-line) monitoring and diagnostics of MEC performance. This study describes a simple MEC equivalent electrical circuit (EEC) model and a parameter estimation procedure, which enable such real-time monitoring. The proposed approach involves MEC voltage and current measurements during its operation with periodic power supply connection/disconnection (on/off operation) followed by parameter estimation using either numerical or analytical solution of the model. The proposed monitoring approach is demonstrated using a membraneless MEC with flow-through porous electrodes. Laboratory tests showed that changes in the influent carbon source concentration and composition significantly affect MEC total internal resistance and capacitance estimated by the model. Fast response of these EEC model parameters to changes in operating conditions enables the development of a model-based approach for real-time monitoring and fault detection.

DEVELOPMENT OF AN IMPROVED SIMULATOR FOR CHEMICAL AND MICROBIAL IOR METHODS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gary A. Pope; Kamy Sepehrnoori; Mojdeh Delshad

2001-10-01

This is the final report of a three-year research project on further development of a chemical and microbial improved oil recovery reservoir simulator. The objective of this research was to extend the capability of an existing simulator (UTCHEM) to improved oil recovery methods which use surfactants, polymers, gels, alkaline chemicals, microorganisms and foam as well as various combinations of these in both conventional and naturally fractured oil reservoirs. The first task was the addition of a dual-porosity model for chemical IOR in naturally fractured oil reservoirs. They formulated and implemented a multiphase, multicomponent dual porosity model for enhanced oil recoverymore » from naturally fractured reservoirs. The multiphase dual porosity model was tested against analytical solutions, coreflood data, and commercial simulators. The second task was the addition of a foam model. They implemented a semi-empirical surfactant/foam model in UTCHEM and validated the foam model by comparison with published laboratory data. The third task addressed several numerical and coding enhancements that will greatly improve its versatility and performance. Major enhancements were made in UTCHEM output files and memory management. A graphical user interface to set up the simulation input and to process the output data on a Windows PC was developed. New solvers for solving the pressure equation and geochemical system of equations were implemented and tested. A corner point grid geometry option for gridding complex reservoirs was implemented and tested. Enhancements of physical property models for both chemical and microbial IOR simulations were included in the final task of this proposal. Additional options for calculating the physical properties such as relative permeability and capillary pressure were added. A microbiological population model was developed and incorporated into UTCHEM. They have applied the model to microbial enhanced oil recovery (MEOR) processes by including the capability of permeability reduction due to biomass growth and retention. The formations of bio-products such as surfactant and polymer surfactant have also been incorporated.« less

Monte-Carlo Simulations of Drug Delivery on Biofilms

NASA Astrophysics Data System (ADS)

Buldum, Alper; Simpson, Andrew

2013-03-01

The focus of this work is on biofilms that grow in the lungs of cystic fibrosis (CF) patients. A discrete model which describes the nutrient and biomass as discrete particles is created. Diffusion of the nutrient, consumption of the nutrient by microbial particles, and growth and decay of microbial particles are simulated using stochastic processes. Our model extends the complexity of the biofilm system by including the conversion and reversion of living bacteria into a hibernated state, known as persister bacteria. Another new contribution is the inclusion of antimicrobial in two forms: an aqueous solution and encapsulated in biodegradable nanoparticles. The bacteria population growth and spatial variation of drugs and their effectiveness are investigated in this work. Supported by NIH

A multi-objective constraint-based approach for modeling genome-scale microbial ecosystems.

PubMed

Budinich, Marko; Bourdon, Jérémie; Larhlimi, Abdelhalim; Eveillard, Damien

2017-01-01

Interplay within microbial communities impacts ecosystems on several scales, and elucidation of the consequent effects is a difficult task in ecology. In particular, the integration of genome-scale data within quantitative models of microbial ecosystems remains elusive. This study advocates the use of constraint-based modeling to build predictive models from recent high-resolution -omics datasets. Following recent studies that have demonstrated the accuracy of constraint-based models (CBMs) for simulating single-strain metabolic networks, we sought to study microbial ecosystems as a combination of single-strain metabolic networks that exchange nutrients. This study presents two multi-objective extensions of CBMs for modeling communities: multi-objective flux balance analysis (MO-FBA) and multi-objective flux variability analysis (MO-FVA). Both methods were applied to a hot spring mat model ecosystem. As a result, multiple trade-offs between nutrients and growth rates, as well as thermodynamically favorable relative abundances at community level, were emphasized. We expect this approach to be used for integrating genomic information in microbial ecosystems. Following models will provide insights about behaviors (including diversity) that take place at the ecosystem scale.

Effects of Soil Organic Matter Properties and Microbial Community Composition on Enzyme Activities in Cryoturbated Arctic Soils

PubMed Central

Schnecker, Jörg; Wild, Birgit; Hofhansl, Florian; Eloy Alves, Ricardo J.; Bárta, Jiří; Čapek, Petr; Fuchslueger, Lucia; Gentsch, Norman; Gittel, Antje; Guggenberger, Georg; Hofer, Angelika; Kienzl, Sandra; Knoltsch, Anna; Lashchinskiy, Nikolay; Mikutta, Robert; Šantrůčková, Hana; Shibistova, Olga; Takriti, Mounir; Urich, Tim; Weltin, Georg; Richter, Andreas

2014-01-01

Enzyme-mediated decomposition of soil organic matter (SOM) is controlled, amongst other factors, by organic matter properties and by the microbial decomposer community present. Since microbial community composition and SOM properties are often interrelated and both change with soil depth, the drivers of enzymatic decomposition are hard to dissect. We investigated soils from three regions in the Siberian Arctic, where carbon rich topsoil material has been incorporated into the subsoil (cryoturbation). We took advantage of this subduction to test if SOM properties shape microbial community composition, and to identify controls of both on enzyme activities. We found that microbial community composition (estimated by phospholipid fatty acid analysis), was similar in cryoturbated material and in surrounding subsoil, although carbon and nitrogen contents were similar in cryoturbated material and topsoils. This suggests that the microbial community in cryoturbated material was not well adapted to SOM properties. We also measured three potential enzyme activities (cellobiohydrolase, leucine-amino-peptidase and phenoloxidase) and used structural equation models (SEMs) to identify direct and indirect drivers of the three enzyme activities. The models included microbial community composition, carbon and nitrogen contents, clay content, water content, and pH. Models for regular horizons, excluding cryoturbated material, showed that all enzyme activities were mainly controlled by carbon or nitrogen. Microbial community composition had no effect. In contrast, models for cryoturbated material showed that enzyme activities were also related to microbial community composition. The additional control of microbial community composition could have restrained enzyme activities and furthermore decomposition in general. The functional decoupling of SOM properties and microbial community composition might thus be one of the reasons for low decomposition rates and the persistence of 400 Gt carbon stored in cryoturbated material. PMID:24705618

An Advanced In Vitro Technology Platform to Study the Mechanism of Action of Prebiotics and Probiotics in the Gastrointestinal Tract.

PubMed

Marzorati, Massimo; Van de Wiele, Tom

The gastrointestinal tract (GIT) hosts the most complex microbial community in the human body. Given the extensive metabolic potential which is present in this community, this additional organ is of key importance to maintain a healthy status and several diseases are frequently correlated with an alteration of the composition/functionality of the gut microbiota. Consequently, there is a great interest in identifying potential approaches that could modulate the microbiota and its metabolism to bring about a positive health effect. A classical approach to reach this goal is the use of prebiotics and/or probiotics. How to study the potential effect of new prebiotics/probiotics and how to localize this effect along the full GIT? Human intervention trials are the golden standard to validate functional properties of food products. Yet, most studies on gut microbiota are based on the analysis of fecal samples because they are easily collected in a non-invasive manner. A complementary option is represented by well-designed in vitro simulation technologies. Among all the available systems, the Simulator of Human Intestinal Microbial Ecosystem has already been shown to be a useful model for nutrition studies in terms of analysis of the intestinal microbial community composition and activity. The Simulator of Human Intestinal Microbial Ecosystem is a scientifically validated platform representing the physiology and microbiology of the adult human GIT. Furthermore, recent advances in in vitro modelling also allow to combine the study of bacteria-host interactions, such as mucosal adhesion and interaction with the immune system, thereby further increasing the value of the scientific output.

Modelling microbial exchanges between forms of soil nitrogen in contrasting ecosystems

NASA Astrophysics Data System (ADS)

Pansu, M.; Machado, D.; Bottner, P.; Sarmiento, L.

2014-02-01

Although nitrogen (N) is often combined with carbon (C) in organic molecules, C passes from the air to the soil through plant photosynthesis, whereas N passes from the soil to plants through a chain of microbial conversions. However, dynamic models do not fully consider the microorganisms at the centre of exchange processes between organic and mineral forms of N. This study monitored the transfer of 14C and 15N between plant materials, microorganisms, humified compartments, and inorganic forms in six very different ecosystems along an altitudinal transect. The microbial conversions of the 15N forms appear to be strongly linked to the previously modelled C cycle, and the same equations and parameters can be used to model both C and N cycles. The only difference is in the modelling of the flows between microbial and inorganic forms. The processes of mineralization and immobilization of N appear to be regulated by a two-way microbial exchange depending on the C : N ratios of microorganisms and available substrates. The MOMOS (Modelling of Organic Matter of Soils) model has already been validated for the C cycle and also appears to be valid for the prediction of microbial transformations of N forms. This study shows that the hypothesis of microbial homeostasis can give robust predictions at global scale. However, the microbial populations did not appear to always be independent of the external constraints. At some altitudes their C : N ratio could be better modelled as decreasing during incubation and increasing with increasing C storage in cold conditions. The ratio of potentially mineralizable-15N/inorganic-15N and the 15N stock in the plant debris and the microorganisms was modelled as increasing with altitude, whereas the 15N storage in stable humus was modelled as decreasing with altitude. This predicts that there is a risk that mineralization of organic reserves in cold areas may increase global warming.

Integrated omics for the identification of key functionalities in biological wastewater treatment microbial communities.

PubMed

Narayanasamy, Shaman; Muller, Emilie E L; Sheik, Abdul R; Wilmes, Paul

2015-05-01

Biological wastewater treatment plants harbour diverse and complex microbial communities which prominently serve as models for microbial ecology and mixed culture biotechnological processes. Integrated omic analyses (combined metagenomics, metatranscriptomics, metaproteomics and metabolomics) are currently gaining momentum towards providing enhanced understanding of community structure, function and dynamics in situ as well as offering the potential to discover novel biological functionalities within the framework of Eco-Systems Biology. The integration of information from genome to metabolome allows the establishment of associations between genetic potential and final phenotype, a feature not realizable by only considering single 'omes'. Therefore, in our opinion, integrated omics will become the future standard for large-scale characterization of microbial consortia including those underpinning biological wastewater treatment processes. Systematically obtained time and space-resolved omic datasets will allow deconvolution of structure-function relationships by identifying key members and functions. Such knowledge will form the foundation for discovering novel genes on a much larger scale compared with previous efforts. In general, these insights will allow us to optimize microbial biotechnological processes either through better control of mixed culture processes or by use of more efficient enzymes in bioengineering applications. © 2015 The Authors. Microbial Biotechnology published by John Wiley & Sons Ltd and Society for Applied Microbiology.

Biogenic nanopalladium production by self-immobilized granular biomass: application for contaminant remediation.

PubMed

Suja, E; Nancharaiah, Y V; Venugopalan, V P

2014-11-15

Microbial granules cultivated in an aerobic bubble column sequencing batch reactor were used for reduction of Pd(II) and formation of biomass associated Pd(0) nanoparticles (Bio-Pd) for reductive transformation of organic and inorganic contaminants. Addition of Pd(II) to microbial granules incubated under fermentative conditions resulted in rapid formation of Bio-Pd. The reduction of soluble Pd(II) to biomass associated Pd(0) was predominantly mediated by H2 produced through fermentation. X-ray diffraction and scanning electron microscope analysis revealed that the produced Pd nanoparticles were associated with the microbial granules. The catalytic activity of Bio-Pd was determined using p-nitrophenol and Cr(VI) as model compounds. Reductive transformation of p-nitrophenol by Bio-Pd was ∼20 times higher in comparison to microbial granules without Pd. Complete reduction of up to 0.25 mM of Cr(VI) by Bio-Pd was achieved in 24 h. Bio-Pd synthesis using self-immobilized microbial granules is advantageous and obviates the need for nanoparticle encapsulation or use of barrier membranes for retaining Bio-Pd in practical applications. In short, microbial granules offer a dual purpose system for Bio-Pd production and retention, wherein in situ generated H2 serves as electron donor powering biotransformations. Copyright © 2014 Elsevier Ltd. All rights reserved.

Dormancy contributes to the maintenance of microbial diversity.

PubMed

Jones, Stuart E; Lennon, Jay T

2010-03-30

Dormancy is a bet-hedging strategy used by a variety of organisms to overcome unfavorable environmental conditions. By entering a reversible state of low metabolic activity, dormant individuals become members of a seed bank, which can determine community dynamics in future generations. Although microbiologists have documented dormancy in both clinical and natural settings, the importance of seed banks for the diversity and functioning of microbial communities remains untested. Here, we develop a theoretical model demonstrating that microbial communities are structured by environmental cues that trigger dormancy. A molecular survey of lake ecosystems revealed that dormancy plays a more important role in shaping bacterial communities than eukaryotic microbial communities. The proportion of dormant bacteria was relatively low in productive ecosystems but accounted for up to 40% of taxon richness in nutrient-poor systems. Our simulations and empirical data suggest that regional environmental cues and dormancy synchronize the composition of active communities across the landscape while decoupling active microbes from the total community at local scales. Furthermore, we observed that rare bacterial taxa were disproportionately active relative to common bacterial taxa, suggesting that microbial rank-abundance curves are more dynamic than previously considered. We propose that repeated transitions to and from the seed bank may help maintain the high levels of microbial biodiversity that are observed in nearly all ecosystems.

In vitro study on the effect of doxycycline on the microbial activity of soil determined by redox-potential measuring system.

PubMed

Szakmár, Katalin; Reichart, Olivér; Szatmári, István; Erdősi, Orsolya; Szili, Zsuzsanna; László, Noémi; Székely Körmöczy, Péter; Laczay, Péter

2014-09-01

The potential effect of doxycycline on the microbial activity was investigated in three types of soil. Soil samples were spiked with doxycycline, incubated at 25°C and tested at 0, 2, 4 and 6 days after treatment. The microbiological activity of the soil was characterized by the viable count determined by plate pouring and by the time necessary to reach a defined rate of the redox-potential decrease termed as time to detection (TTD).The viable count of the samples was not changed during the storage. The TTD values, however exhibited a significant increase in the 0.2-1.6 mg/kg doxycycline concentration range compared to the untreated samples indicating concentration-dependent inhibitory effect on microbial activity. The potency of the effect was different in the 3 soil types. To describe the combined effect of the doxycycline concentration and time on the biological activity of one type of soil a mathematical model was constructed and applied.The change of microbial metabolic rate could be measured also without (detectable) change of microbial count when the traditional microbiological methods are not applicable. The applied new redox potential measurement-based method is a simple and useful procedure for the examination of microbial activity of soil and its potential inhibition by antibiotics.

Linking Spatial Structure and Community-Level Biotic Interactions through Cooccurrence and Time Series Modeling of the Human Intestinal Microbiota.

PubMed

de Muinck, Eric J; Lundin, Knut E A; Trosvik, Pål

2017-01-01

The gastrointestinal (GI) microbiome is a densely populated ecosystem where dynamics are determined by interactions between microbial community members, as well as host factors. The spatial organization of this system is thought to be important in human health, yet this aspect of our resident microbiome is still poorly understood. In this study, we report significant spatial structure of the GI microbiota, and we identify general categories of spatial patterning in the distribution of microbial taxa along a healthy human GI tract. We further estimate the biotic interaction structure in the GI microbiota, both through time series and cooccurrence modeling of microbial community data derived from a large number of sequentially collected fecal samples. Comparison of these two approaches showed that species pairs involved in significant negative interactions had strong positive contemporaneous correlations and vice versa, while for species pairs without significant interactions, contemporaneous correlations were distributed around zero. We observed similar patterns when comparing these models to the spatial correlations between taxa identified in the adherent microbiota. This suggests that colocalization of microbial taxon pairs, and thus the spatial organization of the GI microbiota, is driven, at least in part, by direct or indirect biotic interactions. Thus, our study can provide a basis for an ecological interpretation of the biogeography of the human gut. IMPORTANCE The human gut microbiome is the subject of intense study due to its importance in health and disease. The majority of these studies have been based on the analysis of feces. However, little is known about how the microbial composition in fecal samples relates to the spatial distribution of microbial taxa along the gastrointestinal tract. By characterizing the microbial content both in intestinal tissue samples and in fecal samples obtained daily, we provide a conceptual framework for how the spatial structure relates to biotic interactions on the community level. We further describe general categories of spatial distribution patterns and identify taxa conforming to these categories. To our knowledge, this is the first study combining spatial and temporal analyses of the human gut microbiome. This type of analysis can be used for identifying candidate probiotics and designing strategies for clinical intervention.

Modular spectral imaging system for discrimination of pigments in cells and microbial communities.

PubMed

Polerecky, Lubos; Bissett, Andrew; Al-Najjar, Mohammad; Faerber, Paul; Osmers, Harald; Suci, Peter A; Stoodley, Paul; de Beer, Dirk

2009-02-01

Here we describe a spectral imaging system for minimally invasive identification, localization, and relative quantification of pigments in cells and microbial communities. The modularity of the system allows pigment detection on spatial scales ranging from the single-cell level to regions whose areas are several tens of square centimeters. For pigment identification in vivo absorption and/or autofluorescence spectra are used as the analytical signals. Along with the hardware, which is easy to transport and simple to assemble and allows rapid measurement, we describe newly developed software that allows highly sensitive and pigment-specific analyses of the hyperspectral data. We also propose and describe a number of applications of the system for microbial ecology, including identification of pigments in living cells and high-spatial-resolution imaging of pigments and the associated phototrophic groups in complex microbial communities, such as photosynthetic endolithic biofilms, microbial mats, and intertidal sediments. This system provides new possibilities for studying the role of spatial organization of microorganisms in the ecological functioning of complex benthic microbial communities or for noninvasively monitoring changes in the spatial organization and/or composition of a microbial community in response to changing environmental factors.

Modular Spectral Imaging System for Discrimination of Pigments in Cells and Microbial Communities▿ †

PubMed Central

Polerecky, Lubos; Bissett, Andrew; Al-Najjar, Mohammad; Faerber, Paul; Osmers, Harald; Suci, Peter A.; Stoodley, Paul; de Beer, Dirk

2009-01-01

Here we describe a spectral imaging system for minimally invasive identification, localization, and relative quantification of pigments in cells and microbial communities. The modularity of the system allows pigment detection on spatial scales ranging from the single-cell level to regions whose areas are several tens of square centimeters. For pigment identification in vivo absorption and/or autofluorescence spectra are used as the analytical signals. Along with the hardware, which is easy to transport and simple to assemble and allows rapid measurement, we describe newly developed software that allows highly sensitive and pigment-specific analyses of the hyperspectral data. We also propose and describe a number of applications of the system for microbial ecology, including identification of pigments in living cells and high-spatial-resolution imaging of pigments and the associated phototrophic groups in complex microbial communities, such as photosynthetic endolithic biofilms, microbial mats, and intertidal sediments. This system provides new possibilities for studying the role of spatial organization of microorganisms in the ecological functioning of complex benthic microbial communities or for noninvasively monitoring changes in the spatial organization and/or composition of a microbial community in response to changing environmental factors. PMID:19074609

Quantitative Microbial Risk Assessment Tutorial Installation of Software for Watershed Modeling in Support of QMRA - Updated 2017

EPA Science Inventory

This tutorial provides instructions for accessing, retrieving, and downloading the following software to install on a host computer in support of Quantitative Microbial Risk Assessment (QMRA) modeling: • QMRA Installation • SDMProjectBuilder (which includes the Microbial ...

Guiding bioprocess design by microbial ecology.

PubMed

Volmer, Jan; Schmid, Andreas; Bühler, Bruno

2015-06-01

Industrial bioprocess development is driven by profitability and eco-efficiency. It profits from an early stage definition of process and biocatalyst design objectives. Microbial bioprocess environments can be considered as synthetic technical microbial ecosystems. Natural systems follow Darwinian evolution principles aiming at survival and reproduction. Technical systems objectives are eco-efficiency, productivity, and profitable production. Deciphering technical microbial ecology reveals differences and similarities of natural and technical systems objectives, which are discussed in this review in view of biocatalyst and process design and engineering strategies. Strategies for handling opposing objectives of natural and technical systems and for exploiting and engineering natural properties of microorganisms for technical systems are reviewed based on examples. This illustrates the relevance of considering microbial ecology for bioprocess design and the potential for exploitation by synthetic biology strategies. Copyright © 2015 Elsevier Ltd. All rights reserved.

Potential Evaporite Biomarkers from the Dead Sea

NASA Technical Reports Server (NTRS)

Morris, Penny A.; Wentworth, Susan J.; Thomas-Keprta, Kathie; Allen, Carlton C.; McKay, David S.

