How Far Is "Near"? Inferring Distance from Spatial Descriptions

ERIC Educational Resources Information Center

Carlson, Laura A.; Covey, Eric S.

2005-01-01

A word may mean different things in different contexts. The current study explored the changing denotations of spatial terms, focusing on how the distance inferred from a spatial description varied as a function of the size of the objects being spatially related. We examined both terms that explicitly convey distance (i.e., topological terms such…

The Role of Ventromedial Prefrontal Cortex in Text Comprehension Inferences: Semantic Coherence or Socio-Emotional Perspective?

PubMed Central

Burin, Debora I.; Acion, Laura; Kurczek, Jake; Duff, Melissa C.; Tranel, Daniel; Jorge, Ricardo E.

2015-01-01

Two hypotheses about the role of the ventromedial prefrontal cortex (vmPFC) in narrative comprehension inferences, global semantic coherence versus socio-emotional perspective, were tested. Seven patients with vmPFC lesions and seven demographically matched healthy comparison participants read short narratives. Using the consistency paradigm, narratives required participants to make either an emotional or visuo-spatial inference, in which a target sentence provided consistent or inconsistent information with a previous emotional state of a character or a visuo-spatial location of an object. Healthy comparison participants made the inferences both for spatial and emotional stories, as shown by longer reading times for inconsistent critical sentences. For patients with vmPFC lesions, inconsistent sentences were read slower in the spatial stories, but not in the emotional ones. This pattern of results is compatible with the hypothesis that vmPFC contributes to narrative comprehension by supporting inferences about socio-emotional aspects of verbally described situations. PMID:24561428

Temporal and Spatial Dynamics of Sediment Anaerobic Ammonium Oxidation (Anammox) Bacteria in Freshwater Lakes.

PubMed

Yang, Yuyin; Dai, Yu; Li, Ningning; Li, Bingxin; Xie, Shuguang; Liu, Yong

2017-02-01

Anaerobic ammonium-oxidizing (anammox) process can play an important role in freshwater nitrogen cycle. However, the distribution of anammox bacteria in freshwater lake and the associated environmental factors remain essentially unclear. The present study investigated the temporal and spatial dynamics of sediment anammox bacterial populations in eutrotrophic Dianchi Lake and mesotrophic Erhai Lake on the Yunnan Plateau (southwestern China). The remarkable spatial change of anammox bacterial abundance was found in Dianchi Lake, while the relatively slight spatial shift occurred in Erhai Lake. Dianchi Lake had greater anammox bacterial abundance than Erhai Lake. In both Dianchi Lake and Erhai Lake, anammox bacteria were much more abundant in summer than in spring. Anammox bacterial community richness, diversity, and structure in these two freshwater lakes were subjected to temporal and spatial variations. Sediment anammox bacterial communities in Dianchi Lake and Erhai Lake were dominated by Candidatus Brocadia and a novel phylotype followed by Candidatus Kuenenia; however, these two lakes had distinct anammox bacterial community structure. In addition, trophic status determined sediment anammox bacterial community structure.

Streptococcus massiliensis in the human mouth: a phylogenetic approach for the inference of bacterial habitats.

PubMed

Póntigo, F; Silva, C; Moraga, M; Flores, S V

2015-12-29

Streptococcus is a diverse bacterial lineage. Species of this genus occupy a myriad of environments inside humans and other animals. Despite the elucidation of several of these habitats, many remain to be identified. Here, we explore a methodological approach to reveal unknown bacterial environments. Specifically, we inferred the phylogeny of the Mitis group by analyzing the sequences of eight genes. In addition, information regarding habitat use of species belonging to this group was obtained from the scientific literature. The oral cavity emerged as a potential, previously unknown, environment of Streptococcus massiliensis. This phylogeny-based prediction was confirmed by species-specific polymerase chain reaction (PCR) amplification. We propose employing a similar approach, i.e., use of bibliographic data and molecular phylogenetics as predictive methods, and species-specific PCR as confirmation, in order to reveal other unknown habitats in further bacterial taxa.

Evolution of prokaryote and eukaryote lines inferred from sequence evidence

NASA Technical Reports Server (NTRS)

Hunt, L. T.; George, D. G.; Yeh, L.-S.; Dayhoff, M. O.

1984-01-01

This paper describes the evolution of prokaryotes and early eukaryotes, including their symbiotic relationships, as inferred from phylogenetic trees of bacterial ferredoxin, 5S ribosomal RNA, ribulose-1,5-biphosphate carboxylase large chain, and mitochondrial cytochrome oxidase polypeptide II.

Functional Resistance to Recurrent Spatially Heterogeneous Disturbances Is Facilitated by Increased Activity of Surviving Bacteria in a Virtual Ecosystem

PubMed Central

König, Sara; Worrich, Anja; Banitz, Thomas; Harms, Hauke; Kästner, Matthias; Miltner, Anja; Wick, Lukas Y.; Frank, Karin; Thullner, Martin; Centler, Florian

2018-01-01

Bacterial degradation of organic compounds is an important ecosystem function with relevance to, e.g., the cycling of elements or the degradation of organic contaminants. It remains an open question, however, to which extent ecosystems are able to maintain such biodegradation function under recurrent disturbances (functional resistance) and how this is related to the bacterial biomass abundance. In this paper, we use a numerical simulation approach to systematically analyze the dynamic response of a microbial population to recurrent disturbances of different spatial distribution. The spatially explicit model considers microbial degradation, growth, dispersal, and spatial networks that facilitate bacterial dispersal mimicking effects of mycelial networks in nature. We find: (i) There is a certain capacity for high resistance of biodegradation performance to recurrent disturbances. (ii) If this resistance capacity is exceeded, spatial zones of different biodegradation performance develop, ranging from no or reduced to even increased performance. (iii) Bacterial biomass and biodegradation dynamics respond inversely to the spatial fragmentation of disturbances: overall biodegradation performance improves with increasing fragmentation, but bacterial biomass declines. (iv) Bacterial dispersal networks can enhance functional resistance against recurrent disturbances, mainly by reactivating zones in the core of disturbed areas, even though this leads to an overall reduction of bacterial biomass. PMID:29696013

Novel probabilistic models of spatial genetic ancestry with applications to stratification correction in genome-wide association studies.

PubMed

Bhaskar, Anand; Javanmard, Adel; Courtade, Thomas A; Tse, David

2017-03-15

Genetic variation in human populations is influenced by geographic ancestry due to spatial locality in historical mating and migration patterns. Spatial population structure in genetic datasets has been traditionally analyzed using either model-free algorithms, such as principal components analysis (PCA) and multidimensional scaling, or using explicit spatial probabilistic models of allele frequency evolution. We develop a general probabilistic model and an associated inference algorithm that unify the model-based and data-driven approaches to visualizing and inferring population structure. Our spatial inference algorithm can also be effectively applied to the problem of population stratification in genome-wide association studies (GWAS), where hidden population structure can create fictitious associations when population ancestry is correlated with both the genotype and the trait. Our algorithm Geographic Ancestry Positioning (GAP) relates local genetic distances between samples to their spatial distances, and can be used for visually discerning population structure as well as accurately inferring the spatial origin of individuals on a two-dimensional continuum. On both simulated and several real datasets from diverse human populations, GAP exhibits substantially lower error in reconstructing spatial ancestry coordinates compared to PCA. We also develop an association test that uses the ancestry coordinates inferred by GAP to accurately account for ancestry-induced correlations in GWAS. Based on simulations and analysis of a dataset of 10 metabolic traits measured in a Northern Finland cohort, which is known to exhibit significant population structure, we find that our method has superior power to current approaches. Our software is available at https://github.com/anand-bhaskar/gap . abhaskar@stanford.edu or ajavanma@usc.edu. Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Demographic inference under the coalescent in a spatial continuum.

PubMed

Guindon, Stéphane; Guo, Hongbin; Welch, David

2016-10-01

Understanding population dynamics from the analysis of molecular and spatial data requires sound statistical modeling. Current approaches assume that populations are naturally partitioned into discrete demes, thereby failing to be relevant in cases where individuals are scattered on a spatial continuum. Other models predict the formation of increasingly tight clusters of individuals in space, which, again, conflicts with biological evidence. Building on recent theoretical work, we introduce a new genealogy-based inference framework that alleviates these issues. This approach effectively implements a stochastic model in which the distribution of individuals is homogeneous and stationary, thereby providing a relevant null model for the fluctuation of genetic diversity in time and space. Importantly, the spatial density of individuals in a population and their range of dispersal during the course of evolution are two parameters that can be inferred separately with this method. The validity of the new inference framework is confirmed with extensive simulations and the analysis of influenza sequences collected over five seasons in the USA. Copyright © 2016 Elsevier Inc. All rights reserved.

Sensitivity to the Sampling Process Emerges From the Principle of Efficiency.

PubMed

Jara-Ettinger, Julian; Sun, Felix; Schulz, Laura; Tenenbaum, Joshua B

2018-05-01

Humans can seamlessly infer other people's preferences, based on what they do. Broadly, two types of accounts have been proposed to explain different aspects of this ability. The first account focuses on spatial information: Agents' efficient navigation in space reveals what they like. The second account focuses on statistical information: Uncommon choices reveal stronger preferences. Together, these two lines of research suggest that we have two distinct capacities for inferring preferences. Here we propose that this is not the case, and that spatial-based and statistical-based preference inferences can be explained by the assumption that agents are efficient alone. We show that people's sensitivity to spatial and statistical information when they infer preferences is best predicted by a computational model of the principle of efficiency, and that this model outperforms dual-system models, even when the latter are fit to participant judgments. Our results suggest that, as adults, a unified understanding of agency under the principle of efficiency underlies our ability to infer preferences. Copyright © 2018 Cognitive Science Society, Inc.

Spatial Inference for Distributed Remote Sensing Data

NASA Astrophysics Data System (ADS)

Braverman, A. J.; Katzfuss, M.; Nguyen, H.

2014-12-01

Remote sensing data are inherently spatial, and a substantial portion of their value for scientific analyses derives from the information they can provide about spatially dependent processes. Geophysical variables such as atmopsheric temperature, cloud properties, humidity, aerosols and carbon dioxide all exhibit spatial patterns, and satellite observations can help us learn about the physical mechanisms driving them. However, remote sensing observations are often noisy and incomplete, so inferring properties of true geophysical fields from them requires some care. These data can also be massive, which is both a blessing and a curse: using more data drives uncertainties down, but also drives costs up, particularly when data are stored on different computers or in different physical locations. In this talk I will discuss a methodology for spatial inference on massive, distributed data sets that does not require moving large volumes of data. The idea is based on a combination of ideas including modeling spatial covariance structures with low-rank covariance matrices, and distributed estimation in sensor or wireless networks.

Spatial variation in the bacterial and denitrifying bacterial community in a biofilter treating subsurface agricultural drainage.

PubMed

Andrus, J Malia; Porter, Matthew D; Rodríguez, Luis F; Kuehlhorn, Timothy; Cooke, Richard A C; Zhang, Yuanhui; Kent, Angela D; Zilles, Julie L

2014-02-01

Denitrifying biofilters can remove agricultural nitrates from subsurface drainage, reducing nitrate pollution that contributes to coastal hypoxic zones. The performance and reliability of natural and engineered systems dependent upon microbially mediated processes, such as the denitrifying biofilters, can be affected by the spatial structure of their microbial communities. Furthermore, our understanding of the relationship between microbial community composition and function is influenced by the spatial distribution of samples.In this study we characterized the spatial structure of bacterial communities in a denitrifying biofilter in central Illinois. Bacterial communities were assessed using automated ribosomal intergenic spacer analysis for bacteria and terminal restriction fragment length polymorphism of nosZ for denitrifying bacteria.Non-metric multidimensional scaling and analysis of similarity (ANOSIM) analyses indicated that bacteria showed statistically significant spatial structure by depth and transect,while denitrifying bacteria did not exhibit significant spatial structure. For determination of spatial patterns, we developed a package of automated functions for the R statistical environment that allows directional analysis of microbial community composition data using either ANOSIM or Mantel statistics.Applying this package to the biofilter data, the flow path correlation range for the bacterial community was 6.4 m at the shallower, periodically in undated depth and 10.7 m at the deeper, continually submerged depth. These spatial structures suggest a strong influence of hydrology on the microbial community composition in these denitrifying biofilters. Understanding such spatial structure can also guide optimal sample collection strategies for microbial community analyses.

Map LineUps: Effects of spatial structure on graphical inference.

PubMed

Beecham, Roger; Dykes, Jason; Meulemans, Wouter; Slingsby, Aidan; Turkay, Cagatay; Wood, Jo

2017-01-01

Fundamental to the effective use of visualization as an analytic and descriptive tool is the assurance that presenting data visually provides the capability of making inferences from what we see. This paper explores two related approaches to quantifying the confidence we may have in making visual inferences from mapped geospatial data. We adapt Wickham et al.'s 'Visual Line-up' method as a direct analogy with Null Hypothesis Significance Testing (NHST) and propose a new approach for generating more credible spatial null hypotheses. Rather than using as a spatial null hypothesis the unrealistic assumption of complete spatial randomness, we propose spatially autocorrelated simulations as alternative nulls. We conduct a set of crowdsourced experiments (n=361) to determine the just noticeable difference (JND) between pairs of choropleth maps of geographic units controlling for spatial autocorrelation (Moran's I statistic) and geometric configuration (variance in spatial unit area). Results indicate that people's abilities to perceive differences in spatial autocorrelation vary with baseline autocorrelation structure and the geometric configuration of geographic units. These results allow us, for the first time, to construct a visual equivalent of statistical power for geospatial data. Our JND results add to those provided in recent years by Klippel et al. (2011), Harrison et al. (2014) and Kay & Heer (2015) for correlation visualization. Importantly, they provide an empirical basis for an improved construction of visual line-ups for maps and the development of theory to inform geospatial tests of graphical inference.

Inferring the palaeoenvironment of ancient bacteria on the basis of resurrected proteins

NASA Technical Reports Server (NTRS)

Gaucher, Eric A.; Thomson, J. Michael; Burgan, Michelle F.; Benner, Steven A.

2003-01-01

Features of the physical environment surrounding an ancestral organism can be inferred by reconstructing sequences of ancient proteins made by those organisms, resurrecting these proteins in the laboratory, and measuring their properties. Here, we resurrect candidate sequences for elongation factors of the Tu family (EF-Tu) found at ancient nodes in the bacterial evolutionary tree, and measure their activities as a function of temperature. The ancient EF-Tu proteins have temperature optima of 55-65 degrees C. This value seems to be robust with respect to uncertainties in the ancestral reconstruction. This suggests that the ancient bacteria that hosted these particular genes were thermophiles, and neither hyperthermophiles nor mesophiles. This conclusion can be compared and contrasted with inferences drawn from an analysis of the lengths of branches in trees joining proteins from contemporary bacteria, the distribution of thermophily in derived bacterial lineages, the inferred G + C content of ancient ribosomal RNA, and the geological record combined with assumptions concerning molecular clocks. The study illustrates the use of experimental palaeobiochemistry and assumptions about deep phylogenetic relationships between bacteria to explore the character of ancient life.

The impact of natural transformation on adaptation in spatially structured bacterial populations.

PubMed

Moradigaravand, Danesh; Engelstädter, Jan

2014-06-20

Recent studies have demonstrated that natural transformation and the formation of highly structured populations in bacteria are interconnected. In spite of growing evidence about this connection, little is known about the dynamics of natural transformation in spatially structured bacterial populations. In this work, we model the interdependency between the dynamics of the bacterial gene pool and those of environmental DNA in space to dissect the effect of transformation on adaptation. Our model reveals that even with only a single locus under consideration, transformation with a free DNA fragment pool results in complex adaptation dynamics that do not emerge in previous models focusing only on the gene shuffling effect of transformation at multiple loci. We demonstrate how spatial restriction on population growth and DNA diffusion in the environment affect the impact of transformation on adaptation. We found that in structured bacterial populations intermediate DNA diffusion rates predominantly cause transformation to impede adaptation by spreading deleterious alleles in the population. Overall, our model highlights distinctive evolutionary consequences of bacterial transformation in spatially restricted compared to planktonic bacterial populations.

It's About Time: A Critique of Macroecological Inferences Concerning Plant Competition.

PubMed

Damgaard, Christian; Weiner, Jacob

2017-02-01

Several macroecological studies have used static spatial data to evaluate plant competition in natural ecosystems and to investigate its role in plant community dynamics and species assembly. The assumptions on which the inferences are based have not been consistent with ecological knowledge. Inferences about processes, such as competition, from static data are weak. Macroecology will benefit more from dynamic data, even if limited, than from increasingly sophisticated analyses of static spatial patterns. Copyright © 2016 Elsevier Ltd. All rights reserved.

Spatial distribution of planktonic bacterial and archaeal communities in the upper section of the tidal reach in Yangtze River

PubMed Central

Fan, Limin; Song, Chao; Meng, Shunlong; Qiu, Liping; Zheng, Yao; Wu, Wei; Qu, Jianhong; Li, Dandan; Zhang, Cong; Hu, Gengdong; Chen, Jiazhang

2016-01-01

Bacterioplankton and archaeaplankton communities play key roles in the biogeochemical processes of water, and they may be affected by many factors. In this study, we used high-throughput 16S rRNA gene sequencing to profile planktonic bacterial and archaeal community compositions in the upper section of the tidal reach in Yangtze River. We found that the predominant bacterial phyla in this river section were Proteobacteria, Firmicutes, and Actinobacteria, whereas the predominant archaeal classes were Halobacteria, Methanomicrobia, and unclassified Euryarchaeota. Additionally, the bacterial and archaeal community compositions, richnesses, functional profiles, and ordinations were affected by the spatial heterogeneity related to the concentration changes of sulphate or nitrate. Notably, the bacterial community was more sensitive than the archaeal community to changes in the spatial characteristics of this river section. These findings provide important insights into the distributions of bacterial and archaeal communities in natural water habitats. PMID:27966673

Spatial distribution of planktonic bacterial and archaeal communities in the upper section of the tidal reach in Yangtze River

NASA Astrophysics Data System (ADS)

Fan, Limin; Song, Chao; Meng, Shunlong; Qiu, Liping; Zheng, Yao; Wu, Wei; Qu, Jianhong; Li, Dandan; Zhang, Cong; Hu, Gengdong; Chen, Jiazhang

2016-12-01

Bacterioplankton and archaeaplankton communities play key roles in the biogeochemical processes of water, and they may be affected by many factors. In this study, we used high-throughput 16S rRNA gene sequencing to profile planktonic bacterial and archaeal community compositions in the upper section of the tidal reach in Yangtze River. We found that the predominant bacterial phyla in this river section were Proteobacteria, Firmicutes, and Actinobacteria, whereas the predominant archaeal classes were Halobacteria, Methanomicrobia, and unclassified Euryarchaeota. Additionally, the bacterial and archaeal community compositions, richnesses, functional profiles, and ordinations were affected by the spatial heterogeneity related to the concentration changes of sulphate or nitrate. Notably, the bacterial community was more sensitive than the archaeal community to changes in the spatial characteristics of this river section. These findings provide important insights into the distributions of bacterial and archaeal communities in natural water habitats.

Spatially explicit inference for open populations: estimating demographic parameters from camera-trap studies

USGS Publications Warehouse

Gardner, Beth; Reppucci, Juan; Lucherini, Mauro; Royle, J. Andrew

2010-01-01

We develop a hierarchical capture–recapture model for demographically open populations when auxiliary spatial information about location of capture is obtained. Such spatial capture–recapture data arise from studies based on camera trapping, DNA sampling, and other situations in which a spatial array of devices records encounters of unique individuals. We integrate an individual-based formulation of a Jolly-Seber type model with recently developed spatially explicit capture–recapture models to estimate density and demographic parameters for survival and recruitment. We adopt a Bayesian framework for inference under this model using the method of data augmentation which is implemented in the software program WinBUGS. The model was motivated by a camera trapping study of Pampas cats Leopardus colocolo from Argentina, which we present as an illustration of the model in this paper. We provide estimates of density and the first quantitative assessment of vital rates for the Pampas cat in the High Andes. The precision of these estimates is poor due likely to the sparse data set. Unlike conventional inference methods which usually rely on asymptotic arguments, Bayesian inferences are valid in arbitrary sample sizes, and thus the method is ideal for the study of rare or endangered species for which small data sets are typical.

Spatially explicit inference for open populations: estimating demographic parameters from camera-trap studies.

PubMed

Gardner, Beth; Reppucci, Juan; Lucherini, Mauro; Royle, J Andrew

2010-11-01

We develop a hierarchical capture-recapture model for demographically open populations when auxiliary spatial information about location of capture is obtained. Such spatial capture-recapture data arise from studies based on camera trapping, DNA sampling, and other situations in which a spatial array of devices records encounters of unique individuals. We integrate an individual-based formulation of a Jolly-Seber type model with recently developed spatially explicit capture-recapture models to estimate density and demographic parameters for survival and recruitment. We adopt a Bayesian framework for inference under this model using the method of data augmentation which is implemented in the software program WinBUGS. The model was motivated by a camera trapping study of Pampas cats Leopardus colocolo from Argentina, which we present as an illustration of the model in this paper. We provide estimates of density and the first quantitative assessment of vital rates for the Pampas cat in the High Andes. The precision of these estimates is poor due likely to the sparse data set. Unlike conventional inference methods which usually rely on asymptotic arguments, Bayesian inferences are valid in arbitrary sample sizes, and thus the method is ideal for the study of rare or endangered species for which small data sets are typical.

Spatial distribution of bacterial communities and related biochemical properties in Luzhou-flavor liquor-fermented grains.

PubMed

Zheng, Jia; Wu, Chongde; Huang, Jun; Zhou, Rongqing; Liao, Xuepin

2014-12-01

Grain fermenting with separate layers in a fermentation pit is the typical and experiential brewing technology for Chinese Luzhou-flavor liquor. However, it is still unclear to what extent the bacterial communities in the different layers of fermented grains (FG) effects the liquor's quality. In this study, the spatial distributions of bacterial communities in Luzhou-flavor liquor FG (top, middle, and bottom layers) from 2 distinctive factories (Jiannanchun and Fenggu) were investigated using culture-independent approaches (phospholipid fatty acid [PLFA] and polymerase chain reaction-denaturing gel electrophoresis [DGGE]). The relationship between bacterial community and biochemical properties was also assessed by Canonical correspondence analysis (CCA). No significant variation in moisture was observed in spatial samples, and the highest content of acidity and total ester was detected in the bottom layer (P < 0.05). A high level of ethanol was observed in the top and middle layers of Fenggu and Jiannanchun, respectively. Significant spatial distribution of the total PLFA was only shown in the 50-y-old pits (P < 0.05), and Gram negative bacteria was the prominent community. Bacterial 16S rDNA DGGE analysis revealed that the most abundant bacterial community was in the top layers of the FG both from Fenggu and Jiannanchun, with Lactobacillaceae accounting for 30% of the total DGGE bands and Lactobacillus acetotolerans was the dominant species. FG samples from the same pit had a highly similar bacterial community structure according to the hierarchal cluster tree. CCA suggested that the moisture, acidity, ethanol, and reducing sugar were the main factors affecting the distribution of L. acetotolerans. Our results will facilitate the knowledge about the spatial distribution of bacterial communities and the relationship with their living environment. © 2014 Institute of Food Technologists®

Temporal and Spatial Diversity of Bacterial Communities in Coastal Waters of the South China Sea

PubMed Central

Du, Jikun; Xiao, Kai; Li, Li; Ding, Xian; Liu, Helu; Lu, Yongjun; Zhou, Shining

2013-01-01

Bacteria are recognized as important drivers of biogeochemical processes in all aquatic ecosystems. Temporal and geographical patterns in ocean bacterial communities have been observed in many studies, but the temporal and spatial patterns in the bacterial communities from the South China Sea remained unexplored. To determine the spatiotemporal patterns, we generated 16S rRNA datasets for 15 samples collected from the five regularly distributed sites of the South China Sea in three seasons (spring, summer, winter). A total of 491 representative sequences were analyzed by MOTHUR, yielding 282 operational taxonomic units (OTUs) grouped at 97% stringency. Significant temporal variations of bacterial diversity were observed. Richness and diversity indices indicated that summer samples were the most diverse. The main bacterial group in spring and summer samples was Alphaproteobacteria, followed by Cyanobacteria and Gammaproteobacteria, whereas Cyanobacteria dominated the winter samples. Spatial patterns in the samples were observed that samples collected from the coastal (D151, D221) waters and offshore (D157, D1512, D224) waters clustered separately, the coastal samples harbored more diverse bacterial communities. However, the temporal pattern of the coastal site D151 was contrary to that of the coastal site D221. The LIBSHUFF statistics revealed noticeable differences among the spring, summer and winter libraries collected at five sites. The UPGMA tree showed there were temporal and spatial heterogeneity of bacterial community composition in coastal waters of the South China Sea. The water salinity (P=0.001) contributed significantly to the bacteria-environment relationship. Our results revealed that bacterial community structures were influenced by environmental factors and community-level changes in 16S-based diversity were better explained by spatial patterns than by temporal patterns. PMID:23785512

Contrasting spatial patterns and ecological attributes of soil bacterial and archaeal taxa across a landscape

PubMed Central

Constancias, Florentin; Saby, Nicolas P A; Terrat, Sébastien; Dequiedt, Samuel; Horrigue, Wallid; Nowak, Virginie; Guillemin, Jean-Philippe; Biju-Duval, Luc; Chemidlin Prévost-Bouré, Nicolas; Ranjard, Lionel

2015-01-01

Even though recent studies have clarified the influence and hierarchy of environmental filters on bacterial community structure, those constraining bacterial populations variations remain unclear. In consequence, our ability to understand to ecological attributes of soil bacteria and to predict microbial community response to environmental stress is therefore limited. Here, we characterized the bacterial community composition and the various bacterial taxonomic groups constituting the community across an agricultural landscape of 12 km2, by using a 215 × 215 m systematic grid representing 278 sites to precisely decipher their spatial distribution and drivers at this scale. The bacterial and Archaeal community composition was characterized by applying 16S rRNA gene pyrosequencing directly to soil DNA from samples. Geostatistics tools were used to reveal the heterogeneous distribution of bacterial composition at this scale. Soil physical parameters and land management explained a significant amount of variation, suggesting that environmental selection is the major process shaping bacterial composition. All taxa systematically displayed also a heterogeneous and particular distribution patterns. Different relative influences of soil characteristics, land use and space were observed, depending on the taxa, implying that selection and spatial processes might be differentially but not exclusively involved for each bacterial phylum. Soil pH was a major factor determining the distribution of most of the bacterial taxa and especially the most important factor explaining the spatial patterns of α-Proteobacteria and Planctomycetes. Soil texture, organic carbon content and quality were more specific to a few number of taxa (e.g., β-Proteobacteria and Chlorobi). Land management also influenced the distribution of bacterial taxa across the landscape and revealed different type of response to cropping intensity (positive, negative, neutral or hump-backed relationships) according to phyla. Altogether, this study provided valuable clues about the ecological behavior of soil bacterial and archaeal taxa at an agricultural landscape scale and could be useful for developing sustainable strategies of land management. PMID:25922908

A new normalizing algorithm for BAC CGH arrays with quality control metrics.

PubMed

Miecznikowski, Jeffrey C; Gaile, Daniel P; Liu, Song; Shepherd, Lori; Nowak, Norma

2011-01-01

The main focus in pin-tip (or print-tip) microarray analysis is determining which probes, genes, or oligonucleotides are differentially expressed. Specifically in array comparative genomic hybridization (aCGH) experiments, researchers search for chromosomal imbalances in the genome. To model this data, scientists apply statistical methods to the structure of the experiment and assume that the data consist of the signal plus random noise. In this paper we propose "SmoothArray", a new method to preprocess comparative genomic hybridization (CGH) bacterial artificial chromosome (BAC) arrays and we show the effects on a cancer dataset. As part of our R software package "aCGHplus," this freely available algorithm removes the variation due to the intensity effects, pin/print-tip, the spatial location on the microarray chip, and the relative location from the well plate. removal of this variation improves the downstream analysis and subsequent inferences made on the data. Further, we present measures to evaluate the quality of the dataset according to the arrayer pins, 384-well plates, plate rows, and plate columns. We compare our method against competing methods using several metrics to measure the biological signal. With this novel normalization algorithm and quality control measures, the user can improve their inferences on datasets and pinpoint problems that may arise in their BAC aCGH technology.

Shift in the microbial community composition of surface water and sediment along an urban river.

PubMed

Wang, Lan; Zhang, Jing; Li, Huilin; Yang, Hong; Peng, Chao; Peng, Zhengsong; Lu, Lu

2018-06-15

Urban rivers represent a unique ecosystem in which pollution occurs regularly, leading to significantly altered of chemical and biological characteristics of the surface water and sediments. However, the impact of urbanization on the diversity and structure of the river microbial community has not been well documented. As a major tributary of the Yangtze River, the Jialing River flows through many cities. Here, a comprehensive analysis of the spatial microbial distribution in the surface water and sediments in the Nanchong section of Jialing River and its two urban branches was conducted using 16S rRNA gene-based Illumina MiSeq sequencing. The results revealed distinct differences in surface water bacterial composition along the river with a differential distribution of Proteobacteria, Cyanobacteria, Actinobacteria, Bacteroidetes and Acidobacteria (P < 0.05). The bacterial diversity in sediments was significantly higher than their corresponding water samples. Additionally, archaeal communities showed obvious spatial variability in the surface water. The construction of the hydropower station resulted in increased Cyanobacteria abundance in the upstream (32.2%) compared to its downstream (10.3%). Several taxonomic groups of potential fecal indicator bacteria, like Flavobacteria and Bacteroidia, showed an increasing trend in the urban water. PICRUSt metabolic inference analysis revealed a growing number of genes associated with xenobiotic metabolism and nitrogen metabolism in the urban water, indicating that urban discharges might act as the dominant selective force to alter the microbial communities. Redundancy analysis suggested that the microbial community structure was influenced by several environmental factors. TP (P < 0.01) and NO 3 - (P < 0.05), and metals (Zn, Fe) (P < 0.05) were the most significant drivers determining the microbial community composition in the urban river. These results highlight that river microbial communities exhibit spatial variation in urban areas due to the joint influence of chemical variables associated with sewage discharging and construction of hydropower stations. Copyright © 2018 Elsevier B.V. All rights reserved.

Spatial reconstruction of single-cell gene expression

PubMed Central

Satija, Rahul; Farrell, Jeffrey A.; Gennert, David; Schier, Alexander F.; Regev, Aviv

2015-01-01

Spatial localization is a key determinant of cellular fate and behavior, but spatial RNA assays traditionally rely on staining for a limited number of RNA species. In contrast, single-cell RNA-seq allows for deep profiling of cellular gene expression, but established methods separate cells from their native spatial context. Here we present Seurat, a computational strategy to infer cellular localization by integrating single-cell RNA-seq data with in situ RNA patterns. We applied Seurat to spatially map 851 single cells from dissociated zebrafish (Danio rerio) embryos, inferring a transcriptome-wide map of spatial patterning. We confirmed Seurat’s accuracy using several experimental approaches, and used it to identify a set of archetypal expression patterns and spatial markers. Additionally, Seurat correctly localizes rare subpopulations, accurately mapping both spatially restricted and scattered groups. Seurat will be applicable to mapping cellular localization within complex patterned tissues in diverse systems. PMID:25867923

The Bayesian group lasso for confounded spatial data

USGS Publications Warehouse

Hefley, Trevor J.; Hooten, Mevin B.; Hanks, Ephraim M.; Russell, Robin E.; Walsh, Daniel P.

2017-01-01

Generalized linear mixed models for spatial processes are widely used in applied statistics. In many applications of the spatial generalized linear mixed model (SGLMM), the goal is to obtain inference about regression coefficients while achieving optimal predictive ability. When implementing the SGLMM, multicollinearity among covariates and the spatial random effects can make computation challenging and influence inference. We present a Bayesian group lasso prior with a single tuning parameter that can be chosen to optimize predictive ability of the SGLMM and jointly regularize the regression coefficients and spatial random effect. We implement the group lasso SGLMM using efficient Markov chain Monte Carlo (MCMC) algorithms and demonstrate how multicollinearity among covariates and the spatial random effect can be monitored as a derived quantity. To test our method, we compared several parameterizations of the SGLMM using simulated data and two examples from plant ecology and disease ecology. In all examples, problematic levels multicollinearity occurred and influenced sampling efficiency and inference. We found that the group lasso prior resulted in roughly twice the effective sample size for MCMC samples of regression coefficients and can have higher and less variable predictive accuracy based on out-of-sample data when compared to the standard SGLMM.

Fine-scale population dynamics in a marine fish species inferred from dynamic state-space models.

PubMed

Rogers, Lauren A; Storvik, Geir O; Knutsen, Halvor; Olsen, Esben M; Stenseth, Nils C

2017-07-01

Identifying the spatial scale of population structuring is critical for the conservation of natural populations and for drawing accurate ecological inferences. However, population studies often use spatially aggregated data to draw inferences about population trends and drivers, potentially masking ecologically relevant population sub-structure and dynamics. The goals of this study were to investigate how population dynamics models with and without spatial structure affect inferences on population trends and the identification of intrinsic drivers of population dynamics (e.g. density dependence). Specifically, we developed dynamic, age-structured, state-space models to test different hypotheses regarding the spatial structure of a population complex of coastal Atlantic cod (Gadus morhua). Data were from a 93-year survey of juvenile (age 0 and 1) cod sampled along >200 km of the Norwegian Skagerrak coast. We compared two models: one which assumes all sampled cod belong to one larger population, and a second which assumes that each fjord contains a unique population with locally determined dynamics. Using the best supported model, we then reconstructed the historical spatial and temporal dynamics of Skagerrak coastal cod. Cross-validation showed that the spatially structured model with local dynamics had better predictive ability. Furthermore, posterior predictive checks showed that a model which assumes one homogeneous population failed to capture the spatial correlation pattern present in the survey data. The spatially structured model indicated that population trends differed markedly among fjords, as did estimates of population parameters including density-dependent survival. Recent biomass was estimated to be at a near-record low all along the coast, but the finer scale model indicated that the decline occurred at different times in different regions. Warm temperatures were associated with poor recruitment, but local changes in habitat and fishing pressure may have played a role in driving local dynamics. More generally, we demonstrated how state-space models can be used to test evidence for population spatial structure based on survey time-series data. Our study shows the importance of considering spatially structured dynamics, as the inferences from such an approach can lead to a different ecological understanding of the drivers of population declines, and fundamentally different management actions to restore populations. © 2017 The Authors. Journal of Animal Ecology published by John Wiley & Sons Ltd on behalf of British Ecological Society.

Forward and backward inference in spatial cognition.

PubMed

Penny, Will D; Zeidman, Peter; Burgess, Neil

2013-01-01

This paper shows that the various computations underlying spatial cognition can be implemented using statistical inference in a single probabilistic model. Inference is implemented using a common set of 'lower-level' computations involving forward and backward inference over time. For example, to estimate where you are in a known environment, forward inference is used to optimally combine location estimates from path integration with those from sensory input. To decide which way to turn to reach a goal, forward inference is used to compute the likelihood of reaching that goal under each option. To work out which environment you are in, forward inference is used to compute the likelihood of sensory observations under the different hypotheses. For reaching sensory goals that require a chaining together of decisions, forward inference can be used to compute a state trajectory that will lead to that goal, and backward inference to refine the route and estimate control signals that produce the required trajectory. We propose that these computations are reflected in recent findings of pattern replay in the mammalian brain. Specifically, that theta sequences reflect decision making, theta flickering reflects model selection, and remote replay reflects route and motor planning. We also propose a mapping of the above computational processes onto lateral and medial entorhinal cortex and hippocampus.

Forward and Backward Inference in Spatial Cognition

PubMed Central

Penny, Will D.; Zeidman, Peter; Burgess, Neil

2013-01-01

This paper shows that the various computations underlying spatial cognition can be implemented using statistical inference in a single probabilistic model. Inference is implemented using a common set of ‘lower-level’ computations involving forward and backward inference over time. For example, to estimate where you are in a known environment, forward inference is used to optimally combine location estimates from path integration with those from sensory input. To decide which way to turn to reach a goal, forward inference is used to compute the likelihood of reaching that goal under each option. To work out which environment you are in, forward inference is used to compute the likelihood of sensory observations under the different hypotheses. For reaching sensory goals that require a chaining together of decisions, forward inference can be used to compute a state trajectory that will lead to that goal, and backward inference to refine the route and estimate control signals that produce the required trajectory. We propose that these computations are reflected in recent findings of pattern replay in the mammalian brain. Specifically, that theta sequences reflect decision making, theta flickering reflects model selection, and remote replay reflects route and motor planning. We also propose a mapping of the above computational processes onto lateral and medial entorhinal cortex and hippocampus. PMID:24348230

Spatial pattern in Antarctica: what can we learn from Antarctic bacterial isolates?

PubMed

Chong, Chun Wie; Goh, Yuh Shan; Convey, Peter; Pearce, David; Tan, Irene Kit Ping

2013-09-01

A range of small- to moderate-scale studies of patterns in bacterial biodiversity have been conducted in Antarctica over the last two decades, most suggesting strong correlations between the described bacterial communities and elements of local environmental heterogeneity. However, very few of these studies have advanced interpretations in terms of spatially associated patterns, despite increasing evidence of patterns in bacterial biogeography globally. This is likely to be a consequence of restricted sampling coverage, with most studies to date focusing only on a few localities within a specific Antarctic region. Clearly, there is now a need for synthesis over a much larger spatial to consolidate the available data. In this study, we collated Antarctic bacterial culture identities based on the 16S rRNA gene information available in the literature and the GenBank database (n > 2,000 sequences). In contrast to some recent evidence for a distinct Antarctic microbiome, our phylogenetic comparisons show that a majority (~75 %) of Antarctic bacterial isolates were highly similar (≥99 % sequence similarity) to those retrieved from tropical and temperate regions, suggesting widespread distribution of eurythermal mesophiles in Antarctic environments. However, across different Antarctic regions, the dominant bacterial genera exhibit some spatially distinct diversity patterns analogous to those recently proposed for Antarctic terrestrial macroorganisms. Taken together, our results highlight the threat of cross-regional homogenisation in Antarctic biodiversity, and the imperative to include microbiota within the framework of biosecurity measures for Antarctica.

Spatial-Temporal Survey and Occupancy-Abundance Modeling To Predict Bacterial Community Dynamics in the Drinking Water Microbiome

PubMed Central

Pinto, Ameet J.; Schroeder, Joanna; Lunn, Mary; Sloan, William

2014-01-01

ABSTRACT Bacterial communities migrate continuously from the drinking water treatment plant through the drinking water distribution system and into our built environment. Understanding bacterial dynamics in the distribution system is critical to ensuring that safe drinking water is being supplied to customers. We present a 15-month survey of bacterial community dynamics in the drinking water system of Ann Arbor, MI. By sampling the water leaving the treatment plant and at nine points in the distribution system, we show that the bacterial community spatial dynamics of distance decay and dispersivity conform to the layout of the drinking water distribution system. However, the patterns in spatial dynamics were weaker than those for the temporal trends, which exhibited seasonal cycling correlating with temperature and source water use patterns and also demonstrated reproducibility on an annual time scale. The temporal trends were driven by two seasonal bacterial clusters consisting of multiple taxa with different networks of association within the larger drinking water bacterial community. Finally, we show that the Ann Arbor data set robustly conforms to previously described interspecific occupancy abundance models that link the relative abundance of a taxon to the frequency of its detection. Relying on these insights, we propose a predictive framework for microbial management in drinking water systems. Further, we recommend that long-term microbial observatories that collect high-resolution, spatially distributed, multiyear time series of community composition and environmental variables be established to enable the development and testing of the predictive framework. PMID:24865557

Spatiotemporal patterns of precipitation inferred from streamflow observations across the Sierra Nevada mountain range

NASA Astrophysics Data System (ADS)

Henn, Brian; Clark, Martyn P.; Kavetski, Dmitri; Newman, Andrew J.; Hughes, Mimi; McGurk, Bruce; Lundquist, Jessica D.

2018-01-01

Given uncertainty in precipitation gauge-based gridded datasets over complex terrain, we use multiple streamflow observations as an additional source of information about precipitation, in order to identify spatial and temporal differences between a gridded precipitation dataset and precipitation inferred from streamflow. We test whether gridded datasets capture across-crest and regional spatial patterns of variability, as well as year-to-year variability and trends in precipitation, in comparison to precipitation inferred from streamflow. We use a Bayesian model calibration routine with multiple lumped hydrologic model structures to infer the most likely basin-mean, water-year total precipitation for 56 basins with long-term (>30 year) streamflow records in the Sierra Nevada mountain range of California. We compare basin-mean precipitation derived from this approach with basin-mean precipitation from a precipitation gauge-based, 1/16° gridded dataset that has been used to simulate and evaluate trends in Western United States streamflow and snowpack over the 20th century. We find that the long-term average spatial patterns differ: in particular, there is less precipitation in the gridded dataset in higher-elevation basins whose aspect faces prevailing cool-season winds, as compared to precipitation inferred from streamflow. In a few years and basins, there is less gridded precipitation than there is observed streamflow. Lower-elevation, southern, and east-of-crest basins show better agreement between gridded and inferred precipitation. Implied actual evapotranspiration (calculated as precipitation minus streamflow) then also varies between the streamflow-based estimates and the gridded dataset. Absolute uncertainty in precipitation inferred from streamflow is substantial, but the signal of basin-to-basin and year-to-year differences are likely more robust. The findings suggest that considering streamflow when spatially distributing precipitation in complex terrain may improve its representation, particularly for basins whose orientations (e.g., windward-facing) are favored for orographic precipitation enhancement.

Evaluating Bayesian spatial methods for modelling species distributions with clumped and restricted occurrence data.

PubMed

Redding, David W; Lucas, Tim C D; Blackburn, Tim M; Jones, Kate E

2017-01-01

Statistical approaches for inferring the spatial distribution of taxa (Species Distribution Models, SDMs) commonly rely on available occurrence data, which is often clumped and geographically restricted. Although available SDM methods address some of these factors, they could be more directly and accurately modelled using a spatially-explicit approach. Software to fit models with spatial autocorrelation parameters in SDMs are now widely available, but whether such approaches for inferring SDMs aid predictions compared to other methodologies is unknown. Here, within a simulated environment using 1000 generated species' ranges, we compared the performance of two commonly used non-spatial SDM methods (Maximum Entropy Modelling, MAXENT and boosted regression trees, BRT), to a spatial Bayesian SDM method (fitted using R-INLA), when the underlying data exhibit varying combinations of clumping and geographic restriction. Finally, we tested how any recommended methodological settings designed to account for spatially non-random patterns in the data impact inference. Spatial Bayesian SDM method was the most consistently accurate method, being in the top 2 most accurate methods in 7 out of 8 data sampling scenarios. Within high-coverage sample datasets, all methods performed fairly similarly. When sampling points were randomly spread, BRT had a 1-3% greater accuracy over the other methods and when samples were clumped, the spatial Bayesian SDM method had a 4%-8% better AUC score. Alternatively, when sampling points were restricted to a small section of the true range all methods were on average 10-12% less accurate, with greater variation among the methods. Model inference under the recommended settings to account for autocorrelation was not impacted by clumping or restriction of data, except for the complexity of the spatial regression term in the spatial Bayesian model. Methods, such as those made available by R-INLA, can be successfully used to account for spatial autocorrelation in an SDM context and, by taking account of random effects, produce outputs that can better elucidate the role of covariates in predicting species occurrence. Given that it is often unclear what the drivers are behind data clumping in an empirical occurrence dataset, or indeed how geographically restricted these data are, spatially-explicit Bayesian SDMs may be the better choice when modelling the spatial distribution of target species.

Contrasting spatial patterns and ecological attributes of soil bacterial and archaeal taxa across a landscape.

PubMed

Constancias, Florentin; Saby, Nicolas P A; Terrat, Sébastien; Dequiedt, Samuel; Horrigue, Wallid; Nowak, Virginie; Guillemin, Jean-Philippe; Biju-Duval, Luc; Chemidlin Prévost-Bouré, Nicolas; Ranjard, Lionel

2015-06-01

Even though recent studies have clarified the influence and hierarchy of environmental filters on bacterial community structure, those constraining bacterial populations variations remain unclear. In consequence, our ability to understand to ecological attributes of soil bacteria and to predict microbial community response to environmental stress is therefore limited. Here, we characterized the bacterial community composition and the various bacterial taxonomic groups constituting the community across an agricultural landscape of 12 km(2) , by using a 215 × 215 m systematic grid representing 278 sites to precisely decipher their spatial distribution and drivers at this scale. The bacterial and Archaeal community composition was characterized by applying 16S rRNA gene pyrosequencing directly to soil DNA from samples. Geostatistics tools were used to reveal the heterogeneous distribution of bacterial composition at this scale. Soil physical parameters and land management explained a significant amount of variation, suggesting that environmental selection is the major process shaping bacterial composition. All taxa systematically displayed also a heterogeneous and particular distribution patterns. Different relative influences of soil characteristics, land use and space were observed, depending on the taxa, implying that selection and spatial processes might be differentially but not exclusively involved for each bacterial phylum. Soil pH was a major factor determining the distribution of most of the bacterial taxa and especially the most important factor explaining the spatial patterns of α-Proteobacteria and Planctomycetes. Soil texture, organic carbon content and quality were more specific to a few number of taxa (e.g., β-Proteobacteria and Chlorobi). Land management also influenced the distribution of bacterial taxa across the landscape and revealed different type of response to cropping intensity (positive, negative, neutral or hump-backed relationships) according to phyla. Altogether, this study provided valuable clues about the ecological behavior of soil bacterial and archaeal taxa at an agricultural landscape scale and could be useful for developing sustainable strategies of land management. © 2015 The Authors. MicrobiologyOpen published by John Wiley & Sons Ltd.

Functional mechanisms of probabilistic inference in feature- and space-based attentional systems.

PubMed

Dombert, Pascasie L; Kuhns, Anna; Mengotti, Paola; Fink, Gereon R; Vossel, Simone

2016-11-15

Humans flexibly attend to features or locations and these processes are influenced by the probability of sensory events. We combined computational modeling of response times with fMRI to compare the functional correlates of (re-)orienting, and the modulation by probabilistic inference in spatial and feature-based attention systems. Twenty-four volunteers performed two task versions with spatial or color cues. Percentage of cue validity changed unpredictably. A hierarchical Bayesian model was used to derive trial-wise estimates of probability-dependent attention, entering the fMRI analysis as parametric regressors. Attentional orienting activated a dorsal frontoparietal network in both tasks, without significant parametric modulation. Spatially invalid trials activated a bilateral frontoparietal network and the precuneus, while invalid feature trials activated the left intraparietal sulcus (IPS). Probability-dependent attention modulated activity in the precuneus, left posterior IPS, middle occipital gyrus, and right temporoparietal junction for spatial attention, and in the left anterior IPS for feature-based and spatial attention. These findings provide novel insights into the generality and specificity of the functional basis of attentional control. They suggest that probabilistic inference can distinctively affect each attentional subsystem, but that there is an overlap in the left IPS, which responds to both spatial and feature-based expectancy violations. Copyright © 2016 Elsevier Inc. All rights reserved.

Inferring Spatial Variations of Microstructural Properties from Macroscopic Mechanical Response

PubMed Central

Liu, Tengxiao; Hall, Timothy J.; Barbone, Paul E.; Oberai, Assad A.

2016-01-01

Disease alters tissue microstructure, which in turn affects the macroscopic mechanical properties of tissue. In elasticity imaging, the macroscopic response is measured and is used to infer the spatial distribution of the elastic constitutive parameters. When an empirical constitutive model is used these parameters cannot be linked to the microstructure. However, when the constitutive model is derived from a microstructural representation of the material, it allows for the possibility of inferring the local averages of the spatial distribution of the microstructural parameters. This idea forms the basis of this study. In particular, we first derive a constitutive model by homogenizing the mechanical response of a network of elastic, tortuous fibers. Thereafter, we use this model in an inverse problem to determine the spatial distribution of the microstructural parameters. We solve the inverse problem as a constrained minimization problem, and develop efficient methods for solving it. We apply these methods to displacement fields obtained by deforming gelatin-agar co-gels, and determine the spatial distribution of agar concentration and fiber tortuosity, thereby demonstrating that it is possible to image local averages of microstructural parameters from macroscopic measurements of deformation. PMID:27655420

The Composition and Spatial Patterns of Bacterial Virulence Factors and Antibiotic Resistance Genes in 19 Wastewater Treatment Plants

PubMed Central

Zhang, Bing; Xia, Yu; Wen, Xianghua; Wang, Xiaohui; Yang, Yunfeng; Zhou, Jizhong; Zhang, Yu

2016-01-01

Bacterial pathogenicity and antibiotic resistance are of concern for environmental safety and public health. Accumulating evidence suggests that wastewater treatment plants (WWTPs) are as an important sink and source of pathogens and antibiotic resistance genes (ARGs). Virulence genes (encoding virulence factors) are good indicators for bacterial pathogenic potentials. To achieve a comprehensive understanding of bacterial pathogenic potentials and antibiotic resistance in WWTPs, bacterial virulence genes and ARGs in 19 WWTPs covering a majority of latitudinal zones of China were surveyed by using GeoChip 4.2. A total of 1610 genes covering 13 virulence factors and 1903 genes belonging to 11 ARG families were detected respectively. The bacterial virulence genes exhibited significant spatial distribution patterns of a latitudinal biodiversity gradient and a distance-decay relationship across China. Moreover, virulence genes tended to coexist with ARGs as shown by their strongly positive associations. In addition, key environmental factors shaping the overall virulence gene structure were identified. This study profiles the occurrence, composition and distribution of virulence genes and ARGs in current WWTPs in China, and uncovers spatial patterns and important environmental variables shaping their structure, which may provide the basis for further studies of bacterial virulence factors and antibiotic resistance in WWTPs. PMID:27907117

Inference Based on Transitive Relation in Tree Shrews ("Tupaia belangeri") and Rats ("Rattus norvegicus") on a Spatial Discrimination Task

ERIC Educational Resources Information Center

Takahashi, Makoto; Ushitani, Tomokazu; Fujita, Kazuo

2008-01-01

Six tree shrews and 8 rats were tested for their ability to infer transitively in a spatial discrimination task. The apparatus was a semicircular radial-arm maze with 8 arms labeled A through H. In Experiment 1, the animals were first trained in sequence on 4 discriminations to enter 1 of the paired adjacent arms, AB, BC, CD, and DE, with right…

Underestimating the effects of spatial heterogeneity due to individual movement and spatial scale: infectious disease as an example

USGS Publications Warehouse

Cross, Paul C.; Caillaud, Damien; Heisey, Dennis M.

2013-01-01

Many ecological and epidemiological studies occur in systems with mobile individuals and heterogeneous landscapes. Using a simulation model, we show that the accuracy of inferring an underlying biological process from observational data depends on movement and spatial scale of the analysis. As an example, we focused on estimating the relationship between host density and pathogen transmission. Observational data can result in highly biased inference about the underlying process when individuals move among sampling areas. Even without sampling error, the effect of host density on disease transmission is underestimated by approximately 50 % when one in ten hosts move among sampling areas per lifetime. Aggregating data across larger regions causes minimal bias when host movement is low, and results in less biased inference when movement rates are high. However, increasing data aggregation reduces the observed spatial variation, which would lead to the misperception that a spatially targeted control effort may not be very effective. In addition, averaging over the local heterogeneity will result in underestimating the importance of spatial covariates. Minimizing the bias due to movement is not just about choosing the best spatial scale for analysis, but also about reducing the error associated with using the sampling location as a proxy for an individual’s spatial history. This error associated with the exposure covariate can be reduced by choosing sampling regions with less movement, including longitudinal information of individuals’ movements, or reducing the window of exposure by using repeated sampling or younger individuals.

The evolution of bacterial resistance against bacteriophages in the horse chestnut phyllosphere is general across both space and time.

PubMed

Koskella, Britt; Parr, Nicole

2015-08-19

Insight to the spatial and temporal scales of coevolution is key to predicting the outcome of host-parasite interactions and spread of disease. For bacteria infecting long-lived hosts, selection to overcome host defences is just one factor shaping the course of evolution; populations will also be competing with other microbial species and will themselves be facing infection by bacteriophage viruses. Here, we examine the temporal and spatial patterns of bacterial adaptation against natural phage populations from within leaves of horse chestnut trees. Using a time-shift experiment with both sympatric and allopatric phages from either contemporary or earlier points in the season, we demonstrate that bacterial resistance is higher against phages from the past, regardless of spatial sympatry or how much earlier in the season phages were collected. Similarly, we show that future bacterial hosts are more resistant to both sympatric and allopatric phages than contemporary bacterial hosts. Together, our results suggest the evolution of relatively general bacterial resistance against phages in nature and are contrasting to previously observed patterns of phage adaptation to bacteria from the same tree hosts over the same time frame, indicating a potential asymmetry in coevolutionary dynamics.

The evolution of bacterial resistance against bacteriophages in the horse chestnut phyllosphere is general across both space and time

PubMed Central

Koskella, Britt; Parr, Nicole

2015-01-01

Insight to the spatial and temporal scales of coevolution is key to predicting the outcome of host–parasite interactions and spread of disease. For bacteria infecting long-lived hosts, selection to overcome host defences is just one factor shaping the course of evolution; populations will also be competing with other microbial species and will themselves be facing infection by bacteriophage viruses. Here, we examine the temporal and spatial patterns of bacterial adaptation against natural phage populations from within leaves of horse chestnut trees. Using a time-shift experiment with both sympatric and allopatric phages from either contemporary or earlier points in the season, we demonstrate that bacterial resistance is higher against phages from the past, regardless of spatial sympatry or how much earlier in the season phages were collected. Similarly, we show that future bacterial hosts are more resistant to both sympatric and allopatric phages than contemporary bacterial hosts. Together, our results suggest the evolution of relatively general bacterial resistance against phages in nature and are contrasting to previously observed patterns of phage adaptation to bacteria from the same tree hosts over the same time frame, indicating a potential asymmetry in coevolutionary dynamics. PMID:26150663

Attenuated Salmonella Typhimurium Lacking the Pathogenicity Island-2 Type 3 Secretion System Grow to High Bacterial Numbers inside Phagocytes in Mice

PubMed Central

Grant, Andrew J.; Morgan, Fiona J. E.; McKinley, Trevelyan J.; Foster, Gemma L.; Maskell, Duncan J.; Mastroeni, Pietro

2012-01-01

Intracellular replication within specialized vacuoles and cell-to-cell spread in the tissue are essential for the virulence of Salmonella enterica. By observing infection dynamics at the single-cell level in vivo, we have discovered that the Salmonella pathogenicity island 2 (SPI-2) type 3 secretory system (T3SS) is dispensable for growth to high intracellular densities. This challenges the concept that intracellular replication absolutely requires proteins delivered by SPI-2 T3SS, which has been derived largely by inference from in vitro cell experiments and from unrefined measurement of net growth in mouse organs. Furthermore, we infer from our data that the SPI-2 T3SS mediates exit from infected cells, with consequent formation of new infection foci resulting in bacterial spread in the tissues. This suggests a new role for SPI-2 in vivo as a mediator of bacterial spread in the body. In addition, we demonstrate that very similar net growth rates of attenuated salmonellae in organs can be derived from very different underlying intracellular growth dynamics. PMID:23236281

Optimization of analytical parameters for inferring relationships among Escherichia coli isolates from repetitive-element PCR by maximizing correspondence with multilocus sequence typing data.

PubMed

Goldberg, Tony L; Gillespie, Thomas R; Singer, Randall S

2006-09-01

Repetitive-element PCR (rep-PCR) is a method for genotyping bacteria based on the selective amplification of repetitive genetic elements dispersed throughout bacterial chromosomes. The method has great potential for large-scale epidemiological studies because of its speed and simplicity; however, objective guidelines for inferring relationships among bacterial isolates from rep-PCR data are lacking. We used multilocus sequence typing (MLST) as a "gold standard" to optimize the analytical parameters for inferring relationships among Escherichia coli isolates from rep-PCR data. We chose 12 isolates from a large database to represent a wide range of pairwise genetic distances, based on the initial evaluation of their rep-PCR fingerprints. We conducted MLST with these same isolates and systematically varied the analytical parameters to maximize the correspondence between the relationships inferred from rep-PCR and those inferred from MLST. Methods that compared the shapes of densitometric profiles ("curve-based" methods) yielded consistently higher correspondence values between data types than did methods that calculated indices of similarity based on shared and different bands (maximum correspondences of 84.5% and 80.3%, respectively). Curve-based methods were also markedly more robust in accommodating variations in user-specified analytical parameter values than were "band-sharing coefficient" methods, and they enhanced the reproducibility of rep-PCR. Phylogenetic analyses of rep-PCR data yielded trees with high topological correspondence to trees based on MLST and high statistical support for major clades. These results indicate that rep-PCR yields accurate information for inferring relationships among E. coli isolates and that accuracy can be enhanced with the use of analytical methods that consider the shapes of densitometric profiles.

Spatial scales of bacterial community diversity at cold seeps (Eastern Mediterranean Sea)

PubMed Central

Pop Ristova, Petra; Wenzhöfer, Frank; Ramette, Alban; Felden, Janine; Boetius, Antje

2015-01-01

Cold seeps are highly productive, fragmented marine ecosystems that form at the seafloor around hydrocarbon emission pathways. The products of microbial utilization of methane and other hydrocarbons fuel rich chemosynthetic communities at these sites, with much higher respiration rates compared with the surrounding deep-sea floor. Yet little is known as to the richness, composition and spatial scaling of bacterial communities of cold seeps compared with non-seep communities. Here we assessed the bacterial diversity across nine different cold seeps in the Eastern Mediterranean deep-sea and surrounding seafloor areas. Community similarity analyses were carried out based on automated ribosomal intergenic spacer analysis (ARISA) fingerprinting and high-throughput 454 tag sequencing and were combined with in situ and ex situ geochemical analyses across spatial scales of a few tens of meters to hundreds of kilometers. Seep communities were dominated by Deltaproteobacteria, Epsilonproteobacteria and Gammaproteobacteria and shared, on average, 36% of bacterial types (ARISA OTUs (operational taxonomic units)) with communities from nearby non-seep deep-sea sediments. Bacterial communities of seeps were significantly different from those of non-seep sediments. Within cold seep regions on spatial scales of only tens to hundreds of meters, the bacterial communities differed considerably, sharing <50% of types at the ARISA OTU level. Their variations reflected differences in porewater sulfide concentrations from anaerobic degradation of hydrocarbons. This study shows that cold seep ecosystems contribute substantially to the microbial diversity of the deep-sea. PMID:25500510

Distinct antimicrobial peptide expression determines host species-specific bacterial associations

PubMed Central

Franzenburg, Sören; Walter, Jonas; Künzel, Sven; Wang, Jun; Baines, John F.; Bosch, Thomas C. G.; Fraune, Sebastian

2013-01-01

Animals are colonized by coevolved bacterial communities, which contribute to the host’s health. This commensal microbiota is often highly specific to its host-species, inferring strong selective pressures on the associated microbes. Several factors, including diet, mucus composition, and the immune system have been proposed as putative determinants of host-associated bacterial communities. Here we report that species-specific antimicrobial peptides account for different bacterial communities associated with closely related species of the cnidarian Hydra. Gene family extensions for potent antimicrobial peptides, the arminins, were detected in four Hydra species, with each species possessing a unique composition and expression profile of arminins. For functional analysis, we inoculated arminin-deficient and control polyps with bacterial consortia characteristic for different Hydra species and compared their selective preferences by 454 pyrosequencing of the bacterial microbiota. In contrast to control polyps, arminin-deficient polyps displayed decreased potential to select for bacterial communities resembling their native microbiota. This finding indicates that species-specific antimicrobial peptides shape species-specific bacterial associations. PMID:24003149

Mind the Scales: Harnessing Spatial Big Data for Infectious Disease Surveillance and Inference

PubMed Central

Lee, Elizabeth C.; Asher, Jason M.; Goldlust, Sandra; Kraemer, John D.; Lawson, Andrew B.; Bansal, Shweta

2016-01-01

Spatial big data have the velocity, volume, and variety of big data sources and contain additional geographic information. Digital data sources, such as medical claims, mobile phone call data records, and geographically tagged tweets, have entered infectious diseases epidemiology as novel sources of data to complement traditional infectious disease surveillance. In this work, we provide examples of how spatial big data have been used thus far in epidemiological analyses and describe opportunities for these sources to improve disease-mitigation strategies and public health coordination. In addition, we consider the technical, practical, and ethical challenges with the use of spatial big data in infectious disease surveillance and inference. Finally, we discuss the implications of the rising use of spatial big data in epidemiology to health risk communication, and public health policy recommendations and coordination across scales. PMID:28830109

Hierarchical spatial models of abundance and occurrence from imperfect survey data

USGS Publications Warehouse

Royle, J. Andrew; Kery, M.; Gautier, R.; Schmid, Hans

2007-01-01

Many estimation and inference problems arising from large-scale animal surveys are focused on developing an understanding of patterns in abundance or occurrence of a species based on spatially referenced count data. One fundamental challenge, then, is that it is generally not feasible to completely enumerate ('census') all individuals present in each sample unit. This observation bias may consist of several components, including spatial coverage bias (not all individuals in the Population are exposed to sampling) and detection bias (exposed individuals may go undetected). Thus, observations are biased for the state variable (abundance, occupancy) that is the object of inference. Moreover, data are often sparse for most observation locations, requiring consideration of methods for spatially aggregating or otherwise combining sparse data among sample units. The development of methods that unify spatial statistical models with models accommodating non-detection is necessary to resolve important spatial inference problems based on animal survey data. In this paper, we develop a novel hierarchical spatial model for estimation of abundance and occurrence from survey data wherein detection is imperfect. Our application is focused on spatial inference problems in the Swiss Survey of Common Breeding Birds. The observation model for the survey data is specified conditional on the unknown quadrat population size, N(s). We augment the observation model with a spatial process model for N(s), describing the spatial variation in abundance of the species. The model includes explicit sources of variation in habitat structure (forest, elevation) and latent variation in the form of a correlated spatial process. This provides a model-based framework for combining the spatially referenced samples while at the same time yielding a unified treatment of estimation problems involving both abundance and occurrence. We provide a Bayesian framework for analysis and prediction based on the integrated likelihood, and we use the model to obtain estimates of abundance and occurrence maps for the European Jay (Garrulus glandarius), a widespread, elusive, forest bird. The naive national abundance estimate ignoring imperfect detection and incomplete quadrat coverage was 77 766 territories. Accounting for imperfect detection added approximately 18 000 territories, and adjusting for coverage bias added another 131 000 territories to yield a fully corrected estimate of the national total of about 227 000 territories. This is approximately three times as high as previous estimates that assume every territory is detected in each quadrat.

Terrestrial origin of bacterial communities in complex boreal freshwater networks.

PubMed

Ruiz-González, Clara; Niño-García, Juan Pablo; Del Giorgio, Paul A

2015-08-25

Bacteria inhabiting boreal freshwaters are part of metacommunities where local assemblages are often linked by the flow of water in the landscape, yet the resulting spatial structure and the boundaries of the network metacommunity have never been explored. Here, we reconstruct the spatial structure of the bacterial metacommunity in a complex boreal aquatic network by determining the taxonomic composition of bacterial communities along the entire terrestrial/aquatic continuum, including soil and soilwaters, headwater streams, large rivers and lakes. We show that the network metacommunity has a directional spatial structure driven by a common terrestrial origin of aquatic communities, which are numerically dominated by taxa recruited from soils. Local community assembly is driven by variations along the hydrological continuum in the balance between mass effects and species sorting of terrestrial taxa, and seems further influenced by priority effects related to the spatial sequence of entry of soil bacteria into the network. © 2015 John Wiley & Sons Ltd/CNRS.

Similar Processes but Different Environmental Filters for Soil Bacterial and Fungal Community Composition Turnover on a Broad Spatial Scale

PubMed Central

Chemidlin Prévost-Bouré, Nicolas; Dequiedt, Samuel; Thioulouse, Jean; Lelièvre, Mélanie; Saby, Nicolas P. A.; Jolivet, Claudy; Arrouays, Dominique; Plassart, Pierre; Lemanceau, Philippe; Ranjard, Lionel

2014-01-01

Spatial scaling of microorganisms has been demonstrated over the last decade. However, the processes and environmental filters shaping soil microbial community structure on a broad spatial scale still need to be refined and ranked. Here, we compared bacterial and fungal community composition turnovers through a biogeographical approach on the same soil sampling design at a broad spatial scale (area range: 13300 to 31000 km2): i) to examine their spatial structuring; ii) to investigate the relative importance of environmental selection and spatial autocorrelation in determining their community composition turnover; and iii) to identify and rank the relevant environmental filters and scales involved in their spatial variations. Molecular fingerprinting of soil bacterial and fungal communities was performed on 413 soils from four French regions of contrasting environmental heterogeneity (Landes

Similar processes but different environmental filters for soil bacterial and fungal community composition turnover on a broad spatial scale.

PubMed

Chemidlin Prévost-Bouré, Nicolas; Dequiedt, Samuel; Thioulouse, Jean; Lelièvre, Mélanie; Saby, Nicolas P A; Jolivet, Claudy; Arrouays, Dominique; Plassart, Pierre; Lemanceau, Philippe; Ranjard, Lionel

2014-01-01

Spatial scaling of microorganisms has been demonstrated over the last decade. However, the processes and environmental filters shaping soil microbial community structure on a broad spatial scale still need to be refined and ranked. Here, we compared bacterial and fungal community composition turnovers through a biogeographical approach on the same soil sampling design at a broad spatial scale (area range: 13300 to 31000 km2): i) to examine their spatial structuring; ii) to investigate the relative importance of environmental selection and spatial autocorrelation in determining their community composition turnover; and iii) to identify and rank the relevant environmental filters and scales involved in their spatial variations. Molecular fingerprinting of soil bacterial and fungal communities was performed on 413 soils from four French regions of contrasting environmental heterogeneity (Landes

Spatial distribution of marine airborne bacterial communities

PubMed Central

Seifried, Jasmin S; Wichels, Antje; Gerdts, Gunnar

2015-01-01

The spatial distribution of bacterial populations in marine bioaerosol samples was investigated during a cruise from the North Sea to the Baltic Sea via Skagerrak and Kattegat. The analysis of the sampled bacterial communities with a pyrosequencing approach revealed that the most abundant phyla were represented by the Proteobacteria (49.3%), Bacteroidetes (22.9%), Actinobacteria (16.3%), and Firmicutes (8.3%). Cyanobacteria were assigned to 1.5% of all bacterial reads. A core of 37 bacterial OTUs made up more than 75% of all bacterial sequences. The most abundant OTU was Sphingomonas sp. which comprised 17% of all bacterial sequences. The most abundant bacterial genera were attributed to distinctly different areas of origin, suggesting highly heterogeneous sources for bioaerosols of marine and coastal environments. Furthermore, the bacterial community was clearly affected by two environmental parameters – temperature as a function of wind direction and the sampling location itself. However, a comparison of the wind directions during the sampling and calculated backward trajectories underlined the need for more detailed information on environmental parameters for bioaerosol investigations. The current findings support the assumption of a bacterial core community in the atmosphere. They may be emitted from strong aerosolizing sources, probably being mixed and dispersed over long distances. PMID:25800495

Strain diversity and host specificity in bee gut symbionts revealed by deep sampling of single copy protein-coding sequences

PubMed Central

Powell, J. Elijah; Ratnayeke, Nalin; Moran, Nancy A.

2017-01-01

High throughput rRNA amplicon surveys of bacterial communities provide a rapid snapshot of taxonomic composition. But strains with nearly identical rRNA sequences often differ in gene repertoires and metabolic capabilities. To assess strain-level variation within Snodgrassella alvi, a gut symbiont of corbiculate bees, we performed deep sequencing on amplicons of a single copy coding gene (minD) as well as the 16S rDNA V4 region. We surveyed honey bees (Apis mellifera) sampled globally and 12 bumble bee species (Bombus) sampled from two regions of the USA. The minD analyses reveal that S. alvi contains far more strain diversity than is evident from 16S rDNA analysis. Many taxa inferred on the basis of 16S rDNA are shared between A. mellifera and Bombus species, but taxa inferred on the basis of minD are never shared and often are restricted to particular Bombus species. Clustering based on minD revealed that gut communities often reflect host species and geographic location. Both minD and 16S rDNA analyses indicate that strain diversity is higher in A. mellifera than in Bombus species. The minD locus flanks a 16S gene, enabling development of strain-specific 16S fluorescent probes to illuminate the spatial relationship of strains within the bee gut. PMID:27482856

Associations between soil bacterial community structure and nutrient cycling functions in long-term organic farm soils following cover crop and organic fertilizer amendment.

PubMed

Fernandez, Adria L; Sheaffer, Craig C; Wyse, Donald L; Staley, Christopher; Gould, Trevor J; Sadowsky, Michael J

2016-10-01

Agricultural management practices can produce changes in soil microbial populations whose functions are crucial to crop production and may be detectable using high-throughput sequencing of bacterial 16S rRNA. To apply sequencing-derived bacterial community structure data to on-farm decision-making will require a better understanding of the complex associations between soil microbial community structure and soil function. Here 16S rRNA sequencing was used to profile soil bacterial communities following application of cover crops and organic fertilizer treatments in certified organic field cropping systems. Amendment treatments were hairy vetch (Vicia villosa), winter rye (Secale cereale), oilseed radish (Raphanus sativus), buckwheat (Fagopyrum esculentum), beef manure, pelleted poultry manure, Sustane(®) 8-2-4, and a no-amendment control. Enzyme activities, net N mineralization, soil respiration, and soil physicochemical properties including nutrient levels, organic matter (OM) and pH were measured. Relationships between these functional and physicochemical parameters and soil bacterial community structure were assessed using multivariate methods including redundancy analysis, discriminant analysis, and Bayesian inference. Several cover crops and fertilizers affected soil functions including N-acetyl-β-d-glucosaminidase and β-glucosidase activity. Effects, however, were not consistent across locations and sampling timepoints. Correlations were observed among functional parameters and relative abundances of individual bacterial families and phyla. Bayesian analysis inferred no directional relationships between functional activities, bacterial families, and physicochemical parameters. Soil functional profiles were more strongly predicted by location than by treatment, and differences were largely explained by soil physicochemical parameters. Composition of soil bacterial communities was predictive of soil functional profiles. Differences in soil function were better explained using both soil physicochemical test values and bacterial community structure data than using soil tests alone. Pursuing a better understanding of bacterial community composition and how it is affected by farming practices is a promising avenue for increasing our ability to predict the impact of management practices on important soil functions. Copyright © 2016. Published by Elsevier B.V.

Stair-Step Pattern of Soil Bacterial Diversity Mainly Driven by pH and Vegetation Types Along the Elevational Gradients of Gongga Mountain, China

PubMed Central

Li, Jiabao; Shen, Zehao; Li, Chaonan; Kou, Yongping; Wang, Yansu; Tu, Bo; Zhang, Shiheng; Li, Xiangzhen

2018-01-01

Ecological understandings of soil bacterial community succession and assembly mechanism along elevational gradients in mountains remain not well understood. Here, by employing the high-throughput sequencing technique, we systematically examined soil bacterial diversity patterns, the driving factors, and community assembly mechanisms along the elevational gradients of 1800–4100 m on Gongga Mountain in China. Soil bacterial diversity showed an extraordinary stair-step pattern along the elevational gradients. There was an abrupt decrease of bacterial diversity between 2600 and 2800 m, while no significant change at either lower (1800–2600 m) or higher (2800–4100 m) elevations, which coincided with the variation in soil pH. In addition, the community structure differed significantly between the lower and higher elevations, which could be primarily attributed to shifts in soil pH and vegetation types. Although there was no direct effect of MAP and MAT on bacterial community structure, our partial least squares path modeling analysis indicated that bacterial communities were indirectly influenced by climate via the effect on vegetation and the derived effect on soil properties. As for bacterial community assembly mechanisms, the null model analysis suggested that environmental filtering played an overwhelming role in the assembly of bacterial communities in this region. In addition, variation partition analysis indicated that, at lower elevations, environmental attributes explained much larger fraction of the β-deviation than spatial attributes, while spatial attributes increased their contributions at higher elevations. Our results highlight the importance of environmental filtering, as well as elevation-related spatial attributes in structuring soil bacterial communities in mountain ecosystems. PMID:29636740

Design Principles and First Educational Experiments of pR, a Platform to Infer Geo-Referenced Itineraries from Travel Stories

ERIC Educational Resources Information Center

Loustau, Pierre; Nodenot, Thierry; Gaio, Mauro

2009-01-01

Purpose: The purpose of this paper is to present a computational approach and a toolset to infer spatial displacements as they occur in route narrative documents and report on first experiments done to produce computer-aided learning (CAL) applications and instructional design editors that exploit the inferred georeferenced itineraries.…

A Bayesian Framework for Analysis of Pseudo-Spatial Models of Comparable Engineered Systems with Application to Spacecraft Anomaly Prediction Based on Precedent Data

NASA Astrophysics Data System (ADS)

Ndu, Obibobi Kamtochukwu

To ensure that estimates of risk and reliability inform design and resource allocation decisions in the development of complex engineering systems, early engagement in the design life cycle is necessary. An unfortunate constraint on the accuracy of such estimates at this stage of concept development is the limited amount of high fidelity design and failure information available on the actual system under development. Applying the human ability to learn from experience and augment our state of knowledge to evolve better solutions mitigates this limitation. However, the challenge lies in formalizing a methodology that takes this highly abstract, but fundamentally human cognitive, ability and extending it to the field of risk analysis while maintaining the tenets of generalization, Bayesian inference, and probabilistic risk analysis. We introduce an integrated framework for inferring the reliability, or other probabilistic measures of interest, of a new system or a conceptual variant of an existing system. Abstractly, our framework is based on learning from the performance of precedent designs and then applying the acquired knowledge, appropriately adjusted based on degree of relevance, to the inference process. This dissertation presents a method for inferring properties of the conceptual variant using a pseudo-spatial model that describes the spatial configuration of the family of systems to which the concept belongs. Through non-metric multidimensional scaling, we formulate the pseudo-spatial model based on rank-ordered subjective expert perception of design similarity between systems that elucidate the psychological space of the family. By a novel extension of Kriging methods for analysis of geospatial data to our "pseudo-space of comparable engineered systems", we develop a Bayesian inference model that allows prediction of the probabilistic measure of interest.