2001-01-01

The Dead Sea is located on the northern branch of the African-Levant Rift systems. The rift system, according to one model, was formed by a series of strike slip faults, initially forming approximately two million years ago. The Dead Sea is an evaporite basin that receives freshwater from springs and from the Jordan River. The Dead Sea is different from other evaporite basins, such as the Great Salt Lake, in that it possesses high concentrations of magnesium and has an average pH of 6.1. The dominant cation in the Great Salt Lake is sodium, and the pH is 7.7. Calcium concentrations are also higher in the Dead Sea than in the Great Salt Lake. Both basins are similar in that the dominant anion is chlorine and the salinity levels are approximately 20 %. Other common cations that have been identified from the waters of the Dead Sea and the Great Salt Lake include sodium and potassium. A variety of Archea, Bacteria, and a single genus of a green algal, Dunaliella, has been described from the Dead Sea. Earlier studies concentrated on microbial identification and analysis of their unique physiology that allows them to survive in this type of extreme environment. Potential microbial fossilization processes, microbial fossils, and the metallic ions associated with fossilization have not been studied thoroughly. The present study is restricted to identifying probable microbial morphologies and associated metallic ions. XRD (X Ray Diffraction) analysis indicates the presence of halite, quartz, and orthoclase feldspar. In addition to these minerals, other workers have reported potassium chloride, magnesium bromide, magnesium chloride, calcium chloride, and calcium sulfate. Halite, calcium sulfate, and orthoclase were examined in this report for the presence of microbes, microbially induced deposits or microbial alteration. Neither the gypsum nor the orthoclase surfaces possesses any obvious indications of microbial life or fossilization. The sand-sized orthoclase particles are weathered with 122 extensive fan-shaped mineral deposits. The gypsum deposits are associated with halite minerals and also exhibit extensive weathering. Halite minerals represent the only substrates that have probable rod-shaped microbial structures with long, filamentous, apical extensions. EDS (energy dispersive x-ray) analysis of the putative microbes indicates elevated calcium levels that are enriched with magnesium. The rod-shaped structures exhibit possible fossilization stages. Rhombohedralshaped minerals of magnesium-enriched calcium carbonate are deposited on the microbial surfaces, and eventually coat the entire microbial surface. The sodium chloride continues to crystallize on nearby halite surface and even crystallizes on the fossilized microbial remains. The putative fossils are found exclusively on halite surfaces, and all contained elevated levels of calcium magnesium cations. Both of these metallic cations are associated with microbial activity and fossilization. Their morphological diversity is low in comparison with the reported living Dead Sea microbial population. If we examine the fossil record for multicellular organisms, fossilization rates are lower for soft-bodied organisms than for those possessing hard parts, i.e. shells, bones. For example, smaller, single celled organisms would have a smaller chance of fossilization; their fossilized shapes could be mistaken for abiotic products. Another consideration is that dead organisms in the water column are probably utilized as a food source by other microbes before fossilization processes are completed. This may be an important consideration as we attempt to model and interpret ancient microbial environments either on Earth or on Mars.

Molecular and Imaging Insights into the Formation of Soil Organic Matter in a Red Pine Rhizosphere

NASA Astrophysics Data System (ADS)

Dohnalkova, A.; Tfaily, M.; Smith, A. P.; Chu, R. K.; Crump, A.; Brislawn, C.; Varga, T.; Shi, Z.; Thomashow, L. S.; Harsh, J. B.; Balogh-Brunstad, Z.; Keller, C. K.

2017-12-01

Microbially-derived carbon inputs to soils play an important role in forming soil organic matter (SOM), but detailed knowledge of basic mechanisms of carbon (C) cycling, such as stabilization of organic C compounds originating from rhizodeposition, is limited. The objective of this study aimed to investigate the stability of rhizosphere-produced carbon components in a model laboratory mesocosm of Pinus resinosa grown in a designed mineral soil mix. We hypothesized that nutrient limitation would cause formation of microbially-produced C constituents that would contribute to SOM stabilization. We focused on the processes of rhizodeposition in the rhizosphere, and we utilized a suite of advanced imaging and molecular techniques to obtain a molecular-level identification of the microbial community and the newly-formed SOM compounds in the rhizosphere and the bulk soil. We considered implications regarding their degree of long-term stability. The microbes in this controlled, nutrient-limited system, without pre-existing organic matter, produced extracellular polymeric substances that formed associations with nutrient-bearing minerals and contributed to the microbial mineral weathering process. Electron microscopy revealed unique ultrastructural residual signatures of biogenic C compounds, and the increased presence of an amorphous organic phase associated with the mineral phase was evidenced by X-ray diffraction. These findings provide insight into the various degrees of stability of microbial SOM products in ecosystems and evidence that the residual biogenic material associated with mineral matrices may be important components in current carbon cycle models.

Phenotypic responses to interspecies competition and commensalism in a naturally-derived microbial co-culture.

PubMed

Khan, Nymul; Maezato, Yukari; McClure, Ryan S; Brislawn, Colin J; Mobberley, Jennifer M; Isern, Nancy; Chrisler, William B; Markillie, Lye Meng; Barney, Brett M; Song, Hyun-Seob; Nelson, William C; Bernstein, Hans C

2018-01-10

The fundamental question of whether different microbial species will co-exist or compete in a given environment depends on context, composition and environmental constraints. Model microbial systems can yield some general principles related to this question. In this study we employed a naturally occurring co-culture composed of heterotrophic bacteria, Halomonas sp. HL-48 and Marinobacter sp. HL-58, to ask two fundamental scientific questions: 1) how do the phenotypes of two naturally co-existing species respond to partnership as compared to axenic growth? and 2) how do growth and molecular phenotypes of these species change with respect to competitive and commensal interactions? We hypothesized - and confirmed - that co-cultivation under glucose as the sole carbon source would result in competitive interactions. Similarly, when glucose was swapped with xylose, the interactions became commensal because Marinobacter HL-58 was supported by metabolites derived from Halomonas HL-48. Each species responded to partnership by changing both its growth and molecular phenotype as assayed via batch growth kinetics and global transcriptomics. These phenotypic responses depended on nutrient availability and so the environment ultimately controlled how they responded to each other. This simplified model community revealed that microbial interactions are context-specific and different environmental conditions dictate how interspecies partnerships will unfold.

Phenotypic responses to interspecies competition and commensalism in a naturally-derived microbial co-culture

DOE Office of Scientific and Technical Information (OSTI.GOV)

Khan, Nymul; Maezato, Yukari; McClure, Ryan S.

The fundamental question of whether different microbial species will co-exist or compete in a given environment depends on context, composition and environmental constraints. Model microbial systems can yield some general principles related to this question. In this study we employed a naturally occurring co-culture composed of heterotrophic bacteria, Halomonas sp. HL-48 and Marinobacter sp. HL-58, to ask two fundamental scientific questions: 1) how do the phenotypes of two naturally co-existing species respond to partnership as compared to axenic growth? and 2) how do growth and molecular phenotypes of these species change with respect to competitive and commensal interactions? We hypothesizedmore » – and confirmed – that co-cultivation under glucose as the sole carbon source would result in a competitive interactions. Similarly, when glucose was swapped with xylose, the interactions became commensal because Marinobacter HL-58 was supported by metabolites derived from Halomonas HL-48. Each species responded to partnership by changing both its growth and molecular phenotype as assayed via batch growth kinetics and global transcriptomics. These phenotypic responses depended nutrient availability and so the environment ultimately controlled how they responded to each other. This simplified model community revealed that microbial interactions are context-specific and different environmental conditions dictate how interspecies partnerships will unfold.« less

Early diagenesis and recrystallization of bone

NASA Astrophysics Data System (ADS)

Keenan, Sarah W.; Engel, Annette Summers

2017-01-01

One of the most challenging problems in paleobiology is determining how bone transforms from a living tissue into a fossil. The geologic record is replete with vertebrate fossils preserved from a range of depositional environments, including wetland systems. However, thermodynamic models suggest that bone (modeled as hydroxylapatite) is generally unstable in a range of varying geochemical conditions and should readily dissolve if it does not alter to a more thermodynamically stable phase, such as a fluorine-enriched apatite. Here, we assess diagenesis of alligator bone from fleshed, articulated skeletons buried in wetland soils and from de-fleshed bones in experimental mesocosms with and without microbial colonization. When microbial colonization of bone was inhibited, bioapatite recrystallization to a more stable apatite phase occurred after one month of burial. Ca-Fe-phosphate phases in bone developed after several months to years due to ion substitutions from the protonation of the hydroxyl ion. These rapid changes demonstrate a continuum of structural and bonding transformations to bone that have not been observed previously. When bones were directly in contact with sediment and microbial cells, rapid bioerosion and compositional alteration occurred after one week, but slowed after one month because biofilms reduced exposed surfaces and subsequent bioapatite lattice substitutions. Microbial contributions are likely essential in forming stable apatite phases during early diagenesis and for enabling bone preservation and fossilization.

Assessing Inhalation Exposures Associated with Contamination Events in Water Distribution Systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Davis, Michael J.; Janke, Robert; Taxon, Thomas N.

When a water distribution system (WDS) is contaminated, short-term inhalation exposures to airborne contaminants could occur as the result of domestic water use. The most important domestic sources of such exposures are likely to be showering and the use of aerosol-producing humidifiers, i.e., ultrasonic and impeller (cool-mist) units. A framework is presented for assessing the potential effects of short-term, system-wide inhalation exposures that could result from such activities during a contamination event. This framework utilizes available statistical models for showering frequency and duration, available exposure models for showering and humidifier use, and experimental results on both aerosol generation and themore » volatilization of chemicals during showering. New models for the times when showering occurs are developed using time-use data for the United States. Given a lack of similar models for how humidifiers are used, or the information needed to develop them, an analysis of the sensitivity of results to assumptions concerning humidifier use is presented. The framework is applied using network models for three actual WDSs. Simple models are developed for estimating upper bounds on the potential effects of system-wide inhalation exposures associated with showering and humidifier use. From a system-wide, population perspective, showering could result in significant inhalation doses of volatile chemical contaminants, and humidifier use could result in significant inhalation doses of microbial contaminants during a contamination event. From a system-wide perspective, showering is unlikely to be associated with significant doses of microbial contaminants. In conclusion, given the potential importance of humidifiers as a source of airborne contaminants during a contamination event, an improved understanding of the nature of humidifier use is warranted.« less

Assessing Inhalation Exposures Associated with Contamination Events in Water Distribution Systems

DOE PAGES

Davis, Michael J.; Janke, Robert; Taxon, Thomas N.

2016-12-08

When a water distribution system (WDS) is contaminated, short-term inhalation exposures to airborne contaminants could occur as the result of domestic water use. The most important domestic sources of such exposures are likely to be showering and the use of aerosol-producing humidifiers, i.e., ultrasonic and impeller (cool-mist) units. A framework is presented for assessing the potential effects of short-term, system-wide inhalation exposures that could result from such activities during a contamination event. This framework utilizes available statistical models for showering frequency and duration, available exposure models for showering and humidifier use, and experimental results on both aerosol generation and themore » volatilization of chemicals during showering. New models for the times when showering occurs are developed using time-use data for the United States. Given a lack of similar models for how humidifiers are used, or the information needed to develop them, an analysis of the sensitivity of results to assumptions concerning humidifier use is presented. The framework is applied using network models for three actual WDSs. Simple models are developed for estimating upper bounds on the potential effects of system-wide inhalation exposures associated with showering and humidifier use. From a system-wide, population perspective, showering could result in significant inhalation doses of volatile chemical contaminants, and humidifier use could result in significant inhalation doses of microbial contaminants during a contamination event. From a system-wide perspective, showering is unlikely to be associated with significant doses of microbial contaminants. In conclusion, given the potential importance of humidifiers as a source of airborne contaminants during a contamination event, an improved understanding of the nature of humidifier use is warranted.« less

Assessing Inhalation Exposures Associated with Contamination Events in Water Distribution Systems

PubMed Central

Davis, Michael J.; Janke, Robert; Taxon, Thomas N.

2016-01-01

When a water distribution system (WDS) is contaminated, short-term inhalation exposures to airborne contaminants could occur as the result of domestic water use. The most important domestic sources of such exposures are likely to be showering and the use of aerosol-producing humidifiers, i.e., ultrasonic and impeller (cool-mist) units. A framework is presented for assessing the potential effects of short-term, system-wide inhalation exposures that could result from such activities during a contamination event. This framework utilizes available statistical models for showering frequency and duration, available exposure models for showering and humidifier use, and experimental results on both aerosol generation and the volatilization of chemicals during showering. New models for the times when showering occurs are developed using time-use data for the United States. Given a lack of similar models for how humidifiers are used, or the information needed to develop them, an analysis of the sensitivity of results to assumptions concerning humidifier use is presented. The framework is applied using network models for three actual WDSs. Simple models are developed for estimating upper bounds on the potential effects of system-wide inhalation exposures associated with showering and humidifier use. From a system-wide, population perspective, showering could result in significant inhalation doses of volatile chemical contaminants, and humidifier use could result in significant inhalation doses of microbial contaminants during a contamination event. From a system-wide perspective, showering is unlikely to be associated with significant doses of microbial contaminants. Given the potential importance of humidifiers as a source of airborne contaminants during a contamination event, an improved understanding of the nature of humidifier use is warranted. PMID:27930709

Stochastic growth logistic model with aftereffect for batch fermentation process

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rosli, Norhayati; Ayoubi, Tawfiqullah; Bahar, Arifah

2014-06-19

In this paper, the stochastic growth logistic model with aftereffect for the cell growth of C. acetobutylicum P262 and Luedeking-Piret equations for solvent production in batch fermentation system is introduced. The parameters values of the mathematical models are estimated via Levenberg-Marquardt optimization method of non-linear least squares. We apply Milstein scheme for solving the stochastic models numerically. The effciency of mathematical models is measured by comparing the simulated result and the experimental data of the microbial growth and solvent production in batch system. Low values of Root Mean-Square Error (RMSE) of stochastic models with aftereffect indicate good fits.

Stochastic growth logistic model with aftereffect for batch fermentation process

NASA Astrophysics Data System (ADS)

Rosli, Norhayati; Ayoubi, Tawfiqullah; Bahar, Arifah; Rahman, Haliza Abdul; Salleh, Madihah Md

2014-06-01

In this paper, the stochastic growth logistic model with aftereffect for the cell growth of C. acetobutylicum P262 and Luedeking-Piret equations for solvent production in batch fermentation system is introduced. The parameters values of the mathematical models are estimated via Levenberg-Marquardt optimization method of non-linear least squares. We apply Milstein scheme for solving the stochastic models numerically. The effciency of mathematical models is measured by comparing the simulated result and the experimental data of the microbial growth and solvent production in batch system. Low values of Root Mean-Square Error (RMSE) of stochastic models with aftereffect indicate good fits.

System for enhanced longevity of in situ microbial filter used for bioremediation

DOEpatents

Carman, M. Leslie; Taylor, Robert T.

2000-01-01

An improved method for in situ microbial filter bioremediation having increasingly operational longevity of an in situ microbial filter emplaced into an aquifer. A method for generating a microbial filter of sufficient catalytic density and thickness, which has increased replenishment interval, improved bacteria attachment and detachment characteristics and the endogenous stability under in situ conditions. A system for in situ field water remediation.

Systems and Photosystems: Cellular Limits of Autotrophic Productivity in Cyanobacteria

PubMed Central

Burnap, Robert L.

2014-01-01

Recent advances in the modeling of microbial growth and metabolism have shown that growth rate critically depends upon the optimal allocation of finite proteomic resources among different cellular functions and that modeling growth rates becomes more realistic with the explicit accounting for the costs of macromolecular synthesis, most importantly, protein expression. The “proteomic constraint” is considered together with its application to understanding photosynthetic microbial growth. The central hypothesis is that physical limits of cellular space (and corresponding solvation capacity) in conjunction with cell surface-to-volume ratios represent the underlying constraints on the maximal rate of autotrophic microbial growth. The limitation of cellular space thus constrains the size the total complement of macromolecules, dissolved ions, and metabolites. To a first approximation, the upper limit in the cellular amount of the total proteome is bounded this space limit. This predicts that adaptation to osmotic stress will result in lower maximal growth rates due to decreased cellular concentrations of core metabolic proteins necessary for cell growth owing the accumulation of compatible osmolytes, as surmised previously. The finite capacity of membrane and cytoplasmic space also leads to the hypothesis that the species-specific differences in maximal growth rates likely reflect differences in the allocation of space to niche-specific proteins with the corresponding diminution of space devoted to other functions including proteins of core autotrophic metabolism, which drive cell reproduction. An optimization model for autotrophic microbial growth, the autotrophic replicator model, was developed based upon previous work investigating heterotrophic growth. The present model describes autotrophic growth in terms of the allocation protein resources among core functional groups including the photosynthetic electron transport chain, light-harvesting antennae, and the ribosome groups. PMID:25654078

Teaching the Microbial Growth Curve Concept Using Microalgal Cultures and Flow Cytometry

ERIC Educational Resources Information Center

Forget, Nathalie; Belzile, Claude; Rioux, Pierre; Nozais, Christian

2010-01-01

The microbial growth curve is widely studied within microbiology classes and bacteria are usually the microbial model used. Here, we describe a novel laboratory protocol involving flow cytometry to assess the growth dynamics of the unicellular microalgae "Isochrysis galbana." The algal model represents an appropriate alternative to…

Capturing microbial sources distributed in a mixed-use watershed within an integrated environmental modeling workflow

EPA Science Inventory

Many watershed models simulate overland and instream microbial fate and transport, but few provide loading rates on land surfaces and point sources to the waterbody network. This paper describes the underlying equations for microbial loading rates associated with 1) land-applied ...

Capturing microbial sources distributed in a mixed-use watershed within an integrated environmental modeling workflow

USDA-ARS?s Scientific Manuscript database

Many watershed models simulate overland and instream microbial fate and transport, but few provide loading rates on land surfaces and point sources to the waterbody network. This paper describes the underlying equations for microbial loading rates associated with 1) land-applied manure on undevelope...

FDA-iRISK--a comparative risk assessment system for evaluating and ranking food-hazard pairs: case studies on microbial hazards.

PubMed

Chen, Yuhuan; Dennis, Sherri B; Hartnett, Emma; Paoli, Greg; Pouillot, Régis; Ruthman, Todd; Wilson, Margaret

2013-03-01

Stakeholders in the system of food safety, in particular federal agencies, need evidence-based, transparent, and rigorous approaches to estimate and compare the risk of foodborne illness from microbial and chemical hazards and the public health impact of interventions. FDA-iRISK (referred to here as iRISK), a Web-based quantitative risk assessment system, was developed to meet this need. The modeling tool enables users to assess, compare, and rank the risks posed by multiple food-hazard pairs at all stages of the food supply system, from primary production, through manufacturing and processing, to retail distribution and, ultimately, to the consumer. Using standard data entry templates, built-in mathematical functions, and Monte Carlo simulation techniques, iRISK integrates data and assumptions from seven components: the food, the hazard, the population of consumers, process models describing the introduction and fate of the hazard up to the point of consumption, consumption patterns, dose-response curves, and health effects. Beyond risk ranking, iRISK enables users to estimate and compare the impact of interventions and control measures on public health risk. iRISK provides estimates of the impact of proposed interventions in various ways, including changes in the mean risk of illness and burden of disease metrics, such as losses in disability-adjusted life years. Case studies for Listeria monocytogenes and Salmonella were developed to demonstrate the application of iRISK for the estimation of risks and the impact of interventions for microbial hazards. iRISK was made available to the public at http://irisk.foodrisk.org in October 2012.

Genome-based Modeling and Design of Metabolic Interactions in Microbial Communities

PubMed Central

Mahadevan, Radhakrishnan; Henson, Michael A.

2012-01-01

Biotechnology research is traditionally focused on individual microbial strains that are perceived to have the necessary metabolic functions, or the capability to have these functions introduced, to achieve a particular task. For many important applications, the development of such omnipotent microbes is an extremely challenging if not impossible task. By contrast, nature employs a radically different strategy based on synergistic combinations of different microbial species that collectively achieve the desired task. These natural communities have evolved to exploit the native metabolic capabilities of each species and are highly adaptive to changes in their environments. However, microbial communities have proven difficult to study due to a lack of suitable experimental and computational tools. With the advent of genome sequencing, omics technologies, bioinformatics and genome-scale modeling, researchers now have unprecedented capabilities to analyze and engineer the metabolism of microbial communities. The goal of this review is to summarize recent applications of genome-scale metabolic modeling to microbial communities. A brief introduction to lumped community models is used to motivate the need for genome-level descriptions of individual species and their metabolic interactions. The review of genome-scale models begins with static modeling approaches, which are appropriate for communities where the extracellular environment can be assumed to be time invariant or slowly varying. Dynamic extensions of the static modeling approach are described, and then applications of genome-scale models for design of synthetic microbial communities are reviewed. The review concludes with a summary of metagenomic tools for analyzing community metabolism and an outlook for future research. PMID:24688668

Genome-based Modeling and Design of Metabolic Interactions in Microbial Communities.

PubMed

Mahadevan, Radhakrishnan; Henson, Michael A

2012-01-01

Biotechnology research is traditionally focused on individual microbial strains that are perceived to have the necessary metabolic functions, or the capability to have these functions introduced, to achieve a particular task. For many important applications, the development of such omnipotent microbes is an extremely challenging if not impossible task. By contrast, nature employs a radically different strategy based on synergistic combinations of different microbial species that collectively achieve the desired task. These natural communities have evolved to exploit the native metabolic capabilities of each species and are highly adaptive to changes in their environments. However, microbial communities have proven difficult to study due to a lack of suitable experimental and computational tools. With the advent of genome sequencing, omics technologies, bioinformatics and genome-scale modeling, researchers now have unprecedented capabilities to analyze and engineer the metabolism of microbial communities. The goal of this review is to summarize recent applications of genome-scale metabolic modeling to microbial communities. A brief introduction to lumped community models is used to motivate the need for genome-level descriptions of individual species and their metabolic interactions. The review of genome-scale models begins with static modeling approaches, which are appropriate for communities where the extracellular environment can be assumed to be time invariant or slowly varying. Dynamic extensions of the static modeling approach are described, and then applications of genome-scale models for design of synthetic microbial communities are reviewed. The review concludes with a summary of metagenomic tools for analyzing community metabolism and an outlook for future research.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wu, Tao; Kukkadapu, Ravi K.; Griffin, Aron M.

Fe(III)-oxides and Fe(III)-bearing phyllosilicates are the two major iron sources utilized as electron acceptors by dissimilatory iron-reducing bacteria (DIRB) in anoxic soils and sediments. Although there have been many studies of microbial Fe(III)-oxide and Fe(III)-phyllosilicate reduction with both natural and specimen materials, no controlled experimental information is available on the interaction between these two phases when both are available for microbial reduction. In this study, the model DIRB Geobacter sulfurreducens was used to examine the pathways of Fe(III) reduction in Fe(III)-oxide stripped subsurface sediment that was coated with different amounts of synthetic high surface area goethite. Cryogenic (12K) 57Fe Mössbauermore » spectroscopy was used to determine changes in the relative abundances of Fe(III)-oxide, Fe(III)-phyllosilicate, and phyllosilicate-associated Fe(II) (Fe(II)-phyllosilicate) in bioreduced samples. Analogous Mössbauer analyses were performed on samples from abiotic Fe(II) sorption experiments in which sediments were exposed to a quantity of exogenous soluble Fe(II) (FeCl22H2O) comparable to the amount of Fe(II) produced during microbial reduction. A Fe partitioning model was developed to analyze the fate of Fe(II) and assess the potential for abiotic Fe(II)-catalyzed reduction of Fe(III)-phyllosilicatesilicates. The microbial reduction experiments indicated that although reduction of Fe(III)-oxide accounted for virtually all of the observed bulk Fe(III) reduction activity, there was no significant abiotic electron transfer between oxide-derived Fe(II) and Fe(III)-phyllosilicatesilicates, with 26-87% of biogenic Fe(II) appearing as sorbed Fe(II) in the Fe(II)-phyllosilicate pool. In contrast, the abiotic Fe(II) sorption experiments showed that 41 and 24% of the added Fe(II) engaged in electron transfer to Fe(III)-phyllosilicate surfaces in synthetic goethite-coated and uncoated sediment. Differences in the rate of Fe(II) addition and system redox potential may account for the microbial and abiotic reaction systems. Our experiments provide new insight into pathways for Fe(III) reduction in mixed Fe(III)-oxide/Fe(III)-phyllosilicate assemblages, and provide key mechanistic insight for interpreting microbial reduction experiments and field data from complex natural soils and sediments.« less

Microbial translocation and microbiome dsybiosis in HIV-associated immune activation

PubMed Central

Zevin, Alexander S.; McKinnon, Lyle; Burgener, Adam; Klatt, Nichole R.

2016-01-01

Purpose of Review To describe the mechanisms and consequences of both microbial translocation and microbial dysbiosis in HIV infection. Recent Findings Microbes in HIV are likely playing a large role in contributing to HIV pathogenesis, morbidities and mortality. Two major disruptions to microbial systems in HIV infection include microbial translocation and microbiome dysbiosis. Microbial translocation occurs when the bacteria (or bacterial products) that should be in the lumen of the intestine translocate across the tight epithelial barrier into systemic circulation, where they contribute to inflammation and pathogenesis. This is associated with poorer health outcomes in HIV infected individuals. In addition, microbial populations in the GI tract are also altered after HIV infection, resulting in microbiome dysbiosis, which further exacerbates microbial translocation, epithelial barrier disruption, inflammation, and mucosal immune functioning. Summary Altered microbial regulation in HIV infection can lead to poor health outcomes, and understanding the mechanisms underlying microbial dysbiosis and translocation may result in novel pathways for therapeutic interventions. PMID:26679414

Mechanistic modelling of the inhibitory effect of pH on microbial growth.

PubMed

Akkermans, Simen; Van Impe, Jan F

2018-06-01

Modelling and simulation of microbial dynamics as a function of processing, transportation and storage conditions is a useful tool to improve microbial food safety and quality. The goal of this research is to improve an existing methodology for building mechanistic predictive models based on the environmental conditions. The effect of environmental conditions on microbial dynamics is often described by combining the separate effects in a multiplicative way (gamma concept). This idea was extended further in this work by including the effects of the lag and stationary growth phases on microbial growth rate as independent gamma factors. A mechanistic description of the stationary phase as a function of pH was included, based on a novel class of models that consider product inhibition. Experimental results on Escherichia coli growth dynamics indicated that also the parameters of the product inhibition equations can be modelled with the gamma approach. This work has extended a modelling methodology, resulting in predictive models that are (i) mechanistically inspired, (ii) easily identifiable with a limited work load and (iii) easily extended to additional environmental conditions. Copyright © 2017. Published by Elsevier Ltd.

Energy-positive wastewater treatment and desalination in an integrated microbial desalination cell (MDC)-microbial electrolysis cell (MEC)

NASA Astrophysics Data System (ADS)

Li, Yan; Styczynski, Jordyn; Huang, Yuankai; Xu, Zhiheng; McCutcheon, Jeffrey; Li, Baikun

2017-07-01

Simultaneous removal of nitrogen in municipal wastewater, metal in industrial wastewater and saline in seawater was achieved in an integrated microbial desalination cell-microbial electrolysis cell (MDC-MEC) system. Batch tests showed that more than 95.1% of nitrogen was oxidized by nitrification in the cathode of MDC and reduced by heterotrophic denitrification in the anode of MDC within 48 h, leading to the total nitrogen removal rate of 4.07 mg L-1 h-1. Combining of nitrogen removal and desalination in MDC effectively solved the problem of pH fluctuation in anode and cathode, and led to 63.7% of desalination. Power generation of MDC (293.7 mW m-2) was 2.9 times higher than the one without salt solution. The electric power of MDC was harvested by a capacitor circuit to supply metal reduction in a MEC, and 99.5% of lead (II) was removed within 48 h. A kinetic MDC model was developed to elucidate the correlation of voltage output and desalination efficiency. Ratio of wastewater and sea water was calculated for MDC optimal operation. Energy balance of nutrient removal, metal removal and desalination in the MDC-MEC system was positive (0.0267 kW h m-3), demonstrating the promise of utilizing low power output of MDCs.

Pore-scale simulation of microbial growth using a genome-scale metabolic model: Implications for Darcy-scale reactive transport

NASA Astrophysics Data System (ADS)

Tartakovsky, G. D.; Tartakovsky, A. M.; Scheibe, T. D.; Fang, Y.; Mahadevan, R.; Lovley, D. R.

2013-09-01

Recent advances in microbiology have enabled the quantitative simulation of microbial metabolism and growth based on genome-scale characterization of metabolic pathways and fluxes. We have incorporated a genome-scale metabolic model of the iron-reducing bacteria Geobacter sulfurreducens into a pore-scale simulation of microbial growth based on coupling of iron reduction to oxidation of a soluble electron donor (acetate). In our model, fluid flow and solute transport is governed by a combination of the Navier-Stokes and advection-diffusion-reaction equations. Microbial growth occurs only on the surface of soil grains where solid-phase mineral iron oxides are available. Mass fluxes of chemical species associated with microbial growth are described by the genome-scale microbial model, implemented using a constraint-based metabolic model, and provide the Robin-type boundary condition for the advection-diffusion equation at soil grain surfaces. Conventional models of microbially-mediated subsurface reactions use a lumped reaction model that does not consider individual microbial reaction pathways, and describe reactions rates using empirically-derived rate formulations such as the Monod-type kinetics. We have used our pore-scale model to explore the relationship between genome-scale metabolic models and Monod-type formulations, and to assess the manifestation of pore-scale variability (microenvironments) in terms of apparent Darcy-scale microbial reaction rates. The genome-scale model predicted lower biomass yield, and different stoichiometry for iron consumption, in comparison to prior Monod formulations based on energetics considerations. We were able to fit an equivalent Monod model, by modifying the reaction stoichiometry and biomass yield coefficient, that could effectively match results of the genome-scale simulation of microbial behaviors under excess nutrient conditions, but predictions of the fitted Monod model deviated from those of the genome-scale model under conditions in which one or more nutrients were limiting. The fitted Monod kinetic model was also applied at the Darcy scale; that is, to simulate average reaction processes at the scale of the entire pore-scale model domain. As we expected, even under excess nutrient conditions for which the Monod and genome-scale models predicted equal reaction rates at the pore scale, the Monod model over-predicted the rates of biomass growth and iron and acetate utilization when applied at the Darcy scale. This discrepancy is caused by an inherent assumption of perfect mixing over the Darcy-scale domain, which is clearly violated in the pore-scale models. These results help to explain the need to modify the flux constraint parameters in order to match observations in previous applications of the genome-scale model at larger scales. These results also motivate further investigation of quantitative multi-scale relationships between fundamental behavior at the pore scale (where genome-scale models are appropriately applied) and observed behavior at larger scales (where predictions of reactive transport phenomena are needed).

Pore-scale simulation of microbial growth using a genome-scale metabolic model: Implications for Darcy-scale reactive transport

NASA Astrophysics Data System (ADS)

Scheibe, T. D.; Tartakovsky, G.; Tartakovsky, A. M.; Fang, Y.; Mahadevan, R.; Lovley, D. R.

2012-12-01

Recent advances in microbiology have enabled the quantitative simulation of microbial metabolism and growth based on genome-scale characterization of metabolic pathways and fluxes. We have incorporated a genome-scale metabolic model of the iron-reducing bacteria Geobacter sulfurreducens into a pore-scale simulation of microbial growth based on coupling of iron reduction to oxidation of a soluble electron donor (acetate). In our model, fluid flow and solute transport is governed by a combination of the Navier-Stokes and advection-diffusion-reaction equations. Microbial growth occurs only on the surface of soil grains where solid-phase mineral iron oxides are available. Mass fluxes of chemical species associated with microbial growth are described by the genome-scale microbial model, implemented using a constraint-based metabolic model, and provide the Robin-type boundary condition for the advection-diffusion equation at soil grain surfaces. Conventional models of microbially-mediated subsurface reactions use a lumped reaction model that does not consider individual microbial reaction pathways, and describe reactions rates using empirically-derived rate formulations such as the Monod-type kinetics. We have used our pore-scale model to explore the relationship between genome-scale metabolic models and Monod-type formulations, and to assess the manifestation of pore-scale variability (microenvironments) in terms of apparent Darcy-scale microbial reaction rates. The genome-scale model predicted lower biomass yield, and different stoichiometry for iron consumption, in comparison to prior Monod formulations based on energetics considerations. We were able to fit an equivalent Monod model, by modifying the reaction stoichiometry and biomass yield coefficient, that could effectively match results of the genome-scale simulation of microbial behaviors under excess nutrient conditions, but predictions of the fitted Monod model deviated from those of the genome-scale model under conditions in which one or more nutrients were limiting. The fitted Monod kinetic model was also applied at the Darcy scale; that is, to simulate average reaction processes at the scale of the entire pore-scale model domain. As we expected, even under excess nutrient conditions for which the Monod and genome-scale models predicted equal reaction rates at the pore scale, the Monod model over-predicted the rates of biomass growth and iron and acetate utilization when applied at the Darcy scale. This discrepancy is caused by an inherent assumption of perfect mixing over the Darcy-scale domain, which is clearly violated in the pore-scale models. These results help to explain the need to modify the flux constraint parameters in order to match observations in previous applications of the genome-scale model at larger scales. These results also motivate further investigation of quantitative multi-scale relationships between fundamental behavior at the pore scale (where genome-scale models are appropriately applied) and observed behavior at larger scales (where predictions of reactive transport phenomena are needed).

Pore-scale simulation of microbial growth using a genome-scale metabolic model: Implications for Darcy-scale reactive transport

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tartakovsky, Guzel D.; Tartakovsky, Alexandre M.; Scheibe, Timothy D.

2013-09-07

Recent advances in microbiology have enabled the quantitative simulation of microbial metabolism and growth based on genome-scale characterization of metabolic pathways and fluxes. We have incorporated a genome-scale metabolic model of the iron-reducing bacteria Geobacter sulfurreducens into a pore-scale simulation of microbial growth based on coupling of iron reduction to oxidation of a soluble electron donor (acetate). In our model, fluid flow and solute transport is governed by a combination of the Navier-Stokes and advection-diffusion-reaction equations. Microbial growth occurs only on the surface of soil grains where solid-phase mineral iron oxides are available. Mass fluxes of chemical species associated withmore » microbial growth are described by the genome-scale microbial model, implemented using a constraint-based metabolic model, and provide the Robin-type boundary condition for the advection-diffusion equation at soil grain surfaces. Conventional models of microbially-mediated subsurface reactions use a lumped reaction model that does not consider individual microbial reaction pathways, and describe reactions rates using empirically-derived rate formulations such as the Monod-type kinetics. We have used our pore-scale model to explore the relationship between genome-scale metabolic models and Monod-type formulations, and to assess the manifestation of pore-scale variability (microenvironments) in terms of apparent Darcy-scale microbial reaction rates. The genome-scale model predicted lower biomass yield, and different stoichiometry for iron consumption, in comparisonto prior Monod formulations based on energetics considerations. We were able to fit an equivalent Monod model, by modifying the reaction stoichiometry and biomass yield coefficient, that could effectively match results of the genome-scale simulation of microbial behaviors under excess nutrient conditions, but predictions of the fitted Monod model deviated from those of the genome-scale model under conditions in which one or more nutrients were limiting. The fitted Monod kinetic model was also applied at the Darcy scale; that is, to simulate average reaction processes at the scale of the entire pore-scale model domain. As we expected, even under excess nutrient conditions for which the Monod and genome-scale models predicted equal reaction rates at the pore scale, the Monod model over-predicted the rates of biomass growth and iron and acetate utilization when applied at the Darcy scale. This discrepancy is caused by an inherent assumption of perfect mixing over the Darcy-scale domain, which is clearly violated in the pore-scale models. These results help to explain the need to modify the flux constraint parameters in order to match observations in previous applications of the genome-scale model at larger scales. These results also motivate further investigation of quantitative multi-scale relationships between fundamental behavior at the pore scale (where genome-scale models are appropriately applied) and observed behavior at larger scales (where predictions of reactive transport phenomena are needed).« less

Residue decomposition of submodel of WEPS

USDA-ARS?s Scientific Manuscript database

The Residue Decomposition submodel of the Wind Erosion Prediction System (WEPS) simulates the decrease in crop residue biomass due to microbial activity. The decomposition process is modeled as a first-order reaction with temperature and moisture as driving variables. Decomposition is a function of ...

Modeling of Sustainable Base Production by Microbial Electrolysis Cell.

PubMed

Blatter, Maxime; Sugnaux, Marc; Comninellis, Christos; Nealson, Kenneth; Fischer, Fabian

2016-07-07

A predictive model for the microbial/electrochemical base formation from wastewater was established and compared to experimental conditions within a microbial electrolysis cell. A Na2 SO4 /K2 SO4 anolyte showed that model prediction matched experimental results. Using Shewanella oneidensis MR-1, a strong base (pH≈13) was generated using applied voltages between 0.3 and 1.1 V. Due to the use of bicarbonate, the pH value in the anolyte remained unchanged, which is required to maintain microbial activity. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Rapid acquisition and model-based analysis of cell-free transcription–translation reactions from nonmodel bacteria

PubMed Central

Wienecke, Sarah; Ishwarbhai, Alka; Tsipa, Argyro; Aw, Rochelle; Kylilis, Nicolas; Bell, David J.; McClymont, David W.; Jensen, Kirsten; Biedendieck, Rebekka

2018-01-01

Native cell-free transcription–translation systems offer a rapid route to characterize the regulatory elements (promoters, transcription factors) for gene expression from nonmodel microbial hosts, which can be difficult to assess through traditional in vivo approaches. One such host, Bacillus megaterium, is a giant Gram-positive bacterium with potential biotechnology applications, although many of its regulatory elements remain uncharacterized. Here, we have developed a rapid automated platform for measuring and modeling in vitro cell-free reactions and have applied this to B. megaterium to quantify a range of ribosome binding site variants and previously uncharacterized endogenous constitutive and inducible promoters. To provide quantitative models for cell-free systems, we have also applied a Bayesian approach to infer ordinary differential equation model parameters by simultaneously using time-course data from multiple experimental conditions. Using this modeling framework, we were able to infer previously unknown transcription factor binding affinities and quantify the sharing of cell-free transcription–translation resources (energy, ribosomes, RNA polymerases, nucleotides, and amino acids) using a promoter competition experiment. This allows insights into resource limiting-factors in batch cell-free synthesis mode. Our combined automated and modeling platform allows for the rapid acquisition and model-based analysis of cell-free transcription–translation data from uncharacterized microbial cell hosts, as well as resource competition within cell-free systems, which potentially can be applied to a range of cell-free synthetic biology and biotechnology applications. PMID:29666238

Assessing the public health risk of microbial intrusion events in distribution systems: conceptual model, available data, and challenges.

PubMed

Besner, Marie-Claude; Prévost, Michèle; Regli, Stig

2011-01-01

Low and negative pressure events in drinking water distribution systems have the potential to result in intrusion of pathogenic microorganisms if an external source of contamination is present (e.g., nearby leaking sewer main) and there is a pathway for contaminant entry (e.g., leaks in drinking water main). While the public health risk associated with such events is not well understood, quantitative microbial risk assessment can be used to estimate such risk. A conceptual model is provided and the state of knowledge, current assumptions, and challenges associated with the conceptual model parameters are presented. This review provides a characterization of the causes, magnitudes, durations and frequencies of low/negative pressure events; pathways for pathogen entry; pathogen occurrence in external sources of contamination; volumes of water that may enter through the different pathways; fate and transport of pathogens from the pathways of entry to customer taps; pathogen exposure to populations consuming the drinking water; and risk associated with pathogen exposure. Copyright © 2010 Elsevier Ltd. All rights reserved.

A Synthetic Community System for Probing Microbial Interactions Driven by Exometabolites

PubMed Central

Chodkowski, John L.

2017-01-01

ABSTRACT Though most microorganisms live within a community, we have modest knowledge about microbial interactions and their implications for community properties and ecosystem functions. To advance understanding of microbial interactions, we describe a straightforward synthetic community system that can be used to interrogate exometabolite interactions among microorganisms. The filter plate system (also known as the Transwell system) physically separates microbial populations, but allows for chemical interactions via a shared medium reservoir. Exometabolites, including small molecules, extracellular enzymes, and antibiotics, are assayed from the reservoir using sensitive mass spectrometry. Community member outcomes, such as growth, productivity, and gene regulation, can be determined using flow cytometry, biomass measurements, and transcript analyses, respectively. The synthetic community design allows for determination of the consequences of microbiome diversity for emergent community properties and for functional changes over time or after perturbation. Because it is versatile, scalable, and accessible, this synthetic community system has the potential to practically advance knowledge of microbial interactions that occur within both natural and artificial communities. IMPORTANCE Understanding microbial interactions is a fundamental objective in microbiology and ecology. The synthetic community system described here can set into motion a range of research to investigate how the diversity of a microbiome and interactions among its members impact its function, where function can be measured as exometabolites. The system allows for community exometabolite profiling to be coupled with genome mining, transcript analysis, and measurements of member productivity and population size. It can also facilitate discovery of natural products that are only produced within microbial consortia. Thus, this synthetic community system has utility to address fundamental questions about a diversity of possible microbial interactions that occur in both natural and engineered ecosystems. Author Video: An author video summary of this article is available. PMID:29152587

Microbial respiration and dissolution precipitation reactions of minerals: thermo-kinetics and reactive transport modelling

NASA Astrophysics Data System (ADS)

Azaroual, M. M.; Parmentier, M.; Andre, L.; Croiset, N.; Pettenati, M.; Kremer, S.

2010-12-01

Microbial processes interact closely with abiotic geochemical reactions and mineralogical transformations in several hydrogeochemical systems. Reactive transport models are aimed to analyze these complex mechanisms integrating as well as the degradation of organic matter as the redox reactions involving successive terminal electron acceptors (TEAPs) mediated by microbes through the continuum of unsaturated zone (soil) - saturated zone (aquifer). The involvement of microbial processes in reactive transport in soil and subsurface geologic greatly complicates the mastery of the major mechanisms and the numerical modelling of these systems. The introduction of kinetic constraints of redox reactions in aqueous phase requires the decoupling of equilibrium reactions and the redefinition of mass balance of chemical elements including the concept of basis species and secondary species of thermodynamic databases used in geochemical modelling tools. An integrated methodology for modelling the reactive transport has been developed and implemented to simulate the transfer of arsenic, denitrification processes and the role of metastable aqueous sulfur species with pyrite and organic matter as electron donors entities. A mechanistic rate law of microbial respiration in various geochemical environments was used to simulate reactive transport of arsenic, nitrate and organic matter combined to the generalized rate law of mineral dissolution - precipitation reactions derived from the transition state theory was used for dissolution - precipitation of silica, aluminosilicate, carbonate, oxyhydroxide, and sulphide minerals. The kinetic parameters are compiled from the literature measurements based on laboratory constrained experiments and field observations. Numerical simulations, using the geochemical software PHREEQC, were performed aiming to identify the key reactions mediated by microbes in the framework of in the first hand the concept of the unsaturated - saturated zones of an artificial recharge of deep aquifers system and in a second hand an acid mine drainage system. A large amount of data is available on the old mine site of Cheni (France). This field data on acid mine drainage are compared to a thermokinetic model including biological kinetics, precipitation-dissolution kinetics and surface complexation on ferrihydrite. The kinetic parameters are from literature and from a fitting on batch biological experiments. The integrated approach combining reaction kinetics and biogeochemical thermodynamic constraints is successfully applied to denitrification experiments in the presence of acetate and pyrite conducted in the laboratory for batch and column systems. The powerful of this coupled approach allows a fine description of the different transition species from nitrate to nitrogen. The fitted kinetic parameters established for modelling these laboratory results are thus extended to simulate the denitrification processes in a field case where organic matter and pyrite FeS2 are the electron donors and O2, NO3, Fe(OH)3, SO4 are the electron acceptors in the framework of a continuum UZ - SZ aiming to identify the stabilized redox zones of acid mine drainage. The detailed results obtained on two actual case studies will be presented.