Mapping and determinism of soil microbial community distribution across an agricultural landscape

PubMed Central

Constancias, Florentin; Terrat, Sébastien; Saby, Nicolas P A; Horrigue, Walid; Villerd, Jean; Guillemin, Jean-Philippe; Biju-Duval, Luc; Nowak, Virginie; Dequiedt, Samuel; Ranjard, Lionel; Chemidlin Prévost-Bouré, Nicolas

2015-01-01

Despite the relevance of landscape, regarding the spatial patterning of microbial communities and the relative influence of environmental parameters versus human activities, few investigations have been conducted at this scale. Here, we used a systematic grid to characterize the distribution of soil microbial communities at 278 sites across a monitored agricultural landscape of 13 km². Molecular microbial biomass was estimated by soil DNA recovery and bacterial diversity by 16S rRNA gene pyrosequencing. Geostatistics provided the first maps of microbial community at this scale and revealed a heterogeneous but spatially structured distribution of microbial biomass and diversity with patches of several hundreds of meters. Variance partitioning revealed that both microbial abundance and bacterial diversity distribution were highly dependent of soil properties and land use (total variance explained ranged between 55% and 78%). Microbial biomass and bacterial richness distributions were mainly explained by soil pH and texture whereas bacterial evenness distribution was mainly related to land management. Bacterial diversity (richness, evenness, and Shannon index) was positively influenced by cropping intensity and especially by soil tillage, resulting in spots of low microbial diversity in soils under forest management. Spatial descriptors also explained a small but significant portion of the microbial distribution suggesting that landscape configuration also shapes microbial biomass and bacterial diversity. PMID:25833770

Spatial diversity of bacterioplankton communities in surface water of northern South China Sea.

PubMed

Li, Jialin; Li, Nan; Li, Fuchao; Zou, Tao; Yu, Shuxian; Wang, Yinchu; Qin, Song; Wang, Guangyi

2014-01-01

The South China Sea is one of the largest marginal seas, with relatively frequent passage of eddies and featuring distinct spatial variation in the western tropical Pacific Ocean. Here, we report a phylogenetic study of bacterial community structures in surface seawater of the northern South China Sea (nSCS). Samples collected from 31 sites across large environmental gradients were used to construct clone libraries and yielded 2,443 sequences grouped into 170 OTUs. Phylogenetic analysis revealed 23 bacterial classes with major components α-, β- and γ-Proteobacteria, as well as Cyanobacteria. At class and genus taxon levels, community structure of coastal waters was distinctively different from that of deep-sea waters and displayed a higher diversity index. Redundancy analyses revealed that bacterial community structures displayed a significant correlation with the water depth of individual sampling sites. Members of α-Proteobacteria were the principal component contributing to the differences of the clone libraries. Furthermore, the bacterial communities exhibited heterogeneity within zones of upwelling and anticyclonic eddies. Our results suggested that surface bacterial communities in nSCS had two-level patterns of spatial distribution structured by ecological types (coastal VS. oceanic zones) and mesoscale physical processes, and also provided evidence for bacterial phylogenetic phyla shaped by ecological preferences.

Spatial and Temporal Variation of Archaeal, Bacterial and Fungal Communities in Agricultural Soils

PubMed Central

Pereira e Silva, Michele C.; Dias, Armando Cavalcante Franco; van Elsas, Jan Dirk; Salles, Joana Falcão

2012-01-01

Background Soil microbial communities are in constant change at many different temporal and spatial scales. However, the importance of these changes to the turnover of the soil microbial communities has been rarely studied simultaneously in space and time. Methodology/Principal Findings In this study, we explored the temporal and spatial responses of soil bacterial, archaeal and fungal β-diversities to abiotic parameters. Taking into account data from a 3-year sampling period, we analyzed the abundances and community structures of Archaea, Bacteria and Fungi along with key soil chemical parameters. We questioned how these abiotic variables influence the turnover of bacterial, archaeal and fungal communities and how they impact the long-term patterns of changes of the aforementioned soil communities. Interestingly, we found that the bacterial and fungal β-diversities are quite stable over time, whereas archaeal diversity showed significantly higher fluctuations. These fluctuations were reflected in temporal turnover caused by soil management through addition of N-fertilizers. Conclusions Our study showed that management practices applied to agricultural soils might not significantly affect the bacterial and fungal communities, but cause slow and long-term changes in the abundance and structure of the archaeal community. Moreover, the results suggest that, to different extents, abiotic and biotic factors determine the community assembly of archaeal, bacterial and fungal communities. PMID:23284712

Mental Models of Invisible Logical Networks

NASA Technical Reports Server (NTRS)

Sanderson, P.

1984-01-01

Subjects were required to discover the structure of a logical network whose links were invisible. Network structure had to be inferred from the behavior of the components after a failure. It was hypothesized that since such failure diagnosis tasks often draw on spatial processes, a good deal of spatial complexity in the network should affect network discovery. Results show that the ability to discover the linkages in the network is directly related to the spatial complexity of the pathway described by the linkages. This effect was generally independent of the amount of evidence available to subjects about the existence of the link. These results raise the question of whether inferences about spatially complex pathways were simply not made, or whether they were made but not retained because of a high load on memory resources.

Mind the Scales: Harnessing Spatial Big Data for Infectious Disease Surveillance and Inference.

PubMed

Lee, Elizabeth C; Asher, Jason M; Goldlust, Sandra; Kraemer, John D; Lawson, Andrew B; Bansal, Shweta

2016-12-01

Spatial big data have the velocity, volume, and variety of big data sources and contain additional geographic information. Digital data sources, such as medical claims, mobile phone call data records, and geographically tagged tweets, have entered infectious diseases epidemiology as novel sources of data to complement traditional infectious disease surveillance. In this work, we provide examples of how spatial big data have been used thus far in epidemiological analyses and describe opportunities for these sources to improve disease-mitigation strategies and public health coordination. In addition, we consider the technical, practical, and ethical challenges with the use of spatial big data in infectious disease surveillance and inference. Finally, we discuss the implications of the rising use of spatial big data in epidemiology to health risk communication, and public health policy recommendations and coordination across scales. © The Author 2016. Published by Oxford University Press for the Infectious Diseases Society of America.

Stratification Modelling of Key Bacterial Taxa Driven by Metabolic Dynamics in Meromictic Lakes.

PubMed

Zhu, Kaicheng; Lauro, Federico M; Su, Haibin

2018-06-22

In meromictic lakes, the water column is stratified into distinguishable steady layers with different physico-chemical properties. The bottom portion, known as monimolimnion, has been studied for the functional stratification of microbial populations. Recent experiments have reported the profiles of bacterial and nutrient spatial distributions, but quantitative understanding is invoked to unravel the underlying mechanism of maintaining the discrete spatial organization. Here a reaction-diffusion model is developed to highlight the spatial pattern coupled with the light-driven metabolism of bacteria, which is resilient to a wide range of dynamical correlation between bacterial and nutrient species at the molecular level. Particularly, exact analytical solutions of the system are presented together with numerical results, in a good agreement with measurements in Ace lake and Rogoznica lake. Furthermore, one quantitative prediction is reported here on the dynamics of the seasonal stratification patterns in Ace lake. The active role played by the bacterial metabolism at microscale clearly shapes the biogeochemistry landscape of lake-wide ecology at macroscale.

Solving the problem of comparing whole bacterial genomes across different sequencing platforms.

PubMed

Kaas, Rolf S; Leekitcharoenphon, Pimlapas; Aarestrup, Frank M; Lund, Ole

2014-01-01

Whole genome sequencing (WGS) shows great potential for real-time monitoring and identification of infectious disease outbreaks. However, rapid and reliable comparison of data generated in multiple laboratories and using multiple technologies is essential. So far studies have focused on using one technology because each technology has a systematic bias making integration of data generated from different platforms difficult. We developed two different procedures for identifying variable sites and inferring phylogenies in WGS data across multiple platforms. The methods were evaluated on three bacterial data sets and sequenced on three different platforms (Illumina, 454, Ion Torrent). We show that the methods are able to overcome the systematic biases caused by the sequencers and infer the expected phylogenies. It is concluded that the cause of the success of these new procedures is due to a validation of all informative sites that are included in the analysis. The procedures are available as web tools.

A novel on-line spatial-temporal k-anonymity method for location privacy protection from sequence rules-based inference attacks.

PubMed

Zhang, Haitao; Wu, Chenxue; Chen, Zewei; Liu, Zhao; Zhu, Yunhong

2017-01-01

Analyzing large-scale spatial-temporal k-anonymity datasets recorded in location-based service (LBS) application servers can benefit some LBS applications. However, such analyses can allow adversaries to make inference attacks that cannot be handled by spatial-temporal k-anonymity methods or other methods for protecting sensitive knowledge. In response to this challenge, first we defined a destination location prediction attack model based on privacy-sensitive sequence rules mined from large scale anonymity datasets. Then we proposed a novel on-line spatial-temporal k-anonymity method that can resist such inference attacks. Our anti-attack technique generates new anonymity datasets with awareness of privacy-sensitive sequence rules. The new datasets extend the original sequence database of anonymity datasets to hide the privacy-sensitive rules progressively. The process includes two phases: off-line analysis and on-line application. In the off-line phase, sequence rules are mined from an original sequence database of anonymity datasets, and privacy-sensitive sequence rules are developed by correlating privacy-sensitive spatial regions with spatial grid cells among the sequence rules. In the on-line phase, new anonymity datasets are generated upon LBS requests by adopting specific generalization and avoidance principles to hide the privacy-sensitive sequence rules progressively from the extended sequence anonymity datasets database. We conducted extensive experiments to test the performance of the proposed method, and to explore the influence of the parameter K value. The results demonstrated that our proposed approach is faster and more effective for hiding privacy-sensitive sequence rules in terms of hiding sensitive rules ratios to eliminate inference attacks. Our method also had fewer side effects in terms of generating new sensitive rules ratios than the traditional spatial-temporal k-anonymity method, and had basically the same side effects in terms of non-sensitive rules variation ratios with the traditional spatial-temporal k-anonymity method. Furthermore, we also found the performance variation tendency from the parameter K value, which can help achieve the goal of hiding the maximum number of original sensitive rules while generating a minimum of new sensitive rules and affecting a minimum number of non-sensitive rules.

A novel on-line spatial-temporal k-anonymity method for location privacy protection from sequence rules-based inference attacks

PubMed Central

Wu, Chenxue; Liu, Zhao; Zhu, Yunhong

2017-01-01

Analyzing large-scale spatial-temporal k-anonymity datasets recorded in location-based service (LBS) application servers can benefit some LBS applications. However, such analyses can allow adversaries to make inference attacks that cannot be handled by spatial-temporal k-anonymity methods or other methods for protecting sensitive knowledge. In response to this challenge, first we defined a destination location prediction attack model based on privacy-sensitive sequence rules mined from large scale anonymity datasets. Then we proposed a novel on-line spatial-temporal k-anonymity method that can resist such inference attacks. Our anti-attack technique generates new anonymity datasets with awareness of privacy-sensitive sequence rules. The new datasets extend the original sequence database of anonymity datasets to hide the privacy-sensitive rules progressively. The process includes two phases: off-line analysis and on-line application. In the off-line phase, sequence rules are mined from an original sequence database of anonymity datasets, and privacy-sensitive sequence rules are developed by correlating privacy-sensitive spatial regions with spatial grid cells among the sequence rules. In the on-line phase, new anonymity datasets are generated upon LBS requests by adopting specific generalization and avoidance principles to hide the privacy-sensitive sequence rules progressively from the extended sequence anonymity datasets database. We conducted extensive experiments to test the performance of the proposed method, and to explore the influence of the parameter K value. The results demonstrated that our proposed approach is faster and more effective for hiding privacy-sensitive sequence rules in terms of hiding sensitive rules ratios to eliminate inference attacks. Our method also had fewer side effects in terms of generating new sensitive rules ratios than the traditional spatial-temporal k-anonymity method, and had basically the same side effects in terms of non-sensitive rules variation ratios with the traditional spatial-temporal k-anonymity method. Furthermore, we also found the performance variation tendency from the parameter K value, which can help achieve the goal of hiding the maximum number of original sensitive rules while generating a minimum of new sensitive rules and affecting a minimum number of non-sensitive rules. PMID:28767687

Tigers on trails: occupancy modeling for cluster sampling.

PubMed

Hines, J E; Nichols, J D; Royle, J A; MacKenzie, D I; Gopalaswamy, A M; Kumar, N Samba; Karanth, K U

2010-07-01

Occupancy modeling focuses on inference about the distribution of organisms over space, using temporal or spatial replication to allow inference about the detection process. Inference based on spatial replication strictly requires that replicates be selected randomly and with replacement, but the importance of these design requirements is not well understood. This paper focuses on an increasingly popular sampling design based on spatial replicates that are not selected randomly and that are expected to exhibit Markovian dependence. We develop two new occupancy models for data collected under this sort of design, one based on an underlying Markov model for spatial dependence and the other based on a trap response model with Markovian detections. We then simulated data under the model for Markovian spatial dependence and fit the data to standard occupancy models and to the two new models. Bias of occupancy estimates was substantial for the standard models, smaller for the new trap response model, and negligible for the new spatial process model. We also fit these models to data from a large-scale tiger occupancy survey recently conducted in Karnataka State, southwestern India. In addition to providing evidence of a positive relationship between tiger occupancy and habitat, model selection statistics and estimates strongly supported the use of the model with Markovian spatial dependence. This new model provides another tool for the decomposition of the detection process, which is sometimes needed for proper estimation and which may also permit interesting biological inferences. In addition to designs employing spatial replication, we note the likely existence of temporal Markovian dependence in many designs using temporal replication. The models developed here will be useful either directly, or with minor extensions, for these designs as well. We believe that these new models represent important additions to the suite of modeling tools now available for occupancy estimation in conservation monitoring. More generally, this work represents a contribution to the topic of cluster sampling for situations in which there is a need for specific modeling (e.g., reflecting dependence) for the distribution of the variable(s) of interest among subunits.

Filter forensics: microbiota recovery from residential HVAC filters.

PubMed

Maestre, Juan P; Jennings, Wiley; Wylie, Dennis; Horner, Sharon D; Siegel, Jeffrey; Kinney, Kerry A

2018-01-30

Establishing reliable methods for assessing the microbiome within the built environment is critical for understanding the impact of biological exposures on human health. High-throughput DNA sequencing of dust samples provides valuable insights into the microbiome present in human-occupied spaces. However, the effect that different sampling methods have on the microbial community recovered from dust samples is not well understood across sample types. Heating, ventilation, and air conditioning (HVAC) filters hold promise as long-term, spatially integrated, high volume samplers to characterize the airborne microbiome in homes and other climate-controlled spaces. In this study, the effect that dust recovery method (i.e., cut and elution, swabbing, or vacuuming) has on the microbial community structure, membership, and repeatability inferred by Illumina sequencing was evaluated. The results indicate that vacuum samples captured higher quantities of total, bacterial, and fungal DNA than swab or cut samples. Repeated swab and vacuum samples collected from the same filter were less variable than cut samples with respect to both quantitative DNA recovery and bacterial community structure. Vacuum samples captured substantially greater bacterial diversity than the other methods, whereas fungal diversity was similar across all three methods. Vacuum and swab samples of HVAC filter dust were repeatable and generally superior to cut samples. Nevertheless, the contribution of environmental and human sources to the bacterial and fungal communities recovered via each sampling method was generally consistent across the methods investigated. Dust recovery methodologies have been shown to affect the recovery, repeatability, structure, and membership of microbial communities recovered from dust samples in the built environment. The results of this study are directly applicable to indoor microbiota studies utilizing the filter forensics approach. More broadly, this study provides a better understanding of the microbial community variability attributable to sampling methodology and helps inform interpretation of data collected from other types of dust samples collected from indoor environments.

Analysis on the Spatial Difference of Bacterial Community Structure in Micro-pressure Air-lift Loop Reactor

NASA Astrophysics Data System (ADS)

Wan, L. G.; Lin, Q.; Bian, D. J.; Ren, Q. K.; Xiao, Y. B.; Lu, W. X.

2018-02-01

In order to reveal the spatial difference of the bacterial community structure in the Micro-pressure Air-lift Loop Reactor, the activated sludge bacterial at five different representative sites in the reactor were studied by denaturing gradient gel electrophoresis (DGGE). The results of DGGE showed that the difference of environmental conditions (such as substrate concentration, dissolved oxygen and PH, etc.) resulted in different diversity and similarity of microbial flora in different spatial locations. The Shannon-Wiener diversity index of the total bacterial samples from five sludge samples varied from 0.92 to 1.28, the biodiversity index was the smallest at point 5, and the biodiversity index was the highest at point 2. The similarity of the flora between the point 2, 3 and 4 was 80% or more, respectively. The similarity of the flora between the point 5 and the other samples was below 70%, and the similarity of point 2 was only 59.2%. Due to the different contribution of different strains to the removal of pollutants, it can give full play to the synergistic effect of bacterial degradation of pollutants, and further improve the efficiency of sewage treatment.

Molecular and Ecological Evidence for Species Specificity and Coevolution in a Group of Marine Algal-Bacterial Symbioses

PubMed Central

Ashen, Jon B.; Goff, Lynda J.

2000-01-01

The phylogenetic relationships of bacterial symbionts from three gall-bearing species in the marine red algal genus Prionitis (Rhodophyta) were inferred from 16S rDNA sequence analysis and compared to host phylogeny also inferred from sequence comparisons (nuclear ribosomal internal-transcribed-spacer region). Gall formation has been described previously on two species of Prionitis, P. lanceolata (from central California) and P. decipiens (from Peru). This investigation reports gall formation on a third related host, Prionitis filiformis. Phylogenetic analyses based on sequence comparisons place the bacteria as a single lineage within the Roseobacter grouping of the α subclass of the division Proteobacteria (99.4 to 98.25% sequence identity among phylotypes). Comparison of symbiont and host molecular phylogenies confirms the presence of three gall-bearing algal lineages and is consistent with the hypothesis that these red seaweeds and their bacterial symbionts are coevolving. The species specificity of these associations was investigated in nature by whole-cell hybridization of gall bacteria and in the laboratory by using cross-inoculation trials. Whole-cell in situ hybridization confirmed that a single bacterial symbiont phylotype is present in galls on each host. In laboratory trials, bacterial symbionts were incapable of inducing galls on alternate hosts (including two non-gall-bearing species). Symbiont-host specificity in Prionitis gall formation indicates an effective ecological separation between these closely related symbiont phylotypes and provides an example of a biological context in which to consider the organismic significance of 16S rDNA sequence variation. PMID:10877801

Differentiation of bacterial colonies and temporal growth patterns using hyperspectral imaging

NASA Astrophysics Data System (ADS)

Mehrübeoglu, Mehrube; Buck, Gregory W.; Livingston, Daniel W.

2014-09-01

Detection and identification of bacteria are important for health and safety. Hyperspectral imaging offers the potential to capture unique spectral patterns and spatial information from bacteria which can then be used to detect and differentiate bacterial species. Here, hyperspectral imaging has been used to characterize different bacterial colonies and investigate their growth over time. Six bacterial species (Pseudomonas fluorescens, Escherichia coli, Serratia marcescens, Salmonella enterica, Staphylococcus aureus, Enterobacter aerogenes) were grown on tryptic soy agar plates. Hyperspectral data were acquired immediately after, 24 hours after, and 96 hours after incubation. Spectral signatures from bacterial colonies demonstrated repeatable measurements for five out of six species. Spatial variations as well as changes in spectral signatures were observed across temporal measurements within and among species at multiple wavelengths due to strengthening or weakening reflectance signals from growing bacterial colonies based on their pigmentation. Between-class differences and within-class similarities were the most prominent in hyperspectral data collected 96 hours after incubation.

From broadscale patterns to fine-scale processes: habitat structure influences genetic differentiation in the pitcher plant midge across multiple spatial scales.

PubMed

Rasic, Gordana; Keyghobadi, Nusha

2012-01-01

The spatial scale at which samples are collected and analysed influences the inferences that can be drawn from landscape genetic studies. We examined genetic structure and its landscape correlates in the pitcher plant midge, Metriocnemus knabi, an inhabitant of the purple pitcher plant, Sarracenia purpurea, across several spatial scales that are naturally delimited by the midge's habitat (leaf, plant, cluster of plants, bog and system of bogs). We analysed 11 microsatellite loci in 710 M. knabi larvae from two systems of bogs in Algonquin Provincial Park (Canada) and tested the hypotheses that variables related to habitat structure are associated with genetic differentiation in this midge. Up to 54% of variation in individual-based genetic distances at several scales was explained by broadscale landscape variables of bog size, pitcher plant density within bogs and connectivity of pitcher plant clusters. Our results indicate that oviposition behaviour of females at fine scales, as inferred from the spatial locations of full-sib larvae, and spatially limited gene flow at broad scales represent the important processes underlying observed genetic patterns in M. knabi. Broadscale landscape features (bog size and plant density) appear to influence oviposition behaviour of midges, which in turn influences the patterns of genetic differentiation observed at both fine and broad scales. Thus, we inferred linkages among genetic patterns, landscape patterns and ecological processes across spatial scales in M. knabi. Our results reinforce the value of exploring such links simultaneously across multiple spatial scales and landscapes when investigating genetic diversity within a species. © 2011 Blackwell Publishing Ltd.

Hierarchical spatial models for predicting pygmy rabbit distribution and relative abundance

USGS Publications Warehouse

Wilson, T.L.; Odei, J.B.; Hooten, M.B.; Edwards, T.C.

2010-01-01

Conservationists routinely use species distribution models to plan conservation, restoration and development actions, while ecologists use them to infer process from pattern. These models tend to work well for common or easily observable species, but are of limited utility for rare and cryptic species. This may be because honest accounting of known observation bias and spatial autocorrelation are rarely included, thereby limiting statistical inference of resulting distribution maps. We specified and implemented a spatially explicit Bayesian hierarchical model for a cryptic mammal species (pygmy rabbit Brachylagus idahoensis). Our approach used two levels of indirect sign that are naturally hierarchical (burrows and faecal pellets) to build a model that allows for inference on regression coefficients as well as spatially explicit model parameters. We also produced maps of rabbit distribution (occupied burrows) and relative abundance (number of burrows expected to be occupied by pygmy rabbits). The model demonstrated statistically rigorous spatial prediction by including spatial autocorrelation and measurement uncertainty. We demonstrated flexibility of our modelling framework by depicting probabilistic distribution predictions using different assumptions of pygmy rabbit habitat requirements. Spatial representations of the variance of posterior predictive distributions were obtained to evaluate heterogeneity in model fit across the spatial domain. Leave-one-out cross-validation was conducted to evaluate the overall model fit. Synthesis and applications. Our method draws on the strengths of previous work, thereby bridging and extending two active areas of ecological research: species distribution models and multi-state occupancy modelling. Our framework can be extended to encompass both larger extents and other species for which direct estimation of abundance is difficult. ?? 2010 The Authors. Journal compilation ?? 2010 British Ecological Society.

Accounting for Non-Gaussian Sources of Spatial Correlation in Parametric Functional Magnetic Resonance Imaging Paradigms II: A Method to Obtain First-Level Analysis Residuals with Uniform and Gaussian Spatial Autocorrelation Function and Independent and Identically Distributed Time-Series.

PubMed

Gopinath, Kaundinya; Krishnamurthy, Venkatagiri; Lacey, Simon; Sathian, K

2018-02-01

In a recent study Eklund et al. have shown that cluster-wise family-wise error (FWE) rate-corrected inferences made in parametric statistical method-based functional magnetic resonance imaging (fMRI) studies over the past couple of decades may have been invalid, particularly for cluster defining thresholds less stringent than p < 0.001; principally because the spatial autocorrelation functions (sACFs) of fMRI data had been modeled incorrectly to follow a Gaussian form, whereas empirical data suggest otherwise. Hence, the residuals from general linear model (GLM)-based fMRI activation estimates in these studies may not have possessed a homogenously Gaussian sACF. Here we propose a method based on the assumption that heterogeneity and non-Gaussianity of the sACF of the first-level GLM analysis residuals, as well as temporal autocorrelations in the first-level voxel residual time-series, are caused by unmodeled MRI signal from neuronal and physiological processes as well as motion and other artifacts, which can be approximated by appropriate decompositions of the first-level residuals with principal component analysis (PCA), and removed. We show that application of this method yields GLM residuals with significantly reduced spatial correlation, nearly Gaussian sACF and uniform spatial smoothness across the brain, thereby allowing valid cluster-based FWE-corrected inferences based on assumption of Gaussian spatial noise. We further show that application of this method renders the voxel time-series of first-level GLM residuals independent, and identically distributed across time (which is a necessary condition for appropriate voxel-level GLM inference), without having to fit ad hoc stochastic colored noise models. Furthermore, the detection power of individual subject brain activation analysis is enhanced. This method will be especially useful for case studies, which rely on first-level GLM analysis inferences.

A Dasymetric-Based Monte Carlo Simulation Approach to the Probabilistic Analysis of Spatial Variables

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

Morton, April M; Piburn, Jesse O; McManamay, Ryan A

2017-01-01

Monte Carlo simulation is a popular numerical experimentation technique used in a range of scientific fields to obtain the statistics of unknown random output variables. Despite its widespread applicability, it can be difficult to infer required input probability distributions when they are related to population counts unknown at desired spatial resolutions. To overcome this challenge, we propose a framework that uses a dasymetric model to infer the probability distributions needed for a specific class of Monte Carlo simulations which depend on population counts.

Spatial structure and nutrients promote invasion of IncP-1 plasmids in bacterial populations

PubMed Central

Fox, Randal E; Zhong, Xue; Krone, Stephen M; Top, Eva M

2008-01-01

In spite of the importance of plasmids in bacterial adaptation, we have a poor understanding of their dynamics. It is not known if or how plasmids persist in and spread through (invade) a bacterial population when there is no selection for plasmid-encoded traits. Moreover, the differences in dynamics between spatially structured and mixed populations are poorly understood. Through a joint experimental/theoretical approach, we tested the hypothesis that self-transmissible IncP-1 plasmids can invade a bacterial population in the absence of selection when initially very rare, but only in spatially structured habitats and when nutrients are regularly replenished. Using protocols that differed in the degree of spatial structure and nutrient levels, the invasiveness of plasmid pB10 in Escherichia coli was monitored during at least 15 days, with an initial fraction of plasmid-bearing (p+) cells as low as 10−7. To further explore the mechanisms underlying plasmid dynamics, we developed a spatially explicit mathematical model. When cells were grown on filters and transferred to fresh medium daily, the p+ fraction increased to 13%, whereas almost complete invasion occurred when the population structure was disturbed daily. The plasmid was unable to invade in liquid. When carbon source levels were lower or not replenished, plasmid invasion was hampered. Simulations of the mathematical model closely matched the experimental results and produced estimates of the effects of alternative experimental parameters. This allowed us to isolate the likely mechanisms most responsible for the observations. In conclusion, spatial structure and nutrient availability can be key determinants in the invasiveness of plasmids. PMID:18528415

Seasonal and spatial patterns of heterotrophic bacterial production, respiration, and biomass in the subarctic NE Pacific

NASA Astrophysics Data System (ADS)

Sherry, Nelson D.; Boyd, Philip W.; Sugimoto, Kugako; Harrison, Paul J.

1999-11-01

Heterotrophic bacterial biomass, production, and respiration rates were measured during winter, spring, and summer in the subarctic NE Pacific from September 1995 to June 1997. Sampling took place on six cruises at five hydrographic stations along the east/west line-P transect from slope waters at P4 (1200 m depth) to the open-ocean waters at Ocean Station Papa (OSP) (4250 m depth). Interannual variability was small relative to seasonal and spatial variability. Biomass, derived from cell counts (assuming 20 fg C cell -1), was ca. 12 μg C l -1 in the winter and increased to 20-35 μg C l -1 in the spring and summer all along line-P. Bacterial production from [ 3H]-thymidine and [ 14C]-leucine incorporation rates was lowest in the winter (ca. 0.5 μg C l -1 d -1) with little spatial variability. Production increased 10-fold in spring at P4 (to ca. 4.5 μg C l -1 d -1). In contrast, only a 2-fold increase in bacterial production was observed over this period at the more oceanic stations. Rates of production in late summer were highest over the annual cycle at all stations ranging from ca. 6 at P4 to ca. 2 μg C l -1 d -1 at OSP. Bacterial (<1 μm size fraction) respiration, measured from dark-bottle O 2 consumption over 24 or 48 h, was <10 μg C l -1 d -1 during the winter and spring. Respiration rates increased >10-fold to ca. 100 μg C l -1 d -1 at P4 in the summer, but, interestingly, did not increase from spring to summer at the more oceanic stations. Thus bacterial growth efficiency, defined as production/(production+respiration), decreased in the spring westwards from the slope waters (P4) to the open-ocean (OSP), but increased westwards in the summer. Bacterial production was highly correlated with temperature at OSP ( r2=0.88) and less so at P4 ( r2=0.50). The observed temporal and spatial trends presented in this study suggest that seasonal changes in bacterial biomass were greatly affected by changes in loss processes, that bacterial biomass is regulated by different processes than bacterial production, and that bacterial production alone, without respiration measurements, is not a robust proxy for bacterial activity in the subarctic NE Pacific.

Mapping and determinism of soil microbial community distribution across an agricultural landscape.

PubMed

Constancias, Florentin; Terrat, Sébastien; Saby, Nicolas P A; Horrigue, Walid; Villerd, Jean; Guillemin, Jean-Philippe; Biju-Duval, Luc; Nowak, Virginie; Dequiedt, Samuel; Ranjard, Lionel; Chemidlin Prévost-Bouré, Nicolas

2015-06-01

Despite the relevance of landscape, regarding the spatial patterning of microbial communities and the relative influence of environmental parameters versus human activities, few investigations have been conducted at this scale. Here, we used a systematic grid to characterize the distribution of soil microbial communities at 278 sites across a monitored agricultural landscape of 13 km². Molecular microbial biomass was estimated by soil DNA recovery and bacterial diversity by 16S rRNA gene pyrosequencing. Geostatistics provided the first maps of microbial community at this scale and revealed a heterogeneous but spatially structured distribution of microbial biomass and diversity with patches of several hundreds of meters. Variance partitioning revealed that both microbial abundance and bacterial diversity distribution were highly dependent of soil properties and land use (total variance explained ranged between 55% and 78%). Microbial biomass and bacterial richness distributions were mainly explained by soil pH and texture whereas bacterial evenness distribution was mainly related to land management. Bacterial diversity (richness, evenness, and Shannon index) was positively influenced by cropping intensity and especially by soil tillage, resulting in spots of low microbial diversity in soils under forest management. Spatial descriptors also explained a small but significant portion of the microbial distribution suggesting that landscape configuration also shapes microbial biomass and bacterial diversity. © 2015 The Authors. MicrobiologyOpen published by John Wiley & Sons Ltd.

Estimating spatial variations in water content of clay soils from time-lapse electrical conductivity surveys

USDA-ARS?s Scientific Manuscript database

Soil water content (theta) is one of the most important drivers for many biogeochemical fluxes at different temporal and spatial scales. Hydrogeophysical non-invasive sensors that measure the soil apparent electrical conductivity (ECa) have been widely used to infer spatial and temporal patterns of...

Data-driven sensitivity inference for Thomson scattering electron density measurement systems.

PubMed

Fujii, Keisuke; Yamada, Ichihiro; Hasuo, Masahiro

2017-01-01

We developed a method to infer the calibration parameters of multichannel measurement systems, such as channel variations of sensitivity and noise amplitude, from experimental data. We regard such uncertainties of the calibration parameters as dependent noise. The statistical properties of the dependent noise and that of the latent functions were modeled and implemented in the Gaussian process kernel. Based on their statistical difference, both parameters were inferred from the data. We applied this method to the electron density measurement system by Thomson scattering for the Large Helical Device plasma, which is equipped with 141 spatial channels. Based on the 210 sets of experimental data, we evaluated the correction factor of the sensitivity and noise amplitude for each channel. The correction factor varies by ≈10%, and the random noise amplitude is ≈2%, i.e., the measurement accuracy increases by a factor of 5 after this sensitivity correction. The certainty improvement in the spatial derivative inference was demonstrated.

Cell shape can mediate the spatial organization of the bacterial cytoskeleton

NASA Astrophysics Data System (ADS)

Wang, Siyuan; Wingreen, Ned

2013-03-01

The bacterial cytoskeleton guides the synthesis of cell wall and thus regulates cell shape. Since spatial patterning of the bacterial cytoskeleton is critical to the proper control of cell shape, it is important to ask how the cytoskeleton spatially self-organizes in the first place. In this work, we develop a quantitative model to account for the various spatial patterns adopted by bacterial cytoskeletal proteins, especially the orientation and length of cytoskeletal filaments such as FtsZ and MreB in rod-shaped cells. We show that the combined mechanical energy of membrane bending, membrane pinning, and filament bending of a membrane-attached cytoskeletal filament can be sufficient to prescribe orientation, e.g. circumferential for FtsZ or helical for MreB, with the accuracy of orientation increasing with the length of the cytoskeletal filament. Moreover, the mechanical energy can compete with the chemical energy of cytoskeletal polymerization to regulate filament length. Notably, we predict a conformational transition with increasing polymer length from smoothly curved to end-bent polymers. Finally, the mechanical energy also results in a mutual attraction among polymers on the same membrane, which could facilitate tight polymer spacing or bundling. The predictions of the model can be verified through genetic, microscopic, and microfluidic approaches.

Spatial organization of transcription machinery and its segregation from the replisome in fast-growing bacterial cells

PubMed Central

Cagliero, Cedric; Zhou, Yan Ning; Jin, Ding Jun

2014-01-01

In a fast-growing Escherichia coli cell, most RNA polymerase (RNAP) is allocated to rRNA synthesis forming transcription foci at clusters of rrn operons or bacterial nucleolus, and each of the several nascent nucleoids contains multiple pairs of replication forks. The composition of transcription foci has not been determined. In addition, how the transcription machinery is three-dimensionally organized to promote cell growth in concord with replication machinery in the nucleoid remains essentially unknown. Here, we determine the spatial and functional landscapes of transcription and replication machineries in fast-growing E. coli cells using super-resolution-structured illumination microscopy. Co-images of RNAP and DNA reveal spatial compartmentation and duplication of the transcription foci at the surface of the bacterial chromosome, encompassing multiple nascent nucleoids. Transcription foci cluster with NusA and NusB, which are the rrn anti-termination system and are associated with nascent rRNAs. However, transcription foci tend to separate from SeqA and SSB foci, which track DNA replication forks and/or the replisomes, demonstrating that transcription machinery and replisome are mostly located in different chromosomal territories to maintain harmony between the two major cellular functions in fast-growing cells. Our study suggests that bacterial chromosomes are spatially and functionally organized, analogous to eukaryotes. PMID:25416798

Molecular Phylogenetic Diversity and Spatial Distribution of Bacterial Communities in Cooling Stage during Swine Manure Composting

PubMed Central

Guo, Yan; Zhang, Jinliang; Yan, Yongfeng; Wu, Jian; Zhu, Nengwu; Deng, Changyan

2015-01-01

Polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) and subsequent sub-cloning and sequencing were used in this study to analyze the molecular phylogenetic diversity and spatial distribution of bacterial communities in different spatial locations during the cooling stage of composted swine manure. Total microbial DNA was extracted, and bacterial near full-length 16S rRNA genes were subsequently amplified, cloned, RFLP-screened, and sequenced. A total of 420 positive clones were classified by RFLP and near-full-length 16S rDNA sequences. Approximately 48 operational taxonomic units (OTUs) were found among 139 positive clones from the superstratum sample; 26 among 149 were from the middle-level sample and 35 among 132 were from the substrate sample. Thermobifida fusca was common in the superstratum layer of the pile. Some Bacillus spp. were remarkable in the middle-level layer, and Clostridium sp. was dominant in the substrate layer. Among 109 OTUs, 99 displayed homology with those in the GenBank database. Ten OTUs were not closely related to any known species. The superstratum sample had the highest microbial diversity, and different and distinct bacterial communities were detected in the three different layers. This study demonstrated the spatial characteristics of the microbial community distribution in the cooling stage of swine manure compost. PMID:25925066

Adaptive web sampling.

PubMed

Thompson, Steven K

2006-12-01

A flexible class of adaptive sampling designs is introduced for sampling in network and spatial settings. In the designs, selections are made sequentially with a mixture distribution based on an active set that changes as the sampling progresses, using network or spatial relationships as well as sample values. The new designs have certain advantages compared with previously existing adaptive and link-tracing designs, including control over sample sizes and of the proportion of effort allocated to adaptive selections. Efficient inference involves averaging over sample paths consistent with the minimal sufficient statistic. A Markov chain resampling method makes the inference computationally feasible. The designs are evaluated in network and spatial settings using two empirical populations: a hidden human population at high risk for HIV/AIDS and an unevenly distributed bird population.

Predicted Bacterial Interactions Affect in Vivo Microbial Colonization Dynamics in Nematostella

PubMed Central

Domin, Hanna; Zurita-Gutiérrez, Yazmín H.; Scotti, Marco; Buttlar, Jann; Hentschel Humeida, Ute; Fraune, Sebastian

2018-01-01

The maintenance and resilience of host-associated microbiota during development is a fundamental process influencing the fitness of many organisms. Several host properties were identified as influencing factors on bacterial colonization, including the innate immune system, mucus composition, and diet. In contrast, the importance of bacteria–bacteria interactions on host colonization is less understood. Here, we use bacterial abundance data of the marine model organism Nematostella vectensis to reconstruct potential bacteria–bacteria interactions through co-occurrence networks. The analysis indicates that bacteria–bacteria interactions are dynamic during host colonization and change according to the host’s developmental stage. To assess the predictive power of inferred interactions, we tested bacterial isolates with predicted cooperative or competitive behavior for their ability to influence bacterial recolonization dynamics. Within 3 days of recolonization, all tested bacterial isolates affected bacterial community structure, while only competitive bacteria increased bacterial diversity. Only 1 week after recolonization, almost no differences in bacterial community structure could be observed between control and treatments. These results show that predicted competitive bacteria can influence community structure for a short period of time, verifying the in silico predictions. However, within 1 week, the effects of the bacterial isolates are neutralized, indicating a high degree of resilience of the bacterial community. PMID:29740401

Archaeal and Bacterial Communities Associated with the Surface Mucus of Caribbean Corals Differ in Their Degree of Host Specificity and Community Turnover Over Reefs.

PubMed

Frade, Pedro R; Roll, Katharina; Bergauer, Kristin; Herndl, Gerhard J

2016-01-01

Comparative studies on the distribution of archaeal versus bacterial communities associated with the surface mucus layer of corals have rarely taken place. It has therefore remained enigmatic whether mucus-associated archaeal and bacterial communities exhibit a similar specificity towards coral hosts and whether they vary in the same fashion over spatial gradients and between reef locations. We used microbial community profiling (terminal-restriction fragment length polymorphism, T-RFLP) and clone library sequencing of the 16S rRNA gene to compare the diversity and community structure of dominant archaeal and bacterial communities associating with the mucus of three common reef-building coral species (Porites astreoides, Siderastrea siderea and Orbicella annularis) over different spatial scales on a Caribbean fringing reef. Sampling locations included three reef sites, three reef patches within each site and two depths. Reference sediment samples and ambient water were also taken for each of the 18 sampling locations resulting in a total of 239 samples. While only 41% of the bacterial operational taxonomic units (OTUs) characterized by T-RFLP were shared between mucus and the ambient water or sediment, for archaeal OTUs this percentage was 2-fold higher (78%). About half of the mucus-associated OTUs (44% and 58% of bacterial and archaeal OTUs, respectively) were shared between the three coral species. Our multivariate statistical analysis (ANOSIM, PERMANOVA and CCA) showed that while the bacterial community composition was determined by habitat (mucus, sediment or seawater), host coral species, location and spatial distance, the archaeal community composition was solely determined by the habitat. This study highlights that mucus-associated archaeal and bacterial communities differ in their degree of community turnover over reefs and in their host-specificity.

Spatial organization of bacterial chromosomes

PubMed Central

Wang, Xindan; Rudner, David Z.

2014-01-01

Bacterial chromosomes are organized in stereotypical patterns that are faithfully and robustly regenerated in daughter cells. Two distinct spatial patterns were described almost a decade ago in our most tractable model organisms. In recent years, analysis of chromosome organization in a larger and more diverse set of bacteria and a deeper characterization of chromosome dynamics in the original model systems have provided a broader and more complete picture of both chromosome organization and the activities that generate the observed spatial patterns. Here, we summarize these different patterns highlighting similarities and differences and discuss the protein factors that help establish and maintain them. PMID:25460798

Assessing the resolution-dependent utility of tomograms for geostatistics

USGS Publications Warehouse

Day-Lewis, F. D.; Lane, J.W.

2004-01-01

Geophysical tomograms are used increasingly as auxiliary data for geostatistical modeling of aquifer and reservoir properties. The correlation between tomographic estimates and hydrogeologic properties is commonly based on laboratory measurements, co-located measurements at boreholes, or petrophysical models. The inferred correlation is assumed uniform throughout the interwell region; however, tomographic resolution varies spatially due to acquisition geometry, regularization, data error, and the physics underlying the geophysical measurements. Blurring and inversion artifacts are expected in regions traversed by few or only low-angle raypaths. In the context of radar traveltime tomography, we derive analytical models for (1) the variance of tomographic estimates, (2) the spatially variable correlation with a hydrologic parameter of interest, and (3) the spatial covariance of tomographic estimates. Synthetic examples demonstrate that tomograms of qualitative value may have limited utility for geostatistics; moreover, the imprint of regularization may preclude inference of meaningful spatial statistics from tomograms.

Accounting for Non-Gaussian Sources of Spatial Correlation in Parametric Functional Magnetic Resonance Imaging Paradigms I: Revisiting Cluster-Based Inferences.

PubMed

Gopinath, Kaundinya; Krishnamurthy, Venkatagiri; Sathian, K

2018-02-01

In a recent study, Eklund et al. employed resting-state functional magnetic resonance imaging data as a surrogate for null functional magnetic resonance imaging (fMRI) datasets and posited that cluster-wise family-wise error (FWE) rate-corrected inferences made by using parametric statistical methods in fMRI studies over the past two decades may have been invalid, particularly for cluster defining thresholds less stringent than p < 0.001; this was principally because the spatial autocorrelation functions (sACF) of fMRI data had been modeled incorrectly to follow a Gaussian form, whereas empirical data suggested otherwise. Here, we show that accounting for non-Gaussian signal components such as those arising from resting-state neural activity as well as physiological responses and motion artifacts in the null fMRI datasets yields first- and second-level general linear model analysis residuals with nearly uniform and Gaussian sACF. Further comparison with nonparametric permutation tests indicates that cluster-based FWE corrected inferences made with Gaussian spatial noise approximations are valid.

Transmission network of the 2014-2015 Ebola epidemic in Sierra Leone.

PubMed

Yang, Wan; Zhang, Wenyi; Kargbo, David; Yang, Ruifu; Chen, Yong; Chen, Zeliang; Kamara, Abdul; Kargbo, Brima; Kandula, Sasikiran; Karspeck, Alicia; Liu, Chao; Shaman, Jeffrey

2015-11-06

Understanding the growth and spatial expansion of (re)emerging infectious disease outbreaks, such as Ebola and avian influenza, is critical for the effective planning of control measures; however, such efforts are often compromised by data insufficiencies and observational errors. Here, we develop a spatial-temporal inference methodology using a modified network model in conjunction with the ensemble adjustment Kalman filter, a Bayesian inference method equipped to handle observational errors. The combined method is capable of revealing the spatial-temporal progression of infectious disease, while requiring only limited, readily compiled data. We use this method to reconstruct the transmission network of the 2014-2015 Ebola epidemic in Sierra Leone and identify source and sink regions. Our inference suggests that, in Sierra Leone, transmission within the network introduced Ebola to neighbouring districts and initiated self-sustaining local epidemics; two of the more populous and connected districts, Kenema and Port Loko, facilitated two independent transmission pathways. Epidemic intensity differed by district, was highly correlated with population size (r = 0.76, p = 0.0015) and a critical window of opportunity for containing local Ebola epidemics at the source (ca one month) existed. This novel methodology can be used to help identify and contain the spatial expansion of future (re)emerging infectious disease outbreaks. © 2015 The Author(s).

Data integration for inference about spatial processes: A model-based approach to test and account for data inconsistency

PubMed Central

Pedrini, Paolo; Bragalanti, Natalia; Groff, Claudio

2017-01-01

Recently-developed methods that integrate multiple data sources arising from the same ecological processes have typically utilized structured data from well-defined sampling protocols (e.g., capture-recapture and telemetry). Despite this new methodological focus, the value of opportunistic data for improving inference about spatial ecological processes is unclear and, perhaps more importantly, no procedures are available to formally test whether parameter estimates are consistent across data sources and whether they are suitable for integration. Using data collected on the reintroduced brown bear population in the Italian Alps, a population of conservation importance, we combined data from three sources: traditional spatial capture-recapture data, telemetry data, and opportunistic data. We developed a fully integrated spatial capture-recapture (SCR) model that included a model-based test for data consistency to first compare model estimates using different combinations of data, and then, by acknowledging data-type differences, evaluate parameter consistency. We demonstrate that opportunistic data lend itself naturally to integration within the SCR framework and highlight the value of opportunistic data for improving inference about space use and population size. This is particularly relevant in studies of rare or elusive species, where the number of spatial encounters is usually small and where additional observations are of high value. In addition, our results highlight the importance of testing and accounting for inconsistencies in spatial information from structured and unstructured data so as to avoid the risk of spurious or averaged estimates of space use and consequently, of population size. Our work supports the use of a single modeling framework to combine spatially-referenced data while also accounting for parameter consistency. PMID:28973034

Accounting for the measurement error of spectroscopically inferred soil carbon data for improved precision of spatial predictions.

PubMed

Somarathna, P D S N; Minasny, Budiman; Malone, Brendan P; Stockmann, Uta; McBratney, Alex B

2018-08-01

Spatial modelling of environmental data commonly only considers spatial variability as the single source of uncertainty. In reality however, the measurement errors should also be accounted for. In recent years, infrared spectroscopy has been shown to offer low cost, yet invaluable information needed for digital soil mapping at meaningful spatial scales for land management. However, spectrally inferred soil carbon data are known to be less accurate compared to laboratory analysed measurements. This study establishes a methodology to filter out the measurement error variability by incorporating the measurement error variance in the spatial covariance structure of the model. The study was carried out in the Lower Hunter Valley, New South Wales, Australia where a combination of laboratory measured, and vis-NIR and MIR inferred topsoil and subsoil soil carbon data are available. We investigated the applicability of residual maximum likelihood (REML) and Markov Chain Monte Carlo (MCMC) simulation methods to generate parameters of the Matérn covariance function directly from the data in the presence of measurement error. The results revealed that the measurement error can be effectively filtered-out through the proposed technique. When the measurement error was filtered from the data, the prediction variance almost halved, which ultimately yielded a greater certainty in spatial predictions of soil carbon. Further, the MCMC technique was successfully used to define the posterior distribution of measurement error. This is an important outcome, as the MCMC technique can be used to estimate the measurement error if it is not explicitly quantified. Although this study dealt with soil carbon data, this method is amenable for filtering the measurement error of any kind of continuous spatial environmental data. Copyright © 2018 Elsevier B.V. All rights reserved.

Spatially resolved X-ray emission measurements of the residual velocity during the stagnation phase of inertial confinement fusion implosion experiments

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

Ruby, J. J.; Pak, A., E-mail: pak5@llnl.gov; Field, J. E.

2016-07-15

A technique for measuring residual motion during the stagnation phase of an indirectly driven inertial confinement experiment has been implemented. This method infers a velocity from spatially and temporally resolved images of the X-ray emission from two orthogonal lines of sight. This work investigates the accuracy of recovering spatially resolved velocities from the X-ray emission data. A detailed analytical and numerical modeling of the X-ray emission measurement shows that the accuracy of this method increases as the displacement that results from a residual velocity increase. For the typical experimental configuration, signal-to-noise ratios, and duration of X-ray emission, it is estimatedmore » that the fractional error in the inferred velocity rises above 50% as the velocity of emission falls below 24 μm/ns. By inputting measured parameters into this model, error estimates of the residual velocity as inferred from the X-ray emission measurements are now able to be generated for experimental data. Details of this analysis are presented for an implosion experiment conducted with an unintentional radiation flux asymmetry. The analysis shows a bright localized region of emission that moves through the larger emitting volume at a relatively higher velocity towards the location of the imposed flux deficit. This technique allows for the possibility of spatially resolving velocity flows within the so-called central hot spot of an implosion. This information would help to refine our interpretation of the thermal temperature inferred from the neutron time of flight detectors and the effect of localized hydrodynamic instabilities during the stagnation phase. Across several experiments, along a single line of sight, the average difference in magnitude and direction of the measured residual velocity as inferred from the X-ray and neutron time of flight detectors was found to be ∼13 μm/ns and ∼14°, respectively.« less

Spatially resolved X-ray emission measurements of the residual velocity during the stagnation phase of inertial confinement fusion implosion experiments

DOE PAGES

Ruby, J. J.; Pak, A.; Field, J. E.; ...

2016-07-01

A technique for measuring residual motion during the stagnation phase of an indirectly driven inertial confinement experiment has been implemented. Our method infers a velocity from spatially and temporally resolved images of the X-ray emission from two orthogonal lines of sight. This work investigates the accuracy of recovering spatially resolved velocities from the X-ray emission data. A detailed analytical and numerical modeling of the X-ray emission measurement shows that the accuracy of this method increases as the displacement that results from a residual velocity increase. For the typical experimental configuration, signal-to-noise ratios, and duration of X-ray emission, it is estimatedmore » that the fractional error in the inferred velocity rises above 50% as the velocity of emission falls below 24 μm/ns. Furthermore, by inputting measured parameters into this model, error estimates of the residual velocity as inferred from the X-ray emission measurements are now able to be generated for experimental data. Details of this analysis are presented for an implosion experiment conducted with an unintentional radiation flux asymmetry. The analysis shows a bright localized region of emission that moves through the larger emitting volume at a relatively higher velocity towards the location of the imposed flux deficit. Our technique allows for the possibility of spatially resolving velocity flows within the so-called central hot spot of an implosion. This information would help to refine our interpretation of the thermal temperature inferred from the neutron time of flight detectors and the effect of localized hydrodynamic instabilities during the stagnation phase. Across several experiments, along a single line of sight, the average difference in magnitude and direction of the measured residual velocity as inferred from the X-ray and neutron time of flight detectors was found to be ~13 μm/ns and ~14°, respectively.« less

Evaluating species richness: biased ecological inference results from spatial heterogeneity in species detection probabilities

USGS Publications Warehouse

McNew, Lance B.; Handel, Colleen M.

2015-01-01

Accurate estimates of species richness are necessary to test predictions of ecological theory and evaluate biodiversity for conservation purposes. However, species richness is difficult to measure in the field because some species will almost always be overlooked due to their cryptic nature or the observer's failure to perceive their cues. Common measures of species richness that assume consistent observability across species are inviting because they may require only single counts of species at survey sites. Single-visit estimation methods ignore spatial and temporal variation in species detection probabilities related to survey or site conditions that may confound estimates of species richness. We used simulated and empirical data to evaluate the bias and precision of raw species counts, the limiting forms of jackknife and Chao estimators, and multi-species occupancy models when estimating species richness to evaluate whether the choice of estimator can affect inferences about the relationships between environmental conditions and community size under variable detection processes. Four simulated scenarios with realistic and variable detection processes were considered. Results of simulations indicated that (1) raw species counts were always biased low, (2) single-visit jackknife and Chao estimators were significantly biased regardless of detection process, (3) multispecies occupancy models were more precise and generally less biased than the jackknife and Chao estimators, and (4) spatial heterogeneity resulting from the effects of a site covariate on species detection probabilities had significant impacts on the inferred relationships between species richness and a spatially explicit environmental condition. For a real dataset of bird observations in northwestern Alaska, the four estimation methods produced different estimates of local species richness, which severely affected inferences about the effects of shrubs on local avian richness. Overall, our results indicate that neglecting the effects of site covariates on species detection probabilities may lead to significant bias in estimation of species richness, as well as the inferred relationships between community size and environmental covariates.

Inferring the Chemotactic Strategy of P. putida and E. coli Using Modified Kramers-Moyal Coefficients

PubMed Central

Hintsche, Marius; Beta, Carsten; Stark, Holger

2017-01-01

Many bacteria perform a run-and-tumble random walk to explore their surrounding and to perform chemotaxis. In this article we present a novel method to infer the relevant parameters of bacterial motion from experimental trajectories including the tumbling events. We introduce a stochastic model for the orientation angle, where a shot-noise process initiates tumbles, and analytically calculate conditional moments, reminiscent of Kramers-Moyal coefficients. Matching them with the moments calculated from experimental trajectories of the bacteria E. coli and Pseudomonas putida, we are able to infer their respective tumble rates, the rotational diffusion constants, and the distributions of tumble angles in good agreement with results from conventional tumble recognizers. We also define a novel tumble recognizer, which explicitly quantifies the error in recognizing tumbles. In the presence of a chemical gradient we condition the moments on the bacterial direction of motion and thereby explore the chemotaxis strategy. For both bacteria we recover and quantify the classical chemotactic strategy, where the tumble rate is smallest along the chemical gradient. In addition, for E. coli we detect some cells, which bias their mean tumble angle towards smaller values. Our findings are supported by a scaling analysis of appropriate ratios of conditional moments, which are directly calculated from experimental data. PMID:28114420

The Construction of Visual-spatial Situation Models in Children's Reading and Their Relation to Reading Comprehension

PubMed Central

Barnes, Marcia A.; Raghubar, Kimberly P.; Faulkner, Heather; Denton, Carolyn A.

2014-01-01

Readers construct mental models of situations described by text to comprehend what they read, updating these situation models based on explicitly described and inferred information about causal, temporal, and spatial relations. Fluent adult readers update their situation models while reading narrative text based in part on spatial location information that is consistent with the perspective of the protagonist. The current study investigates whether children update spatial situation models in a similar way, whether there are age-related changes in children's formation of spatial situation models during reading, and whether measures of the ability to construct and update spatial situation models are predictive of reading comprehension. Typically-developing children from ages 9 through 16 years (n=81) were familiarized with a physical model of a marketplace. Then the model was covered, and children read stories that described the movement of a protagonist through the marketplace and were administered items requiring memory for both explicitly stated and inferred information about the character's movements. Accuracy of responses and response times were evaluated. Results indicated that: (a) location and object information during reading appeared to be activated and updated not simply from explicit text-based information but from a mental model of the real world situation described by the text; (b) this pattern showed no age-related differences; and (c) the ability to update the situation model of the text based on inferred information, but not explicitly stated information, was uniquely predictive of reading comprehension after accounting for word decoding. PMID:24315376

Investigation of multimodal forward scatter phenotyping from bacterial colonies

NASA Astrophysics Data System (ADS)

Kim, Huisung

A rapid, label-free, and elastic light scattering (ELS) based bacterial colony phenotyping technology, bacterial rapid detection using optical scattering technology (BARDOT) provides a successful classification of several bacterial genus and species. For a thorough understanding of the phenomena and overcoming the limitations of the previous design, five additional modalities from a bacterial colony: 3D morphology, spatial optical density (OD) distribution, spectral forward scattering pattern, spectral OD, and surface backward reflection pattern are proposed to enhance the classification/identification ratio, and the feasibilities of each modality are verified. For the verification, three different instruments: integrated colony morphology analyzer (ICMA), multi-spectral BARDOT (MS-BARDOT) , and multi-modal BARDOT (MM-BARDOT) are proposed and developed. The ICMA can measure 3D morphology and spatial OD distribution of the colony simultaneously. A commercialized confocal displacement meter is used to measure the profiles of the bacterial colonies, together with a custom built optical density measurement unit to interrogate the biophysics behind the collective behavior of a bacterial colony. The system delivers essential information related to the quantitative growth dynamics (height, diameter, aspect ratio, optical density) of the bacterial colony, as well as, a relationship in between the morphological characteristics of the bacterial colony and its forward scattering pattern. Two different genera: Escherichia coli O157:H7 EDL933, and Staphylococcus aureus ATCC 25923 are selected for the analysis of the spatially resolved growth dynamics, while, Bacillus spp. such as B. subtilis ATCC 6633, B. cereus ATCC 14579, B. thuringiensis DUP6044, B. polymyxa B719W, and B. megaterium DSP 81319, are interrogated since some of the Bacillus spp. provides strikingly different characteristics of ELS patterns, and the origin of the speckle patterns are successfully correlated with the 2-D spatial density map from the ICMA. The MS-BARDOT can measure multispectral elastic-light-scatter patterns of the bacterial colony and its spectral OD to overcome the inherent limits of the single-wavelength BARDOT. A theoretical model for spectral forward scatter patterns from a bacterial colony based on elastic light scatter is presented. The spectral forward scatter patterns are computed by scalar diffraction theory, and compared with experimental results of three discrete wavelengths (405 nm, 635 nm, and 904 nm). Both model and experiment results show an excellent agreement; a longer wavelength induces a wider ring width, a wider ring gap, a smaller pattern size, and smaller numbers of rings. Further analysis using spatial fast Fourier transform (SFFT) shows a good agreement; the spatial frequencies are increasing towards the inward direction, and the slope is inversely proportional to the incoming wavelength. Four major pathogenic bacterial genera (Escherichia coli O157:H7 EDL933, Listeria monocytogenes F4244, Salmonella enterica serovar Enteritidis PT21, and Staphylococcus aureus ATCC 25923) and the seven major Escherichia coli serovar (O26, O45, O103, O111, O121, O145, and O157) with 3-4 strains each are measured and analyzed with the proposed instrument and algorithm. The MM-BARDOT can measure six different modalities: 1) light microscopy, 2) 3D morphology map from confocal microscopy, 3) 3D optical density map, 4) spectral forward scattering pattern, 5) spectral OD, 6) surface backward reflection pattern, and 7) fluorescence of a bacterial colony without moving the specimen. A custom-built confocal microscope with a controller which can be easily attached to an infinity-corrected commercial microscope is designed and built. Since the current BARDOT needs additional information from a bacterial colony to enhance the identification/classification ratio for a lower hierarchy of bacterial taxonomy such as serovar or strain level, the approach can offer a series of coordinates matched and correlated bio-optical characteristics of a colony and enhance the classification accuracy of the previously introduced BARDOT system. Four major pathogenic bacterial genera: Escherichia coli O157:H7 EDL933, Listeria monocytogenes F4244, Salmonella enterica serovar Enteritidis PT21, and Staphylococcus aureus ATCC 25923 are measured and analyzed with the proposed instrument and algorithm. Also, a feasibility test for a smaller colony (up to 500 mum) classification utilizing a surface backward reflection pattern from the measurement is done, and shows a potential as an additional modality for the bacterial phenotyping.

Spatial language and converseness.

PubMed

Burigo, Michele; Coventry, Kenny R; Cangelosi, Angelo; Lynott, Dermot

2016-12-01

Typical spatial language sentences consist of describing the location of an object (the located object) in relation to another object (the reference object) as in "The book is above the vase". While it has been suggested that the properties of the located object (the book) are not translated into language because they are irrelevant when exchanging location information, it has been shown that the orientation of the located object affects the production and comprehension of spatial descriptions. In line with the claim that spatial language apprehension involves inferences about relations that hold between objects it has been suggested that during spatial language apprehension people use the orientation of the located object to evaluate whether the logical property of converseness (e.g., if "the book is above the vase" is true, then also "the vase is below the book" must be true) holds across the objects' spatial relation. In three experiments using sentence acceptability rating tasks we tested this hypothesis and demonstrated that when converseness is violated people's acceptability ratings of a scene's description are reduced indicating that people do take into account geometric properties of the located object and use it to infer logical spatial relations.

Spatial variations of bacterial community and its relationship with water chemistry in Sanya Bay, South China Sea as determined by DGGE fingerprinting and multivariate analysis.

PubMed

Ling, Juan; Zhang, Yan-Ying; Dong, Jun-De; Wang, You-Shao; Feng, Jing-Bing; Zhou, Wei-Hua

2015-10-01

Bacteria play important roles in the structure and function of marine food webs by utilizing nutrients and degrading the pollutants, and their distribution are determined by surrounding water chemistry to a certain extent. It is vital to investigate the bacterial community's structure and identifying the significant factors by controlling the bacterial distribution in the paper. Flow cytometry showed that the total bacterial abundance ranged from 5.27 × 10(5) to 3.77 × 10(6) cells/mL. Molecular fingerprinting technique, denaturing gradient gel electrophoresis (DGGE) followed by DNA sequencing has been employed to investigate the bacterial community composition. The results were then interpreted through multivariate statistical analysis and tended to explain its relationship to the environmental factors. A total of 270 bands at 83 different positions were detected in DGGE profiles and 29 distinct DGGE bands were sequenced. The predominant bacteria were related to Phyla Protebacteria species (31 %, nine sequences), Cyanobacteria (37.9 %, eleven sequences) and Actinobacteria (17.2 %, five sequences). Other phylogenetic groups identified including Firmicutes (6.9 %, two sequences), Bacteroidetes (3.5 %, one sequences) and Verrucomicrobia (3.5 %, one sequences). Conical correspondence analysis was used to elucidate the relationships between the bacterial community compositions and environmental factors. The results showed that the spatial variations in the bacterial community composition was significantly related to phosphate (P = 0.002, P < 0.01), dissolved organic carbon (P = 0.004, P < 0.01), chemical oxygen demand (P = 0.010, P < 0.05) and nitrite (P = 0.016, P < 0.05). This study revealed the spatial variations of bacterial community and significant environmental factors driving the bacterial composition shift. These results may be valuable for further investigation on the functional microbial structure and expression quantitatively under the polluted environments in the world.

Spatial and temporal features of the growth of a bacterial species colonizing the zebrafish gut.

PubMed

Jemielita, Matthew; Taormina, Michael J; Burns, Adam R; Hampton, Jennifer S; Rolig, Annah S; Guillemin, Karen; Parthasarathy, Raghuveer

2014-12-16

The vertebrate intestine is home to microbial ecosystems that play key roles in host development and health. Little is known about the spatial and temporal dynamics of these microbial communities, limiting our understanding of fundamental properties, such as their mechanisms of growth, propagation, and persistence. To address this, we inoculated initially germ-free zebrafish larvae with fluorescently labeled strains of an Aeromonas species, representing an abundant genus in the zebrafish gut. Using light sheet fluorescence microscopy to obtain three-dimensional images spanning the gut, we quantified the entire bacterial load, as founding populations grew from tens to tens of thousands of cells over several hours. The data yield the first ever measurements of the growth kinetics of a microbial species inside a live vertebrate intestine and show dynamics that robustly fit a logistic growth model. Intriguingly, bacteria were nonuniformly distributed throughout the gut, and bacterial aggregates showed considerably higher growth rates than did discrete individuals. The form of aggregate growth indicates intrinsically higher division rates for clustered bacteria, rather than surface-mediated agglomeration onto clusters. Thus, the spatial organization of gut bacteria both relative to the host and to each other impacts overall growth kinetics, suggesting that spatial characterizations will be an important input to predictive models of host-associated microbial community assembly. Our intestines are home to vast numbers of microbes that influence many aspects of health and disease. Though we now know a great deal about the constituents of the gut microbiota, we understand very little about their spatial structure and temporal dynamics in humans or in any animal: how microbial populations establish themselves, grow, fluctuate, and persist. To address this, we made use of a model organism, the zebrafish, and a new optical imaging technique, light sheet fluorescence microscopy, to visualize for the first time the colonization of a live, vertebrate gut by specific bacteria with sufficient resolution to quantify the population over a range from a few individuals to tens of thousands of bacterial cells. Our results provide unprecedented measures of bacterial growth kinetics and also show the influence of spatial structure on bacterial populations, which can be revealed only by direct imaging. Copyright © 2014 Jemielita et al.

What causes the spatial heterogeneity of bacterial flora in the intestine of zebrafish larvae?

PubMed

Yang, Jinyou; Shimogonya, Yuji; Ishikawa, Takuji

2018-06-07

Microbial flora in the intestine has been thoroughly investigated, as it plays an important role in the health of the host. Jemielita et al. (2014) showed experimentally that Aeromonas bacteria in the intestine of zebrafish larvae have a heterogeneous spatial distribution. Although bacterial aggregation is important biologically and clinically, there is no mathematical model describing the phenomenon and its mechanism remains largely unknown. In this study, we developed a computational model to describe the heterogeneous distribution of bacteria in the intestine of zebrafish larvae. The results showed that biological taxis could cause the bacterial aggregation. Intestinal peristalsis had the effect of reducing bacterial aggregation through mixing function. Using a scaling argument, we showed that the taxis velocity of bacteria must be larger than the sum of the diffusive velocity and background bulk flow velocity to induce bacterial aggregation. Our model and findings will be useful to further the scientific understanding of intestinal microbial flora. Copyright © 2018 Elsevier Ltd. All rights reserved.

Spatial and vertical distribution of bacterial community in the northern South China Sea.

PubMed

Sun, Fu-Lin; Wang, You-Shao; Wu, Mei-Lin; Sun, Cui-Ci; Cheng, Hao

2015-10-01

Microbial communities are highly diverse in coastal oceans and response rapidly with changing environments. Learning about this will help us understand the ecology of microbial populations in marine ecosystems. This study aimed to assess the spatial and vertical distributions of the bacterial community in the northern South China Sea. Multi-dimensional scaling analyses revealed structural differences of the bacterial community among sampling sites and vertical depth. Result also indicated that bacterial community in most sites had higher diversity in 0-75 m depths than those in 100-200 m depths. Bacterial community of samples was positively correlation with salinity and depth, whereas was negatively correlation with temperature. Proteobacteria and Cyanobacteria were the dominant groups, which accounted for the majority of sequences. The α-Proteobacteria was highly diverse, and sequences belonged to Rhodobacterales bacteria were dominant in all characterized sequences. The current data indicate that the Rhodobacterales bacteria, especially Roseobacter clade are the diverse group in the tropical waters.

Comparison of Channel Catfish and Blue Catfish Gut Microbiota Assemblages Shows Minimal Effects of Host Genetics on Microbial Structure and Inferred Function.

PubMed

Bledsoe, Jacob W; Waldbieser, Geoffrey C; Swanson, Kelly S; Peterson, Brian C; Small, Brian C

2018-01-01

The microbiota of teleost fish has gained a great deal of research attention within the past decade, with experiments suggesting that both host-genetics and environment are strong ecological forces shaping the bacterial assemblages of fish microbiomes. Despite representing great commercial and scientific importance, the catfish within the family Ictaluridae , specifically the blue and channel catfish, have received very little research attention directed toward their gut-associated microbiota using 16S rRNA gene sequencing. Within this study we utilize multiple genetically distinct strains of blue and channel catfish, verified via microsatellite genotyping, to further quantify the role of host-genetics in shaping the bacterial communities in the fish gut, while maintaining environmental and husbandry parameters constant. Comparisons of the gut microbiota among the two catfish species showed no differences in bacterial species richness (observed and Chao1) or overall composition (weighted and unweighted UniFrac) and UniFrac distances showed no correlation with host genetic distances (Rst) according to Mantel tests. The microbiota of environmental samples (diet and water) were found to be significantly more diverse than that of the catfish gut associated samples, suggesting that factors within the host were further regulating the bacterial communities, despite the lack of a clear connection between microbiota composition and host genotype. The catfish gut communities were dominated by the phyla Fusobacteria, Proteobacteria, and Firmicutes; however, differential abundance analysis between the two catfish species using analysis of composition of microbiomes detected two differential genera, Cetobacterium and Clostridium XI . The metagenomic pathway features inferred from our dataset suggests the catfish gut bacterial communities possess pathways beneficial to their host such as those involved in nutrient metabolism and antimicrobial biosynthesis, while also containing pathways involved in virulence factors of pathogens. Testing of the inferred KEGG (Kyoto Encyclopedia of Genes and Genomes) pathways by DESeq2 revealed minor difference in microbiota function, with only two metagenomic pathways detected as differentially abundant between the two catfish species. As the first study to characterize the gut microbiota of blue catfish, our study results have direct implications on future ictalurid catfish research. Additionally, our insight into the intrinsic factors driving microbiota structure has basic implications for the future study of fish gut microbiota.

Limitations to estimating bacterial cross-species transmission using genetic and genomic markers: inferences from simulation modeling

PubMed Central

Benavides, Julio A; Cross, Paul C; Luikart, Gordon; Creel, Scott

2014-01-01

Cross-species transmission (CST) of bacterial pathogens has major implications for human health, livestock, and wildlife management because it determines whether control actions in one species may have subsequent effects on other potential host species. The study of bacterial transmission has benefitted from methods measuring two types of genetic variation: variable number of tandem repeats (VNTRs) and single nucleotide polymorphisms (SNPs). However, it is unclear whether these data can distinguish between different epidemiological scenarios. We used a simulation model with two host species and known transmission rates (within and between species) to evaluate the utility of these markers for inferring CST. We found that CST estimates are biased for a wide range of parameters when based on VNTRs and a most parsimonious reconstructed phylogeny. However, estimations of CST rates lower than 5% can be achieved with relatively low bias using as low as 250 SNPs. CST estimates are sensitive to several parameters, including the number of mutations accumulated since introduction, stochasticity, the genetic difference of strains introduced, and the sampling effort. Our results suggest that, even with whole-genome sequences, unbiased estimates of CST will be difficult when sampling is limited, mutation rates are low, or for pathogens that were recently introduced. PMID:25469159

Bacterial growth laws reflect the evolutionary importance of energy efficiency.

PubMed

Maitra, Arijit; Dill, Ken A

2015-01-13

We are interested in the balance of energy and protein synthesis in bacterial growth. How has evolution optimized this balance? We describe an analytical model that leverages extensive literature data on growth laws to infer the underlying fitness landscape and to draw inferences about what evolution has optimized in Escherichia coli. Is E. coli optimized for growth speed, energy efficiency, or some other property? Experimental data show that at its replication speed limit, E. coli produces about four mass equivalents of nonribosomal proteins for every mass equivalent of ribosomes. This ratio can be explained if the cell's fitness function is the the energy efficiency of cells under fast growth conditions, indicating a tradeoff between the high energy costs of ribosomes under fast growth and the high energy costs of turning over nonribosomal proteins under slow growth. This model gives insight into some of the complex nonlinear relationships between energy utilization and ribosomal and nonribosomal production as a function of cell growth conditions.

Inferring Models of Bacterial Dynamics toward Point Sources

PubMed Central

Jashnsaz, Hossein; Nguyen, Tyler; Petrache, Horia I.; Pressé, Steve

2015-01-01

Experiments have shown that bacteria can be sensitive to small variations in chemoattractant (CA) concentrations. Motivated by these findings, our focus here is on a regime rarely studied in experiments: bacteria tracking point CA sources (such as food patches or even prey). In tracking point sources, the CA detected by bacteria may show very large spatiotemporal fluctuations which vary with distance from the source. We present a general statistical model to describe how bacteria locate point sources of food on the basis of stochastic event detection, rather than CA gradient information. We show how all model parameters can be directly inferred from single cell tracking data even in the limit of high detection noise. Once parameterized, our model recapitulates bacterial behavior around point sources such as the “volcano effect”. In addition, while the search by bacteria for point sources such as prey may appear random, our model identifies key statistical signatures of a targeted search for a point source given any arbitrary source configuration. PMID:26466373

PHYLOSCANNER: Inferring Transmission from Within- and Between-Host Pathogen Genetic Diversity

PubMed Central

Hall, Matthew; Ratmann, Oliver; Bonsall, David; Golubchik, Tanya; de Cesare, Mariateresa; Gall, Astrid; Cornelissen, Marion; Fraser, Christophe

2018-01-01

Abstract A central feature of pathogen genomics is that different infectious particles (virions and bacterial cells) within an infected individual may be genetically distinct, with patterns of relatedness among infectious particles being the result of both within-host evolution and transmission from one host to the next. Here, we present a new software tool, phyloscanner, which analyses pathogen diversity from multiple infected hosts. phyloscanner provides unprecedented resolution into the transmission process, allowing inference of the direction of transmission from sequence data alone. Multiply infected individuals are also identified, as they harbor subpopulations of infectious particles that are not connected by within-host evolution, except where recombinant types emerge. Low-level contamination is flagged and removed. We illustrate phyloscanner on both viral and bacterial pathogens, namely HIV-1 sequenced on Illumina and Roche 454 platforms, HCV sequenced with the Oxford Nanopore MinION platform, and Streptococcus pneumoniae with sequences from multiple colonies per individual. phyloscanner is available from https://github.com/BDI-pathogens/phyloscanner. PMID:29186559

High-resolution infrared thermography for capturing wildland fire behaviour - RxCADRE 2012

Treesearch

Joseph J. O’Brien; E. Louise Loudermilk; Benjamin Hornsby; Andrew T. Hudak; Benjamin C. Bright; Matthew B. Dickinson; J. Kevin Hiers; Casey Teske; Roger D. Ottmar

2016-01-01

Wildland fire radiant energy emission is one of the only measurements of combustion that can be made at wide spatial extents and high temporal and spatial resolutions. Furthermore, spatially and temporally explicit measurements are critical for making inferences about fire effects and useful for examining patterns of fire spread. In this study we describe our...

Lights, Camera, Action! Antimicrobial Peptide Mechanisms Imaged in Space and Time

PubMed Central

Choi, Heejun; Rangarajan, Nambirajan; Weisshaar, James C.

2015-01-01

Deeper understanding of the bacteriostatic and bactericidal mechanisms of antimicrobial peptides (AMPs) should help in the design of new antibacterial agents. Over several decades, a variety of biochemical assays have been applied to bulk bacterial cultures. While some of these bulk assays provide time resolution on the order of 1 min, they do not capture faster mechanistic events. Nor can they provide subcellular spatial information or discern cell-to-cell heterogeneity within the bacterial population. Single-cell, time-resolved imaging assays bring a completely new spatiotemporal dimension to AMP mechanistic studies. We review recent work that provides new insights into the timing, sequence, and spatial distribution of AMP-induced effects on bacterial cells. PMID:26691950

Modeling species distribution and change using random forest [Chapter 8

Treesearch

Jeffrey S. Evans; Melanie A. Murphy; Zachary A. Holden; Samuel A. Cushman

2011-01-01

Although inference is a critical component in ecological modeling, the balance between accurate predictions and inference is the ultimate goal in ecological studies (Peters 1991; De’ath 2007). Practical applications of ecology in conservation planning, ecosystem assessment, and bio-diversity are highly dependent on very accurate spatial predictions of...

Spatial scaling and multi-model inference in landscape genetics: Martes americana in northern Idaho

Treesearch

Tzeidle N. Wasserman; Samuel A. Cushman; Michael K. Schwartz; David O. Wallin

2010-01-01

Individual-based analyses relating landscape structure to genetic distances across complex landscapes enable rigorous evaluation of multiple alternative hypotheses linking landscape structure to gene flow. We utilize two extensions to increase the rigor of the individual-based causal modeling approach to inferring relationships between landscape patterns and gene flow...

Factors Driving Potential Ammonia Oxidation in Canadian Arctic Ecosystems: Does Spatial Scale Matter?