Integrated Modeling and Carbonate Reservoir Analysis, Upper Jurassic Smackover Formation, Fishpond Field, Southwest Alabama

NASA Astrophysics Data System (ADS)

Owen, Alexander Emory

This field case study focuses on Upper Jurassic (Oxfordian) Smackover hydrocarbon reservoir characterization, modeling and evaluation at Fishpond Field, Escambia County, Alabama, eastern Gulf Coastal Plain of North America. The field is located in the Conecuh Embayment area, south of the Little Cedar Creek Field in Conecuh County and east of Appleton Field in Escambia County. In the Conecuh Embayment, Smackover microbial buildups commonly developed on Paleozoic basement paleohighs in an inner to middle carbonate ramp setting. The microbial and associated facies identified in Fishpond Field are: (F-1) peloidal wackestone, (F-2) peloidal packstone, (F-3) peloidal grainstone, (F-4) peloidal grainstone/packstone, (F-5) microbially-influenced wackestone, (F-6) microbially-influenced packstone, (F-7) microbial boundstone, (F-8) oolitic grainstone, (F-9) shale, and (F-10) dolomitized wackestone/packstone. The Smackover section consists of an alternation of carbonate facies, including F-1 through F-8. The repetitive vertical trend in facies indicates variations in depositional conditions in the area as a result of changes in water depth, energy conditions, salinity, and/or water chemistry due to temporal variations or changes in relative sea level. Accommodation for sediment accumulation also was produced by a change in base level due to differential movement of basement rocks as a result of faulting and/or subsidence due to burial compaction and extension. These changes in base level contributed to the development of a microbial buildup that ranges between 130-165 ft in thickness. The Fishpond Field carbonate reservoir includes a lower microbial buildup interval, a middle grainstone/packstone interval and an upper microbial buildup interval. The Fishpond Field has sedimentary and petroleum system characteristics similar to the neighboring Appleton and Little Cedar Creek Fields, but also has distinct differences from these Smackover fields. The characteristics of the petroleum trap and reservoir at Fishpond Field requires modification of the exploration strategy presently in use to identify Smackover reservoirs productive of hydrocarbons in the Conecuh Embayment area. The complexity of the geologic history of the petroleum trap and reservoir development at Fishpond Field distinguishes this field from the Appleton basement paleohigh and related microbial buildup and the Little Cedar Creek stratigraphic trap and associated inner ramp microbial buildups.

Microbial mutualism at a distance: The role of geometry in diffusive exchanges

NASA Astrophysics Data System (ADS)

Peaudecerf, François J.; Bunbury, Freddy; Bhardwaj, Vaibhav; Bees, Martin A.; Smith, Alison G.; Goldstein, Raymond E.; Croze, Ottavio A.

2018-02-01

The exchange of diffusive metabolites is known to control the spatial patterns formed by microbial populations, as revealed by recent studies in the laboratory. However, the matrices used, such as agarose pads, lack the structured geometry of many natural microbial habitats, including in the soil or on the surfaces of plants or animals. Here we address the important question of how such geometry may control diffusive exchanges and microbial interaction. We model mathematically mutualistic interactions within a minimal unit of structure: two growing reservoirs linked by a diffusive channel through which metabolites are exchanged. The model is applied to study a synthetic mutualism, experimentally parametrized on a model algal-bacterial co-culture. Analytical and numerical solutions of the model predict conditions for the successful establishment of remote mutualisms, and how this depends, often counterintuitively, on diffusion geometry. We connect our findings to understanding complex behavior in synthetic and naturally occurring microbial communities.

Multi -omics and metabolic modelling pipelines: challenges and tools for systems microbiology.

PubMed

Fondi, Marco; Liò, Pietro

2015-02-01

Integrated -omics approaches are quickly spreading across microbiology research labs, leading to (i) the possibility of detecting previously hidden features of microbial cells like multi-scale spatial organization and (ii) tracing molecular components across multiple cellular functional states. This promises to reduce the knowledge gap between genotype and phenotype and poses new challenges for computational microbiologists. We underline how the capability to unravel the complexity of microbial life will strongly depend on the integration of the huge and diverse amount of information that can be derived today from -omics experiments. In this work, we present opportunities and challenges of multi -omics data integration in current systems biology pipelines. We here discuss which layers of biological information are important for biotechnological and clinical purposes, with a special focus on bacterial metabolism and modelling procedures. A general review of the most recent computational tools for performing large-scale datasets integration is also presented, together with a possible framework to guide the design of systems biology experiments by microbiologists. Copyright © 2015. Published by Elsevier GmbH.

Linking Microbial Dynamics and Physicochemical Processes in High-temperature Acidic Fe(III)- Mineralizing Systems

NASA Astrophysics Data System (ADS)

Inskeep, W.

2014-12-01

Microbial activity is responsible for the mineralization of Fe(III)-oxides in high-temperature chemotrophic communities that flourish within oxygenated zones of low pH (2.5 - 4) geothermal outflow channels (Yellowstone National Park, WY). High-temperature Fe(II)-oxidizing communities contain several lineages of Archaea, and are excellent model systems for studying microbial interactions and spatiotemporal dynamics across geochemical gradients. We hypothesize that acidic Fe(III)-oxide mats form as a result of constant interaction among primary colonizers including Hydrogenobaculum spp. (Aquificales) and Metallosphaera spp. (Sulfolobales), and subsequent colonization by archaeal heterotrophs, which vary in abundance as a function of oxygen, pH and temperature. We are integrating a complementary suite of geochemical, stable isotope, genomic, proteomic and modeling analyses to study the role of microorganisms in Fe(III)-oxide mat development, and to elucidate the primary microbial interactions that are coupled with key abiotic events. Curated de novo assemblies of major phylotypes are being used to analyze additional -omics datasets from these microbial mats. Hydrogenobaculum spp. (Aquificales) are the dominant bacterial population(s) present, and predominate during early mat development (< 30 d). Other Sulfolobales populations known to oxidize Fe(II) and fix carbon dioxide (e.g., Metallosphaera spp.) represent a secondary stage of mat development (e.g., 14 - 30 d). Hydrogenobaculum filaments appear to promote the nucleation and subsequent mineralization of Fe(III)-oxides, which likely affect the growth and turnover rates of these organisms. Other heterotrophs colonize Fe(III)-oxide mats during succession (> 30 d), including novel lineages of Archaea and representatives within the Crenarchaeota, Euryarchaeota, Thaumarchaeota and Nanoarchaeota. In situ oxygen consumption rates show that steep gradients occur within the top 1 mm of mat surface, and which correlate with changes in the abundance of different organisms that occupy these microenvironments. The relative consumption of oxygen by different members of Fe(II)-oxidizing mat communities has implications for autotroph-heterotroph associations and the dynamic micromorphology of active Fe(III)-oxide terraces.

A network model shows the importance of coupled processes in the microbial N cycle in the Cape Fear River Estuary

NASA Astrophysics Data System (ADS)

Hines, David E.; Lisa, Jessica A.; Song, Bongkeun; Tobias, Craig R.; Borrett, Stuart R.

2012-06-01

Estuaries serve important ecological and economic functions including habitat provision and the removal of nutrients. Eutrophication can overwhelm the nutrient removal capacity of estuaries and poses a widely recognized threat to the health and function of these ecosystems. Denitrification and anaerobic ammonium oxidation (anammox) are microbial processes responsible for the removal of fixed nitrogen and diminish the effects of eutrophication. Both of these microbial removal processes can be influenced by direct inputs of dissolved inorganic nitrogen substrates or supported by microbial interactions with other nitrogen transforming pathways such as nitrification and dissimilatory nitrate reduction to ammonium (DNRA). The coupling of nitrogen removal pathways to other transformation pathways facilitates the removal of some forms of inorganic nitrogen; however, differentiating between direct and coupled nitrogen removal is difficult. Network modeling provides a tool to examine interactions among microbial nitrogen cycling processes and to determine the within-system history of nitrogen involved in denitrification and anammox. To examine the coupling of nitrogen cycling processes, we built a nitrogen budget mass balance network model in two adjacent 1 cm3 sections of bottom water and sediment in the oligohaline portion of the Cape Fear River Estuary, NC, USA. Pathway, flow, and environ ecological network analyses were conducted to characterize the organization of nitrogen flow in the estuary and to estimate the coupling of nitrification to denitrification and of nitrification and DNRA to anammox. Centrality analysis indicated NH4+ is the most important form of nitrogen involved in removal processes. The model analysis further suggested that direct denitrification and coupled nitrification-denitrification had similar contributions to nitrogen removal while direct anammox was dominant to coupled forms of anammox. Finally, results also indicated that partial nitrification-anammox may play an important role in anammox nitrogen removal in the Cape Fear River Estuary.

Biogeochemical cycling at the aquatic–terrestrial interface is linked to parafluvial hyporheic zone inundation history

DOE Office of Scientific and Technical Information (OSTI.GOV)

Goldman, Amy E.; Graham, Emily B.; Crump, Alex R.

The parafluvial hyporheic zone combines the heightened biogeochemical and microbial interactions indicative of a hyporheic region with direct atmospheric/terrestrial inputs and the effects of wet–dry cycles. Therefore, understanding biogeochemical cycling and microbial interactions in this ecotone is fundamental to understanding biogeochemical cycling at the aquatic–terrestrial interface and to creating robust hydrobiogeochemical models of dynamic river corridors. We aimed to (i) characterize biogeochemical and microbial differences in the parafluvial hyporheic zone across a small spatial domain (6 lateral meters) that spans a breadth of inundation histories and (ii) examine how parafluvial hyporheic sediments respond to laboratory-simulated re-inundation. Surface sediment was collected at fourmore » elevations along transects perpendicular to flow of the Columbia River, eastern WA, USA. The sediments were inundated by the river 0, 13, 127, and 398 days prior to sampling. Spatial variation in environmental variables (organic matter, moisture, nitrate, glucose, %C, %N) and microbial communities (16S and internal transcribed spacer (ITS) rRNA gene sequencing, qPCR) were driven by differences in inundation history. Microbial respiration did not differ significantly across inundation histories prior to forced inundation in laboratory incubations. Forced inundation suppressed microbial respiration across all histories, but the degree of suppression was dramatically different between the sediments saturated and unsaturated at the time of sample collection, indicating a binary threshold response to re-inundation. We present a conceptual model in which irregular hydrologic fluctuations facilitate microbial communities adapted to local conditions and a relatively high flux of CO 2. Upon rewetting, microbial communities are initially suppressed metabolically, which results in lower CO 2 flux rates primarily due to suppression of fungal respiration. Following prolonged inundation, the microbial community adapts to saturation by shifting composition, and the CO 2 flux rebounds to prior levels due to the subsequent change in respiration. Our results indicate that the time between inundation events can push the system into alternate states: we suggest (i) that, above some threshold of inundation interval, re-inundation suppresses respiration to a consistent, low rate and (ii) that, below some inundation interval, re-inundation has a minor effect on respiration. In conclusion, extending reactive transport models to capture processes that govern such dynamics will provide more robust predictions of river corridor biogeochemical function under altered surface water flow regimes in both managed and natural watersheds.« less

Biogeochemical cycling at the aquatic–terrestrial interface is linked to parafluvial hyporheic zone inundation history

DOE PAGES

Goldman, Amy E.; Graham, Emily B.; Crump, Alex R.; ...

2017-09-21

The parafluvial hyporheic zone combines the heightened biogeochemical and microbial interactions indicative of a hyporheic region with direct atmospheric/terrestrial inputs and the effects of wet–dry cycles. Therefore, understanding biogeochemical cycling and microbial interactions in this ecotone is fundamental to understanding biogeochemical cycling at the aquatic–terrestrial interface and to creating robust hydrobiogeochemical models of dynamic river corridors. We aimed to (i) characterize biogeochemical and microbial differences in the parafluvial hyporheic zone across a small spatial domain (6 lateral meters) that spans a breadth of inundation histories and (ii) examine how parafluvial hyporheic sediments respond to laboratory-simulated re-inundation. Surface sediment was collected at fourmore » elevations along transects perpendicular to flow of the Columbia River, eastern WA, USA. The sediments were inundated by the river 0, 13, 127, and 398 days prior to sampling. Spatial variation in environmental variables (organic matter, moisture, nitrate, glucose, %C, %N) and microbial communities (16S and internal transcribed spacer (ITS) rRNA gene sequencing, qPCR) were driven by differences in inundation history. Microbial respiration did not differ significantly across inundation histories prior to forced inundation in laboratory incubations. Forced inundation suppressed microbial respiration across all histories, but the degree of suppression was dramatically different between the sediments saturated and unsaturated at the time of sample collection, indicating a binary threshold response to re-inundation. We present a conceptual model in which irregular hydrologic fluctuations facilitate microbial communities adapted to local conditions and a relatively high flux of CO 2. Upon rewetting, microbial communities are initially suppressed metabolically, which results in lower CO 2 flux rates primarily due to suppression of fungal respiration. Following prolonged inundation, the microbial community adapts to saturation by shifting composition, and the CO 2 flux rebounds to prior levels due to the subsequent change in respiration. Our results indicate that the time between inundation events can push the system into alternate states: we suggest (i) that, above some threshold of inundation interval, re-inundation suppresses respiration to a consistent, low rate and (ii) that, below some inundation interval, re-inundation has a minor effect on respiration. In conclusion, extending reactive transport models to capture processes that govern such dynamics will provide more robust predictions of river corridor biogeochemical function under altered surface water flow regimes in both managed and natural watersheds.« less

Biophysical controls on cluster dynamics and architectural differentiation of microbial biofilms in contrasting flow environments

PubMed Central

Hödl, Iris; Mari, Lorenzo; Bertuzzo, Enrico; Suweis, Samir; Besemer, Katharina; Rinaldo, Andrea; Battin, Tom J

2014-01-01

Ecology, with a traditional focus on plants and animals, seeks to understand the mechanisms underlying structure and dynamics of communities. In microbial ecology, the focus is changing from planktonic communities to attached biofilms that dominate microbial life in numerous systems. Therefore, interest in the structure and function of biofilms is on the rise. Biofilms can form reproducible physical structures (i.e. architecture) at the millimetre-scale, which are central to their functioning. However, the spatial dynamics of the clusters conferring physical structure to biofilms remains often elusive. By experimenting with complex microbial communities forming biofilms in contrasting hydrodynamic microenvironments in stream mesocosms, we show that morphogenesis results in ‘ripple-like’ and ‘star-like’ architectures – as they have also been reported from monospecies bacterial biofilms, for instance. To explore the potential contribution of demographic processes to these architectures, we propose a size-structured population model to simulate the dynamics of biofilm growth and cluster size distribution. Our findings establish that basic physical and demographic processes are key forces that shape apparently universal biofilm architectures as they occur in diverse microbial but also in single-species bacterial biofilms. PMID:23879839

Assessing Coral Reefs on a Pacific-Wide Scale Using the Microbialization Score

PubMed Central

McDole, Tracey; Nulton, James; Barott, Katie L.; Felts, Ben; Hand, Carol; Hatay, Mark; Lee, Hochul; Nadon, Marc O.; Nosrat, Bahador; Salamon, Peter; Bailey, Barbara; Sandin, Stuart A.; Vargas-Angel, Bernardo; Youle, Merry; Zgliczynski, Brian J.; Brainard, Russell E.; Rohwer, Forest

2012-01-01

The majority of the world's coral reefs are in various stages of decline. While a suite of disturbances (overfishing, eutrophication, and global climate change) have been identified, the mechanism(s) of reef system decline remain elusive. Increased microbial and viral loading with higher percentages of opportunistic and specific microbial pathogens have been identified as potentially unifying features of coral reefs in decline. Due to their relative size and high per cell activity, a small change in microbial biomass may signal a large reallocation of available energy in an ecosystem; that is the microbialization of the coral reef. Our hypothesis was that human activities alter the energy budget of the reef system, specifically by altering the allocation of metabolic energy between microbes and macrobes. To determine if this is occurring on a regional scale, we calculated the basal metabolic rates for the fish and microbial communities at 99 sites on twenty-nine coral islands throughout the Pacific Ocean using previously established scaling relationships. From these metabolic rate predictions, we derived a new metric for assessing and comparing reef health called the microbialization score. The microbialization score represents the percentage of the combined fish and microbial predicted metabolic rate that is microbial. Our results demonstrate a strong positive correlation between reef microbialization scores and human impact. In contrast, microbialization scores did not significantly correlate with ocean net primary production, local chla concentrations, or the combined metabolic rate of the fish and microbial communities. These findings support the hypothesis that human activities are shifting energy to the microbes, at the expense of the macrobes. Regardless of oceanographic context, the microbialization score is a powerful metric for assessing the level of human impact a reef system is experiencing. PMID:22970122

Assessing coral reefs on a Pacific-wide scale using the microbialization score.

PubMed

McDole, Tracey; Nulton, James; Barott, Katie L; Felts, Ben; Hand, Carol; Hatay, Mark; Lee, Hochul; Nadon, Marc O; Nosrat, Bahador; Salamon, Peter; Bailey, Barbara; Sandin, Stuart A; Vargas-Angel, Bernardo; Youle, Merry; Zgliczynski, Brian J; Brainard, Russell E; Rohwer, Forest

2012-01-01

The majority of the world's coral reefs are in various stages of decline. While a suite of disturbances (overfishing, eutrophication, and global climate change) have been identified, the mechanism(s) of reef system decline remain elusive. Increased microbial and viral loading with higher percentages of opportunistic and specific microbial pathogens have been identified as potentially unifying features of coral reefs in decline. Due to their relative size and high per cell activity, a small change in microbial biomass may signal a large reallocation of available energy in an ecosystem; that is the microbialization of the coral reef. Our hypothesis was that human activities alter the energy budget of the reef system, specifically by altering the allocation of metabolic energy between microbes and macrobes. To determine if this is occurring on a regional scale, we calculated the basal metabolic rates for the fish and microbial communities at 99 sites on twenty-nine coral islands throughout the Pacific Ocean using previously established scaling relationships. From these metabolic rate predictions, we derived a new metric for assessing and comparing reef health called the microbialization score. The microbialization score represents the percentage of the combined fish and microbial predicted metabolic rate that is microbial. Our results demonstrate a strong positive correlation between reef microbialization scores and human impact. In contrast, microbialization scores did not significantly correlate with ocean net primary production, local chla concentrations, or the combined metabolic rate of the fish and microbial communities. These findings support the hypothesis that human activities are shifting energy to the microbes, at the expense of the macrobes. Regardless of oceanographic context, the microbialization score is a powerful metric for assessing the level of human impact a reef system is experiencing.

Life Support Systems Microbial Challenges

NASA Technical Reports Server (NTRS)

Roman, Monserrate C.

2009-01-01

This viewgraph presentation reviews the current microbial challenges of environmental control and life support systems. The contents include: 1) Environmental Control and Life Support Systems (ECLSS) What is it?; 2) A Look Inside the International Space Station (ISS); 3) The Complexity of a Water Recycling System; 4) ISS Microbiology Acceptability Limits; 5) Overview of Current Microbial Challenges; 6) In a Perfect World What we Would like to Have; and 7) The Future.

Disentangling Mechanisms That Mediate the Balance Between Stochastic and Deterministic Processes in Microbial Succession

DOE PAGES

Dini-Andreote, Francisco; Stegen, James C.; van Elsas, Jan D.; ...

2015-03-17

Despite growing recognition that deterministic and stochastic factors simultaneously influence bacterial communities, little is known about mechanisms shifting their relative importance. To better understand underlying mechanisms, we developed a conceptual model linking ecosystem development during primary succession to shifts in the stochastic/deterministic balance. To evaluate the conceptual model we coupled spatiotemporal data on soil bacterial communities with environmental conditions spanning 105 years of salt marsh development. At the local scale there was a progression from stochasticity to determinism due to Na accumulation with increasing ecosystem age, supporting a main element of the conceptual model. At the regional-scale, soil organic mattermore » (SOM) governed the relative influence of stochasticity and the type of deterministic ecological selection, suggesting scale-dependency in how deterministic ecological selection is imposed. Analysis of a new ecological simulation model supported these conceptual inferences. Looking forward, we propose an extended conceptual model that integrates primary and secondary succession in microbial systems.« less

Fluidized-bed bioreactor system for the microbial solubilization of coal

DOEpatents

Scott, C.D.; Strandberg, G.W.

1987-09-14

A fluidized-bed bioreactor system for the conversion of coal into microbially solubilized coal products. The fluidized-bed bioreactor continuously or periodically receives coal and bio-reactants and provides for the production of microbially solubilized coal products in an economical and efficient manner. An oxidation pretreatment process for rendering coal uniformly and more readily susceptible to microbial solubilization may be employed with the fluidized-bed bioreactor. 2 figs.

Enzymatic desulfurization of coal: Third quarterly report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Marquis, Judith K.; Kitchell, Judith P.

Our current efforts to develop clean coal technology emphasize the advantages of enzymatic desulfurization techniques and have specifically addressed the potential of using partially-purified extracellular microbial enzymes or commercially available enzymes. Our work is focused on the treatment of ''model'' organic sulfur compounds such as dibenzothiophene (DBT) and ethylphenylsulfide (EPS). Furthermore, we are designing experiments to facilitate the enzymatic process by means of a hydrated organic solvent matrix. In this quarter we obtained important results both with the development of our understanding of the enzyme reaction systems and also with the microbial work at Woods Hole. 12 figs., 11 tabs.

Tracking microbial impact on crop production

USDA-ARS?s Scientific Manuscript database

One of the benefits of no-till systems is that activity of the soil microbial community increases. Producers gain an array of improvements in their production systems due to enhanced microbial functioning. For example, corn yield can increase approximately 25% with the same inputs with more microb...

Changes in soil microbial community structure influenced by agricultural management practices in a mediterranean agro-ecosystem.

PubMed

García-Orenes, Fuensanta; Morugán-Coronado, Alicia; Zornoza, Raul; Cerdà, Artemi; Scow, Kate

2013-01-01

Agricultural practices have proven to be unsuitable in many cases, causing considerable reductions in soil quality. Land management practices can provide solutions to this problem and contribute to get a sustainable agriculture model. The main objective of this work was to assess the effect of different agricultural management practices on soil microbial community structure (evaluated as abundance of phospholipid fatty acids, PLFA). Five different treatments were selected, based on the most common practices used by farmers in the study area (eastern Spain): residual herbicides, tillage, tillage with oats and oats straw mulching; these agricultural practices were evaluated against an abandoned land after farming and an adjacent long term wild forest coverage. The results showed a substantial level of differentiation in the microbial community structure, in terms of management practices, which was highly associated with soil organic matter content. Addition of oats straw led to a microbial community structure closer to wild forest coverage soil, associated with increases in organic carbon, microbial biomass and fungal abundances. The microbial community composition of the abandoned agricultural soil was characterised by increases in both fungal abundances and the metabolic quotient (soil respiration per unit of microbial biomass), suggesting an increase in the stability of organic carbon. The ratio of bacteria:fungi was higher in wild forest coverage and land abandoned systems, as well as in the soil treated with oat straw. The most intensively managed soils showed higher abundances of bacteria and actinobacteria. Thus, the application of organic matter, such as oats straw, appears to be a sustainable management practice that enhances organic carbon, microbial biomass and activity and fungal abundances, thereby changing the microbial community structure to one more similar to those observed in soils under wild forest coverage.

Using isotopic tracers to assess the impact of tillage and straw management on the microbial metabolic network in soil

NASA Astrophysics Data System (ADS)

Van Groenigen, K.; Forristal, D.; Jones, M. B.; Schwartz, E.; Hungate, B. A.; Dijkstra, P.

2013-12-01

By decomposing soil organic matter, microbes gain energy and building blocks for biosynthesis and release CO2 to the atmosphere. Therefore, insight into the effect of management practices on microbial metabolic pathways and C use efficiency (CUE; microbial C produced per substrate C utilized) may help to predict long term changes in soil C stocks. We studied the effects of reduced (RT) and conventional tillage (CT) on the microbial central C metabolic network, using soil samples from a 12-year-old field experiment in an Irish winter wheat cropping system. Each year after harvest, straw was removed from half of the RT and CT plots or incorporated into the soil in the other half, resulting in four treatment combinations. We added 1-13C and 2,3-13C pyruvate and 1-13C and U-13C glucose as metabolic tracer isotopomers to composite soil samples taken at two depths (0-15 cm and 15-30 cm) from each treatment and used the rate of position-specific respired 13CO2 to parameterize a metabolic model. Model outcomes were then used to calculate CUE of the microbial community. We found that the composite samples differed in CUE, but the changes were small, with values ranging between 0.757-0.783 across treatments and soil depth. Increases in CUE were associated with a decrease in tricarboxylic acid cycle and reductive pentose phosphate pathway activity and increased consumption of metabolic intermediates for biosynthesis. Our results indicate that RT and straw incorporation promote soil C storage without substantially changing CUE or any of the microbial metabolic pathways. This suggests that at our site, RT and straw incorporation promote soil C storage mostly through direct effects such as increased soil C input and physical protection from decomposition, rather than by feedback responses of the microbial community.

Development and evaluation of the microbial fate and transport module for the Agricultural Policy/Environmental eXtender (APEX) model

USDA-ARS?s Scientific Manuscript database

Microbial contamination of waters in agricultural watershed is the critical public health issue. The watershed-scale model has been proven to be one of the candidate tools for predicting microbial water quality and evaluating management practices. The Agricultural Policy/Environmental eXtender (APEX...

ETV REPORT - PHYSICAL REMOVAL OF CRYPTOSPORIDIUM OOCYSTS AND GIARDIA CYSTS IN DRINKING WATER AQUASOURCE NORTH AMERICA ULTRAFILTRATION SYSTEM A35 AT PITTSBURGH, PA. - NSF00/07/EPADW395

EPA Science Inventory

Verification testing of the Aquasource Ultrafiltration Treatment System Model A35 was conducted from 12/1 - 12/31/98. The treatment system underwent microbial challenge testing on 1/22/99 and demonstrated a 5.5 log10 removal of Giardia cysts and a 6.5 log10 removal of Cryptospori...

[Carbon Source Utilization Characteristics of Soil Microbial Community for Apple Orchard with Interplanting Herbage].

PubMed

Du, Yi-fei; Fang, Kai-kai; Wang, Zhi-kang; Li, Hui-ke; Mao, Peng-juan; Zhang, Xiang-xu; Wang, Jing

2015-11-01

As soil fertility in apple orchard with clean tillage is declined continuously, interplanting herbage in orchard, which is a new orchard management model, plays an important role in improving orchard soil conditions. By using biolog micro-plate technique, this paper studied the functional diversity of soil microbial community under four species of management model in apple orchards, including clear tillage model, interplanting white clover model, interplanting small crown flower model and interplanting cocksfoot model, and the carbon source utilization characteristics of microbial community were explored, which could provide a reference for revealing driving mechanism of ecological process of orchard soil. The results showed that the functional diversity of microbial community had a significant difference among different treatments and in the order of white clover > small crown flower > cocksfoot > clear tillage. The correlation analysis showed that the average well color development (AWCD), Shannon index, Richness index and McIntosh index were all highly significantly positively correlated with soil organic carbon, total nitrogen, microbial biomass carbon, and Shannon index was significantly positively correlated with soil pH. The principal component analysis and the fingerprints of the physiological carbon metabolism of the microbial community demonstrated that grass treatments improved carbon source metabolic ability of soil microbial community, and the soil microbes with perennial legumes (White Clover and small crown flower) had a significantly higher utilization rate in carbohydrates (N-Acetyl-D-Glucosamine, D-Mannitol, β-Methyl-D-Glucoside), amino acids (Glycyl-L-Glutamic acid, L-Serine, L-Threonine) and polymers (Tween 40, Glycogen) than the soil microbes with clear tillage. It was considered that different treatments had the unique microbial community structure and peculiar carbon source utilization characteristics.

Assessing the influence of reactor system design criteria on the performance of model colon fermentation units.

PubMed

Moorthy, Arun S; Eberl, Hermann J

2014-04-01

Fermentation reactor systems are a key platform in studying intestinal microflora, specifically with respect to questions surrounding the effects of diet. In this study, we develop computational representations of colon fermentation reactor systems as a way to assess the influence of three design elements (number of reactors, emptying mechanism, and inclusion of microbial immobilization) on three performance measures (total biomass density, biomass composition, and fibre digestion efficiency) using a fractional-factorial experimental design. It was determined that the choice of emptying mechanism showed no effect on any of the performance measures. Additionally, it was determined that none of the design criteria had any measurable effect on reactor performance with respect to biomass composition. It is recommended that model fermentation systems used in the experimenting of dietary effects on intestinal biomass composition be streamlined to only include necessary system design complexities, as the measured performance is not benefited by the addition of microbial immobilization mechanisms or semi-continuous emptying scheme. Additionally, the added complexities significantly increase computational time during simulation experiments. It was also noted that the same factorial experiment could be directly adapted using in vitro colon fermentation systems. Copyright © 2013 The Society for Biotechnology, Japan. Published by Elsevier B.V. All rights reserved.

Shift in the Microbial Ecology of a Hospital Hot Water System following the Introduction of an On-Site Monochloramine Disinfection System

PubMed Central

Baron, Julianne L.; Vikram, Amit; Duda, Scott; Stout, Janet E.; Bibby, Kyle

2014-01-01

Drinking water distribution systems, including premise plumbing, contain a diverse microbiological community that may include opportunistic pathogens. On-site supplemental disinfection systems have been proposed as a control method for opportunistic pathogens in premise plumbing. The majority of on-site disinfection systems to date have been installed in hospitals due to the high concentration of opportunistic pathogen susceptible occupants. The installation of on-site supplemental disinfection systems in hospitals allows for evaluation of the impact of on-site disinfection systems on drinking water system microbial ecology prior to widespread application. This study evaluated the impact of supplemental monochloramine on the microbial ecology of a hospital’s hot water system. Samples were taken three months and immediately prior to monochloramine treatment and monthly for the first six months of treatment, and all samples were subjected to high throughput Illumina 16S rRNA region sequencing. The microbial community composition of monochloramine treated samples was dramatically different than the baseline months. There was an immediate shift towards decreased relative abundance of Betaproteobacteria, and increased relative abundance of Firmicutes, Alphaproteobacteria, Gammaproteobacteria, Cyanobacteria and Actinobacteria. Following treatment, microbial populations grouped by sampling location rather than sampling time. Over the course of treatment the relative abundance of certain genera containing opportunistic pathogens and genera containing denitrifying bacteria increased. The results demonstrate the driving influence of supplemental disinfection on premise plumbing microbial ecology and suggest the value of further investigation into the overall effects of premise plumbing disinfection strategies on microbial ecology and not solely specific target microorganisms. PMID:25033448

Shift in the microbial ecology of a hospital hot water system following the introduction of an on-site monochloramine disinfection system.

PubMed

Baron, Julianne L; Vikram, Amit; Duda, Scott; Stout, Janet E; Bibby, Kyle

2014-01-01

Drinking water distribution systems, including premise plumbing, contain a diverse microbiological community that may include opportunistic pathogens. On-site supplemental disinfection systems have been proposed as a control method for opportunistic pathogens in premise plumbing. The majority of on-site disinfection systems to date have been installed in hospitals due to the high concentration of opportunistic pathogen susceptible occupants. The installation of on-site supplemental disinfection systems in hospitals allows for evaluation of the impact of on-site disinfection systems on drinking water system microbial ecology prior to widespread application. This study evaluated the impact of supplemental monochloramine on the microbial ecology of a hospital's hot water system. Samples were taken three months and immediately prior to monochloramine treatment and monthly for the first six months of treatment, and all samples were subjected to high throughput Illumina 16S rRNA region sequencing. The microbial community composition of monochloramine treated samples was dramatically different than the baseline months. There was an immediate shift towards decreased relative abundance of Betaproteobacteria, and increased relative abundance of Firmicutes, Alphaproteobacteria, Gammaproteobacteria, Cyanobacteria and Actinobacteria. Following treatment, microbial populations grouped by sampling location rather than sampling time. Over the course of treatment the relative abundance of certain genera containing opportunistic pathogens and genera containing denitrifying bacteria increased. The results demonstrate the driving influence of supplemental disinfection on premise plumbing microbial ecology and suggest the value of further investigation into the overall effects of premise plumbing disinfection strategies on microbial ecology and not solely specific target microorganisms.

Status of microbial diversity in agroforestry systems in Tamil Nadu, India.

PubMed

Radhakrishnan, Srinivasan; Varadharajan, Mohan

2016-06-01

Soil is a complex and dynamic biological system. Agroforestry systems are considered to be an alternative land use option to help and prevent soil degradation, improve soil fertility, microbial diversity, and organic matter status. An increasing interest has emerged with respect to the importance of microbial diversity in soil habitats. The present study deals with the status of microbial diversity in agroforestry systems in Tamil Nadu. Eight soil samples were collected from different fields in agroforestry systems in Cuddalore, Villupuram, Tiruvanamalai, and Erode districts, Tamil Nadu. The number of microorganisms and physico-chemical parameters of soils were quantified. Among different microbial population, the bacterial population was recorded maximum (64%), followed by actinomycetes (23%) and fungi (13%) in different samples screened. It is interesting to note that the microbial population was positively correlated with the physico-chemical properties of different soil samples screened. Total bacterial count had positive correlation with soil organic carbon (C), moisture content, pH, nitrogen (N), and micronutrients such as Iron (Fe), copper (Cu), and zinc (Zn). Similarly, the total actinomycete count also showed positive correlations with bulk density, moisture content, pH, C, N, phosphorus (P), potassium (K), calcium (Ca), copper (Cu), magnesium (Mg), manganese (Mn), and zinc (Zn). It was also noticed that the soil organic matter, vegetation, and soil nutrients altered the microbial community under agroforestry systems. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Novel Barite Chimneys at the Loki's Castle Vent Field Shed Light on Key Factors Shaping Microbial Communities and Functions in Hydrothermal Systems.

PubMed

Steen, Ida H; Dahle, Håkon; Stokke, Runar; Roalkvam, Irene; Daae, Frida-Lise; Rapp, Hans Tore; Pedersen, Rolf B; Thorseth, Ingunn H

2015-01-01

In order to fully understand the cycling of elements in hydrothermal systems it is critical to understand intra-field variations in geochemical and microbiological processes in both focused, high-temperature and diffuse, low-temperature areas. To reveal important causes and effects of this variation, we performed an extensive chemical and microbiological characterization of a low-temperature venting area in the Loki's Castle Vent Field (LCVF). This area, located at the flank of the large sulfide mound, is characterized by numerous chimney-like barite (BaSO4) structures (≤ 1 m high) covered with white cotton-like microbial mats. Results from geochemical analyses, microscopy (FISH, SEM), 16S rRNA gene amplicon-sequencing and metatranscriptomics were compared to results from previous analyses of biofilms growing on black smoker chimneys at LCVF. Based on our results, we constructed a conceptual model involving the geochemistry and microbiology in the LCVF. The model suggests that CH4 and H2S are important electron donors for microorganisms in both high-temperature and low-temperature areas, whereas the utilization of H2 seems restricted to high-temperature areas. This further implies that sub-seafloor processes can affect energy-landscapes, elemental cycling, and the metabolic activity of primary producers on the seafloor. In the cotton-like microbial mats on top of the active barite chimneys, a unique network of single cells of Epsilonproteobacteria interconnected by threads of extracellular polymeric substances (EPS) was seen, differing significantly from the long filamentous Sulfurovum filaments observed in biofilms on the black smokers. This network also induced nucleation of barite crystals and is suggested to play an essential role in the formation of the microbial mats and the chimneys. Furthermore, it illustrates variations in how different genera of Epsilonproteobacteria colonize and position cells in different vent fluid mixing zones within a vent field. This may be related to niche-specific physical characteristics. Altogether, the model provides a reference for future studies and illustrates the importance of systematic comparative studies of spatially closely connected niches in order to fully understand the geomicrobiology of hydrothermal systems.

Methane production from formate, acetate and H2/CO2; focusing on kinetics and microbial characterization.

PubMed

Pan, Xiaofang; Angelidaki, Irini; Alvarado-Morales, Merlin; Liu, Houguang; Liu, Yuhong; Huang, Xu; Zhu, Gefu

2016-10-01

For evaluating the methanogenesis from typical methanogenic precursors (formate, acetate and H2/CO2), CH4 production kinetics were investigated at 37±1°C in batch anaerobic digestion tests and stimulated by modified Gompertz model. The results showed that maximum methanation rate from formate, acetate and H2/CO2 were 19.58±0.49, 42.65±1.17 and 314.64±3.58NmL/gVS/d in digested manure system and 6.53±0.31, 132.04±3.96 and 640.16±19.92NmL/gVS/d in sewage sludge system during second generation incubation. Meanwhile the model could not fit well in granular sludge system, while the rate of formate methanation was faster than from H2/CO2 and acetate. Considering both the kinetic results and microbial assay we could conclude that H2/CO2 methanation was the fastest methanogenic step in digested manure and sewage sludge system with Methanomicrobiales as dominant methanogens, while granular sludge with Methanobacteriales as dominant methanogens contributed to the fastest formate methanation. Copyright © 2016. Published by Elsevier Ltd.

Combining Microbial Enzyme Kinetics Models with Light Use Efficiency Models to Predict CO2 and CH4 Ecosystem Exchange from Flooded and Drained Peatland Systems

NASA Astrophysics Data System (ADS)

Oikawa, P. Y.; Jenerette, D.; Knox, S. H.; Sturtevant, C. S.; Verfaillie, J. G.; Baldocchi, D. D.

2014-12-01

Under California's Cap-and-Trade program, companies are looking to invest in land-use practices that will reduce greenhouse gas (GHG) emissions. The Sacramento-San Joaquin River Delta is a drained cultivated peatland system and a large source of CO2. To slow soil subsidence and reduce CO2 emissions, there is growing interest in converting drained peatlands to wetlands. However, wetlands are large sources of CH4 that could offset CO2-based GHG reductions. The goal of our research is to provide accurate measurements and model predictions of the changes in GHG budgets that occur when drained peatlands are restored to wetland conditions. We have installed a network of eddy covariance towers across multiple land use types in the Delta and have been measuring CO2 and CH4 ecosystem exchange for multiple years. In order to upscale these measurements through space and time we are using these data to parameterize and validate a process-based biogeochemical model. To predict gross primary productivity (GPP), we are using a simple light use efficiency (LUE) model which requires estimates of light, leaf area index and air temperature and can explain 90% of the observed variation in GPP in a mature wetland. To predict ecosystem respiration we have adapted the Dual Arrhenius Michaelis-Menten (DAMM) model. The LUE-DAMM model allows accurate simulation of half-hourly net ecosystem exchange (NEE) in a mature wetland (r2=0.85). We are working to expand the model to pasture, rice and alfalfa systems in the Delta. To predict methanogenesis, we again apply a modified DAMM model, using simple enzyme kinetics. However CH4 exchange is complex and we have thus expanded the model to predict not only microbial CH4 production, but also CH4 oxidation, CH4 storage and the physical processes regulating the release of CH4 to the atmosphere. The CH4-DAMM model allows accurate simulation of daily CH4 ecosystem exchange in a mature wetland (r2=0.55) and robust estimates of annual CH4 budgets. The LUE- and CH4-DAMM models will advance understanding of biogeochemisty and microbial processes in managed peatland systems as well as aid the development of a GHG protocol in the Delta that can provide financial incentive to farmers to reduce GHG emissions under California's Cap and Trade program.

MICROBIAL CHARACTERIZATION OF DRINKING WATER SYSTEMS RECEIVING GROUNDWATER AND SURFACE WATER AS THE PRIMARY SOURCES OF WATER

EPA Science Inventory

Earlier descriptions of water distribution systems (WDS) microbial communities have relied on culturing techniques. These techniques are known to be highly selective in nature, but more importantly, they tend to grossly underestimate the microbial diversity of most environments. ...

Constructing COMSOL Models of a Bacteriological Fuel Cell

NASA Technical Reports Server (NTRS)

Coker, Robert; Mansell, James

2012-01-01

We show very initial work on a specific bioelectrochemical system (BES), a bacteriologically driven 'fuel cell' (BFS), that is intended to process waste products, such as CO2 and brine. (1) Processing is the priority, not power generation (2) Really a Microbial Electrolysis Cell (MEC)

A systems framework for identifying candidate microbial assemblages for disease management

USDA-ARS?s Scientific Manuscript database

Network models of soil and plant microbiomes present new opportunities for enhancing disease management, but also challenges for interpretation. We present a framework for interpreting microbiome networks, illustrating how the observed structure of networks can be used to generate testable hypothese...

Reconstruction of the evolution of microbial defense systems.

PubMed

Puigbò, Pere; Makarova, Kira S; Kristensen, David M; Wolf, Yuri I; Koonin, Eugene V

2017-04-04

Evolution of bacterial and archaeal genomes is a highly dynamic process that involves intensive loss of genes as well as gene gain via horizontal transfer, with a lesser contribution from gene duplication. The rates of these processes can be estimated by comparing genomes that are linked by an evolutionary tree. These estimated rates of genome dynamics events substantially differ for different functional classes of genes. The genes involved in defense against viruses and other invading DNA are among those that are gained and lost at the highest rates. We employed a stochastic birth-and-death model to obtain maximum likelihood estimates of the rates of gain and loss of defense genes in 35 groups of closely related bacterial genomes and one group of archaeal genomes. We find that on average, the defense genes experience 1.4 fold higher flux than the rest of microbial genes. This excessive flux of defense genes over the genomic mean is consistent across diverse microbial groups. The few exceptions include intracellular parasites with small, degraded genomes that possess few defense systems which are more stable than in other microbes. Generally, defense genes follow the previously established pattern of genome dynamics, with gene family loss being about 3 times more common than gain and an order of magnitude more common than expansion or contraction of gene families. Case by case analysis of the evolutionary dynamics of defense genes indicates frequent multiple events in the same locus and widespread involvement of mobile elements in the gain and loss of defense genes. Evolution of microbial defense systems is highly dynamic but, notwithstanding the host-parasite arms race, generally follows the same trends that have been established for the rest of the genes. Apart from the paucity and the low flux of defense genes in parasitic bacteria with deteriorating genomes, there is no clear connection between the evolutionary regime of defense systems and microbial life style.