PubMed Central

Banerjee, Samiran

2012-01-01

Ammonia oxidation is a major process in nitrogen cycling, and it plays a key role in nitrogen limited soil ecosystems such as those in the arctic. Although mm-scale spatial dependency of ammonia oxidizers has been investigated, little is known about the field-scale spatial dependency of aerobic ammonia oxidation processes and ammonia-oxidizing archaeal and bacterial communities, particularly in arctic soils. The purpose of this study was to explore the drivers of ammonia oxidation at the field scale in cryosols (soils with permafrost within 1 m of the surface). We measured aerobic ammonia oxidation potential (both autotrophic and heterotrophic) and functional gene abundance (bacterial amoA and archaeal amoA) in 279 soil samples collected from three arctic ecosystems. The variability associated with quantifying genes was substantially less than the spatial variability observed in these soils, suggesting that molecular methods can be used reliably evaluate spatial dependency in arctic ecosystems. Ammonia-oxidizing archaeal and bacterial communities and aerobic ammonia oxidation were spatially autocorrelated. Gene abundances were spatially structured within 4 m, whereas biochemical processes were structured within 40 m. Ammonia oxidation was driven at small scales (<1m) by moisture and total organic carbon, whereas gene abundance and other edaphic factors drove ammonia oxidation at medium (1 to 10 m) and large (10 to 100 m) scales. In these arctic soils heterotrophs contributed between 29 and 47% of total ammonia oxidation potential. The spatial scale for aerobic ammonia oxidation genes differed from potential ammonia oxidation, suggesting that in arctic ecosystems edaphic, rather than genetic, factors are an important control on ammonia oxidation. PMID:22081570

Spatially Correlated Gene Expression in Bacterial Groups: The Role of Lineage History, Spatial Gradients, and Cell-Cell Interactions.

PubMed

van Vliet, Simon; Dal Co, Alma; Winkler, Annina R; Spriewald, Stefanie; Stecher, Bärbel; Ackermann, Martin

2018-04-25

Gene expression levels in clonal bacterial groups have been found to be spatially correlated. These correlations can partly be explained by the shared lineage history of nearby cells, although they could also arise from local cell-cell interactions. Here, we present a quantitative framework that allows us to disentangle the contributions of lineage history, long-range spatial gradients, and local cell-cell interactions to spatial correlations in gene expression. We study pathways involved in toxin production, SOS stress response, and metabolism in Escherichia coli microcolonies and find for all pathways that shared lineage history is the main cause of spatial correlations in gene expression levels. However, long-range spatial gradients and local cell-cell interactions also contributed to spatial correlations in SOS response, amino acid biosynthesis, and overall metabolic activity. Together, our data show that the phenotype of a cell is influenced by its lineage history and population context, raising the question of whether bacteria can arrange their activities in space to perform functions they cannot achieve alone. Copyright © 2018 Elsevier Inc. All rights reserved.

Mistaking geography for biology: inferring processes from species distributions.

PubMed

Warren, Dan L; Cardillo, Marcel; Rosauer, Dan F; Bolnick, Daniel I

2014-10-01

Over the past few decades, there has been a rapid proliferation of statistical methods that infer evolutionary and ecological processes from data on species distributions. These methods have led to considerable new insights, but they often fail to account for the effects of historical biogeography on present-day species distributions. Because the geography of speciation can lead to patterns of spatial and temporal autocorrelation in the distributions of species within a clade, this can result in misleading inferences about the importance of deterministic processes in generating spatial patterns of biodiversity. In this opinion article, we discuss ways in which patterns of species distributions driven by historical biogeography are often interpreted as evidence of particular evolutionary or ecological processes. We focus on three areas that are especially prone to such misinterpretations: community phylogenetics, environmental niche modelling, and analyses of beta diversity (compositional turnover of biodiversity). Crown Copyright © 2014. Published by Elsevier Ltd. All rights reserved.

Inference of Vohradský's Models of Genetic Networks by Solving Two-Dimensional Function Optimization Problems

PubMed Central

Kimura, Shuhei; Sato, Masanao; Okada-Hatakeyama, Mariko

2013-01-01

The inference of a genetic network is a problem in which mutual interactions among genes are inferred from time-series of gene expression levels. While a number of models have been proposed to describe genetic networks, this study focuses on a mathematical model proposed by Vohradský. Because of its advantageous features, several researchers have proposed the inference methods based on Vohradský's model. When trying to analyze large-scale networks consisting of dozens of genes, however, these methods must solve high-dimensional non-linear function optimization problems. In order to resolve the difficulty of estimating the parameters of the Vohradský's model, this study proposes a new method that defines the problem as several two-dimensional function optimization problems. Through numerical experiments on artificial genetic network inference problems, we showed that, although the computation time of the proposed method is not the shortest, the method has the ability to estimate parameters of Vohradský's models more effectively with sufficiently short computation times. This study then applied the proposed method to an actual inference problem of the bacterial SOS DNA repair system, and succeeded in finding several reasonable regulations. PMID:24386175

Inferring Plasmodium vivax Transmission Networks from Tempo-Spatial Surveillance Data

PubMed Central

Shi, Benyun; Liu, Jiming; Zhou, Xiao-Nong; Yang, Guo-Jing

2014-01-01

Background The transmission networks of Plasmodium vivax characterize how the parasite transmits from one location to another, which are informative and insightful for public health policy makers to accurately predict the patterns of its geographical spread. However, such networks are not apparent from surveillance data because P. vivax transmission can be affected by many factors, such as the biological characteristics of mosquitoes and the mobility of human beings. Here, we pay special attention to the problem of how to infer the underlying transmission networks of P. vivax based on available tempo-spatial patterns of reported cases. Methodology We first define a spatial transmission model, which involves representing both the heterogeneous transmission potential of P. vivax at individual locations and the mobility of infected populations among different locations. Based on the proposed transmission model, we further introduce a recurrent neural network model to infer the transmission networks from surveillance data. Specifically, in this model, we take into account multiple real-world factors, including the length of P. vivax incubation period, the impact of malaria control at different locations, and the total number of imported cases. Principal Findings We implement our proposed models by focusing on the P. vivax transmission among 62 towns in Yunnan province, People's Republic China, which have been experiencing high malaria transmission in the past years. By conducting scenario analysis with respect to different numbers of imported cases, we can (i) infer the underlying P. vivax transmission networks, (ii) estimate the number of imported cases for each individual town, and (iii) quantify the roles of individual towns in the geographical spread of P. vivax. Conclusion The demonstrated models have presented a general means for inferring the underlying transmission networks from surveillance data. The inferred networks will offer new insights into how to improve the predictability of P. vivax transmission. PMID:24516684

Temporal and spatial changes of microbial community in an industrial effluent receiving area in Hangzhou Bay.

PubMed

Zhang, Yan; Chen, Lujun; Sun, Renhua; Dai, Tianjiao; Tian, Jinping; Zheng, Wei; Wen, Donghui

2016-06-01

Anthropogenic activities usually contaminate water environments, and have led to the eutrophication of many estuaries and shifts in microbial communities. In this study, the temporal and spatial changes of the microbial community in an industrial effluent receiving area in Hangzhou Bay were investigated by 454 pyrosequencing. The bacterial community showed higher richness and biodiversity than the archaeal community in all sediments. Proteobacteria dominated in the bacterial communities of all the samples; Marine_Group_I and Methanomicrobia were the two dominant archaeal classes in the effluent receiving area. PCoA and AMOVA revealed strong seasonal but minor spatial changes in both bacterial and archaeal communities in the sediments. The seasonal changes of the bacterial community were less significant than those of the archaeal community, which mainly consisted of fluctuations in abundance of a large proportion of longstanding species rather than the appearance and disappearance of major archaeal species. Temperature was found to positively correlate with the dominant bacteria, Betaproteobacteria, and negatively correlate with the dominant archaea, Marine_Group_I; and might be the primary driving force for the seasonal variation of the microbial community. Copyright © 2016. Published by Elsevier B.V.

Disconnect of microbial structure and function: enzyme activities and bacterial communities in nascent stream corridors.

PubMed

Frossard, Aline; Gerull, Linda; Mutz, Michael; Gessner, Mark O

2012-03-01

A fundamental issue in microbial and general ecology is the question to what extent environmental conditions dictate the structure of communities and the linkages with functional properties of ecosystems (that is, ecosystem function). We approached this question by taking advantage of environmental gradients established in soil and sediments of small stream corridors in a recently created, early successional catchment. Specifically, we determined spatial and temporal patterns of bacterial community structure and their linkages with potential microbial enzyme activities along the hydrological flow paths of the catchment. Soil and sediments were sampled in a total of 15 sites on four occasions spread throughout a year. Denaturing gradient gel electrophoresis (DGGE) was used to characterize bacterial communities, and substrate analogs linked to fluorescent molecules served to track 10 different enzymes as specific measures of ecosystem function. Potential enzyme activities varied little among sites, despite contrasting environmental conditions, especially in terms of water availability. Temporal changes, in contrast, were pronounced and remarkably variable among the enzymes tested. This suggests much greater importance of temporal dynamics than spatial heterogeneity in affecting specific ecosystem functions. Most strikingly, bacterial community structure revealed neither temporal nor spatial patterns. The resulting disconnect between bacterial community structure and potential enzyme activities indicates high functional redundancy within microbial communities even in the physically and biologically simplified stream corridors of early successional landscapes.

Incidence of bacterial diseases associated with irrigation methods on onions (Allium cepa).

PubMed

Chorolque, A; Pozzo Ardizzi, C; Pellejero, G; Aschkar, G; García Navarro, F J; Jiménez Ballesta, R

2018-04-24

In the last decade, diseases of bacterial origin in onions have increased and this has led to significant losses in production. These diseases are currently observed in both the Old and New Worlds. The aim of the experimental work reported here was to evaluate whether the irrigation method influences the incidence of diseases of bacterial origin. In cases where the inoculum was natural, the initial incidence of Soft Bacterial Rot was not manifested in any treatment in the first year, whereas at the end of the conservation period all treatments had increased incidences of infection. Sprinkler irrigation (8%) was statistically differentiated from the other treatments, for which the final incidence was similar (4.5%). For all irrigation treatments, the final incidence of Bacterial Soft Rot decreased or remained stable towards the end of the cycle, with the exception of sprinkler irrigation in 2015, which increased. It can be inferred from the results that the irrigation method does have an influence on the incidence of diseases of bacterial origin in the post-harvest stage for onions. This article is protected by copyright. All rights reserved.

Spatially Resolved Mid-IR Spectra from Meteorites; Linking Composition, Crystallographic Orientation and Spectra on the Micro-Scale

NASA Astrophysics Data System (ADS)

Stephen, N. R.

2016-08-01

IR spectroscopy is used to infer composition of extraterrestrial bodies, comparing bulk spectra to databases of separate mineral phases. We extract spatially resolved meteorite-specific spectra from achondrites with respect to zonation and orientation.

Unraveling the processes shaping mammalian gut microbiomes over evolutionary time

PubMed Central

Groussin, Mathieu; Mazel, Florent; Sanders, Jon G.; Smillie, Chris S.; Lavergne, Sébastien; Thuiller, Wilfried; Alm, Eric J.

2017-01-01

Whether mammal–microbiome interactions are persistent and specific over evolutionary time is controversial. Here we show that host phylogeny and major dietary shifts have affected the distribution of different gut bacterial lineages and did so on vastly different bacterial phylogenetic resolutions. Diet mostly influences the acquisition of ancient and large microbial lineages. Conversely, correlation with host phylogeny is mostly seen among more recently diverged bacterial lineages, consistent with processes operating at similar timescales to host evolution. Considering microbiomes at appropriate phylogenetic scales allows us to model their evolution along the mammalian tree and to infer ancient diets from the predicted microbiomes of mammalian ancestors. Phylogenetic analyses support co-speciation as having a significant role in the evolution of mammalian gut microbiome compositions. Highly co-speciating bacterial genera are also associated with immune diseases in humans, laying a path for future studies that probe these co-speciating bacteria for signs of co-evolution. PMID:28230052

Comparison of cosmology and seabed acoustics measurements using statistical inference from maximum entropy

NASA Astrophysics Data System (ADS)

Knobles, David; Stotts, Steven; Sagers, Jason

2012-03-01

Why can one obtain from similar measurements a greater amount of information about cosmological parameters than seabed parameters in ocean waveguides? The cosmological measurements are in the form of a power spectrum constructed from spatial correlations of temperature fluctuations within the microwave background radiation. The seabed acoustic measurements are in the form of spatial correlations along the length of a spatial aperture. This study explores the above question from the perspective of posterior probability distributions obtained from maximizing a relative entropy functional. An answer is in part that the seabed in shallow ocean environments generally has large temporal and spatial inhomogeneities, whereas the early universe was a nearly homogeneous cosmological soup with small but important fluctuations. Acoustic propagation models used in shallow water acoustics generally do not capture spatial and temporal variability sufficiently well, which leads to model error dominating the statistical inference problem. This is not the case in cosmology. Further, the physics of the acoustic modes in cosmology is that of a standing wave with simple initial conditions, whereas for underwater acoustics it is a traveling wave in a strongly inhomogeneous bounded medium.

Bacterial community diversity of the deep-sea octocoral Paramuricea placomus.

PubMed

Kellogg, Christina A; Ross, Steve W; Brooke, Sandra D

2016-01-01

Compared to tropical corals, much less is known about deep-sea coral biology and ecology. Although the microbial communities of some deep-sea corals have been described, this is the first study to characterize the bacterial community associated with the deep-sea octocoral, Paramuricea placomus . Samples from five colonies of P. placomus were collected from Baltimore Canyon (379-382 m depth) in the Atlantic Ocean off the east coast of the United States of America. DNA was extracted from the coral samples and 16S rRNA gene amplicons were pyrosequenced using V4-V5 primers. Three samples sequenced deeply (>4,000 sequences each) and were further analyzed. The dominant microbial phylum was Proteobacteria, but other major phyla included Firmicutes and Planctomycetes. A conserved community of bacterial taxa held in common across the three P. placomus colonies was identified, comprising 68-90% of the total bacterial community depending on the coral individual. The bacterial community of P. placomus does not appear to include the genus Endozoicomonas , which has been found previously to be the dominant bacterial associate in several temperate and tropical gorgonians. Inferred functionality suggests the possibility of nitrogen cycling by the core bacterial community.

Bacterial community diversity of the deep-sea octocoral Paramuricea placomus

USGS Publications Warehouse

Kellogg, Christina A.; Ross, Steve W.; Brooke, Sandra D.

2016-01-01

Compared to tropical corals, much less is known about deep-sea coral biology and ecology. Although the microbial communities of some deep-sea corals have been described, this is the first study to characterize the bacterial community associated with the deep-sea octocoral, Paramuricea placomus. Samples from five colonies of P. placomus were collected from Baltimore Canyon (379–382 m depth) in the Atlantic Ocean off the east coast of the United States of America. DNA was extracted from the coral samples and 16S rRNA gene amplicons were pyrosequenced using V4-V5 primers. Three samples sequenced deeply (>4,000 sequences each) and were further analyzed. The dominant microbial phylum was Proteobacteria, but other major phyla included Firmicutes and Planctomycetes. A conserved community of bacterial taxa held in common across the three P. placomuscolonies was identified, comprising 68–90% of the total bacterial community depending on the coral individual. The bacterial community of P. placomusdoes not appear to include the genus Endozoicomonas, which has been found previously to be the dominant bacterial associate in several temperate and tropical gorgonians. Inferred functionality suggests the possibility of nitrogen cycling by the core bacterial community.

Mapping and predictive variations of soil bacterial richness across France

PubMed Central

Dequietd, Samuel; Saby, Nicolas P. A.; Lelièvre, Mélanie; Nowak, Virginie; Tripied, Julie; Régnier, Tiffanie; Jolivet, Claudy; Arrouays, Dominique; Wincker, Patrick; Cruaud, Corinne; Karimi, Battle; Bispo, Antonio; Maron, Pierre Alain; Chemidlin Prévost-Bouré, Nicolas; Ranjard, Lionel

2017-01-01

Although numerous studies have demonstrated the key role of bacterial diversity in soil functions and ecosystem services, little is known about the variations and determinants of such diversity on a nationwide scale. The overall objectives of this study were i) to describe the bacterial taxonomic richness variations across France, ii) to identify the ecological processes (i.e. selection by the environment and dispersal limitation) influencing this distribution, and iii) to develop a statistical predictive model of soil bacterial richness. We used the French Soil Quality Monitoring Network (RMQS), which covers all of France with 2,173 sites. The soil bacterial richness (i.e. OTU number) was determined by pyrosequencing 16S rRNA genes and related to the soil characteristics, climatic conditions, geomorphology, land use and space. Mapping of bacterial richness revealed a heterogeneous spatial distribution, structured into patches of about 111km, where the main drivers were the soil physico-chemical properties (18% of explained variance), the spatial descriptors (5.25%, 1.89% and 1.02% for the fine, medium and coarse scales, respectively), and the land use (1.4%). Based on these drivers, a predictive model was developed, which allows a good prediction of the bacterial richness (R2adj of 0.56) and provides a reference value for a given pedoclimatic condition. PMID:29059218

Mapping and predictive variations of soil bacterial richness across France.

PubMed

Terrat, Sébastien; Horrigue, Walid; Dequiedt, Samuel; Saby, Nicolas P A; Lelièvre, Mélanie; Nowak, Virginie; Tripied, Julie; Régnier, Tiffanie; Jolivet, Claudy; Arrouays, Dominique; Wincker, Patrick; Cruaud, Corinne; Karimi, Battle; Bispo, Antonio; Maron, Pierre Alain; Chemidlin Prévost-Bouré, Nicolas; Ranjard, Lionel

2017-01-01

Although numerous studies have demonstrated the key role of bacterial diversity in soil functions and ecosystem services, little is known about the variations and determinants of such diversity on a nationwide scale. The overall objectives of this study were i) to describe the bacterial taxonomic richness variations across France, ii) to identify the ecological processes (i.e. selection by the environment and dispersal limitation) influencing this distribution, and iii) to develop a statistical predictive model of soil bacterial richness. We used the French Soil Quality Monitoring Network (RMQS), which covers all of France with 2,173 sites. The soil bacterial richness (i.e. OTU number) was determined by pyrosequencing 16S rRNA genes and related to the soil characteristics, climatic conditions, geomorphology, land use and space. Mapping of bacterial richness revealed a heterogeneous spatial distribution, structured into patches of about 111km, where the main drivers were the soil physico-chemical properties (18% of explained variance), the spatial descriptors (5.25%, 1.89% and 1.02% for the fine, medium and coarse scales, respectively), and the land use (1.4%). Based on these drivers, a predictive model was developed, which allows a good prediction of the bacterial richness (R2adj of 0.56) and provides a reference value for a given pedoclimatic condition.

Network-scale spatial and temporal variation in Chinook salmon (Oncorhynchus tshawytscha) redd distributions: patterns inferred from spatially continuous replicate surveys

Treesearch

Daniel J. Isaak; Russell F. Thurow

2006-01-01

Spatially continuous sampling designs, when temporally replicated, provide analytical flexibility and are unmatched in their ability to provide a dynamic system view. We have compiled such a data set by georeferencing the network-scale distribution of Chinook salmon (Oncorhynchus tshawytscha) redds across a large wilderness basin (7330 km2) in...

Inferring controls on the epidemiology of beech bark disease from spatial patterning of disease organisms

Treesearch

Jeffrey R. Garnas; David R. Houston; Mark J. Twery; Matthew P. Ayres; Celia Evans

2013-01-01

Spatial pattern in the distribution and abundance of organisms is an emergent property of collective rates of reproduction, survival and movement of individuals in a heterogeneous environment. The form, intensity and scale of spatial patterning can be used to test hypotheses regarding the relative importance of candidate processes to population dynamics. Using 84 plots...

Genetic network inference as a series of discrimination tasks.

PubMed

Kimura, Shuhei; Nakayama, Satoshi; Hatakeyama, Mariko

2009-04-01

Genetic network inference methods based on sets of differential equations generally require a great deal of time, as the equations must be solved many times. To reduce the computational cost, researchers have proposed other methods for inferring genetic networks by solving sets of differential equations only a few times, or even without solving them at all. When we try to obtain reasonable network models using these methods, however, we must estimate the time derivatives of the gene expression levels with great precision. In this study, we propose a new method to overcome the drawbacks of inference methods based on sets of differential equations. Our method infers genetic networks by obtaining classifiers capable of predicting the signs of the derivatives of the gene expression levels. For this purpose, we defined a genetic network inference problem as a series of discrimination tasks, then solved the defined series of discrimination tasks with a linear programming machine. Our experimental results demonstrated that the proposed method is capable of correctly inferring genetic networks, and doing so more than 500 times faster than the other inference methods based on sets of differential equations. Next, we applied our method to actual expression data of the bacterial SOS DNA repair system. And finally, we demonstrated that our approach relates to the inference method based on the S-system model. Though our method provides no estimation of the kinetic parameters, it should be useful for researchers interested only in the network structure of a target system. Supplementary data are available at Bioinformatics online.

A necessarily complex model to explain the biogeography of the amphibians and reptiles of Madagascar.

PubMed

Brown, Jason L; Cameron, Alison; Yoder, Anne D; Vences, Miguel

2014-10-09

Pattern and process are inextricably linked in biogeographic analyses, though we can observe pattern, we must infer process. Inferences of process are often based on ad hoc comparisons using a single spatial predictor. Here, we present an alternative approach that uses mixed-spatial models to measure the predictive potential of combinations of hypotheses. Biodiversity patterns are estimated from 8,362 occurrence records from 745 species of Malagasy amphibians and reptiles. By incorporating 18 spatially explicit predictions of 12 major biogeographic hypotheses, we show that mixed models greatly improve our ability to explain the observed biodiversity patterns. We conclude that patterns are influenced by a combination of diversification processes rather than by a single predominant mechanism. A 'one-size-fits-all' model does not exist. By developing a novel method for examining and synthesizing spatial parameters such as species richness, endemism and community similarity, we demonstrate the potential of these analyses for understanding the diversification history of Madagascar's biota.

Deploying digital health data to optimize influenza surveillance at national and local scales

PubMed Central

Arab, Ali; Viboud, Cécile; Grenfell, Bryan T.; Bansal, Shweta

2018-01-01

The surveillance of influenza activity is critical to early detection of epidemics and pandemics and the design of disease control strategies. Case reporting through a voluntary network of sentinel physicians is a commonly used method of passive surveillance for monitoring rates of influenza-like illness (ILI) worldwide. Despite its ubiquity, little attention has been given to the processes underlying the observation, collection, and spatial aggregation of sentinel surveillance data, and its subsequent effects on epidemiological understanding. We harnessed the high specificity of diagnosis codes in medical claims from a database that represented 2.5 billion visits from upwards of 120,000 United States healthcare providers each year. Among influenza seasons from 2002-2009 and the 2009 pandemic, we simulated limitations of sentinel surveillance systems such as low coverage and coarse spatial resolution, and performed Bayesian inference to probe the robustness of ecological inference and spatial prediction of disease burden. Our models suggest that a number of socio-environmental factors, in addition to local population interactions, state-specific health policies, as well as sampling effort may be responsible for the spatial patterns in U.S. sentinel ILI surveillance. In addition, we find that biases related to spatial aggregation were accentuated among areas with more heterogeneous disease risk, and sentinel systems designed with fixed reporting locations across seasons provided robust inference and prediction. With the growing availability of health-associated big data worldwide, our results suggest mechanisms for optimizing digital data streams to complement traditional surveillance in developed settings and enhance surveillance opportunities in developing countries. PMID:29513661

Variance in composition of inquiline communities in leaves of Sarracenia purpurea L. on multiple spatial scales.

PubMed

Harvey, E; Miller, T E

1996-11-01

A survey of the abundances of species that inhabit the water-bearing leaves of the pitcher plant Sarracenia purpurea was conducted at several different spatial scales in northern Florida. Individual leaves are hosts to communities of inquiline species, including mosquitoes, midges, mites, copepods, cladocerans, and a diverse bacterial assemblage. Inquiline communities were quantified from four pitchers per plant, three plants per subpopulation, two subpopulations per population, and three populations. Species varied in abundance at different spatial scales. Variation in the abundances of mosquitoes and copepods was not significantly associated with any spatial scale. Midges varied in abundance at the level of populations; one population contained significantly more midges than the other two. Cladocerans varied at the level of the subpopulation, whereas mites varied at the level of the individual plants. Bacterial communities were described by means of Biolog plates, which quantify the types of carbon media used by the bacteria in each pitcher. Bacterial communities were found to vary significantly in composition among individual plants but not among populations or subpopulations. These results suggest that independent factors determining the abundances of individual species are important in determining community patterns in pitcher-plant inquilines.

A geostatistical analysis of small-scale spatial variability in bacterial abundance and community structure in salt marsh creek bank sediments

NASA Technical Reports Server (NTRS)

Franklin, Rima B.; Blum, Linda K.; McComb, Alison C.; Mills, Aaron L.

2002-01-01

Small-scale variations in bacterial abundance and community structure were examined in salt marsh sediments from Virginia's eastern shore. Samples were collected at 5 cm intervals (horizontally) along a 50 cm elevation gradient, over a 215 cm horizontal transect. For each sample, bacterial abundance was determined using acridine orange direct counts and community structure was analyzed using randomly amplified polymorphic DNA fingerprinting of whole-community DNA extracts. A geostatistical analysis was used to determine the degree of spatial autocorrelation among the samples, for each variable and each direction (horizontal and vertical). The proportion of variance in bacterial abundance that could be accounted for by the spatial model was quite high (vertical: 60%, horizontal: 73%); significant autocorrelation was found among samples separated by 25 cm in the vertical direction and up to 115 cm horizontally. In contrast, most of the variability in community structure was not accounted for by simply considering the spatial separation of samples (vertical: 11%, horizontal: 22%), and must reflect variability from other parameters (e.g., variation at other spatial scales, experimental error, or environmental heterogeneity). Microbial community patch size based upon overall similarity in community structure varied between 17 cm (vertical) and 35 cm (horizontal). Overall, variability due to horizontal position (distance from the creek bank) was much smaller than that due to vertical position (elevation) for both community properties assayed. This suggests that processes more correlated with elevation (e.g., drainage and redox potential) vary at a smaller scale (therefore producing smaller patch sizes) than processes controlled by distance from the creek bank. c2002 Federation of European Microbiological Societies. Published by Elsevier Science B.V. All rights reserved.

Spatial occupancy models applied to atlas data show Southern Ground Hornbills strongly depend on protected areas.

PubMed

Broms, Kristin M; Johnson, Devin S; Altwegg, Res; Conquest, Loveday L

2014-03-01

Determining the range of a species and exploring species--habitat associations are central questions in ecology and can be answered by analyzing presence--absence data. Often, both the sampling of sites and the desired area of inference involve neighboring sites; thus, positive spatial autocorrelation between these sites is expected. Using survey data for the Southern Ground Hornbill (Bucorvus leadbeateri) from the Southern African Bird Atlas Project, we compared advantages and disadvantages of three increasingly complex models for species occupancy: an occupancy model that accounted for nondetection but assumed all sites were independent, and two spatial occupancy models that accounted for both nondetection and spatial autocorrelation. We modeled the spatial autocorrelation with an intrinsic conditional autoregressive (ICAR) model and with a restricted spatial regression (RSR) model. Both spatial models can readily be applied to any other gridded, presence--absence data set using a newly introduced R package. The RSR model provided the best inference and was able to capture small-scale variation that the other models did not. It showed that ground hornbills are strongly dependent on protected areas in the north of their South African range, but less so further south. The ICAR models did not capture any spatial autocorrelation in the data, and they took an order, of magnitude longer than the RSR models to run. Thus, the RSR occupancy model appears to be an attractive choice for modeling occurrences at large spatial domains, while accounting for imperfect detection and spatial autocorrelation.

Current practices in the spatial analysis of cancer: flies in the ointment

PubMed Central

Jacquez, Geoffrey M

2004-01-01

While many lessons have been learned from the spatial analysis of cancer, there are several caveats that apply to many, if not all such analyses. As "flies in the ointment", these can substantially detract from a spatial analysis, and if not accounted for, can lead to weakened and erroneous conclusions. This paper discusses several assumptions and limitations of spatial analysis, identifies problems of scientific inference, and concludes with potential solutions and future directions. PMID:15479473

Effects of sample size, number of markers, and allelic richness on the detection of spatial genetic pattern

Treesearch

Erin L. Landguth; Bradley C. Fedy; Sara J. Oyler-McCance; Andrew L. Garey; Sarah L. Emel; Matthew Mumma; Helene H. Wagner; Marie-Josee Fortin; Samuel A. Cushman

2012-01-01

The influence of study design on the ability to detect the effects of landscape pattern on gene flow is one of the most pressing methodological gaps in landscape genetic research. To investigate the effect of study design on landscape genetics inference, we used a spatially-explicit, individual-based program to simulate gene flow in a spatially continuous population...

LACTB is a filament-forming protein localized in mitochondria

PubMed Central

Polianskyte, Zydrune; Peitsaro, Nina; Dapkunas, Arvydas; Liobikas, Julius; Soliymani, Rabah; Lalowski, Maciej; Speer, Oliver; Seitsonen, Jani; Butcher, Sarah; Cereghetti, Grazia M.; Linder, Matts D.; Merckel, Michael; Thompson, James; Eriksson, Ove

2009-01-01

LACTB is a mammalian active-site serine protein that has evolved from a bacterial penicillin-binding protein. Penicillin-binding proteins are involved in the metabolism of peptidoglycan, the major bacterial cell wall constituent, implying that LACTB has been endowed with novel biochemical properties during eukaryote evolution. Here we demonstrate that LACTB is localized in the mitochondrial intermembrane space, where it is polymerized into stable filaments with a length extending more than a hundred nanometers. We infer that LACTB, through polymerization, promotes intramitochondrial membrane organization and micro-compartmentalization. These findings have implications for our understanding of mitochondrial evolution and function. PMID:19858488

Fine Spatial Scale Variation of Soil Microbial Communities under European Beech and Norway Spruce

PubMed Central

Nacke, Heiko; Goldmann, Kezia; Schöning, Ingo; Pfeiffer, Birgit; Kaiser, Kristin; Castillo-Villamizar, Genis A.; Schrumpf, Marion; Buscot, François; Daniel, Rolf; Wubet, Tesfaye

2016-01-01

The complex interactions between trees and soil microbes in forests as well as their inherent seasonal and spatial variations are poorly understood. In this study, we analyzed the effects of major European tree species (Fagus sylvatica L. and Picea abies (L.) Karst) on soil bacterial and fungal communities. Mineral soil samples were collected from different depths (0–10, 10–20 cm) and at different horizontal distances from beech or spruce trunks (0.5, 1.5, 2.5, 3.5 m) in early summer and autumn. We assessed the composition of soil bacterial and fungal communities based on 16S rRNA gene and ITS DNA sequences. Community composition of bacteria and fungi was most strongly affected by soil pH and tree species. Different ectomycorrhizal fungi (e.g., Tylospora) known to establish mutualistic associations with plant roots showed a tree species preference. Moreover, bacterial and fungal community composition showed spatial and seasonal shifts in soil surrounding beech and spruce. The relative abundance of saprotrophic fungi was higher at a depth of 0–10 vs. 10–20 cm depth. This was presumably a result of changes in nutrient availability, as litter input and organic carbon content decreased with soil depth. Overall bacterial community composition showed strong variations under spruce with increasing distance from the tree trunks, which might be attributed in part to higher fine root biomass near spruce trunks. Furthermore, overall bacterial community composition was strongly affected by season under deciduous trees. PMID:28066384

Fine Spatial Scale Variation of Soil Microbial Communities under European Beech and Norway Spruce.

PubMed

Nacke, Heiko; Goldmann, Kezia; Schöning, Ingo; Pfeiffer, Birgit; Kaiser, Kristin; Castillo-Villamizar, Genis A; Schrumpf, Marion; Buscot, François; Daniel, Rolf; Wubet, Tesfaye

2016-01-01

The complex interactions between trees and soil microbes in forests as well as their inherent seasonal and spatial variations are poorly understood. In this study, we analyzed the effects of major European tree species ( Fagus sylvatica L. and Picea abies (L.) Karst) on soil bacterial and fungal communities. Mineral soil samples were collected from different depths (0-10, 10-20 cm) and at different horizontal distances from beech or spruce trunks (0.5, 1.5, 2.5, 3.5 m) in early summer and autumn. We assessed the composition of soil bacterial and fungal communities based on 16S rRNA gene and ITS DNA sequences. Community composition of bacteria and fungi was most strongly affected by soil pH and tree species. Different ectomycorrhizal fungi (e.g., Tylospora ) known to establish mutualistic associations with plant roots showed a tree species preference. Moreover, bacterial and fungal community composition showed spatial and seasonal shifts in soil surrounding beech and spruce. The relative abundance of saprotrophic fungi was higher at a depth of 0-10 vs. 10-20 cm depth. This was presumably a result of changes in nutrient availability, as litter input and organic carbon content decreased with soil depth. Overall bacterial community composition showed strong variations under spruce with increasing distance from the tree trunks, which might be attributed in part to higher fine root biomass near spruce trunks. Furthermore, overall bacterial community composition was strongly affected by season under deciduous trees.

Phylogeography Takes a Relaxed Random Walk in Continuous Space and Time

PubMed Central

Lemey, Philippe; Rambaut, Andrew; Welch, John J.; Suchard, Marc A.

2010-01-01

Research aimed at understanding the geographic context of evolutionary histories is burgeoning across biological disciplines. Recent endeavors attempt to interpret contemporaneous genetic variation in the light of increasingly detailed geographical and environmental observations. Such interest has promoted the development of phylogeographic inference techniques that explicitly aim to integrate such heterogeneous data. One promising development involves reconstructing phylogeographic history on a continuous landscape. Here, we present a Bayesian statistical approach to infer continuous phylogeographic diffusion using random walk models while simultaneously reconstructing the evolutionary history in time from molecular sequence data. Moreover, by accommodating branch-specific variation in dispersal rates, we relax the most restrictive assumption of the standard Brownian diffusion process and demonstrate increased statistical efficiency in spatial reconstructions of overdispersed random walks by analyzing both simulated and real viral genetic data. We further illustrate how drawing inference about summary statistics from a fully specified stochastic process over both sequence evolution and spatial movement reveals important characteristics of a rabies epidemic. Together with recent advances in discrete phylogeographic inference, the continuous model developments furnish a flexible statistical framework for biogeographical reconstructions that is easily expanded upon to accommodate various landscape genetic features. PMID:20203288

"HOOF-Print" Genotyping and Haplotype Inference Discriminates among Brucella spp Isolates From a Small Spatial Scale

USDA-ARS?s Scientific Manuscript database

We demonstrate that the “HOOF-Print” assay provides high power to discriminate among Brucella isolates collected on a small spatial scale (within Portugal). Additionally, we illustrate how haplotype identification using non-random association among markers allows resolution of B. melitensis biovars ...

Probabilistic and spatially variable niches inferred from demography

Treesearch

Jeffrey M. Diez; Itamar Giladi; Robert Warren; H. Ronald Pulliam

2014-01-01

Summary 1. Mismatches between species distributions and habitat suitability are predicted by niche theory and have important implications for forecasting how species may respond to environmental changes. Quantifying these mismatches is challenging, however, due to the high dimensionality of species niches and the large spatial and temporal variability in population...

Spatiotemporal variation of bacterial community composition and possible controlling factors in tropical shallow lagoons.

PubMed

Laque, Thaís; Farjalla, Vinicius F; Rosado, Alexandre S; Esteves, Francisco A

2010-05-01

Bacterial community composition (BCC) has been extensively related to specific environmental conditions. Tropical coastal lagoons present great temporal and spatial variation in their limnological conditions, which, in turn, should influence the BCC. Here, we sought for the limnological factors that influence, in space and time, the BCC in tropical coastal lagoons (Rio de Janeiro State, Brazil). The Visgueiro lagoon was sampled monthly for 1 year and eight lagoons were sampled once for temporal and spatial analysis, respectively. BCC was evaluated by bacteria-specific PCR-DGGE methods. Great variations were observed in limnological conditions and BCC on both temporal and spatial scales. Changes in the BCC of Visgueiro lagoon throughout the year were best related to salinity and concentrations of NO (3) (-) , dissolved phosphorus and chlorophyll-a, while changes in BCC between lagoons were best related to salinity and dissolved phosphorus concentration. Salinity has a direct impact on the integrity of the bacterial cell, and it was previously observed that phosphorus is the main limiting nutrient to bacterial growth in these lagoons. Therefore, we conclude that great variations in limnological conditions of coastal lagoons throughout time and space resulted in different BCCs and salinity and nutrient concentration, particularly dissolved phosphorus, are the main limnological factors influencing BCC in these tropical coastal lagoons.

Nonparametric Bayesian Segmentation of a Multivariate Inhomogeneous Space-Time Poisson Process.

PubMed

Ding, Mingtao; He, Lihan; Dunson, David; Carin, Lawrence

2012-12-01

A nonparametric Bayesian model is proposed for segmenting time-evolving multivariate spatial point process data. An inhomogeneous Poisson process is assumed, with a logistic stick-breaking process (LSBP) used to encourage piecewise-constant spatial Poisson intensities. The LSBP explicitly favors spatially contiguous segments, and infers the number of segments based on the observed data. The temporal dynamics of the segmentation and of the Poisson intensities are modeled with exponential correlation in time, implemented in the form of a first-order autoregressive model for uniformly sampled discrete data, and via a Gaussian process with an exponential kernel for general temporal sampling. We consider and compare two different inference techniques: a Markov chain Monte Carlo sampler, which has relatively high computational complexity; and an approximate and efficient variational Bayesian analysis. The model is demonstrated with a simulated example and a real example of space-time crime events in Cincinnati, Ohio, USA.

The stock-flow model of spatial data infrastructure development refined by fuzzy logic.

PubMed

Abdolmajidi, Ehsan; Harrie, Lars; Mansourian, Ali

2016-01-01

The system dynamics technique has been demonstrated to be a proper method by which to model and simulate the development of spatial data infrastructures (SDI). An SDI is a collaborative effort to manage and share spatial data at different political and administrative levels. It is comprised of various dynamically interacting quantitative and qualitative (linguistic) variables. To incorporate linguistic variables and their joint effects in an SDI-development model more effectively, we suggest employing fuzzy logic. Not all fuzzy models are able to model the dynamic behavior of SDIs properly. Therefore, this paper aims to investigate different fuzzy models and their suitability for modeling SDIs. To that end, two inference and two defuzzification methods were used for the fuzzification of the joint effect of two variables in an existing SDI model. The results show that the Average-Average inference and Center of Area defuzzification can better model the dynamics of SDI development.

Inferring collective dynamical states from widely unobserved systems.

PubMed

Wilting, Jens; Priesemann, Viola

2018-06-13

When assessing spatially extended complex systems, one can rarely sample the states of all components. We show that this spatial subsampling typically leads to severe underestimation of the risk of instability in systems with propagating events. We derive a subsampling-invariant estimator, and demonstrate that it correctly infers the infectiousness of various diseases under subsampling, making it particularly useful in countries with unreliable case reports. In neuroscience, recordings are strongly limited by subsampling. Here, the subsampling-invariant estimator allows to revisit two prominent hypotheses about the brain's collective spiking dynamics: asynchronous-irregular or critical. We identify consistently for rat, cat, and monkey a state that combines features of both and allows input to reverberate in the network for hundreds of milliseconds. Overall, owing to its ready applicability, the novel estimator paves the way to novel insight for the study of spatially extended dynamical systems.

Modeling the Round Earth through Diagrams

NASA Astrophysics Data System (ADS)

Padalkar, Shamin; Ramadas, Jayashree

Earlier studies have found that students, including adults, have problems understanding the scientifically accepted model of the Sun-Earth-Moon system and explaining day-to-day astronomical phenomena based on it. We have been examining such problems in the context of recent research on visual-spatial reasoning. Working with middle school students in India, we have developed a pedagogical sequence to build the mental model of the Earth and tried it in three schools for socially and educationally disadvantaged students. This pedagogy was developed on the basis of (1) a reading of current research in imagery and visual-spatial reasoning and (2) students' difficulties identified during the course of pretests and interviews. Visual-spatial tools such as concrete (physical) models, gestures, and diagrams are used extensively in the teaching sequence. The building of a mental model is continually integrated with drawing inferences to understand and explain everyday phenomena. The focus of this article is inferences drawn with diagrams.

Forest strata drive spatial structure of bacterial and archaeal communities and microbial methane cycling in neotropical bromeliad wetlands

NASA Astrophysics Data System (ADS)

Martinson, Guntars; Brandt, Franziska; Conrad, Ralf

2016-04-01

Several thousands of tank bromeliads per hectare of neotropical forest create a unique wetland ecosystem that harbors diverse communities of archaea and bacteria and emit substantial amounts of methane. We studied spatial distribution of archaeal and bacterial communities, microbial methane cycling and their environmental drivers in tank bromeliad wetlands. We selected tank bromeliads of different species and functional types (terrestrial and canopy bromeliads) in a neotropical montane forest of Southern Ecuador and sampled the organic tank slurry. Archaeal and bacterial communities were characterized using terminal-restriction fragment length polymorphism (T-RFLP) and Illumina MiSeq sequencing, respectively, and linked with physico-chemical tank-slurry properties. Additionally, we performed tank-slurry incubations to measure methane production potential, stable carbon isotope fractionation and pathway of methane formation. Archaeal and bacterial community composition in bromeliad wetlands was dominated by methanogens and by Alphaproteobacteria, respectively, and did not differ between species but between functional types. Hydrogenotrophic Methanomicrobiales were the dominant methanogens among all bromeliads but the relative abundance of aceticlastic Methanosaetaceae increased in terrestrial bromeliads. Complementary, hydrogenotrophic methanogenesis was the dominant pathway of methane formation but the relative contribution of aceticlastic methanogenesis increased in terrestrial bromeliads and led to a concomitant increase in total methane production. Rhodospirillales were characteristic for canopy bromeliads, Planctomycetales and Actinomycetalis for terrestrial bromeliads. While nitrogen concentration and pH explained 32% of the archaeal community variability, 29% of the bacterial community variability was explained by nitrogen, acetate and propionate concentrations. Our study demonstrates that bromeliad functional types, associated with different forest strata, and their constrained environmental characteristics shape the spatial structure of archaeal and bacterial communities and microbial methane cycling in neotropical bromeliad wetlands.

Spatial Distribution of Bacterial Communities and Phenanthrene Degradation in the Rhizosphere of Lolium perenne L.

PubMed Central

Corgié, S. C.; Beguiristain, T.; Leyval, C.

2004-01-01

Rhizodegradation of organic pollutants, such as polycyclic aromatic hydrocarbons, is based on the effect of root-produced compounds, known as exudates. These exudates constitute an important and constant carbon source that selects microbial populations in the plant rhizosphere, modifying global as well as specific microbial activities. We conducted an experiment in two-compartment devices to show the selection of bacterial communities by root exudates and phenanthrene as a function of distance to roots. Using direct DNA extraction, PCR amplification, and thermal gradient gel electrophoresis screening, bacterial population profiles were analyzed in parallel to bacterial counts and quantification of phenanthrene biodegradation in three layers (0 to 3, 3 to 6, and 6 to 9 mm from root mat) of unplanted-polluted (phenanthrene), planted-polluted, and planted-unpolluted treatments. Bacterial community differed as a function of the distance to roots, in both the presence and the absence of phenanthrene. In the planted and polluted treatment, biodegradation rates showed a strong gradient with higher values near the roots. In the nonplanted treatment, bacterial communities were comparable in the three layers and phenanthrene biodegradation was high. Surprisingly, no biodegradation was detected in the section of planted polluted treatment farthest from the roots, where the bacterial community structure was similar to those of the nonplanted treatment. We conclude that root exudates and phenanthrene induce modifications of bacterial communities in polluted environments and spatially modify the activity of degrading bacteria. PMID:15184156

Real-time detection of antibiotic activity by measuring nanometer-scale bacterial deformation

NASA Astrophysics Data System (ADS)

Iriya, Rafael; Syal, Karan; Jing, Wenwen; Mo, Manni; Yu, Hui; Haydel, Shelley E.; Wang, Shaopeng; Tao, Nongjian

2017-12-01

Diagnosing antibiotic-resistant bacteria currently requires sensitive detection of phenotypic changes associated with antibiotic action on bacteria. Here, we present an optical imaging-based approach to quantify bacterial membrane deformation as a phenotypic feature in real-time with a nanometer scale (˜9 nm) detection limit. Using this approach, we found two types of antibiotic-induced membrane deformations in different bacterial strains: polymyxin B induced relatively uniform spatial deformation of Escherichia coli O157:H7 cells leading to change in cellular volume and ampicillin-induced localized spatial deformation leading to the formation of bulges or protrusions on uropathogenic E. coli CFT073 cells. We anticipate that the approach will contribute to understanding of antibiotic phenotypic effects on bacteria with a potential for applications in rapid antibiotic susceptibility testing.

Astrophysical data analysis with information field theory

NASA Astrophysics Data System (ADS)

Enßlin, Torsten

2014-12-01

Non-parametric imaging and data analysis in astrophysics and cosmology can be addressed by information field theory (IFT), a means of Bayesian, data based inference on spatially distributed signal fields. IFT is a statistical field theory, which permits the construction of optimal signal recovery algorithms. It exploits spatial correlations of the signal fields even for nonlinear and non-Gaussian signal inference problems. The alleviation of a perception threshold for recovering signals of unknown correlation structure by using IFT will be discussed in particular as well as a novel improvement on instrumental self-calibration schemes. IFT can be applied to many areas. Here, applications in in cosmology (cosmic microwave background, large-scale structure) and astrophysics (galactic magnetism, radio interferometry) are presented.

It is all about location: how to pinpoint microorganisms and their functions in multispecies biofilms.

PubMed

Costa, Angela M; Mergulhão, Filipe J; Briandet, Romain; Azevedo, Nuno F

2017-09-01

Multispecies biofilms represent the dominant mode of life for the vast majority of microorganisms. Bacterial spatial localization in such biostructures governs ecological interactions between different populations and triggers the overall community functions. Here, we discuss the pros and cons of fluorescence-based techniques used to decipher bacterial species patterns in biofilms at single cell level, including fluorescence in situ hybridization and the use of genetically modified bacteria that express fluorescent proteins, reporting the significant improvements of those techniques. The development of tools for spatial and temporal study of multispecies biofilms will allow live imaging and spatial localization of cells in naturally occurring biofilms coupled with metabolic information, increasing insight of microbial community and the relation between its structure and functions.

Investigating Bacterial-Animal Symbioses with Light Sheet Microscopy

PubMed Central

Taormina, Michael J.; Jemielita, Matthew; Stephens, W. Zac; Burns, Adam R.; Troll, Joshua V.; Parthasarathy, Raghuveer; Guillemin, Karen

2014-01-01

SUMMARY Microbial colonization of the digestive tract is a crucial event in vertebrate development, required for maturation of host immunity and establishment of normal digestive physiology. Advances in genomic, proteomic, and metabolomic technologies are providing a more detailed picture of the constituents of the intestinal habitat, but these approaches lack the spatial and temporal resolution needed to characterize the assembly and dynamics of microbial communities in this complex environment. We report the use of light sheet microscopy to provide high resolution imaging of bacterial colonization of the zebrafish intestine. The methodology allows us to characterize bacterial population dynamics across the entire organ and the behaviors of individual bacterial and host cells throughout the colonization process. The large four-dimensional datasets generated by these imaging approaches require new strategies for image analysis. When integrated with other “omics” datasets, information about the spatial and temporal dynamics of microbial cells within the vertebrate intestine will provide new mechanistic insights into how microbial communities assemble and function within hosts. PMID:22983029

Long-term spatial and temporal microbial community dynamics in a large-scale drinking water distribution system with multiple disinfectant regimes.

PubMed

Potgieter, Sarah; Pinto, Ameet; Sigudu, Makhosazana; du Preez, Hein; Ncube, Esper; Venter, Stephanus

2018-08-01

Long-term spatial-temporal investigations of microbial dynamics in full-scale drinking water distribution systems are scarce. These investigations can reveal the process, infrastructure, and environmental factors that influence the microbial community, offering opportunities to re-think microbial management in drinking water systems. Often, these insights are missed or are unreliable in short-term studies, which are impacted by stochastic variabilities inherent to large full-scale systems. In this two-year study, we investigated the spatial and temporal dynamics of the microbial community in a large, full scale South African drinking water distribution system that uses three successive disinfection strategies (i.e. chlorination, chloramination and hypochlorination). Monthly bulk water samples were collected from the outlet of the treatment plant and from 17 points in the distribution system spanning nearly 150 km and the bacterial community composition was characterised by Illumina MiSeq sequencing of the V4 hypervariable region of the 16S rRNA gene. Like previous studies, Alpha- and Betaproteobacteria dominated the drinking water bacterial communities, with an increase in Betaproteobacteria post-chloramination. In contrast with previous reports, the observed richness, diversity, and evenness of the bacterial communities were higher in the winter months as opposed to the summer months in this study. In addition to temperature effects, the seasonal variations were also likely to be influenced by changes in average water age in the distribution system and corresponding changes in disinfectant residual concentrations. Spatial dynamics of the bacterial communities indicated distance decay, with bacterial communities becoming increasingly dissimilar with increasing distance between sampling locations. These spatial effects dampened the temporal changes in the bulk water community and were the dominant factor when considering the entire distribution system. However, temporal variations were consistently stronger as compared to spatial changes at individual sampling locations and demonstrated seasonality. This study emphasises the need for long-term studies to comprehensively understand the temporal patterns that would otherwise be missed in short-term investigations. Furthermore, systematic long-term investigations are particularly critical towards determining the impact of changes in source water quality, environmental conditions, and process operations on the changes in microbial community composition in the drinking water distribution system. Copyright © 2018 Elsevier Ltd. All rights reserved.

Assessing the role of spatial structure on cell-specific activity and interactions within uncultured methane-oxidizing syntrophic consortia (Invited)

NASA Astrophysics Data System (ADS)

Orphan, V. J.; McGlynn, S.; Chadwick, G.; Dekas, A.; Green-Saxena, A.

2013-12-01

Sulfate-coupled anaerobic oxidation of methane is catalysed through symbiotic associations between archaea and sulphate-reducing bacteria and represents the dominant sink for methane in the oceans. These methane-oxidizing symbiotic consortia form well-structured multi-celled aggregations in marine methane seeps, where close spatial proximity is believed to be essential for efficient exchange of substrates between syntrophic partners. The nature of this interspecies metabolic relationship is still unknown however there are a number of hypotheses regarding the electron carrying intermediate and ecophysiology of the partners, each of which should be affected by, and influence, the spatial arrangement of archaeal and bacterial cells within aggregates. To advance our understanding of the role of spatial structure within naturally occurring environmental consortia, we are using spatial statistical methods combined with fluorescence in situ hybridization and high-resolution nanoscale secondary ion mass spectrometry (FISH-nanoSIMS) to quantify the effect of spatial organization and intra- and inter-species interactions on cell-specific microbial activity within these diverse archaeal-bacterial partnerships.

Spatial Vulnerability: Bacterial Arrangements, Microcolonies, and Biofilms as Responses to Low Rather than High Phage Densities

PubMed Central

Abedon, Stephen T.

2012-01-01

The ability of bacteria to survive and propagate can be dramatically reduced upon exposure to lytic bacteriophages. Study of this impact, from a bacterium’s perspective, tends to focus on phage-bacterial interactions that are governed by mass action, such as can be observed within continuous flow or similarly planktonic ecosystems. Alternatively, bacterial molecular properties can be examined, such as specific phage‑resistance adaptations. In this study I address instead how limitations on bacterial movement, resulting in the formation of cellular arrangements, microcolonies, or biofilms, could increase the vulnerability of bacteria to phages. Principally: (1) Physically associated clonal groupings of bacteria can represent larger targets for phage adsorption than individual bacteria; and (2), due to a combination of proximity and similar phage susceptibility, individual bacteria should be especially vulnerable to phages infecting within the same clonal, bacterial grouping. Consistent with particle transport theory—the physics of movement within fluids—these considerations are suggestive that formation into arrangements, microcolonies, or biofilms could be either less profitable to bacteria when phage predation pressure is high or require more effective phage-resistance mechanisms than seen among bacteria not living within clonal clusters. I consider these ideas of bacterial ‘spatial vulnerability’ in part within a phage therapy context. PMID:22754643

Smoothed Particle Inference Analysis of SNR RCW 103

NASA Astrophysics Data System (ADS)

Frank, Kari A.; Burrows, David N.; Dwarkadas, Vikram

2016-04-01

We present preliminary results of applying a novel analysis method, Smoothed Particle Inference (SPI), to an XMM-Newton observation of SNR RCW 103. SPI is a Bayesian modeling process that fits a population of gas blobs ("smoothed particles") such that their superposed emission reproduces the observed spatial and spectral distribution of photons. Emission-weighted distributions of plasma properties, such as abundances and temperatures, are then extracted from the properties of the individual blobs. This technique has important advantages over analysis techniques which implicitly assume that remnants are two-dimensional objects in which each line of sight encompasses a single plasma. By contrast, SPI allows superposition of as many blobs of plasma as are needed to match the spectrum observed in each direction, without the need to bin the data spatially. This RCW 103 analysis is part of a pilot study for the larger SPIES (Smoothed Particle Inference Exploration of SNRs) project, in which SPI will be applied to a sample of 12 bright SNRs.

Diversity of bacterioplankton in coastal seawaters of Fildes Peninsula, King George Island, Antarctica.

PubMed

Zeng, Yin-Xin; Yu, Yong; Qiao, Zong-Yun; Jin, Hai-Yan; Li, Hui-Rong

2014-02-01

The bacterioplankton not only serves critical functions in marine nutrient cycles, but can also serve as indicators of the marine environment. The compositions of bacterial communities in the surface seawater of Ardley Cove and Great Wall Cove were analyzed using a 16S rRNA multiplex 454 pyrosequencing approach. Similar patterns of bacterial composition were found between the two coves, in which Bacteroidetes, Alphaproteobacteria, and Gammaproteobacteria were the dominant members of the bacterioplankton communities. In addition, a large fraction of the bacterial sequence reads (on average 5.3 % per station) could not be assigned below the domain level. Compared with Ardley Cove, Great Wall Cove showed higher chlorophyll and particulate organic carbon concentrations and exhibited relatively lower bacterial richness and diversity. Inferred metabolisms of summer bacterioplankton in the two coves were characterized by chemoheterotrophy and photoheterotrophy. Results suggest that some cosmopolitan species (e.g., Polaribacter and Sulfitobacter) belonging to a few bacterial groups that usually dominate in marine bacterioplankton communities may have similar ecological functions in similar marine environments but at different geographic locations.

Structural geology practice and learning, from the perspective of cognitive science

NASA Astrophysics Data System (ADS)

Shipley, Thomas F.; Tikoff, Basil; Ormand, Carol; Manduca, Cathy

2013-09-01

Spatial ability is required by practitioners and students of structural geology and so, considering spatial skills in the context of cognitive science has the potential to improve structural geology teaching and practice. Spatial thinking skills may be organized using three dichotomies, which can be linked to structural geology practice. First, a distinction is made between separating (attending to part of a whole) and combining (linking together aspects of the whole). While everyone has a basic ability to separate and combine, experts attend to differences guided by experiences of rock properties in context. Second, a distinction is made between seeing the relations among multiple objects as separate items or the relations within a single object with multiple parts. Experts can flexibly consider relations among or between objects to optimally reason about different types of spatial problems. Third, a distinction is made between reasoning about stationary and moving objects. Experts recognize static configurations that encode a movement history, and create mental models of the processes that led to the static state. The observations and inferences made by a geologist leading a field trip are compared with the corresponding observations and inferences made by a cognitive psychologist interested in spatial learning. The presented framework provides a vocabulary for discussing spatial skills both within and between the fields of structural geology and cognitive psychology.

How Much Can Remotely-Sensed Natural Resource Inventories Benefit from Finer Spatial Resolutions?

NASA Astrophysics Data System (ADS)

Hou, Z.; Xu, Q.; McRoberts, R. E.; Ståhl, G.; Greenberg, J. A.

2017-12-01

For remote sensing facilitated natural resource inventories, the effects of spatial resolution in the form of pixel size and the effects of subpixel information on estimates of population parameters were evaluated by comparing results obtained using Landsat 8 and RapidEye auxiliary imagery. The study area was in Burkina Faso, and the variable of interest was the stem volume (m3/ha) convertible to the woodland aboveground biomass. A sample consisting of 160 field plots was selected and measured from the population following a two-stage sampling design. Models were fit using weighted least squares; the population mean, mu, and the variance of the estimator of the population mean, Var(mu.hat), were estimated in two inferential frameworks, model-based and model-assisted, and compared; for each framework, Var(mu.hat) was estimated both analytically and empirically. Empirical variances were estimated with bootstrapping that for resampling takes clustering effects into account. The primary results were twofold. First, for the effects of spatial resolution and subpixel information, four conclusions are relevant: (1) finer spatial resolution imagery indeed contributes to greater precision for estimators of population parameter, but this increase is slight at a maximum rate of 20% considering that RapidEye data are 36 times finer resolution than Landsat 8 data; (2) subpixel information on texture is marginally beneficial when it comes to making inference for population of large areas; (3) cost-effectiveness is more favorable for the free of charge Landsat 8 imagery than RapidEye imagery; and (4) for a given plot size, candidate remote sensing auxiliary datasets are more cost-effective when their spatial resolutions are similar to the plot size than with much finer alternatives. Second, for the comparison between estimators, three conclusions are relevant: (1) model-based variance estimates are consistent with each other and about half as large as stabilized model-assisted estimates, suggesting superior effectiveness of model-based inference to model-assisted inference; (2) bootstrapping is an effective alternative to analytical variance estimators; and (3) prediction accuracy expressed by RMSE is useful for screening candidate models to be used for population inferences.

From learning taxonomies to phylogenetic learning: integration of 16S rRNA gene data into FAME-based bacterial classification.

PubMed

Slabbinck, Bram; Waegeman, Willem; Dawyndt, Peter; De Vos, Paul; De Baets, Bernard

2010-01-30

Machine learning techniques have shown to improve bacterial species classification based on fatty acid methyl ester (FAME) data. Nonetheless, FAME analysis has a limited resolution for discrimination of bacteria at the species level. In this paper, we approach the species classification problem from a taxonomic point of view. Such a taxonomy or tree is typically obtained by applying clustering algorithms on FAME data or on 16S rRNA gene data. The knowledge gained from the tree can then be used to evaluate FAME-based classifiers, resulting in a novel framework for bacterial species classification. In view of learning in a taxonomic framework, we consider two types of trees. First, a FAME tree is constructed with a supervised divisive clustering algorithm. Subsequently, based on 16S rRNA gene sequence analysis, phylogenetic trees are inferred by the NJ and UPGMA methods. In this second approach, the species classification problem is based on the combination of two different types of data. Herein, 16S rRNA gene sequence data is used for phylogenetic tree inference and the corresponding binary tree splits are learned based on FAME data. We call this learning approach 'phylogenetic learning'. Supervised Random Forest models are developed to train the classification tasks in a stratified cross-validation setting. In this way, better classification results are obtained for species that are typically hard to distinguish by a single or flat multi-class classification model. FAME-based bacterial species classification is successfully evaluated in a taxonomic framework. Although the proposed approach does not improve the overall accuracy compared to flat multi-class classification, it has some distinct advantages. First, it has better capabilities for distinguishing species on which flat multi-class classification fails. Secondly, the hierarchical classification structure allows to easily evaluate and visualize the resolution of FAME data for the discrimination of bacterial species. Summarized, by phylogenetic learning we are able to situate and evaluate FAME-based bacterial species classification in a more informative context.

From learning taxonomies to phylogenetic learning: Integration of 16S rRNA gene data into FAME-based bacterial classification

PubMed Central

2010-01-01

Background Machine learning techniques have shown to improve bacterial species classification based on fatty acid methyl ester (FAME) data. Nonetheless, FAME analysis has a limited resolution for discrimination of bacteria at the species level. In this paper, we approach the species classification problem from a taxonomic point of view. Such a taxonomy or tree is typically obtained by applying clustering algorithms on FAME data or on 16S rRNA gene data. The knowledge gained from the tree can then be used to evaluate FAME-based classifiers, resulting in a novel framework for bacterial species classification. Results In view of learning in a taxonomic framework, we consider two types of trees. First, a FAME tree is constructed with a supervised divisive clustering algorithm. Subsequently, based on 16S rRNA gene sequence analysis, phylogenetic trees are inferred by the NJ and UPGMA methods. In this second approach, the species classification problem is based on the combination of two different types of data. Herein, 16S rRNA gene sequence data is used for phylogenetic tree inference and the corresponding binary tree splits are learned based on FAME data. We call this learning approach 'phylogenetic learning'. Supervised Random Forest models are developed to train the classification tasks in a stratified cross-validation setting. In this way, better classification results are obtained for species that are typically hard to distinguish by a single or flat multi-class classification model. Conclusions FAME-based bacterial species classification is successfully evaluated in a taxonomic framework. Although the proposed approach does not improve the overall accuracy compared to flat multi-class classification, it has some distinct advantages. First, it has better capabilities for distinguishing species on which flat multi-class classification fails. Secondly, the hierarchical classification structure allows to easily evaluate and visualize the resolution of FAME data for the discrimination of bacterial species. Summarized, by phylogenetic learning we are able to situate and evaluate FAME-based bacterial species classification in a more informative context. PMID:20113515

Intermediate scale plasma density irregularities in the polar ionosphere inferred from radio occultation

NASA Astrophysics Data System (ADS)

Shume, E. B.; Komjathy, A.; Langley, R. B.; Verkhoglyadova, O. P.; Butala, M.; Mannucci, A. J.

2014-12-01

In this research, we report intermediate scale plasma density irregularities in the high-latitude ionosphere inferred from high-resolution radio occultation (RO) measurements in the CASSIOPE (CAScade Smallsat and IOnospheric Polar Explorer) - GPS (Global Positioning System) satellites radio link. The high inclination of the CASSIOPE satellite and high rate of signal receptionby the occultation antenna of the GPS Attitude, Positioning and Profiling (GAP) instrument on the Enhanced Polar Outflow Probe platform on CASSIOPE enable a high temporal and spatial resolution investigation of the dynamics of the polar ionosphere, magnetosphere-ionospherecoupling, solar wind effects, etc. with unprecedented details compared to that possible in the past. We have carried out high spatial resolution analysis in altitude and geomagnetic latitude of scintillation-producing plasma density irregularities in the polar ionosphere. Intermediate scale, scintillation-producing plasma density irregularities, which corresponds to 2 to 40 km spatial scales were inferred by applying multi-scale spectral analysis on the RO phase delay measurements. Using our multi-scale spectral analysis approach and Polar Operational Environmental Satellites (POES) and Defense Meteorological Satellite Program (DMSP) observations, we infer that the irregularity scales and phase scintillations have distinct features in the auroral oval and polar cap regions. In specific terms, we found that large length scales and and more intense phase scintillations are prevalent in the auroral oval compared to the polar cap region. Hence, the irregularity scales and phase scintillation characteristics are a function of the solar wind and the magnetospheric forcing. Multi-scale analysis may become a powerful diagnostic tool for characterizing how the ionosphere is dynamically driven by these factors.

The effects of spatial autoregressive dependencies on inference in ordinary least squares: a geometric approach

NASA Astrophysics Data System (ADS)

Smith, Tony E.; Lee, Ka Lok

2012-01-01

There is a common belief that the presence of residual spatial autocorrelation in ordinary least squares (OLS) regression leads to inflated significance levels in beta coefficients and, in particular, inflated levels relative to the more efficient spatial error model (SEM). However, our simulations show that this is not always the case. Hence, the purpose of this paper is to examine this question from a geometric viewpoint. The key idea is to characterize the OLS test statistic in terms of angle cosines and examine the geometric implications of this characterization. Our first result is to show that if the explanatory variables in the regression exhibit no spatial autocorrelation, then the distribution of test statistics for individual beta coefficients in OLS is independent of any spatial autocorrelation in the error term. Hence, inferences about betas exhibit all the optimality properties of the classic uncorrelated error case. However, a second more important series of results show that if spatial autocorrelation is present in both the dependent and explanatory variables, then the conventional wisdom is correct. In particular, even when an explanatory variable is statistically independent of the dependent variable, such joint spatial dependencies tend to produce "spurious correlation" that results in over-rejection of the null hypothesis. The underlying geometric nature of this problem is clarified by illustrative examples. The paper concludes with a brief discussion of some possible remedies for this problem.

Spatial capture-recapture: a promising method for analyzing data collected using artificial cover objects

USGS Publications Warehouse

Sutherland, Chris; Munoz, David; Miller, David A.W.; Grant, Evan H. Campbell

2016-01-01

Spatial capture–recapture (SCR) is a relatively recent development in ecological statistics that provides a spatial context for estimating abundance and space use patterns, and improves inference about absolute population density. SCR has been applied to individual encounter data collected noninvasively using methods such as camera traps, hair snares, and scat surveys. Despite the widespread use of capture-based surveys to monitor amphibians and reptiles, there are few applications of SCR in the herpetological literature. We demonstrate the utility of the application of SCR for studies of reptiles and amphibians by analyzing capture–recapture data from Red-Backed Salamanders, Plethodon cinereus, collected using artificial cover boards. Using SCR to analyze spatial encounter histories of marked individuals, we found evidence that density differed little among four sites within the same forest (on average, 1.59 salamanders/m2) and that salamander detection probability peaked in early October (Julian day 278) reflecting expected surface activity patterns of the species. The spatial scale of detectability, a measure of space use, indicates that the home range size for this population of Red-Backed Salamanders in autumn was 16.89 m2. Surveying reptiles and amphibians using artificial cover boards regularly generates spatial encounter history data of known individuals, which can readily be analyzed using SCR methods, providing estimates of absolute density and inference about the spatial scale of habitat use.

The role of right frontal brain regions in integration of spatial relation.

PubMed

Han, Jiahui; Cao, Bihua; Cao, Yunfei; Gao, Heming; Li, Fuhong

2016-06-01

Previous studies have explored the neural mechanisms of spatial reasoning on a two-dimensional (2D) plane; however, it remains unclear how spatial reasoning is conducted in a three-dimensional (3D) condition. In the present study, we presented 3D geometric objects to 16 adult participants, and asked them to process the spatial relationship between different corners of the geometric objects. In premise-1, the first two corners of a geometric shape (e.g., A vs. B) were displayed. In premise-2, the second and third corners (e.g., B vs. C) were displayed. After integrating the two premises, participants were required to infer the spatial relationship between the first and the third corners (e.g., A and C). Finally, the participants were presented with a conclusion object, and they were required to judge whether the conclusion was true or false based on their inference. The event-related potential evoked by premise-2 revealed that (1) compared with 2D spatial reasoning, 3D reasoning elicited a smaller P3b component, and (2) in the right frontal areas, increased negativities were found in the 3D condition during the N400 and late negative components (LNC). These findings imply that higher brain activity in the right frontal brain regions were related with the integration and maintenance of spatial information in working memory for reasoning. Copyright © 2016 Elsevier Ltd. All rights reserved.

I Know Who My Friends Are, But Do You? Predictors of Self-reported and Peer-inferred Relationships

PubMed Central

Neal, Jennifer Watling; Neal, Zachary P.; Cappella, Elise

2013-01-01

Using social network data, this study examines which features of social and spatial proximity predict self-reported, or “real,” and peer-reported, or “inferred,” relationships among 2695 pairwise combinations of African American second through fourth grade students (ages 7-11). Relationships were more likely to exist, and more likely to be inferred to exist by peers, between pairs of children who were the same sex, sat near one another, shared a positive academic orientation, or shared athletic ability. Sex similarity had a dramatically larger effect on peers’ inferences about relationships than on self-reported real relationships, suggesting that children overestimate the importance of sex in their inferences about relationships. Results were stable across different grade levels in middle childhood and for boys and girls. PMID:24320155

Bacterial Dispersal Promotes Biodegradation in Heterogeneous Systems Exposed to Osmotic Stress

PubMed Central

Worrich, Anja; König, Sara; Banitz, Thomas; Centler, Florian; Frank, Karin; Thullner, Martin; Harms, Hauke; Miltner, Anja; Wick, Lukas Y.; Kästner, Matthias

2016-01-01

Contaminant biodegradation in soils is hampered by the heterogeneous distribution of degrading communities colonizing isolated microenvironments as a result of the soil architecture. Over the last years, soil salinization was recognized as an additional problem especially in arid and semiarid ecosystems as it drastically reduces the activity and motility of bacteria. Here, we studied the importance of different spatial processes for benzoate biodegradation at an environmentally relevant range of osmotic potentials (ΔΨo) using model ecosystems exhibiting a heterogeneous distribution of the soil-borne bacterium Pseudomonas putida KT2440. Three systematically manipulated scenarios allowed us to cover the effects of (i) substrate diffusion, (ii) substrate diffusion and autonomous bacterial dispersal, and (iii) substrate diffusion and autonomous as well as mediated bacterial dispersal along glass fiber networks mimicking fungal hyphae. To quantify the relative importance of the different spatial processes, we compared these heterogeneous scenarios to a reference value obtained for each ΔΨo by means of a quasi-optimal scenario in which degraders were ab initio homogeneously distributed. Substrate diffusion as the sole spatial process was insufficient to counteract the disadvantage due to spatial degrader heterogeneity at ΔΨo ranging from 0 to −1 MPa. In this scenario, only 13.8−21.3% of the quasi-optimal biodegradation performance could be achieved. In the same range of ΔΨo values, substrate diffusion in combination with bacterial dispersal allowed between 68.6 and 36.2% of the performance showing a clear downwards trend with decreasing ΔΨo. At −1.5 MPa, however, this scenario performed worse than the diffusion scenario, possibly as a result of energetic disadvantages associated with flagellum synthesis and emerging requirements to exceed a critical population density to resist osmotic stress. Network-mediated bacterial dispersal kept biodegradation almost consistently high with an average of 70.7 ± 7.8%, regardless of the strength of the osmotic stress. We propose that especially fungal network-mediated bacterial dispersal is a key process to achieve high functionality of heterogeneous microbial ecosystems also at reduced osmotic potentials. Thus, mechanical stress by, for example, soil homogenization should be kept low in order to preserve fungal network integrity. PMID:27536297

Spatial Description of Drinking Water Bacterial Community Structures in Bulk Water Samples Collected in a Metropolitan Distribution System

EPA Science Inventory

The description of microorganisms inhabiting drinking water distribution systems has commonly been performed using techniques that are biased towards easy to culture bacterial populations. As most environmental microorganisms cannot be grown on artificial media, our understanding...

Spatial Patterning of Newly-Inserted Material during Bacterial Cell Growth

NASA Astrophysics Data System (ADS)

Ursell, Tristan

2012-02-01

In the life cycle of a bacterium, rudimentary microscopy demonstrates that cell growth and elongation are essential characteristics of cellular reproduction. The peptidoglycan cell wall is the main load-bearing structure that determines both cell shape and overall size. However, simple imaging of cellular growth gives no indication of the spatial patterning nor mechanism by which material is being incorporated into the pre-existing cell wall. We employ a combination of high-resolution pulse-chase fluorescence microscopy, 3D computational microscopy, and detailed mechanistic simulations to explore how spatial patterning results in uniform growth and maintenance of cell shape. We show that growth is happening in discrete bursts randomly distributed over the cell surface, with a well-defined mean size and average rate. We further use these techniques to explore the effects of division and cell wall disrupting antibiotics, like cephalexin and A22, respectively, on the patterning of cell wall growth in E. coli. Finally, we explore the spatial correlation between presence of the bacterial actin-like cytoskeletal protein, MreB, and local cell wall growth. Together these techniques form a powerful method for exploring the detailed dynamics and involvement of antibiotics and cell wall-associated proteins in bacterial cell growth.[4pt] In collaboration with Kerwyn Huang, Stanford University.

Statistical Inference and Spatial Patterns in Correlates of IQ

ERIC Educational Resources Information Center

Hassall, Christopher; Sherratt, Thomas N.

2011-01-01

Cross-national comparisons of IQ have become common since the release of a large dataset of international IQ scores. However, these studies have consistently failed to consider the potential lack of independence of these scores based on spatial proximity. To demonstrate the importance of this omission, we present a re-evaluation of several…

Scale issues in soil hydrology related to measurement and simulation: A case study in Colorado

USDA-ARS?s Scientific Manuscript database

State variables, such as soil water content (SWC), are typically measured or inferred at very small scales while being simulated at larger scales relevant to spatial management or hillslope areas. Thus there is an implicit spatial disparity that is often ignored. Surface runoff, on the other hand, ...

Tensor-guided fitting of subduction slab depths

USGS Publications Warehouse

Bazargani, Farhad; Hayes, Gavin P.

2013-01-01

Geophysical measurements are often acquired at scattered locations in space. Therefore, interpolating or fitting the sparsely sampled data as a uniform function of space (a procedure commonly known as gridding) is a ubiquitous problem in geophysics. Most gridding methods require a model of spatial correlation for data. This spatial correlation model can often be inferred from some sort of secondary information, which may also be sparsely sampled in space. In this paper, we present a new method to model the geometry of a subducting slab in which we use a data‐fitting approach to address the problem. Earthquakes and active‐source seismic surveys provide estimates of depths of subducting slabs but only at scattered locations. In addition to estimates of depths from earthquake locations, focal mechanisms of subduction zone earthquakes also provide estimates of the strikes of the subducting slab on which they occur. We use these spatially sparse strike samples and the Earth’s curved surface geometry to infer a model for spatial correlation that guides a blended neighbor interpolation of slab depths. We then modify the interpolation method to account for the uncertainties associated with the depth estimates.

Bacterial cooperation in the wild and in the clinic: are pathogen social behaviours relevant outside the laboratory?

PubMed

Harrison, Freya

2013-02-01

Individual bacterial cells can communicate via quorum sensing, cooperate to harvest nutrients from their environment, form multicellular biofilms, compete over resources and even kill one another. When the environment that bacteria inhabit is an animal host, these social behaviours mediate virulence. Over the last decade, much attention has focussed on the ecology, evolution and pathology of bacterial cooperation, and the possibility that it could be exploited or destabilised to treat infections. But how far can we really extrapolate from theoretical predictions and laboratory experiments to make inferences about 'cooperative' behaviours in hosts and reservoirs? To determine the likely importance and evolution of cooperation 'in the wild', several questions must be addressed. A recent paper that reports the dynamics of bacterial cooperation and virulence in a field experiment provides an excellent nucleus for bringing together key empirical and theoretical results which help us to frame - if not completely to answer - these questions. Copyright © 2013 WILEY Periodicals, Inc.

Characterization of microbial consortia in a terephthalate-degrading anaerobic granular sludge system.

PubMed

Wu, J H; Liu, W T; Tseng, I C; Cheng, S S

2001-02-01

The microbial composition and spatial distribution in a terephthalate-degrading anaerobic granular sludge system were characterized using molecular techniques. 16S rDNA clone library and sequence analysis revealed that 78.5% of 106 bacterial clones belonged to the delta subclass of the class Proteobacteria; the remaining clones were assigned to the green non-sulfur bacteria (7.5%), Synergistes (0.9%) and unidentified divisions (13.1%). Most of the bacterial clones in the delta-Proteobacteria formed a novel group containing no known bacterial isolates. For the domain Archaea, 81.7% and 18.3% of 72 archaeal clones were affiliated with Methanosaeta and Methanospirillum, respectively. Spatial localization of microbial populations inside granules was determined by transmission electron microscopy and fluorescent in situ hybridization with oligonucleotide probes targeting the novel delta-proteobacterial group, the acetoclastic Methanosaeta, and the hydrogenotrophic Methanospirillum and members of Methanobacteriaceae. The novel group included at least two different populations with identical rod-shape morphology, which made up more than 87% of the total bacterial cells, and were closely associated with methanogenic populations to form a nonlayered granular structure. This novel group was presumed to be the primary bacterial population involved in the terephthalate degradation in the methanogenic granular consortium.