Temperature sensitivity of soil respiration rates enhanced by microbial community response.

PubMed

Karhu, Kristiina; Auffret, Marc D; Dungait, Jennifer A J; Hopkins, David W; Prosser, James I; Singh, Brajesh K; Subke, Jens-Arne; Wookey, Philip A; Agren, Göran I; Sebastià, Maria-Teresa; Gouriveau, Fabrice; Bergkvist, Göran; Meir, Patrick; Nottingham, Andrew T; Salinas, Norma; Hartley, Iain P

2014-09-04

Soils store about four times as much carbon as plant biomass, and soil microbial respiration releases about 60 petagrams of carbon per year to the atmosphere as carbon dioxide. Short-term experiments have shown that soil microbial respiration increases exponentially with temperature. This information has been incorporated into soil carbon and Earth-system models, which suggest that warming-induced increases in carbon dioxide release from soils represent an important positive feedback loop that could influence twenty-first-century climate change. The magnitude of this feedback remains uncertain, however, not least because the response of soil microbial communities to changing temperatures has the potential to either decrease or increase warming-induced carbon losses substantially. Here we collect soils from different ecosystems along a climate gradient from the Arctic to the Amazon and investigate how microbial community-level responses control the temperature sensitivity of soil respiration. We find that the microbial community-level response more often enhances than reduces the mid- to long-term (90 days) temperature sensitivity of respiration. Furthermore, the strongest enhancing responses were observed in soils with high carbon-to-nitrogen ratios and in soils from cold climatic regions. After 90 days, microbial community responses increased the temperature sensitivity of respiration in high-latitude soils by a factor of 1.4 compared to the instantaneous temperature response. This suggests that the substantial carbon stores in Arctic and boreal soils could be more vulnerable to climate warming than currently predicted.

The Yeast Saccharomyces cerevisiae: a versatile model system for the identification and characterization of bacterial virulence proteins.

PubMed

Siggers, Keri A; Lesser, Cammie F

2008-07-17

Microbial pathogens utilize complex secretion systems to deliver proteins into host cells. These effector proteins target and usurp host cell processes to promote infection and cause disease. While secretion systems are conserved, each pathogen delivers its own unique set of effectors. The identification and characterization of these effector proteins has been difficult, often limited by the lack of detectable signal sequences and functional redundancy. Model systems including yeast, worms, flies, and fish are being used to circumvent these issues. This technical review details the versatility and utility of yeast Saccharomyces cerevisiae as a system to identify and characterize bacterial effectors.

Impact of inoculum sources on biotransformation of pharmaceuticals and personal care products.

PubMed

Kim, Sunah; Rossmassler, Karen; Broeckling, Corey D; Galloway, Sarah; Prenni, Jessica; De Long, Susan K

2017-11-15

Limited knowledge of optimal microbial community composition for PPCP biotreatment, and of the microbial phylotypes that drive biotransformation within mixed microbial communities, has hindered the rational design and operation of effective and reliable biological PPCP treatment technologies. Herein, bacterial community composition was investigated as an isolated variable within batch biofilm reactors via comparison of PPCP removals for three distinct inocula. Inocula pre-acclimated to model PPCPs were derived from activated sludge (AS), ditch sediment historically-impacted by wastewater treatment plant effluent (Sd), and material from laboratory-scale soil aquifer treatment (SAT) columns. PPCP removals were found to be substantially higher for AS- and Sd-derived inocula compared to the SAT-derived inocula despite comparable biomass. Removal patterns differed among the 6 model compounds examined (diclofenac, 5-fluorouracil, gabapentin, gemfibrozil, ibuprofen, and triclosan) indicating differences in biotransformation mechanisms. Sphingomonas, Beijerinckia, Methylophilus, and unknown Cytophagaceae were linked with successful PPCP biodegradation via next-generation sequencing of 16S rRNA genes over time. Results indicate the criticality of applying engineering approaches to control bacterial community compositions in biotreatment systems. Copyright © 2017 Elsevier Ltd. All rights reserved.

Best practices for germ-free derivation and gnotobiotic zebrafish husbandry

PubMed Central

Melancon, E.; De La Torre Canny, S. Gomez; Sichel, S.; Kelly, M.; Wiles, T.J.; Rawls, J.F.; Eisen, J.S.; Guillemin, K.

2017-01-01

All animals are ecosystems with resident microbial communities, referred to as microbiota, which play profound roles in host development, physiology, and evolution. Enabled by new DNA sequencing technologies, there is a burgeoning interest in animal–microbiota interactions, but dissecting the specific impacts of microbes on their hosts is experimentally challenging. Gnotobiology, the study of biological systems in which all members are known, enables precise experimental analysis of the necessity and sufficiency of microbes in animal biology by deriving animals germ-free (GF) and inoculating them with defined microbial lineages. Mammalian host models have long dominated gnotobiology, but we have recently adapted gnotobiotic approaches to the zebrafish (Danio rerio), an important aquatic model. Zebrafish offer several experimental attributes that enable rapid, large-scale gnotobiotic experimentation with high replication rates and exquisite optical resolution. Here we describe detailed protocols for three procedures that form the foundation of zebrafish gnotobiology: derivation of GF embryos, microbial association of GF animals, and long-term, GF husbandry. Our aim is to provide sufficient guidance in zebrafish gnotobiotic methodology to expand and enrich this exciting field of research. PMID:28129860

Comparison of model microbial allocation parameters in soils of varying texture

NASA Astrophysics Data System (ADS)

Hagerty, S. B.; Slessarev, E.; Schimel, J.

2017-12-01

The soil microbial community decomposes the majority of carbon (C) inputs to the soil. However, not all of this C is respired—rather, a substantial portion of the carbon processed by microbes may remain stored in the soil. The balance between C storage and respiration is controlled by microbial turnover rates and C allocation strategies. These microbial community properties may depend on soil texture, which has the potential to influence both the nature and the fate of microbial necromass and extracellular products. To evaluate the role of texture on microbial turnover and C allocation, we sampled four soils from the University of California's Hastings Reserve that varied in texture (one silt loam, two sandy loam, and on clay soil), but support similar grassland plant communities. We added 14C- glucose to the soil and measured the concentration of the label in the carbon dioxide (CO2), microbial biomass, and extractable C pools over 7 weeks. The labeled biomass turned over the slowest in the clay soil; the concentration of labeled biomass was more than 1.5 times the concentration of the other soils after 8 weeks. The clay soil also had the lowest mineralization rate of the label, and mineralization slowed after two weeks. In contrast, in the sandier soils mineralization rates were higher and did not plateau until 5 weeks into the incubation period. We fit the 14C data to a microbial allocation model and estimated microbial parameters; assimilation efficiency, exudation, and biomass specific respiration and turnover for each soil. We compare these parameters across the soil texture gradient to assess the extent to which models may need to account for variability in microbial C allocation across soils of different texture. Our results suggest that microbial C turns over more slowly in high-clay soils than in sandy soils, and that C lost from microbial biomass is retained at higher rates in high-clay soils. Accounting for these differences in microbial allocation and carbon stabilization could improve model representations of C cycling across a range of soil types.

Microbial communities associated with wet flue gas desulfurization systems

PubMed Central

Brown, Bryan P.; Brown, Shannon R.; Senko, John M.

2012-01-01

Flue gas desulfurization (FGD) systems are employed to remove SOx gasses that are produced by the combustion of coal for electric power generation, and consequently limit acid rain associated with these activities. Wet FGDs represent a physicochemically extreme environment due to the high operating temperatures and total dissolved solids (TDS) of fluids in the interior of the FGD units. Despite the potential importance of microbial activities in the performance and operation of FGD systems, the microbial communities associated with them have not been evaluated. Microbial communities associated with distinct process points of FGD systems at several coal-fired electricity generation facilities were evaluated using culture-dependent and -independent approaches. Due to the high solute concentrations and temperatures in the FGD absorber units, culturable halothermophilic/tolerant bacteria were more abundant in samples collected from within the absorber units than in samples collected from the makeup waters that are used to replenish fluids inside the absorber units. Evaluation of bacterial 16S rRNA genes recovered from scale deposits on the walls of absorber units revealed that the microbial communities associated with these deposits are primarily composed of thermophilic bacterial lineages. These findings suggest that unique microbial communities develop in FGD systems in response to physicochemical characteristics of the different process points within the systems. The activities of the thermophilic microbial communities that develop within scale deposits could play a role in the corrosion of steel structures in FGD systems. PMID:23226147

Fixed-bed bioreactor system for the microbial solubilization of coal

DOEpatents

Scott, C.D.; Strandberg, G.W.

1987-09-14

A fixed-bed bioreactor system for the conversion of coal into microbially solubilized coal products. The fixed-bed bioreactor continuously or periodically receives coal and bio-reactants and provides for the large scale production of microbially solubilized coal products in an economical and efficient manner. An oxidation pretreatment process for rendering coal uniformly and more readily susceptible to microbial solubilization may be employed with the fixed-bed bioreactor. 1 fig., 1 tab.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Velsko, S. P.

The microbial DNA Index System (MiDIS) is a concept for a microbial forensic database and investigative decision support system that can be used to help investigators identify the sources of microbial agents that have been used in a criminal or terrorist incident. The heart of the proposed system is a rigorous method for calculating source probabilities by using certain fundamental sampling distributions associated with the propagation and mutation of microbes on disease transmission networks. This formalism has a close relationship to mitochondrial and Y-chromosomal human DNA forensics, and the proposed decision support system is somewhat analogous to the CODIS andmore » SWGDAM mtDNA databases. The MiDIS concept does not involve the use of opportunistic collections of microbial isolates and phylogenetic tree building as a basis for inference. A staged approach can be used to build MiDIS as an enduring capability, beginning with a pilot demonstration program that must meet user expectations for performance and validation before evolving into a continuing effort. Because MiDIS requires input from a a broad array of expertise including outbreak surveillance, field microbial isolate collection, microbial genome sequencing, disease transmission networks, and laboratory mutation rate studies, it will be necessary to assemble a national multi-laboratory team to develop such a system. The MiDIS effort would lend direction and focus to the national microbial genetics research program for microbial forensics, and would provide an appropriate forensic framework for interfacing to future national and international disease surveillance efforts.« less

Games of life and death: antibiotic resistance and production through the lens of evolutionary game theory.

PubMed

Conlin, Peter L; Chandler, Josephine R; Kerr, Benjamin

2014-10-01

In this review, we demonstrate how game theory can be a useful first step in modeling and understanding interactions among bacteria that produce and resist antibiotics. We introduce the basic features of evolutionary game theory and explore model microbial systems that correspond to some classical games. Each game discussed defines a different category of social interaction with different resulting population dynamics (exclusion, coexistence, bistability, cycling). We then explore how the framework can be extended to incorporate some of the complexity of natural microbial communities. Overall, the game theoretical perspective helps to guide our expectations about the evolution of some forms of antibiotic resistance and production because it makes clear the precise nature of social interaction in this context. Copyright © 2014 Elsevier Ltd. All rights reserved.

Forensic microbiology: Evolving from discriminating distinct microbes to characterizing entire microbial communities on decomposing remains

USDA-ARS?s Scientific Manuscript database

The body of an animal encompasses a multitude of compositionally and functionally unique microbial environments, from the skin to the gastrointestinal system. Each of these systems harbor microbial communities that have adapted in order to cohabitate with their specific host resulting in a distinct...

Divergence in plant and microbial allocation strategies explains continental patterns in microbial allocation and biogeochemical fluxes.

PubMed

Averill, Colin

2014-10-01

Allocation trade-offs shape ecological and biogeochemical phenomena at local to global scale. Plant allocation strategies drive major changes in ecosystem carbon cycling. Microbial allocation to enzymes that decompose carbon vs. organic nutrients may similarly affect ecosystem carbon cycling. Current solutions to this allocation problem prioritise stoichiometric tradeoffs implemented in plant ecology. These solutions may not maximise microbial growth and fitness under all conditions, because organic nutrients are also a significant carbon resource for microbes. I created multiple allocation frameworks and simulated microbial growth using a microbial explicit biogeochemical model. I demonstrate that prioritising stoichiometric trade-offs does not optimise microbial allocation, while exploiting organic nutrients as carbon resources does. Analysis of continental-scale enzyme data supports the allocation patterns predicted by this framework, and modelling suggests large deviations in soil C loss based on which strategy is implemented. Therefore, understanding microbial allocation strategies will likely improve our understanding of carbon cycling and climate. © 2014 John Wiley & Sons Ltd/CNRS.

Microbial ecology of terrestrial Antarctica: Are microbial systems at risk from human activities?

DOE Office of Scientific and Technical Information (OSTI.GOV)

White, G.J.

1996-08-01

Many of the ecological systems found in continental Antarctica are comprised entirely of microbial species. Concerns have arisen that these microbial systems might be at risk either directly through the actions of humans or indirectly through increased competition from introduced species. Although protection of native biota is covered by the Protocol on Environmental Protection to the Antarctic Treaty, strict measures for preventing the introduction on non-native species or for protecting microbial habitats may be impractical. This report summarizes the research conducted to date on microbial ecosystems in continental Antarctica and discusses the need for protecting these ecosystems. The focus ismore » on communities inhabiting soil and rock surfaces in non-coastal areas of continental Antarctica. Although current polices regarding waste management and other operations in Antarctic research stations serve to reduce the introduction on non- native microbial species, importation cannot be eliminated entirely. Increased awareness of microbial habitats by field personnel and protection of certain unique habitats from physical destruction by humans may be necessary. At present, small-scale impacts from human activities are occurring in certain areas both in terms of introduced species and destruction of habitat. On a large scale, however, it is questionable whether the introduction of non-native microbial species to terrestrial Antarctica merits concern.« less

Design, engineering, and construction of photosynthetic microbial cell factories for renewable solar fuel production.

PubMed

Lindblad, Peter; Lindberg, Pia; Oliveira, Paulo; Stensjö, Karin; Heidorn, Thorsten

2012-01-01

There is an urgent need to develop sustainable solutions to convert solar energy into energy carriers used in the society. In addition to solar cells generating electricity, there are several options to generate solar fuels. This paper outlines and discusses the design and engineering of photosynthetic microbial systems for the generation of renewable solar fuels, with a focus on cyanobacteria. Cyanobacteria are prokaryotic microorganisms with the same type of photosynthesis as higher plants. Native and engineered cyanobacteria have been used by us and others as model systems to examine, demonstrate, and develop photobiological H(2) production. More recently, the production of carbon-containing solar fuels like ethanol, butanol, and isoprene have been demonstrated. We are using a synthetic biology approach to develop efficient photosynthetic microbial cell factories for direct generation of biofuels from solar energy. Present progress and advances in the design, engineering, and construction of such cyanobacterial cells for the generation of a portfolio of solar fuels, e.g., hydrogen, alcohols, and isoprene, are presented and discussed. Possibilities and challenges when introducing and using synthetic biology are highlighted.

Microbial metaproteomics for characterizing the range of metabolic functions and activities of human gut microbiota.

PubMed

Xiong, Weili; Abraham, Paul E; Li, Zhou; Pan, Chongle; Hettich, Robert L

2015-10-01

The human gastrointestinal tract is a complex, dynamic ecosystem that consists of a carefully tuned balance of human host and microbiota membership. The microbiome is not merely a collection of opportunistic parasites, but rather provides important functions to the host that are absolutely critical to many aspects of health, including nutrient transformation and absorption, drug metabolism, pathogen defense, and immune system development. Microbial metaproteomics provides the ability to characterize the human gut microbiota functions and metabolic activities at a remarkably deep level, revealing information about microbiome development and stability as well as their interactions with their human host. Generally, microbial and human proteins can be extracted and then measured by high performance MS-based proteomics technology. Here, we review the field of human gut microbiome metaproteomics, with a focus on the experimental and informatics considerations involved in characterizing systems ranging from low-complexity model gut microbiota in gnotobiotic mice, to the emerging gut microbiome in the GI tract of newborn human infants, and finally to an established gut microbiota in human adults. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Microbial community pattern detection in human body habitats via ensemble clustering framework.

PubMed

Yang, Peng; Su, Xiaoquan; Ou-Yang, Le; Chua, Hon-Nian; Li, Xiao-Li; Ning, Kang

2014-01-01

The human habitat is a host where microbial species evolve, function, and continue to evolve. Elucidating how microbial communities respond to human habitats is a fundamental and critical task, as establishing baselines of human microbiome is essential in understanding its role in human disease and health. Recent studies on healthy human microbiome focus on particular body habitats, assuming that microbiome develop similar structural patterns to perform similar ecosystem function under same environmental conditions. However, current studies usually overlook a complex and interconnected landscape of human microbiome and limit the ability in particular body habitats with learning models of specific criterion. Therefore, these methods could not capture the real-world underlying microbial patterns effectively. To obtain a comprehensive view, we propose a novel ensemble clustering framework to mine the structure of microbial community pattern on large-scale metagenomic data. Particularly, we first build a microbial similarity network via integrating 1920 metagenomic samples from three body habitats of healthy adults. Then a novel symmetric Nonnegative Matrix Factorization (NMF) based ensemble model is proposed and applied onto the network to detect clustering pattern. Extensive experiments are conducted to evaluate the effectiveness of our model on deriving microbial community with respect to body habitat and host gender. From clustering results, we observed that body habitat exhibits a strong bound but non-unique microbial structural pattern. Meanwhile, human microbiome reveals different degree of structural variations over body habitat and host gender. In summary, our ensemble clustering framework could efficiently explore integrated clustering results to accurately identify microbial communities, and provide a comprehensive view for a set of microbial communities. The clustering results indicate that structure of human microbiome is varied systematically across body habitats and host genders. Such trends depict an integrated biography of microbial communities, which offer a new insight towards uncovering pathogenic model of human microbiome.

Microbial community pattern detection in human body habitats via ensemble clustering framework

PubMed Central

2014-01-01

Background The human habitat is a host where microbial species evolve, function, and continue to evolve. Elucidating how microbial communities respond to human habitats is a fundamental and critical task, as establishing baselines of human microbiome is essential in understanding its role in human disease and health. Recent studies on healthy human microbiome focus on particular body habitats, assuming that microbiome develop similar structural patterns to perform similar ecosystem function under same environmental conditions. However, current studies usually overlook a complex and interconnected landscape of human microbiome and limit the ability in particular body habitats with learning models of specific criterion. Therefore, these methods could not capture the real-world underlying microbial patterns effectively. Results To obtain a comprehensive view, we propose a novel ensemble clustering framework to mine the structure of microbial community pattern on large-scale metagenomic data. Particularly, we first build a microbial similarity network via integrating 1920 metagenomic samples from three body habitats of healthy adults. Then a novel symmetric Nonnegative Matrix Factorization (NMF) based ensemble model is proposed and applied onto the network to detect clustering pattern. Extensive experiments are conducted to evaluate the effectiveness of our model on deriving microbial community with respect to body habitat and host gender. From clustering results, we observed that body habitat exhibits a strong bound but non-unique microbial structural pattern. Meanwhile, human microbiome reveals different degree of structural variations over body habitat and host gender. Conclusions In summary, our ensemble clustering framework could efficiently explore integrated clustering results to accurately identify microbial communities, and provide a comprehensive view for a set of microbial communities. The clustering results indicate that structure of human microbiome is varied systematically across body habitats and host genders. Such trends depict an integrated biography of microbial communities, which offer a new insight towards uncovering pathogenic model of human microbiome. PMID:25521415

Soil microbial biomass and function are altered by 12 years of crop rotation

NASA Astrophysics Data System (ADS)

McDaniel, Marshall D.; Grandy, A. Stuart

2016-11-01

Declines in plant diversity will likely reduce soil microbial biomass, alter microbial functions, and threaten the provisioning of soil ecosystem services. We examined whether increasing temporal plant biodiversity in agroecosystems (by rotating crops) can partially reverse these trends and enhance soil microbial biomass and function. We quantified seasonal patterns in soil microbial biomass, respiration rates, extracellular enzyme activity, and catabolic potential three times over one growing season in a 12-year crop rotation study at the W. K. Kellogg Biological Station LTER. Rotation treatments varied from one to five crops in a 3-year rotation cycle, but all soils were sampled under a corn year. We hypothesized that crop diversity would increase microbial biomass, activity, and catabolic evenness (a measure of functional diversity). Inorganic N, the stoichiometry of microbial biomass and dissolved organic C and N varied seasonally, likely reflecting fluctuations in soil resources during the growing season. Soils from biodiverse cropping systems increased microbial biomass C by 28-112 % and N by 18-58 % compared to low-diversity systems. Rotations increased potential C mineralization by as much as 53 %, and potential N mineralization by 72 %, and both were related to substantially higher hydrolase and lower oxidase enzyme activities. The catabolic potential of the soil microbial community showed no, or slightly lower, catabolic evenness in more diverse rotations. However, the catabolic potential indicated that soil microbial communities were functionally distinct, and microbes from monoculture corn preferentially used simple substrates like carboxylic acids, relative to more diverse cropping systems. By isolating plant biodiversity from differences in fertilization and tillage, our study illustrates that crop biodiversity has overarching effects on soil microbial biomass and function that last throughout the growing season. In simplified agricultural systems, relatively small increases in crop diversity can have large impacts on microbial community size and function, with cover crops appearing to facilitate the largest increases.