Assessing NARCCAP climate model effects using spatial confidence regions.

PubMed

French, Joshua P; McGinnis, Seth; Schwartzman, Armin

2017-01-01

We assess similarities and differences between model effects for the North American Regional Climate Change Assessment Program (NARCCAP) climate models using varying classes of linear regression models. Specifically, we consider how the average temperature effect differs for the various global and regional climate model combinations, including assessment of possible interaction between the effects of global and regional climate models. We use both pointwise and simultaneous inference procedures to identify regions where global and regional climate model effects differ. We also show conclusively that results from pointwise inference are misleading, and that accounting for multiple comparisons is important for making proper inference.

Phylogenetic Diversity of the Enteric Pathogen Salmonella enterica subsp. enterica Inferred from Genome-Wide Reference-Free SNP Characters

USDA-ARS?s Scientific Manuscript database

Salmonella enterica is a major cause of food-borne illness in the US, leading to more deaths than any other food-related pathogen. This is an extremely diverse bacterial species consisting of six subspecies and over 2500 named serovars. Examining the evolutionary history within Salmonella with techn...

Bacterial communities associated with production facilities of two newly drilled thermogenic natural gas wells in the Barnett Shale (Texas, USA).

PubMed

Davis, James P; Struchtemeyer, Christopher G; Elshahed, Mostafa S

2012-11-01

We monitored the bacterial communities in the gas-water separator and water storage tank of two newly drilled natural gas wells in the Barnett Shale in north central Texas, using a 16S rRNA gene pyrosequencing approach over a period of 6 months. Overall, the communities were composed mainly of moderately halophilic and halotolerant members of the phyla Firmicutes and Proteobacteria (classes Βeta-, Gamma-, and Epsilonproteobacteria) in both wells at all sampling times and locations. Many of the observed lineages were encountered in prior investigations of microbial communities from various fossil fluid formations and production facilities. In all of the samples, multiple H(2)S-producing lineages were encountered; belonging to the sulfate- and sulfur-reducing class Deltaproteobacteria, order Clostridiales, and phylum Synergistetes, as well as the thiosulfate-reducing order Halanaerobiales. The bacterial communities from the separator and tank samples bore little resemblance to the bacterial communities in the drilling mud and hydraulic-fracture waters that were used to drill these wells, suggesting the in situ development of the unique bacterial communities in such well components was in response to the prevalent geochemical conditions present. Conversely, comparison of the bacterial communities on temporal and spatial scales suggested the establishment of a core microbial community in each sampled location. The results provide the first overview of bacterial dynamics and colonization patterns in newly drilled, thermogenic natural gas wells and highlights patterns of spatial and temporal variability observed in bacterial communities in natural gas production facilities.

Spatial capture-recapture

USGS Publications Warehouse

Royle, J. Andrew; Chandler, Richard B.; Sollmann, Rahel; Gardner, Beth

2013-01-01

Spatial Capture-Recapture provides a revolutionary extension of traditional capture-recapture methods for studying animal populations using data from live trapping, camera trapping, DNA sampling, acoustic sampling, and related field methods. This book is a conceptual and methodological synthesis of spatial capture-recapture modeling. As a comprehensive how-to manual, this reference contains detailed examples of a wide range of relevant spatial capture-recapture models for inference about population size and spatial and temporal variation in demographic parameters. Practicing field biologists studying animal populations will find this book to be a useful resource, as will graduate students and professionals in ecology, conservation biology, and fisheries and wildlife management.

Top-down effects of a lytic bacteriophage and protozoa on bacteria in aqueous and biofilm phases.

PubMed

Zhang, Ji; Ormälä-Odegrip, Anni-Maria; Mappes, Johanna; Laakso, Jouni

2014-12-01

Lytic bacteriophages and protozoan predators are the major causes of bacterial mortality in natural microbial communities, which also makes them potential candidates for biological control of bacterial pathogens. However, little is known about the relative impact of bacteriophages and protozoa on the dynamics of bacterial biomass in aqueous and biofilm phases. Here, we studied the temporal and spatial dynamics of bacterial biomass in a microcosm experiment where opportunistic pathogenic bacteria Serratia marcescens was exposed to particle-feeding ciliates, surface-feeding amoebas, and lytic bacteriophages for 8 weeks, ca. 1300 generations. We found that ciliates were the most efficient enemy type in reducing bacterial biomass in the open water, but least efficient in reducing the biofilm biomass. Biofilm was rather resistant against bacterivores, but amoebae had a significant long-term negative effect on bacterial biomass both in the open-water phase and biofilm. Bacteriophages had only a minor long-term effect on bacterial biomass in open-water and biofilm phases. However, separate short-term experiments with the ancestral bacteriophages and bacteria revealed that bacteriophages crash the bacterial biomass dramatically in the open-water phase within the first 24 h. Thereafter, the bacteria evolve phage-resistance that largely prevents top-down effects. The combination of all three enemy types was most effective in reducing biofilm biomass, whereas in the open-water phase the ciliates dominated the trophic effects. Our results highlight the importance of enemy feeding mode on determining the spatial distribution and abundance of bacterial biomass. Moreover, the enemy type can be crucially important predictor of whether the rapid defense evolution can significantly affect top-down regulation of bacteria.

Inferring animal social networks and leadership: applications for passive monitoring arrays.

PubMed

Jacoby, David M P; Papastamatiou, Yannis P; Freeman, Robin

2016-11-01

Analyses of animal social networks have frequently benefited from techniques derived from other disciplines. Recently, machine learning algorithms have been adopted to infer social associations from time-series data gathered using remote, telemetry systems situated at provisioning sites. We adapt and modify existing inference methods to reveal the underlying social structure of wide-ranging marine predators moving through spatial arrays of passive acoustic receivers. From six months of tracking data for grey reef sharks (Carcharhinus amblyrhynchos) at Palmyra atoll in the Pacific Ocean, we demonstrate that some individuals emerge as leaders within the population and that this behavioural coordination is predicted by both sex and the duration of co-occurrences between conspecifics. In doing so, we provide the first evidence of long-term, spatially extensive social processes in wild sharks. To achieve these results, we interrogate simulated and real tracking data with the explicit purpose of drawing attention to the key considerations in the use and interpretation of inference methods and their impact on resultant social structure. We provide a modified translation of the GMMEvents method for R, including new analyses quantifying the directionality and duration of social events with the aim of encouraging the careful use of these methods more widely in less tractable social animal systems but where passive telemetry is already widespread. © 2016 The Authors.

Inferring animal social networks and leadership: applications for passive monitoring arrays

PubMed Central

Papastamatiou, Yannis P.; Freeman, Robin

2016-01-01

Analyses of animal social networks have frequently benefited from techniques derived from other disciplines. Recently, machine learning algorithms have been adopted to infer social associations from time-series data gathered using remote, telemetry systems situated at provisioning sites. We adapt and modify existing inference methods to reveal the underlying social structure of wide-ranging marine predators moving through spatial arrays of passive acoustic receivers. From six months of tracking data for grey reef sharks (Carcharhinus amblyrhynchos) at Palmyra atoll in the Pacific Ocean, we demonstrate that some individuals emerge as leaders within the population and that this behavioural coordination is predicted by both sex and the duration of co-occurrences between conspecifics. In doing so, we provide the first evidence of long-term, spatially extensive social processes in wild sharks. To achieve these results, we interrogate simulated and real tracking data with the explicit purpose of drawing attention to the key considerations in the use and interpretation of inference methods and their impact on resultant social structure. We provide a modified translation of the GMMEvents method for R, including new analyses quantifying the directionality and duration of social events with the aim of encouraging the careful use of these methods more widely in less tractable social animal systems but where passive telemetry is already widespread. PMID:27881803

Biologically Inspired Model for Inference of 3D Shape from Texture

PubMed Central

Gomez, Olman; Neumann, Heiko

2016-01-01

A biologically inspired model architecture for inferring 3D shape from texture is proposed. The model is hierarchically organized into modules roughly corresponding to visual cortical areas in the ventral stream. Initial orientation selective filtering decomposes the input into low-level orientation and spatial frequency representations. Grouping of spatially anisotropic orientation responses builds sketch-like representations of surface shape. Gradients in orientation fields and subsequent integration infers local surface geometry and globally consistent 3D depth. From the distributions in orientation responses summed in frequency, an estimate of the tilt and slant of the local surface can be obtained. The model suggests how 3D shape can be inferred from texture patterns and their image appearance in a hierarchically organized processing cascade along the cortical ventral stream. The proposed model integrates oriented texture gradient information that is encoded in distributed maps of orientation-frequency representations. The texture energy gradient information is defined by changes in the grouped summed normalized orientation-frequency response activity extracted from the textured object image. This activity is integrated by directed fields to generate a 3D shape representation of a complex object with depth ordering proportional to the fields output, with higher activity denoting larger distance in relative depth away from the viewer. PMID:27649387

The epiphytic microbiota of the globally widespread macroalga Cladophora glomerata (Chlorophyta, Cladophorales).

PubMed

Zulkifly, Shahrizim; Hanshew, Alissa; Young, Erica B; Lee, Philip; Graham, Melissa E; Graham, Michael E; Piotrowski, Michael; Graham, Linda E

2012-09-01

The filamentous chlorophyte Cladophora produces abundant nearshore populations in marine and freshwaters worldwide, often dominating periphyton communities and producing nuisance growths under eutrophic conditions. High surface area and environmental persistence foster such high functional and taxonomic diversity of epiphytic microfauna and microalgae that Cladophora has been labeled an ecological engineer. We tested the hypotheses that (1) Cladophora supports a structurally and functionally diverse epiphytic prokaryotic microbiota that influences materials cycling and (2) mutualistic host-microbe interactions occur. Because previous molecular sequencing-based analyses of the microbiota of C. glomerata found as western Lake Michigan beach drift had identified pathogenic associates such as Escherichia coli, we also asked if actively growing lentic C. glomerata harbors known pathogens. We used 16S rRNA gene amplicon pyrosequencing to examine the microbiota of C. glomerata of Lake Mendota, Dane, Wisconsin, United States, during the growing season of 2011, at the genus- or species-level to infer functional phenotypes. We used correlative scanning electron and fluorescence microscopy to describe major prokaryotic morphotypes. We found microscopic evidence for diverse bacterial morphotypes, and molecular evidence for ca. 100 distinct sequence types classifiable to genus at the 80% confidence level or species at the 96-97% level within nine bacterial phyla, but not E. coli or related human pathogens. We inferred that bacterial epiphytes of lentic C. glomerata have diverse functions in materials cycling, with traits that indicate the occurrence of mutualistic interactions with the algal host.

Can we infer plant facilitation from remote sensing? A test across global drylands

PubMed Central

Xu, Chi; Holmgren, Milena; Van Nes, Egbert H.; Maestre, Fernando T.; Soliveres, Santiago; Berdugo, Miguel; Kéfi, Sonia; Marquet, Pablo A.; Abades, Sebastian; Scheffer, Marten

2016-01-01

Facilitation is a major force shaping the structure and diversity of plant communities in terrestrial ecosystems. Detecting positive plant-plant interactions relies on the combination of field experimentation and the demonstration of spatial association between neighboring plants. This has often restricted the study of facilitation to particular sites, limiting the development of systematic assessments of facilitation over regional and global scales. Here we explore whether the frequency of plant spatial associations detected from high-resolution remotely-sensed images can be used to infer plant facilitation at the community level in drylands around the globe. We correlated the information from remotely-sensed images freely available through Google Earth™ with detailed field assessments, and used a simple individual-based model to generate patch-size distributions using different assumptions about the type and strength of plant-plant interactions. Most of the patterns found from the remotely-sensed images were more right-skewed than the patterns from the null model simulating a random distribution. This suggests that the plants in the studied drylands show stronger spatial clustering than expected by chance. We found that positive plant co-occurrence, as measured in the field, was significantly related to the skewness of vegetation patch-size distribution measured using Google Earth™ images. Our findings suggest that the relative frequency of facilitation may be inferred from spatial pattern signals measured from remotely-sensed images, since facilitation often determines positive co-occurrence among neighboring plants. They pave the road for a systematic global assessment of the role of facilitation in terrestrial ecosystems. PMID:26552256

How Spatial Abilities Enhance, and Are Enhanced by, Dental Education

ERIC Educational Resources Information Center

Hegarty, Mary; Keehner, Madeleine; Khooshabeh, Peter; Montello, Daniel R.

2009-01-01

In two studies with a total of 324 participants, dentistry students were assessed on psychometric measures of spatial ability, reasoning ability, and on new measures of the ability to infer the appearance of a cross-section of a three-dimensional (3-D) object. We examined how these abilities and skills predict success in dental education programs,…

Observing Fearful Faces Leads to Visuo-Spatial Perspective Taking

ERIC Educational Resources Information Center

Zwickel, Jan; Muller, Hermann J.

2010-01-01

A number of recent studies suggested that visuo-spatial perspective taking (VSPT) occurs spontaneously when viewing either a human body or an action by an agent. However, it remains unclear whether VSPT is caused by the observation of an (potential) action or occurs because the observer infers from certain cues that another mind is present…

Changes in Visual/Spatial and Analytic Strategy Use in Organic Chemistry with the Development of Expertise

ERIC Educational Resources Information Center

Vlacholia, Maria; Vosniadou, Stella; Roussos, Petros; Salta, Katerina; Kazi, Smaragda; Sigalas, Michael; Tzougraki, Chryssa

2017-01-01

We present two studies that investigated the adoption of visual/spatial and analytic strategies by individuals at different levels of expertise in the area of organic chemistry, using the Visual Analytic Chemistry Task (VACT). The VACT allows the direct detection of analytic strategy use without drawing inferences about underlying mental…

Spatial Reasoning with External Visualizations: What Matters Is What You See, Not whether You Interact

ERIC Educational Resources Information Center

Keehner, Madeleine; Hegarty, Mary; Cohen, Cheryl; Khooshabeh, Peter; Montello, Daniel R.

2008-01-01

Three experiments examined the effects of interactive visualizations and spatial abilities on a task requiring participants to infer and draw cross sections of a three-dimensional (3D) object. The experiments manipulated whether participants could interactively control a virtual 3D visualization of the object while performing the task, and…

Soil bacterial communities are shaped by temporal and environmental filtering: evidence from a long-term chronosequence.

PubMed

Freedman, Zachary; Zak, Donald R

2015-09-01

Soil microbial communities are abundant, hyper-diverse and mediate global biogeochemical cycles, but we do not yet understand the processes mediating their assembly. Current hypothetical frameworks suggest temporal (e.g. dispersal limitation) and environmental (e.g. soil pH) filters shape microbial community composition; however, there is limited empirical evidence supporting this framework in the hyper-diverse soil environment, particularly at large spatial (i.e. regional to continental) and temporal (i.e. 100 to 1000 years) scales. Here, we present evidence from a long-term chronosequence (4000 years) that temporal and environmental filters do indeed shape soil bacterial community composition. Furthermore, nearly 20 years of environmental monitoring allowed us to control for potentially confounding environmental variation. Soil bacterial communities were phylogenetically distinct across the chronosequence. We determined that temporal and environmental factors accounted for significant portions of bacterial phylogenetic structure using distance-based linear models. Environmental factors together accounted for the majority of phylogenetic structure, namely, soil temperature (19%), pH (17%) and litter carbon:nitrogen (C:N; 17%). However, of all individual factors, time since deglaciation accounted for the greatest proportion of bacterial phylogenetic structure (20%). Taken together, our results provide empirical evidence that temporal and environmental filters act together to structure soil bacterial communities across large spatial and long-term temporal scales. © 2015 Society for Applied Microbiology and John Wiley & Sons Ltd.

Bacterial taxa–area and distance–decay relationships in marine environments

PubMed Central

Zinger, L; Boetius, A; Ramette, A

2014-01-01

The taxa–area relationship (TAR) and the distance–decay relationship (DDR) both describe spatial turnover of taxa and are central patterns of biodiversity. Here, we compared TAR and DDR of bacterial communities across different marine realms and ecosystems at the global scale. To obtain reliable global estimates for both relationships, we quantified the poorly assessed effects of sequencing depth, rare taxa removal and number of sampling sites. Slope coefficients of bacterial TARs were within the range of those of plants and animals, whereas slope coefficients of bacterial DDR were much lower. Slope coefficients were mostly affected by removing rare taxa and by the number of sampling sites considered in the calculations. TAR and DDR slope coefficients were overestimated at sequencing depth <4000 sequences per sample. Noticeably, bacterial TAR and DDR patterns did not correlate with each other both within and across ecosystem types, suggesting that (i) TAR cannot be directly derived from DDR and (ii) TAR and DDR may be influenced by different ecological factors. Nevertheless, we found marine bacterial TAR and DDR to be steeper in ecosystems associated with high environmental heterogeneity or spatial isolation, namely marine sediments and coastal environments compared with pelagic ecosystems. Hence, our study provides information on macroecological patterns of marine bacteria, as well as methodological and conceptual insights, at a time when biodiversity surveys increasingly make use of high-throughput sequencing technologies. PMID:24460915

Local dependence in random graph models: characterization, properties and statistical inference

PubMed Central

Schweinberger, Michael; Handcock, Mark S.

2015-01-01

Summary Dependent phenomena, such as relational, spatial and temporal phenomena, tend to be characterized by local dependence in the sense that units which are close in a well-defined sense are dependent. In contrast with spatial and temporal phenomena, though, relational phenomena tend to lack a natural neighbourhood structure in the sense that it is unknown which units are close and thus dependent. Owing to the challenge of characterizing local dependence and constructing random graph models with local dependence, many conventional exponential family random graph models induce strong dependence and are not amenable to statistical inference. We take first steps to characterize local dependence in random graph models, inspired by the notion of finite neighbourhoods in spatial statistics and M-dependence in time series, and we show that local dependence endows random graph models with desirable properties which make them amenable to statistical inference. We show that random graph models with local dependence satisfy a natural domain consistency condition which every model should satisfy, but conventional exponential family random graph models do not satisfy. In addition, we establish a central limit theorem for random graph models with local dependence, which suggests that random graph models with local dependence are amenable to statistical inference. We discuss how random graph models with local dependence can be constructed by exploiting either observed or unobserved neighbourhood structure. In the absence of observed neighbourhood structure, we take a Bayesian view and express the uncertainty about the neighbourhood structure by specifying a prior on a set of suitable neighbourhood structures. We present simulation results and applications to two real world networks with ‘ground truth’. PMID:26560142

Slip rates and spatially variable creep on faults of the northern San Andreas system inferred through Bayesian inversion of Global Positioning System data

USGS Publications Warehouse

Murray, Jessica R.; Minson, Sarah E.; Svarc, Jerry L.

2014-01-01

Fault creep, depending on its rate and spatial extent, is thought to reduce earthquake hazard by releasing tectonic strain aseismically. We use Bayesian inversion and a newly expanded GPS data set to infer the deep slip rates below assigned locking depths on the San Andreas, Maacama, and Bartlett Springs Faults of Northern California and, for the latter two, the spatially variable interseismic creep rate above the locking depth. We estimate deep slip rates of 21.5 ± 0.5, 13.1 ± 0.8, and 7.5 ± 0.7 mm/yr below 16 km, 9 km, and 13 km on the San Andreas, Maacama, and Bartlett Springs Faults, respectively. We infer that on average the Bartlett Springs fault creeps from the Earth's surface to 13 km depth, and below 5 km the creep rate approaches the deep slip rate. This implies that microseismicity may extend below the locking depth; however, we cannot rule out the presence of locked patches in the seismogenic zone that could generate moderate earthquakes. Our estimated Maacama creep rate, while comparable to the inferred deep slip rate at the Earth's surface, decreases with depth, implying a slip deficit exists. The Maacama deep slip rate estimate, 13.1 mm/yr, exceeds long-term geologic slip rate estimates, perhaps due to distributed off-fault strain or the presence of multiple active fault strands. While our creep rate estimates are relatively insensitive to choice of model locking depth, insufficient independent information regarding locking depths is a source of epistemic uncertainty that impacts deep slip rate estimates.

Spatial organization shapes the turnover of a bacterial transcriptome

PubMed Central

Moffitt, Jeffrey R; Pandey, Shristi; Boettiger, Alistair N; Wang, Siyuan; Zhuang, Xiaowei

2016-01-01

Spatial organization of the transcriptome has emerged as a powerful means for regulating the post-transcriptional fate of RNA in eukaryotes; however, whether prokaryotes use RNA spatial organization as a mechanism for post-transcriptional regulation remains unclear. Here we used super-resolution microscopy to image the E. coli transcriptome and observed a genome-wide spatial organization of RNA: mRNAs encoding inner-membrane proteins are enriched at the membrane, whereas mRNAs encoding outer-membrane, cytoplasmic and periplasmic proteins are distributed throughout the cytoplasm. Membrane enrichment is caused by co-translational insertion of signal peptides recognized by the signal-recognition particle. Time-resolved RNA-sequencing revealed that degradation rates of inner-membrane-protein mRNAs are on average greater that those of the other mRNAs and that this selective destabilization of inner-membrane-protein mRNAs is abolished by dissociating the RNA degradosome from the membrane. Together, these results demonstrate that the bacterial transcriptome is spatially organized and suggest that this organization shapes the post-transcriptional dynamics of mRNAs. DOI: http://dx.doi.org/10.7554/eLife.13065.001 PMID:27198188

Spatial filtering, color constancy, and the color-changing dress.

PubMed

Dixon, Erica L; Shapiro, Arthur G

2017-03-01

The color-changing dress is a 2015 Internet phenomenon in which the colors in a picture of a dress are reported as blue-black by some observers and white-gold by others. The standard explanation is that observers make different inferences about the lighting (is the dress in shadow or bright yellow light?); based on these inferences, observers make a best guess about the reflectance of the dress. The assumption underlying this explanation is that reflectance is the key to color constancy because reflectance alone remains invariant under changes in lighting conditions. Here, we demonstrate an alternative type of invariance across illumination conditions: An object that appears to vary in color under blue, white, or yellow illumination does not change color in the high spatial frequency region. A first approximation to color constancy can therefore be accomplished by a high-pass filter that retains enough low spatial frequency content so as to not to completely desaturate the object. We demonstrate the implications of this idea on the Rubik's cube illusion; on a shirt placed under white, yellow, and blue illuminants; and on spatially filtered images of the dress. We hypothesize that observer perceptions of the dress's color vary because of individual differences in how the visual system extracts high and low spatial frequency color content from the environment, and we demonstrate cross-group differences in average sensitivity to low spatial frequency patterns.

Variation in coastal Antarctic microbial community composition at sub-mesoscale: spatial distance or environmental filtering?

PubMed

Moreno-Pino, Mario; De la Iglesia, Rodrigo; Valdivia, Nelson; Henríquez-Castilo, Carlos; Galán, Alexander; Díez, Beatriz; Trefault, Nicole

2016-07-01

Spatial environmental heterogeneity influences diversity of organisms at different scales. Environmental filtering suggests that local environmental conditions provide habitat-specific scenarios for niche requirements, ultimately determining the composition of local communities. In this work, we analyze the spatial variation of microbial communities across environmental gradients of sea surface temperature, salinity and photosynthetically active radiation and spatial distance in Fildes Bay, King George Island, Antarctica. We hypothesize that environmental filters are the main control of the spatial variation of these communities. Thus, strong relationships between community composition and environmental variation and weak relationships between community composition and spatial distance are expected. Combining physical characterization of the water column, cell counts by flow cytometry, small ribosomal subunit genes fingerprinting and next generation sequencing, we contrast the abundance and composition of photosynthetic eukaryotes and heterotrophic bacterial local communities at a submesoscale. Our results indicate that the strength of the environmental controls differed markedly between eukaryotes and bacterial communities. Whereas eukaryotic photosynthetic assemblages responded weakly to environmental variability, bacteria respond promptly to fine-scale environmental changes in this polar marine system. © FEMS 2016. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

High taxonomic variability despite stable functional structure across microbial communities.

PubMed

Louca, Stilianos; Jacques, Saulo M S; Pires, Aliny P F; Leal, Juliana S; Srivastava, Diane S; Parfrey, Laura Wegener; Farjalla, Vinicius F; Doebeli, Michael

2016-12-05

Understanding the processes that are driving variation of natural microbial communities across space or time is a major challenge for ecologists. Environmental conditions strongly shape the metabolic function of microbial communities; however, other processes such as biotic interactions, random demographic drift or dispersal limitation may also influence community dynamics. The relative importance of these processes and their effects on community function remain largely unknown. To address this uncertainty, here we examined bacterial and archaeal communities in replicate 'miniature' aquatic ecosystems contained within the foliage of wild bromeliads. We used marker gene sequencing to infer the taxonomic composition within nine metabolic functional groups, and shotgun environmental DNA sequencing to estimate the relative abundances of these groups. We found that all of the bromeliads exhibited remarkably similar functional community structures, but that the taxonomic composition within individual functional groups was highly variable. Furthermore, using statistical analyses, we found that non-neutral processes, including environmental filtering and potentially biotic interactions, at least partly shaped the composition within functional groups and were more important than spatial dispersal limitation and demographic drift. Hence both the functional structure and taxonomic composition within functional groups of natural microbial communities may be shaped by non-neutral and roughly separate processes.

Epidemic Spread of Symbiotic and Non-Symbiotic Bradyrhizobium Genotypes Across California.

PubMed

Hollowell, A C; Regus, J U; Gano, K A; Bantay, R; Centeno, D; Pham, J; Lyu, J Y; Moore, D; Bernardo, A; Lopez, G; Patil, A; Patel, S; Lii, Y; Sachs, J L

2016-04-01

The patterns and drivers of bacterial strain dominance remain poorly understood in natural populations. Here, we cultured 1292 Bradyrhizobium isolates from symbiotic root nodules and the soil root interface of the host plant Acmispon strigosus across a >840-km transect in California. To investigate epidemiology and the potential role of accessory loci as epidemic drivers, isolates were genotyped at two chromosomal loci and were assayed for presence or absence of accessory "symbiosis island" loci that encode capacity to form nodules on hosts. We found that Bradyrhizobium populations were very diverse but dominated by few haplotypes-with a single "epidemic" haplotype constituting nearly 30 % of collected isolates and spreading nearly statewide. In many Bradyrhizobium lineages, we inferred presence and absence of the symbiosis island suggesting recurrent evolutionary gain and or loss of symbiotic capacity. We did not find statistical phylogenetic evidence that the symbiosis island acquisition promotes strain dominance and both symbiotic and non-symbiotic strains exhibited population dominance and spatial spread. Our dataset reveals that a strikingly few Bradyrhizobium genotypes can rapidly spread to dominate a landscape and suggests that these epidemics are not driven by the acquisition of accessory loci as occurs in key human pathogens.

Using GIS to generate spatially balanced random survey designs for natural resource applications.

PubMed

Theobald, David M; Stevens, Don L; White, Denis; Urquhart, N Scott; Olsen, Anthony R; Norman, John B

2007-07-01

Sampling of a population is frequently required to understand trends and patterns in natural resource management because financial and time constraints preclude a complete census. A rigorous probability-based survey design specifies where to sample so that inferences from the sample apply to the entire population. Probability survey designs should be used in natural resource and environmental management situations because they provide the mathematical foundation for statistical inference. Development of long-term monitoring designs demand survey designs that achieve statistical rigor and are efficient but remain flexible to inevitable logistical or practical constraints during field data collection. Here we describe an approach to probability-based survey design, called the Reversed Randomized Quadrant-Recursive Raster, based on the concept of spatially balanced sampling and implemented in a geographic information system. This provides environmental managers a practical tool to generate flexible and efficient survey designs for natural resource applications. Factors commonly used to modify sampling intensity, such as categories, gradients, or accessibility, can be readily incorporated into the spatially balanced sample design.

Genetic analysis reveals efficient sexual spore dispersal at a fine spatial scale in Armillaria ostoyae, the causal agent of root-rot disease in conifers.

PubMed

Dutech, Cyril; Labbé, Frédéric; Capdevielle, Xavier; Lung-Escarmant, Brigitte

Armillaria ostoyae (sometimes named Armillaria solidipes) is a fungal species causing root diseases in numerous coniferous forests of the northern hemisphere. The importance of sexual spores for the establishment of new disease centres remains unclear, particularly in the large maritime pine plantations of southwestern France. An analysis of the genetic diversity of a local fungal population distributed over 500 ha in this French forest showed genetic recombination between genotypes to be frequent, consistent with regular sexual reproduction within the population. The estimated spatial genetic structure displayed a significant pattern of isolation by distance, consistent with the dispersal of sexual spores mostly at the spatial scale studied. Using these genetic data, we inferred an effective density of reproductive individuals of 0.1-0.3 individuals/ha, and a second moment of parent-progeny dispersal distance of 130-800 m, compatible with the main models of fungal spore dispersal. These results contrast with those obtained for studies of A. ostoyae over larger spatial scales, suggesting that inferences about mean spore dispersal may be best performed at fine spatial scales (i.e. a few kilometres) for most fungal species. Copyright © 2017 British Mycological Society. Published by Elsevier Ltd. All rights reserved.

Ionospheric and Birkeland current distributions inferred from the MAGSAT magnetometer data

NASA Technical Reports Server (NTRS)

Zanetti, L. J.; Potemra, T. A.; Baumjohann, W.

1983-01-01

Ionospheric and field-aligned sheet current density distributions are presently inferred by means of MAGSAT vector magnetometer data, together with an accurate magnetic field model. By comparing Hall current densities inferred from the MAGSAT data and those inferred from simultaneously recorded ground based data acquired by the Scandinavian magnetometer array, it is determined that the former have previously been underestimated due to high damping of magnetic variations with high spatial wave numbers between the ionosphere and the MAGSAT orbit. Among important results of this study is noted the fact that the Birkeland and electrojet current systems are colocated. The analyses have shown a tendency for triangular rather than constant electrojet current distributions as a function of latitude, consistent with the statistical, uniform regions 1 and 2 Birkeland current patterns.

Real-time detection of antibiotic activity by measuring nanometer-scale bacterial deformation.

PubMed

Iriya, Rafael; Syal, Karan; Jing, Wenwen; Mo, Manni; Yu, Hui; Haydel, Shelley E; Wang, Shaopeng; Tao, Nongjian

2017-12-01

Diagnosing antibiotic-resistant bacteria currently requires sensitive detection of phenotypic changes associated with antibiotic action on bacteria. Here, we present an optical imaging-based approach to quantify bacterial membrane deformation as a phenotypic feature in real-time with a nanometer scale (∼9  nm) detection limit. Using this approach, we found two types of antibiotic-induced membrane deformations in different bacterial strains: polymyxin B induced relatively uniform spatial deformation of Escherichia coli O157:H7 cells leading to change in cellular volume and ampicillin-induced localized spatial deformation leading to the formation of bulges or protrusions on uropathogenic E. coli CFT073 cells. We anticipate that the approach will contribute to understanding of antibiotic phenotypic effects on bacteria with a potential for applications in rapid antibiotic susceptibility testing. (2017) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE).

Spatial relationships among soil biota in a contaminated grassland ecosystem at Aberdeen Proving Ground, Maryland

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

Kuperman, R.; Williams, G.; Parmelee, R.

1995-12-31

Spatial relationships among soil nematodes and soil microorganisms were investigated in a grassland ecosystem contaminated with heavy metals in the US Army`s Aberdeen Proving Ground. The study quantified fungal and bacterial biomass, the abundance of soil protozoa, and nematodes. Geostatistical techniques were used to determine spatial distributions of these parameters and to evaluate various cross-correlations. The cross-correlations among soil biota numbers were analyzed using two methods: a cross general relative semi-variogram and an interactive graphical data representation using geostatistically estimated data distributions. Both the visualization technique and the cross general relative semi-variogram and an interactive graphical data representation using geostatisticallymore » estimated data distributions. Both the visualization technique and the cross general relative semi-variogram showed a negative correlation between the abundance of fungivore nematodes and fungal biomass, the abundance of bacterivore nematodes and bacterial biomass, the abundance of omnivore/predator nematodes and numbers of protozoa, and between numbers of protozoa and both fungal and bacterial biomass. The negative cross-correlation between soil biota and metal concentrations showed that soil fungi were particularly sensitive to heavy metal concentrations and can be used for quantitative ecological risk assessment of metal-contaminated soils. This study found that geostatistics are a useful tool for describing and analyzing spatial relationships among components of food webs in the soil community.« less

Spatial scaling of bacterial community diversity at shallow hydrothermal vents: a global comparison

NASA Astrophysics Data System (ADS)

Pop Ristova, P.; Hassenrueck, C.; Molari, M.; Fink, A.; Bühring, S. I.

2016-02-01

Marine shallow hydrothermal vents are extreme environments, often characterized by discharge of fluids with e.g. high temperatures, low pH, and laden with elements toxic to higher organisms. They occur at continental margins around the world's oceans, but represent fragmented, isolated habitats of locally small areal coverage. Microorganisms contribute the main biomass at shallow hydrothermal vent ecosystems and build the basis of the food chain by autotrophic fixation of carbon both via chemosynthesis and photosynthesis, occurring simultaneously. Despite their importance and unique capacity to adapt to these extreme environments, little is known about the spatial scales on which the alpha- and beta-diversity of microbial communities vary at shallow vents, and how the geochemical habitat heterogeneity influences shallow vent biodiversity. Here for the first time we investigated the spatial scaling of microbial biodiversity patterns and their interconnectivity at geochemically diverse shallow vents on a global scale. This study presents data on the comparison of bacterial community structures on large (> 1000 km) and small (0.1 - 100 m) spatial scales as derived from ARISA and Illumina sequencing. Despite the fragmented global distribution of shallow hydrothermal vents, similarity of vent bacterial communities decreased with geographic distance, confirming the ubiquity of distance-decay relationship. Moreover, at all investigated vents, pH was the main factor locally structuring these communities, while temperature influenced both the alpha- and beta-diversity.

Spatio-temporal transitions in the dynamics of bacterial populations

NASA Astrophysics Data System (ADS)

Lin, Anna; Lincoln, Bryan; Mann, Bernward; Torres, Gelsy; Kas, Josef; Swinney, Harry

2001-03-01

We experimentally investigate the population dynamics of a strain of E. coli bacteria living under spatially inhomogeneous growth conditions. A localized perturbation that moves with a well-defined drift velocity is imposed on the system. A reaction-diffusion model of this situation^1 predicts that an abrupt transition between spatial localization and extinction of the colony occurs for a fixed average growth rate when the drift velocity exceeds a critical value. Also, a transition between localized and delocalized populations is predicted to occur at a fixed drift velocity when the spatially averaged growth rate is varied. We create a spatially localized perturbation with UV light and vary the strength and drift velocity of the perturbation to investigate the existence of the different bacterial population distributions and the transitions between them. Numerical simulations of a 250 mm by 20 mm system guide our experiments. ^1K. A. Dahmen, D. R. Nelson, N. M. Shnerb, Jour. Math. Bio., 41 1 (2000).

THE EVOLUTION OF RESTRAINT IN BACTERIAL BIOFILMS UNDER NONTRANSITIVE COMPETITION

PubMed Central

Prado, Federico; Kerr, Benjamin

2009-01-01

Theoretical and empirical evidence indicates that competing species can coexist if dispersal, migration, and competitive interactions occur over relatively small spatial scales. In particular, spatial structure appears to be critical to certain communities with nontransitive competition. A typical nontransitive system involves three competing species that satisfy a relationship similar to the children’s game of rock–paper–scissors. Although the ecological dynamics of nontransitive systems in spatially structured communities have received some attention, fewer studies have incorporated evolutionary change. Here we investigate evolution within toxic bacterial biofilms using an agent-based simulation that represents a nontransitive community containing three populations of Escherichia coli. In structured, nontransitive communities, strains evolve that do not maximize their competitive ability: They do not reduce their probability of death to a minimum or increase their toxicity to a maximum. That is, types evolve that exercise restraint. We show that nontransitivity and spatial structure (in the form of localized interactions) are both necessary for the evolution of restraint in these biofilms. PMID:18039324

The evolution of restraint in bacterial biofilms under nontransitive competition.

PubMed

Prado, Federico; Kerr, Benjamin

2008-03-01

Theoretical and empirical evidence indicates that competing species can coexist if dispersal, migration, and competitive interactions occur over relatively small spatial scales. In particular, spatial structure appears to be critical to certain communities with nontransitive competition. A typical nontransitive system involves three competing species that satisfy a relationship similar to the children's game of rock-paper-scissors. Although the ecological dynamics of nontransitive systems in spatially structured communities have received some attention, fewer studies have incorporated evolutionary change. Here we investigate evolution within toxic bacterial biofilms using an agent-based simulation that represents a nontransitive community containing three populations of Escherichia coli. In structured, nontransitive communities, strains evolve that do not maximize their competitive ability: They do not reduce their probability of death to a minimum or increase their toxicity to a maximum. That is, types evolve that exercise restraint. We show that nontransitivity and spatial structure (in the form of localized interactions) are both necessary for the evolution of restraint in these biofilms.

Assessing NARCCAP climate model effects using spatial confidence regions

PubMed Central

French, Joshua P.; McGinnis, Seth; Schwartzman, Armin

2017-01-01

We assess similarities and differences between model effects for the North American Regional Climate Change Assessment Program (NARCCAP) climate models using varying classes of linear regression models. Specifically, we consider how the average temperature effect differs for the various global and regional climate model combinations, including assessment of possible interaction between the effects of global and regional climate models. We use both pointwise and simultaneous inference procedures to identify regions where global and regional climate model effects differ. We also show conclusively that results from pointwise inference are misleading, and that accounting for multiple comparisons is important for making proper inference. PMID:28936474

Host-to-host variation of ecological interactions in polymicrobial infections

NASA Astrophysics Data System (ADS)

Mukherjee, Sayak; Weimer, Kristin E.; Seok, Sang-Cheol; Ray, Will C.; Jayaprakash, C.; Vieland, Veronica J.; Swords, W. Edward; Das, Jayajit

2015-02-01

Host-to-host variability with respect to interactions between microorganisms and multicellular hosts are commonly observed in infection and in homeostasis. However, the majority of mechanistic models used to analyze host-microorganism relationships, as well as most of the ecological theories proposed to explain coevolution of hosts and microbes, are based on averages across a host population. By assuming that observed variations are random and independent, these models overlook the role of differences between hosts. Here, we analyze mechanisms underlying host-to-host variations of bacterial infection kinetics, using the well characterized experimental infection model of polymicrobial otitis media (OM) in chinchillas, in combination with population dynamic models and a maximum entropy (MaxEnt) based inference scheme. We find that the nature of the interactions between bacterial species critically regulates host-to-host variations in these interactions. Surprisingly, seemingly unrelated phenomena, such as the efficiency of individual bacterial species in utilizing nutrients for growth, and the microbe-specific host immune response, can become interdependent in a host population. The latter finding suggests a potential mechanism that could lead to selection of specific strains of bacterial species during the coevolution of the host immune response and the bacterial species.

Coupled cryoconite ecosystem structure-function relationships are revealed by comparing bacterial communities in alpine and Arctic glaciers.

PubMed

Edwards, Arwyn; Mur, Luis A J; Girdwood, Susan E; Anesio, Alexandre M; Stibal, Marek; Rassner, Sara M E; Hell, Katherina; Pachebat, Justin A; Post, Barbara; Bussell, Jennifer S; Cameron, Simon J S; Griffith, Gareth Wyn; Hodson, Andrew J; Sattler, Birgit

2014-08-01

Cryoconite holes are known as foci of microbial diversity and activity on polar glacier surfaces, but are virtually unexplored microbial habitats in alpine regions. In addition, whether cryoconite community structure reflects ecosystem functionality is poorly understood. Terminal restriction fragment length polymorphism and Fourier transform infrared metabolite fingerprinting of cryoconite from glaciers in Austria, Greenland and Svalbard demonstrated cryoconite bacterial communities are closely correlated with cognate metabolite fingerprints. The influence of bacterial-associated fatty acids and polysaccharides was inferred, underlining the importance of bacterial community structure in the properties of cryoconite. Thus, combined application of T-RFLP and FT-IR metabolite fingerprinting promises high throughput, and hence, rapid assessment of community structure-function relationships. Pyrosequencing revealed Proteobacteria were particularly abundant, with Cyanobacteria likely acting as ecosystem engineers in both alpine and Arctic cryoconite communities. However, despite these generalities, significant differences in bacterial community structures, compositions and metabolomes are found between alpine and Arctic cryoconite habitats, reflecting the impact of local and regional conditions on the challenges of thriving in glacial ecosystems. © 2014 Federation of European Microbiological Societies. Published by John Wiley & Sons Ltd. All rights reserved.

Temporal and Spatial Variations of Bacterial and Faunal Communities Associated with Deep-Sea Wood Falls.

PubMed

Pop Ristova, Petra; Bienhold, Christina; Wenzhöfer, Frank; Rossel, Pamela E; Boetius, Antje

2017-01-01

Sinking of large organic food falls i.e. kelp, wood and whale carcasses to the oligotrophic deep-sea floor promotes the establishment of locally highly productive and diverse ecosystems, often with specifically adapted benthic communities. However, the fragmented spatial distribution and small area poses challenges for the dispersal of their microbial and faunal communities. Our study focused on the temporal dynamics and spatial distributions of sunken wood bacterial communities, which were deployed in the vicinity of different cold seeps in the Eastern Mediterranean and the Norwegian deep-seas. By combining fingerprinting of bacterial communities by ARISA and 454 sequencing with in situ and ex situ biogeochemical measurements, we show that sunken wood logs have a locally confined long-term impact (> 3y) on the sediment geochemistry and community structure. We confirm previous hypotheses of different successional stages in wood degradation including a sulphophilic one, attracting chemosynthetic fauna from nearby seep systems. Wood experiments deployed at similar water depths (1100-1700 m), but in hydrographically different oceanic regions harbored different wood-boring bivalves, opportunistic faunal communities, and chemosynthetic species. Similarly, bacterial communities on sunken wood logs were more similar within one geographic region than between different seas. Diverse sulphate-reducing bacteria of the Deltaproteobacteria, the sulphide-oxidizing bacteria Sulfurovum as well as members of the Acidimicrobiia and Bacteroidia dominated the wood falls in the Eastern Mediterranean, while Alphaproteobacteria and Flavobacteriia colonized the Norwegian Sea wood logs. Fauna and bacterial wood-associated communities changed between 1 to 3 years of immersion, with sulphate-reducers and sulphide-oxidizers increasing in proportion, and putative cellulose degraders decreasing with time. Only 6% of all bacterial genera, comprising the core community, were found at any time on the Eastern Mediterranean sunken wooden logs. This study suggests that biogeography and succession play an important role for the composition of bacteria and fauna of wood-associated communities, and that wood can act as stepping-stones for seep biota.

Temporal and Spatial Variations of Bacterial and Faunal Communities Associated with Deep-Sea Wood Falls

PubMed Central

Bienhold, Christina; Wenzhöfer, Frank; Rossel, Pamela E.; Boetius, Antje

2017-01-01

Sinking of large organic food falls i.e. kelp, wood and whale carcasses to the oligotrophic deep-sea floor promotes the establishment of locally highly productive and diverse ecosystems, often with specifically adapted benthic communities. However, the fragmented spatial distribution and small area poses challenges for the dispersal of their microbial and faunal communities. Our study focused on the temporal dynamics and spatial distributions of sunken wood bacterial communities, which were deployed in the vicinity of different cold seeps in the Eastern Mediterranean and the Norwegian deep-seas. By combining fingerprinting of bacterial communities by ARISA and 454 sequencing with in situ and ex situ biogeochemical measurements, we show that sunken wood logs have a locally confined long-term impact (> 3y) on the sediment geochemistry and community structure. We confirm previous hypotheses of different successional stages in wood degradation including a sulphophilic one, attracting chemosynthetic fauna from nearby seep systems. Wood experiments deployed at similar water depths (1100–1700 m), but in hydrographically different oceanic regions harbored different wood-boring bivalves, opportunistic faunal communities, and chemosynthetic species. Similarly, bacterial communities on sunken wood logs were more similar within one geographic region than between different seas. Diverse sulphate-reducing bacteria of the Deltaproteobacteria, the sulphide-oxidizing bacteria Sulfurovum as well as members of the Acidimicrobiia and Bacteroidia dominated the wood falls in the Eastern Mediterranean, while Alphaproteobacteria and Flavobacteriia colonized the Norwegian Sea wood logs. Fauna and bacterial wood-associated communities changed between 1 to 3 years of immersion, with sulphate-reducers and sulphide-oxidizers increasing in proportion, and putative cellulose degraders decreasing with time. Only 6% of all bacterial genera, comprising the core community, were found at any time on the Eastern Mediterranean sunken wooden logs. This study suggests that biogeography and succession play an important role for the composition of bacteria and fauna of wood-associated communities, and that wood can act as stepping-stones for seep biota. PMID:28122036

Predicting gene regulatory networks by combining spatial and temporal gene expression data in Arabidopsis root stem cells

PubMed Central

de Luis Balaguer, Maria Angels; Fisher, Adam P.; Clark, Natalie M.; Fernandez-Espinosa, Maria Guadalupe; Möller, Barbara K.; Weijers, Dolf; Williams, Cranos; Lorenzo, Oscar; Sozzani, Rosangela

2017-01-01

Identifying the transcription factors (TFs) and associated networks involved in stem cell regulation is essential for understanding the initiation and growth of plant tissues and organs. Although many TFs have been shown to have a role in the Arabidopsis root stem cells, a comprehensive view of the transcriptional signature of the stem cells is lacking. In this work, we used spatial and temporal transcriptomic data to predict interactions among the genes involved in stem cell regulation. To accomplish this, we transcriptionally profiled several stem cell populations and developed a gene regulatory network inference algorithm that combines clustering with dynamic Bayesian network inference. We leveraged the topology of our networks to infer potential major regulators. Specifically, through mathematical modeling and experimental validation, we identified PERIANTHIA (PAN) as an important molecular regulator of quiescent center function. The results presented in this work show that our combination of molecular biology, computational biology, and mathematical modeling is an efficient approach to identify candidate factors that function in the stem cells. PMID:28827319

Uncertain relational reasoning in the parietal cortex.

PubMed

Ragni, Marco; Franzmeier, Imke; Maier, Simon; Knauff, Markus

2016-04-01

The psychology of reasoning is currently transitioning from the study of deductive inferences under certainty to inferences that have degrees of uncertainty in both their premises and conclusions; however, only a few studies have explored the cortical basis of uncertain reasoning. Using transcranial magnetic stimulation (TMS), we show that areas in the right superior parietal lobe (rSPL) are necessary for solving spatial relational reasoning problems under conditions of uncertainty. Twenty-four participants had to decide whether a single presented order of objects agreed with a given set of indeterminate premises that could be interpreted in more than one way. During the presentation of the order, 10-Hz TMS was applied over the rSPL or a sham control site. Right SPL TMS during the inference phase disrupted performance in uncertain relational reasoning. Moreover, we found differences in the error rates between preferred mental models, alternative models, and inconsistent models. Our results suggest that different mechanisms are involved when people reason spatially and evaluate different kinds of uncertain conclusions. Copyright © 2016 Elsevier Inc. All rights reserved.

Exploring the effects of photon correlations from thermal sources on bacterial photosynthesis

NASA Astrophysics Data System (ADS)

Manrique, Pedro D.; Caycedo-Soler, Felipe; De Mendoza, Adriana; Rodríguez, Ferney; Quiroga, Luis; Johnson, Neil F.

Thermal light sources can produce photons with strong spatial correlations. We study the role that these correlations might potentially play in bacterial photosynthesis. Our findings show a relationship between the transversal distance between consecutive absorptions and the efficiency of the photosynthetic process. Furthermore, membranes where the clustering of core complexes (so-called RC-LH1) is high, display a range where the organism profits maximally from the spatial correlation of the incoming light. By contrast, no maximum is found for membranes with low core-core clustering. We employ a detailed membrane model with state-of-the-art empirical inputs. Our results suggest that the organization of the membrane's antenna complexes may be well-suited to the spatial correlations present in an natural light source. Future experiments will be needed to test this prediction.

Evidence that Intraspecific Trait Variation among Nasal Bacteria Shapes the Distribution of Staphylococcus aureus

PubMed Central

Libberton, Ben; Coates, Rosanna E.

2014-01-01

Nasal carriage of Staphylococcus aureus is a risk factor for infection, yet the bacterial determinants required for carriage are poorly defined. Interactions between S. aureus and other members of the bacterial flora may determine colonization and have been inferred in previous studies by using correlated species distributions. However, traits mediating species interactions are often polymorphic, suggesting that understanding how interactions structure communities requires a trait-based approach. We characterized S. aureus growth inhibition by the culturable bacterial aerobe consortia of 60 nasal microbiomes, and this revealed intraspecific variation in growth inhibition and that inhibitory isolates clustered within communities that were culture negative for S. aureus. Across microbiomes, the cumulative community-level growth inhibition was negatively associated with S. aureus incidence. To fully understand the ecological processes structuring microbiomes, it will be crucial to account for intraspecific variation in the traits that mediate species interactions. PMID:24980973

Tracking the Remodeling of SNOMED CT's Bacterial Infectious Diseases.

PubMed

Ochs, Christopher; Case, James T; Perl, Yehoshua

2016-01-01

SNOMED CT's content undergoes many changes from one release to the next. Over the last year SNOMED CT's Bacterial infectious disease subhierarchy has undergone significant editing to bring consistent modeling to its concepts. In this paper we analyze the stated and inferred structural modifications that affected the Bacterial infectious disease subhierarchy between the Jan 2015 and Jan 2016 SNOMED CT releases using a two-phased approach. First, we introduce a methodology for creating a human readable list of changes. Next, we utilize partial-area taxonomies, which are compact summaries of SNOMED CT's content and structure, to identify the "big picture" changes that occurred in the subhierarchy. We illustrate how partial-area taxonomies can be used to help identify groups of concepts that were affected by these editing operations and the nature of these changes. Modeling issues identified using our two-phase methodology are discussed.

BAC-end sequence-based SNP mining in Allotetraploid Cotton (Gossypium) utilizing re-sequencing data, phylogenetic inferences and perspectives for genetic mapping

USDA-ARS?s Scientific Manuscript database

A bacterial artificial chromosome (BAC) library and BAC-end sequences for Gossypium hirsutum L. have recently been developed. Here we report on genomic-based genome-wide SNP mining utilizing re-sequencing data with a BAC-end sequence reference for twelve G. hirsutum L. lines, one G. barbadense L. li...

Effects of predation and dispersal on bacterial abundance and contaminant biodegradation.

PubMed

Otto, Sally; Harms, Hauke; Wick, Lukas Y

2017-02-01

Research into the biodegradation of soil contaminants has rarely addressed the consequences of predator-prey interactions. Here, we investigated the joint effect of predation and dispersal networks on contaminant degradation by linking spatial abundances of degrader (Pseudomonas fluorescens LP6a) and predator (Bdellovibrio bacteriovorus) bacteria to the degradation of the major soil contaminant phenanthrene (PHE). We used a laboratory microcosm with a PHE passive dosing system and a glass fiber network to facilitate bacterial dispersal. Different predator-to-prey ratios and spatial arrangements of prey and predator inoculation were used to study predation pressure effects on PHE degradation. We observed that predation resulted in (i) enhanced PHE-degradation at low predator counts (PC) compared to controls lacking predation, (ii) reduced PHE-degradation at elevated PC relative to low PC, and (iii) significant effects of the spatial arrangement of prey and predator inoculation on PHE degradation. Our data suggest that predation facilitated by dispersal networks (such as fungal mycelia) may support the build-up of an effective bacterial biomass and, hence, contaminant biodegradation in heterogeneous systems such as soil. © FEMS 2016. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Spatial scale affects the relative role of stochasticity versus determinism in soil bacterial communities in wheat fields across the North China Plain.

PubMed

Shi, Yu; Li, Yuntao; Xiang, Xingjia; Sun, Ruibo; Yang, Teng; He, Dan; Zhang, Kaoping; Ni, Yingying; Zhu, Yong-Guan; Adams, Jonathan M; Chu, Haiyan

2018-02-05

The relative importance of stochasticity versus determinism in soil bacterial communities is unclear, as are the possible influences that alter the balance between these. Here, we investigated the influence of spatial scale on the relative role of stochasticity and determinism in agricultural monocultures consisting only of wheat, thereby minimizing the influence of differences in plant species cover and in cultivation/disturbance regime, extending across a wide range of soils and climates of the North China Plain (NCP). We sampled 243 sites across 1092 km and sequenced the 16S rRNA bacterial gene using MiSeq. We hypothesized that determinism would play a relatively stronger role at the broadest scales, due to the strong influence of climate and soil differences in selecting many distinct OTUs of bacteria adapted to the different environments. In order to test the more general applicability of the hypothesis, we also compared with a natural ecosystem on the Tibetan Plateau. Our results revealed that the relative importance of stochasticity vs. determinism did vary with spatial scale, in the direction predicted. On the North China Plain, stochasticity played a dominant role from 150 to 900 km (separation between pairs of sites) and determinism dominated at more than 900 km (broad scale). On the Tibetan Plateau, determinism played a dominant role from 130 to 1200 km and stochasticity dominated at less than 130 km. Among the identifiable deterministic factors, soil pH showed the strongest influence on soil bacterial community structure and diversity across the North China Plain. Together, 23.9% of variation in soil microbial community composition could be explained, with environmental factors accounting for 19.7% and spatial parameters 4.1%. Our findings revealed that (1) stochastic processes are relatively more important on the North China Plain, while deterministic processes are more important on the Tibetan Plateau; (2) soil pH was the major factor in shaping soil bacterial community structure of the North China Plain; and (3) most variation in soil microbial community composition could not be explained with existing environmental and spatial factors. Further studies are needed to dissect the influence of stochastic factors (e.g., mutations or extinctions) on soil microbial community distribution, which might make it easier to predictably manipulate the microbial community to produce better yield and soil sustainability outcomes.

A Fuzzy Logic Based Controller for the Automated Alignment of a Laser-beam-smoothing Spatial Filter

NASA Technical Reports Server (NTRS)

Krasowski, M. J.; Dickens, D. E.

1992-01-01

A fuzzy logic based controller for a laser-beam-smoothing spatial filter is described. It is demonstrated that a human operator's alignment actions can easily be described by a system of fuzzy rules of inference. The final configuration uses inexpensive, off-the-shelf hardware and allows for a compact, readily implemented embedded control system.

Connectopic mapping with resting-state fMRI.

PubMed

Haak, Koen V; Marquand, Andre F; Beckmann, Christian F

2018-04-15

Brain regions are often topographically connected: nearby locations within one brain area connect with nearby locations in another area. Mapping these connection topographies, or 'connectopies' in short, is crucial for understanding how information is processed in the brain. Here, we propose principled, fully data-driven methods for mapping connectopies using functional magnetic resonance imaging (fMRI) data acquired at rest by combining spectral embedding of voxel-wise connectivity 'fingerprints' with a novel approach to spatial statistical inference. We apply the approach in human primary motor and visual cortex, and show that it can trace biologically plausible, overlapping connectopies in individual subjects that follow these regions' somatotopic and retinotopic maps. As a generic mechanism to perform inference over connectopies, the new spatial statistics approach enables rigorous statistical testing of hypotheses regarding the fine-grained spatial profile of functional connectivity and whether that profile is different between subjects or between experimental conditions. The combined framework offers a fundamental alternative to existing approaches to investigating functional connectivity in the brain, from voxel- or seed-pair wise characterizations of functional association, towards a full, multivariate characterization of spatial topography. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Implementations of geographically weighted lasso in spatial data with multicollinearity (Case study: Poverty modeling of Java Island)

NASA Astrophysics Data System (ADS)

Setiyorini, Anis; Suprijadi, Jadi; Handoko, Budhi

2017-03-01

Geographically Weighted Regression (GWR) is a regression model that takes into account the spatial heterogeneity effect. In the application of the GWR, inference on regression coefficients is often of interest, as is estimation and prediction of the response variable. Empirical research and studies have demonstrated that local correlation between explanatory variables can lead to estimated regression coefficients in GWR that are strongly correlated, a condition named multicollinearity. It later results on a large standard error on estimated regression coefficients, and, hence, problematic for inference on relationships between variables. Geographically Weighted Lasso (GWL) is a method which capable to deal with spatial heterogeneity and local multicollinearity in spatial data sets. GWL is a further development of GWR method, which adds a LASSO (Least Absolute Shrinkage and Selection Operator) constraint in parameter estimation. In this study, GWL will be applied by using fixed exponential kernel weights matrix to establish a poverty modeling of Java Island, Indonesia. The results of applying the GWL to poverty datasets show that this method stabilizes regression coefficients in the presence of multicollinearity and produces lower prediction and estimation error of the response variable than GWR does.

Spatial Variability of PAHs and Microbial Community Structure in Surrounding Surficial Soil of Coal-Fired Power Plants in Xuzhou, China

PubMed Central

Ma, Jing; Zhang, Wangyuan; Chen, Yi; Zhang, Shaoliang; Feng, Qiyan; Hou, Huping; Chen, Fu

2016-01-01

This work investigated the spatial profile and source analysis of polycyclic aromatic hydrocarbons (PAHs) in soil that surrounds coal-fired power plants in Xuzhou, China. High-throughput sequencing was employed to investigate the composition and structure of soil bacterial communities. The total concentration of 15 PAHs in the surface soils ranged from 164.87 to 3494.81 μg/kg dry weight. The spatial profile of PAHs was site-specific with a concentration of 1400.09–3494.81 μg/kg in Yaozhuang. Based on the qualitative and principal component analysis results, coal burning and vehicle emission were found to be the main sources of PAHs in the surface soils. The phylogenetic analysis revealed differences in bacterial community compositions among different sampling sites. Proteobacteria was the most abundant phylum, while Acidobacteria was the second most abundant. The orders of Campylobacterales, Desulfobacterales and Hydrogenophilales had the most significant differences in relative abundance among the sampling sites. The redundancy analysis revealed that the differences in bacterial communities could be explained by the organic matter content. They could also be explicated by the acenaphthene concentration with longer arrows. Furthermore, OTUs of Proteobacteria phylum plotted around particular samples were confirmed to have a different composition of Proteobacteria phylum among the sample sites. Evaluating the relationship between soil PAHs concentration and bacterial community composition may provide useful information for the remediation of PAH contaminated sites. PMID:27598188

Spatial Variability of PAHs and Microbial Community Structure in Surrounding Surficial Soil of Coal-Fired Power Plants in Xuzhou, China.

PubMed

Ma, Jing; Zhang, Wangyuan; Chen, Yi; Zhang, Shaoliang; Feng, Qiyan; Hou, Huping; Chen, Fu

2016-09-02

This work investigated the spatial profile and source analysis of polycyclic aromatic hydrocarbons (PAHs) in soil that surrounds coal-fired power plants in Xuzhou, China. High-throughput sequencing was employed to investigate the composition and structure of soil bacterial communities. The total concentration of 15 PAHs in the surface soils ranged from 164.87 to 3494.81 μg/kg dry weight. The spatial profile of PAHs was site-specific with a concentration of 1400.09-3494.81 μg/kg in Yaozhuang. Based on the qualitative and principal component analysis results, coal burning and vehicle emission were found to be the main sources of PAHs in the surface soils. The phylogenetic analysis revealed differences in bacterial community compositions among different sampling sites. Proteobacteria was the most abundant phylum, while Acidobacteria was the second most abundant. The orders of Campylobacterales, Desulfobacterales and Hydrogenophilales had the most significant differences in relative abundance among the sampling sites. The redundancy analysis revealed that the differences in bacterial communities could be explained by the organic matter content. They could also be explicated by the acenaphthene concentration with longer arrows. Furthermore, OTUs of Proteobacteria phylum plotted around particular samples were confirmed to have a different composition of Proteobacteria phylum among the sample sites. Evaluating the relationship between soil PAHs concentration and bacterial community composition may provide useful information for the remediation of PAH contaminated sites.

Curved tails in polymerization-based bacterial motility

NASA Astrophysics Data System (ADS)

Rutenberg, Andrew D.; Grant, Martin

2001-08-01

The curved actin ``comet-tail'' of the bacterium Listeria monocytogenes is a visually striking signature of actin polymerization-based motility. Similar actin tails are associated with Shigella flexneri, spotted-fever Rickettsiae, the Vaccinia virus, and vesicles and microspheres in related in vitro systems. We show that the torque required to produce the curvature in the tail can arise from randomly placed actin filaments pushing the bacterium or particle. We find that the curvature magnitude determines the number of actively pushing filaments, independent of viscosity and of the molecular details of force generation. The variation of the curvature with time can be used to infer the dynamics of actin filaments at the bacterial surface.

Whole Genome Sequencing Reveals Local Transmission Patterns of Mycobacterium bovis in Sympatric Cattle and Badger Populations

PubMed Central

Wright, David; Mallon, Tom; McCormick, Carl; Orton, Richard J.; McDowell, Stanley; Trewby, Hannah; Skuce, Robin A.; Kao, Rowland R.

2012-01-01

Whole genome sequencing (WGS) technology holds great promise as a tool for the forensic epidemiology of bacterial pathogens. It is likely to be particularly useful for studying the transmission dynamics of an observed epidemic involving a largely unsampled ‘reservoir’ host, as for bovine tuberculosis (bTB) in British and Irish cattle and badgers. BTB is caused by Mycobacterium bovis, a member of the M. tuberculosis complex that also includes the aetiological agent for human TB. In this study, we identified a spatio-temporally linked group of 26 cattle and 4 badgers infected with the same Variable Number Tandem Repeat (VNTR) type of M. bovis. Single-nucleotide polymorphisms (SNPs) between sequences identified differences that were consistent with bacterial lineages being persistent on or near farms for several years, despite multiple clear whole herd tests in the interim. Comparing WGS data to mathematical models showed good correlations between genetic divergence and spatial distance, but poor correspondence to the network of cattle movements or within-herd contacts. Badger isolates showed between zero and four SNP differences from the nearest cattle isolate, providing evidence for recent transmissions between the two hosts. This is the first direct genetic evidence of M. bovis persistence on farms over multiple outbreaks with a continued, ongoing interaction with local badgers. However, despite unprecedented resolution, directionality of transmission cannot be inferred at this stage. Despite the often notoriously long timescales between time of infection and time of sampling for TB, our results suggest that WGS data alone can provide insights into TB epidemiology even where detailed contact data are not available, and that more extensive sampling and analysis will allow for quantification of the extent and direction of transmission between cattle and badgers. PMID:23209404

Denoising, deconvolving, and decomposing photon observations. Derivation of the D3PO algorithm

NASA Astrophysics Data System (ADS)

Selig, Marco; Enßlin, Torsten A.

2015-02-01

The analysis of astronomical images is a non-trivial task. The D3PO algorithm addresses the inference problem of denoising, deconvolving, and decomposing photon observations. Its primary goal is the simultaneous but individual reconstruction of the diffuse and point-like photon flux given a single photon count image, where the fluxes are superimposed. In order to discriminate between these morphologically different signal components, a probabilistic algorithm is derived in the language of information field theory based on a hierarchical Bayesian parameter model. The signal inference exploits prior information on the spatial correlation structure of the diffuse component and the brightness distribution of the spatially uncorrelated point-like sources. A maximum a posteriori solution and a solution minimizing the Gibbs free energy of the inference problem using variational Bayesian methods are discussed. Since the derivation of the solution is not dependent on the underlying position space, the implementation of the D3PO algorithm uses the nifty package to ensure applicability to various spatial grids and at any resolution. The fidelity of the algorithm is validated by the analysis of simulated data, including a realistic high energy photon count image showing a 32 × 32 arcmin2 observation with a spatial resolution of 0.1 arcmin. In all tests the D3PO algorithm successfully denoised, deconvolved, and decomposed the data into a diffuse and a point-like signal estimate for the respective photon flux components. A copy of the code is available at the CDS via anonymous ftp to http://cdsarc.u-strasbg.fr (ftp://130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/qcat?J/A+A/574/A74

Diversity of Bacterial Communities in Container Habitats of Mosquitoes

PubMed Central

Ponnusamy, Loganathan; Xu, Ning; Stav, Gil; Wesson, Dawn M.; Schal, Coby

2010-01-01

We investigated the bacterial diversity of microbial communities in water-filled, human-made and natural container habitats of the mosquitoes Aedes aegypti and Aedes albopictus in suburban landscapes of New Orleans, Louisiana in 2003. We collected water samples from three classes of containers, including tires (n=12), cemetery urns (n=23), and miscellaneous containers that included two tree holes (n=19). Total genomic DNA was extracted from water samples, and 16S ribosomal DNA fragments (operational taxonomic units, OTUs) were amplified by PCR and separated by denaturing gradient gel electrophoresis (DGGE). The bacterial communities in containers represented diverse DGGE-DNA banding patterns that were not related to the class of container or to the local spatial distribution of containers. Mean richness and evenness of OTUs were highest in water samples from tires. Bacterial phylotypes were identified by comparative sequence analysis of 90 16S rDNA DGGE band amplicons. The majority of sequences were placed in five major taxa: Alpha-, Beta- and Gammaproteobacteria, Actinobacteria, Bacteroidetes, Cyanobacteria, Firmicutes, and an unclassified group; Proteobacteria and Bacteroidetes were the predominant heterotrophic bacteria in containers. The bacterial communities in human-made containers consisted mainly of undescribed species, and a phylogenetic analysis based on 16S rRNA sequences suggested that species composition was independent of both container type and the spatial distribution of containers. Comparative PCR-based, cultivation-independent rRNA surveys of microbial communities associated with mosquito habitats can provide significant insight into community organization and dynamics of bacterial species. PMID:18373113

Microbes on mountainsides: Contrasting elevational patterns of bacterial and plant diversity

PubMed Central

Bryant, Jessica A.; Lamanna, Christine; Morlon, Hélène; Kerkhoff, Andrew J.; Enquist, Brian J.; Green, Jessica L.

2008-01-01

The study of elevational diversity gradients dates back to the foundation of biogeography. Although elevational patterns of plant and animal diversity have been studied for centuries, such patterns have not been reported for microorganisms and remain poorly understood. Here, in an effort to assess the generality of elevational diversity patterns, we examined soil bacterial and plant diversity along an elevation gradient. To gain insight into the forces that structure these patterns, we adopted a multifaceted approach to incorporate information about the structure, diversity, and spatial turnover of montane communities in a phylogenetic context. We found that observed patterns of plant and bacterial diversity were fundamentally different. While bacterial taxon richness and phylogenetic diversity decreased monotonically from the lowest to highest elevations, plants followed a unimodal pattern, with a peak in richness and phylogenetic diversity at mid-elevations. At all elevations bacterial communities had a tendency to be phylogenetically clustered, containing closely related taxa. In contrast, plant communities did not exhibit a uniform phylogenetic structure across the gradient: they became more overdispersed with increasing elevation, containing distantly related taxa. Finally, a metric of phylogenetic beta-diversity showed that bacterial lineages were not randomly distributed, but rather exhibited significant spatial structure across the gradient, whereas plant lineages did not exhibit a significant phylogenetic signal. Quantifying the influence of sample scale in intertaxonomic comparisons remains a challenge. Nevertheless, our findings suggest that the forces structuring microorganism and macroorganism communities along elevational gradients differ. PMID:18695215

Cluster mass inference via random field theory.

PubMed

Zhang, Hui; Nichols, Thomas E; Johnson, Timothy D

2009-01-01

Cluster extent and voxel intensity are two widely used statistics in neuroimaging inference. Cluster extent is sensitive to spatially extended signals while voxel intensity is better for intense but focal signals. In order to leverage strength from both statistics, several nonparametric permutation methods have been proposed to combine the two methods. Simulation studies have shown that of the different cluster permutation methods, the cluster mass statistic is generally the best. However, to date, there is no parametric cluster mass inference available. In this paper, we propose a cluster mass inference method based on random field theory (RFT). We develop this method for Gaussian images, evaluate it on Gaussian and Gaussianized t-statistic images and investigate its statistical properties via simulation studies and real data. Simulation results show that the method is valid under the null hypothesis and demonstrate that it can be more powerful than the cluster extent inference method. Further, analyses with a single subject and a group fMRI dataset demonstrate better power than traditional cluster size inference, and good accuracy relative to a gold-standard permutation test.

Activity and growth efficiency of heterotrophic bacteria in a salt marsh (Ria de Aveiro, Portugal).

PubMed

Cunha, M A; Pedro, R; Almeida, M A; Silva, M H

2005-01-01

Bacterial utilization of monomers is recognized as an important step in the biogeochemical cycling of organic matter. In this study we have compared the heterotrophic activity of bacterial communities from different micro-habitats within a salt marsh environment (Ria de Aveiro, Portugal) in order to establish spatial patterns of bacterial abundance, monomer turnover rates (Tr) and bacterial growth efficiency (BGE). Differences in bacterial abundance and activity could be found between distinct plant rhizospheres. BGE tended to be lower at Halimione portulacoides banks, when compared to Sarcocornia perennis subsp. perennis banks which, on the contrary, showed the highest bacterial densities. Experiments of amendment of natural samples with organic and inorganic supplements indicated that salt marsh bacteria are not strongly regulated by salinity but the increased availability of labile organic matter causes a significant metabolic shift towards mineralization.

Fast and Accurate Multivariate Gaussian Modeling of Protein Families: Predicting Residue Contacts and Protein-Interaction Partners

PubMed Central

Feinauer, Christoph; Procaccini, Andrea; Zecchina, Riccardo; Weigt, Martin; Pagnani, Andrea

2014-01-01

In the course of evolution, proteins show a remarkable conservation of their three-dimensional structure and their biological function, leading to strong evolutionary constraints on the sequence variability between homologous proteins. Our method aims at extracting such constraints from rapidly accumulating sequence data, and thereby at inferring protein structure and function from sequence information alone. Recently, global statistical inference methods (e.g. direct-coupling analysis, sparse inverse covariance estimation) have achieved a breakthrough towards this aim, and their predictions have been successfully implemented into tertiary and quaternary protein structure prediction methods. However, due to the discrete nature of the underlying variable (amino-acids), exact inference requires exponential time in the protein length, and efficient approximations are needed for practical applicability. Here we propose a very efficient multivariate Gaussian modeling approach as a variant of direct-coupling analysis: the discrete amino-acid variables are replaced by continuous Gaussian random variables. The resulting statistical inference problem is efficiently and exactly solvable. We show that the quality of inference is comparable or superior to the one achieved by mean-field approximations to inference with discrete variables, as done by direct-coupling analysis. This is true for (i) the prediction of residue-residue contacts in proteins, and (ii) the identification of protein-protein interaction partner in bacterial signal transduction. An implementation of our multivariate Gaussian approach is available at the website http://areeweb.polito.it/ricerca/cmp/code. PMID:24663061

Ecological modeling from time-series inference: insight into dynamics and stability of intestinal microbiota.

PubMed

Stein, Richard R; Bucci, Vanni; Toussaint, Nora C; Buffie, Charlie G; Rätsch, Gunnar; Pamer, Eric G; Sander, Chris; Xavier, João B

2013-01-01

The intestinal microbiota is a microbial ecosystem of crucial importance to human health. Understanding how the microbiota confers resistance against enteric pathogens and how antibiotics disrupt that resistance is key to the prevention and cure of intestinal infections. We present a novel method to infer microbial community ecology directly from time-resolved metagenomics. This method extends generalized Lotka-Volterra dynamics to account for external perturbations. Data from recent experiments on antibiotic-mediated Clostridium difficile infection is analyzed to quantify microbial interactions, commensal-pathogen interactions, and the effect of the antibiotic on the community. Stability analysis reveals that the microbiota is intrinsically stable, explaining how antibiotic perturbations and C. difficile inoculation can produce catastrophic shifts that persist even after removal of the perturbations. Importantly, the analysis suggests a subnetwork of bacterial groups implicated in protection against C. difficile. Due to its generality, our method can be applied to any high-resolution ecological time-series data to infer community structure and response to external stimuli.

Ecological Modeling from Time-Series Inference: Insight into Dynamics and Stability of Intestinal Microbiota

PubMed Central

Toussaint, Nora C.; Buffie, Charlie G.; Rätsch, Gunnar; Pamer, Eric G.; Sander, Chris; Xavier, João B.

2013-01-01

The intestinal microbiota is a microbial ecosystem of crucial importance to human health. Understanding how the microbiota confers resistance against enteric pathogens and how antibiotics disrupt that resistance is key to the prevention and cure of intestinal infections. We present a novel method to infer microbial community ecology directly from time-resolved metagenomics. This method extends generalized Lotka–Volterra dynamics to account for external perturbations. Data from recent experiments on antibiotic-mediated Clostridium difficile infection is analyzed to quantify microbial interactions, commensal-pathogen interactions, and the effect of the antibiotic on the community. Stability analysis reveals that the microbiota is intrinsically stable, explaining how antibiotic perturbations and C. difficile inoculation can produce catastrophic shifts that persist even after removal of the perturbations. Importantly, the analysis suggests a subnetwork of bacterial groups implicated in protection against C. difficile. Due to its generality, our method can be applied to any high-resolution ecological time-series data to infer community structure and response to external stimuli. PMID:24348232

Small-scale spatial heterogeneity of ecosystem properties, microbial community composition and microbial activities in a temperate mountain forest soil.

PubMed

Štursová, Martina; Bárta, Jiří; Šantrůčková, Hana; Baldrian, Petr

2016-12-01

Forests are recognised as spatially heterogeneous ecosystems. However, knowledge of the small-scale spatial variation in microbial abundance, community composition and activity is limited. Here, we aimed to describe the heterogeneity of environmental properties, namely vegetation, soil chemical composition, fungal and bacterial abundance and community composition, and enzymatic activity, in the topsoil in a small area (36 m 2 ) of a highly heterogeneous regenerating temperate natural forest, and to explore the relationships among these variables. The results demonstrated a high level of spatial heterogeneity in all properties and revealed differences between litter and soil. Fungal communities had substantially higher beta-diversity than bacterial communities, which were more uniform and less spatially autocorrelated. In litter, fungal communities were affected by vegetation and appeared to be more involved in decomposition. In the soil, chemical composition affected both microbial abundance and the rates of decomposition, whereas the effect of vegetation was small. Importantly, decomposition appeared to be concentrated in hotspots with increased activity of multiple enzymes. Overall, forest topsoil should be considered a spatially heterogeneous environment in which the mean estimates of ecosystem-level processes and microbial community composition may confound the existence of highly specific microenvironments. © FEMS 2016. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Genexpi: a toolset for identifying regulons and validating gene regulatory networks using time-course expression data.

PubMed

Modrák, Martin; Vohradský, Jiří

2018-04-13

Identifying regulons of sigma factors is a vital subtask of gene network inference. Integrating multiple sources of data is essential for correct identification of regulons and complete gene regulatory networks. Time series of expression data measured with microarrays or RNA-seq combined with static binding experiments (e.g., ChIP-seq) or literature mining may be used for inference of sigma factor regulatory networks. We introduce Genexpi: a tool to identify sigma factors by combining candidates obtained from ChIP experiments or literature mining with time-course gene expression data. While Genexpi can be used to infer other types of regulatory interactions, it was designed and validated on real biological data from bacterial regulons. In this paper, we put primary focus on CyGenexpi: a plugin integrating Genexpi with the Cytoscape software for ease of use. As a part of this effort, a plugin for handling time series data in Cytoscape called CyDataseries has been developed and made available. Genexpi is also available as a standalone command line tool and an R package. Genexpi is a useful part of gene network inference toolbox. It provides meaningful information about the composition of regulons and delivers biologically interpretable results.

RegPrecise 3.0--a resource for genome-scale exploration of transcriptional regulation in bacteria.

PubMed

Novichkov, Pavel S; Kazakov, Alexey E; Ravcheev, Dmitry A; Leyn, Semen A; Kovaleva, Galina Y; Sutormin, Roman A; Kazanov, Marat D; Riehl, William; Arkin, Adam P; Dubchak, Inna; Rodionov, Dmitry A

2013-11-01

Genome-scale prediction of gene regulation and reconstruction of transcriptional regulatory networks in prokaryotes is one of the critical tasks of modern genomics. Bacteria from different taxonomic groups, whose lifestyles and natural environments are substantially different, possess highly diverged transcriptional regulatory networks. The comparative genomics approaches are useful for in silico reconstruction of bacterial regulons and networks operated by both transcription factors (TFs) and RNA regulatory elements (riboswitches). RegPrecise (http://regprecise.lbl.gov) is a web resource for collection, visualization and analysis of transcriptional regulons reconstructed by comparative genomics. We significantly expanded a reference collection of manually curated regulons we introduced earlier. RegPrecise 3.0 provides access to inferred regulatory interactions organized by phylogenetic, structural and functional properties. Taxonomy-specific collections include 781 TF regulogs inferred in more than 160 genomes representing 14 taxonomic groups of Bacteria. TF-specific collections include regulogs for a selected subset of 40 TFs reconstructed across more than 30 taxonomic lineages. Novel collections of regulons operated by RNA regulatory elements (riboswitches) include near 400 regulogs inferred in 24 bacterial lineages. RegPrecise 3.0 provides four classifications of the reference regulons implemented as controlled vocabularies: 55 TF protein families; 43 RNA motif families; ~150 biological processes or metabolic pathways; and ~200 effectors or environmental signals. Genome-wide visualization of regulatory networks and metabolic pathways covered by the reference regulons are available for all studied genomes. A separate section of RegPrecise 3.0 contains draft regulatory networks in 640 genomes obtained by an conservative propagation of the reference regulons to closely related genomes. RegPrecise 3.0 gives access to the transcriptional regulons reconstructed in bacterial genomes. Analytical capabilities include exploration of: regulon content, structure and function; TF binding site motifs; conservation and variations in genome-wide regulatory networks across all taxonomic groups of Bacteria. RegPrecise 3.0 was selected as a core resource on transcriptional regulation of the Department of Energy Systems Biology Knowledgebase, an emerging software and data environment designed to enable researchers to collaboratively generate, test and share new hypotheses about gene and protein functions, perform large-scale analyses, and model interactions in microbes, plants, and their communities.

Spatial and temporal corroboration of a fire-scar-based fire history in a frequently burned ponderosa pine forest

Treesearch

Calvin A. Farris; Christopher H. Baisan; Donald A. Falk; Stephen R. Yool; Thomas W. Swetnam

2010-01-01

Fire scars are used widely to reconstruct historical fire regime parameters in forests around the world. Because fire scars provide incomplete records of past fire occurrence at discrete points in space, inferences must be made to reconstruct fire frequency and extent across landscapes using spatial networks of fire-scar samples. Assessing the relative accuracy of fire...

The Use of Spatial Cognition in Graph Interpretation

DTIC Science & Technology

2007-08-01

Mathematics has emphasized the importance of proactively teaching students of all ages to interpret graphs and use them to make inferences ( NCTM ... Mathematics . Reston, VA: National Council of Teachers of Mathematics . Oh, S., & Kim, M. (2004). The role of spatial working memory in visual...in learning science (Schunn et al, in press). Not coincidentally, in developing its recent national standards, the National Council of Teachers of

A Causal Inference Analysis of the Effect of Wildland Fire ...

EPA Pesticide Factsheets

Wildfire smoke is a major contributor to ambient air pollution levels. In this talk, we develop a spatio-temporal model to estimate the contribution of fire smoke to overall air pollution in different regions of the country. We combine numerical model output with observational data within a causal inference framework. Our methods account for aggregation and potential bias of the numerical model simulation, and address uncertainty in the causal estimates. We apply the proposed method to estimation of ozone and fine particulate matter from wildland fires and the impact on health burden assessment. We develop a causal inference framework to assess contributions of fire to ambient PM in the presence of spatial interference.

Substrate utilization profiles of bacterial strains in plankton from the River Warnow, a humic and eutrophic river in north Germany.

PubMed

Freese, Heike M; Eggert, Anja; Garland, Jay L; Schumann, Rhena

2010-01-01

Bacteria are very important degraders of organic substances in aquatic environments. Despite their influential role in the carbon (and many other element) cycle(s), the specific genetic identity of active bacteria is mostly unknown, although contributing phylogenetic groups had been investigated. Moreover, the degree to which phenotypic potential (i. e., utilization of environmentally relevant carbon substrates) is related to the genomic identity of bacteria or bacterial groups is unclear. The present study compared the genomic fingerprints of 27 bacterial isolates from the humic River Warnow with their ability to utilize 14 environmentally relevant substrates. Acetate was the only substrate utilized by all bacterial strains. Only 60% of the strains respired glucose, but this substrate always stimulated the highest bacterial activity (respiration and growth). Two isolates, both closely related to the same Pseudomonas sp., also had very similar substrate utilization patterns. However, similar substrate utilization profiles commonly belonged to genetically different strains (e.g., the substrate profile of Janthinobacterium lividum OW6/RT-3 and Flavobacterium sp. OW3/15-5 differed by only three substrates). Substrate consumption was sometimes totally different for genetically related isolates. Thus, the genomic profiles of bacterial strains were not congruent with their different substrate utilization profiles. Additionally, changes in pre-incubation conditions strongly influenced substrate utilization. Therefore, it is problematic to infer substrate utilization and especially microbial dissolved organic matter transformation in aquatic systems from bacterial molecular taxonomy.

Spatial and temporal distribution of the vibrionaceae in coastal waters of Hawaii, Australia, and France.

PubMed

Jones, B W; Maruyama, A; Ouverney, C C; Nishiguchi, M K

2007-08-01

Relatively little is known about large-scale spatial and temporal fluctuations in bacterioplankton, especially within the bacterial families. In general, however, a number of abiotic factors (namely, nutrients and temperature) appear to influence distribution. Community dynamics within the Vibrionaceae are of particular interest to biologists because this family contains a number of important pathogenic, commensal, and mutualist species. Of special interest to this study is the mutualism between sepiolid squids and Vibrio fischeri and Vibrio logei, where host squids seed surrounding waters daily with their bacterial partners. This study seeks to examine the spatial and temporal distribution of the Vibrionaceae with respect to V. fischeri and V. logei in Hawaii, southeastern Australia, and southern France sampling sites. In particular, we examine how the presence of sepiolid squid hosts influences community population structure within the Vibrionaceae. We found that abiotic (temperature) and biotic (host distribution) factors both influence population dynamics. In Hawaii, three sites within squid host habitat contained communities of Vibrionaceae with higher proportions of V. fischeri. In Australia, V. fischeri numbers at host collection sites were greater than other populations; however, there were no spatial or temporal patterns seen at other sample sites. In France, host presence did not appear to influence Vibrio communities, although sampled populations were significantly greater in the winter than summer sampling periods. Results of this study demonstrate the importance of understanding how both abiotic and biotic factors interact to influence bacterial community structure within the Vibrionaceae.

Temporal and spatial influences incur reconfiguration of Arctic heathland soil bacterial community structure.

PubMed

Hill, Richard; Saetnan, Eli R; Scullion, John; Gwynn-Jones, Dylan; Ostle, Nick; Edwards, Arwyn

2016-06-01

Microbial responses to Arctic climate change could radically alter the stability of major stores of soil carbon. However, the sensitivity of plot-scale experiments simulating climate change effects on Arctic heathland soils to potential confounding effects of spatial and temporal changes in soil microbial communities is unknown. Here, the variation in heathland soil bacterial communities at two survey sites in Sweden between spring and summer 2013 and at scales between 0-1 m and, 1-100 m and between sites (> 100 m) were investigated in parallel using 16S rRNA gene T-RFLP and amplicon sequencing. T-RFLP did not reveal spatial structuring of communities at scales < 100 m in any site or season. However, temporal changes were striking. Amplicon sequencing corroborated shifts from r- to K-selected taxon-dominated communities, influencing in silico predictions of functional potential. Network analyses reveal temporal keystone taxa, with a spring betaproteobacterial sub-network centred upon a Burkholderia operational taxonomic unit (OTU) and a reconfiguration to a summer sub-network centred upon an alphaproteobacterial OTU. Although spatial structuring effects may not confound comparison between plot-scale treatments, temporal change is a significant influence. Moreover, the prominence of two temporally exclusive keystone taxa suggests that the stability of Arctic heathland soil bacterial communities could be disproportionally influenced by seasonal perturbations affecting individual taxa. © 2015 Society for Applied Microbiology and John Wiley & Sons Ltd.

Inferring Human Activity in Mobile Devices by Computing Multiple Contexts.

PubMed

Chen, Ruizhi; Chu, Tianxing; Liu, Keqiang; Liu, Jingbin; Chen, Yuwei

2015-08-28

This paper introduces a framework for inferring human activities in mobile devices by computing spatial contexts, temporal contexts, spatiotemporal contexts, and user contexts. A spatial context is a significant location that is defined as a geofence, which can be a node associated with a circle, or a polygon; a temporal context contains time-related information that can be e.g., a local time tag, a time difference between geographical locations, or a timespan; a spatiotemporal context is defined as a dwelling length at a particular spatial context; and a user context includes user-related information that can be the user's mobility contexts, environmental contexts, psychological contexts or social contexts. Using the measurements of the built-in sensors and radio signals in mobile devices, we can snapshot a contextual tuple for every second including aforementioned contexts. Giving a contextual tuple, the framework evaluates the posteriori probability of each candidate activity in real-time using a Naïve Bayes classifier. A large dataset containing 710,436 contextual tuples has been recorded for one week from an experiment carried out at Texas A&M University Corpus Christi with three participants. The test results demonstrate that the multi-context solution significantly outperforms the spatial-context-only solution. A classification accuracy of 61.7% is achieved for the spatial-context-only solution, while 88.8% is achieved for the multi-context solution.

Spatial variability in airborne bacterial communities across land-use types and their relationship to the bacterial communities of potential source environments

PubMed Central

Bowers, Robert M; McLetchie, Shawna; Knight, Rob; Fierer, Noah

2011-01-01

Although bacteria are ubiquitous in the near-surface atmosphere and they can have important effects on human health, airborne bacteria have received relatively little attention and their spatial dynamics remain poorly understood. Owing to differences in meteorological conditions and the potential sources of airborne bacteria, we would expect the atmosphere over different land-use types to harbor distinct bacterial communities. To test this hypothesis, we sampled the near-surface atmosphere above three distinct land-use types (agricultural fields, suburban areas and forests) across northern Colorado, USA, sampling five sites per land-use type. Microbial abundances were stable across land-use types, with ∼105–106 bacterial cells per m3 of air, but the concentrations of biological ice nuclei, determined using a droplet freezing assay, were on average two and eight times higher in samples from agricultural areas than in the other two land-use types. Likewise, the composition of the airborne bacterial communities, assessed via bar-coded pyrosequencing, was significantly related to land-use type and these differences were likely driven by shifts in the sources of bacteria to the atmosphere across the land-uses, not local meteorological conditions. A meta-analysis of previously published data shows that atmospheric bacterial communities differ from those in potential source environments (leaf surfaces and soils), and we demonstrate that we may be able to use this information to determine the relative inputs of bacteria from these source environments to the atmosphere. This work furthers our understanding of bacterial diversity in the atmosphere, the terrestrial controls on this diversity and potential approaches for source tracking of airborne bacteria. PMID:21048802

Seasonal and spatial distribution of bacterial biomass and the percentage of viable cells in a reservoir of Alabama

USGS Publications Warehouse

Tietjen, T.E.; Wetzel, R.G.

2003-01-01

Spatial community dynamics of bacterioplankton were evaluated along the length of the former stream channel of Elledge Lake, a small reservoir in western Alabama. The reservoir was strongly stratified from April to October with up to a 10??C temperature difference across the 1 m deep metalimnion. Bacterial biomass was highest during late summer, with a general pattern of increasing abundance from the inflowing river (???10 ??g C l-1) to the dam (???20-30 ??g C l-1). Bacterial numbers also increased following a >10-fold increase in turbidity associated with a major precipitation event, although only ???10% of these cells were viable. The percentage of viable cells generally increased through the stratified period with 50-70% viable cells in late summer. Overall, an average of 38% of bacterial cells were viable, with a range from <20 to 70%. Although these values were similar to those found by others, additional patterns were identified that have not been previously observed: a marked decline in viable cells was found following turbid storm inflows and increases in the percentage of viable cells occurred during spring warming and following autumnal mixing events. Although a modest increase in abundance occurred along the gradient from inflow down-reservoir to the dam, bacterial abundance did not increase near the dam in a pattern coincident with the commonly observed increased algal biomass in the lacustrine portion of reservoir ecosystems. The increases observed in bacterial viability moving from the inflowing rivers towards the dam and later in stratified periods stress the importance of differences in environmental conditions in time and space in regulating bacterial biomass and development, as well as of shifts that would be anticipated accompanying altered hydrological regimes under climatic change.

Spatio-Temporal Interdependence of Bacteria and Phytoplankton during a Baltic Sea Spring Bloom

PubMed Central

Bunse, Carina; Bertos-Fortis, Mireia; Sassenhagen, Ingrid; Sildever, Sirje; Sjöqvist, Conny; Godhe, Anna; Gross, Susanna; Kremp, Anke; Lips, Inga; Lundholm, Nina; Rengefors, Karin; Sefbom, Josefin; Pinhassi, Jarone; Legrand, Catherine

2016-01-01

In temperate systems, phytoplankton spring blooms deplete inorganic nutrients and are major sources of organic matter for the microbial loop. In response to phytoplankton exudates and environmental factors, heterotrophic microbial communities are highly dynamic and change their abundance and composition both on spatial and temporal scales. Yet, most of our understanding about these processes comes from laboratory model organism studies, mesocosm experiments or single temporal transects. Spatial-temporal studies examining interactions of phytoplankton blooms and bacterioplankton community composition and function, though being highly informative, are scarce. In this study, pelagic microbial community dynamics (bacteria and phytoplankton) and environmental variables were monitored during a spring bloom across the Baltic Proper (two cruises between North Germany to Gulf of Finland). To test to what extent bacterioplankton community composition relates to the spring bloom, we used next generation amplicon sequencing of the 16S rRNA gene, phytoplankton diversity analysis based on microscopy counts and population genotyping of the dominating diatom Skeletonema marinoi. Several phytoplankton bloom related and environmental variables were identified to influence bacterial community composition. Members of Bacteroidetes and Alphaproteobacteria dominated the bacterial community composition but the bacterial groups showed no apparent correlation with direct bloom related variables. The less abundant bacterial phyla Actinobacteria, Planctomycetes, and Verrucomicrobia, on the other hand, were strongly associated with phytoplankton biomass, diatom:dinoflagellate ratio, and colored dissolved organic matter (cDOM). Many bacterial operational taxonomic units (OTUs) showed high niche specificities. For example, particular Bacteroidetes OTUs were associated with two distinct genetic clusters of S. marinoi. Our study revealed the complexity of interactions of bacterial taxa with inter- and intraspecific genetic variation in phytoplankton. Overall, our findings imply that biotic and abiotic factors during spring bloom influence bacterial community dynamics in a hierarchical manner. PMID:27148206

Aspect has a greater impact on alpine soil bacterial community structure than elevation.

PubMed

Wu, Jieyun; Anderson, Barbara J; Buckley, Hannah L; Lewis, Gillian; Lear, Gavin

2017-03-01

Gradients in environmental conditions, including climate factors and resource availability, occur along mountain inclines, providing a 'natural laboratory' to explore their combined impacts on microbial distributions. Conflicting spatial patterns observed across elevation gradients in soil bacterial community structure suggest that they are driven by various interacting factors at different spatial scales. Here, we investigated the relative impacts of non-resource (e.g. soil temperature, pH) and resource conditions (e.g. soil carbon and nitrogen) on the biogeography of soil bacterial communities across broad (i.e. along a 1500 m mountain elevation gradient) and fine sampling scales (i.e. along sunny and shady aspects of a mountain ridge). Our analysis of 16S rRNA gene data confirmed that when sampling across distances of < 1000 m, bacterial community composition was more closely related to the aspect of a site than its elevation. However, despite large differences in climate and resource-availability factors across elevation- and aspect-related gradients, bacterial community composition and richness were most strongly correlated with soil pH. These findings highlight the need to incorporate knowledge of multiple factors, including site aspect and soil pH for the appropriate use of elevation gradients as a proxy to explore the impacts of climate change on microbial community composition. © FEMS 2016. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Mitochondrial phylogeography of a Beringian relict: the endemic freshwater genus of blackfish Dallia (Esociformes).

PubMed

Campbell, M A; Lopéz, J A

2014-02-01

Mitochondrial genetic variability among populations of the blackfish genus Dallia (Esociformes) across Beringia was examined. Levels of divergence and patterns of geographic distribution of mitochondrial DNA lineages were characterized using phylogenetic inference, median-joining haplotype networks, Bayesian skyline plots, mismatch analysis and spatial analysis of molecular variance (SAMOVA) to infer genealogical relationships and to assess patterns of phylogeography among extant mitochondrial lineages in populations of species of Dallia. The observed variation includes extensive standing mitochondrial genetic diversity and patterns of distinct spatial segregation corresponding to historical and contemporary barriers with minimal or no mixing of mitochondrial haplotypes between geographic areas. Mitochondrial diversity is highest in the common delta formed by the Yukon and Kuskokwim Rivers where they meet the Bering Sea. Other regions sampled in this study host comparatively low levels of mitochondrial diversity. The observed levels of mitochondrial diversity and the spatial distribution of that diversity are consistent with persistence of mitochondrial lineages in multiple refugia through the last glacial maximum. © 2014 The Fisheries Society of the British Isles.

Perceptual Real-Time 2D-to-3D Conversion Using Cue Fusion.

PubMed

Leimkuhler, Thomas; Kellnhofer, Petr; Ritschel, Tobias; Myszkowski, Karol; Seidel, Hans-Peter

2018-06-01

We propose a system to infer binocular disparity from a monocular video stream in real-time. Different from classic reconstruction of physical depth in computer vision, we compute perceptually plausible disparity, that is numerically inaccurate, but results in a very similar overall depth impression with plausible overall layout, sharp edges, fine details and agreement between luminance and disparity. We use several simple monocular cues to estimate disparity maps and confidence maps of low spatial and temporal resolution in real-time. These are complemented by spatially-varying, appearance-dependent and class-specific disparity prior maps, learned from example stereo images. Scene classification selects this prior at runtime. Fusion of prior and cues is done by means of robust MAP inference on a dense spatio-temporal conditional random field with high spatial and temporal resolution. Using normal distributions allows this in constant-time, parallel per-pixel work. We compare our approach to previous 2D-to-3D conversion systems in terms of different metrics, as well as a user study and validate our notion of perceptually plausible disparity.

Testing hypotheses on distribution shifts and changes in phenology of imperfectly detectable species

USGS Publications Warehouse

Chambert, Thierry A.; Kendall, William L.; Hines, James E.; Nichols, James D.; Pedrini, Paolo; Waddle, J. Hardin; Tavecchia, Giacomo; Walls, Susan C.; Tenan, Simone

2015-01-01

With ongoing climate change, many species are expected to shift their spatial and temporal distributions. To document changes in species distribution and phenology, detection/non-detection data have proven very useful. Occupancy models provide a robust way to analyse such data, but inference is usually focused on species spatial distribution, not phenology.We present a multi-season extension of the staggered-entry occupancy model of Kendall et al. (2013, Ecology, 94, 610), which permits inference about the within-season patterns of species arrival and departure at sampling sites. The new model presented here allows investigation of species phenology and spatial distribution across years, as well as site extinction/colonization dynamics.We illustrate the model with two data sets on European migratory passerines and one data set on North American treefrogs. We show how to derive several additional phenological parameters, such as annual mean arrival and departure dates, from estimated arrival and departure probabilities.Given the extent of detection/non-detection data that are available, we believe that this modelling approach will prove very useful to further understand and predict species responses to climate change.

Bacterial predator–prey dynamics in microscale patchy landscapes

PubMed Central

Rotem, Or; Jurkevitch, Edouard; Dekker, Cees

2016-01-01

Soil is a microenvironment with a fragmented (patchy) spatial structure in which many bacterial species interact. Here, we explore the interaction between the predatory bacterium Bdellovibrio bacteriovorus and its prey Escherichia coli in microfabricated landscapes. We ask how fragmentation influences the prey dynamics at the microscale and compare two landscape geometries: a patchy landscape and a continuous landscape. By following the dynamics of prey populations with high spatial and temporal resolution for many generations, we found that the variation in predation rates was twice as large in the patchy landscape and the dynamics was correlated over shorter length scales. We also found that while the prey population in the continuous landscape was almost entirely driven to extinction, a significant part of the prey population in the fragmented landscape persisted over time. We observed significant surface-associated growth, especially in the fragmented landscape and we surmise that this sub-population is more resistant to predation. Our results thus show that microscale fragmentation can significantly influence bacterial interactions. PMID:26865299

Harnessing cell-to-cell variations to probe bacterial structure and biophysics

NASA Astrophysics Data System (ADS)

Cass, Julie A.

Advances in microscopy and biotechnology have given us novel insights into cellular biology and physics. While bacteria were long considered to be relatively unstructured, the development of fluorescence microscopy techniques, and spatially and temporally resolved high-throughput quantitative studies, have uncovered that the bacterial cell is highly organized, and its structure rigorously maintained. In this thesis I will describe our gateTool software, designed to harness cell-to-cell variations to probe bacterial structure, and discuss two exciting aspects of structure that we have employed gateTool to investigate: (i) chromosome organization and the cellular mechanisms for controlling DNA dynamics, and (ii) the study of cell wall synthesis, and how the genes in the synthesis pathway impact cellular shape. In the first project, we develop a spatial and temporal mapping of cell-cycle-dependent chromosomal organization, and use this quantitative map to discover that chromosomal loci segregate from midcell with universal dynamics. In the second project, I describe preliminary time- lapse and snapshot imaging analysis suggesting phentoypical coherence across peptidoglycan synthesis pathways.

Bacterial bioluminescence onset and quenching: a dynamical model for a quorum sensing-mediated property

PubMed Central

Side, Domenico Delle; Nassisi, Vincenzo; Pennetta, Cecilia; Alifano, Pietro; Di Salvo, Marco; Talà, Adelfia; Chechkin, Aleksei; Seno, Flavio

2017-01-01

We present an effective dynamical model for the onset of bacterial bioluminescence, one of the most studied quorum sensing-mediated traits. Our model is built upon simple equations that describe the growth of the bacterial colony, the production and accumulation of autoinducer signal molecules, their sensing within bacterial cells, and the ensuing quorum activation mechanism that triggers bioluminescent emission. The model is directly tested to quantitatively reproduce the experimental distributions of photon emission times, previously measured for bacterial colonies of Vibrio jasicida, a luminescent bacterium belonging to the Harveyi clade, growing in a highly drying environment. A distinctive and novel feature of the proposed model is bioluminescence ‘quenching’ after a given time elapsed from activation. Using an advanced fitting procedure based on the simulated annealing algorithm, we are able to infer from the experimental observations the biochemical parameters used in the model. Such parameters are in good agreement with the literature data. As a further result, we find that, at least in our experimental conditions, light emission in bioluminescent bacteria appears to originate from a subtle balance between colony growth and quorum activation due to autoinducers diffusion, with the two phenomena occurring on the same time scale. This finding is consistent with a negative feedback mechanism previously reported for Vibrio harveyi. PMID:29308273

Identification and characterization of rhizospheric microbial diversity by 16S ribosomal RNA gene sequencing.

PubMed

Naveed, Muhammad; Mubeen, Samavia; Khan, SamiUllah; Ahmed, Iftikhar; Khalid, Nauman; Suleria, Hafiz Ansar Rasul; Bano, Asghari; Mumtaz, Abdul Samad

2014-01-01

In the present study, samples of rhizosphere and root nodules were collected from different areas of Pakistan to isolate plant growth promoting rhizobacteria. Identification of bacterial isolates was made by 16S rRNA gene sequence analysis and taxonomical confirmation on EzTaxon Server. The identified bacterial strains were belonged to 5 genera i.e. Ensifer, Bacillus, Pseudomona, Leclercia and Rhizobium. Phylogenetic analysis inferred from 16S rRNA gene sequences showed the evolutionary relationship of bacterial strains with the respective genera. Based on phylogenetic analysis, some candidate novel species were also identified. The bacterial strains were also characterized for morphological, physiological, biochemical tests and glucose dehydrogenase (gdh) gene that involved in the phosphate solublization using cofactor pyrroloquinolone quinone (PQQ). Seven rhizoshperic and 3 root nodulating stains are positive for gdh gene. Furthermore, this study confirms a novel association between microbes and their hosts like field grown crops, leguminous and non-leguminous plants. It was concluded that a diverse group of bacterial population exist in the rhizosphere and root nodules that might be useful in evaluating the mechanisms behind plant microbial interactions and strains QAU-63 and QAU-68 have sequence similarity of 97 and 95% which might be declared as novel after further taxonomic characterization.

Bacterial bioluminescence onset and quenching: a dynamical model for a quorum sensing-mediated property.

PubMed

Side, Domenico Delle; Nassisi, Vincenzo; Pennetta, Cecilia; Alifano, Pietro; Di Salvo, Marco; Talà, Adelfia; Chechkin, Aleksei; Seno, Flavio; Trovato, Antonio

2017-12-01

We present an effective dynamical model for the onset of bacterial bioluminescence, one of the most studied quorum sensing-mediated traits. Our model is built upon simple equations that describe the growth of the bacterial colony, the production and accumulation of autoinducer signal molecules, their sensing within bacterial cells, and the ensuing quorum activation mechanism that triggers bioluminescent emission. The model is directly tested to quantitatively reproduce the experimental distributions of photon emission times, previously measured for bacterial colonies of Vibrio jasicida , a luminescent bacterium belonging to the Harveyi clade, growing in a highly drying environment. A distinctive and novel feature of the proposed model is bioluminescence 'quenching' after a given time elapsed from activation. Using an advanced fitting procedure based on the simulated annealing algorithm, we are able to infer from the experimental observations the biochemical parameters used in the model. Such parameters are in good agreement with the literature data. As a further result, we find that, at least in our experimental conditions, light emission in bioluminescent bacteria appears to originate from a subtle balance between colony growth and quorum activation due to autoinducers diffusion, with the two phenomena occurring on the same time scale. This finding is consistent with a negative feedback mechanism previously reported for Vibrio harveyi .

Prokaryotic diversity, composition structure, and phylogenetic analysis of microbial communities in leachate sediment ecosystems.

PubMed

Liu, Jingjing; Wu, Weixiang; Chen, Chongjun; Sun, Faqian; Chen, Yingxu

2011-09-01

In order to obtain insight into the prokaryotic diversity and community in leachate sediment, a culture-independent DNA-based molecular phylogenetic approach was performed with archaeal and bacterial 16S rRNA gene clone libraries derived from leachate sediment of an aged landfill. A total of 59 archaeal and 283 bacterial rDNA phylotypes were identified in 425 archaeal and 375 bacterial analyzed clones. All archaeal clones distributed within two archaeal phyla of the Euryarchaeota and Crenarchaeota, and well-defined methanogen lineages, especially Methanosaeta spp., are the most numerically dominant species of the archaeal community. Phylogenetic analysis of the bacterial library revealed a variety of pollutant-degrading and biotransforming microorganisms, including 18 distinct phyla. A substantial fraction of bacterial clones showed low levels of similarity with any previously documented sequences and thus might be taxonomically new. Chemical characteristics and phylogenetic inferences indicated that (1) ammonium-utilizing bacteria might form consortia to alleviate or avoid the negative influence of high ammonium concentration on other microorganisms, and (2) members of the Crenarchaeota found in the sediment might be involved in ammonium oxidation. This study is the first to report the composition of the microbial assemblages and phylogenetic characteristics of prokaryotic populations extant in leachate sediment. Additional work on microbial activity and contaminant biodegradation remains to be explored.

Identification and characterization of rhizospheric microbial diversity by 16S ribosomal RNA gene sequencing

PubMed Central

Naveed, Muhammad; Mubeen, Samavia; khan, SamiUllah; Ahmed, Iftikhar; Khalid, Nauman; Suleria, Hafiz Ansar Rasul; Bano, Asghari; Mumtaz, Abdul Samad

2014-01-01

In the present study, samples of rhizosphere and root nodules were collected from different areas of Pakistan to isolate plant growth promoting rhizobacteria. Identification of bacterial isolates was made by 16S rRNA gene sequence analysis and taxonomical confirmation on EzTaxon Server. The identified bacterial strains were belonged to 5 genera i.e. Ensifer, Bacillus, Pseudomona, Leclercia and Rhizobium. Phylogenetic analysis inferred from 16S rRNA gene sequences showed the evolutionary relationship of bacterial strains with the respective genera. Based on phylogenetic analysis, some candidate novel species were also identified. The bacterial strains were also characterized for morphological, physiological, biochemical tests and glucose dehydrogenase (gdh) gene that involved in the phosphate solublization using cofactor pyrroloquinolone quinone (PQQ). Seven rhizoshperic and 3 root nodulating stains are positive for gdh gene. Furthermore, this study confirms a novel association between microbes and their hosts like field grown crops, leguminous and non-leguminous plants. It was concluded that a diverse group of bacterial population exist in the rhizosphere and root nodules that might be useful in evaluating the mechanisms behind plant microbial interactions and strains QAU-63 and QAU-68 have sequence similarity of 97 and 95% which might be declared as novel after further taxonomic characterization. PMID:25477935

FuncPatch: a web server for the fast Bayesian inference of conserved functional patches in protein 3D structures.

PubMed

Huang, Yi-Fei; Golding, G Brian

2015-02-15

A number of statistical phylogenetic methods have been developed to infer conserved functional sites or regions in proteins. Many methods, e.g. Rate4Site, apply the standard phylogenetic models to infer site-specific substitution rates and totally ignore the spatial correlation of substitution rates in protein tertiary structures, which may reduce their power to identify conserved functional patches in protein tertiary structures when the sequences used in the analysis are highly similar. The 3D sliding window method has been proposed to infer conserved functional patches in protein tertiary structures, but the window size, which reflects the strength of the spatial correlation, must be predefined and is not inferred from data. We recently developed GP4Rate to solve these problems under the Bayesian framework. Unfortunately, GP4Rate is computationally slow. Here, we present an intuitive web server, FuncPatch, to perform a fast approximate Bayesian inference of conserved functional patches in protein tertiary structures. Both simulations and four case studies based on empirical data suggest that FuncPatch is a good approximation to GP4Rate. However, FuncPatch is orders of magnitudes faster than GP4Rate. In addition, simulations suggest that FuncPatch is potentially a useful tool complementary to Rate4Site, but the 3D sliding window method is less powerful than FuncPatch and Rate4Site. The functional patches predicted by FuncPatch in the four case studies are supported by experimental evidence, which corroborates the usefulness of FuncPatch. The software FuncPatch is freely available at the web site, http://info.mcmaster.ca/yifei/FuncPatch golding@mcmaster.ca Supplementary data are available at Bioinformatics online. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Bayesian inference in camera trapping studies for a class of spatial capture-recapture models

USGS Publications Warehouse

Royle, J. Andrew; Karanth, K. Ullas; Gopalaswamy, Arjun M.; Kumar, N. Samba

2009-01-01

We develop a class of models for inference about abundance or density using spatial capture-recapture data from studies based on camera trapping and related methods. The model is a hierarchical model composed of two components: a point process model describing the distribution of individuals in space (or their home range centers) and a model describing the observation of individuals in traps. We suppose that trap- and individual-specific capture probabilities are a function of distance between individual home range centers and trap locations. We show that the models can be regarded as generalized linear mixed models, where the individual home range centers are random effects. We adopt a Bayesian framework for inference under these models using a formulation based on data augmentation. We apply the models to camera trapping data on tigers from the Nagarahole Reserve, India, collected over 48 nights in 2006. For this study, 120 camera locations were used, but cameras were only operational at 30 locations during any given sample occasion. Movement of traps is common in many camera-trapping studies and represents an important feature of the observation model that we address explicitly in our application.

Drivers of coastal bacterioplankton community diversity and structure along a nutrient gradient in the East China Sea

NASA Astrophysics Data System (ADS)

He, Jiaying; Wang, Kai; Xiong, Jinbo; Guo, Annan; Zhang, Demin; Fei, Yuejun; Ye, Xiansen

2017-04-01

Anthropogenic nutrient discharge poses widespread threats to coastal ecosystems and has increased environmental gradients from coast to sea. Bacterioplankton play crucial roles in coastal biogeochemical cycling, and a variety of factors affect bacterial community diversity and structure. We used 16S rRNA gene pyrosequencing to investigate the spatial variation in bacterial community composition (BCC) across five sites on a coast-offshore gradient in the East China Sea. Overall, bacterial alpha-diversity did not differ across sites, except that richness and phylogenetic diversity were lower in the offshore sites, and the highest alpha-diversity was found in the most landward site, with Chl-a being the main factor. BCCs generally clustered into coastal and offshore groups. Chl-a explained 12.3% of the variation in BCCs, more than that explained by either the physicochemical (5.7%) or spatial (8.5%) variables. Nutrients (particularly nitrate and phosphate), along with phytoplankton abundance, were more important than other physicochemical factors, co-explaining 20.0% of the variation in BCCs. Additionally, a series of discriminant families (primarily affiliated with Gammaproteobacteria and Alphaproteobacteria), whose relative abundances correlated with Chl-a, DIN, and phosphate concentrations, were identified, implying their potential to indicate phytoplankton blooms and nutrient enrichment in this marine ecosystem. This study provides insight into bacterioplankton response patterns along a coast-offshore gradient, with phytoplankton abundance increasing in the offshore sites. Time-series sampling across multiple transects should be performed to determine the seasonal and spatial patterns in bacterial diversity and community structure along this gradient.

Drivers of coastal bacterioplankton community diversity and structure along a nutrient gradient in the East China Sea

NASA Astrophysics Data System (ADS)

He, Jiaying; Wang, Kai; Xiong, Jinbo; Guo, Annan; Zhang, Demin; Fei, Yuejun; Ye, Xiansen

2018-03-01

Anthropogenic nutrient discharge poses widespread threats to coastal ecosystems and has increased environmental gradients from coast to sea. Bacterioplankton play crucial roles in coastal biogeochemical cycling, and a variety of factors affect bacterial community diversity and structure. We used 16S rRNA gene pyrosequencing to investigate the spatial variation in bacterial community composition (BCC) across five sites on a coast-offshore gradient in the East China Sea. Overall, bacterial alpha-diversity did not differ across sites, except that richness and phylogenetic diversity were lower in the offshore sites, and the highest alpha-diversity was found in the most landward site, with Chl-a being the main factor. BCCs generally clustered into coastal and offshore groups. Chl-a explained 12.3% of the variation in BCCs, more than that explained by either the physicochemical (5.7%) or spatial (8.5%) variables. Nutrients (particularly nitrate and phosphate), along with phytoplankton abundance, were more important than other physicochemical factors, co-explaining 20.0% of the variation in BCCs. Additionally, a series of discriminant families (primarily affiliated with Gammaproteobacteria and Alphaproteobacteria), whose relative abundances correlated with Chl-a, DIN, and phosphate concentrations, were identified, implying their potential to indicate phytoplankton blooms and nutrient enrichment in this marine ecosystem. This study provides insight into bacterioplankton response patterns along a coast-offshore gradient, with phytoplankton abundance increasing in the offshore sites. Time-series sampling across multiple transects should be performed to determine the seasonal and spatial patterns in bacterial diversity and community structure along this gradient.

A Spatially Resolving X-ray Crystal Spectrometer for Measurement of Ion-temperature and Rotation-velocity Profiles on the AlcatorC-Mod Tokamak

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

Hill, K. W.; Bitter, M. L.; Scott, S. D.

2009-03-24

A new spatially resolving x-ray crystal spectrometer capable of measuring continuous spatial profiles of high resolution spectra (λ/dλ > 6000) of He-like and H-like Ar Kα lines with good spatial (~1 cm) and temporal (~10 ms) resolutions has been installed on the Alcator C-Mod tokamak. Two spherically bent crystals image the spectra onto four two-dimensional Pilatus II pixel detectors. Tomographic inversion enables inference of local line emissivity, ion temperature (Ti), and toroidal plasma rotation velocity (vφ) from the line Doppler widths and shifts. The data analysis techniqu

Spatial and temporal changes in the broiler chicken cecal and fecal microbiomes and correlations of bacterial taxa with cytokine gene expression

USDA-ARS?s Scientific Manuscript database

To better understand the ecology of the poultry gastrointestinal (GI) microbiome and its interactions with the host, we compared GI bacterial communities by sample type (fecal or cecal), time (1, 3, and 6 weeks post-hatch), and pen (1, 2, 3, or 4), and measured serum levels of the cytokines IL18, IL...

Tracing the HIV-1 subtype B mobility in Europe: a phylogeographic approach

PubMed Central

Paraskevis, Dimitrios; Pybus, Oliver; Magiorkinis, Gkikas; Hatzakis, Angelos; Wensing, Annemarie MJ; van de Vijver, David A; Albert, Jan; Angarano, Guiseppe; Åsjö, Birgitta; Balotta, Claudia; Boeri, Enzo; Camacho, Ricardo; Chaix, Marie-Laure; Coughlan, Suzie; Costagliola, Dominique; De Luca, Andrea; de Mendoza, Carmen; Derdelinckx, Inge; Grossman, Zehava; Hamouda, Osama; Hoepelman, IM; Horban, Andrzej; Korn, Klaus; Kücherer, Claudia; Leitner, Thomas; Loveday, Clive; MacRae, Eilidh; Maljkovic-Berry, I; Meyer, Laurence; Nielsen, Claus; Op de Coul, Eline LM; Ormaasen, Vidar; Perrin, Luc; Puchhammer-Stöckl, Elisabeth; Ruiz, Lidia; Salminen, Mika O; Schmit, Jean-Claude; Schuurman, Rob; Soriano, Vincent; Stanczak, J; Stanojevic, Maja; Struck, Daniel; Van Laethem, Kristel; Violin, M; Yerly, Sabine; Zazzi, Maurizio; Boucher, Charles A; Vandamme, Anne-Mieke

2009-01-01

Background The prevalence and the origin of HIV-1 subtype B, the most prevalent circulating clade among the long-term residents in Europe, have been studied extensively. However the spatial diffusion of the epidemic from the perspective of the virus has not previously been traced. Results In the current study we inferred the migration history of HIV-1 subtype B by way of a phylogeography of viral sequences sampled from 16 European countries and Israel. Migration events were inferred from viral phylogenies by character reconstruction using parsimony. With regard to the spatial dispersal of the HIV subtype B sequences across viral phylogenies, in most of the countries in Europe the epidemic was introduced by multiple sources and subsequently spread within local networks. Poland provides an exception where most of the infections were the result of a single point introduction. According to the significant migratory pathways, we show that there are considerable differences across Europe. Specifically, Greece, Portugal, Serbia and Spain, provide sources shedding HIV-1; Austria, Belgium and Luxembourg, on the other hand, are migratory targets, while for Denmark, Germany, Italy, Israel, Norway, the Netherlands, Sweden, Switzerland and the UK we inferred significant bidirectional migration. For Poland no significant migratory pathways were inferred. Conclusion Subtype B phylogeographies provide a new insight about the geographical distribution of viral lineages, as well as the significant pathways of virus dispersal across Europe, suggesting that intervention strategies should also address tourists, travellers and migrants. PMID:19457244

Tracing the HIV-1 subtype B mobility in Europe: a phylogeographic approach

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

Leitner, Thomas; Paraskevis, D; Pybus, O

2008-01-01

The prevalence and the origin of HIV-1 subtype B, the most prevalent circulating clade among the long-term residents in Europe, have been studied extensively. However the spatial diffusion of the epidemic from the perspective of the virus has not previously been traced. In the current study we inferred the migration history of HIV-1 subtype B by way of a phylogeography of viral sequences sampled from 16 European countries and Israel. Migration events were inferred from viral phylogenies by character reconstruction using parsimony. With regard to the spatial dispersal of the HIV subtype B sequences across viral phylogenies, in most ofmore » the countries in Europe the epidemic was introduced by multiple sources and subsequently spread within local networks. Poland provides an exception where most of the infections were the result of a single point introduction. According to the significant migratory pathways, we show that there are considerable differences across Europe. Specifically, Greece, Portugal, Serbia and Spain, provide sources shedding HIV-1; Austria, Belgium and Luxembourg, on the other hand, are migratory targets, while for Denmark, Germany, Italy, Israel, Norway, the Netherlands, Sweden, Switzerland and the UK we inferred significant bidirectional migration. For Poland no significant migratory pathways were inferred. Subtype B phylogeographies provide a new insight about the geographical distribution of viral lineages, as well as the significant pathways of virus dispersal across Europe, suggesting that intervention strategies should also address tourists, travellers and migrants.« less

Spatial vulnerability assessments by regression kriging

NASA Astrophysics Data System (ADS)

Pásztor, László; Laborczi, Annamária; Takács, Katalin; Szatmári, Gábor

2016-04-01

Two fairly different complex environmental phenomena, causing natural hazard were mapped based on a combined spatial inference approach. The behaviour is related to various environmental factors and the applied approach enables the inclusion of several, spatially exhaustive auxiliary variables that are available for mapping. Inland excess water (IEW) is an interrelated natural and human induced phenomenon causes several problems in the flat-land regions of Hungary, which cover nearly half of the country. The term 'inland excess water' refers to the occurrence of inundations outside the flood levee that originate from sources differing from flood overflow, it is surplus surface water forming due to the lack of runoff, insufficient absorption capability of soil or the upwelling of groundwater. There is a multiplicity of definitions, which indicate the complexity of processes that govern this phenomenon. Most of the definitions have a common part, namely, that inland excess water is temporary water inundation that occurs in flat-lands due to both precipitation and groundwater emerging on the surface as substantial sources. Radon gas is produced in the radioactive decay chain of uranium, which is an element that is naturally present in soils. Radon is transported mainly by diffusion and convection mechanisms through the soil depending mainly on soil physical and meteorological parameters and can enter and accumulate in the buildings. Health risk originating from indoor radon concentration attributed to natural factors is characterized by geogenic radon potential (GRP). In addition to geology and meteorology, physical soil properties play significant role in the determination of GRP. Identification of areas with high risk requires spatial modelling, that is mapping of specific natural hazards. In both cases external environmental factors determine the behaviour of the target process (occurrence/frequncy of IEW and grade of GRP respectively). Spatial auxiliary information representing IEW or GRP forming environmental factors were taken into account to support the spatial inference of the locally experienced IEW frequency and measured GRP values respectively. An efficient spatial prediction methodology was applied to construct reliable maps, namely regression kriging (RK) using spatially exhaustive auxiliary data on soil, geology, topography, land use and climate. RK divides the spatial inference into two parts. Firstly the deterministic component of the target variable is determined by a regression model. The residuals of the multiple linear regression analysis represent the spatially varying but dependent stochastic component, which are interpolated by kriging. The final map is the sum of the two component predictions. Application of RK also provides the possibility of inherent accuracy assessment. The resulting maps are characterized by global and local measures of its accuracy. Additionally the method enables interval estimation for spatial extension of the areas of predefined risk categories. All of these outputs provide useful contribution to spatial planning, action planning and decision making. Acknowledgement: Our work was partly supported by the Hungarian National Scientific Research Foundation (OTKA, Grant No. K105167).

Archaeal and eukaryotic homologs of Hfq

PubMed Central

Mura, Cameron; Randolph, Peter S.; Patterson, Jennifer; Cozen, Aaron E.

2013-01-01

Hfq and other Sm proteins are central in RNA metabolism, forming an evolutionarily conserved family that plays key roles in RNA processing in organisms ranging from archaea to bacteria to human. Sm-based cellular pathways vary in scope from eukaryotic mRNA splicing to bacterial quorum sensing, with at least one step in each of these pathways being mediated by an RNA-associated molecular assembly built upon Sm proteins. Though the first structures of Sm assemblies were from archaeal systems, the functions of Sm-like archaeal proteins (SmAPs) remain murky. Our ignorance about SmAP biology, particularly vis-à-vis the eukaryotic and bacterial Sm homologs, can be partly reduced by leveraging the homology between these lineages to make phylogenetic inferences about Sm functions in archaea. Nevertheless, whether SmAPs are more eukaryotic (RNP scaffold) or bacterial (RNA chaperone) in character remains unclear. Thus, the archaeal domain of life is a missing link, and an opportunity, in Sm-based RNA biology. PMID:23579284

Spatial reconstruction of single-cell gene expression data.

PubMed

Satija, Rahul; Farrell, Jeffrey A; Gennert, David; Schier, Alexander F; Regev, Aviv

2015-05-01

Spatial localization is a key determinant of cellular fate and behavior, but methods for spatially resolved, transcriptome-wide gene expression profiling across complex tissues are lacking. RNA staining methods assay only a small number of transcripts, whereas single-cell RNA-seq, which measures global gene expression, separates cells from their native spatial context. Here we present Seurat, a computational strategy to infer cellular localization by integrating single-cell RNA-seq data with in situ RNA patterns. We applied Seurat to spatially map 851 single cells from dissociated zebrafish (Danio rerio) embryos and generated a transcriptome-wide map of spatial patterning. We confirmed Seurat's accuracy using several experimental approaches, then used the strategy to identify a set of archetypal expression patterns and spatial markers. Seurat correctly localizes rare subpopulations, accurately mapping both spatially restricted and scattered groups. Seurat will be applicable to mapping cellular localization within complex patterned tissues in diverse systems.

3D printing of bacteria into functional complex materials.

PubMed

Schaffner, Manuel; Rühs, Patrick A; Coulter, Fergal; Kilcher, Samuel; Studart, André R

2017-12-01

Despite recent advances to control the spatial composition and dynamic functionalities of bacteria embedded in materials, bacterial localization into complex three-dimensional (3D) geometries remains a major challenge. We demonstrate a 3D printing approach to create bacteria-derived functional materials by combining the natural diverse metabolism of bacteria with the shape design freedom of additive manufacturing. To achieve this, we embedded bacteria in a biocompatible and functionalized 3D printing ink and printed two types of "living materials" capable of degrading pollutants and of producing medically relevant bacterial cellulose. With this versatile bacteria-printing platform, complex materials displaying spatially specific compositions, geometry, and properties not accessed by standard technologies can be assembled from bottom up for new biotechnological and biomedical applications.

3D printing of bacteria into functional complex materials

PubMed Central

Schaffner, Manuel; Rühs, Patrick A.; Coulter, Fergal; Kilcher, Samuel; Studart, André R.

2017-01-01

Despite recent advances to control the spatial composition and dynamic functionalities of bacteria embedded in materials, bacterial localization into complex three-dimensional (3D) geometries remains a major challenge. We demonstrate a 3D printing approach to create bacteria-derived functional materials by combining the natural diverse metabolism of bacteria with the shape design freedom of additive manufacturing. To achieve this, we embedded bacteria in a biocompatible and functionalized 3D printing ink and printed two types of “living materials” capable of degrading pollutants and of producing medically relevant bacterial cellulose. With this versatile bacteria-printing platform, complex materials displaying spatially specific compositions, geometry, and properties not accessed by standard technologies can be assembled from bottom up for new biotechnological and biomedical applications. PMID:29214219

Morphomechanics of bacterial biofilms undergoing anisotropic differential growth

NASA Astrophysics Data System (ADS)

Zhang, Cheng; Li, Bo; Huang, Xiao; Ni, Yong; Feng, Xi-Qiao

2016-10-01

Growing bacterial biofilms exhibit a number of surface morphologies, e.g., concentric wrinkles, radial ridges, and labyrinthine networks, depending on their physiological status and nutrient access. We explore the mechanisms underlying the emergence of these greatly different morphologies. Ginzburg-Landau kinetic method and Fourier spectral method are integrated to simulate the morphological evolution of bacterial biofilms. It is shown that the morphological instability of biofilms is triggered by the stresses induced by anisotropic and heterogeneous bacterial expansion, and involves the competition between membrane energy and bending energy. Local interfacial delamination further enriches the morphologies of biofilms. Phase diagrams are established to reveal how the anisotropy and spatial heterogeneity of growth modulate the surface patterns. The mechanics of three-dimensional microbial morphogenesis may also underpin self-organization in other development systems and provide a potential strategy for engineering microscopic structures from bacterial aggregates.

Analyzing the molecular mechanism of lipoprotein localization in Brucella

PubMed Central

Goolab, Shivani; Roth, Robyn L.; van Heerden, Henriette; Crampton, Michael C.

2015-01-01

Bacterial lipoproteins possess diverse structure and functionality, ranging from bacterial physiology to pathogenic processes. As such many lipoproteins, originating from Brucella are exploited as potential vaccines to countermeasure brucellosis infection in the host. These membrane proteins are translocated from the cytoplasm to the cell membrane where they are anchored peripherally by a multifaceted targeting mechanism. Although much research has focused on the identification and classification of Brucella lipoproteins and their potential use as vaccine candidates for the treatment of Brucellosis, the underlying route for the translocation of these lipoproteins to the outer surface of the Brucella (and other pathogens) outer membrane (OM) remains mostly unknown. This is partly due to the complexity of the organism and evasive tactics used to escape the host immune system, the variation in biological structure and activity of lipoproteins, combined with the complex nature of the translocation machinery. The biosynthetic pathway of Brucella lipoproteins involves a distinct secretion system aiding translocation from the cytoplasm, where they are modified by lipidation, sorted by the lipoprotein localization machinery pathway and thereafter equipped for export to the OM. Surface localized lipoproteins in Brucella may employ a lipoprotein flippase or the β-barrel assembly complex for translocation. This review provides an overview of the characterized Brucella OM proteins that form part of the OM, including a handful of other characterized bacterial lipoproteins and their mechanisms of translocation. Lipoprotein localization pathways in gram negative bacteria will be used as a model to identify gaps in Brucella lipoprotein localization and infer a potential pathway. Of particular interest are the dual topology lipoproteins identified in Escherichia coli and Haemophilus influenza. The localization and topology of these lipoproteins from other gram negative bacteria are well characterized and may be useful to infer a solution to better understand the translocation process in Brucella. PMID:26579096

Characterization of the Gut Microbiome Using 16S or Shotgun Metagenomics

PubMed Central

Jovel, Juan; Patterson, Jordan; Wang, Weiwei; Hotte, Naomi; O'Keefe, Sandra; Mitchel, Troy; Perry, Troy; Kao, Dina; Mason, Andrew L.; Madsen, Karen L.; Wong, Gane K.-S.

2016-01-01

The advent of next generation sequencing (NGS) has enabled investigations of the gut microbiome with unprecedented resolution and throughput. This has stimulated the development of sophisticated bioinformatics tools to analyze the massive amounts of data generated. Researchers therefore need a clear understanding of the key concepts required for the design, execution and interpretation of NGS experiments on microbiomes. We conducted a literature review and used our own data to determine which approaches work best. The two main approaches for analyzing the microbiome, 16S ribosomal RNA (rRNA) gene amplicons and shotgun metagenomics, are illustrated with analyses of libraries designed to highlight their strengths and weaknesses. Several methods for taxonomic classification of bacterial sequences are discussed. We present simulations to assess the number of sequences that are required to perform reliable appraisals of bacterial community structure. To the extent that fluctuations in the diversity of gut bacterial populations correlate with health and disease, we emphasize various techniques for the analysis of bacterial communities within samples (α-diversity) and between samples (β-diversity). Finally, we demonstrate techniques to infer the metabolic capabilities of a bacteria community from these 16S and shotgun data. PMID:27148170

Evolutionary Instability of Symbiotic Function in Bradyrhizobium japonicum

PubMed Central

Sachs, Joel L.; Russell, James E.; Hollowell, Amanda C.

2011-01-01

Bacterial mutualists are often acquired from the environment by eukaryotic hosts. However, both theory and empirical work suggest that this bacterial lifestyle is evolutionarily unstable. Bacterial evolution outside of the host is predicted to favor traits that promote an independent lifestyle in the environment at a cost to symbiotic function. Consistent with these predictions, environmentally-acquired bacterial mutualists often lose symbiotic function over evolutionary time. Here, we investigate the evolutionary erosion of symbiotic traits in Bradyrhizobium japonicum, a nodulating root symbiont of legumes. Building on a previous published phylogeny we infer loss events of nodulation capability in a natural population of Bradyrhizobium, potentially driven by mutation or deletion of symbiosis loci. Subsequently, we experimentally evolved representative strains from the symbiont population under host-free in vitro conditions to examine potential drivers of these loss events. Among Bradyrhizobium genotypes that evolved significant increases in fitness in vitro, two exhibited reduced symbiotic quality, but no experimentally evolved strain lost nodulation capability or evolved any fixed changes at six sequenced loci. Our results are consistent with trade-offs between symbiotic quality and fitness in a host free environment. However, the drivers of loss-of-nodulation events in natural Bradyrhizobium populations remain unknown. PMID:22073160

Minerals in soil select distinct bacterial communities in their microhabitats.

PubMed

Carson, Jennifer K; Campbell, Louise; Rooney, Deirdre; Clipson, Nicholas; Gleeson, Deirdre B

2009-03-01

We tested the hypothesis that different minerals in soil select distinct bacterial communities in their microhabitats. Mica (M), basalt (B) and rock phosphate (RP) were incubated separately in soil planted with Trifolium subterraneum, Lolium rigidum or left unplanted. After 70 days, the mineral and soil fractions were separated by sieving. Automated ribosomal intergenic spacer analysis was used to determine whether the bacterial community structure was affected by the mineral, fraction and plant treatments. Principal coordinate plots showed clustering of bacterial communities from different fraction and mineral treatments, but not from different plant treatments. Permutational multivariate anova (permanova) showed that the microhabitats of M, B and RP selected bacterial communities different from each other in unplanted and L. rigidum, and in T. subterraneum, bacterial communities from M and B differed (P<0.046). permanova also showed that each mineral fraction selected bacterial communities different from the surrounding soil fraction (P<0.05). This study shows that the structure of bacterial communities in soil is influenced by the mineral substrates in their microhabitat and that minerals in soil play a greater role in bacterial ecology than simply providing an inert matrix for bacterial growth. This study suggests that mineral heterogeneity in soil contributes to the spatial variation in bacterial communities.

Spatial clustering of high load ocular Chlamydia trachomatis infection in trachoma: a cross-sectional population-based study.

PubMed

Last, Anna; Burr, Sarah; Alexander, Neal; Harding-Esch, Emma; Roberts, Chrissy H; Nabicassa, Meno; Cassama, Eunice Teixeira da Silva; Mabey, David; Holland, Martin; Bailey, Robin

2017-07-31

Chlamydia trachomatis (Ct) is the most common cause of bacterial sexually transmitted infection and infectious cause of blindness (trachoma) worldwide. Understanding the spatial distribution of Ct infection may enable us to identify populations at risk and improve our understanding of Ct transmission. In this study, we sought to investigate the spatial distribution of Ct infection and the clinical features associated with high Ct load in trachoma-endemic communities on the Bijagós Archipelago (Guinea Bissau). We collected 1507 conjunctival samples and corresponding detailed clinical data during a cross-sectional population-based geospatially representative trachoma survey. We used droplet digital PCR to estimate Ct load on conjunctival swabs. Geostatistical tools were used to investigate clustering of ocular Ct infections. Spatial clusters (independent of age and gender) of individuals with high Ct loads were identified using local indicators of spatial association. We did not detect clustering of individuals with low load infections. These data suggest that infections with high bacterial load may be important in Ct transmission. These geospatial tools may be useful in the study of ocular Ct transmission dynamics and as part of trachoma surveillance post-treatment, to identify clusters of infection and thresholds of Ct load that may be important foci of re-emergent infection in communities. © FEMS 2017.

Spatial extreme value analysis to project extremes of large-scale indicators for severe weather

PubMed Central

Gilleland, Eric; Brown, Barbara G; Ammann, Caspar M

2013-01-01

Concurrently high values of the maximum potential wind speed of updrafts (Wmax) and 0–6 km wind shear (Shear) have been found to represent conducive environments for severe weather, which subsequently provides a way to study severe weather in future climates. Here, we employ a model for the product of these variables (WmSh) from the National Center for Atmospheric Research/United States National Center for Environmental Prediction reanalysis over North America conditioned on their having extreme energy in the spatial field in order to project the predominant spatial patterns of WmSh. The approach is based on the Heffernan and Tawn conditional extreme value model. Results suggest that this technique estimates the spatial behavior of WmSh well, which allows for exploring possible changes in the patterns over time. While the model enables a method for inferring the uncertainty in the patterns, such analysis is difficult with the currently available inference approach. A variation of the method is also explored to investigate how this type of model might be used to qualitatively understand how the spatial patterns of WmSh correspond to extreme river flow events. A case study for river flows from three rivers in northwestern Tennessee is studied, and it is found that advection of WmSh from the Gulf of Mexico prevails while elsewhere, WmSh is generally very low during such extreme events. © 2013 The Authors. Environmetrics published by JohnWiley & Sons, Ltd. PMID:24223482

Canopy-derived fuels drive patterns of in-fire energy release and understory plant mortality in a longleaf pine ( Pinus palustris ) sandhill in northwest Florida, USA

Treesearch

Joseph J. O' Brien; E. Louise Loudermilk; J. Kevin Hiers; Scott Pokswinski; Benjamin Hornsby; Andrew Hudak; Dexter Strother; Eric Rowell; Benjamin C. Bright

2016-01-01

Wildland fire radiant energy emission is one of the only measurements of combustion that can be made at high temporal and spatial resolutions. Furthermore, spatially and temporally explicit measurements are critical for making inferences about ecological fire effects. Although the correlation between fire frequency and plant biological diversity in frequently burned ...

Hierarchical modeling and inference in ecology: The analysis of data from populations, metapopulations and communities

USGS Publications Warehouse

Royle, J. Andrew; Dorazio, Robert M.

2008-01-01

A guide to data collection, modeling and inference strategies for biological survey data using Bayesian and classical statistical methods. This book describes a general and flexible framework for modeling and inference in ecological systems based on hierarchical models, with a strict focus on the use of probability models and parametric inference. Hierarchical models represent a paradigm shift in the application of statistics to ecological inference problems because they combine explicit models of ecological system structure or dynamics with models of how ecological systems are observed. The principles of hierarchical modeling are developed and applied to problems in population, metapopulation, community, and metacommunity systems. The book provides the first synthetic treatment of many recent methodological advances in ecological modeling and unifies disparate methods and procedures. The authors apply principles of hierarchical modeling to ecological problems, including * occurrence or occupancy models for estimating species distribution * abundance models based on many sampling protocols, including distance sampling * capture-recapture models with individual effects * spatial capture-recapture models based on camera trapping and related methods * population and metapopulation dynamic models * models of biodiversity, community structure and dynamics.

Identification of individual biofilm-forming bacterial cells using Raman tweezers

NASA Astrophysics Data System (ADS)

Samek, Ota; Bernatová, Silvie; Ježek, Jan; Šiler, Martin; Šerý, Mojmir; Krzyžánek, Vladislav; Hrubanová, Kamila; Zemánek, Pavel; Holá, Veronika; Růžička, Filip

2015-05-01

A method for in vitro identification of individual bacterial cells is presented. The method is based on a combination of optical tweezers for spatial trapping of individual bacterial cells and Raman microspectroscopy for acquisition of spectral "Raman fingerprints" obtained from the trapped cell. Here, Raman spectra were taken from the biofilm-forming cells without the influence of an extracellular matrix and were compared with biofilm-negative cells. Results of principal component analyses of Raman spectra enabled us to distinguish between the two strains of Staphylococcus epidermidis. Thus, we propose that Raman tweezers can become the technique of choice for a clearer understanding of the processes involved in bacterial biofilms which constitute a highly privileged way of life for bacteria, protected from the external environment.

Identification of individual biofilm-forming bacterial cells using Raman tweezers.

PubMed

Samek, Ota; Bernatová, Silvie; Ježek, Jan; Šiler, Martin; Šerý, Mojmir; Krzyžánek, Vladislav; Hrubanová, Kamila; Zemánek, Pavel; Holá, Veronika; Růžička, Filip

2015-05-01

A method for in vitro identification of individual bacterial cells is presented. The method is based on a combination of optical tweezers for spatial trapping of individual bacterial cells and Raman microspectroscopy for acquisition of spectral “Raman fingerprints” obtained from the trapped cell. Here, Raman spectra were taken from the biofilm-forming cells without the influence of an extracellular matrix and were compared with biofilm-negative cells. Results of principal component analyses of Raman spectra enabled us to distinguish between the two strains of Staphylococcus epidermidis. Thus, we propose that Raman tweezers can become the technique of choice for a clearer understanding of the processes involved in bacterial biofilms which constitute a highly privileged way of life for bacteria, protected from the external environment.

Experiment, monitoring, and gradient methods used to infer climate change effects on plant communities yield consistent patterns.

PubMed

Elmendorf, Sarah C; Henry, Gregory H R; Hollister, Robert D; Fosaa, Anna Maria; Gould, William A; Hermanutz, Luise; Hofgaard, Annika; Jónsdóttir, Ingibjörg S; Jónsdóttir, Ingibjörg I; Jorgenson, Janet C; Lévesque, Esther; Magnusson, Borgþór; Molau, Ulf; Myers-Smith, Isla H; Oberbauer, Steven F; Rixen, Christian; Tweedie, Craig E; Walker, Marilyn D; Walker, Marilyn

2015-01-13

Inference about future climate change impacts typically relies on one of three approaches: manipulative experiments, historical comparisons (broadly defined to include monitoring the response to ambient climate fluctuations using repeat sampling of plots, dendroecology, and paleoecology techniques), and space-for-time substitutions derived from sampling along environmental gradients. Potential limitations of all three approaches are recognized. Here we address the congruence among these three main approaches by comparing the degree to which tundra plant community composition changes (i) in response to in situ experimental warming, (ii) with interannual variability in summer temperature within sites, and (iii) over spatial gradients in summer temperature. We analyzed changes in plant community composition from repeat sampling (85 plant communities in 28 regions) and experimental warming studies (28 experiments in 14 regions) throughout arctic and alpine North America and Europe. Increases in the relative abundance of species with a warmer thermal niche were observed in response to warmer summer temperatures using all three methods; however, effect sizes were greater over broad-scale spatial gradients relative to either temporal variability in summer temperature within a site or summer temperature increases induced by experimental warming. The effect sizes for change over time within a site and with experimental warming were nearly identical. These results support the view that inferences based on space-for-time substitution overestimate the magnitude of responses to contemporary climate warming, because spatial gradients reflect long-term processes. In contrast, in situ experimental warming and monitoring approaches yield consistent estimates of the magnitude of response of plant communities to climate warming.

Characterizing and estimating noise in InSAR and InSAR time series with MODIS

USGS Publications Warehouse

Barnhart, William D.; Lohman, Rowena B.

2013-01-01

InSAR time series analysis is increasingly used to image subcentimeter displacement rates of the ground surface. The precision of InSAR observations is often affected by several noise sources, including spatially correlated noise from the turbulent atmosphere. Under ideal scenarios, InSAR time series techniques can substantially mitigate these effects; however, in practice the temporal distribution of InSAR acquisitions over much of the world exhibit seasonal biases, long temporal gaps, and insufficient acquisitions to confidently obtain the precisions desired for tectonic research. Here, we introduce a technique for constraining the magnitude of errors expected from atmospheric phase delays on the ground displacement rates inferred from an InSAR time series using independent observations of precipitable water vapor from MODIS. We implement a Monte Carlo error estimation technique based on multiple (100+) MODIS-based time series that sample date ranges close to the acquisitions times of the available SAR imagery. This stochastic approach allows evaluation of the significance of signals present in the final time series product, in particular their correlation with topography and seasonality. We find that topographically correlated noise in individual interferograms is not spatially stationary, even over short-spatial scales (<10 km). Overall, MODIS-inferred displacements and velocities exhibit errors of similar magnitude to the variability within an InSAR time series. We examine the MODIS-based confidence bounds in regions with a range of inferred displacement rates, and find we are capable of resolving velocities as low as 1.5 mm/yr with uncertainties increasing to ∼6 mm/yr in regions with higher topographic relief.

Effect of flow and active mixing on bacterial growth in a colon-like geometry

NASA Astrophysics Data System (ADS)

Cremer, Jonas; Segota, Igor; Arnoldini, Markus; Groisman, Alex; Hwa, Terence

The large intestine harbors bacteria from hundreds of species, with bacterial densities reaching up to 1012 cells per gram. Many different factors influence bacterial growth dynamics and thus bacterial density and microbiota composition. One dominant force is flow which can in principle lead to a washout of bacteria from the proximal colon. Active mixing by Contractions of the colonic wall together with bacterial growth might counteract such flow-forces and allow high bacterial densities to occur. As a step towards understanding bacterial growth in the presence of mixing and flow, we constructed an in-vitro setup where controlled wall-deformations of a channel emulate Contractions. We investigate growth along the channel under a steady nutrient inflow. In the limits of no or very frequent Contractions, the device behaves like a plug-flow reactor and a chemostat respectively. Depending on mixing and flow, we observe varying spatial gradients in bacterial density along the channel. Active mixing by deformations of the channel wall is shown to be crucial in maintaining a steady-state bacterial population in the presence of flow. The growth-dynamics is quantitatively captured by a simple mathematical model, with the effect of mixing described by an effective diffusion term.

Stress during pregnancy alters temporal and spatial dynamics of the maternal and offspring microbiome in a sex-specific manner

PubMed Central

Jašarević, Eldin; Howard, Christopher D.; Misic, Ana M.; Beiting, Daniel P.; Bale, Tracy L.

2017-01-01

The microbiome is a regulator of host immunity, metabolism, neurodevelopment, and behavior. During early life, bacterial communities within maternal gut and vaginal compartments can have an impact on directing these processes. Maternal stress experience during pregnancy may impact offspring development by altering the temporal and spatial dynamics of the maternal microbiome during pregnancy. To examine the hypothesis that maternal stress disrupts gut and vaginal microbial dynamics during critical prenatal and postnatal windows, we used high-resolution 16S rRNA marker gene sequencing to examine outcomes in our mouse model of early prenatal stress. Consistent with predictions, maternal fecal communities shift across pregnancy, a process that is disrupted by stress. Vaginal bacterial community structure and composition exhibit lasting disruption following stress exposure. Comparison of maternal and offspring microbiota revealed that similarities in bacterial community composition was predicted by a complex interaction between maternal body niche and offspring age and sex. Importantly, early prenatal stress influenced offspring bacterial community assembly in a temporal and sex-specific manner. Taken together, our results demonstrate that early prenatal stress may influence offspring development through converging modifications to gut microbial composition during pregnancy and transmission of dysbiotic vaginal microbiome at birth. PMID:28266645

Spatial distribution of vanadium and microbial community responses in surface soil of Panzhihua mining and smelting area, China.

PubMed

Cao, Xuelong; Diao, Muhe; Zhang, Baogang; Liu, Hui; Wang, Song; Yang, Meng

2017-09-01

Spatial distribution of vanadium in surface soils from different processing stages of vanadium-bearing titanomagnetite in Panzhihua mining and smelting area (China) as well as responses of microbial communities including bacteria and fungi to vanadium were investigated by fieldwork and laboratory incubation experiment. The vanadium contents in this region ranged from 149.3 to 4793.6 mg kg -1 , exceeding the soil background value of vanadium in China (82 mg kg -1 ) largely. High-throughput DNA sequencing results showed bacterial communities from different manufacturing locations were quite diverse, but Bacteroidetes and Proteobacteria were abundant in all samples. The contents of organic matter, available P, available S and vanadium had great influences on the structures of bacterial communities in soils. Bacterial communities converged to similar structure after long-term (240 d) cultivation with vanadium containing medium, dominating by bacteria which can tolerate or reduce toxicities of heavy metals. Fungal diversities decreased after cultivation, but Ascomycota and Ciliophora were still the most abundant phyla as in the original soil samples. Results in this study emphasize the urgency of investigating vanadium contaminations in soils and provide valuable information on how vanadium contamination influences bacterial and fungal communities. Copyright © 2017 Elsevier Ltd. All rights reserved.

BiomeNet: A Bayesian Model for Inference of Metabolic Divergence among Microbial Communities

PubMed Central

Chipman, Hugh; Gu, Hong; Bielawski, Joseph P.

2014-01-01

Metagenomics yields enormous numbers of microbial sequences that can be assigned a metabolic function. Using such data to infer community-level metabolic divergence is hindered by the lack of a suitable statistical framework. Here, we describe a novel hierarchical Bayesian model, called BiomeNet (Bayesian inference of metabolic networks), for inferring differential prevalence of metabolic subnetworks among microbial communities. To infer the structure of community-level metabolic interactions, BiomeNet applies a mixed-membership modelling framework to enzyme abundance information. The basic idea is that the mixture components of the model (metabolic reactions, subnetworks, and networks) are shared across all groups (microbiome samples), but the mixture proportions vary from group to group. Through this framework, the model can capture nested structures within the data. BiomeNet is unique in modeling each metagenome sample as a mixture of complex metabolic systems (metabosystems). The metabosystems are composed of mixtures of tightly connected metabolic subnetworks. BiomeNet differs from other unsupervised methods by allowing researchers to discriminate groups of samples through the metabolic patterns it discovers in the data, and by providing a framework for interpreting them. We describe a collapsed Gibbs sampler for inference of the mixture weights under BiomeNet, and we use simulation to validate the inference algorithm. Application of BiomeNet to human gut metagenomes revealed a metabosystem with greater prevalence among inflammatory bowel disease (IBD) patients. Based on the discriminatory subnetworks for this metabosystem, we inferred that the community is likely to be closely associated with the human gut epithelium, resistant to dietary interventions, and interfere with human uptake of an antioxidant connected to IBD. Because this metabosystem has a greater capacity to exploit host-associated glycans, we speculate that IBD-associated communities might arise from opportunist growth of bacteria that can circumvent the host's nutrient-based mechanism for bacterial partner selection. PMID:25412107

Ecological Inferences from a deep screening of the Complex Bacterial Consortia associated with the coral, Porites astreoides.

PubMed

Rodriguez-Lanetty, Mauricio; Granados-Cifuentes, Camila; Barberan, Albert; Bellantuono, Anthony J; Bastidas, Carolina

2013-08-01

The functional role of the bacterial organisms in the reef ecosystem and their contribution to the coral well-being remain largely unclear. The first step in addressing this gap of knowledge relies on in-depth characterization of the coral microbial community and its changes in diversity across coral species, space and time. In this study, we focused on the exploration of microbial community assemblages associated with an ecologically important Caribbean scleractinian coral, Porites astreoides, using Illumina high-throughput sequencing of the V5 fragment of 16S rRNA gene. We collected data from a large set of biological replicates, allowing us to detect patterns of geographical structure and resolve co-occurrence patterns using network analyses. The taxonomic analysis of the resolved diversity showed consistent and dominant presence of two OTUs affiliated with the order Oceanospirillales, which corroborates a specific pattern of bacterial association emerging for this coral species and for many other corals within the genus Porites. We argue that this specific association might indicate a symbiotic association with the adult coral partner. Furthermore, we identified a highly diverse rare bacterial 'biosphere' (725 OTUs) also living along with the dominant bacterial symbionts, but the assemblage of this biosphere is significantly structured along the geographical scale. We further discuss that some of these rare bacterial members show significant association with other members of the community reflecting the complexity of the networked consortia within the coral holobiont. © 2013 John Wiley & Sons Ltd.

Coordination of genomic structure and transcription by the main bacterial nucleoid-associated protein HU

PubMed Central

Berger, Michael; Farcas, Anca; Geertz, Marcel; Zhelyazkova, Petya; Brix, Klaudia; Travers, Andrew; Muskhelishvili, Georgi

2010-01-01

The histone-like protein HU is a highly abundant DNA architectural protein that is involved in compacting the DNA of the bacterial nucleoid and in regulating the main DNA transactions, including gene transcription. However, the coordination of the genomic structure and function by HU is poorly understood. Here, we address this question by comparing transcript patterns and spatial distributions of RNA polymerase in Escherichia coli wild-type and hupA/B mutant cells. We demonstrate that, in mutant cells, upregulated genes are preferentially clustered in a large chromosomal domain comprising the ribosomal RNA operons organized on both sides of OriC. Furthermore, we show that, in parallel to this transcription asymmetry, mutant cells are also impaired in forming the transcription foci—spatially confined aggregations of RNA polymerase molecules transcribing strong ribosomal RNA operons. Our data thus implicate HU in coordinating the global genomic structure and function by regulating the spatial distribution of RNA polymerase in the nucleoid. PMID:20010798

Localizing transcripts to single cells suggests an important role of uncultured deltaproteobacteria in the termite gut hydrogen economy.

PubMed

Rosenthal, Adam Z; Zhang, Xinning; Lucey, Kaitlyn S; Ottesen, Elizabeth A; Trivedi, Vikas; Choi, Harry M T; Pierce, Niles A; Leadbetter, Jared R

2013-10-01

Identifying microbes responsible for particular environmental functions is challenging, given that most environments contain an uncultivated microbial diversity. Here we combined approaches to identify bacteria expressing genes relevant to catabolite flow and to locate these genes within their environment, in this case the gut of a "lower," wood-feeding termite. First, environmental transcriptomics revealed that 2 of the 23 formate dehydrogenase (FDH) genes known in the system accounted for slightly more than one-half of environmental transcripts. FDH is an essential enzyme of H2 metabolism that is ultimately important for the assimilation of lignocellulose-derived energy by the insect. Second, single-cell PCR analysis revealed that two different bacterial types expressed these two transcripts. The most commonly transcribed FDH in situ is encoded by a previously unappreciated deltaproteobacterium, whereas the other FDH is spirochetal. Third, PCR analysis of fractionated gut contents demonstrated that these bacteria reside in different spatial niches; the spirochete is free-swimming, whereas the deltaproteobacterium associates with particulates. Fourth, the deltaproteobacteria expressing FDH were localized to protozoa via hybridization chain reaction-FISH, an approach for multiplexed, spatial mapping of mRNA and rRNA targets. These results underscore the importance of making direct vs. inference-based gene-species associations, and have implications in higher termites, the most successful termite lineage, in which protozoa have been lost from the gut community. Contrary to expectations, in higher termites, FDH genes related to those from the protozoan symbiont dominate, whereas most others were absent, suggesting that a successful gene variant can persist and flourish after a gut perturbation alters a major environmental niche.