Novel food packaging systems with natural antimicrobial agents.

PubMed

Irkin, Reyhan; Esmer, Ozlem Kizilirmak

2015-10-01

A new type of packaging that combines food packaging materials with antimicrobial substances to control microbial surface contamination of foods to enhance product microbial safety and to extend shelf-life is attracting interest in the packaging industry. Several antimicrobial compounds can be combined with different types of packaging materials. But in recent years, since consumer demand for natural food ingredients has increased because of safety and availability, these natural compounds are beginning to replace the chemical additives in foods and are perceived to be safer and claimed to alleviate safety concerns. Recent research studies are mainly focused on the application of natural antimicrobials in food packaging system. Biologically derived compounds like bacteriocins, phytochemicals, enzymes can be used in antimicrobial food packaging. The aim of this review is to give an overview of most important knowledge about application of natural antimicrobial packagings with model food systems and their antimicrobial effects on food products.

Resolution in forensic microbial genotyping

DOE Office of Scientific and Technical Information (OSTI.GOV)

Velsko, S P

2005-08-30

Resolution is a key parameter for differentiating among the large number of strain typing methods that could be applied to pathogens involved in bioterror events or biocrimes. In this report we develop a first-principles analysis of strain typing resolution using a simple mathematical model to provide a basis for the rational design of microbial typing systems for forensic applications. We derive two figures of merit that describe the resolving power and phylogenetic depth of a strain typing system. Rough estimates of these figures-of-merit for MLVA, MLST, IS element, AFLP, hybridization microarrays, and other bacterial typing methods are derived from mutationmore » rate data reported in the literature. We also discuss the general problem of how to construct a ''universal'' practical typing system that has the highest possible resolution short of whole-genome sequencing, and that is applicable with minimal modification to a wide range of pathogens.« less

Industrial systems biology and its impact on synthetic biology of yeast cell factories.

PubMed

Fletcher, Eugene; Krivoruchko, Anastasia; Nielsen, Jens

2016-06-01

Engineering industrial cell factories to effectively yield a desired product while dealing with industrially relevant stresses is usually the most challenging step in the development of industrial production of chemicals using microbial fermentation processes. Using synthetic biology tools, microbial cell factories such as Saccharomyces cerevisiae can be engineered to express synthetic pathways for the production of fuels, biopharmaceuticals, fragrances, and food flavors. However, directing fluxes through these synthetic pathways towards the desired product can be demanding due to complex regulation or poor gene expression. Systems biology, which applies computational tools and mathematical modeling to understand complex biological networks, can be used to guide synthetic biology design. Here, we present our perspective on how systems biology can impact synthetic biology towards the goal of developing improved yeast cell factories. Biotechnol. Bioeng. 2016;113: 1164-1170. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

Microbial Successions Are Associated with Changes in Chemical Profiles of a Model Refrigerated Fresh Pork Sausage during an 80-Day Shelf Life Study

PubMed Central

David, Jairus R. D.; Gilbreth, Stefanie Evans; Smith, Gordon; Nietfeldt, Joseph; Legge, Ryan; Kim, Jaehyoung; Sinha, Rohita; Duncan, Christopher E.; Ma, Junjie; Singh, Indarpal

2014-01-01

Fresh pork sausage is produced without a microbial kill step and therefore chilled or frozen to control microbial growth. In this report, the microbiota in a chilled fresh pork sausage model produced with or without an antimicrobial combination of sodium lactate and sodium diacetate was studied using a combination of traditional microbiological methods and deep pyrosequencing of 16S rRNA gene amplicons. In the untreated system, microbial populations rose from 102 to 106 CFU/g within 15 days of storage at 4°C, peaking at nearly 108 CFU/g by day 30. Pyrosequencing revealed a complex community at day 0, with taxa belonging to the Bacilli, Gammaproteobacteria, Betaproteobacteria, Actinobacteria, Bacteroidetes, and Clostridia. During storage at 4°C, the untreated system displayed a complex succession, with species of Weissella and Leuconostoc that dominate the product at day 0 being displaced by species of Pseudomonas (P. lini and P. psychrophila) within 15 days. By day 30, a second wave of taxa (Lactobacillus graminis, Carnobacterium divergens, Buttiauxella brennerae, Yersinia mollaretti, and a taxon of Serratia) dominated the population, and this succession coincided with significant chemical changes in the matrix. Treatment with lactate-diacetate altered the dynamics dramatically, yielding a monophasic growth curve of a single species of Lactobacillus (L. graminis), followed by a uniform selective die-off of the majority of species in the population. Of the six species of Lactobacillus that were routinely detected, L. graminis became the dominant member in all samples, and its origins were traced to the spice blend used in the formulation. PMID:24928886

Seasonal hyporheic dynamics control coupled microbiology and geochemistry in Colorado River sediments

DOE PAGES

Danczak, Robert E.; Sawyer, Audrey H.; Williams, Kenneth H.; ...

2016-12-03

Riverbed microbial communities play an oversized role in many watershed ecosystem functions, including the processing of organic carbon, cycling of nitrogen, and alterations to metal mobility. The structure and activity of microbial assemblages depend in part on geochemical conditions set by river-groundwater exchange or hyporheic exchange. In order to assess how seasonal changes in river-groundwater mixing affect these populations in a snowmelt-dominated fluvial system, vertical sediment and pore water profiles were sampled at three time points at one location in the hyporheic zone of the Colorado River and analyzed by using geochemical measurements, 16S rRNA gene sequencing, and ecological modeling.more » Oxic river water penetrated deepest into the subsurface during peak river discharge, while under base flow conditions, anoxic groundwater dominated shallower depths. Over a 70 cm thick interval, riverbed sediments were therefore exposed to seasonally fluctuating redox conditions and hosted microbial populations statistically different from those at both shallower and deeper locations. Additionally, microbial populations within this zone were shown to be the most dynamic across sampling time points, underlining the critical role that hyporheic mixing plays in constraining microbial abundances. Given such mixing effects, we anticipate that future changes in river discharge in mountainous, semiarid western U.S. watersheds may affect microbial community structure and function in riverbed environments, with potential implications for biogeochemical processes in riparian regions.« less

Seasonal hyporheic dynamics control coupled microbiology and geochemistry in Colorado River sediments

DOE Office of Scientific and Technical Information (OSTI.GOV)

Danczak, Robert E.; Sawyer, Audrey H.; Williams, Kenneth H.

Riverbed microbial communities play an oversized role in many watershed ecosystem functions, including the processing of organic carbon, cycling of nitrogen, and alterations to metal mobility. The structure and activity of microbial assemblages depend in part on geochemical conditions set by river-groundwater exchange or hyporheic exchange. In order to assess how seasonal changes in river-groundwater mixing affect these populations in a snowmelt-dominated fluvial system, vertical sediment and pore water profiles were sampled at three time points at one location in the hyporheic zone of the Colorado River and analyzed by using geochemical measurements, 16S rRNA gene sequencing, and ecological modeling.more » Oxic river water penetrated deepest into the subsurface during peak river discharge, while under base flow conditions, anoxic groundwater dominated shallower depths. Over a 70 cm thick interval, riverbed sediments were therefore exposed to seasonally fluctuating redox conditions and hosted microbial populations statistically different from those at both shallower and deeper locations. Additionally, microbial populations within this zone were shown to be the most dynamic across sampling time points, underlining the critical role that hyporheic mixing plays in constraining microbial abundances. Given such mixing effects, we anticipate that future changes in river discharge in mountainous, semiarid western U.S. watersheds may affect microbial community structure and function in riverbed environments, with potential implications for biogeochemical processes in riparian regions.« less

Seasonal hyporheic dynamics control coupled microbiology and geochemistry in Colorado River sediments

NASA Astrophysics Data System (ADS)

Danczak, Robert E.; Sawyer, Audrey H.; Williams, Kenneth H.; Stegen, James C.; Hobson, Chad; Wilkins, Michael J.

2016-12-01

Riverbed microbial communities play an oversized role in many watershed ecosystem functions, including the processing of organic carbon, cycling of nitrogen, and alterations to metal mobility. The structure and activity of microbial assemblages depend in part on geochemical conditions set by river-groundwater exchange or hyporheic exchange. To assess how seasonal changes in river-groundwater mixing affect these populations in a snowmelt-dominated fluvial system, vertical sediment and pore water profiles were sampled at three time points at one location in the hyporheic zone of the Colorado River and analyzed by using geochemical measurements, 16S rRNA gene sequencing, and ecological modeling. Oxic river water penetrated deepest into the subsurface during peak river discharge, while under base flow conditions, anoxic groundwater dominated shallower depths. Over a 70 cm thick interval, riverbed sediments were therefore exposed to seasonally fluctuating redox conditions and hosted microbial populations statistically different from those at both shallower and deeper locations. Additionally, microbial populations within this zone were shown to be the most dynamic across sampling time points, underlining the critical role that hyporheic mixing plays in constraining microbial abundances. Given such mixing effects, we anticipate that future changes in river discharge in mountainous, semiarid western U.S. watersheds may affect microbial community structure and function in riverbed environments, with potential implications for biogeochemical processes in riparian regions.

Microbial dormancy improves development and experimental validation of ecosystem model

DOE PAGES

Wang, Gangsheng; Jagadamma, Sindhu; Mayes, Melanie; ...

2014-07-11

Climate feedbacks from soils can result from environmental change followed by response of plant and microbial communities, and/or associated changes in nutrient cycling. Explicit consideration of microbial life history traits and functions may be necessary to predict climate feedbacks due to changes in the physiology and community composition of microbes and their associated effect on carbon cycling. Here, we enhanced the Microbial-Enzyme-mediated Decomposition (MEND) model by incorporating microbial dormancy and the ability to track multiple isotopes of carbon. We tested two versions of MEND, i.e., MEND with dormancy and MEND without dormancy, against long-term (270 d) lab incubations of fourmore » soils with isotopically-labeled substrates. MEND without dormancy adequately fitted multiple observations (total and 14C respiration, and dissolved organic carbon), but at the cost of significantly underestimating the total microbial biomass. The MEND with dormancy improved estimates of microbial biomass by 20 71% over the MEND without dormancy. We observed large differences for two fitted model parameters, the specific maintenance and growth rates for active microbes, depending on whether dormancy was considered. Together our model extrapolations of the incubation study show that long-term soil incubations with observations in multiple carbon pools are necessary to estimate both decomposition and microbial parameters. These efforts should provide essential support to future field- and global-scale simulations and enable more confident predictions of feedbacks between environmental change and carbon cycling.« less

Simulated Carbon Cycling in a Model Microbial Mat.

NASA Astrophysics Data System (ADS)

Decker, K. L.; Potter, C. S.

2006-12-01

We present here the novel addition of detailed organic carbon cycling to our model of a hypersaline microbial mat ecosystem. This ecosystem model, MBGC (Microbial BioGeoChemistry), simulates carbon fixation through oxygenic and anoxygenic photosynthesis, and the release of C and electrons for microbial heterotrophs via cyanobacterial exudates and also via a pool of dead cells. Previously in MBGC, the organic portion of the carbon cycle was simplified into a black-box rate of accumulation of simple and complex organic compounds based on photosynthesis and mortality rates. We will discuss the novel inclusion of fermentation as a source of carbon and electrons for use in methanogenesis and sulfate reduction, and the influence of photorespiration on labile carbon exudation rates in cyanobacteria. We will also discuss the modeling of decomposition of dead cells and the ultimate release of inorganic carbon. The detailed modeling of organic carbon cycling is important to the accurate representation of inorganic carbon flux through the mat, as well as to accurate representation of growth models of the heterotrophs under different environmental conditions. Because the model ecosystem is an analog of ancient microbial mats that had huge impacts on the atmosphere of early earth, this MBGC can be useful as a biological component to either early earth models or models of other planets that potentially harbor life.

Coupling among Microbial Communities, Biogeochemistry, and Mineralogy across Biogeochemical Facies

DOE Office of Scientific and Technical Information (OSTI.GOV)

Stegen, James C.; Konopka, Allan; McKinely, Jim

Physical properties of sediments are commonly used to define subsurface lithofacies and these same physical properties influence subsurface microbial communities. This suggests an (unexploited) opportunity to use the spatial distribution of facies to predict spatial variation in biogeochemically relevant microbial attributes. Here, we characterize three biogeochemical facies—oxidized, reduced, and transition—within one lithofacies and elucidate relationships among facies features and microbial community biomass, diversity, and community composition. Consistent with previous observations of biogeochemical hotspots at environmental transition zones, we find elevated biomass within a biogeochemical facies that occurred at the transition between oxidized and reduced biogeochemical facies. Microbial diversity—the number ofmore » microbial taxa—was lower within the reduced facies and was well-explained by a combination of pH and mineralogy. Null modeling revealed that microbial community composition was influenced by ecological selection imposed by redox state and mineralogy, possibly due to effects on nutrient availability or transport. As an illustrative case, we predict microbial biomass concentration across a three-dimensional spatial domain by coupling the spatial distribution of subsurface biogeochemical facies with biomass-facies relationships revealed here. We expect that merging such an approach with hydro-biogeochemical models will provide important constraints on simulated dynamics, thereby reducing uncertainty in model predictions.« less

Variable-Internal-Stores models of microbial growth and metabolism with dynamic allocation of cellular resources.

PubMed

Nev, Olga A; van den Berg, Hugo A

2017-01-01

Variable-Internal-Stores models of microbial metabolism and growth have proven to be invaluable in accounting for changes in cellular composition as microbial cells adapt to varying conditions of nutrient availability. Here, such a model is extended with explicit allocation of molecular building blocks among various types of catalytic machinery. Such an extension allows a reconstruction of the regulatory rules employed by the cell as it adapts its physiology to changing environmental conditions. Moreover, the extension proposed here creates a link between classic models of microbial growth and analyses based on detailed transcriptomics and proteomics data sets. We ascertain the compatibility between the extended Variable-Internal-Stores model and the classic models, demonstrate its behaviour by means of simulations, and provide a detailed treatment of the uniqueness and the stability of its equilibrium point as a function of the availabilities of the various nutrients.

Estimating bacterial diversity in Scirtothrips dorsalis Hood (Thysanoptera: Thripidae) via next generation sequencing

USDA-ARS?s Scientific Manuscript database

The last two decades have produced a better understanding of insect-microbial associations and yielded some important opportunities for insect control. However, most of our knowledge comes from model systems. Thrips (Thysanoptera: Thripidae) have been understudied despite their global importance as ...

Changes in the Size of the Active Microbial Pool Explain Short-Term Soil Respiratory Responses to Temperature and Moisture

PubMed Central

Salazar-Villegas, Alejandro; Blagodatskaya, Evgenia; Dukes, Jeffrey S.

2016-01-01

Heterotrophic respiration contributes a substantial fraction of the carbon flux from soil to atmosphere, and responds strongly to environmental conditions. However, the mechanisms through which short-term changes in environmental conditions affect microbial respiration still remain unclear. Microorganisms cope with adverse environmental conditions by transitioning into and out of dormancy, a state in which they minimize rates of metabolism and respiration. These transitions are poorly characterized in soil and are generally omitted from decomposition models. Most current approaches to model microbial control over soil CO2 production relate responses to total microbial biomass (TMB) and do not differentiate between microorganisms in active and dormant physiological states. Indeed, few data for active microbial biomass (AMB) exist with which to compare model output. Here, we tested the hypothesis that differences in soil microbial respiration rates across various environmental conditions are more closely related to differences in AMB (e.g., due to activation of dormant microorganisms) than in TMB. We measured basal respiration (SBR) of soil incubated for a week at two temperatures (24 and 33°C) and two moisture levels (10 and 20% soil dry weight [SDW]), and then determined TMB, AMB, microbial specific growth rate, and the lag time before microbial growth (tlag) using the Substrate-Induced Growth Response (SIGR) method. As expected, SBR was more strongly correlated with AMB than with TMB. This relationship indicated that each g active biomass C contributed ~0.04 g CO2-C h−1 of SBR. TMB responded very little to short-term changes in temperature and soil moisture and did not explain differences in SBR among the treatments. Maximum specific growth rate did not respond to environmental conditions, suggesting that the dominant microbial populations remained similar. However, warmer temperatures and increased soil moisture both reduced tlag, indicating that favorable abiotic conditions activated soil microorganisms. We conclude that soil respiratory responses to short-term changes in environmental conditions are better explained by changes in AMB than in TMB. These results suggest that decomposition models that explicitly represent microbial carbon pools should take into account the active microbial pool, and researchers should be cautious in comparing modeled microbial pool sizes with measurements of TMB. PMID:27148213

Measurements and modeling of surface-atmosphere exchange of microorganisms in Mediterranean grassland

NASA Astrophysics Data System (ADS)

Carotenuto, Federico; Georgiadis, Teodoro; Gioli, Beniamino; Leyronas, Christel; Morris, Cindy E.; Nardino, Marianna; Wohlfahrt, Georg; Miglietta, Franco

2017-12-01

Microbial aerosols (mainly composed of bacterial and fungal cells) may constitute up to 74 % of the total aerosol volume. These biological aerosols are not only relevant to the dispersion of pathogens, but they also have geochemical implications. Some bacteria and fungi may, in fact, serve as cloud condensation or ice nuclei, potentially affecting cloud formation and precipitation and are active at higher temperatures compared to their inorganic counterparts. Simulations of the impact of microbial aerosols on climate are still hindered by the lack of information regarding their emissions from ground sources. This present work tackles this knowledge gap by (i) applying a rigorous micrometeorological approach to the estimation of microbial net fluxes above a Mediterranean grassland and (ii) developing a deterministic model (the PLAnET model) to estimate these emissions on the basis of a few meteorological parameters that are easy to obtain. The grassland is characterized by an abundance of positive net microbial fluxes and the model proves to be a promising tool capable of capturing the day-to-day variability in microbial fluxes with a relatively small bias and sufficient accuracy. PLAnET is still in its infancy and will benefit from future campaigns extending the available training dataset as well as the inclusion of ever more complex and critical phenomena triggering the emission of microbial aerosol (such as rainfall). The model itself is also adaptable as an emission module for dispersion and chemical transport models, allowing further exploration of the impact of land-cover-driven microbial aerosols on the atmosphere and climate.

Mechanistic modeling of microbial interactions at pore to profile scale resolve methane emission dynamics from permafrost soil

NASA Astrophysics Data System (ADS)

Ebrahimi, Ali; Or, Dani

2017-05-01

The sensitivity of polar regions to raising global temperatures is reflected in rapidly changing hydrological processes associated with pronounced seasonal thawing of permafrost soil and increased biological activity. Of particular concern is the potential release of large amounts of soil carbon and stimulation of other soil-borne greenhouse gas emissions such as methane. Soil methanotrophic and methanogenic microbial communities rapidly adjust their activity and spatial organization in response to permafrost thawing and other environmental factors. Soil structural elements such as aggregates and layering affect oxygen and nutrient diffusion processes thereby contributing to methanogenic activity within temporal anoxic niches (hot spots). We developed a mechanistic individual-based model to quantify microbial activity dynamics in soil pore networks considering transport processes and enzymatic activity associated with methane production in soil. The model was upscaled from single aggregates to the soil profile where freezing/thawing provides macroscopic boundary conditions for microbial activity at different soil depths. The model distinguishes microbial activity in aerate bulk soil from aggregates (or submerged profile) for resolving methane production and oxidation rates. Methane transport pathways by diffusion and ebullition of bubbles vary with hydration dynamics. The model links seasonal thermal and hydrologic dynamics with evolution of microbial community composition and function affecting net methane emissions in good agreement with experimental data. The mechanistic model enables systematic evaluation of key controlling factors in thawing permafrost and microbial response (e.g., nutrient availability and enzyme activity) on long-term methane emissions and carbon decomposition rates in the rapidly changing polar regions.

Predicting the response of soil organic matter microbial decomposition to moisture

NASA Astrophysics Data System (ADS)

Chenu, Claire; Garnier, Patricia; Monga, Olivier; Moyano, Fernando; Pot, Valérie; Nunan, Naoise; Coucheney, Elsa; Otten, Wilfred

2014-05-01

Next to temperature, soil moisture is a main driver of soil C and N transformations in soils, because it affects microbial activity and survival. The moisture sensitivity of soil organic matter decay may be a source of uncertainty of similar magnitude to that of the temperature sensitivity and receives much less attention. The basic concepts and mechanisms relating soil water to microorganisms were identified early (i.e. in steady state conditions : direct effects on microbial physiology, diffusion substrates, nutrients, extracellular enzymes, diffusion of oxygen, movement of microorganisms). However, accounting for how moisture controls soil microbial activity remains essentially empirical and poorly accounts for soil characteristics. Soil microorganisms live in a complex 3-D framework of mineral and organic particles defining pores of various sizes, connections with adjacent pores, and with pore walls of contrasted nature, which result in a variety of microhabitats. The water regime to which microorganisms are exposed can be predicted to depend the size and connectivity of pores in which they are located. Furthermore, the spatial distribution of microorganisms as well as that of organic matter is very heterogeneous, determining the diffusion distances between substrates and decomposers. A new generation of pore scale models of C dynamics in soil may challenge the difficulty of modelling such a complex system. These models are based on an explicit representation of soil structure (i.e. soil particles and voids), microorganisms and organic matter localisation. We tested here the ability of such a model to account for changes in microbial respiration with soil moisture. In the model MOSAIC II, soil pore space is described using a sphere network coming from a geometrical modelling algorithm. MicroCT tomography images were used to implement this representation of soil structure. A biological sub-model describes the hydrolysis of insoluble SOM into dissolved organic matter, its assimilation, respiration and microbial mortality. A recent improvement of the model was the description of the diffusion of soluble organic matter. We tested the model using the results from an experiment where a simple substrate (fructose) was decomposed by bacteria within a simple media (sand). Separate incubations in microcosms were carried out using five different bacterial communities at two different moisture conditions corresponding to water potentials of -0.01 and -0.1 bars. We calibrated the biological parameters using the experimental data obtained at high water content and we tested the model without any parameters change at low water content. Both the experiments and simulations showed a decrease in mineralisation with a decrease of water content, of which pattern depended on the bacterial species and its physiological characteristics. The model was able to correctly simulate the decrease of connectivity between substrate and microorganism due the decrease of water content. The potential and required developments of such models in describing how heterotrophic respiration is affected by micro-scale distribution and processes in soils and in testing scenarios regarding water regimes in a changing climate is discussed.