Standard Deviation of Spatially-Averaged Surface Cross Section Data from the TRMM Precipitation Radar

NASA Technical Reports Server (NTRS)

Meneghini, Robert; Jones, Jeffrey A.

2010-01-01

We investigate the spatial variability of the normalized radar cross section of the surface (NRCS or Sigma(sup 0)) derived from measurements of the TRMM Precipitation Radar (PR) for the period from 1998 to 2009. The purpose of the study is to understand the way in which the sample standard deviation of the Sigma(sup 0) data changes as a function of spatial resolution, incidence angle, and surface type (land/ocean). The results have implications regarding the accuracy by which the path integrated attenuation from precipitation can be inferred by the use of surface scattering properties.

Gaussian Process Regression Model in Spatial Logistic Regression

NASA Astrophysics Data System (ADS)

Sofro, A.; Oktaviarina, A.

2018-01-01

Spatial analysis has developed very quickly in the last decade. One of the favorite approaches is based on the neighbourhood of the region. Unfortunately, there are some limitations such as difficulty in prediction. Therefore, we offer Gaussian process regression (GPR) to accommodate the issue. In this paper, we will focus on spatial modeling with GPR for binomial data with logit link function. The performance of the model will be investigated. We will discuss the inference of how to estimate the parameters and hyper-parameters and to predict as well. Furthermore, simulation studies will be explained in the last section.

Bacterial community succession during in situ uranium bioremediation: spatial similarities along controlled flow paths.

PubMed

Hwang, Chiachi; Wu, Weimin; Gentry, Terry J; Carley, Jack; Corbin, Gail A; Carroll, Sue L; Watson, David B; Jardine, Phil M; Zhou, Jizhong; Criddle, Craig S; Fields, Matthew W

2009-01-01

Bacterial community succession was investigated in a field-scale subsurface reactor formed by a series of wells that received weekly ethanol additions to re-circulating groundwater. Ethanol additions stimulated denitrification, metal reduction, sulfate reduction and U(VI) reduction to sparingly soluble U(IV). Clone libraries of SSU rRNA gene sequences from groundwater samples enabled tracking of spatial and temporal changes over a 1.5-year period. Analyses showed that the communities changed in a manner consistent with geochemical variations that occurred along temporal and spatial scales. Canonical correspondence analysis revealed that the levels of nitrate, uranium, sulfide, sulfate and ethanol were strongly correlated with particular bacterial populations. As sulfate and U(VI) levels declined, sequences representative of sulfate reducers and metal reducers were detected at high levels. Ultimately, sequences associated with sulfate-reducing populations predominated, and sulfate levels declined as U(VI) remained at low levels. When engineering controls were compared with the population variation through canonical ordination, changes could be related to dissolved oxygen control and ethanol addition. The data also indicated that the indigenous populations responded differently to stimulation for bioreduction; however, the two biostimulated communities became more similar after different transitions in an idiosyncratic manner. The strong associations between particular environmental variables and certain populations provide insight into the establishment of practical and successful remediation strategies in radionuclide-contaminated environments with respect to engineering controls and microbial ecology.

The cell shape proteins MreB and MreC control cell morphogenesis by positioning cell wall synthetic complexes.

PubMed

Divakaruni, Arun V; Baida, Cyril; White, Courtney L; Gober, James W

2007-10-01

MreB, the bacterial actin homologue, is thought to function in spatially co-ordinating cell morphogenesis in conjunction with MreC, a protein that wraps around the outside of the cell within the periplasmic space. In Caulobacter crescentus, MreC physically associates with penicillin-binding proteins (PBPs) which catalyse the insertion of intracellularly synthesized precursors into the peptidoglycan cell wall. Here we show that MreC is required for the spatial organization of components of the peptidoglycan-synthesizing holoenzyme in the periplasm and MreB directs the localization of a peptidoglycan precursor synthesis protein in the cytosol. Additionally, fluorescent vancomycin (Van-FL) labelling revealed that the bacterial cytoskeletal proteins MreB and FtsZ, as well as MreC and RodA, were required for peptidoglycan synthetic activity. MreB and FtsZ were found to be required for morphogenesis of the polar stalk. FtsZ was required for a cell cycle-regulated burst of peptidoglycan synthesis early in the cell cycle resulting in the synthesis of cross-band structures, whereas MreB was required for lengthening of the stalk. Thus, the bacterial cytoskeleton and cell shape-determining proteins such as MreC, function in concert to orchestrate the localization of cell wall synthetic complexes resulting in spatially co-ordinated and efficient peptidoglycan synthetic activity.

Agent Based Modeling of Human Gut Microbiome Interactions and Perturbations.

PubMed

Shashkova, Tatiana; Popenko, Anna; Tyakht, Alexander; Peskov, Kirill; Kosinsky, Yuri; Bogolubsky, Lev; Raigorodskii, Andrei; Ischenko, Dmitry; Alexeev, Dmitry; Govorun, Vadim

2016-01-01

Intestinal microbiota plays an important role in the human health. It is involved in the digestion and protects the host against external pathogens. Examination of the intestinal microbiome interactions is required for understanding of the community influence on host health. Studies of the microbiome can provide insight on methods of improving health, including specific clinical procedures for individual microbial community composition modification and microbiota correction by colonizing with new bacterial species or dietary changes. In this work we report an agent-based model of interactions between two bacterial species and between species and the gut. The model is based on reactions describing bacterial fermentation of polysaccharides to acetate and propionate and fermentation of acetate to butyrate. Antibiotic treatment was chosen as disturbance factor and used to investigate stability of the system. System recovery after antibiotic treatment was analyzed as dependence on quantity of feedback interactions inside the community, therapy duration and amount of antibiotics. Bacterial species are known to mutate and acquire resistance to the antibiotics. The ability to mutate was considered to be a stochastic process, under this suggestion ratio of sensitive to resistant bacteria was calculated during antibiotic therapy and recovery. The model confirms a hypothesis of feedbacks mechanisms necessity for providing functionality and stability of the system after disturbance. High fraction of bacterial community was shown to mutate during antibiotic treatment, though sensitive strains could become dominating after recovery. The recovery of sensitive strains is explained by fitness cost of the resistance. The model demonstrates not only quantitative dynamics of bacterial species, but also gives an ability to observe the emergent spatial structure and its alteration, depending on various feedback mechanisms. Visual version of the model shows that spatial structure is a key factor, which helps bacteria to survive and to adapt to changed environmental conditions.

Bacterial Community Assembly and Turnover within the Intestines of Developing Zebrafish

PubMed Central

Yan, Qingyun; van der Gast, Christopher J.; Yu, Yuhe

2012-01-01

Background The majority of animal associated microorganisms are present in digestive tract communities. These intestinal communities arise from selective pressures of the gut habitats as well as host's genotype are regarded as an extra ‘organ’ regulate functions that have not evolved wholly on the host. They are functionally essential in providing nourishment, regulating epithelial development, and influencing immunity in the vertebrate host. As vertebrates are born free of microorganisms, what is poorly understood is how intestinal bacterial communities assemble and develop in conjunction with the development of the host. Methodology/Principal Findings Set within an ecological framework, we investigated the bacterial community assembly and turnover within the intestinal habitats of developing zebrafish (from larvae to adult animals). Spatial and temporal species-richness relationships and Mantel and partial Mantel tests revealed that turnover was low and that richness and composition was best predicted by time and not intestinal volume (habitat size) or changes in food diet. We also observed that bacterial communities within the zebrafish intestines were deterministically assembled (reflected by the observed low turnover) switching to stochastic assembly in the later stages of zebrafish development. Conclusions/Significance This study is of importance as it provides a novel insight into how intestinal bacterial communities assemble in tandem with the host's development (from early to adult stages). It is our hope that by studying intestinal microbiota of this vertebrate model with such or some more refined approaches in the future could well provide ecological insights for clinical benefit. In addition, this study also adds to our still fledgling knowledge of how spatial and temporal species-richness relationships are shaped and provides further mounting evidence that bacterial community assembly and dynamics are shaped by both deterministic and stochastic considerations. PMID:22276219

Changes in the water quality and bacterial community composition of an alkaline and saline oxbow lake used for temporary reservoir of geothermal waters.

PubMed

Borsodi, Andrea K; Szirányi, Barbara; Krett, Gergely; Márialigeti, Károly; Janurik, Endre; Pekár, Ferenc

2016-09-01

Geothermal waters exploited in the southeastern region of Hungary are alkali-hydrogen-carbonate type, and beside the high amount of dissolved salt, they contain a variety of aromatic, heteroaromatic, and polyaromatic hydrocarbons. The majority of these geothermal waters used for heating are directed into surface waters following a temporary storage in reservoir lakes. The aim of this study was to gain information about the temporal and spatial changes of the water quality as well as the bacterial community composition of an alkaline and saline oxbow lake operated as reservoir of used geothermal water. On the basis of the water physical and chemical measurements as well as the denaturing gradient gel electrophoresis (DGGE) patterns of the bacterial communities, temporal changes were more pronounced than spatial differences. During the storage periods, the inflow, reservoir water, and sediment samples were characterized with different bacterial community structures in both studied years. The 16S ribosomal RNA (rRNA) gene sequences of the bacterial strains and molecular clones confirmed the differences among the studied habitats. Thermophilic bacteria were most abundant in the geothermal inflow, whereas the water of the reservoir was dominated by cyanobacteria and various anoxygenic phototrophic prokaryotes. In addition, members of several facultative anaerobic denitrifying, obligate anaerobic sulfate-reducing and syntrophic bacterial species capable of decomposition of different organic compounds including phenols were revealed from the water and sediment of the reservoir. Most of these alkaliphilic and/or halophilic species may participate in the local nitrogen and sulfur cycles and contribute to the bloom of phototrophs manifesting in a characteristic pink-reddish discoloration of the water of the reservoir.

Integrated Approach to Reconstruction of Microbial Regulatory Networks

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

Rodionov, Dmitry A; Novichkov, Pavel S

2013-11-04

This project had the goal(s) of development of integrated bioinformatics platform for genome-scale inference and visualization of transcriptional regulatory networks (TRNs) in bacterial genomes. The work was done in Sanford-Burnham Medical Research Institute (SBMRI, P.I. D.A. Rodionov) and Lawrence Berkeley National Laboratory (LBNL, co-P.I. P.S. Novichkov). The developed computational resources include: (1) RegPredict web-platform for TRN inference and regulon reconstruction in microbial genomes, and (2) RegPrecise database for collection, visualization and comparative analysis of transcriptional regulons reconstructed by comparative genomics. These analytical resources were selected as key components in the DOE Systems Biology KnowledgeBase (SBKB). The high-quality data accumulated inmore » RegPrecise will provide essential datasets of reference regulons in diverse microbes to enable automatic reconstruction of draft TRNs in newly sequenced genomes. We outline our progress toward the three aims of this grant proposal, which were: Develop integrated platform for genome-scale regulon reconstruction; Infer regulatory annotations in several groups of bacteria and building of reference collections of microbial regulons; and Develop KnowledgeBase on microbial transcriptional regulation.« less

An approach for modeling cross-immunity of two strains, with application to variants of Bartonella in terms of genetic similarity.

PubMed

Ahn, Kwang Woo; Kosoy, Michael; Chan, Kung-Sik

2014-06-01

We developed a two-strain susceptible-infected-recovered (SIR) model that provides a framework for inferring the cross-immunity between two strains of a bacterial species in the host population with discretely sampled co-infection time-series data. Moreover, the model accounts for seasonality in host reproduction. We illustrate an approach using a dataset describing co-infections by several strains of bacteria circulating within a population of cotton rats (Sigmodon hispidus). Bartonella strains were clustered into three genetically close groups, between which the divergence is correspondent to the accepted level of separate bacterial species. The proposed approach revealed no cross-immunity between genetic clusters while limited cross-immunity might exist between subgroups within the clusters. Copyright © 2014. Published by Elsevier B.V.

Causal Inference for Cross-Modal Action Selection: A Computational Study in a Decision Making Framework.

PubMed

Daemi, Mehdi; Harris, Laurence R; Crawford, J Douglas

2016-01-01

Animals try to make sense of sensory information from multiple modalities by categorizing them into perceptions of individual or multiple external objects or internal concepts. For example, the brain constructs sensory, spatial representations of the locations of visual and auditory stimuli in the visual and auditory cortices based on retinal and cochlear stimulations. Currently, it is not known how the brain compares the temporal and spatial features of these sensory representations to decide whether they originate from the same or separate sources in space. Here, we propose a computational model of how the brain might solve such a task. We reduce the visual and auditory information to time-varying, finite-dimensional signals. We introduce controlled, leaky integrators as working memory that retains the sensory information for the limited time-course of task implementation. We propose our model within an evidence-based, decision-making framework, where the alternative plan units are saliency maps of space. A spatiotemporal similarity measure, computed directly from the unimodal signals, is suggested as the criterion to infer common or separate causes. We provide simulations that (1) validate our model against behavioral, experimental results in tasks where the participants were asked to report common or separate causes for cross-modal stimuli presented with arbitrary spatial and temporal disparities. (2) Predict the behavior in novel experiments where stimuli have different combinations of spatial, temporal, and reliability features. (3) Illustrate the dynamics of the proposed internal system. These results confirm our spatiotemporal similarity measure as a viable criterion for causal inference, and our decision-making framework as a viable mechanism for target selection, which may be used by the brain in cross-modal situations. Further, we suggest that a similar approach can be extended to other cognitive problems where working memory is a limiting factor, such as target selection among higher numbers of stimuli and selections among other modality combinations.

Highly Heterogeneous Soil Bacterial Communities around Terra Nova Bay of Northern Victoria Land, Antarctica

PubMed Central

Lim, Hyoun Soo; Hong, Soon Gyu; Kim, Ji Hee; Lee, Joohan; Choi, Taejin; Ahn, Tae Seok; Kim, Ok-Sun

2015-01-01

Given the diminished role of biotic interactions in soils of continental Antarctica, abiotic factors are believed to play a dominant role in structuring of microbial communities. However, many ice-free regions remain unexplored, and it is unclear which environmental gradients are primarily responsible for the variations among bacterial communities. In this study, we investigated the soil bacterial community around Terra Nova Bay of Victoria Land by pyrosequencing and determined which environmental variables govern the bacterial community structure at the local scale. Six bacterial phyla, Actinobacteria, Proteobacteria, Acidobacteria, Chloroflexi, Cyanobacteria, and Bacteroidetes, were dominant, but their relative abundance varied greatly across locations. Bacterial community structures were affected little by spatial distance, but structured more strongly by site, which was in accordance with the soil physicochemical compositions. At both the phylum and species levels, bacterial community structure was explained primarily by pH and water content, while certain earth elements and trace metals also played important roles in shaping community variation. The higher heterogeneity of the bacterial community structure found at this site indicates how soil bacterial communities have adapted to different compositions of edaphic variables under extreme environmental conditions. Taken together, these findings greatly advance our understanding of the adaption of soil bacterial populations to this harsh environment. PMID:25799273

Bacterial Communities of Three Saline Meromictic Lakes in Central Asia

PubMed Central

Baatar, Bayanmunkh; Chiang, Pei-Wen; Rogozin, Denis Yu; Wu, Yu-Ting; Tseng, Ching-Hung; Yang, Cheng-Yu; Chiu, Hsiu-Hui; Oyuntsetseg, Bolormaa; Degermendzhy, Andrey G.; Tang, Sen-Lin

2016-01-01

Meromictic lakes located in landlocked steppes of central Asia (~2500 km inland) have unique geophysiochemical characteristics compared to other meromictic lakes. To characterize their bacteria and elucidate relationships between those bacteria and surrounding environments, water samples were collected from three saline meromictic lakes (Lakes Shira, Shunet and Oigon) in the border between Siberia and the West Mongolia, near the center of Asia. Based on in-depth tag pyrosequencing, bacterial communities were highly variable and dissimilar among lakes and between oxic and anoxic layers within individual lakes. Proteobacteria, Bacteroidetes, Cyanobacteria, Actinobacteria and Firmicutes were the most abundant phyla, whereas three genera of purple sulfur bacteria (a novel genus, Thiocapsa and Halochromatium) were predominant bacterial components in the anoxic layer of Lake Shira (~20.6% of relative abundance), Lake Shunet (~27.1%) and Lake Oigon (~9.25%), respectively. However, few known green sulfur bacteria were detected. Notably, 3.94% of all sequencing reads were classified into 19 candidate divisions, which was especially high (23.12%) in the anoxic layer of Lake Shunet. Furthermore, several hydro-parameters (temperature, pH, dissolved oxygen, H2S and salinity) were associated (P< 0.05) with variations in dominant bacterial groups. In conclusion, based on highly variable bacterial composition in water layers or lakes, we inferred that the meromictic ecosystem was characterized by high diversity and heterogenous niches. PMID:26934492

Bacterial Communities of Three Saline Meromictic Lakes in Central Asia.

PubMed

Baatar, Bayanmunkh; Chiang, Pei-Wen; Rogozin, Denis Yu; Wu, Yu-Ting; Tseng, Ching-Hung; Yang, Cheng-Yu; Chiu, Hsiu-Hui; Oyuntsetseg, Bolormaa; Degermendzhy, Andrey G; Tang, Sen-Lin

2016-01-01

Meromictic lakes located in landlocked steppes of central Asia (~2500 km inland) have unique geophysiochemical characteristics compared to other meromictic lakes. To characterize their bacteria and elucidate relationships between those bacteria and surrounding environments, water samples were collected from three saline meromictic lakes (Lakes Shira, Shunet and Oigon) in the border between Siberia and the West Mongolia, near the center of Asia. Based on in-depth tag pyrosequencing, bacterial communities were highly variable and dissimilar among lakes and between oxic and anoxic layers within individual lakes. Proteobacteria, Bacteroidetes, Cyanobacteria, Actinobacteria and Firmicutes were the most abundant phyla, whereas three genera of purple sulfur bacteria (a novel genus, Thiocapsa and Halochromatium) were predominant bacterial components in the anoxic layer of Lake Shira (~20.6% of relative abundance), Lake Shunet (~27.1%) and Lake Oigon (~9.25%), respectively. However, few known green sulfur bacteria were detected. Notably, 3.94% of all sequencing reads were classified into 19 candidate divisions, which was especially high (23.12%) in the anoxic layer of Lake Shunet. Furthermore, several hydro-parameters (temperature, pH, dissolved oxygen, H2S and salinity) were associated (P< 0.05) with variations in dominant bacterial groups. In conclusion, based on highly variable bacterial composition in water layers or lakes, we inferred that the meromictic ecosystem was characterized by high diversity and heterogenous niches.

Analysis of hyperspectral fluorescence images for poultry skin tumor inspection

NASA Astrophysics Data System (ADS)

Kong, Seong G.; Chen, Yud-Ren; Kim, Intaek; Kim, Moon S.

2004-02-01

We present a hyperspectral fluorescence imaging system with a fuzzy inference scheme for detecting skin tumors on poultry carcasses. Hyperspectral images reveal spatial and spectral information useful for finding pathological lesions or contaminants on agricultural products. Skin tumors are not obvious because the visual signature appears as a shape distortion rather than a discoloration. Fluorescence imaging allows the visualization of poultry skin tumors more easily than reflectance. The hyperspectral image samples obtained for this poultry tumor inspection contain 65 spectral bands of fluorescence in the visible region of the spectrum at wavelengths ranging from 425 to 711 nm. The large amount of hyperspectral image data is compressed by use of a discrete wavelet transform in the spatial domain. Principal-component analysis provides an effective compressed representation of the spectral signal of each pixel in the spectral domain. A small number of significant features are extracted from two major spectral peaks of relative fluorescence intensity that have been identified as meaningful spectral bands for detecting tumors. A fuzzy inference scheme that uses a small number of fuzzy rules and Gaussian membership functions successfully detects skin tumors on poultry carcasses. Spatial-filtering techniques are used to significantly reduce false positives.

Spatial assessment of land degradation through key ecosystem services: The role of globally available data.

PubMed

Cerretelli, Stefania; Poggio, Laura; Gimona, Alessandro; Yakob, Getahun; Boke, Shiferaw; Habte, Mulugeta; Coull, Malcolm; Peressotti, Alessandro; Black, Helaina

2018-07-01

Land degradation is a serious issue especially in dry and developing countries leading to ecosystem services (ESS) degradation due to soil functions' depletion. Reliably mapping land degradation spatial distribution is therefore important for policy decisions. The main objectives of this paper were to infer land degradation through ESS assessment and compare the modelling results obtained using different sets of data. We modelled important physical processes (sediment erosion and nutrient export) and the equivalent ecosystem services (sediment and nutrient retention) to infer land degradation in an area in the Ethiopian Great Rift Valley. To model soil erosion/retention capability, and nitrogen export/retention capability, two datasets were used: a 'global' dataset derived from existing global-coverage data and a hybrid dataset where global data were integrated with data from local surveys. The results showed that ESS assessments can be used to infer land degradation and identify priority areas for interventions. The comparison between the modelling results of the two different input datasets showed that caution is necessary if only global-coverage data are used at a local scale. In remote and data-poor areas, an approach that integrates global data with targeted local sampling campaigns might be a good compromise to use ecosystem services in decision-making. Copyright © 2018. Published by Elsevier B.V.

Extinction in Phylogenetics and Biogeography: From Timetrees to Patterns of Biotic Assemblage

PubMed Central

Meseguer, Andrea S.

2016-01-01

Global climate change and its impact on biodiversity levels have made extinction a relevant topic in biological research. Yet, until recently, extinction has received less attention in macroevolutionary studies than speciation; the reason is the difficulty to infer an event that actually eliminates rather than creates new taxa. For example, in biogeography, extinction has often been seen as noise, introducing homoplasy in biogeographic relationships, rather than a pattern-generating process. The molecular revolution and the possibility to integrate time into phylogenetic reconstructions have allowed studying extinction under different perspectives. Here, we review phylogenetic (temporal) and biogeographic (spatial) approaches to the inference of extinction and the challenges this process poses for reconstructing evolutionary history. Specifically, we focus on the problem of discriminating between alternative high extinction scenarios using time trees with only extant taxa, and on the confounding effect introduced by asymmetric spatial extinction – different rates of extinction across areas – in biogeographic inference. Finally, we identify the most promising avenues of research in both fields, which include the integration of additional sources of evidence such as the fossil record or environmental information in birth–death models and biogeographic reconstructions, the development of new models that tie extinction rates to phenotypic or environmental variation, or the implementation within a Bayesian framework of parametric non-stationary biogeographic models. PMID:27047538

Surface radiant flux densities inferred from LAC and GAC AVHRR data

NASA Astrophysics Data System (ADS)

Berger, F.; Klaes, D.

To infer surface radiant flux densities from current (NOAA-AVHRR, ERS-1/2 ATSR) and future meteorological (Envisat AATSR, MSG, METOP) satellite data, the complex, modular analysis scheme SESAT (Strahlungs- und Energieflüsse aus Satellitendaten) could be developed (Berger, 2001). This scheme allows the determination of cloud types, optical and microphysical cloud properties as well as surface and TOA radiant flux densities. After testing of SESAT in Central Europe and the Baltic Sea catchment (more than 400scenes U including a detailed validation with various surface measurements) it could be applied to a large number of NOAA-16 AVHRR overpasses covering the globe.For the analysis, two different spatial resolutions U local area coverage (LAC) andwere considered. Therefore, all inferred results, like global area coverage (GAC) U cloud cover, cloud properties and radiant properties, could be intercompared. Specific emphasis could be made to the surface radiant flux densities (all radiative balance compoments), where results for different regions, like Southern America, Southern Africa, Northern America, Europe, and Indonesia, will be presented. Applying SESAT, energy flux densities, like latent and sensible heat flux densities could also be determined additionally. A statistical analysis of all results including a detailed discussion for the two spatial resolutions will close this study.

A Mach-Zender digital holographic microscope with sub-micrometer resolution for imaging and tracking of marine micro-organisms

NASA Astrophysics Data System (ADS)

Kühn, Jonas; Niraula, Bimochan; Liewer, Kurt; Kent Wallace, J.; Serabyn, Eugene; Graff, Emilio; Lindensmith, Christian; Nadeau, Jay L.

2014-12-01

Digital holographic microscopy is an ideal tool for investigation of microbial motility. However, most designs do not exhibit sufficient spatial resolution for imaging bacteria. In this study we present an off-axis Mach-Zehnder design of a holographic microscope with spatial resolution of better than 800 nm and the ability to resolve bacterial samples at varying densities over a 380 μm × 380 μm × 600 μm three-dimensional field of view. Larger organisms, such as protozoa, can be resolved in detail, including cilia and flagella. The instrument design and performance are presented, including images and tracks of bacterial and protozoal mixed samples and pure cultures of six selected species. Organisms as small as 1 μm (bacterial spores) and as large as 60 μm (Paramecium bursaria) may be resolved and tracked without changes in the instrument configuration. Finally, we present a dilution series investigating the maximum cell density that can be imaged, a type of analysis that has not been presented in previous holographic microscopy studies.

Seismic Study of the Subsurface Structure and Dynamics of the Solar Interior from High Spatial Resolution Observations

NASA Technical Reports Server (NTRS)

Korzennik, Sylvain G.

1997-01-01

We have carried out the data reduction and analysis of Mt. Wilson 60' solar tower high spatial resolution observations. The reduction of the 100-day-long summer of 1990 observation campaign in terms of rotational splittings was completed leading to an excess of 600,000 splittings. The analysis of these splittings lead to a new inference of the solar internal rotation rate as a function of depth and latitude.

The human skin double-stranded DNA virome: topographical and temporal diversity, genetic enrichment, and dynamic associations with the host microbiome.

PubMed

Hannigan, Geoffrey D; Meisel, Jacquelyn S; Tyldsley, Amanda S; Zheng, Qi; Hodkinson, Brendan P; SanMiguel, Adam J; Minot, Samuel; Bushman, Frederic D; Grice, Elizabeth A

2015-10-20

Viruses make up a major component of the human microbiota but are poorly understood in the skin, our primary barrier to the external environment. Viral communities have the potential to modulate states of cutaneous health and disease. Bacteriophages are known to influence the structure and function of microbial communities through predation and genetic exchange. Human viruses are associated with skin cancers and a multitude of cutaneous manifestations. Despite these important roles, little is known regarding the human skin virome and its interactions with the host microbiome. Here we evaluated the human cutaneous double-stranded DNA virome by metagenomic sequencing of DNA from purified virus-like particles (VLPs). In parallel, we employed metagenomic sequencing of the total skin microbiome to assess covariation and infer interactions with the virome. Samples were collected from 16 subjects at eight body sites over 1 month. In addition to the microenviroment, which is known to partition the bacterial and fungal microbiota, natural skin occlusion was strongly associated with skin virome community composition. Viral contigs were enriched for genes indicative of a temperate phage replication style and also maintained genes encoding potential antibiotic resistance and virulence factors. CRISPR spacers identified in the bacterial DNA sequences provided a record of phage predation and suggest a mechanism to explain spatial partitioning of skin phage communities. Finally, we modeled the structure of bacterial and phage communities together to reveal a complex microbial environment with a Corynebacterium hub. These results reveal the previously underappreciated diversity, encoded functions, and viral-microbial dynamic unique to the human skin virome. To date, most cutaneous microbiome studies have focused on bacterial and fungal communities. Skin viral communities and their relationships with their hosts remain poorly understood despite their potential to modulate states of cutaneous health and disease. Previous studies employing whole-metagenome sequencing without purification for virus-like particles (VLPs) have provided some insight into the viral component of the skin microbiome but have not completely characterized these communities or analyzed interactions with the host microbiome. Here we present an optimized virus purification technique and corresponding analysis tools for gaining novel insights into the skin virome, including viral "dark matter," and its potential interactions with the host microbiome. The work presented here establishes a baseline of the healthy human skin virome and is a necessary foundation for future studies examining viral perturbations in skin health and disease. Copyright © 2015 Hannigan et al.

Spatiotemporal changes in bacterial community and microbial activity in a full-scale drinking water treatment plant.

PubMed

Hou, Luanfeng; Zhou, Qin; Wu, Qingping; Gu, Qihui; Sun, Ming; Zhang, Jumei

2018-06-01

To gain insight into the bacterial dynamics present in drinking water treatment (DWT) systems, the microbial community and activity in a full-scale DWT plant (DWTP) in Guangzhou, South China, were investigated using Illumina Hiseq sequencing analyses combined with cultivation-based techniques during the wet and dry seasons. Illumina sequencing analysis of 16S rRNA genes revealed a large shift in the proportion of Actinobacteria, Proteobacteria and Firmicutes during the treatment process, with the proportion of Actinobacteria decreased sharply, whereas that of Proteobacteria and Firmicutes increased and predominated in treated water. Both microbial activity and bacterial diversity during the treatment process showed obvious spatial variation, with higher levels observed during the dry season and lower levels during the wet season. Clustering analysis and principal component analysis indicated dramatic shifts in the bacterial community after chlorination, suggesting that chlorination was highly effective at influencing the bacterial community. The bacterial community structure of finished water primarily comprised Pseudomonas, Citrobacter, and Acinetobacter, and interestingly showed high similarity to biofilms on granular activated carbon. Additionally, the abundance of bacterial communities was relatively stable in finished water and did not change with the season. A large number of unique operational taxonomic units were shared during treatment steps, indicating the presence of a diverse core microbiome throughout the treatment process. Opportunistic pathogens, including Pseudomonas, Acinetobacter, Citrobacter, Mycobacterium, Salmonella, Staphylococcus, Legionella, Streptococcus and Enterococcus, were detected in water including finished water, suggesting a potential threat to drinking-water safety. We also detected bacteria isolated from each treatment step using the pure-culture method. In particular, two isolates, identified as Mycobacterium sp. and Blastococcus sp., which belong to the phylum Actinobacteria, were obtained from finished water during the dry season. Together, these results provided evidence of spatial and temporal variations in DWTPs and contributed to the beneficial manipulation of the drinking water microbiome. Copyright © 2017. Published by Elsevier B.V.

Temporal and Spatial Impact of Human Cadaver Decomposition on Soil Bacterial and Arthropod Community Structure and Function

PubMed Central

Singh, Baneshwar; Minick, Kevan J.; Strickland, Michael S.; Wickings, Kyle G.; Crippen, Tawni L.; Tarone, Aaron M.; Benbow, M. Eric; Sufrin, Ness; Tomberlin, Jeffery K.; Pechal, Jennifer L.

2018-01-01

As vertebrate carrion decomposes, there is a release of nutrient-rich fluids into the underlying soil, which can impact associated biological community structure and function. How these changes alter soil biogeochemical cycles is relatively unknown and may prove useful in the identification of carrion decomposition islands that have long lasting, focal ecological effects. This study investigated the spatial (0, 1, and 5 m) and temporal (3–732 days) dynamics of human cadaver decomposition on soil bacterial and arthropod community structure and microbial function. We observed strong evidence of a predictable response to cadaver decomposition that varies over space for soil bacterial and arthropod community structure, carbon (C) mineralization and microbial substrate utilization patterns. In the presence of a cadaver (i.e., 0 m samples), the relative abundance of Bacteroidetes and Firmicutes was greater, while the relative abundance of Acidobacteria, Chloroflexi, Gemmatimonadetes, and Verrucomicrobia was lower when compared to samples at 1 and 5 m. Micro-arthropods were more abundant (15 to 17-fold) in soils collected at 0 m compared to either 1 or 5 m, but overall, micro-arthropod community composition was unrelated to either bacterial community composition or function. Bacterial community structure and microbial function also exhibited temporal relationships, whereas arthropod community structure did not. Cumulative precipitation was more effective in predicting temporal variations in bacterial abundance and microbial activity than accumulated degree days. In the presence of the cadaver (i.e., 0 m samples), the relative abundance of Actinobacteria increased significantly with cumulative precipitation. Furthermore, soil bacterial communities and C mineralization were sensitive to the introduction of human cadavers as they diverged from baseline levels and did not recover completely in approximately 2 years. These data are valuable for understanding ecosystem function surrounding carrion decomposition islands and can be applicable to environmental bio-monitoring and forensic sciences. PMID:29354106

Temporal and Spatial Impact of Human Cadaver Decomposition on Soil Bacterial and Arthropod Community Structure and Function.

PubMed

Singh, Baneshwar; Minick, Kevan J; Strickland, Michael S; Wickings, Kyle G; Crippen, Tawni L; Tarone, Aaron M; Benbow, M Eric; Sufrin, Ness; Tomberlin, Jeffery K; Pechal, Jennifer L

2017-01-01

As vertebrate carrion decomposes, there is a release of nutrient-rich fluids into the underlying soil, which can impact associated biological community structure and function. How these changes alter soil biogeochemical cycles is relatively unknown and may prove useful in the identification of carrion decomposition islands that have long lasting, focal ecological effects. This study investigated the spatial (0, 1, and 5 m) and temporal (3-732 days) dynamics of human cadaver decomposition on soil bacterial and arthropod community structure and microbial function. We observed strong evidence of a predictable response to cadaver decomposition that varies over space for soil bacterial and arthropod community structure, carbon (C) mineralization and microbial substrate utilization patterns. In the presence of a cadaver (i.e., 0 m samples), the relative abundance of Bacteroidetes and Firmicutes was greater, while the relative abundance of Acidobacteria, Chloroflexi, Gemmatimonadetes, and Verrucomicrobia was lower when compared to samples at 1 and 5 m. Micro-arthropods were more abundant (15 to 17-fold) in soils collected at 0 m compared to either 1 or 5 m, but overall, micro-arthropod community composition was unrelated to either bacterial community composition or function. Bacterial community structure and microbial function also exhibited temporal relationships, whereas arthropod community structure did not. Cumulative precipitation was more effective in predicting temporal variations in bacterial abundance and microbial activity than accumulated degree days. In the presence of the cadaver (i.e., 0 m samples), the relative abundance of Actinobacteria increased significantly with cumulative precipitation. Furthermore, soil bacterial communities and C mineralization were sensitive to the introduction of human cadavers as they diverged from baseline levels and did not recover completely in approximately 2 years. These data are valuable for understanding ecosystem function surrounding carrion decomposition islands and can be applicable to environmental bio-monitoring and forensic sciences.

Model selection and Bayesian inference for high-resolution seabed reflection inversion.

PubMed

Dettmer, Jan; Dosso, Stan E; Holland, Charles W

2009-02-01

This paper applies Bayesian inference, including model selection and posterior parameter inference, to inversion of seabed reflection data to resolve sediment structure at a spatial scale below the pulse length of the acoustic source. A practical approach to model selection is used, employing the Bayesian information criterion to decide on the number of sediment layers needed to sufficiently fit the data while satisfying parsimony to avoid overparametrization. Posterior parameter inference is carried out using an efficient Metropolis-Hastings algorithm for high-dimensional models, and results are presented as marginal-probability depth distributions for sound velocity, density, and attenuation. The approach is applied to plane-wave reflection-coefficient inversion of single-bounce data collected on the Malta Plateau, Mediterranean Sea, which indicate complex fine structure close to the water-sediment interface. This fine structure is resolved in the geoacoustic inversion results in terms of four layers within the upper meter of sediments. The inversion results are in good agreement with parameter estimates from a gravity core taken at the experiment site.

MultiNest: Efficient and Robust Bayesian Inference

NASA Astrophysics Data System (ADS)

Feroz, F.; Hobson, M. P.; Bridges, M.

2011-09-01

We present further development and the first public release of our multimodal nested sampling algorithm, called MultiNest. This Bayesian inference tool calculates the evidence, with an associated error estimate, and produces posterior samples from distributions that may contain multiple modes and pronounced (curving) degeneracies in high dimensions. The developments presented here lead to further substantial improvements in sampling efficiency and robustness, as compared to the original algorithm presented in Feroz & Hobson (2008), which itself significantly outperformed existing MCMC techniques in a wide range of astrophysical inference problems. The accuracy and economy of the MultiNest algorithm is demonstrated by application to two toy problems and to a cosmological inference problem focusing on the extension of the vanilla LambdaCDM model to include spatial curvature and a varying equation of state for dark energy. The MultiNest software is fully parallelized using MPI and includes an interface to CosmoMC. It will also be released as part of the SuperBayeS package, for the analysis of supersymmetric theories of particle physics, at this http URL.

Bayesian estimation of the transmissivity spatial structure from pumping test data

NASA Astrophysics Data System (ADS)

Demir, Mehmet Taner; Copty, Nadim K.; Trinchero, Paolo; Sanchez-Vila, Xavier

2017-06-01

Estimating the statistical parameters (mean, variance, and integral scale) that define the spatial structure of the transmissivity or hydraulic conductivity fields is a fundamental step for the accurate prediction of subsurface flow and contaminant transport. In practice, the determination of the spatial structure is a challenge because of spatial heterogeneity and data scarcity. In this paper, we describe a novel approach that uses time drawdown data from multiple pumping tests to determine the transmissivity statistical spatial structure. The method builds on the pumping test interpretation procedure of Copty et al. (2011) (Continuous Derivation method, CD), which uses the time-drawdown data and its time derivative to estimate apparent transmissivity values as a function of radial distance from the pumping well. A Bayesian approach is then used to infer the statistical parameters of the transmissivity field by combining prior information about the parameters and the likelihood function expressed in terms of radially-dependent apparent transmissivities determined from pumping tests. A major advantage of the proposed Bayesian approach is that the likelihood function is readily determined from randomly generated multiple realizations of the transmissivity field, without the need to solve the groundwater flow equation. Applying the method to synthetically-generated pumping test data, we demonstrate that, through a relatively simple procedure, information on the spatial structure of the transmissivity may be inferred from pumping tests data. It is also shown that the prior parameter distribution has a significant influence on the estimation procedure, given the non-uniqueness of the estimation procedure. Results also indicate that the reliability of the estimated transmissivity statistical parameters increases with the number of available pumping tests.

Analysis of Co-spatial UV-Optical STIS Spectra of Seven Planetary Nebulae From HST Cycle 19 GO 12600

NASA Astrophysics Data System (ADS)

Miller, Timothy R.; Henry, Richard B. C.; Dufour, Reginald J.; Kwitter, Karen B.; Shaw, Richard A.; Balick, Bruce; Corradi, Romano

2016-01-01

We present an analysis of seven spatially resolved planetary nebulae (PNe), NGC 2440, NGC 3242, NGC 5315, NGC 5882, NGC 7662, IC 2165, and IC 3568, from observations in the Cycle 19 program GO 12600 using HST STIS. These seven observations cover the wavelength range 1150-10,270 Å with 0.2 and 0.5 arcsec wide slits, and are co-spatial to within 0.1 arcsec along a 25 arcsec length across each nebula. The wavelength and spatial coverage enabled a detailed study of physical conditions and abundances from UV and optical line emissions (compared to only optical lines) for these seven PNe. The first UV lines of interest are those of carbon. The resolved lines of C III] 1906.68 and 1908.73 yielded a direct measurement of the density within the volume occupied by doubly-ionized carbon and other similar co-spatial ions as well as contributed to an accurate measurement of the carbon abundance. Each PN spectrum was divided into smaller spatial regions or segments in order to assess inferred density variations among the regions along the entire slit. There is a clear difference in the inferred density for several regions of each PNe. Variations in electron temperature and chemical abundances were also probed and shown to be completely homogeneous within the errors. Lastly, these nebulae were modeled in detail with the photoionization code CLOUDY. This modeling constrained the central star parameters of temperature and luminosity and tested the effects different density profiles have on these parameters. We gratefully acknowledge generous support from NASA through grants related to the Cycle 19 program GO 12600, as well as from the University of Oklahoma.

Reading biological processes from nucleotide sequences

NASA Astrophysics Data System (ADS)

Murugan, Anand

Cellular processes have traditionally been investigated by techniques of imaging and biochemical analysis of the molecules involved. The recent rapid progress in our ability to manipulate and read nucleic acid sequences gives us direct access to the genetic information that directs and constrains biological processes. While sequence data is being used widely to investigate genotype-phenotype relationships and population structure, here we use sequencing to understand biophysical mechanisms. We present work on two different systems. First, in chapter 2, we characterize the stochastic genetic editing mechanism that produces diverse T-cell receptors in the human immune system. We do this by inferring statistical distributions of the underlying biochemical events that generate T-cell receptor coding sequences from the statistics of the observed sequences. This inferred model quantitatively describes the potential repertoire of T-cell receptors that can be produced by an individual, providing insight into its potential diversity and the probability of generation of any specific T-cell receptor. Then in chapter 3, we present work on understanding the functioning of regulatory DNA sequences in both prokaryotes and eukaryotes. Here we use experiments that measure the transcriptional activity of large libraries of mutagenized promoters and enhancers and infer models of the sequence-function relationship from this data. For the bacterial promoter, we infer a physically motivated 'thermodynamic' model of the interaction of DNA-binding proteins and RNA polymerase determining the transcription rate of the downstream gene. For the eukaryotic enhancers, we infer heuristic models of the sequence-function relationship and use these models to find synthetic enhancer sequences that optimize inducibility of expression. Both projects demonstrate the utility of sequence information in conjunction with sophisticated statistical inference techniques for dissecting underlying biophysical mechanisms.

Causation in risk assessment and management: models, inference, biases, and a microbial risk-benefit case study.

PubMed

Cox, L A; Ricci, P F

2005-04-01

Causal inference of exposure-response relations from data is a challenging aspect of risk assessment with important implications for public and private risk management. Such inference, which is fundamentally empirical and based on exposure (or dose)-response models, seldom arises from a single set of data; rather, it requires integrating heterogeneous information from diverse sources and disciplines including epidemiology, toxicology, and cell and molecular biology. The causal aspects we discuss focus on these three aspects: drawing sound inferences about causal relations from one or more observational studies; addressing and resolving biases that can affect a single multivariate empirical exposure-response study; and applying the results from these considerations to the microbiological risk management of human health risks and benefits of a ban on antibiotic use in animals, in the context of banning enrofloxacin or macrolides, antibiotics used against bacterial illnesses in poultry, and the effects of such bans on changing the risk of human food-borne campylobacteriosis infections. The purposes of this paper are to describe novel causal methods for assessing empirical causation and inference; exemplify how to deal with biases that routinely arise in multivariate exposure- or dose-response modeling; and provide a simplified discussion of a case study of causal inference using microbial risk analysis as an example. The case study supports the conclusion that the human health benefits from a ban are unlikely to be greater than the excess human health risks that it could create, even when accounting for uncertainty. We conclude that quantitative causal analysis of risks is a preferable to qualitative assessments because it does not involve unjustified loss of information and is sound under the inferential use of risk results by management.

Bacterial carbon utilization in vertical subsurface flow constructed wetlands.

PubMed

Tietz, Alexandra; Langergraber, Günter; Watzinger, Andrea; Haberl, Raimund; Kirschner, Alexander K T

2008-03-01

Subsurface vertical flow constructed wetlands with intermittent loading are considered as state of the art and can comply with stringent effluent requirements. It is usually assumed that microbial activity in the filter body of constructed wetlands, responsible for the removal of carbon and nitrogen, relies mainly on bacterially mediated transformations. However, little quantitative information is available on the distribution of bacterial biomass and production in the "black-box" constructed wetland. The spatial distribution of bacterial carbon utilization, based on bacterial (14)C-leucine incorporation measurements, was investigated for the filter body of planted and unplanted indoor pilot-scale constructed wetlands, as well as for a planted outdoor constructed wetland. A simple mass-balance approach was applied to explain the bacterially catalysed organic matter degradation in this system by comparing estimated bacterial carbon utilization rates with simultaneously measured carbon reduction values. The pilot-scale constructed wetlands proved to be a suitable model system for investigating microbial carbon utilization in constructed wetlands. Under an ideal operating mode, the bulk of bacterial productivity occurred within the first 10cm of the filter body. Plants seemed to have no significant influence on productivity and biomass of bacteria, as well as on wastewater total organic carbon removal.

A synthesis of the basal thermal state of the Greenland Ice Sheet

PubMed Central

MacGregor, Joseph A.; Fahnestock, Mark A.; Catania, Ginny A.; Aschwanden, Andy; Clow, Gary D.; Colgan, William T.; Gogineni, S. Prasad; Morlighem, Mathieu; Nowicki, Sophie M. J.; Paden, John D.; Price, Stephen F.; Seroussi, Hélène

2017-01-01

The basal thermal state of an ice sheet (frozen or thawed) is an important control upon its evolution, dynamics and response to external forcings. However, this state can only be observed directly within sparse boreholes or inferred conclusively from the presence of subglacial lakes. Here we synthesize spatially extensive inferences of the basal thermal state of the Greenland Ice Sheet to better constrain this state. Existing inferences include outputs from the eight thermomechanical ice-flow models included in the SeaRISE effort. New remote-sensing inferences of the basal thermal state are derived from Holocene radiostratigraphy, modern surface velocity and MODIS imagery. Both thermomechanical modeling and remote inferences generally agree that the Northeast Greenland Ice Stream and large portions of the southwestern ice-drainage systems are thawed at the bed, whereas the bed beneath the central ice divides, particularly their west-facing slopes, is frozen. Elsewhere, there is poor agreement regarding the basal thermal state. Both models and remote inferences rarely represent the borehole-observed basal thermal state accurately near NorthGRIP and DYE-3. This synthesis identifies a large portion of the Greenland Ice Sheet (about one third by area) where additional observations would most improve knowledge of its overall basal thermal state. PMID:28163988

A synthesis of the basal thermal state of the Greenland Ice Sheet.

PubMed

MacGregor, Joseph A; Fahnestock, Mark A; Catania, Ginny A; Aschwanden, Andy; Clow, Gary D; Colgan, William T; Gogineni, S Prasad; Morlighem, Mathieu; Nowicki, Sophie M J; Paden, John D; Price, Stephen F; Seroussi, Hélène

2016-08-10

The basal thermal state of an ice sheet (frozen or thawed) is an important control upon its evolution, dynamics and response to external forcings. However, this state can only be observed directly within sparse boreholes or inferred conclusively from the presence of subglacial lakes. Here we synthesize spatially extensive inferences of the basal thermal state of the Greenland Ice Sheet to better constrain this state. Existing inferences include outputs from the eight thermomechanical ice-flow models included in the SeaRISE effort. New remote-sensing inferences of the basal thermal state are derived from Holocene radiostratigraphy, modern surface velocity and MODIS imagery. Both thermomechanical modeling and remote inferences generally agree that the Northeast Greenland Ice Stream and large portions of the southwestern ice-drainage systems are thawed at the bed, whereas the bed beneath the central ice divides, particularly their west-facing slopes, is frozen. Elsewhere, there is poor agreement regarding the basal thermal state. Both models and remote inferences rarely represent the borehole-observed basal thermal state accurately near NorthGRIP and DYE-3. This synthesis identifies a large portion of the Greenland Ice Sheet (about one third by area) where additional observations would most improve knowledge of its overall basal thermal state.

A synthesis of the basal thermal state of the Greenland Ice Sheet

USGS Publications Warehouse

MacGregor, Joseph A; Fahnestock, Mark A; Catania, Ginny A; Aschwanden, Andy; Clow, Gary D.; Colgan, William T.; Gogineni, Prasad S.; Morlighem, Mathieu; Nowicki, Sophie M .J.; Paden, John D; Price, Stephen F.; Seroussi, Helene

2016-01-01

The basal thermal state of an ice sheet (frozen or thawed) is an important control upon its evolution, dynamics and response to external forcings. However, this state can only be observed directly within sparse boreholes or inferred conclusively from the presence of subglacial lakes. Here we synthesize spatially extensive inferences of the basal thermal state of the Greenland Ice Sheet to better constrain this state. Existing inferences include outputs from the eight thermomechanical ice-flow models included in the SeaRISE effort. New remote-sensing inferences of the basal thermal state are derived from Holocene radiostratigraphy, modern surface velocity and MODIS imagery. Both thermomechanical modeling and remote inferences generally agree that the Northeast Greenland Ice Stream and large portions of the southwestern ice-drainage systems are thawed at the bed, whereas the bed beneath the central ice divides, particularly their west-facing slopes, is frozen. Elsewhere, there is poor agreement regarding the basal thermal state. Both models and remote inferences rarely represent the borehole-observed basal thermal state accurately near NorthGRIP and DYE-3. This synthesis identifies a large portion of the Greenland Ice Sheet (about one third by area) where additional observations would most improve knowledge of its overall basal thermal state.

Bacterial subversion of host actin dynamics at the plasma membrane.

PubMed

Carabeo, Rey

2011-10-01

Invasion of non-phagocytic cells by a number of bacterial pathogens involves the subversion of the actin cytoskeletal remodelling machinery to produce actin-rich cell surface projections designed to engulf the bacteria. The signalling that occurs to induce these actin-rich structures has considerable overlap among a diverse group of bacteria. The molecular organization within these structures act in concert to internalize the invading pathogen. This dynamic process could be subdivided into three acts - actin recruitment, engulfment, and finally, actin disassembly/internalization. This review will present the current state of knowledge of the molecular processes involved in each stage of bacterial invasion, and provide a perspective that highlights the temporal and spatial control of actin remodelling that occurs during bacterial invasion. © 2011 Blackwell Publishing Ltd.

Sustainability of virulence in a phage-bacterial ecosystem.

PubMed

Heilmann, Silja; Sneppen, Kim; Krishna, Sandeep

2010-03-01

Virulent phages and their bacterial hosts represent an unusual sort of predator-prey system where each time a prey is eaten, hundreds of new predators are born. It is puzzling how, despite the apparent effectiveness of the phage predators, they manage to avoid driving their bacterial prey to extinction. Here we consider a phage-bacterial ecosystem on a two-dimensional (2-d) surface and show that homogeneous space in itself enhances coexistence. We analyze different behavioral mechanisms that can facilitate coexistence in a spatial environment. For example, we find that when the latent times of the phage are allowed to evolve, selection favors "mediocre killers," since voracious phage rapidly deplete local resources and go extinct. Our model system thus emphasizes the differences between short-term proliferation and long-term ecosystem sustainability.

Growth-altering microbial interactions are responsive to chemical context

PubMed Central

2017-01-01

Microbial interactions are ubiquitous in nature, and are equally as relevant to human wellbeing as the identities of the interacting microbes. However, microbial interactions are difficult to measure and characterize. Furthermore, there is growing evidence that they are not fixed, but dependent on environmental context. We present a novel workflow for inferring microbial interactions that integrates semi-automated image analysis with a colony stamping mechanism, with the overall effect of improving throughput and reproducibility of colony interaction assays. We apply our approach to infer interactions among bacterial species associated with the normal lung microbiome, and how those interactions are altered by the presence of benzo[a]pyrene, a carcinogenic compound found in cigarettes. We found that the presence of this single compound changed the interaction network, demonstrating that microbial interactions are indeed dynamic and responsive to local chemical context. PMID:28319121

Phage-Bacterial Dynamics with Spatial Structure: Self Organization around Phage Sinks Can Promote Increased Cell Densities

PubMed Central

Bull, James J.; Christensen, Kelly A.; Scott, Carly; Crandall, Cameron J.; Krone, Stephen M.

2018-01-01

Bacteria growing on surfaces appear to be profoundly more resistant to control by lytic bacteriophages than do the same cells grown in liquid. Here, we use simulation models to investigate whether spatial structure per se can account for this increased cell density in the presence of phages. A measure is derived for comparing cell densities between growth in spatially structured environments versus well mixed environments (known as mass action). Maintenance of sensitive cells requires some form of phage death; we invoke death mechanisms that are spatially fixed, as if produced by cells. Spatially structured phage death provides cells with a means of protection that can boost cell densities an order of magnitude above that attained under mass action, although the effect is sometimes in the opposite direction. Phage and bacteria self organize into separate refuges, and spatial structure operates so that the phage progeny from a single burst do not have independent fates (as they do with mass action). Phage incur a high loss when invading protected areas that have high cell densities, resulting in greater protection for the cells. By the same metric, mass action dynamics either show no sustained bacterial elevation or oscillate between states of low and high cell densities and an elevated average. The elevated cell densities observed in models with spatial structure do not approach the empirically observed increased density of cells in structured environments with phages (which can be many orders of magnitude), so the empirical phenomenon likely requires additional mechanisms than those analyzed here. PMID:29382134

Recently Deglaciated High-Altitude Soils of the Himalaya: Diverse Environments, Heterogenous Bacterial Communities and Long-Range Dust Inputs from the Upper Troposphere

PubMed Central

Stres, Blaz; Sul, Woo Jun; Murovec, Bostjan; Tiedje, James M.

2013-01-01

Background The Himalaya with its altitude and geographical position forms a barrier to atmospheric transport, which produces much aqueous-particle monsoon precipitation and makes it the largest continuous ice-covered area outside polar regions. There is a paucity of data on high-altitude microbial communities, their native environments and responses to environmental-spatial variables relative to seasonal and deglaciation events. Methodology/Principal Findings Soils were sampled along altitude transects from 5000 m to 6000 m to determine environmental, spatial and seasonal factors structuring bacterial communities characterized by 16 S rRNA gene deep sequencing. Dust traps and fresh-snow samples were used to assess dust abundance and viability, community structure and abundance of dust associated microbial communities. Significantly different habitats among the altitude-transect samples corresponded to both phylogenetically distant and closely-related communities at distances as short as 50 m showing high community spatial divergence. High within-group variability that was related to an order of magnitude higher dust deposition obscured seasonal and temporal rearrangements in microbial communities. Although dust particle and associated cell deposition rates were highly correlated, seasonal dust communities of bacteria were distinct and differed significantly from recipient soil communities. Analysis of closest relatives to dust OTUs, HYSPLIT back-calculation of airmass trajectories and small dust particle size (4–12 µm) suggested that the deposited dust and microbes came from distant continental, lacustrine and marine sources, e.g. Sahara, India, Caspian Sea and Tibetan plateau. Cyanobacteria represented less than 0.5% of microbial communities suggesting that the microbial communities benefitted from (co)deposited carbon which was reflected in the psychrotolerant nature of dust-particle associated bacteria. Conclusions/Significance The spatial, environmental and temporal complexity of the high-altitude soils of the Himalaya generates ongoing disturbance and colonization events that subject heterogeneous microniches to stochastic colonization by far away dust associated microbes and result in the observed spatially divergent bacterial communities. PMID:24086740

Ecology of coarse wood decomposition by the saprotrophic fungus Fomes fomentarius.

PubMed

Větrovský, Tomáš; Voříšková, Jana; Snajdr, Jaroslav; Gabriel, Jiří; Baldrian, Petr

2011-07-01

Saprotrophic wood-inhabiting basidiomycetes are the most important decomposers of lignin and cellulose in dead wood and as such they attracted considerable attention. The aims of this work were to quantify the activity and spatial distribution of extracellular enzymes in coarse wood colonised by the white-rot basidiomycete Fomes fomentarius and in adjacent fruitbodies of the fungus and to analyse the diversity of the fungal and bacterial community in a fungus-colonised wood and its potential effect on enzyme production by F. fomentarius. Fungus-colonised wood and fruitbodies were collected in low management intensity forests in the Czech Republic. There were significant differences in enzyme production by F. fomentarius between Betula pendula and Fagus sylvatica wood, the activity of cellulose and xylan-degrading enzymes was significantly higher in beech wood than in birch wood. Spatial analysis of a sample B. pendula log segment proved that F. fomentarius was the single fungal representative found in the log. There was a high level of spatial variability in the amount of fungal biomass detected, but no effects on enzyme activities were observed. Samples from the fruiting body showed high β-glucosidase and chitinase activities compared to wood samples. Significantly higher levels of xylanase and cellobiohydrolase were found in samples located near the fruitbody (proximal), and higher laccase and Mn-peroxidase activities were found in the distal ones. The microbial community in wood was dominated by the fungus (fungal to bacterial DNA ratio of 62-111). Bacterial abundance composition was lower in proximal than distal parts of wood by a factor of 24. These results show a significant level of spatial heterogeneity in coarse wood. One of the explanations may be the successive colonization of wood by the fungus: due to differential enzyme production, the rates of biodegradation of coarse wood are also spatially inhomogeneous.

Inference of multi-Gaussian property fields by probabilistic inversion of crosshole ground penetrating radar data using an improved dimensionality reduction

NASA Astrophysics Data System (ADS)

Hunziker, Jürg; Laloy, Eric; Linde, Niklas

2016-04-01

Deterministic inversion procedures can often explain field data, but they only deliver one final subsurface model that depends on the initial model and regularization constraints. This leads to poor insights about the uncertainties associated with the inferred model properties. In contrast, probabilistic inversions can provide an ensemble of model realizations that accurately span the range of possible models that honor the available calibration data and prior information allowing a quantitative description of model uncertainties. We reconsider the problem of inferring the dielectric permittivity (directly related to radar velocity) structure of the subsurface by inversion of first-arrival travel times from crosshole ground penetrating radar (GPR) measurements. We rely on the DREAM_(ZS) algorithm that is a state-of-the-art Markov chain Monte Carlo (MCMC) algorithm. Such algorithms need several orders of magnitude more forward simulations than deterministic algorithms and often become infeasible in high parameter dimensions. To enable high-resolution imaging with MCMC, we use a recently proposed dimensionality reduction approach that allows reproducing 2D multi-Gaussian fields with far fewer parameters than a classical grid discretization. We consider herein a dimensionality reduction from 5000 to 257 unknowns. The first 250 parameters correspond to a spectral representation of random and uncorrelated spatial fluctuations while the remaining seven geostatistical parameters are (1) the standard deviation of the data error, (2) the mean and (3) the variance of the relative electric permittivity, (4) the integral scale along the major axis of anisotropy, (5) the anisotropy angle, (6) the ratio of the integral scale along the minor axis of anisotropy to the integral scale along the major axis of anisotropy and (7) the shape parameter of the Matérn function. The latter essentially defines the type of covariance function (e.g., exponential, Whittle, Gaussian). We present an improved formulation of the dimensionality reduction, and numerically show how it reduces artifacts in the generated models and provides better posterior estimation of the subsurface geostatistical structure. We next show that the results of the method compare very favorably against previous deterministic and stochastic inversion results obtained at the South Oyster Bacterial Transport Site in Virginia, USA. The long-term goal of this work is to enable MCMC-based full waveform inversion of crosshole GPR data.

A statistical approach for inferring the 3D structure of the genome.

PubMed

Varoquaux, Nelle; Ay, Ferhat; Noble, William Stafford; Vert, Jean-Philippe

2014-06-15

Recent technological advances allow the measurement, in a single Hi-C experiment, of the frequencies of physical contacts among pairs of genomic loci at a genome-wide scale. The next challenge is to infer, from the resulting DNA-DNA contact maps, accurate 3D models of how chromosomes fold and fit into the nucleus. Many existing inference methods rely on multidimensional scaling (MDS), in which the pairwise distances of the inferred model are optimized to resemble pairwise distances derived directly from the contact counts. These approaches, however, often optimize a heuristic objective function and require strong assumptions about the biophysics of DNA to transform interaction frequencies to spatial distance, and thereby may lead to incorrect structure reconstruction. We propose a novel approach to infer a consensus 3D structure of a genome from Hi-C data. The method incorporates a statistical model of the contact counts, assuming that the counts between two loci follow a Poisson distribution whose intensity decreases with the physical distances between the loci. The method can automatically adjust the transfer function relating the spatial distance to the Poisson intensity and infer a genome structure that best explains the observed data. We compare two variants of our Poisson method, with or without optimization of the transfer function, to four different MDS-based algorithms-two metric MDS methods using different stress functions, a non-metric version of MDS and ChromSDE, a recently described, advanced MDS method-on a wide range of simulated datasets. We demonstrate that the Poisson models reconstruct better structures than all MDS-based methods, particularly at low coverage and high resolution, and we highlight the importance of optimizing the transfer function. On publicly available Hi-C data from mouse embryonic stem cells, we show that the Poisson methods lead to more reproducible structures than MDS-based methods when we use data generated using different restriction enzymes, and when we reconstruct structures at different resolutions. A Python implementation of the proposed method is available at http://cbio.ensmp.fr/pastis. © The Author 2014. Published by Oxford University Press.

Bacterial community of cushion plant Thylacospermum ceaspitosum on elevational gradient in the Himalayan cold desert.

PubMed

Řeháková, Klára; Chroňáková, Alica; Krištůfek, Václav; Kuchtová, Barbora; Čapková, Kateřina; Scharfen, Josef; Čapek, Petr; Doležal, Jiří

2015-01-01

Although bacterial assemblages are important components of soils in arid ecosystems, the knowledge about composition, life-strategies, and environmental drivers is still fragmentary, especially in remote high-elevation mountains. We compared the quality and quantity of heterotrophic bacterial assemblages between the rhizosphere of the dominant cushion-forming plant Thylacospermum ceaspitosum and its surrounding bulk soil in two mountain ranges (East Karakoram: 4850-5250 m and Little Tibet: 5350-5850 m), in communities from cold steppes to the subnival zone in Ladakh, arid Trans-Himalaya, northwest India. Bacterial communities were characterized by molecular fingerprinting in combination with culture-dependent methods. The effects of environmental factors (elevation, mountain range, and soil physico-chemical parameters) on the bacterial community composition and structure were tested by multivariate redundancy analysis and conditional inference trees. Actinobacteria dominate the cultivable part of community and represent a major bacterial lineage of cold desert soils. The most abundant genera were Streptomyces, Arthrobacter, and Paenibacillus, representing both r- and K-strategists. The soil texture is the most important factor for the community structure and the total bacteria counts. Less abundant and diverse assemblages are found in East Karakoram with coarser soils derived from leucogranite bedrock, while more diverse assemblages in Little Tibet are associated with finer soils derived from easily weathering gneisses. Cushion rhizosphere is in general less diverse than bulk soil, and contains more r-strategists. K-strategists are more associated with the extremes of the gradient, with drought at lowest elevations (4850-5000 m) and frost at the highest elevations (5750-5850 m). The present study illuminates the composition of soil bacterial assemblages in relation to the cushion plant T. ceaspitosum in a xeric environment and brings important information about heterotrophic bacteria in Himalayan soil.

A metagenome for lacustrine Cladophora (Cladophorales) reveals remarkable diversity of eukaryotic epibionts and genes relevant to materials cycling.

PubMed

Graham, Linda E; Knack, Jennifer J; Graham, Melissa E; Graham, James M; Zulkifly, Shahrizim

2015-06-01

Periphyton dominated by the cellulose-rich filamentous green alga Cladophora forms conspicuous growths along rocky marine and freshwater shorelines worldwide, providing habitat for diverse epibionts. Bacterial epibionts have been inferred to display diverse functions of biogeochemical significance: N-fixation and other redox reactions, phosphorus accumulation, and organic degradation. Here, we report taxonomic diversity of eukaryotic and prokaryotic epibionts and diversity of genes associated with materials cycling in a Cladophora metagenome sampled from Lake Mendota, Dane Co., WI, USA, during the growing season of 2012. A total of 1,060 distinct 16S, 173 18S, and 351 28S rRNA operational taxonomic units, from which >220 genera or species of bacteria (~60), protists (~80), fungi (6), and microscopic metazoa (~80), were distinguished with the use of reference databases. We inferred the presence of several algal taxa generally associated with marine systems and detected Jaoa, a freshwater periphytic ulvophyte previously thought endemic to China. We identified six distinct nifH gene sequences marking nitrogen fixation, >25 bacterial and eukaryotic cellulases relevant to sedimentary C-cycling and technological applications, and genes encoding enzymes in aerobic and anaerobic pathways for vitamin B12 biosynthesis. These results emphasize the importance of Cladophora in providing habitat for microscopic metazoa, fungi, protists, and bacteria that are often inconspicuous, yet play important roles in ecosystem biogeochemistry. © 2015 Phycological Society of America.

Bird Boxes Build Content Area Knowledge

ERIC Educational Resources Information Center

Cianca, Sherri Ann

2013-01-01

This article describes a preservice teacher training in line with meeting the Common Core State Standards for Mathematics (CCSSM) using geometric reasoning, spatial sense, measurement, representation, communication, and problem solving. The author infers that when preservice teachers lack pedagogical content knowledge they cannot successfully…

Proteogenomic analyses indicate bacterial methylotrophy and archaeal heterotrophy are prevalent below the grass root zone

DOE PAGES

Butterfield, Cristina N.; Li, Zhou; Andeer, Peter F.; ...

2016-11-08

Annually, half of all plant-derived carbon is added to soil where it is microbially respired to CO 2. However, understanding of the microbiology of this process is limited because most culture-independent methods cannot link metabolic processes to the organisms present, and this link to causative agents is necessary to predict the results of perturbations on the system. We collected soil samples at two sub-root depths (10–20 cm and 30–40 cm) before and after a rainfall-driven nutrient perturbation event in a Northern California grassland that experiences a Mediterranean climate. From ten samples, we reconstructed 198 metagenome-assembled genomes that represent all major phylotypes. Wemore » also quantified 6,835 proteins and 175 metabolites and showed that after the rain event the concentrations of many sugars and amino acids approach zero at the base of the soil profile. Unexpectedly, the genomes of novel members of the Gemmatimonadetes and Candidate Phylum Rokubacteria phyla encode pathways for methylotrophy. We infer that these abundant organisms contribute substantially to carbon turnover in the soil, given that methylotrophy proteins were among the most abundant proteins in the proteome. Previously undescribed Bathyarchaeota and Thermoplasmatales archaea are abundant in deeper soil horizons and are inferred to contribute appreciably to aromatic amino acid degradation. Many of the other bacteria appear to breakdown other components of plant biomass, as evidenced by the prevalence of various sugar and amino acid transporters and corresponding hydrolyzing machinery in the proteome. Overall, our work provides organism-resolved insight into the spatial distribution of bacteria and archaea whose activities combine to degrade plant-derived organics, limiting the transport of methanol, amino acids and sugars into underlying weathered rock. Finally, the new insights into the soil carbon cycle during an intense period of carbon turnover, including biogeochemical roles to previously little known soil microbes, were made possible via the combination of metagenomics, proteomics, and metabolomics.« less

Proteogenomic analyses indicate bacterial methylotrophy and archaeal heterotrophy are prevalent below the grass root zone

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

Butterfield, Cristina N.; Li, Zhou; Andeer, Peter F.

Annually, half of all plant-derived carbon is added to soil where it is microbially respired to CO 2. However, understanding of the microbiology of this process is limited because most culture-independent methods cannot link metabolic processes to the organisms present, and this link to causative agents is necessary to predict the results of perturbations on the system. We collected soil samples at two sub-root depths (10–20 cm and 30–40 cm) before and after a rainfall-driven nutrient perturbation event in a Northern California grassland that experiences a Mediterranean climate. From ten samples, we reconstructed 198 metagenome-assembled genomes that represent all major phylotypes. Wemore » also quantified 6,835 proteins and 175 metabolites and showed that after the rain event the concentrations of many sugars and amino acids approach zero at the base of the soil profile. Unexpectedly, the genomes of novel members of the Gemmatimonadetes and Candidate Phylum Rokubacteria phyla encode pathways for methylotrophy. We infer that these abundant organisms contribute substantially to carbon turnover in the soil, given that methylotrophy proteins were among the most abundant proteins in the proteome. Previously undescribed Bathyarchaeota and Thermoplasmatales archaea are abundant in deeper soil horizons and are inferred to contribute appreciably to aromatic amino acid degradation. Many of the other bacteria appear to breakdown other components of plant biomass, as evidenced by the prevalence of various sugar and amino acid transporters and corresponding hydrolyzing machinery in the proteome. Overall, our work provides organism-resolved insight into the spatial distribution of bacteria and archaea whose activities combine to degrade plant-derived organics, limiting the transport of methanol, amino acids and sugars into underlying weathered rock. Finally, the new insights into the soil carbon cycle during an intense period of carbon turnover, including biogeochemical roles to previously little known soil microbes, were made possible via the combination of metagenomics, proteomics, and metabolomics.« less

Proteogenomic analyses indicate bacterial methylotrophy and archaeal heterotrophy are prevalent below the grass root zone

PubMed Central

Butterfield, Cristina N.; Li, Zhou; Andeer, Peter F.; Spaulding, Susan; Thomas, Brian C.; Singh, Andrea; Hettich, Robert L.; Suttle, Kenwyn B.; Probst, Alexander J.; Tringe, Susannah G.; Northen, Trent; Pan, Chongle

2016-01-01

Annually, half of all plant-derived carbon is added to soil where it is microbially respired to CO2. However, understanding of the microbiology of this process is limited because most culture-independent methods cannot link metabolic processes to the organisms present, and this link to causative agents is necessary to predict the results of perturbations on the system. We collected soil samples at two sub-root depths (10–20 cm and 30–40 cm) before and after a rainfall-driven nutrient perturbation event in a Northern California grassland that experiences a Mediterranean climate. From ten samples, we reconstructed 198 metagenome-assembled genomes that represent all major phylotypes. We also quantified 6,835 proteins and 175 metabolites and showed that after the rain event the concentrations of many sugars and amino acids approach zero at the base of the soil profile. Unexpectedly, the genomes of novel members of the Gemmatimonadetes and Candidate Phylum Rokubacteria phyla encode pathways for methylotrophy. We infer that these abundant organisms contribute substantially to carbon turnover in the soil, given that methylotrophy proteins were among the most abundant proteins in the proteome. Previously undescribed Bathyarchaeota and Thermoplasmatales archaea are abundant in deeper soil horizons and are inferred to contribute appreciably to aromatic amino acid degradation. Many of the other bacteria appear to breakdown other components of plant biomass, as evidenced by the prevalence of various sugar and amino acid transporters and corresponding hydrolyzing machinery in the proteome. Overall, our work provides organism-resolved insight into the spatial distribution of bacteria and archaea whose activities combine to degrade plant-derived organics, limiting the transport of methanol, amino acids and sugars into underlying weathered rock. The new insights into the soil carbon cycle during an intense period of carbon turnover, including biogeochemical roles to previously little known soil microbes, were made possible via the combination of metagenomics, proteomics, and metabolomics. PMID:27843720

DEVELOPMENT OF AN AGAR LIFT-DNA/DNA HYBRIDIZATION TECHNIQUE FOR USE IN VISUALIZATION OF THE SPATIAL DISTRIBUTION OF EUBACTERIA ON SOIL SURFACES. (R825415)

EPA Science Inventory

Abstract

While microbial growth is well-understood in pure culture systems, less is known about growth in intact soil systems. The objective of this work was to develop a technique to allow visualization of the two-dimensional spatial distribution of bacterial growth o...

Flow and active mixing have a strong impact on bacterial growth dynamics in the proximal large intestine

NASA Astrophysics Data System (ADS)

Cremer, Jonas; Segota, Igor; Yang, Chih-Yu; Arnoldini, Markus; Groisman, Alex; Hwa, Terence

2016-11-01

More than half of fecal dry weight is bacterial mass with bacterial densities reaching up to 1012 cells per gram. Mostly, these bacteria grow in the proximal large intestine where lateral flow along the intestine is strong: flow can in principal lead to a washout of bacteria from the proximal large intestine. Active mixing by contractions of the intestinal wall together with bacterial growth might counteract such a washout and allow high bacterial densities to occur. As a step towards understanding bacterial growth in the presence of mixing and flow, we constructed an in-vitro setup where controlled wall-deformations of a channel emulate contractions. We investigate growth along the channel under a steady nutrient inflow. Depending on mixing and flow, we observe varying spatial gradients in bacterial density along the channel. Active mixing by deformations of the channel wall is shown to be crucial in maintaining a steady-state bacterial population in the presence of flow. The growth-dynamics is quantitatively captured by a simple mathematical model, with the effect of mixing described by an effective diffusion term. Based on this model, we discuss bacterial growth dynamics in the human large intestine using flow- and mixing-behavior having been observed for humans.

Integrating Space with Place in Health Research: A Multilevel Spatial Investigation Using Child Mortality in 1880 Newark, New Jersey

PubMed Central

Xu, Hongwei; Logan, John R.; Short, Susan E.

2014-01-01

Research on neighborhoods and health increasingly acknowledges the need to conceptualize, measure, and model spatial features of social and physical environments. In ignoring underlying spatial dynamics, we run the risk of biased statistical inference and misleading results. In this paper, we propose an integrated multilevel-spatial approach for Poisson models of discrete responses. In an empirical example of child mortality in 1880 Newark, New Jersey, we compare this multilevel-spatial approach with the more typical aspatial multilevel approach. Results indicate that spatially-defined egocentric neighborhoods, or distance-based measures, outperform administrative areal units, such as census units. In addition, although results did not vary by specific definitions of egocentric neighborhoods, they were sensitive to geographic scale and modeling strategy. Overall, our findings confirm that adopting a spatial-multilevel approach enhances our ability to disentangle the effect of space from that of place, and point to the need for more careful spatial thinking in population research on neighborhoods and health. PMID:24763980

Can you escape the beat? Modelling spatiotemporal biodegradation dynamics during periodic disturbances

NASA Astrophysics Data System (ADS)

König, Sara; Worrich, Anja; Wick, Lukas Y.; Miltner, Anja; Kästner, Matthias; Thullner, Martin; Centler, Florian; Banitz, Thomas; Frank, Karin

2016-04-01

Biodegradation of organic compounds in soil is an important microbial ecosystem service. Soil ecosystems are constantly exposed to disturbances of different spatial configurations and frequencies, challenging their ability to recover the biodegradation function. Thus, the response to these disturbances is crucial for the soil systems' biodegradation performance. The influence of spatial aspects of the disturbance regimes on long-term biodegradation dynamics under periodic disturbances has not been examined, yet. We applied a numerical simulation model considering bacterial growth, degradation, and dispersal to analyze the spatiotemporal biodegradation dynamics under disturbances occuring with different frequencies and with different spatial configurations. We found biodegradation performance decreasing in response to periodic disturbances but on average approaching a new quasi steady state. This mean performance of the disturbed systems increases with both, the interval length between disturbance events and the fragmentation of the spatial disturbance patterns. A detailed spatiotemporal analysis of degradation activity reveals that under highly fragmented disturbance patterns, biodegradation still takes place in the entire disturbed area. For moderately fragmented disturbance patterns, parts of the disturbed area become completely inactive. However, areas with high degradation activity emerge at the interface between disturbed and undisturbed areas, allowing the systems to maintain a relatively high degradation performance. Further decreasing the disturbance patterns' fragmentation, fewer interfaces between disturbed and undisturbed area and, thus, fewer active habitats occur, which reduces biodegradation performances. In additional simulations, we found that bacterial dispersal networks, as for example provided by fungal hyphae, usually increase the areas of high degradation activity and, thus, the biodegradation performance in presence of periodic disturbances. However, for some specific regimes with highly fragmented disturbance patterns, dispersal networks can in turn decrease the biodegradation performance. Our results show that spatial aspects of the periodic disturbance regime influence the biodegradation dynamics, indicating the relevance of spatial processes for functional stability. The level of connectivity between disturbed and undisturbed areas is crucial for the local and global dynamics of the ecosystem service biodegradation. Networks enhancing bacterial dispersal may often, but not always, increase the functional stability.

Spatial Distribution of Lactococcus lactis Colonies Modulates the Production of Major Metabolites during the Ripening of a Model Cheese.

PubMed

Le Boucher, Clémentine; Gagnaire, Valérie; Briard-Bion, Valérie; Jardin, Julien; Maillard, Marie-Bernadette; Dervilly-Pinel, Gaud; Le Bizec, Bruno; Lortal, Sylvie; Jeanson, Sophie; Thierry, Anne

2016-01-01

In cheese, lactic acid bacteria are immobilized at the coagulation step and grow as colonies. The spatial distribution of bacterial colonies is characterized by the size and number of colonies for a given bacterial population within cheese. Our objective was to demonstrate that different spatial distributions, which lead to differences in the exchange surface between the colonies and the cheese matrix, can influence the ripening process. The strategy was to generate cheeses with the same growth and acidification of a Lactococcus lactis strain with two different spatial distributions, big and small colonies, to monitor the production of the major ripening metabolites, including sugars, organic acids, peptides, free amino acids, and volatile metabolites, over 1 month of ripening. The monitored metabolites were qualitatively the same for both cheeses, but many of them were more abundant in the small-colony cheeses than in the big-colony cheeses over 1 month of ripening. Therefore, the results obtained showed that two different spatial distributions of L. lactis modulated the ripening time course by generating moderate but significant differences in the rates of production or consumption for many of the metabolites commonly monitored throughout ripening. The present work further explores the immobilization of bacteria as colonies within cheese and highlights the consequences of this immobilization on cheese ripening. Copyright © 2015, American Society for Microbiology. All Rights Reserved.

Black hole mass measurement using molecular gas kinematics: what ALMA can do

NASA Astrophysics Data System (ADS)

Yoon, Ilsang

2017-04-01

We study the limits of the spatial and velocity resolution of radio interferometry to infer the mass of supermassive black holes (SMBHs) in galactic centres using the kinematics of circum-nuclear molecular gas, by considering the shapes of the galaxy surface brightness profile, signal-to-noise ratios (S/Ns) of the position-velocity diagram (PVD) and systematic errors due to the spatial and velocity structure of the molecular gas. We argue that for fixed galaxy stellar mass and SMBH mass, the spatial and velocity scales that need to be resolved increase and decrease, respectively, with decreasing Sérsic index of the galaxy surface brightness profile. We validate our arguments using simulated PVDs for varying beam size and velocity channel width. Furthermore, we consider the systematic effects on the inference of the SMBH mass by simulating PVDs including the spatial and velocity structure of the molecular gas, which demonstrates that their impacts are not significant for a PVD with good S/N unless the spatial and velocity scale associated with the systematic effects are comparable to or larger than the angular resolution and velocity channel width of the PVD from pure circular motion. Also, we caution that a bias in a galaxy surface brightness profile owing to the poor resolution of a galaxy photometric image can largely bias the SMBH mass by an order of magnitude. This study shows the promise and the limits of ALMA observations for measuring SMBH mass using molecular gas kinematics and provides a useful technical justification for an ALMA proposal with the science goal of measuring SMBH mass.

Analysis of Co-spatial UV-Optical STIS Spectra of Six Planetary Nebulae From HST Cycle 19 GO 12600

NASA Astrophysics Data System (ADS)

Reid Miller, Timothy; Henry, Richard B. C.; Dufour, Reginald J.; Kwitter, Karen; Shaw, Richard A.; Balick, Bruce; Corradi, Romano

2015-08-01

We present an analysis of six spatially resolved planetary nebulae (PNe), NGC 3242, NGC 5315, NGC5882, NGC 7662, IC 2165, and IC 3568, from observations in the Cycle 19 program GO 12600 using HSTSTIS. These six observations cover the wavelength range 1150-10,270 Å with 0.2 and 0.5 arcsec wideslits, and are co-spatial to 0.1 arcsec along a 25 arcsec length across each nebula. The wavelength andspatial coverage enabled this detailed study of physical conditions and abundances from UV and opticalline emissions (compared to only optical lines) for these six PNe. The first UV lines of interest are thoseof carbon. The resolved lines of C III] 1906.68 and 1908.73 yielded a direct measurement of the densitywithin the volume occupied by doubly-ionized carbon and other similar co-spatial ions as well ascontributed to an accurate measurement of the carbon abundance. Each PN spectrum was divided intosmaller spatial regions in order to assess inferred density variations among the regions along the entireslit. There is a clear difference in the inferred density for several regions of each PNe. Variations inelectron temperature and chemical abundances were also probed and shown to be nearly completelyhomogeneous within the errors. Lastly, these nebulae were modeled in detail with the photoionizationcode CLOUDY. This modeling tested different density profiles in order to reproduce the observed densityvariations and temperature fluctuations, and constrain central star parameters. We gratefullyacknowledge generous support from NASA through grants related to the Cycle 19 program GO 12600, aswell as from the University of Oklahoma.

Systems, methods, and software for determining spatially variable distributions of the dielectric properties of a heterogeneous material

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

Farrington, Stephen P.

Systems, methods, and software for measuring the spatially variable relative dielectric permittivity of materials along a linear or otherwise configured sensor element, and more specifically the spatial variability of soil moisture in one dimension as inferred from the dielectric profile of the soil matrix surrounding a linear sensor element. Various methods provided herein combine advances in the processing of time domain reflectometry data with innovations in physical sensing apparatuses. These advancements enable high temporal (and thus spatial) resolution of electrical reflectance continuously along an insulated waveguide that is permanently emplaced in contact with adjacent soils. The spatially resolved reflectance ismore » directly related to impedance changes along the waveguide that are dominated by electrical permittivity contrast due to variations in soil moisture. Various methods described herein are thus able to monitor soil moisture in profile with high spatial resolution.« less

Forest fire spatial pattern analysis in Galicia (NW Spain).

PubMed

Fuentes-Santos, I; Marey-Pérez, M F; González-Manteiga, W

2013-10-15

Knowledge of fire behaviour is of key importance in forest management. In the present study, we analysed the spatial structure of forest fire with spatial point pattern analysis and inference techniques recently developed in the Spatstat package of R. Wildfires have been the primary threat to Galician forests in recent years. The district of Fonsagrada-Ancares is one of the most seriously affected by fire in the region and, therefore, the central focus of the study. Our main goal was to determine the spatial distribution of ignition points to model and predict fire occurrence. These data are of great value in establishing enhanced fire prevention and fire fighting plans. We found that the spatial distribution of wildfires is not random and that fire occurrence may depend on ownership conflicts. We also found positive interaction between small and large fires and spatial independence between wildfires in consecutive years. Copyright © 2013 Elsevier Ltd. All rights reserved.

Computational pathology: Exploring the spatial dimension of tumor ecology.

PubMed

Nawaz, Sidra; Yuan, Yinyin

2016-09-28

Tumors are evolving ecosystems where cancer subclones and the microenvironment interact. This is analogous to interaction dynamics between species in their natural habitats, which is a prime area of study in ecology. Spatial statistics are frequently used in ecological studies to infer complex relations including predator-prey, resource dependency and co-evolution. Recently, the emerging field of computational pathology has enabled high-throughput spatial analysis by using image processing to identify different cell types and their locations within histological tumor samples. We discuss how these data may be analyzed with spatial statistics used in ecology to reveal patterns and advance our understanding of ecological interactions occurring among cancer cells and their microenvironment. Copyright © 2015 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

msCentipede: Modeling Heterogeneity across Genomic Sites and Replicates Improves Accuracy in the Inference of Transcription Factor Binding

PubMed Central

Gilad, Yoav; Pritchard, Jonathan K.; Stephens, Matthew

2015-01-01

Understanding global gene regulation depends critically on accurate annotation of regulatory elements that are functional in a given cell type. CENTIPEDE, a powerful, probabilistic framework for identifying transcription factor binding sites from tissue-specific DNase I cleavage patterns and genomic sequence content, leverages the hypersensitivity of factor-bound chromatin and the information in the DNase I spatial cleavage profile characteristic of each DNA binding protein to accurately infer functional factor binding sites. However, the model for the spatial profile in this framework fails to account for the substantial variation in the DNase I cleavage profiles across different binding sites. Neither does it account for variation in the profiles at the same binding site across multiple replicate DNase I experiments, which are increasingly available. In this work, we introduce new methods, based on multi-scale models for inhomogeneous Poisson processes, to account for such variation in DNase I cleavage patterns both within and across binding sites. These models account for the spatial structure in the heterogeneity in DNase I cleavage patterns for each factor. Using DNase-seq measurements assayed in a lymphoblastoid cell line, we demonstrate the improved performance of this model for several transcription factors by comparing against the Chip-seq peaks for those factors. Finally, we explore the effects of DNase I sequence bias on inference of factor binding using a simple extension to our framework that allows for a more flexible background model. The proposed model can also be easily applied to paired-end ATAC-seq and DNase-seq data. msCentipede, a Python implementation of our algorithm, is available at http://rajanil.github.io/msCentipede. PMID:26406244

msCentipede: Modeling Heterogeneity across Genomic Sites and Replicates Improves Accuracy in the Inference of Transcription Factor Binding.

PubMed

Raj, Anil; Shim, Heejung; Gilad, Yoav; Pritchard, Jonathan K; Stephens, Matthew

2015-01-01

Understanding global gene regulation depends critically on accurate annotation of regulatory elements that are functional in a given cell type. CENTIPEDE, a powerful, probabilistic framework for identifying transcription factor binding sites from tissue-specific DNase I cleavage patterns and genomic sequence content, leverages the hypersensitivity of factor-bound chromatin and the information in the DNase I spatial cleavage profile characteristic of each DNA binding protein to accurately infer functional factor binding sites. However, the model for the spatial profile in this framework fails to account for the substantial variation in the DNase I cleavage profiles across different binding sites. Neither does it account for variation in the profiles at the same binding site across multiple replicate DNase I experiments, which are increasingly available. In this work, we introduce new methods, based on multi-scale models for inhomogeneous Poisson processes, to account for such variation in DNase I cleavage patterns both within and across binding sites. These models account for the spatial structure in the heterogeneity in DNase I cleavage patterns for each factor. Using DNase-seq measurements assayed in a lymphoblastoid cell line, we demonstrate the improved performance of this model for several transcription factors by comparing against the Chip-seq peaks for those factors. Finally, we explore the effects of DNase I sequence bias on inference of factor binding using a simple extension to our framework that allows for a more flexible background model. The proposed model can also be easily applied to paired-end ATAC-seq and DNase-seq data. msCentipede, a Python implementation of our algorithm, is available at http://rajanil.github.io/msCentipede.

Transplant experiments uncover Baltic Sea basin-specific responses in bacterioplankton community composition and metabolic activities.

PubMed

Lindh, Markus V; Figueroa, Daniela; Sjöstedt, Johanna; Baltar, Federico; Lundin, Daniel; Andersson, Agneta; Legrand, Catherine; Pinhassi, Jarone

2015-01-01

Anthropogenically induced changes in precipitation are projected to generate increased river runoff to semi-enclosed seas, increasing loads of terrestrial dissolved organic matter and decreasing salinity. To determine how bacterial community structure and functioning adjust to such changes, we designed microcosm transplant experiments with Baltic Proper (salinity 7.2) and Bothnian Sea (salinity 3.6) water. Baltic Proper bacteria generally reached higher abundances than Bothnian Sea bacteria in both Baltic Proper and Bothnian Sea water, indicating higher adaptability. Moreover, Baltic Proper bacteria growing in Bothnian Sea water consistently showed highest bacterial production and beta-glucosidase activity. These metabolic responses were accompanied by basin-specific changes in bacterial community structure. For example, Baltic Proper Pseudomonas and Limnobacter populations increased markedly in relative abundance in Bothnian Sea water, indicating a replacement effect. In contrast, Roseobacter and Rheinheimera populations were stable or increased in abundance when challenged by either of the waters, indicating an adjustment effect. Transplants to Bothnian Sea water triggered the initial emergence of particular Burkholderiaceae populations, and transplants to Baltic Proper water triggered Alteromonadaceae populations. Notably, in the subsequent re-transplant experiment, a priming effect resulted in further increases to dominance of these populations. Correlated changes in community composition and metabolic activity were observed only in the transplant experiment and only at relatively high phylogenetic resolution. This suggested an importance of successional progression for interpreting relationships between bacterial community composition and functioning. We infer that priming effects on bacterial community structure by natural episodic events or climate change induced forcing could translate into long-term changes in bacterial ecosystem process rates.

Transplant experiments uncover Baltic Sea basin-specific responses in bacterioplankton community composition and metabolic activities

PubMed Central

Lindh, Markus V.; Figueroa, Daniela; Sjöstedt, Johanna; Baltar, Federico; Lundin, Daniel; Andersson, Agneta; Legrand, Catherine; Pinhassi, Jarone

2015-01-01

Anthropogenically induced changes in precipitation are projected to generate increased river runoff to semi-enclosed seas, increasing loads of terrestrial dissolved organic matter and decreasing salinity. To determine how bacterial community structure and functioning adjust to such changes, we designed microcosm transplant experiments with Baltic Proper (salinity 7.2) and Bothnian Sea (salinity 3.6) water. Baltic Proper bacteria generally reached higher abundances than Bothnian Sea bacteria in both Baltic Proper and Bothnian Sea water, indicating higher adaptability. Moreover, Baltic Proper bacteria growing in Bothnian Sea water consistently showed highest bacterial production and beta-glucosidase activity. These metabolic responses were accompanied by basin-specific changes in bacterial community structure. For example, Baltic Proper Pseudomonas and Limnobacter populations increased markedly in relative abundance in Bothnian Sea water, indicating a replacement effect. In contrast, Roseobacter and Rheinheimera populations were stable or increased in abundance when challenged by either of the waters, indicating an adjustment effect. Transplants to Bothnian Sea water triggered the initial emergence of particular Burkholderiaceae populations, and transplants to Baltic Proper water triggered Alteromonadaceae populations. Notably, in the subsequent re-transplant experiment, a priming effect resulted in further increases to dominance of these populations. Correlated changes in community composition and metabolic activity were observed only in the transplant experiment and only at relatively high phylogenetic resolution. This suggested an importance of successional progression for interpreting relationships between bacterial community composition and functioning. We infer that priming effects on bacterial community structure by natural episodic events or climate change induced forcing could translate into long-term changes in bacterial ecosystem process rates. PMID:25883589

Crop monoculture rather than agriculture reduces the spatial turnover of soil bacterial communities at a regional scale.

PubMed

Figuerola, Eva L M; Guerrero, Leandro D; Türkowsky, Dominique; Wall, Luis G; Erijman, Leonardo

2015-03-01

The goal of this study was to investigate the spatial turnover of soil bacterial communities in response to environmental changes introduced by the practices of soybean monoculture or crop rotations, relative to grassland soils. Amplicon sequencing of the 16S rRNA gene was used to analyse bacterial diversity in producer fields through three successive cropping cycles within one and a half years, across a regional scale of the Argentinean Pampas. Unlike local diversity, which was not significantly affected by land use type, agricultural management had a strong influence on β-diversity patterns. Distributions of pairwise distances between all soils samples under soybean monoculture had significantly lower β-diversity and narrower breadth compared with distributions of pairwise distances between soils managed with crop rotation. Interestingly, good agricultural practices had similar degree of β-diversity as natural grasslands. The higher phylogenetic relatedness of bacterial communities in soils under monoculture across the region was likely determined by the observed loss of endemic species, and affected mostly to phyla with low regional diversity, such as Acidobacteria, Verrucomicrobia and the candidates phyla SPAM and WS3. These results suggest that the implementation of good agricultural practices, including crop rotation, may be critical for the long-term conservation of soil biodiversity. © 2014 Society for Applied Microbiology and John Wiley & Sons Ltd.

Uncovering stability mechanisms in microbial ecosystems - combining microcosm experiments, computational modelling and ecological theory in a multidisciplinary approach

NASA Astrophysics Data System (ADS)

Worrich, Anja; König, Sara; Banitz, Thomas; Centler, Florian; Frank, Karin; Kästner, Matthias; Miltner, Anja; Thullner, Martin; Wick, Lukas

2015-04-01

Although bacterial degraders in soil are commonly exposed to fluctuating environmental conditions, the functional performance of the biodegradation processes can often be maintained by resistance and resilience mechanisms. However, there is still a gap in the mechanistic understanding of key factors contributing to the stability of such an ecosystem service. Therefore we developed an integrated approach combining microcosm experiments, simulation models and ecological theory to directly make use of the strengths of these disciplines. In a continuous interplay process, data, hypotheses, and central questions are exchanged between disciplines to initiate new experiments and models to ultimately identify buffer mechanisms and factors providing functional stability. We focus on drying and rewetting-cycles in soil ecosystems, which are a major abiotic driver for bacterial activity. Functional recovery of the system was found to depend on different spatial processes in the computational model. In particular, bacterial motility is a prerequisite for biodegradation if either bacteria or substrate are heterogeneously distributed. Hence, laboratory experiments focussing on bacterial dispersal processes were conducted and confirmed this finding also for functional resistance. Obtained results will be incorporated into the model in the next step. Overall, the combination of computational modelling and laboratory experiments identified spatial processes as the main driving force for functional stability in the considered system, and has proved a powerful methodological approach.

Bacterial Population Genetics in a Forensic Context

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

Velsko, S P

This report addresses the recent Department of Homeland Security (DHS) call for a Phase I study to (1) assess gaps in the forensically relevant knowledge about the population genetics of eight bacterial agents of concern, (2) formulate a technical roadmap to address those gaps, and (3) identify new bioinformatics tools that would be necessary to analyze and interpret population genetic data in a forensic context. The eight organisms that were studied are B. anthracis, Y. pestis, F. tularensis, Brucella spp., E. coli O157/H7, Burkholderia mallei, Burkholderia pseudomallei, and C. botulinum. Our study focused on the use of bacterial population geneticsmore » by forensic investigators to test hypotheses about the possible provenance of an agent that was used in a crime or act of terrorism. Just as human population genetics underpins the calculations of match probabilities for human DNA evidence, bacterial population genetics determines the level of support that microbial DNA evidence provides for or against certain well-defined hypotheses about the origins of an infecting strain. Our key findings are: (1) Bacterial population genetics is critical for answering certain types of questions in a probabilistic manner, akin (but not identical) to 'match probabilities' in DNA forensics. (2) A basic theoretical framework for calculating likelihood ratios or posterior probabilities for forensic hypotheses based on microbial genetic comparisons has been formulated. This 'inference-on-networks' framework has deep but simple connections to the population genetics of mtDNA and Y-STRs in human DNA forensics. (3) The 'phylogeographic' approach to identifying microbial sources is not an adequate basis for understanding bacterial population genetics in a forensic context, and has limited utility, even for generating 'leads' with respect to strain origin. (4) A collection of genotyped isolates obtained opportunistically from international locations augmented by phylogenetic representations of relatedness will not and enzootic outbreaks noted through international outbreak surveillance systems, and 'representative' genetic sequences from each outbreak. (5) Interpretation of genetic comparisons between an attack strain and reference strains requires a model for the network structure of maintenance foci, enzootic outbreaks, and human outbreaks of that disease, coupled with estimates of mutational rate constants. Validation of the model requires a set of sequences from exemplary outbreaks and laboratory data on mutation rates during animal passage. The necessary number of isolates in each validation set is determined by disease transmission network theory, and is based on the 'network diameter' of the outbreak. (6) The 8 bacteria in this study can be classified into 4 categories based on the complexity of the transmission network structure of their natural maintenance foci and their outbreaks, both enzootic and zoonotic. (7) For B. anthracis, Y. pestis, E. coli O157, and Brucella melitensis, and their primary natural animal hosts, most of the fundamental parameters needed for modeling genetic change within natural host or human transmission networks have been determined or can be estimated from existing field and laboratory studies. (8) For Burkholderia mallei, plausible approaches to transmission network models exist, but much of the fundamental parameterization does not. In addition, a validated high-resolution typing system for characterizing genetic change within outbreaks or foci has not yet been demonstrated, although a candidate system exists. (9) For Francisella tularensis, the increased complexity of the transmission network and unresolved questions about maintenance and transmission suggest that it will be more complex and difficult to develop useful models based on currently available data. (10) For Burkholderia pseudomallei and Clostridium botulinum, the transmission and maintenance networks involve complex soil communities and metapopulations about which very little is known. It is not clear that these pathogens can be brought into the inference-on-networks framework without additional conceptual advances. (11) For all 8 bacteria some combination of field studies, computational modeling, and laboratory experiments are needed to provide a useful forensic capability for bacterial genetic inference.« less

Revisiting crash spatial heterogeneity: A Bayesian spatially varying coefficients approach.

PubMed

Xu, Pengpeng; Huang, Helai; Dong, Ni; Wong, S C

2017-01-01

This study was performed to investigate the spatially varying relationships between crash frequency and related risk factors. A Bayesian spatially varying coefficients model was elaborately introduced as a methodological alternative to simultaneously account for the unstructured and spatially structured heterogeneity of the regression coefficients in predicting crash frequencies. The proposed method was appealing in that the parameters were modeled via a conditional autoregressive prior distribution, which involved a single set of random effects and a spatial correlation parameter with extreme values corresponding to pure unstructured or pure spatially correlated random effects. A case study using a three-year crash dataset from the Hillsborough County, Florida, was conducted to illustrate the proposed model. Empirical analysis confirmed the presence of both unstructured and spatially correlated variations in the effects of contributory factors on severe crash occurrences. The findings also suggested that ignoring spatially structured heterogeneity may result in biased parameter estimates and incorrect inferences, while assuming the regression coefficients to be spatially clustered only is probably subject to the issue of over-smoothness. Copyright © 2016 Elsevier Ltd. All rights reserved.

Nutrients removal and bacterial community structure for low C/N municipal wastewater using a modified anaerobic/anoxic/oxic (mA2/O) process in North China.

PubMed

Zhang, Shihua; Huang, Zhijia; Lu, Shujian; Zheng, Jun; Zhang, Xinxi

2017-11-01

A modified anaerobic/anoxic/oxic (mA2/O) process based on utilizing the internal carbon source and adding polypropylene carriers was operated for 90d to investigate the nutrients removal performance and bacterial community. This system exhibited a stable and efficient performance, particularly, in removing the NH 4 + -N and total phosphorus. The results of high-throughput sequencing showed that the 13 dominant genera containing Pseudomonas, Comamonas, Arcobacter, Nitrobacteria, Nitrosospira, Nitrosomonas, Bacteroides, Flavobacterium, Rhizobium, Acinetobacter, Zoogloea, Rhodocyclus and Moraxella were shared by five zones, inferring that they were the essential players in treating low C/N (below 5.0) municipal wastewater around 10°C. The average abundance of Nitrosospira (4.21%) was higher than that of Nitrosomonas (2.93%), suggested that Nitrosospira performed well under low temperature for nitrification. Additionally, both known Rhodocyclus-related PAOs and GAOs Competibacter were not detected possibly due to low temperature. Redundancy analysis (RDA) indicated that DO played more important roles in regulating bacterial community composition than HRT. Copyright © 2017 Elsevier Ltd. All rights reserved.

Group-theoretic models of the inversion process in bacterial genomes.

PubMed

Egri-Nagy, Attila; Gebhardt, Volker; Tanaka, Mark M; Francis, Andrew R

2014-07-01

The variation in genome arrangements among bacterial taxa is largely due to the process of inversion. Recent studies indicate that not all inversions are equally probable, suggesting, for instance, that shorter inversions are more frequent than longer, and those that move the terminus of replication are less probable than those that do not. Current methods for establishing the inversion distance between two bacterial genomes are unable to incorporate such information. In this paper we suggest a group-theoretic framework that in principle can take these constraints into account. In particular, we show that by lifting the problem from circular permutations to the affine symmetric group, the inversion distance can be found in polynomial time for a model in which inversions are restricted to acting on two regions. This requires the proof of new results in group theory, and suggests a vein of new combinatorial problems concerning permutation groups on which group theorists will be needed to collaborate with biologists. We apply the new method to inferring distances and phylogenies for published Yersinia pestis data.

Prevalence of potential nitrogen-fixing, green sulphur bacteria in the skeleton of reef-building coral Isopora palifera

NASA Astrophysics Data System (ADS)

Yang, S. H.

2016-02-01

Microbial endoliths, which inhabit interior pores of rocks, skeletons and coral, are ubiquitous in terrestrial and marine environments. In the present study, various colored layers stratified the endolithic environment within the skeleton of Isopora palifera; however, there was a distinct green-pigmented layer in the skeleton (beneath the living coral tissue). To characterize diversity of endolithic microorganisms, 16S ribosomal RNA gene amplicon pyrosequencing was used to investigate bacterial communities in the green layer of Isopora palifera coral colonies retrieved fromGreen Island, Taiwan. The dominant bacterial group in the green layer belonged to the bacterial phylum Chlorobi, green sulphur bacteria capable of anoxygenic photosynthesis and nitrogen fixation. Specifically, bacteria of the genus Prosthecochloris were dominant in this green layer. To our knowledge, this is the first study to provide a detailed profile of endolithic bacteria in coral and to determine prevalence of Prosthecochloris in the green layer. Based on our findings, we infer that these bacteria may have an important functional role in the coral holobiont in the nutrient-limited coral reef ecosystem.

3'-NADP and 3'-NAADP, Two Metabolites Formed by the Bacterial Type III Effector AvrRxo1.

PubMed

Schuebel, Felix; Rocker, Andrea; Edelmann, Daniel; Schessner, Julia; Brieke, Clara; Meinhart, Anton

2016-10-28

An arsenal of effector proteins is injected by bacterial pathogens into the host cell or its vicinity to increase virulence. The commonly used top-down approaches inferring the toxic mechanism of individual effector proteins from the host's phenotype are often impeded by multiple targets of different effectors as well as by their pleiotropic effects. Here we describe our bottom-up approach, showing that the bacterial type III effector AvrRxo1 of plant pathogens is an authentic phosphotransferase that produces two novel metabolites by phosphorylating nicotinamide/nicotinic acid adenine dinucleotide at the adenosine 3'-hydroxyl group. Both products of AvrRxo1, 3'-NADP and 3'-nicotinic acid adenine dinucleotide phosphate (3'-NAADP), are substantially different from the ubiquitous co-enzyme 2'-NADP and the calcium mobilizer 2'-NAADP. Interestingly, 3'-NADP and 3'-NAADP have previously been used as inhibitors or signaling molecules but were regarded as "artificial" compounds so far. Our findings now necessitate a shift in thinking about the biological importance of 3'-phosphorylated NAD derivatives. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.

About probabilistic integration of ill-posed geophysical tomography and logging data: A knowledge discovery approach versus petrophysical transfer function concepts illustrated using cross-borehole radar-, P- and S-wave traveltime tomography in combination with cone penetration and dielectric logging data

NASA Astrophysics Data System (ADS)

Paasche, Hendrik

2018-01-01

Site characterization requires detailed and ideally spatially continuous information about the subsurface. Geophysical tomographic experiments allow for spatially continuous imaging of physical parameter variations, e.g., seismic wave propagation velocities. Such physical parameters are often related to typical geotechnical or hydrological target parameters, e.g. as achieved from 1D direct push or borehole logging. Here, the probabilistic inference of 2D tip resistance, sleeve friction, and relative dielectric permittivity distributions in near-surface sediments is constrained by ill-posed cross-borehole seismic P- and S-wave and radar wave traveltime tomography. In doing so, we follow a discovery science strategy employing a fully data-driven approach capable of accounting for tomographic ambiguity and differences in spatial resolution between the geophysical tomograms and the geotechnical logging data used for calibration. We compare the outcome to results achieved employing classical hypothesis-driven approaches, i.e., deterministic transfer functions derived empirically for the inference of 2D sleeve friction from S-wave velocity tomograms and theoretically for the inference of 2D dielectric permittivity from radar wave velocity tomograms. The data-driven approach offers maximal flexibility in combination with very relaxed considerations about the character of the expected links. This makes it a versatile tool applicable to almost any combination of data sets. However, error propagation may be critical and justify thinking about a hypothesis-driven pre-selection of an optimal database going along with the risk of excluding relevant information from the analyses. Results achieved by transfer function rely on information about the nature of the link and optimal calibration settings drawn as retrospective hypothesis by other authors. Applying such transfer functions at other sites turns them into a priori valid hypothesis, which can, particularly for empirically derived transfer functions, result in poor predictions. However, a mindful utilization and critical evaluation of the consequences of turning a retrospectively drawn hypothesis into an a priori valid hypothesis can also result in good results for inference and prediction problems when using classical transfer function concepts.

Using absolute x-ray spectral measurements to infer stagnation conditions in ICF implosions

NASA Astrophysics Data System (ADS)

Patel, Pravesh; Benedetti, L. R.; Cerjan, C.; Clark, D. S.; Hurricane, O. A.; Izumi, N.; Jarrott, L. C.; Khan, S.; Kritcher, A. L.; Ma, T.; Macphee, A. G.; Landen, O.; Spears, B. K.; Springer, P. T.

2016-10-01

Measurements of the continuum x-ray spectrum emitted from the hot-spot of an ICF implosion can be used to infer a number thermodynamic properties at stagnation including temperature, pressure, and hot-spot mix. In deuterium-tritium (DT) layered implosion experiments on the National Ignition Facility (NIF) we field a number of x-ray diagnostics that provide spatial, temporal, and spectrally-resolved measurements of the radiated x-ray emission. We report on analysis of these measurements using a 1-D hot-spot model to infer thermodynamic properties at stagnation. We compare these to similar properties that can be derived from DT fusion neutron measurements. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.

Structured statistical models of inductive reasoning.

PubMed

Kemp, Charles; Tenenbaum, Joshua B

2009-01-01

Everyday inductive inferences are often guided by rich background knowledge. Formal models of induction should aim to incorporate this knowledge and should explain how different kinds of knowledge lead to the distinctive patterns of reasoning found in different inductive contexts. This article presents a Bayesian framework that attempts to meet both goals and describes [corrected] 4 applications of the framework: a taxonomic model, a spatial model, a threshold model, and a causal model. Each model makes probabilistic inferences about the extensions of novel properties, but the priors for the 4 models are defined over different kinds of structures that capture different relationships between the categories in a domain. The framework therefore shows how statistical inference can operate over structured background knowledge, and the authors argue that this interaction between structure and statistics is critical for explaining the power and flexibility of human reasoning.

Evolution in Mind: Evolutionary Dynamics, Cognitive Processes, and Bayesian Inference.

PubMed

Suchow, Jordan W; Bourgin, David D; Griffiths, Thomas L

2017-07-01

Evolutionary theory describes the dynamics of population change in settings affected by reproduction, selection, mutation, and drift. In the context of human cognition, evolutionary theory is most often invoked to explain the origins of capacities such as language, metacognition, and spatial reasoning, framing them as functional adaptations to an ancestral environment. However, evolutionary theory is useful for understanding the mind in a second way: as a mathematical framework for describing evolving populations of thoughts, ideas, and memories within a single mind. In fact, deep correspondences exist between the mathematics of evolution and of learning, with perhaps the deepest being an equivalence between certain evolutionary dynamics and Bayesian inference. This equivalence permits reinterpretation of evolutionary processes as algorithms for Bayesian inference and has relevance for understanding diverse cognitive capacities, including memory and creativity. Copyright © 2017 Elsevier Ltd. All rights reserved.

Region-specific patterns and drivers of macroscale forest plant invasions

Treesearch

Basil V. Iannone; Christopher M. Oswalt; Andrew M. Liebhold; Qinfeng Guo; Kevin M. Potter; Gabriela C. Nunez-Mir; Sonja N. Oswalt; Bryan C. Pijanowski; Songlin Fei; Bethany Bradley

2015-01-01

Aim Stronger inferences about biological invasions may be obtained when accounting for multiple invasion measures and the spatial heterogeneity occurring across large geographic areas. We pursued this enquiry by utilizing a multimeasure, multiregional framework to investigate forest plant invasions at a subcontinental scale. ...

Inference of tumor evolution during chemotherapy by computational modeling and in situ analysis of genetic and phenotypic cellular diversity.

PubMed

Almendro, Vanessa; Cheng, Yu-Kang; Randles, Amanda; Itzkovitz, Shalev; Marusyk, Andriy; Ametller, Elisabet; Gonzalez-Farre, Xavier; Muñoz, Montse; Russnes, Hege G; Helland, Aslaug; Rye, Inga H; Borresen-Dale, Anne-Lise; Maruyama, Reo; van Oudenaarden, Alexander; Dowsett, Mitchell; Jones, Robin L; Reis-Filho, Jorge; Gascon, Pere; Gönen, Mithat; Michor, Franziska; Polyak, Kornelia

2014-02-13

Cancer therapy exerts a strong selection pressure that shapes tumor evolution, yet our knowledge of how tumors change during treatment is limited. Here, we report the analysis of cellular heterogeneity for genetic and phenotypic features and their spatial distribution in breast tumors pre- and post-neoadjuvant chemotherapy. We found that intratumor genetic diversity was tumor-subtype specific, and it did not change during treatment in tumors with partial or no response. However, lower pretreatment genetic diversity was significantly associated with pathologic complete response. In contrast, phenotypic diversity was different between pre- and posttreatment samples. We also observed significant changes in the spatial distribution of cells with distinct genetic and phenotypic features. We used these experimental data to develop a stochastic computational model to infer tumor growth patterns and evolutionary dynamics. Our results highlight the importance of integrated analysis of genotypes and phenotypes of single cells in intact tissues to predict tumor evolution. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.

Inference of tumor evolution during chemotherapy by computational modeling and in situ analysis of cellular diversity for genetic and phenotypic features

PubMed Central

Almendro, Vanessa; Cheng, Yu-Kang; Randles, Amanda; Itzkovitz, Shalev; Marusyk, Andriy; Ametller, Elisabet; Gonzalez-Farre, Xavier; Muñoz, Montse; Russnes, Hege G.; Helland, Åslaug; Rye, Inga H.; Borresen-Dale, Anne-Lise; Maruyama, Reo; van Oudenaarden, Alexander; Dowsett, Mitchell; Jones, Robin L.; Reis-Filho, Jorge; Gascon, Pere; Gönen, Mithat; Michor, Franziska; Polyak, Kornelia

2014-01-01

SUMMARY Cancer therapy exerts a strong selection pressure that shapes tumor evolution, yet our knowledge of how tumors change during treatment is limited. Here we report the analysis of cellular heterogeneity for genetic and phenotypic features and their spatial distribution in breast tumors pre- and post-neoadjuvant chemotherapy. We found that intratumor genetic diversity was tumor subtype-specific and it did not change during treatment in tumors with partial or no response. However, lower pre-treatment genetic diversity was significantly associated with complete pathologic response. In contrast, phenotypic diversity was different between pre- and post-treatment samples. We also observed significant changes in the spatial distribution of cells with distinct genetic and phenotypic features. We used these experimental data to develop a stochastic computational model to infer tumor growth patterns and evolutionary dynamics. Our results highlight the importance of integrated analysis of genotypes and phenotypes of single cells in intact tissues to predict tumor evolution. PMID:24462293

A New Approach to X-ray Analysis of SNRs

NASA Astrophysics Data System (ADS)

Frank, Kari A.; Burrows, David; Dwarkadas, Vikram

2016-06-01

We present preliminary results of applying a novel analysis method, Smoothed Particle Inference (SPI), to XMM-Newton observations of SNR RCW 103 and Tycho. SPI is a Bayesian modeling process that fits a population of gas blobs (”smoothed particles”) such that their superposed emission reproduces the observed spatial and spectral distribution of photons. Emission-weighted distributions of plasma properties, such as abundances and temperatures, are then extracted from the properties of the individual blobs. This technique has important advantages over analysis techniques which implicitly assume that remnants are two-dimensional objects in which each line of sight encompasses a single plasma. By contrast, SPI allows superposition of as many blobs of plasma as are needed to match the spectrum observed in each direction, without the need to bin the data spatially. The analyses of RCW 103 and Tycho are part of a pilot study for the larger SPIES (Smoothed Particle Inference Exploration of SNRs) project, in which SPI will be applied to a sample of 12 bright SNRs.

Spatiotemporal drivers of dissolved organic matter in high alpine lakes: Role of Saharan dust inputs and bacterial activity.

PubMed

Mladenov, Natalie; Pulido-Villena, Elvira; Morales-Baquero, Rafael; Ortega-Retuerta, Eva; Sommaruga, Ruben; Reche, Isabel

2008-01-01

The effects of many environmental stressors such as UV radiation are mediated by dissolved organic matter (DOM) properties. Therefore, determining the factors shaping spatial and temporal patterns is particularly essential in the most susceptible, low dissolved organic carbon (DOC) lakes. We analyzed spatiotemporal variations in dissolved organic carbon concentration and dissolved organic matter optical properties (absorption and fluorescence) in 11 transparent lakes located above tree line in the Sierra Nevada Mountains (Spain), and we assessed potential external (evaporation and atmospheric deposition) and internal (bacterial abundance, bacterial production, chlorophyll a, and catchment vegetation) drivers of DOM patterns. At spatial and temporal scales, bacteria were related to chromophoric DOM (CDOM). At the temporal scale, water soluble organic carbon (WSOC) in dust deposition and evaporation were found to have a significant influence on DOC and CDOM in two Sierra Nevada lakes studied during the ice-free periods of 2000-2002. DOC concentrations and absorption coefficients at 320 nm were strongly correlated over the spatial scale (n = 11, R(2) = 0.86; p < 0.01), but inconsistently correlated over time, indicating seasonal and interannual variability in external factors and a differential response of DOC concentration and CDOM to these factors. At the continental scale, higher mean DOC concentrations and more CDOM in lakes of the Sierra Nevada than in lakes of the Pyrenees and Alps may be due to a combination of more extreme evaporation, and greater atmospheric dust deposition.

Spatiotemporal drivers of dissolved organic matter in high alpine lakes: Role of Saharan dust inputs and bacterial activity

PubMed Central

Mladenov, Natalie; Pulido-Villena, Elvira; Morales-Baquero, Rafael; Ortega-Retuerta, Eva; Sommaruga, Ruben; Reche, Isabel

2010-01-01

The effects of many environmental stressors such as UV radiation are mediated by dissolved organic matter (DOM) properties. Therefore, determining the factors shaping spatial and temporal patterns is particularly essential in the most susceptible, low dissolved organic carbon (DOC) lakes. We analyzed spatiotemporal variations in dissolved organic carbon concentration and dissolved organic matter optical properties (absorption and fluorescence) in 11 transparent lakes located above tree line in the Sierra Nevada Mountains (Spain), and we assessed potential external (evaporation and atmospheric deposition) and internal (bacterial abundance, bacterial production, chlorophyll a, and catchment vegetation) drivers of DOM patterns. At spatial and temporal scales, bacteria were related to chromophoric DOM (CDOM). At the temporal scale, water soluble organic carbon (WSOC) in dust deposition and evaporation were found to have a significant influence on DOC and CDOM in two Sierra Nevada lakes studied during the ice-free periods of 2000–2002. DOC concentrations and absorption coefficients at 320 nm were strongly correlated over the spatial scale (n = 11, R2 = 0.86; p < 0.01), but inconsistently correlated over time, indicating seasonal and interannual variability in external factors and a differential response of DOC concentration and CDOM to these factors. At the continental scale, higher mean DOC concentrations and more CDOM in lakes of the Sierra Nevada than in lakes of the Pyrenees and Alps may be due to a combination of more extreme evaporation, and greater atmospheric dust deposition. PMID:20582227

Soil Bacteria and Fungi Respond on Different Spatial Scales to Invasion by the Legume Lespedeza cuneata.

PubMed

Yannarell, Anthony C; Busby, Ryan R; Denight, Michael L; Gebhart, Dick L; Taylor, Steven J

2011-01-01

The spatial scale on which microbial communities respond to plant invasions may provide important clues as to the nature of potential invader-microbe interactions. Lespedeza cuneata (Dum. Cours.) G. Don is an invasive legume that may benefit from associations with mycorrhizal fungi; however, it has also been suggested that the plant is allelopathic and may alter the soil chemistry of invaded sites through secondary metabolites in its root exudates or litter. Thus, L. cuneata invasion may interact with soil microorganisms on a variety of scales. We investigated L. cuneata-related changes to soil bacterial and fungal communities at two spatial scales using multiple sites from across its invaded N. American range. Using whole-community DNA fingerprinting, we characterized microbial community variation at the scale of entire invaded sites and at the scale of individual plants. Based on permutational multivariate analysis of variance, soil bacterial communities in heavily invaded sites were significantly different from those of uninvaded sites, but bacteria did not show any evidence of responding at very local scales around individual plants. In contrast, soil fungi did not change significantly at the scale of entire sites, but there were significant differences between fungal communities of native versus exotic plants within particular sites. The differential scaling of bacterial and fungal responses indicates that L. cuneata interacts differently with soil bacteria and soil fungi, and these microorganisms may play very different roles in the invasion process of this plant.

Interactions between hydrology and water chemistry shape bacterioplankton biogeography across boreal freshwater networks

PubMed Central

Niño-García, Juan Pablo; Ruiz-González, Clara; del Giorgio, Paul A

2016-01-01

Disentangling the mechanisms shaping bacterioplankton communities across freshwater ecosystems requires considering a hydrologic dimension that can influence both dispersal and local sorting, but how the environment and hydrology interact to shape the biogeography of freshwater bacterioplankton over large spatial scales remains unexplored. Using Illumina sequencing of the 16S ribosomal RNA gene, we investigate the large-scale spatial patterns of bacterioplankton across 386 freshwater systems from seven distinct regions in boreal Québec. We show that both hydrology and local water chemistry (mostly pH) interact to shape a sequential structuring of communities from highly diverse assemblages in headwater streams toward larger rivers and lakes dominated by fewer taxa. Increases in water residence time along the hydrologic continuum were accompanied by major losses of bacterial richness and by an increased differentiation of communities driven by local conditions (pH and other related variables). This suggests that hydrology and network position modulate the relative role of environmental sorting and mass effects on community assembly by determining both the time frame for bacterial growth and the composition of the immigrant pool. The apparent low dispersal limitation (that is, the lack of influence of geographic distance on the spatial patterns observed at the taxonomic resolution used) suggests that these boreal bacterioplankton communities derive from a shared bacterial pool that enters the networks through the smallest streams, largely dominated by mass effects, and that is increasingly subjected to local sorting of species during transit along the hydrologic continuum. PMID:26849312

Interactions between hydrology and water chemistry shape bacterioplankton biogeography across boreal freshwater networks.

PubMed

Niño-García, Juan Pablo; Ruiz-González, Clara; Del Giorgio, Paul A

2016-07-01

Disentangling the mechanisms shaping bacterioplankton communities across freshwater ecosystems requires considering a hydrologic dimension that can influence both dispersal and local sorting, but how the environment and hydrology interact to shape the biogeography of freshwater bacterioplankton over large spatial scales remains unexplored. Using Illumina sequencing of the 16S ribosomal RNA gene, we investigate the large-scale spatial patterns of bacterioplankton across 386 freshwater systems from seven distinct regions in boreal Québec. We show that both hydrology and local water chemistry (mostly pH) interact to shape a sequential structuring of communities from highly diverse assemblages in headwater streams toward larger rivers and lakes dominated by fewer taxa. Increases in water residence time along the hydrologic continuum were accompanied by major losses of bacterial richness and by an increased differentiation of communities driven by local conditions (pH and other related variables). This suggests that hydrology and network position modulate the relative role of environmental sorting and mass effects on community assembly by determining both the time frame for bacterial growth and the composition of the immigrant pool. The apparent low dispersal limitation (that is, the lack of influence of geographic distance on the spatial patterns observed at the taxonomic resolution used) suggests that these boreal bacterioplankton communities derive from a shared bacterial pool that enters the networks through the smallest streams, largely dominated by mass effects, and that is increasingly subjected to local sorting of species during transit along the hydrologic continuum.

Spatial variation of physicochemical and bacteriological parameters elucidation with GIS in Rangat Bay, Middle Andaman, India

NASA Astrophysics Data System (ADS)

Dheenan, P. S.; Jha, Dilip Kumar; Vinithkumar, N. V.; Ponmalar, A. Angelin; Venkateshwaran, P.; Kirubagaran, R.

2014-01-01

The purpose of this study was to determine the concentration, distribution of bacteria and physicochemical property of surface seawater in Rangat Bay, Middle Andaman, Andaman Islands (India). The bay experiences tidal variations. Perhaps physicochemical properties of seawater in Rangat Bay were found not to vary significantly. The concentration of faecal streptococci was high (2.2 × 103 CFU/100 mL) at creek and harbour area, whereas total coliforms were high (7.0 × 102 CFU/100 mL) at mangrove area. Similarly, total heterotrophic bacterial concentration was high (5.92 × 104 CFU/100 mL) in mangrove and harbour area. The Vibrio cholerae and Vibrio parahaemolyticus concentration was high (4.2 × 104 CFU/100 mL and 9 × 103 CFU/100 mL) at open sea. Cluster analysis showed grouping of stations in different tidal periods. The spatial maps clearly depicted the bacterial concentration pattern in the bay. The combined approach of multivariate analysis and spatial mapping techniques was proved to be useful in the current study.

Estimating mountain basin-mean precipitation from streamflow using Bayesian inference

NASA Astrophysics Data System (ADS)

Henn, Brian; Clark, Martyn P.; Kavetski, Dmitri; Lundquist, Jessica D.

2015-10-01

Estimating basin-mean precipitation in complex terrain is difficult due to uncertainty in the topographical representativeness of precipitation gauges relative to the basin. To address this issue, we use Bayesian methodology coupled with a multimodel framework to infer basin-mean precipitation from streamflow observations, and we apply this approach to snow-dominated basins in the Sierra Nevada of California. Using streamflow observations, forcing data from lower-elevation stations, the Bayesian Total Error Analysis (BATEA) methodology and the Framework for Understanding Structural Errors (FUSE), we infer basin-mean precipitation, and compare it to basin-mean precipitation estimated using topographically informed interpolation from gauges (PRISM, the Parameter-elevation Regression on Independent Slopes Model). The BATEA-inferred spatial patterns of precipitation show agreement with PRISM in terms of the rank of basins from wet to dry but differ in absolute values. In some of the basins, these differences may reflect biases in PRISM, because some implied PRISM runoff ratios may be inconsistent with the regional climate. We also infer annual time series of basin precipitation using a two-step calibration approach. Assessment of the precision and robustness of the BATEA approach suggests that uncertainty in the BATEA-inferred precipitation is primarily related to uncertainties in hydrologic model structure. Despite these limitations, time series of inferred annual precipitation under different model and parameter assumptions are strongly correlated with one another, suggesting that this approach is capable of resolving year-to-year variability in basin-mean precipitation.

Sustainability of Virulence in a Phage-Bacterial Ecosystem ▿ †

PubMed Central

Heilmann, Silja; Sneppen, Kim; Krishna, Sandeep

2010-01-01

Virulent phages and their bacterial hosts represent an unusual sort of predator-prey system where each time a prey is eaten, hundreds of new predators are born. It is puzzling how, despite the apparent effectiveness of the phage predators, they manage to avoid driving their bacterial prey to extinction. Here we consider a phage-bacterial ecosystem on a two-dimensional (2-d) surface and show that homogeneous space in itself enhances coexistence. We analyze different behavioral mechanisms that can facilitate coexistence in a spatial environment. For example, we find that when the latent times of the phage are allowed to evolve, selection favors “mediocre killers,” since voracious phage rapidly deplete local resources and go extinct. Our model system thus emphasizes the differences between short-term proliferation and long-term ecosystem sustainability. PMID:20071588

Exploring complex dynamics in multi agent-based intelligent systems: Theoretical and experimental approaches using the Multi Agent-based Behavioral Economic Landscape (MABEL) model

NASA Astrophysics Data System (ADS)

Alexandridis, Konstantinos T.

This dissertation adopts a holistic and detailed approach to modeling spatially explicit agent-based artificial intelligent systems, using the Multi Agent-based Behavioral Economic Landscape (MABEL) model. The research questions that addresses stem from the need to understand and analyze the real-world patterns and dynamics of land use change from a coupled human-environmental systems perspective. Describes the systemic, mathematical, statistical, socio-economic and spatial dynamics of the MABEL modeling framework, and provides a wide array of cross-disciplinary modeling applications within the research, decision-making and policy domains. Establishes the symbolic properties of the MABEL model as a Markov decision process, analyzes the decision-theoretic utility and optimization attributes of agents towards comprising statistically and spatially optimal policies and actions, and explores the probabilogic character of the agents' decision-making and inference mechanisms via the use of Bayesian belief and decision networks. Develops and describes a Monte Carlo methodology for experimental replications of agent's decisions regarding complex spatial parcel acquisition and learning. Recognizes the gap on spatially-explicit accuracy assessment techniques for complex spatial models, and proposes an ensemble of statistical tools designed to address this problem. Advanced information assessment techniques such as the Receiver-Operator Characteristic curve, the impurity entropy and Gini functions, and the Bayesian classification functions are proposed. The theoretical foundation for modular Bayesian inference in spatially-explicit multi-agent artificial intelligent systems, and the ensembles of cognitive and scenario assessment modular tools build for the MABEL model are provided. Emphasizes the modularity and robustness as valuable qualitative modeling attributes, and examines the role of robust intelligent modeling as a tool for improving policy-decisions related to land use change. Finally, the major contributions to the science are presented along with valuable directions for future research.

A New Pansharpening Method Based on Spatial and Spectral Sparsity Priors.

PubMed

He, Xiyan; Condat, Laurent; Bioucas-Diaz, Jose; Chanussot, Jocelyn; Xia, Junshi

2014-06-27

The development of multisensor systems in recent years has led to great increase in the amount of available remote sensing data. Image fusion techniques aim at inferring high quality images of a given area from degraded versions of the same area obtained by multiple sensors. This paper focuses on pansharpening, which is the inference of a high spatial resolution multispectral image from two degraded versions with complementary spectral and spatial resolution characteristics: a) a low spatial resolution multispectral image; and b) a high spatial resolution panchromatic image. We introduce a new variational model based on spatial and spectral sparsity priors for the fusion. In the spectral domain we encourage low-rank structure, whereas in the spatial domain we promote sparsity on the local differences. Given the fact that both panchromatic and multispectral images are integrations of the underlying continuous spectra using different channel responses, we propose to exploit appropriate regularizations based on both spatial and spectral links between panchromatic and the fused multispectral images. A weighted version of the vector Total Variation (TV) norm of the data matrix is employed to align the spatial information of the fused image with that of the panchromatic image. With regard to spectral information, two different types of regularization are proposed to promote a soft constraint on the linear dependence between the panchromatic and the fused multispectral images. The first one estimates directly the linear coefficients from the observed panchromatic and low resolution multispectral images by Linear Regression (LR) while the second one employs the Principal Component Pursuit (PCP) to obtain a robust recovery of the underlying low-rank structure. We also show that the two regularizers are strongly related. The basic idea of both regularizers is that the fused image should have low-rank and preserve edge locations. We use a variation of the recently proposed Split Augmented Lagrangian Shrinkage (SALSA) algorithm to effectively solve the proposed variational formulations. Experimental results on simulated and real remote sensing images show the effectiveness of the proposed pansharpening method compared to the state-of-the-art.

Global marine bacterial diversity peaks at high latitudes in winter

PubMed Central

Ladau, Joshua; Sharpton, Thomas J; Finucane, Mariel M; Jospin, Guillaume; Kembel, Steven W; O'Dwyer, James; Koeppel, Alexander F; Green, Jessica L; Pollard, Katherine S

2013-01-01

Genomic approaches to characterizing bacterial communities are revealing significant differences in diversity and composition between environments. But bacterial distributions have not been mapped at a global scale. Although current community surveys are way too sparse to map global diversity patterns directly, there is now sufficient data to fit accurate models of how bacterial distributions vary across different environments and to make global scale maps from these models. We apply this approach to map the global distributions of bacteria in marine surface waters. Our spatially and temporally explicit predictions suggest that bacterial diversity peaks in temperate latitudes across the world's oceans. These global peaks are seasonal, occurring 6 months apart in the two hemispheres, in the boreal and austral winters. This pattern is quite different from the tropical, seasonally consistent diversity patterns observed for most macroorganisms. However, like other marine organisms, surface water bacteria are particularly diverse in regions of high human environmental impacts on the oceans. Our maps provide the first picture of bacterial distributions at a global scale and suggest important differences between the diversity patterns of bacteria compared with other organisms. PMID:23514781

Nematode grazing promotes bacterial community dynamics in soil at the aggregate level

PubMed Central

Jiang, Yuji; Liu, Manqiang; Zhang, Jiabao; Chen, Yan; Chen, Xiaoyun; Chen, Lijun; Li, Huixin; Zhang, Xue-Xian; Sun, Bo

2017-01-01

Nematode predation has important roles in determining bacterial community composition and dynamics, but the extent of the effects remains largely rudimentary, particularly in natural environment settings. Here, we investigated the complex microbial–microfaunal interactions in the rhizosphere of maize grown in red soils, which were derived from four long-term fertilization regimes. Root-free rhizosphere soil samples were separated into three aggregate fractions whereby the abundance and community composition were examined for nematode and total bacterial communities. A functional group of alkaline phosphomonoesterase (ALP) producing bacteria was included to test the hypothesis that nematode grazing may significantly affect specific bacteria-mediated ecological functions, that is, organic phosphate cycling in soil. Results of correlation analysis, structural equation modeling and interaction networks combined with laboratory microcosm experiments consistently indicated that bacterivorous nematodes enhanced bacterial diversity, and the abundance of bacterivores was positively correlated with bacterial biomass, including ALP-producing bacterial abundance. Significantly, such effects were more pronounced in large macroaggregates than in microaggregates. There was a positive correlation between the most dominant bacterivores Protorhabditis and the ALP-producing keystone 'species' Mesorhizobium. Taken together, these findings implicate important roles of nematodes in stimulating bacterial dynamics in a spatially dependent manner. PMID:28742069

Nematode grazing promotes bacterial community dynamics in soil at the aggregate level.

PubMed

Jiang, Yuji; Liu, Manqiang; Zhang, Jiabao; Chen, Yan; Chen, Xiaoyun; Chen, Lijun; Li, Huixin; Zhang, Xue-Xian; Sun, Bo

2017-12-01

Nematode predation has important roles in determining bacterial community composition and dynamics, but the extent of the effects remains largely rudimentary, particularly in natural environment settings. Here, we investigated the complex microbial-microfaunal interactions in the rhizosphere of maize grown in red soils, which were derived from four long-term fertilization regimes. Root-free rhizosphere soil samples were separated into three aggregate fractions whereby the abundance and community composition were examined for nematode and total bacterial communities. A functional group of alkaline phosphomonoesterase (ALP) producing bacteria was included to test the hypothesis that nematode grazing may significantly affect specific bacteria-mediated ecological functions, that is, organic phosphate cycling in soil. Results of correlation analysis, structural equation modeling and interaction networks combined with laboratory microcosm experiments consistently indicated that bacterivorous nematodes enhanced bacterial diversity, and the abundance of bacterivores was positively correlated with bacterial biomass, including ALP-producing bacterial abundance. Significantly, such effects were more pronounced in large macroaggregates than in microaggregates. There was a positive correlation between the most dominant bacterivores Protorhabditis and the ALP-producing keystone 'species' Mesorhizobium. Taken together, these findings implicate important roles of nematodes in stimulating bacterial dynamics in a spatially dependent manner.

Enhanced mixing and spatial instability in concentrated bacterial suspensions

NASA Astrophysics Data System (ADS)

Sokolov, Andrey; Goldstein, Raymond E.; Feldchtein, Felix I.; Aranson, Igor S.

2009-09-01

High-resolution optical coherence tomography is used to study the onset of a large-scale convective motion in free-standing thin films of adjustable thickness containing suspensions of swimming aerobic bacteria. Clear evidence is found that beyond a threshold film thickness there exists a transition from quasi-two-dimensional collective swimming to three-dimensional turbulent behavior. The latter state, qualitatively different from bioconvection in dilute bacterial suspensions, is characterized by enhanced diffusivities of oxygen and bacteria. These results emphasize the impact of self-organized bacterial locomotion on the onset of three-dimensional dynamics, and suggest key ingredients necessary to extend standard models of bioconvection to incorporate effects of large-scale collective motion.

Millennial-scale ocean acidification and late Quaternary decline of cryptic bacterial crusts in tropical reefs.

PubMed

Riding, R; Liang, L; Braga, J C

2014-09-01

Ocean acidification by atmospheric carbon dioxide has increased almost continuously since the last glacial maximum (LGM), 21,000 years ago. It is expected to impair tropical reef development, but effects on reefs at the present day and in the recent past have proved difficult to evaluate. We present evidence that acidification has already significantly reduced the formation of calcified bacterial crusts in tropical reefs. Unlike major reef builders such as coralline algae and corals that more closely control their calcification, bacterial calcification is very sensitive to ambient changes in carbonate chemistry. Bacterial crusts in reef cavities have declined in thickness over the past 14,000 years with largest reduction occurring 12,000-10,000 years ago. We interpret this as an early effect of deglacial ocean acidification on reef calcification and infer that similar crusts were likely to have been thicker when seawater carbonate saturation was increased during earlier glacial intervals, and thinner during interglacials. These changes in crust thickness could have substantially affected reef development over glacial cycles, as rigid crusts significantly strengthen framework and their reduction would have increased the susceptibility of reefs to biological and physical erosion. Bacterial crust decline reveals previously unrecognized millennial-scale acidification effects on tropical reefs. This directs attention to the role of crusts in reef formation and the ability of bioinduced calcification to reflect changes in seawater chemistry. It also provides a long-term context for assessing anticipated anthropogenic effects. © 2014 John Wiley & Sons Ltd.

Mobile Bacterial Group II Introns at the Crux of Eukaryotic Evolution

PubMed Central

Lambowitz, Alan M.; Belfort, Marlene

2015-01-01

SUMMARY This review focuses on recent developments in our understanding of group II intron function, the relationships of these introns to retrotransposons and spliceosomes, and how their common features have informed thinking about bacterial group II introns as key elements in eukaryotic evolution. Reverse transcriptase-mediated and host factor-aided intron retrohoming pathways are considered along with retrotransposition mechanisms to novel sites in bacteria, where group II introns are thought to have originated. DNA target recognition and movement by target-primed reverse transcription infer an evolutionary relationship among group II introns, non-LTR retrotransposons, such as LINE elements, and telomerase. Additionally, group II introns are almost certainly the progenitors of spliceosomal introns. Their profound similarities include splicing chemistry extending to RNA catalysis, reaction stereochemistry, and the position of two divalent metals that perform catalysis at the RNA active site. There are also sequence and structural similarities between group II introns and the spliceosome’s small nuclear RNAs (snRNAs) and between a highly conserved core spliceosomal protein Prp8 and a group II intron-like reverse transcriptase. It has been proposed that group II introns entered eukaryotes during bacterial endosymbiosis or bacterial-archaeal fusion, proliferated within the nuclear genome, necessitating evolution of the nuclear envelope, and fragmented giving rise to spliceosomal introns. Thus, these bacterial self-splicing mobile elements have fundamentally impacted the composition of extant eukaryotic genomes, including the human genome, most of which is derived from close relatives of mobile group II introns. PMID:25878921

Bioprinting Living Biofilms through Optogenetic Manipulation.

PubMed

Huang, Yajia; Xia, Aiguo; Yang, Guang; Jin, Fan

2018-04-18

In this paper, we present a new strategy for microprinting dense bacterial communities with a prescribed organization on a substrate. Unlike conventional bioprinting techniques that require bioinks, through optogenetic manipulation, we directly manipulated the behaviors of Pseudomonas aeruginosa to allow these living bacteria to autonomically form patterned biofilms following prescribed illumination. The results showed that through optogenetic manipulation, patterned bacterial communities with high spatial resolution (approximately 10 μm) could be constructed in 6 h. Thus, optogenetic manipulation greatly increases the range of available bioprinting techniques.

Effects of remediation on the bacterial community of an acid mine drainage impacted stream.

PubMed

Ghosh, Suchismita; Moitra, Moumita; Woolverton, Christopher J; Leff, Laura G

2012-11-01

Acid mine drainage (AMD) represents a global threat to water resources, and as such, remediation of AMD-impacted streams is a common practice. During this study, we examined bacterial community structure and environmental conditions in a low-order AMD-impacted stream before, during, and after remediation. Bacterial community structure was examined via polymerase chain reaction amplification of 16S rRNA genes followed by denaturing gradient gel electrophoresis. Also, bacterial abundance and physicochemical data (including metal concentrations) were collected and relationships to bacterial community structure were determined using BIO-ENV analysis. Remediation of the study stream altered environmental conditions, including pH and concentrations of some metals, and consequently, the bacterial community changed. However, remediation did not necessarily restore the stream to conditions found in the unimpacted reference stream; for example, bacterial abundances and concentrations of some elements, such as sulfur, magnesium, and manganese, were different in the remediated stream than in the reference stream. BIO-ENV analysis revealed that changes in pH and iron concentration, associated with remediation, primarily explained temporal alterations in bacterial community structure. Although the sites sampled in the remediated stream were in relatively close proximity to each other, spatial variation in community composition suggests that differences in local environmental conditions may have large impacts on the microbial assemblage.

USING GIS TO GENERATE SPATIALLY-BALANCED RANDOM SURVEY DESIGNS FOR NATURAL RESOURCE APPLICATIONS

EPA Science Inventory

Sampling of a population is frequently required to understand trends and patterns in natural resource management because financial and time constraints preclude a complete census. A rigorous probability-based survey design specifies where to sample so that inferences from the sam...

Multi-scale habitat selection modeling: A review and outlook

Treesearch

Kevin McGarigal; Ho Yi Wan; Kathy A. Zeller; Brad C. Timm; Samuel A. Cushman

2016-01-01

Scale is the lens that focuses ecological relationships. Organisms select habitat at multiple hierarchical levels and at different spatial and/or temporal scales within each level. Failure to properly address scale dependence can result in incorrect inferences in multi-scale habitat selection modeling studies.

Efficiency of temporary storage of geothermal waters in a lake system: Monitoring the changes of water quality and bacterial community structures.

PubMed

Szirányi, Barbara; Krett, Gergely; Kosáros, Tünde; Janurik, Endre; Pekár, Ferenc; Márialigeti, Károly; Borsodi, Andrea K

2017-12-01

Disposal of used geothermal waters in Hungary often means temporary storage in reservoir lakes to reduce temperature and improve water quality. In this study, the physical and chemical properties and changes in the bacterial community structure of a reservoir lake system in southeast region of Hungary were monitored and compared through 2 years, respectively. The values of biological oxygen demand, concentrations of ammonium ion, total inorganic nitrogen, total phosphorous, and total phenol decreased, whereas oxygen saturation, total organic nitrogen, pH, and conductivity increased during the storage period. Bacterial community structure of water and sediment samples was compared by denaturing gradient gel electrophoresis (DGGE) following the amplification of the 16S rRNA gene. According to the DGGE patterns, greater seasonal than spatial differences of bacterial communities were revealed in both water and sediment of the lakes. Representatives of the genera Arthrospira and Anabaenopsis (cyanobacteria) were identified as permanent and dominant members of the bacterial communities.

Changing bacterial profile of Sundarbans, the world heritage mangrove: impact of anthropogenic interventions.

PubMed

Chakraborty, Arpita; Bera, Amit; Mukherjee, Arghya; Basak, Pijush; Khan, Imroze; Mondal, Arindam; Roy, Arunava; Bhattacharyya, Anish; SenGupta, Sohan; Roy, Debojyoti; Nag, Sudip; Ghosh, Abhrajyoti; Chattopadhyay, Dhrubajyoti; Bhattacharyya, Maitree

2015-04-01

Mangrove microbial communities and their associated activities have profound impact on biogeochemical cycles. Although microbial composition and structure are known to be influenced by biotic and abiotic factors in the mangrove sediments, finding direct correlations between them remains a challenge. In this study we have explored sediment bacterial diversity of the Sundarbans, a world heritage site using a culture-independent molecular approach. Bacterial diversity was analyzed from three different locations with a history of exposure to differential anthropogenic activities. 16S rRNA gene libraries were constructed and partial sequencing of the clones was performed to identify the microbial strains. We identified bacterial strains known to be involved in a variety of biodegradation/biotransformation processes including hydrocarbon degradation, and heavy metal resistance. Canonical Correspondence Analysis of the environmental and exploratory datasets revealed correlations between the ecological indices associated with pollutant levels and bacterial diversity across the sites. Our results indicate that sites with similar exposure of anthropogenic intervention reflect similar patterns of microbial diversity besides spatial commonalities.

Features of the bronchial bacterial microbiome associated with atopy, asthma, and responsiveness to inhaled corticosteroid treatment.

PubMed

Durack, Juliana; Lynch, Susan V; Nariya, Snehal; Bhakta, Nirav R; Beigelman, Avraham; Castro, Mario; Dyer, Anne-Marie; Israel, Elliot; Kraft, Monica; Martin, Richard J; Mauger, David T; Rosenberg, Sharon R; Sharp-King, Tonya; White, Steven R; Woodruff, Prescott G; Avila, Pedro C; Denlinger, Loren C; Holguin, Fernando; Lazarus, Stephen C; Lugogo, Njira; Moore, Wendy C; Peters, Stephen P; Que, Loretta; Smith, Lewis J; Sorkness, Christine A; Wechsler, Michael E; Wenzel, Sally E; Boushey, Homer A; Huang, Yvonne J

2017-07-01

Compositional differences in the bronchial bacterial microbiota have been associated with asthma, but it remains unclear whether the findings are attributable to asthma, to aeroallergen sensitization, or to inhaled corticosteroid treatment. We sought to compare the bronchial bacterial microbiota in adults with steroid-naive atopic asthma, subjects with atopy but no asthma, and nonatopic healthy control subjects and to determine relationships of the bronchial microbiota to phenotypic features of asthma. Bacterial communities in protected bronchial brushings from 42 atopic asthmatic subjects, 21 subjects with atopy but no asthma, and 21 healthy control subjects were profiled by using 16S rRNA gene sequencing. Bacterial composition and community-level functions inferred from sequence profiles were analyzed for between-group differences. Associations with clinical and inflammatory variables were examined, including markers of type 2-related inflammation and change in airway hyperresponsiveness after 6 weeks of fluticasone treatment. The bronchial microbiome differed significantly among the 3 groups. Asthmatic subjects were uniquely enriched in members of the Haemophilus, Neisseria, Fusobacterium, and Porphyromonas species and the Sphingomonodaceae family and depleted in members of the Mogibacteriaceae family and Lactobacillales order. Asthma-associated differences in predicted bacterial functions included involvement of amino acid and short-chain fatty acid metabolism pathways. Subjects with type 2-high asthma harbored significantly lower bronchial bacterial burden. Distinct changes in specific microbiota members were seen after fluticasone treatment. Steroid responsiveness was linked to differences in baseline compositional and functional features of the bacterial microbiome. Even in subjects with mild steroid-naive asthma, differences in the bronchial microbiome are associated with immunologic and clinical features of the disease. The specific differences identified suggest possible microbiome targets for future approaches to asthma treatment or prevention. Copyright © 2016 American Academy of Allergy, Asthma & Immunology. Published by Elsevier Inc. All rights reserved.

Characterization of Polar Stratospheric Clouds With Spaceborne Lidar: CALIPSO and the 2006 Antarctic Season

NASA Technical Reports Server (NTRS)

Pitts, Michael C.; Thomason, L. W.; Poole, Lamont R.; Winker, David M.

2007-01-01

The role of polar stratospheric clouds in polar ozone loss has been well documented. The CALIPSO satellite mission offers a new opportunity to characterize PSCs on spatial and temporal scales previously unavailable. A PSC detection algorithm based on a single wavelength threshold approach has been developed for CALIPSO. The method appears to accurately detect PSCs of all opacities, including tenuous clouds, with a very low rate of false positives and few missed clouds. We applied the algorithm to CALIPSO data acquired during the 2006 Antarctic winter season from 13 June through 31 October. The spatial and temporal distribution of CALIPSO PSC observations is illustrated with weekly maps of PSC occurrence. The evolution of the 2006 PSC season is depicted by time series of daily PSC frequency as a function of altitude. Comparisons with virtual solar occultation data indicate that CALIPSO provides a different view of the PSC season than attained with previous solar occultation satellites. Measurement-based time series of PSC areal coverage and vertically-integrated PSC volume are computed from the CALIPSO data. The observed area covered with PSCs is significantly smaller than would be inferred from a temperature-based proxy such as TNAT but is similar in magnitude to that inferred from TSTS. The potential of CALIPSO measurements for investigating PSC microphysics is illustrated using combinations of lidar backscatter coefficient and volume depolarization to infer composition for two CALIPSO PSC scenes.

A Coalitional Game for Distributed Inference in Sensor Networks With Dependent Observations

NASA Astrophysics Data System (ADS)

He, Hao; Varshney, Pramod K.

2016-04-01

We consider the problem of collaborative inference in a sensor network with heterogeneous and statistically dependent sensor observations. Each sensor aims to maximize its inference performance by forming a coalition with other sensors and sharing information within the coalition. It is proved that the inference performance is a nondecreasing function of the coalition size. However, in an energy constrained network, the energy consumption of inter-sensor communication also increases with increasing coalition size, which discourages the formation of the grand coalition (the set of all sensors). In this paper, the formation of non-overlapping coalitions with statistically dependent sensors is investigated under a specific communication constraint. We apply a game theoretical approach to fully explore and utilize the information contained in the spatial dependence among sensors to maximize individual sensor performance. Before formulating the distributed inference problem as a coalition formation game, we first quantify the gain and loss in forming a coalition by introducing the concepts of diversity gain and redundancy loss for both estimation and detection problems. These definitions, enabled by the statistical theory of copulas, allow us to characterize the influence of statistical dependence among sensor observations on inference performance. An iterative algorithm based on merge-and-split operations is proposed for the solution and the stability of the proposed algorithm is analyzed. Numerical results are provided to demonstrate the superiority of our proposed game theoretical approach.

Cortical Hierarchies Perform Bayesian Causal Inference in Multisensory Perception

PubMed Central

Rohe, Tim; Noppeney, Uta

2015-01-01

To form a veridical percept of the environment, the brain needs to integrate sensory signals from a common source but segregate those from independent sources. Thus, perception inherently relies on solving the “causal inference problem.” Behaviorally, humans solve this problem optimally as predicted by Bayesian Causal Inference; yet, the underlying neural mechanisms are unexplored. Combining psychophysics, Bayesian modeling, functional magnetic resonance imaging (fMRI), and multivariate decoding in an audiovisual spatial localization task, we demonstrate that Bayesian Causal Inference is performed by a hierarchy of multisensory processes in the human brain. At the bottom of the hierarchy, in auditory and visual areas, location is represented on the basis that the two signals are generated by independent sources (= segregation). At the next stage, in posterior intraparietal sulcus, location is estimated under the assumption that the two signals are from a common source (= forced fusion). Only at the top of the hierarchy, in anterior intraparietal sulcus, the uncertainty about the causal structure of the world is taken into account and sensory signals are combined as predicted by Bayesian Causal Inference. Characterizing the computational operations of signal interactions reveals the hierarchical nature of multisensory perception in human neocortex. It unravels how the brain accomplishes Bayesian Causal Inference, a statistical computation fundamental for perception and cognition. Our results demonstrate how the brain combines information in the face of uncertainty about the underlying causal structure of the world. PMID:25710328

Relationship between spatial and genetic distance in Agrobacterium spp. in 1 cubic centimeter of soil.

PubMed

Vogel, J; Normand, P; Thioulouse, J; Nesme, X; Grundmann, G L

2003-03-01

The spatial and genetic unit of bacterial population structure is the clone. Surprisingly, very little is known about the spread of a clone (spatial distance between clonally related bacteria) and the relationship between spatial distance and genetic distance, especially at very short scale (microhabitat scale), where cell division takes place. Agrobacterium spp. Biovar 1 was chosen because it is a soil bacterial taxon easy to isolate. A total of 865 microsamples 500 microm in diameter were sampled with spatial coordinates in 1 cm(3) of undisturbed soil. The 55 isolates obtained yielded 42 ribotypes, covering three genomic species based on amplified ribosomal DNA restriction analysis (ARDRA) of the intergenic spacer 16S-23S, seven of which contained two to six isolates. These clonemates (identical ARDRA patterns) could be found in the same microsample or 1 cm apart. The genetic diversity did not change with distance, indicating the same habitat variability across the cube. The mixing of ribotypes, as assessed by the spatial position of clonemates, corresponded to an overlapping of clones. Although the population probably was in a recession stage in the cube (10(3) agrobacteria g(-1)), a high genetic diversity was maintained. In two independent microsamples (500 microm in diameter) at the invasion stage, the average genetic diversity was at the same level as in the cube. Quantification of the microdiversity landscape will help to estimate the probability of encounter between bacteria under realistic natural conditions and to set appropriate sampling strategies for population genetic analysis.

An accessible method for implementing hierarchical models with spatio-temporal abundance data

USGS Publications Warehouse

Ross, Beth E.; Hooten, Melvin B.; Koons, David N.

2012-01-01

A common goal in ecology and wildlife management is to determine the causes of variation in population dynamics over long periods of time and across large spatial scales. Many assumptions must nevertheless be overcome to make appropriate inference about spatio-temporal variation in population dynamics, such as autocorrelation among data points, excess zeros, and observation error in count data. To address these issues, many scientists and statisticians have recommended the use of Bayesian hierarchical models. Unfortunately, hierarchical statistical models remain somewhat difficult to use because of the necessary quantitative background needed to implement them, or because of the computational demands of using Markov Chain Monte Carlo algorithms to estimate parameters. Fortunately, new tools have recently been developed that make it more feasible for wildlife biologists to fit sophisticated hierarchical Bayesian models (i.e., Integrated Nested Laplace Approximation, ‘INLA’). We present a case study using two important game species in North America, the lesser and greater scaup, to demonstrate how INLA can be used to estimate the parameters in a hierarchical model that decouples observation error from process variation, and accounts for unknown sources of excess zeros as well as spatial and temporal dependence in the data. Ultimately, our goal was to make unbiased inference about spatial variation in population trends over time.

Influence of substrate type on microbial community structure in vertical-flow constructed wetland treating polluted river water.

PubMed

Guan, Wei; Yin, Min; He, Tao; Xie, Shuguang

2015-10-01

Microorganisms attached on the surfaces of substrate materials in constructed wetland play crucial roles in the removal of organic and inorganic pollutants. However, the impact of substrate material on wetland microbial community structure remains unclear. Moreover, little is known about microbial community in constructed wetland purifying polluted surface water. In this study, Illumina high-throughput sequencing was applied to profile the spatial variation of microbial communities in three pilot-scale surface water constructed wetlands with different substrate materials (sand, zeolite, and gravel). Bacterial community diversity and structure showed remarkable spatial variation in both sand and zeolite wetland systems, but changed slightly in gravel wetland system. Bacterial community was found to be significantly influenced by wetland substrate type. A number of bacterial groups were detected in wetland systems, including Proteobacteria, Chloroflexi, Bacteroidetes, Acidobacteria, Cyanobacteria, Nitrospirae, Planctomycetes, Actinobacteria, Firmicutes, Chlorobi, Spirochaetae, Gemmatimonadetes, Deferribacteres, OP8, WS3, TA06, and OP3, while Proteobacteria (accounting for 29.1-62.3 %), mainly composed of Alpha-, Beta-, Gamma-, and Deltaproteobacteria, showed the dominance and might contribute to the effective reduction of organic pollutants. In addition, Nitrospira-like microorganisms were abundant in surface water constructed wetlands.