Bioenergy cropping systems that incorporate native grasses stimulate growth of plant-associated soil microbes in the absence of nitrogen fertilization

DOE PAGES

Oates, Lawrence G.; Duncan, David S.; Sanford, Gregg R.; ...

2016-10-03

The choice of crops and their management can strongly influence soil microbial communities and their processes. Here, we used lipid biomarker profiling to characterize how soil microbial composition of five potential bioenergy cropping systems diverged from a common baseline five years after they were established. The cropping systems we studied included an annual system (continuous no-till corn) and four perennial crops (switchgrass, miscanthus, hybrid poplar, and restored prairie). Partial- and no-stover removal were compared for the corn system, while N-additions were compared to unfertilized plots for the perennial cropping systems. Arbuscular mycorrhizal fungi (AMF) and Gram-negative biomass was higher inmore » unfertilized perennial grass systems, especially in switchgrass and prairie. Gram-positive bacterial biomass decreased in all systems relative to baseline values in surface soils (0–10 cm), but not subsurface soils (10–25 cm). Overall microbial composition was similar between the two soil depths. Our findings demonstrate the capacity of unfertilized perennial cropping systems to recreate microbial composition found in undisturbed soil environments and indicate how strongly agroecosystem management decisions such as N addition and plant community composition can influence soil microbial assemblages.« less

Bioenergy cropping systems that incorporate native grasses stimulate growth of plant-associated soil microbes in the absence of nitrogen fertilization

DOE Office of Scientific and Technical Information (OSTI.GOV)

Oates, Lawrence G.; Duncan, David S.; Sanford, Gregg R.

The choice of crops and their management can strongly influence soil microbial communities and their processes. Here, we used lipid biomarker profiling to characterize how soil microbial composition of five potential bioenergy cropping systems diverged from a common baseline five years after they were established. The cropping systems we studied included an annual system (continuous no-till corn) and four perennial crops (switchgrass, miscanthus, hybrid poplar, and restored prairie). Partial- and no-stover removal were compared for the corn system, while N-additions were compared to unfertilized plots for the perennial cropping systems. Arbuscular mycorrhizal fungi (AMF) and Gram-negative biomass was higher inmore » unfertilized perennial grass systems, especially in switchgrass and prairie. Gram-positive bacterial biomass decreased in all systems relative to baseline values in surface soils (0–10 cm), but not subsurface soils (10–25 cm). Overall microbial composition was similar between the two soil depths. Our findings demonstrate the capacity of unfertilized perennial cropping systems to recreate microbial composition found in undisturbed soil environments and indicate how strongly agroecosystem management decisions such as N addition and plant community composition can influence soil microbial assemblages.« less

Long-term effect of rice-based farming systems on soil health.

PubMed

Bihari, Priyanka; Nayak, A K; Gautam, Priyanka; Lal, B; Shahid, M; Raja, R; Tripathi, R; Bhattacharyya, P; Panda, B B; Mohanty, S; Rao, K S

2015-05-01

Integrated rice-fish culture, an age-old farming system, is a technology which could produce rice and fish sustainably at a time by optimizing scarce resource use through complementary use of land and water. An understanding of microbial processes is important for the management of farming systems as soil microbes are the living part of soil organic matter and play critical roles in soil C and N cycling and ecosystem functioning of farming system. Rice-based integrated farming system model for small and marginal farmers was established in 2001 at Central Rice Research Institute, Cuttack, Odisha. The different enterprises of farming system were rice-fish, fish-fingerlings, fruits, vegetables, rice-fish refuge, and agroforestry. This study was conducted with the objective to assess the soil physicochemical properties, microbial population, carbon and nitrogen fractions, soil enzymatic activity, and productivity of different enterprises. The effect of enterprises induced significant changes in the chemical composition and organic matter which in turn influenced the activities of enzymes (urease, acid, and alkaline phosphatase) involved in the C, N, and P cycles. The different enterprises of long-term rice-based farming system caused significant variations in nutrient content of soil, which was higher in rice-fish refuge followed by rice-fish enterprise. Highest microbial populations and enzymatic properties were recorded in rice-fish refuge system because of waterlogging and reduced condition prolonged in this system leading to less decomposition of organic matter. The maximum alkaline phosphatase, urease, and FDA were observed in rice-fish enterprise. However, highest acid phosphatase and dehydrogenase activity were obtained in vegetable enterprise and fish-fingerlings enterprise, respectively.

Constraint Based Modeling Going Multicellular.

PubMed

Martins Conde, Patricia do Rosario; Sauter, Thomas; Pfau, Thomas

2016-01-01

Constraint based modeling has seen applications in many microorganisms. For example, there are now established methods to determine potential genetic modifications and external interventions to increase the efficiency of microbial strains in chemical production pipelines. In addition, multiple models of multicellular organisms have been created including plants and humans. While initially the focus here was on modeling individual cell types of the multicellular organism, this focus recently started to switch. Models of microbial communities, as well as multi-tissue models of higher organisms have been constructed. These models thereby can include different parts of a plant, like root, stem, or different tissue types in the same organ. Such models can elucidate details of the interplay between symbiotic organisms, as well as the concerted efforts of multiple tissues and can be applied to analyse the effects of drugs or mutations on a more systemic level. In this review we give an overview of the recent development of multi-tissue models using constraint based techniques and the methods employed when investigating these models. We further highlight advances in combining constraint based models with dynamic and regulatory information and give an overview of these types of hybrid or multi-level approaches.

Strategies to diagnose and control microbial souring in natural gas storage reservoirs and produced water systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Morris, E.A.; Derr, R.M.; Pope, D.H.

1995-12-31

Hydrogen sulfide production (souring) in natural gas storage reservoirs and produced water systems is a safety and environmental problem that can lead to operational shutdown when local hydrogen sulfide standards are exceeded. Systems affected by microbial souring have historically been treated using biocides that target the general microbial community. However, requirements for more environmentally friendly solutions have led to treatment strategies in which sulfide production can be controlled with minimal impact to the system and environment. Some of these strategies are based on microbial and/or nutritional augmentation of the sour environment. Through research sponsored by the Gas Research Institute (GRI)more » in Chicago, Illinois, methods have been developed for early detection of microbial souring in natural gas storage reservoirs, and a variety of mitigation strategies have been evaluated. The effectiveness of traditional biocide treatment in gas storage reservoirs was shown to depend heavily on the methods by which the chemical is applied. An innovative strategy using nitrate was tested and proved ideal for produced water and wastewater systems. Another strategy using elemental iodine was effective for sulfide control in evaporation ponds and is currently being tested in microbially sour natural gas storage wells.« less

Emergence of heterogeneity and political organization in information exchange networks

NASA Astrophysics Data System (ADS)

Guttenberg, Nicholas; Goldenfeld, Nigel

2010-04-01

We present a simple model of the emergence of the division of labor and the development of a system of resource subsidy from an agent-based model of directed resource production with variable degrees of trust between the agents. The model has three distinct phases corresponding to different forms of societal organization: disconnected (independent agents), homogeneous cooperative (collective state), and inhomogeneous cooperative (collective state with a leader). Our results indicate that such levels of organization arise generically as a collective effect from interacting agent dynamics and may have applications in a variety of systems including social insects and microbial communities.

Emergence of heterogeneity and political organization in information exchange networks.

PubMed

Guttenberg, Nicholas; Goldenfeld, Nigel

2010-04-01

We present a simple model of the emergence of the division of labor and the development of a system of resource subsidy from an agent-based model of directed resource production with variable degrees of trust between the agents. The model has three distinct phases corresponding to different forms of societal organization: disconnected (independent agents), homogeneous cooperative (collective state), and inhomogeneous cooperative (collective state with a leader). Our results indicate that such levels of organization arise generically as a collective effect from interacting agent dynamics and may have applications in a variety of systems including social insects and microbial communities.

One Step Closer to Mars with Aquaponics: Cultivating Citizen Science in K12 Schools

NASA Technical Reports Server (NTRS)

Kolattukudy, Maria; Puranik, Niyati; Sane, Nishant; Bisht, Kritika; Saffat, Nabeeha; Gupta, Anika; McHugh, Anne; Detweiler, Angela; Bebout, Brad; Everroad, R. Craig

2017-01-01

The Microbial Ecology and Biogeochemistry Research Laboratory at NASA Ames Research Center focuses primarily on the nutrient cycling and diversity of complex microbial communities. NASA is interested in the composition and functioning of microbial mat communities as these processes fundamentally shape the form and function of these analogs for the earliest forms of life on Earth (3.6 billion years ago), and likely will on other planets as well. Aquaponics systems are supported by microbial communities who perform many complex ecosystem services, including cycling nitrogen. Microbes are integral to the stability and productivity of aquaponics systems, which are analogous to microbial communities in food production systems that are essential for building efficient life support systems for long-distance space travel. Students at Meadow Park Middle School created 10 parallel aquaponics systems and took temporal microbial samples to characterize whether any macro-ecology variables impacted or changed the microbial diversity of these systems. Students additionally created a website so that other classrooms can pursue similar projects in their own schools (https://go.nasa.gov/2uJhxmF). Our lab at NASA Ames has sequenced water samples from each of the 10 tanks at 3 timepoints using a MinION sequencer. MPMS students will be involved in the analysis of the bioinformatics data generated through this collaboration. Our ongoing collaboration aims to collect and analyze data in the classroom setting that has utility for research scientists, while involving students as collaborators in the research process.

Immune Organs and Haemopoietic System Under Modelling of the Mission Factors

NASA Astrophysics Data System (ADS)

Sapin, M. R.; Grigoriev, A. I.; Erofeeva, L. M.; Grigorenko, D. E.; Fedorenko, B. S.

1997-07-01

Literary and experimental data on the character of changes in immune organs and lymphoid tissue of respiratory system and digestive system in laboratory animals during the mission factors model are given. Inhibition of reproductive function in bone marrow, thymus and spleen under irradiation of gamma-rays and accelerated carbon ions, tensity of immune response in the lymphoid structures of larynx, trachea and bronchi under the influence of acetaldehyde vapors and decrease of lymphoid tissue square on histological series in spleen and small intestine with an increase of concentration of microbial bodies in the drinking water were estimated.

Models of microbiome evolution incorporating host and microbial selection.

PubMed

Zeng, Qinglong; Wu, Steven; Sukumaran, Jeet; Rodrigo, Allen

2017-09-25

Numerous empirical studies suggest that hosts and microbes exert reciprocal selective effects on their ecological partners. Nonetheless, we still lack an explicit framework to model the dynamics of both hosts and microbes under selection. In a previous study, we developed an agent-based forward-time computational framework to simulate the neutral evolution of host-associated microbial communities in a constant-sized, unstructured population of hosts. These neutral models allowed offspring to sample microbes randomly from parents and/or from the environment. Additionally, the environmental pool of available microbes was constituted by fixed and persistent microbial OTUs and by contributions from host individuals in the preceding generation. In this paper, we extend our neutral models to allow selection to operate on both hosts and microbes. We do this by constructing a phenome for each microbial OTU consisting of a sample of traits that influence host and microbial fitnesses independently. Microbial traits can influence the fitness of hosts ("host selection") and the fitness of microbes ("trait-mediated microbial selection"). Additionally, the fitness effects of traits on microbes can be modified by their hosts ("host-mediated microbial selection"). We simulate the effects of these three types of selection, individually or in combination, on microbiome diversities and the fitnesses of hosts and microbes over several thousand generations of hosts. We show that microbiome diversity is strongly influenced by selection acting on microbes. Selection acting on hosts only influences microbiome diversity when there is near-complete direct or indirect parental contribution to the microbiomes of offspring. Unsurprisingly, microbial fitness increases under microbial selection. Interestingly, when host selection operates, host fitness only increases under two conditions: (1) when there is a strong parental contribution to microbial communities or (2) in the absence of a strong parental contribution, when host-mediated selection acts on microbes concomitantly. We present a computational framework that integrates different selective processes acting on the evolution of microbiomes. Our framework demonstrates that selection acting on microbes can have a strong effect on microbial diversities and fitnesses, whereas selection on hosts can have weaker outcomes.

Evaluating the effects of variable water chemistry on bacterial transport during infiltration.

PubMed

Zhang, Haibo; Nordin, Nahjan Amer; Olson, Mira S

2013-07-01

Bacterial infiltration through the subsurface has been studied experimentally under different conditions of interest and is dependent on a variety of physical, chemical and biological factors. However, most bacterial transport studies fail to adequately represent the complex processes occurring in natural systems. Bacteria are frequently detected in stormwater runoff, and may present risk of microbial contamination during stormwater recharge into groundwater. Mixing of stormwater runoff with groundwater during infiltration results in changes in local solution chemistry, which may lead to changes in both bacterial and collector surface properties and subsequent bacterial attachment rates. This study focuses on quantifying changes in bacterial transport behavior under variable solution chemistry, and on comparing the influences of chemical variability and physical variability on bacterial attachment rates. Bacterial attachment rate at the soil-water interface was predicted analytically using a combined rate equation, which varies temporally and spatially with respect to changes in solution chemistry. Two-phase Monte Carlo analysis was conducted and an overall input-output correlation coefficient was calculated to quantitatively describe the importance of physiochemical variation on the estimates of attachment rate. Among physical variables, soil particle size has the highest correlation coefficient, followed by porosity of the soil media, bacterial size and flow velocity. Among chemical variables, ionic strength has the highest correlation coefficient. A semi-reactive microbial transport model was developed within HP1 (HYDRUS1D-PHREEQC) and applied to column transport experiments with constant and variable solution chemistries. Bacterial attachment rates varied from 9.10×10(-3)min(-1) to 3.71×10(-3)min(-1) due to mixing of synthetic stormwater (SSW) with artificial groundwater (AGW), while bacterial attachment remained constant at 9.10×10(-3)min(-1) in a constant solution chemistry (AGW only). The model matched observed bacterial breakthrough curves well. Although limitations exist in the application of a semi-reactive microbial transport model, this method represents one step towards a more realistic model of bacterial transport in complex microbial-water-soil systems. Copyright © 2013 Elsevier B.V. All rights reserved.

Measuring and modeling C flux rates through the central metabolic pathways in microbial communities using position-specific 13C-labeled tracers

NASA Astrophysics Data System (ADS)

Dijkstra, P.; van Groenigen, K.; Hagerty, S.; Salpas, E.; Fairbanks, D. E.; Hungate, B. A.; KOCH, G. W.; Schwartz, E.

2012-12-01

The production of energy and metabolic precursors occurs in well-known processes such as glycolysis and Krebs cycle. We use position-specific 13C-labeled metabolic tracers, combined with models of microbial metabolic organization, to analyze the response of microbial community energy production, biosynthesis, and C use efficiency (CUE) in soils, decomposing litter, and aquatic communities. The method consists of adding position-specific 13C -labeled metabolic tracers to parallel soil incubations, in this case 1-13C and 2,3-13C pyruvate and 1-13C and U-13C glucose. The measurement of CO2 released from the labeled tracers is used to calculate the C flux rates through the various metabolic pathways. A simplified metabolic model consisting of 23 reactions is solved using results of the metabolic tracer experiments and assumptions of microbial precursor demand. This new method enables direct estimation of fundamental aspects of microbial energy production, CUE, and soil organic matter formation in relatively undisturbed microbial communities. We will present results showing the range of metabolic patterns observed in these communities and discuss results from testing metabolic models.

Strategies to Optimize Microbially-Mediated Mitigation of Greenhouse Gas Emissions from Landfill Cover Soils

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jeremy Semrau; Sung-Woo Lee; Jeongdae Im

2010-09-30

The overall objective of this project, 'Strategies to Optimize Microbially-Mediated Mitigation of Greenhouse Gas Emissions from Landfill Cover Soils' was to develop effective, efficient, and economic methodologies by which microbial production of nitrous oxide can be minimized while also maximizing microbial consumption of methane in landfill cover soils. A combination of laboratory and field site experiments found that the addition of nitrogen and phenylacetylene stimulated in situ methane oxidation while minimizing nitrous oxide production. Molecular analyses also indicated that methane-oxidizing bacteria may play a significant role in not only removing methane, but in nitrous oxide production as well, although themore » contribution of ammonia-oxidizing archaea to nitrous oxide production can not be excluded at this time. Future efforts to control both methane and nitrous oxide emissions from landfills as well as from other environments (e.g., agricultural soils) should consider these issues. Finally, a methanotrophic biofiltration system was designed and modeled for the promotion of methanotrophic activity in local methane 'hotspots' such as landfills. Model results as well as economic analyses of these biofilters indicate that the use of methanotrophic biofilters for controlling methane emissions is technically feasible, and provided either the costs of biofilter construction and operation are reduced or the value of CO{sub 2} credits is increased, can also be economically attractive.« less

Evaluation of a Microbial Sensor as a Tool for Antimicrobial Activity Test of Cosmetic Preservatives.

PubMed

Gomyo, Hideyuki; Ookawa, Masaki; Oshibuchi, Kota; Sugamura, Yuriko; Hosokawa, Masahito; Shionoiri, Nozomi; Maeda, Yoshiaki; Matsunaga, Tadashi; Tanaka, Tsuyoshi

2015-01-01

For high-throughput screening of novel cosmetic preservatives, a rapid and simple assay to evaluate the antimicrobial activities should be developed because the conventional agar dilution method is time-consuming and labor-intensive. To address this issue, we evaluated a microbial sensor as a tool for rapid antimicrobial activity testing. The sensor consists of an oxygen electrode and a filter membrane that holds the test microorganisms, Staphylococcus aureus and Candida albicans. The antimicrobial activity of the tested cosmetic preservative was evaluated by measuring the current increases corresponding to the decreases in oxygen consumption in the microbial respiration. The current increases detected by the sensor showed positive correlation to the concentrations of two commercially used preservatives, chlorphenesin and 2-phenoxyethanol. The same tendency was also observed when a model cosmetic product was used as a preservative solvent, indicating the feasibility in practical use. Furthermore, the microbial sensor and microfluidic flow-cell was assembled to achieve sequential measurements. The sensor system presented in this study could be useful in large-scale screening experiments.

Characterization of mediators of microbial virulence and innate immunity using the Caenorhabditis elegans host-pathogen model.

PubMed

Alegado, Rosanna A; Campbell, Marianne C; Chen, Will C; Slutz, Sandra S; Tan, Man-Wah

2003-07-01

The soil-borne nematode, Caenorhabditis elegans, is emerging as a versatile model in which to study host-pathogen interactions. The worm model has shown to be particularly effective in elucidating both microbial and animal genes involved in toxin-mediated killing. In addition, recent work on worm infection by a variety of bacterial pathogens has shown that a number of virulence regulatory genes mediate worm susceptibility. Many of these regulatory genes, including the PhoP/Q two-component regulators in Salmonella and LasR in Pseudomonas aeruginosa, have also been implicated in mammalian models suggesting that findings in the worm model will be relevant to other systems. In keeping with this concept, experiments aimed at identifying host innate immunity genes have also implicated pathways that have been suggested to play a role in plants and animals, such as the p38 MAP kinase pathway. Despite rapid forward progress using this model, much work remains to be done including the design of more sensitive methods to find effector molecules and further characterization of the exact interaction between invading pathogens and C. elegans' cellular components.

Modeling microbial diversity in anaerobic digestion through an extended ADM1 model.

PubMed

Ramirez, Ivan; Volcke, Eveline I P; Rajinikanth, Rajagopal; Steyer, Jean-Philippe

2009-06-01

The anaerobic digestion process comprises a whole network of sequential and parallel reactions, of both biochemical and physicochemical nature. Mathematical models, aiming at understanding and optimization of the anaerobic digestion process, describe these reactions in a structured way, the IWA Anaerobic Digestion Model No. 1 (ADM1) being the most well established example. While these models distinguish between different microorganisms involved in different reactions, to our knowledge they all neglect species diversity between organisms with the same function, i.e. performing the same reaction. Nevertheless, available experimental evidence suggests that the structure and properties of a microbial community may be influenced by process operation and on their turn also determine the reactor functioning. In order to adequately describe these phenomena, mathematical models need to consider the underlying microbial diversity. This is demonstrated in this contribution by extending the ADM1 to describe microbial diversity between organisms of the same functional group. The resulting model has been compared with the traditional ADM1 in describing experimental data of a pilot-scale hybrid Upflow Anaerobic Sludge Filter Bed (UASFB) reactor, as well as in a more detailed simulation study. The presented model is further shown useful in assessing the relationship between reactor performance and microbial community structure in mesophilic CSTRs seeded with slaughterhouse wastewater when facing increasing levels of ammonia.