Multivariate inference of pathway activity in host immunity and response to therapeutics

PubMed Central

Goel, Gautam; Conway, Kara L.; Jaeger, Martin; Netea, Mihai G.; Xavier, Ramnik J.

2014-01-01

Developing a quantitative view of how biological pathways are regulated in response to environmental factors is central for understanding of disease phenotypes. We present a computational framework, named Multivariate Inference of Pathway Activity (MIPA), which quantifies degree of activity induced in a biological pathway by computing five distinct measures from transcriptomic profiles of its member genes. Statistical significance of inferred activity is examined using multiple independent self-contained tests followed by a competitive analysis. The method incorporates a new algorithm to identify a subset of genes that may regulate the extent of activity induced in a pathway. We present an in-depth evaluation of specificity, robustness, and reproducibility of our method. We benchmarked MIPA's false positive rate at less than 1%. Using transcriptomic profiles representing distinct physiological and disease states, we illustrate applicability of our method in (i) identifying gene–gene interactions in autophagy-dependent response to Salmonella infection, (ii) uncovering gene–environment interactions in host response to bacterial and viral pathogens and (iii) identifying driver genes and processes that contribute to wound healing and response to anti-TNFα therapy. We provide relevant experimental validation that corroborates the accuracy and advantage of our method. PMID:25147207

Measuring spatial variability in soil characteristics

DOEpatents

Hoskinson, Reed L.; Svoboda, John M.; Sawyer, J. Wayne; Hess, John R.; Hess, J. Richard

2002-01-01

The present invention provides systems and methods for measuring a load force associated with pulling a farm implement through soil that is used to generate a spatially variable map that represents the spatial variability of the physical characteristics of the soil. An instrumented hitch pin configured to measure a load force is provided that measures the load force generated by a farm implement when the farm implement is connected with a tractor and pulled through or across soil. Each time a load force is measured, a global positioning system identifies the location of the measurement. This data is stored and analyzed to generate a spatially variable map of the soil. This map is representative of the physical characteristics of the soil, which are inferred from the magnitude of the load force.

A spatially resolving x-ray crystal spectrometer for measurement of ion-temperature and rotation-velocity profiles on the Alcator C-Mod tokamak.

PubMed

Hill, K W; Bitter, M L; Scott, S D; Ince-Cushman, A; Reinke, M; Rice, J E; Beiersdorfer, P; Gu, M-F; Lee, S G; Broennimann, Ch; Eikenberry, E F

2008-10-01

A new spatially resolving x-ray crystal spectrometer capable of measuring continuous spatial profiles of high resolution spectra (lambda/d lambda>6000) of He-like and H-like Ar K alpha lines with good spatial (approximately 1 cm) and temporal (approximately 10 ms) resolutions has been installed on the Alcator C-Mod tokamak. Two spherically bent crystals image the spectra onto four two-dimensional Pilatus II pixel detectors. Tomographic inversion enables inference of local line emissivity, ion temperature (T(i)), and toroidal plasma rotation velocity (upsilon(phi)) from the line Doppler widths and shifts. The data analysis techniques, T(i) and upsilon(phi) profiles, analysis of fusion-neutron background, and predictions of performance on other tokamaks, including ITER, will be presented.

Geographic patterns of networks derived from extreme precipitation over the Indian subcontinent

NASA Astrophysics Data System (ADS)

Stolbova, Veronika; Bookhagen, Bodo; Marwan, Norbert; Kurths, Juergen

2014-05-01

Complex networks (CN) and event synchronization (ES) methods have been applied to study a number of climate phenomena such as Indian Summer Monsoon (ISM), South-American Monsoon, and African Monsoon. These methods proved to be powerful tools to infer interdependencies in climate dynamics between geographical sites, spatial structures, and key regions of the considered climate phenomenon. Here, we use these methods to study the spatial temporal variability of the extreme rainfall over the Indian subcontinent, in order to filter the data by coarse-graining the network, and to identify geographic patterns that are signature features (spatial signatures) of the ISM. We find four main geographic patterns of networks derived from extreme precipitation over the Indian subcontinent using up-to-date satellite-derived, and high temporal and spatial resolution rain-gauge interpolated daily rainfall datasets. In order to prove that our results are also relevant for other climatic variables like pressure and temperature, we use re-analysis data provided by the National Center for Environmental Prediction and National Center for Atmospheric Research (NCEP/NCAR). We find that two of the patterns revealed from the CN extreme rainfall analysis coincide with those obtained for the pressure and temperature fields, and all four above mentioned patterns can be explained by topography, winds, and monsoon circulation. CN and ES enable to select the most informative regions for the ISM, providing realistic description of the ISM dynamics with fewer data, and also help to infer geographic pattern that are spatial signatures of the ISM. These patterns deserve a special attention for the meteorologists and can be used as markers of the ISM variability.

Comparing spatial diversification and meta-population models in the Indo-Australian Archipelago

PubMed Central

Chalmandrier, Loïc; Albouy, Camille; Descombes, Patrice; Sandel, Brody; Faurby, Soren; Svenning, Jens-Christian; Zimmermann, Niklaus E.

2018-01-01

Reconstructing the processes that have shaped the emergence of biodiversity gradients is critical to understand the dynamics of diversification of life on Earth. Islands have traditionally been used as model systems to unravel the processes shaping biological diversity. MacArthur and Wilson's island biogeographic model predicts diversity to be based on dynamic interactions between colonization and extinction rates, while treating islands themselves as geologically static entities. The current spatial configuration of islands should influence meta-population dynamics, but long-term geological changes within archipelagos are also expected to have shaped island biodiversity, in part by driving diversification. Here, we compare two mechanistic models providing inferences on species richness at a biogeographic scale: a mechanistic spatial-temporal model of species diversification and a spatial meta-population model. While the meta-population model operates over a static landscape, the diversification model is driven by changes in the size and spatial configuration of islands through time. We compare the inferences of both models to floristic diversity patterns among land patches of the Indo-Australian Archipelago. Simulation results from the diversification model better matched observed diversity than a meta-population model constrained only by the contemporary landscape. The diversification model suggests that the dynamic re-positioning of islands promoting land disconnection and reconnection induced an accumulation of particularly high species diversity on Borneo, which is central within the island network. By contrast, the meta-population model predicts a higher diversity on the mainlands, which is less compatible with empirical data. Our analyses highlight that, by comparing models with contrasting assumptions, we can pinpoint the processes that are most compatible with extant biodiversity patterns. PMID:29657753

Comparing spatial diversification and meta-population models in the Indo-Australian Archipelago.

PubMed

Chalmandrier, Loïc; Albouy, Camille; Descombes, Patrice; Sandel, Brody; Faurby, Soren; Svenning, Jens-Christian; Zimmermann, Niklaus E; Pellissier, Loïc

2018-03-01

Reconstructing the processes that have shaped the emergence of biodiversity gradients is critical to understand the dynamics of diversification of life on Earth. Islands have traditionally been used as model systems to unravel the processes shaping biological diversity. MacArthur and Wilson's island biogeographic model predicts diversity to be based on dynamic interactions between colonization and extinction rates, while treating islands themselves as geologically static entities. The current spatial configuration of islands should influence meta-population dynamics, but long-term geological changes within archipelagos are also expected to have shaped island biodiversity, in part by driving diversification. Here, we compare two mechanistic models providing inferences on species richness at a biogeographic scale: a mechanistic spatial-temporal model of species diversification and a spatial meta-population model. While the meta-population model operates over a static landscape, the diversification model is driven by changes in the size and spatial configuration of islands through time. We compare the inferences of both models to floristic diversity patterns among land patches of the Indo-Australian Archipelago. Simulation results from the diversification model better matched observed diversity than a meta-population model constrained only by the contemporary landscape. The diversification model suggests that the dynamic re-positioning of islands promoting land disconnection and reconnection induced an accumulation of particularly high species diversity on Borneo, which is central within the island network. By contrast, the meta-population model predicts a higher diversity on the mainlands, which is less compatible with empirical data. Our analyses highlight that, by comparing models with contrasting assumptions, we can pinpoint the processes that are most compatible with extant biodiversity patterns.

Remote sensing of potential lunar resources. 2: High spatial resolution mapping of spectral reflectance ratios and implications for nearside mare TiO2 content`

NASA Technical Reports Server (NTRS)

Melendrez, David E.; Johnson, Jeffrey R.; Larson, Stephen M.; Singer, Robert B.

1994-01-01

High spatial resolution maps illustrating variations in spectral reflectance 400/560 nm ratio values have been generated for the following mare regions: (1) the border between southern Mare Serenitatis and northern Mare Tranquillitatis (including the MS-2 standard area and Apollo 17 landing site), (2) central Mare Tranquillitatis, (3) Oceanus Procellarum near Seleucus, and (4) southern Oceanus Procellarum and Flamsteed. We have also obtained 320-1000 nm reflectance spectra of several sites relative to MS-2 to facilitate scaling of the images and provide additional information on surface composition. Inferred TiO2 abundances for these mare regions have been determined using an empirical calibration which relates the weight percent TiO2 in mature mare regolith to the observed 400/560 nm ratio. Mare areas with high TiO2 abundances are probably rich in ilmenite (FeTiO3) a potential lunar resource. The highest potential TiO2 concentrations we have identified in the nearside maria occur in central Mare Tranquillitatis. Inferred TiO2 contents for these areas are greater than 9 wt% and are spatially consistent with the highest-TiO2 regions mapped previously at lower spatial resolution. We note that the morphology of surface units with high 400/560 nm ratio values increases in complexity at higher spatial resolutions. Comparisons have been made with previously published geologic maps, Lunar Orbiter IV, and ground-based images, and some possible morphologic correlatins have been found between our mapped 400/560 nm ratio values and volcanic landforms such as lava flows, mare domes, and collapse pits.

Density of founder cells affects spatial pattern formation and cooperation in Bacillus subtilis biofilms

PubMed Central

van Gestel, Jordi; Weissing, Franz J; Kuipers, Oscar P; Kovács, Ákos T

2014-01-01

In nature, most bacteria live in surface-attached sedentary communities known as biofilms. Biofilms are often studied with respect to bacterial interactions. Many cells inhabiting biofilms are assumed to express ‘cooperative traits', like the secretion of extracellular polysaccharides (EPS). These traits can enhance biofilm-related properties, such as stress resilience or colony expansion, while being costly to the cells that express them. In well-mixed populations cooperation is difficult to achieve, because non-cooperative individuals can reap the benefits of cooperation without having to pay the costs. The physical process of biofilm growth can, however, result in the spatial segregation of cooperative from non-cooperative individuals. This segregation can prevent non-cooperative cells from exploiting cooperative neighbors. Here we examine the interaction between spatial pattern formation and cooperation in Bacillus subtilis biofilms. We show, experimentally and by mathematical modeling, that the density of cells at the onset of biofilm growth affects pattern formation during biofilm growth. At low initial cell densities, co-cultured strains strongly segregate in space, whereas spatial segregation does not occur at high initial cell densities. As a consequence, EPS-producing cells have a competitive advantage over non-cooperative mutants when biofilms are initiated at a low density of founder cells, whereas EPS-deficient cells have an advantage at high cell densities. These results underline the importance of spatial pattern formation for competition among bacterial strains and the evolution of microbial cooperation. PMID:24694715

Density of founder cells affects spatial pattern formation and cooperation in Bacillus subtilis biofilms.

PubMed

van Gestel, Jordi; Weissing, Franz J; Kuipers, Oscar P; Kovács, Akos T

2014-10-01

In nature, most bacteria live in surface-attached sedentary communities known as biofilms. Biofilms are often studied with respect to bacterial interactions. Many cells inhabiting biofilms are assumed to express 'cooperative traits', like the secretion of extracellular polysaccharides (EPS). These traits can enhance biofilm-related properties, such as stress resilience or colony expansion, while being costly to the cells that express them. In well-mixed populations cooperation is difficult to achieve, because non-cooperative individuals can reap the benefits of cooperation without having to pay the costs. The physical process of biofilm growth can, however, result in the spatial segregation of cooperative from non-cooperative individuals. This segregation can prevent non-cooperative cells from exploiting cooperative neighbors. Here we examine the interaction between spatial pattern formation and cooperation in Bacillus subtilis biofilms. We show, experimentally and by mathematical modeling, that the density of cells at the onset of biofilm growth affects pattern formation during biofilm growth. At low initial cell densities, co-cultured strains strongly segregate in space, whereas spatial segregation does not occur at high initial cell densities. As a consequence, EPS-producing cells have a competitive advantage over non-cooperative mutants when biofilms are initiated at a low density of founder cells, whereas EPS-deficient cells have an advantage at high cell densities. These results underline the importance of spatial pattern formation for competition among bacterial strains and the evolution of microbial cooperation.

Simulations inform design of regional occupancy-based monitoring for a sparsely distributed, territorial species

Treesearch

Quresh S. Latif; Martha M. Ellis; Victoria A. Saab; Kim Mellen-McLean

2017-01-01

Sparsely distributed species attract conservation concern, but insufficient information on population trends challenges conservation and funding prioritization. Occupancy-based monitoring is attractive for these species, but appropriate sampling design and inference depend on particulars of the study system. We employed spatially explicit simulations to identify...

Bayesian analysis for inference of an emerging epidemic: citrus canker in urban landscapes

USDA-ARS?s Scientific Manuscript database

Outbreaks of infectious diseases require a rapid response from policy makers. The strength and efficacy of the responses depend upon available knowledge of the spatial and temporal parameters governing pathogen spread, affecting, amongst others, the predicted severity of the epidemic. Yet, when a ne...

FUNCTIONAL OVERLAP OF ROOT SYSTEMS IN AN OLD-GROWTH FOREST INFERRED FROM TRACER 15N UPTAKE

EPA Science Inventory

Belowground competition for nutrients and water is considered a key factor affecting spatial organization and productivity of individual stems within forest stands, yet there are few data describing the lateral extent and overlap of competing root systems. We quantified the func...

Reasoning About Relations

ERIC Educational Resources Information Center

Goodwin, Geoffrey P.; Johnson-Laird, P. N.

2005-01-01

Inferences about spatial, temporal, and other relations are ubiquitous. This article presents a novel model-based theory of such reasoning. The theory depends on 5 principles. (a) The structure of mental models is iconic as far as possible. (b) The logical consequences of relations emerge from models constructed from the meanings of the relations…

Inferring High-Resolution Individual’s Activity and Trip Purposes with the Fusion of Social Media, Land Use and Connected Vehicle Trajectories

DOT National Transportation Integrated Search

2017-11-30

Trip purpose is crucial to travel behavior modeling and travel demand estimation for transportation planning and investment decisions. However, the spatial-temporal complexity of human activities makes the prediction of trip purpose a challenging pro...

Inferring geographic isolation of wolverines in California using historical DNA

Treesearch

Michael K. Schwartz; Keith B. Aubry; Kevin S. McKelvey; Kristine L. Pilgrim; Jeffrey P. Copeland; John R. Squires; Robert M. Inman; Samantha M. Wisely; Leonard F. Ruggiero

2007-01-01

Delineating a species' geographic range using the spatial distribution of museum specimens or even contemporary detection-non-detection data can be difficult. This is particularly true at the periphery of a species range where species' distributions are often disjunct. Wolverines (Gulo gulo) are wide-ranging mammals with discontinuous and...

CONFRONTING THE MODIFIABLE AREAL UNIT PROBLEM FOR INFERENCE ON NITRATE IN REGIONAL SHALLOW GROUND WATER

EPA Science Inventory

This work addresses a potentially serious problem in synthesis of
spatially explicit data on ground water quality from wells, known to
geographers as the modifiable areal unit problem (MAUP). Investigators
are faced with choosing a level of aggregation appropriate to
...

Always look on both sides: Phylogenetic information conveyed by simple sequence repeat allele sequences

USDA-ARS?s Scientific Manuscript database

Simple sequence repeat (SSR) markers are widely used tools for inferences about genetic diversity, phylogeography and spatial genetic structure. Their applications assume that variation among alleles is essentially caused by an expansion or contraction of the number of repeats and that, accessorily,...

Space-Time Data fusion for Remote Sensing Applications

NASA Technical Reports Server (NTRS)

Braverman, Amy; Nguyen, H.; Cressie, N.

2011-01-01

NASA has been collecting massive amounts of remote sensing data about Earth's systems for more than a decade. Missions are selected to be complementary in quantities measured, retrieval techniques, and sampling characteristics, so these datasets are highly synergistic. To fully exploit this, a rigorous methodology for combining data with heterogeneous sampling characteristics is required. For scientific purposes, the methodology must also provide quantitative measures of uncertainty that propagate input-data uncertainty appropriately. We view this as a statistical inference problem. The true but notdirectly- observed quantities form a vector-valued field continuous in space and time. Our goal is to infer those true values or some function of them, and provide to uncertainty quantification for those inferences. We use a spatiotemporal statistical model that relates the unobserved quantities of interest at point-level to the spatially aggregated, observed data. We describe and illustrate our method using CO2 data from two NASA data sets.

The NIFTy way of Bayesian signal inference

NASA Astrophysics Data System (ADS)

Selig, Marco

2014-12-01

We introduce NIFTy, "Numerical Information Field Theory", a software package for the development of Bayesian signal inference algorithms that operate independently from any underlying spatial grid and its resolution. A large number of Bayesian and Maximum Entropy methods for 1D signal reconstruction, 2D imaging, as well as 3D tomography, appear formally similar, but one often finds individualized implementations that are neither flexible nor easily transferable. Signal inference in the framework of NIFTy can be done in an abstract way, such that algorithms, prototyped in 1D, can be applied to real world problems in higher-dimensional settings. NIFTy as a versatile library is applicable and already has been applied in 1D, 2D, 3D and spherical settings. A recent application is the D3PO algorithm targeting the non-trivial task of denoising, deconvolving, and decomposing photon observations in high energy astronomy.

Probabilistic measures of persistence and extinction in measles (meta)populations.

PubMed

Gunning, Christian E; Wearing, Helen J

2013-08-01

Persistence and extinction are fundamental processes in ecological systems that are difficult to accurately measure due to stochasticity and incomplete observation. Moreover, these processes operate on multiple scales, from individual populations to metapopulations. Here, we examine an extensive new data set of measles case reports and associated demographics in pre-vaccine era US cities, alongside a classic England & Wales data set. We first infer the per-population quasi-continuous distribution of log incidence. We then use stochastic, spatially implicit metapopulation models to explore the frequency of rescue events and apparent extinctions. We show that, unlike critical community size, the inferred distributions account for observational processes, allowing direct comparisons between metapopulations. The inferred distributions scale with population size. We use these scalings to estimate extinction boundary probabilities. We compare these predictions with measurements in individual populations and random aggregates of populations, highlighting the importance of medium-sized populations in metapopulation persistence. © 2013 John Wiley & Sons Ltd/CNRS.

Moment inference from tomograms

USGS Publications Warehouse

Day-Lewis, F. D.; Chen, Y.; Singha, K.

2007-01-01

Time-lapse geophysical tomography can provide valuable qualitative insights into hydrologic transport phenomena associated with aquifer dynamics, tracer experiments, and engineered remediation. Increasingly, tomograms are used to infer the spatial and/or temporal moments of solute plumes; these moments provide quantitative information about transport processes (e.g., advection, dispersion, and rate-limited mass transfer) and controlling parameters (e.g., permeability, dispersivity, and rate coefficients). The reliability of moments calculated from tomograms is, however, poorly understood because classic approaches to image appraisal (e.g., the model resolution matrix) are not directly applicable to moment inference. Here, we present a semi-analytical approach to construct a moment resolution matrix based on (1) the classic model resolution matrix and (2) image reconstruction from orthogonal moments. Numerical results for radar and electrical-resistivity imaging of solute plumes demonstrate that moment values calculated from tomograms depend strongly on plume location within the tomogram, survey geometry, regularization criteria, and measurement error. Copyright 2007 by the American Geophysical Union.

Moment inference from tomograms

USGS Publications Warehouse

Day-Lewis, Frederick D.; Chen, Yongping; Singha, Kamini

2007-01-01

Time-lapse geophysical tomography can provide valuable qualitative insights into hydrologic transport phenomena associated with aquifer dynamics, tracer experiments, and engineered remediation. Increasingly, tomograms are used to infer the spatial and/or temporal moments of solute plumes; these moments provide quantitative information about transport processes (e.g., advection, dispersion, and rate-limited mass transfer) and controlling parameters (e.g., permeability, dispersivity, and rate coefficients). The reliability of moments calculated from tomograms is, however, poorly understood because classic approaches to image appraisal (e.g., the model resolution matrix) are not directly applicable to moment inference. Here, we present a semi-analytical approach to construct a moment resolution matrix based on (1) the classic model resolution matrix and (2) image reconstruction from orthogonal moments. Numerical results for radar and electrical-resistivity imaging of solute plumes demonstrate that moment values calculated from tomograms depend strongly on plume location within the tomogram, survey geometry, regularization criteria, and measurement error.

Control of bacterial adhesion and growth on honeycomb-like patterned surfaces.

PubMed

Yang, Meng; Ding, Yonghui; Ge, Xiang; Leng, Yang

2015-11-01

It is a great challenge to construct a persistent bacteria-resistant surface even though it has been demonstrated that several surface features might be used to control bacterial behavior, including surface topography. In this study, we develop micro-scale honeycomb-like patterns of different sizes (0.5-10 μm) as well as a flat area as the control on a single platform to evaluate the bacterial adhesion and growth. Bacteria strains, Escherichia coli and Staphylococcus aureus with two distinct shapes (rod and sphere) are cultured on the platforms, with the patterned surface-up and surface-down in the culture medium. The results demonstrate that the 1 μm patterns remarkably reduce bacterial adhesion and growth while suppressing bacterial colonization when compared to the flat surface. The selective adhesion of the bacterial cells on the patterns reveals that the bacterial adhesion is cooperatively mediated by maximizing the cell-substrate contact area and minimizing the cell deformation, from a thermodynamic point of view. Moreover, study of bacterial behaviors on the surface-up vs. surface-down samples shows that gravity does not apparently affect the spatial distribution of the adherent cells although it indeed facilitates bacterial adhesion. Furthermore, the experimental results suggest that two major factors, i.e. the availability of energetically favorable adhesion sites and the physical confinements, contribute to the anti-bacterial nature of the honeycomb-like patterns. Copyright © 2015 Elsevier B.V. All rights reserved.

Soil bacterial diversity patterns and drivers along an elevational gradient on Shennongjia Mountain, China

PubMed Central

Zhang, Yuguang; Cong, Jing; Lu, Hui; Li, Guangliang; Xue, Yadong; Deng, Ye; Li, Hui; Zhou, Jizhong; Li, Diqiang

2015-01-01

Understanding biological diversity elevational pattern and the driver factors are indispensable to develop the ecological theories. Elevational gradient may minimize the impact of environmental factors and is the ideal places to study soil microbial elevational patterns. In this study, we selected four typical vegetation types from 1000 to 2800 m above the sea level on the northern slope of Shennongjia Mountain in central China, and analysed the soil bacterial community composition, elevational patterns and the relationship between soil bacterial diversity and environmental factors by using the 16S rRNA Illumina sequencing and multivariate statistical analysis. The results revealed that the dominant bacterial phyla were Acidobacteria, Actinobacteria, Alphaproteobacteria, Betaproteobacteria, Gammaproteobacteria and Verrucomicrobia, which accounted for over 75% of the bacterial sequences obtained from tested samples, and the soil bacterial operational taxonomic unit (OTU) richness was a significant monotonous decreasing (P < 0.01) trend with the elevational increasing. The similarity of soil bacterial population composition decreased significantly (P < 0.01) with elevational distance increased as measured by the Jaccard and Bray–Curtis index. Canonical correspondence analysis and Mantel test analysis indicated that plant diversity and soil pH were significantly correlated (P < 0.01) with the soil bacterial community. Therefore, the soil bacterial diversity on Shennongjia Mountain had a significant and different elevational pattern, and plant diversity and soil pH may be the key factors in shaping the soil bacterial spatial pattern. PMID:26032124

Z ring as executor of bacterial cell division.

PubMed

Dajkovic, Alex; Lutkenhaus, Joe

2006-01-01

It has become apparent that bacteria possess ancestors of the major eukaryotic cytoskeletal proteins. FtsZ, the ancestral homologue of tubulin, assembles into a cytoskeletal structure associated with cell division, designated the Z ring. Formation of the Z ring represents a major point of both spatial and temporal regulation of cell division. Here we discuss findings concerning the structure and the formation of the ring as well as its spatial and temporal regulation.

Network inference from multimodal data: A review of approaches from infectious disease transmission.

PubMed

Ray, Bisakha; Ghedin, Elodie; Chunara, Rumi

2016-12-01

Networks inference problems are commonly found in multiple biomedical subfields such as genomics, metagenomics, neuroscience, and epidemiology. Networks are useful for representing a wide range of complex interactions ranging from those between molecular biomarkers, neurons, and microbial communities, to those found in human or animal populations. Recent technological advances have resulted in an increasing amount of healthcare data in multiple modalities, increasing the preponderance of network inference problems. Multi-domain data can now be used to improve the robustness and reliability of recovered networks from unimodal data. For infectious diseases in particular, there is a body of knowledge that has been focused on combining multiple pieces of linked information. Combining or analyzing disparate modalities in concert has demonstrated greater insight into disease transmission than could be obtained from any single modality in isolation. This has been particularly helpful in understanding incidence and transmission at early stages of infections that have pandemic potential. Novel pieces of linked information in the form of spatial, temporal, and other covariates including high-throughput sequence data, clinical visits, social network information, pharmaceutical prescriptions, and clinical symptoms (reported as free-text data) also encourage further investigation of these methods. The purpose of this review is to provide an in-depth analysis of multimodal infectious disease transmission network inference methods with a specific focus on Bayesian inference. We focus on analytical Bayesian inference-based methods as this enables recovering multiple parameters simultaneously, for example, not just the disease transmission network, but also parameters of epidemic dynamics. Our review studies their assumptions, key inference parameters and limitations, and ultimately provides insights about improving future network inference methods in multiple applications. Copyright © 2016 Elsevier Inc. All rights reserved.

Engineering the Bacterial Microcompartment Domain for Molecular Scaffolding Applications

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

Young, Eric J.; Burton, Rodney; Mahalik, Jyoti P.

As synthetic biology advances the intricacy of engineered biological systems, the importance of spatial organization within the cellular environment must not be marginalized. Increasingly, biological engineers are investigating means to control spatial organization within the cell, mimicking strategies used by natural pathways to increase flux and reduce cross-talk. A modular platform for constructing a diverse set of defined, programmable architectures would greatly assist in improving yields from introduced metabolic pathways and increasing insulation of other heterologous systems. Here, we review recent research on the shell proteins of bacterial microcompartments and discuss their potential application as “building blocks” for a rangemore » of customized intracellular scaffolds. As a result, we summarize the state of knowledge on the self-assembly of BMC shell proteins and discuss future avenues of research that will be important to realize the potential of BMC shell proteins as predictively assembling and programmable biological materials for bioengineering.« less

Engineering the Bacterial Microcompartment Domain for Molecular Scaffolding Applications

DOE PAGES

Young, Eric J.; Burton, Rodney; Mahalik, Jyoti P.; ...

2017-07-31

As synthetic biology advances the intricacy of engineered biological systems, the importance of spatial organization within the cellular environment must not be marginalized. Increasingly, biological engineers are investigating means to control spatial organization within the cell, mimicking strategies used by natural pathways to increase flux and reduce cross-talk. A modular platform for constructing a diverse set of defined, programmable architectures would greatly assist in improving yields from introduced metabolic pathways and increasing insulation of other heterologous systems. Here, we review recent research on the shell proteins of bacterial microcompartments and discuss their potential application as “building blocks” for a rangemore » of customized intracellular scaffolds. As a result, we summarize the state of knowledge on the self-assembly of BMC shell proteins and discuss future avenues of research that will be important to realize the potential of BMC shell proteins as predictively assembling and programmable biological materials for bioengineering.« less

Engineering the Bacterial Microcompartment Domain for Molecular Scaffolding Applications

PubMed Central

Young, Eric J.; Burton, Rodney; Mahalik, Jyoti P.; Sumpter, Bobby G.; Fuentes-Cabrera, Miguel; Kerfeld, Cheryl A.; Ducat, Daniel C.

2017-01-01

As synthetic biology advances the intricacy of engineered biological systems, the importance of spatial organization within the cellular environment must not be marginalized. Increasingly, biological engineers are investigating means to control spatial organization within the cell, mimicking strategies used by natural pathways to increase flux and reduce cross-talk. A modular platform for constructing a diverse set of defined, programmable architectures would greatly assist in improving yields from introduced metabolic pathways and increasing insulation of other heterologous systems. Here, we review recent research on the shell proteins of bacterial microcompartments and discuss their potential application as “building blocks” for a range of customized intracellular scaffolds. We summarize the state of knowledge on the self-assembly of BMC shell proteins and discuss future avenues of research that will be important to realize the potential of BMC shell proteins as predictively assembling and programmable biological materials for bioengineering. PMID:28824573

A Straightforward Approach for 3D Bacterial Printing

PubMed Central

2017-01-01

Sustainable and personally tailored materials production is an emerging challenge to society. Living organisms can produce and pattern an extraordinarily wide range of different molecules in a sustainable way. These natural systems offer an abundant source of inspiration for the development of new environmentally friendly materials production techniques. In this paper, we describe the first steps toward the 3-dimensional printing of bacterial cultures for materials production and patterning. This methodology combines the capability of bacteria to form new materials with the reproducibility and tailored approach of 3D printing systems. For this purpose, a commercial 3D printer was modified for bacterial systems, and new alginate-based bioink chemistry was developed. Printing temperature, printhead speed, and bioink extrusion rate were all adapted and customized to maximize bacterial health and spatial resolution of printed structures. Our combination of 3D printing technology with biological systems enables a sustainable approach for the production of numerous new materials. PMID:28225616

A Straightforward Approach for 3D Bacterial Printing.

PubMed

Lehner, Benjamin A E; Schmieden, Dominik T; Meyer, Anne S

2017-07-21

Sustainable and personally tailored materials production is an emerging challenge to society. Living organisms can produce and pattern an extraordinarily wide range of different molecules in a sustainable way. These natural systems offer an abundant source of inspiration for the development of new environmentally friendly materials production techniques. In this paper, we describe the first steps toward the 3-dimensional printing of bacterial cultures for materials production and patterning. This methodology combines the capability of bacteria to form new materials with the reproducibility and tailored approach of 3D printing systems. For this purpose, a commercial 3D printer was modified for bacterial systems, and new alginate-based bioink chemistry was developed. Printing temperature, printhead speed, and bioink extrusion rate were all adapted and customized to maximize bacterial health and spatial resolution of printed structures. Our combination of 3D printing technology with biological systems enables a sustainable approach for the production of numerous new materials.

Bacterial cell identification in differential interference contrast microscopy images.

PubMed

Obara, Boguslaw; Roberts, Mark A J; Armitage, Judith P; Grau, Vicente

2013-04-23

Microscopy image segmentation lays the foundation for shape analysis, motion tracking, and classification of biological objects. Despite its importance, automated segmentation remains challenging for several widely used non-fluorescence, interference-based microscopy imaging modalities. For example in differential interference contrast microscopy which plays an important role in modern bacterial cell biology. Therefore, new revolutions in the field require the development of tools, technologies and work-flows to extract and exploit information from interference-based imaging data so as to achieve new fundamental biological insights and understanding. We have developed and evaluated a high-throughput image analysis and processing approach to detect and characterize bacterial cells and chemotaxis proteins. Its performance was evaluated using differential interference contrast and fluorescence microscopy images of Rhodobacter sphaeroides. Results demonstrate that the proposed approach provides a fast and robust method for detection and analysis of spatial relationship between bacterial cells and their chemotaxis proteins.

Bacterial Contamination of Boar Semen and its Relationship to Sperm Quality Preserved in Commercial Extender Containing Gentamicin Sulfate.

PubMed

Gączarzewicz, D; Udała, J; Piasecka, M; Błaszczyk, B; Stankiewicz, T

2016-09-01

This study was designed to determine the degree and type of bacterial contamination in boar semen (79 ejaculates from Large White and Landrace boars) and its consequences for sperm quality during storage (27 extended semen samples, 16°C for five days) under practical conditions of artificial insemination (AI). The results revealed the presence of aerobic bacteria in 99% of the ejaculates (from 80 to 370 ×106 colony-forming units/mL). Most of the ejaculates contained two or three bacterial contaminants, while the Staphylococcus, Streptococcus, and Pseudomonas bacterial genera were most frequently isolated. Also detected were Enterobacter spp., Bacillus spp., Proteus spp., Escherichia coli, P. fluorescens, and P. aeruginosa. In general, the growth of certain bacterial types isolated prior to semen processing (Enterobacter spp., E. coli, P. fluorescens, and P. aeruginosa) was not discovered on different days of storage, but fluctuations (with a tendency towards increases) were found in the frequencies of Bacillus spp., Pseudomonas spp., and Staphylococcus spp. isolates up to the end of storage. Semen preserved for five days exhibited decreases in sperm motility and increases in the average number of total aerobic bacteria; this was associated with sperm agglutination, plasma membrane disruption, and acrosome damage. We inferred that, due to the different degrees and types of bacterial contaminants in the boar ejaculates, the inhibitory activity of some antimicrobial agents used in swine extenders (such as gentamicin sulfate) may be limited. Because such agents can contribute to the overgrowth of certain aerobic bacteria and a reduction in the quality of stored semen, procedures with high standards of hygiene and microbiological control should be used when processing boar semen.

Spatial and temporal distributions of surface mass balance between Concordia and Vostok stations, Antarctica, from combined radar and ice core data: first results and detailed error analysis

NASA Astrophysics Data System (ADS)

Le Meur, Emmanuel; Magand, Olivier; Arnaud, Laurent; Fily, Michel; Frezzotti, Massimo; Cavitte, Marie; Mulvaney, Robert; Urbini, Stefano

2018-05-01

Results from ground-penetrating radar (GPR) measurements and shallow ice cores carried out during a scientific traverse between Dome Concordia (DC) and Vostok stations are presented in order to infer both spatial and temporal characteristics of snow accumulation over the East Antarctic Plateau. Spatially continuous accumulation rates along the traverse are computed from the identification of three equally spaced radar reflections spanning about the last 600 years. Accurate dating of these internal reflection horizons (IRHs) is obtained from a depth-age relationship derived from volcanic horizons and bomb testing fallouts on a DC ice core and shows a very good consistency when tested against extra ice cores drilled along the radar profile. Accumulation rates are then inferred by accounting for density profiles down to each IRH. For the latter purpose, a careful error analysis showed that using a single and more accurate density profile along a DC core provided more reliable results than trying to include the potential spatial variability in density from extra (but less accurate) ice cores distributed along the profile. The most striking feature is an accumulation pattern that remains constant through time with persistent gradients such as a marked decrease from 26 mm w.e. yr-1 at DC to 20 mm w.e. yr-1 at the south-west end of the profile over the last 234 years on average (with a similar decrease from 25 to 19 mm w.e. yr-1 over the last 592 years). As for the time dependency, despite an overall consistency with similar measurements carried out along the main East Antarctic divides, interpreting possible trends remains difficult. Indeed, error bars in our measurements are still too large to unambiguously infer an apparent time increase in accumulation rate. For the proposed absolute values, maximum margins of error are in the range 4 mm w.e. yr-1 (last 234 years) to 2 mm w.e. yr-1 (last 592 years), a decrease with depth mainly resulting from the time-averaging when computing accumulation rates.

Going local: technologies for exploring bacterial microenvironments

PubMed Central

Wessel, Aimee K.; Hmelo, Laura; Parsek, Matthew R.; Whiteley, Marvin

2014-01-01

Microorganisms lead social lives and use coordinated chemical and physical interactions to establish complex communities. Mechanistic insights into these interactions have revealed that there are remarkably intricate systems for coordinating microbial behaviour, but little is known about how these interactions proceed in the spatially organized communities that are found in nature. This Review describes the technologies available for spatially organizing small microbial communities and the analytical methods for characterizing the chemical environment surrounding these communities. Together, these complementary technologies have provided novel insights into the impact of spatial organization on both microbial behaviour and the development of phenotypic heterogeneity within microbial communities. PMID:23588251

Horizontal Temperature Variability in the Stratosphere: Global Variations Inferred from CRISTA Data

NASA Technical Reports Server (NTRS)

Eidmann, G.; Offermann, D.; Jarisch, M.; Preusse, P.; Eckermann, S. D.; Schmidlin, F. J.

2001-01-01

In two separate orbital campaigns (November, 1994 and August, 1997), the Cryogenic Infrared Spectrometers and Telescopes for the Atmosphere (CRISTA) instrument acquired global stratospheric data of high accuracy and high spatial resolution. The standard limb-scanned CRISTA measurements resolved atmospheric spatial structures with vertical dimensions greater than or equal to 1.5 - 2 km and horizontal dimensions is greater than or equal to 100 - 200 km. A fluctuation analysis of horizontal temperature distributions derived from these data is presented. This method is somewhat complementary to conventional power-spectral analysis techniques.

Terrain classification in navigation of an autonomous mobile robot

NASA Astrophysics Data System (ADS)

Dodds, David R.

1991-03-01

In this paper we describe a method of path planning that integrates terrain classification (by means of fractals) the certainty grid method of spatial representation Kehtarnavaz Griswold collision-zones Dubois Prade fuzzy temporal and spatial knowledge and non-point sized qualitative navigational planning. An initially planned (" end-to-end" ) path is piece-wise modified to accommodate known and inferred moving obstacles and includes attention to time-varying multiple subgoals which may influence a section of path at a time after the robot has begun traversing that planned path.

Bacterial Artificial Chromosome Clones of Viruses Comprising the Towne Cytomegalovirus Vaccine

PubMed Central

Cui, Xiaohong; Adler, Stuart P.; Davison, Andrew J.; Smith, Larry; Habib, EL-Sayed E.; McVoy, Michael A.

2012-01-01

Bacterial artificial chromosome (BAC) clones have proven invaluable for genetic manipulation of herpesvirus genomes. BAC cloning can also be useful for capturing representative genomes that comprise a viral stock or mixture. The Towne live attenuated cytomegalovirus vaccine was developed in the 1970s by serial passage in cultured fibroblasts. Although its safety, immunogenicity, and efficacy have been evaluated in nearly a thousand human subjects, the vaccine itself has been little studied. Instead, genetic composition and in vitro growth properties have been inferred from studies of laboratory stocks that may not always accurately represent the viruses that comprise the vaccine. Here we describe the use of BAC cloning to define the genotypic and phenotypic properties of viruses from the Towne vaccine. Given the extensive safety history of the Towne vaccine, these BACs provide a logical starting point for the development of next-generation rationally engineered cytomegalovirus vaccines. PMID:22187535

Nitric oxide prevents a pathogen permissive granulocytic inflammation during tuberculosis

PubMed Central

Mishra, Bibhuti B.; Lovewell, Rustin R.; Olive, Andrew J; Zhang, Guoliang; Wang, Wenfei; Eugenin, Eliseo; Smith, Clare M; Yao, Jia Phuah; Long, Jarukit E; Dubuke, Michelle L; Palace, Samantha G.; Goguen, Jon D.; Baker, Richard E.; Nambi, Subhalaxmi; Mishra, Rabinarayan; Booty, Matthew G; Baer, Christina E.; Shaffer, Scott A; Dartois, Veronique; McCormick, Beth; Chen, Xinchun; Sassetti, Christopher M.

2017-01-01

Nitric oxide (NO) contributes to protection from tuberculosis (TB). It is generally assumed that this protection is due to direct inhibition of Mycobacterium tuberculosis (Mtb) growth, which prevents subsequent pathological inflammation. In contrast, we report NO primarily protects mice by repressing an interleukin-1 and 12/15-lipoxygenase dependent neutrophil recruitment cascade that promotes bacterial replication. Using Mtb mutants as indicators of the pathogen's environment, we inferred that granulocytic inflammation generates a nutrient-replete niche that supports Mtb growth. Parallel clinical studies indicate that a similar inflammatory pathway promotes TB in patients. The human 12/15 lipoxygenase ortholog, ALOX12, is expressed in cavitary TB lesions, the abundance of its products correlate with the number of airway neutrophils and bacterial burden, and a genetic polymorphism that increases ALOX12 expression is associated with TB risk. These data suggest that Mtb exploits neutrophilic inflammation to preferentially replicate at sites of tissue damage that promote contagion. PMID:28504669

Nitric oxide prevents a pathogen-permissive granulocytic inflammation during tuberculosis.

PubMed

Mishra, Bibhuti B; Lovewell, Rustin R; Olive, Andrew J; Zhang, Guoliang; Wang, Wenfei; Eugenin, Eliseo; Smith, Clare M; Phuah, Jia Yao; Long, Jarukit E; Dubuke, Michelle L; Palace, Samantha G; Goguen, Jon D; Baker, Richard E; Nambi, Subhalaxmi; Mishra, Rabinarayan; Booty, Matthew G; Baer, Christina E; Shaffer, Scott A; Dartois, Veronique; McCormick, Beth A; Chen, Xinchun; Sassetti, Christopher M

2017-05-15

Nitric oxide contributes to protection from tuberculosis. It is generally assumed that this protection is due to direct inhibition of Mycobacterium tuberculosis growth, which prevents subsequent pathological inflammation. In contrast, we report that nitric oxide primarily protects mice by repressing an interleukin-1- and 12/15-lipoxygenase-dependent neutrophil recruitment cascade that promotes bacterial replication. Using M. tuberculosis mutants as indicators of the pathogen's environment, we inferred that granulocytic inflammation generates a nutrient-replete niche that supports M. tuberculosis growth. Parallel clinical studies indicate that a similar inflammatory pathway promotes tuberculosis in patients. The human 12/15-lipoxygenase orthologue, ALOX12, is expressed in cavitary tuberculosis lesions; the abundance of its products correlates with the number of airway neutrophils and bacterial burden and a genetic polymorphism that increases ALOX12 expression is associated with tuberculosis risk. These data suggest that M. tuberculosis exploits neutrophilic inflammation to preferentially replicate at sites of tissue damage that promote contagion.

Bacterial artificial chromosome clones of viruses comprising the towne cytomegalovirus vaccine.

PubMed

Cui, Xiaohong; Adler, Stuart P; Davison, Andrew J; Smith, Larry; Habib, El-Sayed E; McVoy, Michael A

2012-01-01

Bacterial artificial chromosome (BAC) clones have proven invaluable for genetic manipulation of herpesvirus genomes. BAC cloning can also be useful for capturing representative genomes that comprise a viral stock or mixture. The Towne live attenuated cytomegalovirus vaccine was developed in the 1970s by serial passage in cultured fibroblasts. Although its safety, immunogenicity, and efficacy have been evaluated in nearly a thousand human subjects, the vaccine itself has been little studied. Instead, genetic composition and in vitro growth properties have been inferred from studies of laboratory stocks that may not always accurately represent the viruses that comprise the vaccine. Here we describe the use of BAC cloning to define the genotypic and phenotypic properties of viruses from the Towne vaccine. Given the extensive safety history of the Towne vaccine, these BACs provide a logical starting point for the development of next-generation rationally engineered cytomegalovirus vaccines.

Oxygen and iron isotope studies of magnetite produced by magnetotactic bacteria

USGS Publications Warehouse

Mandernack, K.W.; Bazylinski, D.A.; Shanks, Wayne C.; Bullen, T.D.

1999-01-01

A series of carefully controlled laboratory studies was carried out to investigate oxygen and iron isotope fractionation during the intracellular production of magnetite (Fe3O4) by two different species of magnetotactic bacteria at temperatures between 4??and 35??C under microaerobic and anaerobic conditions. No detectable fractionation of iron isotopes in the bacterial magnetites was observed. However, oxygen isotope measurements indicated a temperature-dependent fractionation for Fe3O4 and water that is consistent with that observed for Fe3O4 produced extracellularly by thermophilic Fe3+-reducing bacteria. These results contrast with established fractionation curves estimated from either high-temperature experiments or theoretical calculations. With the fractionation curve established in this report, oxygen-18 isotope values of bacterial Fe3O4 may be useful in paleoenvironmental studies for determining the oxygen-18 isotope values of formation waters and for inferring paleotemperatures.

Rapid, High-Throughput Tracking of Bacterial Motility in 3D via Phase-Contrast Holographic Video Microscopy

PubMed Central

Cheong, Fook Chiong; Wong, Chui Ching; Gao, YunFeng; Nai, Mui Hoon; Cui, Yidan; Park, Sungsu; Kenney, Linda J.; Lim, Chwee Teck

2015-01-01

Tracking fast-swimming bacteria in three dimensions can be extremely challenging with current optical techniques and a microscopic approach that can rapidly acquire volumetric information is required. Here, we introduce phase-contrast holographic video microscopy as a solution for the simultaneous tracking of multiple fast moving cells in three dimensions. This technique uses interference patterns formed between the scattered and the incident field to infer the three-dimensional (3D) position and size of bacteria. Using this optical approach, motility dynamics of multiple bacteria in three dimensions, such as speed and turn angles, can be obtained within minutes. We demonstrated the feasibility of this method by effectively tracking multiple bacteria species, including Escherichia coli, Agrobacterium tumefaciens, and Pseudomonas aeruginosa. In addition, we combined our fast 3D imaging technique with a microfluidic device to present an example of a drug/chemical assay to study effects on bacterial motility. PMID:25762336

Inferences about landbird abundance from count data: recent advances and future directions

USGS Publications Warehouse

Nichols, J.D.; Thomas, L.; Conn, P.B.; Thomson, David L.; Cooch, Evan G.; Conroy, Michael J.

2009-01-01

We summarize results of a November 2006 workshop dealing with recent research on the estimation of landbird abundance from count data. Our conceptual framework includes a decomposition of the probability of detecting a bird potentially exposed to sampling efforts into four separate probabilities. Primary inference methods are described and include distance sampling, multiple observers, time of detection, and repeated counts. The detection parameters estimated by these different approaches differ, leading to different interpretations of resulting estimates of density and abundance. Simultaneous use of combinations of these different inference approaches can not only lead to increased precision but also provides the ability to decompose components of the detection process. Recent efforts to test the efficacy of these different approaches using natural systems and a new bird radio test system provide sobering conclusions about the ability of observers to detect and localize birds in auditory surveys. Recent research is reported on efforts to deal with such potential sources of error as bird misclassification, measurement error, and density gradients. Methods for inference about spatial and temporal variation in avian abundance are outlined. Discussion topics include opinions about the need to estimate detection probability when drawing inference about avian abundance, methodological recommendations based on the current state of knowledge and suggestions for future research.

Radar attenuation and temperature within the Greenland Ice Sheet

USGS Publications Warehouse

MacGregor, Joseph A; Li, Jilu; Paden, John D; Catania, Ginny A; Clow, Gary D.; Fahnestock, Mark A; Gogineni, Prasad S.; Grimm, Robert E.; Morlighem, Mathieu; Nandi, Soumyaroop; Seroussi, Helene; Stillman, David E

2015-01-01

The flow of ice is temperature-dependent, but direct measurements of englacial temperature are sparse. The dielectric attenuation of radio waves through ice is also temperature-dependent, and radar sounding of ice sheets is sensitive to this attenuation. Here we estimate depth-averaged radar-attenuation rates within the Greenland Ice Sheet from airborne radar-sounding data and its associated radiostratigraphy. Using existing empirical relationships between temperature, chemistry, and radar attenuation, we then infer the depth-averaged englacial temperature. The dated radiostratigraphy permits a correction for the confounding effect of spatially varying ice chemistry. Where radar transects intersect boreholes, radar-inferred temperature is consistently higher than that measured directly. We attribute this discrepancy to the poorly recognized frequency dependence of the radar-attenuation rate and correct for this effect empirically, resulting in a robust relationship between radar-inferred and borehole-measured depth-averaged temperature. Radar-inferred englacial temperature is often lower than modern surface temperature and that of a steady state ice-sheet model, particularly in southern Greenland. This pattern suggests that past changes in surface boundary conditions (temperature and accumulation rate) affect the ice sheet's present temperature structure over a much larger area than previously recognized. This radar-inferred temperature structure provides a new constraint for thermomechanical models of the Greenland Ice Sheet.

A phylogenetic perspective on species diversity, β-diversity and biogeography for the microbial world.

PubMed

Barberán, Albert; Casamayor, Emilio O

2014-12-01

There is an increasing interest to combine phylogenetic data with distributional and ecological records to assess how natural communities arrange under an evolutionary perspective. In the microbial world, there is also a need to go beyond the problematic species definition to deeply explore ecological patterns using genetic data. We explored links between evolution/phylogeny and community ecology using bacterial 16S rRNA gene information from a high-altitude lakes district data set. We described phylogenetic community composition, spatial distribution, and β-diversity and biogeographical patterns applying evolutionary relatedness without relying on any particular operational taxonomic unit definition. High-altitude lakes districts usually contain a large mosaic of highly diverse small water bodies and conform a fine biogeographical model of spatially close but environmentally heterogeneous ecosystems. We sampled 18 lakes in the Pyrenees with a selection criteria focused on capturing the maximum environmental variation within the smallest geographical area. The results showed highly diverse communities nonrandomly distributed with phylogenetic β-diversity patterns mainly shaped by the environment and not by the spatial distance. Community similarity based on both bacterial taxonomic composition and phylogenetic β-diversity shared similar patterns and was primarily structured by similar environmental drivers. We observed a positive relationship between lake area and phylogenetic diversity with a slope consistent with highly dispersive planktonic organisms. The phylogenetic approach incorporated patterns of common ancestry into bacterial community analysis and emerged as a very convenient analytical tool for direct inter- and intrabiome biodiversity comparisons and sorting out microbial habitats with potential application in conservation studies. © 2014 John Wiley & Sons Ltd.

Coastal Bacterioplankton Community Dynamics in Response to a Natural Disturbance

PubMed Central

Rappé, Michael S.

2013-01-01

In order to characterize how disturbances to microbial communities are propagated over temporal and spatial scales in aquatic environments, the dynamics of bacterial assemblages throughout a subtropical coastal embayment were investigated via SSU rRNA gene analyses over an 8-month period, which encompassed a large storm event. During non-perturbed conditions, sampling sites clustered into three groups based on their microbial community composition: an offshore oceanic group, a freshwater group, and a distinct and persistent coastal group. Significant differences in measured environmental parameters or in the bacterial community due to the storm event were found only within the coastal cluster of sampling sites, and only at 5 of 12 locations; three of these sites showed a significant response in both environmental and bacterial community characteristics. These responses were most pronounced at sites close to the shoreline. During the storm event, otherwise common bacterioplankton community members such as marine Synechococcus sp. and members of the SAR11 clade of Alphaproteobacteria decreased in relative abundance in the affected coastal zone, whereas several lineages of Gammaproteobacteria, Betaproteobacteria, and members of the Roseobacter clade of Alphaproteobacteria increased. The complex spatial patterns in both environmental conditions and microbial community structure related to freshwater runoff and wind convection during the perturbation event leads us to conclude that spatial heterogeneity was an important factor influencing both the dynamics and the resistance of the bacterioplankton communities to disturbances throughout this complex subtropical coastal system. This heterogeneity may play a role in facilitating a rapid rebound of regions harboring distinctly coastal bacterioplankton communities to their pre-disturbed taxonomic composition. PMID:23409156

Historical distribution and host-vector diversity of Francisella tularensis, the causative agent of tularemia, in Ukraine.

PubMed

Hightower, Jake; Kracalik, Ian T; Vydayko, Nataliya; Goodin, Douglas; Glass, Gregory; Blackburn, Jason K

2014-10-16

Francisella tularensis, the causative agent of tularemia, is a zoonotic agent that remains across much of the northern hemisphere, where it exists in enzootic cycles. In Ukraine, tularemia has a long history that suggests a need for sustained surveillance in natural foci. To better characterize the host-vector diversity and spatial distribution of tularemia, we analyzed historical data from field collections carried out from 1941 to 2008. We analyzed the spatial-temporal distribution of bacterial isolates collected from field samples. Isolates were characterized by source and dominant land cover type. To identify environmental persistence and spatial variation in the source of isolation, we used the space-time permutation and multinomial models in SaTScan. A total of 3,086 positive isolates were taken from 1,084 geographic locations. Isolation of F. tularensis was more frequent among arthropods [n = 2,045 (66.3%)] followed by mammals [n = 619 (20.1%)], water [n = 393 (12.7%)], and farm produce [n = 29 (0.94%)], respectively. Four areas of persistent bacterial isolation were identified. Water and farm produce as sources of bacterial isolation were clustered. Our findings confirm the presence of long-standing natural foci of F. tularensis in Ukraine. Given the history of tularemia as well as its environmental persistence there exists a possibility of (re)emergence in human populations. Heterogeneity in the distribution of tularemia isolate recovery related to land cover type supports the theory of natural nidality and clusters identify areas to target potential sources of the pathogen and improve surveillance.

Rational design of thermostability in bacterial 1,3-1,4-β-glucanases through spatial compartmentalization of mutational hotspots.

PubMed

Niu, Chengtuo; Zhu, Linjiang; Xu, Xin; Li, Qi

2017-02-01

Higher thermostability is required for 1,3-1,4-β-glucanase to maintain high activity under harsh conditions in the brewing and animal feed industries. In this study, a comprehensive and comparative analysis of thermostability in bacterial β-glucanases was conducted through a method named spatial compartmentalization of mutational hotspots (SCMH), which combined alignment of homologous protein sequences, spatial compartmentalization, and molecular dynamic (MD) simulation. The overall/local flexibility of six homologous β-glucanases was calculated by MD simulation and linearly fitted with enzyme optimal enzymatic temperatures. The calcium region was predicted to be the crucial region for thermostability of bacterial 1,3-1,4-β-glucanases, and optimization of four residue sites in this region by iterative saturation mutagenesis greatly increased the thermostability of a mesophilic β-glucanase (BglT) from Bacillus terquilensis. The E46P/S43E/H205P/S40E mutant showed a 20 °C increase in optimal enzymatic temperature and a 13.8 °C rise in protein melting temperature (T m ) compared to wild-type BglT. Its half-life values at 60 and 70 °C were 3.86-fold and 7.13-fold higher than those of wild-type BglT. The specific activity of E46P/S43E/H205P/S40E mutant was increased by 64.4 %, while its stability under acidic environment was improved. The rational design strategy used in this study might be applied to improve the thermostability of other industrial enzymes.

Introduction of digital soil mapping techniques for the nationwide regionalization of soil condition in Hungary; the first results of the DOSoReMI.hu (Digital, Optimized, Soil Related Maps and Information in Hungary) project

NASA Astrophysics Data System (ADS)

Pásztor, László; Laborczi, Annamária; Szatmári, Gábor; Takács, Katalin; Bakacsi, Zsófia; Szabó, József; Dobos, Endre

2014-05-01

Due to the former soil surveys and mapping activities significant amount of soil information has accumulated in Hungary. Present soil data requirements are mainly fulfilled with these available datasets either by their direct usage or after certain specific and generally fortuitous, thematic and/or spatial inference. Due to the more and more frequently emerging discrepancies between the available and the expected data, there might be notable imperfection as for the accuracy and reliability of the delivered products. With a recently started project (DOSoReMI.hu; Digital, Optimized, Soil Related Maps and Information in Hungary) we would like to significantly extend the potential, how countrywide soil information requirements could be satisfied in Hungary. We started to compile digital soil related maps which fulfil optimally the national and international demands from points of view of thematic, spatial and temporal accuracy. The spatial resolution of the targeted countrywide, digital, thematic maps is at least 1:50.000 (approx. 50-100 meter raster resolution). DOSoReMI.hu results are also planned to contribute to the European part of GSM.net products. In addition to the auxiliary, spatial data themes related to soil forming factors and/or to indicative environmental elements we heavily lean on the various national soil databases. The set of the applied digital soil mapping techniques is gradually broadened incorporating and eventually integrating geostatistical, data mining and GIS tools. In our paper we will present the first results. - Regression kriging (RK) has been used for the spatial inference of certain quantitative data, like particle size distribution components, rootable depth and organic matter content. In the course of RK-based mapping spatially segmented categorical information provided by the SMUs of Digital Kreybig Soil Information System (DKSIS) has been also used in the form of indicator variables. - Classification and regression trees (CART) were used to improve the spatial resolution of category-type soil maps (thematic downscaling), like genetic soil type and soil productivity maps. The approach was justified by the fact that certain thematic soil maps are not available in the required scale. Decision trees were applied for the understanding of the soil-landscape models involved in existing soil maps, and for the post-formalization of survey/compilation rules. The relationships identified and expressed in decision rules made the creation of spatially refined maps possible with the aid of high resolution environmental auxiliary variables. Among these co-variables, a special role was played by larger scale spatial soil information with diverse attributes. As a next step, the testing of random forests for the same purposes has been started. - Due to the simultaneous richness of available Hungarian legacy soil data, spatial inference methods and auxiliary environmental information, there is a high versatility of possible approaches for the compilation of a given soil (related) map. This suggests the opportunity of optimization. For the creation of an object specific soil (related) map with predefined parameters (resolution, accuracy, reliability etc.) one might intend to identify the optimum set of soil data, method and auxiliary co-variables optimized for the resources (data costs, computation requirements etc.). The first findings on the inclusion and joint usage of spatial soil data as well as on the consistency of various evaluations of the result maps will be also presented. Acknowledgement: Our work has been supported by the Hungarian National Scientific Research Foundation (OTKA, Grant No. K105167).

Selective influence of prior allocentric knowledge on the kinesthetic learning of a path.

PubMed

Lafon, Matthieu; Vidal, Manuel; Berthoz, Alain

2009-04-01

Spatial cognition studies have described two main cognitive strategies involved in the memorization of traveled paths in human navigation. One of these strategies uses the action-based memory (egocentric) of the traveled route or paths, which involves kinesthetic memory, optic flow, and episodic memory, whereas the other strategy privileges a survey memory of cartographic type (allocentric). Most studies have dealt with these two strategies separately, but none has tried to show the interaction between them in spite of the fact that we commonly use a map to imagine our journey and then proceed using egocentric navigation. An interesting question is therefore: how does prior allocentric knowledge of the environment affect the egocentric, purely kinesthetic navigation processes involved in human navigation? We designed an experiment in which blindfolded subjects had first to walk and memorize a path with kinesthetic cues only. They had previously been shown a map of the path, which was either correct or distorted (consistent shrinking or growing). The latter transformations were studied in order to observe what influence a distorted prior knowledge could have on spatial mechanisms. After having completed the first learning travel along the path, they had to perform several spatial tasks during the testing phase: (1) pointing towards the origin and (2) to specific points encountered along the path, (3) a free locomotor reproduction, and (4) a drawing of the memorized path. The results showed that prior cartographic knowledge influences the paths drawn and the spatial inference capacity, whereas neither locomotor reproduction nor spatial updating was disturbed. Our results strongly support the notion that (1) there are two independent neural bases underlying these mechanisms: a map-like representation allowing allocentric spatial inferences, and a kinesthetic memory of self-motion in space; and (2) a common use of, or a switching between, these two strategies is possible. Nevertheless, allocentric representations can emerge from the experience of kinesthetic cues alone.

Novel Perspectives on the Characterization of Species-Dependent Optical Signatures of Bacterial Colonies by Digital Holography.

PubMed

Buzalewicz, Igor; Kujawińska, Małgorzata; Krauze, Wojciech; Podbielska, Halina

2016-01-01

The use of light diffraction for the microbiological diagnosis of bacterial colonies was a significant breakthrough with widespread implications for the food industry and clinical practice. We previously confirmed that optical sensors for bacterial colony light diffraction can be used for bacterial identification. This paper is focused on the novel perspectives of this method based on digital in-line holography (DIH), which is able to reconstruct the amplitude and phase properties of examined objects, as well as the amplitude and phase patterns of the optical field scattered/diffracted by the bacterial colony in any chosen observation plane behind the object from single digital hologram. Analysis of the amplitude and phase patterns inside a colony revealed its unique optical properties, which are associated with the internal structure and geometry of the bacterial colony. Moreover, on a computational level, it is possible to select the desired scattered/diffracted pattern within the entire observation volume that exhibits the largest amount of unique, differentiating bacterial features. These properties distinguish this method from the already proposed sensing techniques based on light diffraction/scattering of bacterial colonies. The reconstructed diffraction patterns have a similar spatial distribution as the recorded Fresnel patterns, previously applied for bacterial identification with over 98% accuracy, but they are characterized by both intensity and phase distributions. Our results using digital holography provide new optical discriminators of bacterial species revealed in one single step in form of new optical signatures of bacterial colonies: digital holograms, reconstructed amplitude and phase patterns, as well as diffraction patterns from all observation space, which exhibit species-dependent features. To the best of our knowledge, this is the first report on bacterial colony analysis via digital holography and our study represents an innovative approach to the subject.

Novel Perspectives on the Characterization of Species-Dependent Optical Signatures of Bacterial Colonies by Digital Holography

PubMed Central

Buzalewicz, Igor; Kujawińska, Małgorzata; Krauze, Wojciech; Podbielska, Halina

2016-01-01

The use of light diffraction for the microbiological diagnosis of bacterial colonies was a significant breakthrough with widespread implications for the food industry and clinical practice. We previously confirmed that optical sensors for bacterial colony light diffraction can be used for bacterial identification. This paper is focused on the novel perspectives of this method based on digital in-line holography (DIH), which is able to reconstruct the amplitude and phase properties of examined objects, as well as the amplitude and phase patterns of the optical field scattered/diffracted by the bacterial colony in any chosen observation plane behind the object from single digital hologram. Analysis of the amplitude and phase patterns inside a colony revealed its unique optical properties, which are associated with the internal structure and geometry of the bacterial colony. Moreover, on a computational level, it is possible to select the desired scattered/diffracted pattern within the entire observation volume that exhibits the largest amount of unique, differentiating bacterial features. These properties distinguish this method from the already proposed sensing techniques based on light diffraction/scattering of bacterial colonies. The reconstructed diffraction patterns have a similar spatial distribution as the recorded Fresnel patterns, previously applied for bacterial identification with over 98% accuracy, but they are characterized by both intensity and phase distributions. Our results using digital holography provide new optical discriminators of bacterial species revealed in one single step in form of new optical signatures of bacterial colonies: digital holograms, reconstructed amplitude and phase patterns, as well as diffraction patterns from all observation space, which exhibit species-dependent features. To the best of our knowledge, this is the first report on bacterial colony analysis via digital holography and our study represents an innovative approach to the subject. PMID:26943121

A keystone predator controls bacterial diversity in the pitcher-plant (Sarracenia purpurea) microecosystem.

PubMed

Peterson, Celeste N; Day, Stephanie; Wolfe, Benjamin E; Ellison, Aaron M; Kolter, Roberto; Pringle, Anne

2008-09-01

The community of organisms inhabiting the water-filled leaves of the carnivorous pitcher-plant Sarracenia purpurea includes arthropods, protozoa and bacteria, and serves as a model system for studies of food web dynamics. Despite the wealth of data collected by ecologists and zoologists on this food web, very little is known about the bacterial assemblage in this microecosystem. We used terminal restriction fragment length polymorphism (T-RFLP) analysis to quantify bacterial diversity within the pitchers as a function of pitcher size, pH of the pitcher fluid and the presence of the keystone predator in this food web, larvae of the pitcher-plant mosquito Wyeomyia smithii. Results were analysed at two spatial scales: within a single bog and across three isolated bogs. Pitchers were sterile before they opened and composition of the bacterial assemblage was more variable between different bogs than within bogs. Measures of bacterial richness and diversity were greater in the presence of W. smithii and increased with increasing pitcher size. Our results suggest that fundamental ecological concepts derived from macroscopic food webs can also be used to predict the bacterial assemblages in pitcher plants.

Effect of flow and peristaltic mixing on bacterial growth in a gut-like channel

PubMed Central

Cremer, Jonas; Segota, Igor; Yang, Chih-yu; Arnoldini, Markus; Sauls, John T.; Zhang, Zhongge; Gutierrez, Edgar; Groisman, Alex; Hwa, Terence

2016-01-01

The ecology of microbes in the gut has been shown to play important roles in the health of the host. To better understand microbial growth and population dynamics in the proximal colon, the primary region of bacterial growth in the gut, we built and applied a fluidic channel that we call the “minigut.” This is a channel with an array of membrane valves along its length, which allows mimicking active contractions of the colonic wall. Repeated contraction is shown to be crucial in maintaining a steady-state bacterial population in the device despite strong flow along the channel that would otherwise cause bacterial washout. Depending on the flow rate and the frequency of contractions, the bacterial density profile exhibits varying spatial dependencies. For a synthetic cross-feeding community, the species abundance ratio is also strongly affected by mixing and flow along the length of the device. Complex mixing dynamics due to contractions is described well by an effective diffusion term. Bacterial dynamics is captured by a simple reaction–diffusion model without adjustable parameters. Our results suggest that flow and mixing play a major role in shaping the microbiota of the colon. PMID:27681630

Adaptive evolution of Escherichia coli to Ciprofloxacin in controlled stress environments: emergence of tolerance in spatial and temporal gradients

NASA Astrophysics Data System (ADS)

Deng, J.; Sanford, R. A.; Dong, Y.; Shechtman, L. A.; Zhou, L.; Alcalde, R.; Werth, C. J.; Fouke, B. W.

2016-12-01

Microorganisms in nature have evolved in response to a variety of environmental stresses, including gradients of temperature, pH, substrate availability and aqueous chemistry. While environmental stresses are considered to be the driving forces of adaptive evolution, the impact and extent of any specific stress needed to drive such changes has not been well characterized. In this study, the antibiotic Ciprofloxacin was used as a stressor and systematically applied to E. coli st. 307 cells via a spatial gradient in a microfluidic pore network and a temporal gradient in batch cultures. The microfluidic device facilitated in vitro real-time tracking of bacterial abundances and dynamic spatial distributions in response to the gradients of both the antibiotic and nutrients. Cells collected from the microfluidic device showed growth on plates containing up to 10-times the original minimum inhibition concentration (MIC). In batch systems, Ciprofloxacin was used to evaluate adaptive responses via temporal gradients, in which the stressor concentration was incrementally increased over time with each transfer of the culture after 24 hours of growth. Responses of E. coli 307 to these stress patterns were measured by quantifying changes in the MIC for Ciprofloxacin. Over a period of 18 days of step-wise concentration increments, bacterial cells were observed to acquire tolerance gradually and eventually adapt to a 28-fold increase in the original MIC. Samples at different stages within the temporal Ciprofloxacin gradient treatment show different extents of resistance. All samples exhibited resistance exceeding the highest exposure stress concentration. In combination with the spatial and temporal gradient systems, this work provides the first comprehensive measure of the dynamic resistance of E. coli in response to Ciprofloxacin concentration gradients. These will provide invaluable insights to understand the effects of antibiotic stresses on bacterial adaptive evolution in medical settings and shed light on understanding the mechanics of microbial evolution.

Spatial Homogeneity of Bacterial Communities Associated with the Surface Mucus Layer of the Reef-Building Coral Acropora palmata.

PubMed

Kemp, Dustin W; Rivers, Adam R; Kemp, Keri M; Lipp, Erin K; Porter, James W; Wares, John P

2015-01-01

Coral surface mucus layer (SML) microbiota are critical components of the coral holobiont and play important roles in nutrient cycling and defense against pathogens. We sequenced 16S rRNA amplicons to examine the structure of the SML microbiome within and between colonies of the threatened Caribbean reef-building coral Acropora palmata in the Florida Keys. Samples were taken from three spatially distinct colony regions--uppermost (high irradiance), underside (low irradiance), and the colony base--representing microhabitats that vary in irradiance and water flow. Phylogenetic diversity (PD) values of coral SML bacteria communities were greater than surrounding seawater and lower than adjacent sediment. Bacterial diversity and community composition was consistent among the three microhabitats. Cyanobacteria, Bacteroidetes, Alphaproteobacteria, and Proteobacteria, respectively were the most abundant phyla represented in the samples. This is the first time spatial variability of the surface mucus layer of A. palmata has been studied. Homogeneity in the microbiome of A. palmata contrasts with SML heterogeneity found in other Caribbean corals. These findings suggest that, during non-stressful conditions, host regulation of SML microbiota may override diverse physiochemical influences induced by the topographical complexity of A. palmata. Documenting the spatial distribution of SML microbes is essential to understanding the functional roles these microorganisms play in coral health and adaptability to environmental perturbations.

Widespread bacterial populations at glacier beds and their relationship to rock weathering and carbon cycling

NASA Astrophysics Data System (ADS)

Sharp, Martin; Parkes, John; Cragg, Barry; Fairchild, Ian J.; Lamb, Helen; Tranter, Martyn

1999-02-01

Bacterial populations found in subglacial meltwaters and basal ice are comparable to those in the active layer of permafrost and orders of magnitude larger than those found in ice cores from large ice sheets. Populations increase with sediment concentration, and 5% 24% of the bacteria are dividing or have just divided, suggesting that the populations are active. These findings (1) support inferences from recent studies of basal ice and meltwater chemistry that microbially mediated redox reactions may be important at glacier beds, (2) challenge the view that chemical weathering in glacial environments arises from purely inorganic reactions, and (3) raise the possibilities that redox reactions are a major source of protons consumed in subglacial weathering and that these reactions may be the dominant proton source beneath ice sheets where meltwaters are isolated from an atmospheric source of CO2. Microbial mediation may increase the rate of sulfide oxidation under subglacial conditions, a suggestion supported by the results of simple weathering experiments. If subglacial bacterial populations can oxidize and ferment organic carbon, it is important to reconsider the fate of soil organic carbon accumulated under interglacial conditions in areas subsequently overridden by Pleistocene ice sheets.

Bacterial Community Associated with Organs of Shallow Hydrothermal Vent Crab Xenograpsus testudinatus near Kuishan Island, Taiwan.

PubMed

Yang, Shan-Hua; Chiang, Pei-Wen; Hsu, Tin-Chang; Kao, Shuh-Ji; Tang, Sen-Lin

2016-01-01

Shallow-water hydrothermal vents off Kueishan Island (northeastern Taiwan) provide a unique, sulfur-rich, highly acidic (pH 1.75-4.6) and variable-temperature environment. In this species-poor habitat, the crab Xenograpsus testudinatus is dominant, as it mainly feeds on zooplankton killed by sulfurous plumes. In this study, 16S ribosomal RNA gene amplicon pyrosequencing was used to investigate diversity and composition of bacteria residing in digestive gland, gill, stomach, heart, and mid-gut of X. testudinatus, as well as in surrounding seawater. Dominant bacteria were Gamma- and Epsilonproteobacteria that might be capable of autotrophic growth by oxidizing reduced sulfur compounds and are usually resident in deep-sea hydrothermal systems. Dominant bacterial OTUs in X. testudinatus had both host and potential organ specificities, consistent with a potential trophic symbiotic relationship (nutrient transfer between host and bacteria). We inferred that versatile ways to obtain nutrients may provide an adaptive advantage for X. testudinatus in this demanding environment. To our knowledge, this is the first study of bacterial communities in various organs/tissues of a crustacean in a shallow-water hydrothermal system, and as such, may be a convenient animal model for studying these systems.

3′-NADP and 3′-NAADP, Two Metabolites Formed by the Bacterial Type III Effector AvrRxo1*♦

PubMed Central

Schuebel, Felix; Rocker, Andrea; Edelmann, Daniel; Schessner, Julia; Brieke, Clara; Meinhart, Anton

2016-01-01

An arsenal of effector proteins is injected by bacterial pathogens into the host cell or its vicinity to increase virulence. The commonly used top-down approaches inferring the toxic mechanism of individual effector proteins from the host's phenotype are often impeded by multiple targets of different effectors as well as by their pleiotropic effects. Here we describe our bottom-up approach, showing that the bacterial type III effector AvrRxo1 of plant pathogens is an authentic phosphotransferase that produces two novel metabolites by phosphorylating nicotinamide/nicotinic acid adenine dinucleotide at the adenosine 3′-hydroxyl group. Both products of AvrRxo1, 3′-NADP and 3′-nicotinic acid adenine dinucleotide phosphate (3′-NAADP), are substantially different from the ubiquitous co-enzyme 2′-NADP and the calcium mobilizer 2′-NAADP. Interestingly, 3′-NADP and 3′-NAADP have previously been used as inhibitors or signaling molecules but were regarded as “artificial” compounds so far. Our findings now necessitate a shift in thinking about the biological importance of 3′-phosphorylated NAD derivatives. PMID:27621317

Exploring the dynamics of bacterial community composition in soil: the pan-bacteriome approach.

PubMed

Bacci, Giovanni; Ceccherini, Maria Teresa; Bani, Alessia; Bazzicalupo, Marco; Castaldini, Maurizio; Galardini, Marco; Giovannetti, Luciana; Mocali, Stefano; Pastorelli, Roberta; Pantani, Ottorino Luca; Arfaioli, Paola; Pietramellara, Giacomo; Viti, Carlo; Nannipieri, Paolo; Mengoni, Alessio

2015-03-01

We performed a longitudinal study (repeated observations of the same sample over time) to investigate both the composition and structure of temporal changes of bacterial community composition in soil mesocosms, subjected to three different treatments (water and 5 or 25 mg kg(-1) of dried soil Cd(2+)). By analogy with the pan genome concept, we identified a core bacteriome and an accessory bacteriome. Resident taxa were assigned to the core bacteriome, while occasional taxa were assigned to the accessory bacteriome. Core and accessory bacteriome represented roughly 35 and 50 % of the taxa detected, respectively, and were characterized by different taxonomic signatures from phylum to genus level while 15 % of the taxa were found to be unique to a particular sample. In particular, the core bacteriome was characterized by higher abundance of members of Planctomycetes, Actinobacteria, Verrucomicrobia and Acidobacteria, while the accessory bacteriome included more members of Firmicutes, Clamydiae and Proteobacteria, suggesting potentially different responses to environmental changes of members from these phyla. We conclude that the pan-bacteriome model may be a useful approach to gain insight for modeling bacterial community structure and inferring different abilities of bacteria taxa.

Nitrogen starvation affects bacterial adhesion to soil

PubMed Central

Borges, Maria Tereza; Nascimento, Antônio Galvão; Rocha, Ulisses Nunes; Tótola, Marcos Rogério

2008-01-01

One of the main factors limiting the bioremediation of subsoil environments based on bioaugmentation is the transport of selected microorganisms to the contaminated zones. The characterization of the physiological responses of the inoculated microorganisms to starvation, especially the evaluation of characteristics that affect the adhesion of the cells to soil particles, is fundamental to anticipate the success or failure of bioaugmentation. The objective of this study was to investigate the effect of nitrogen starvation on cell surface hydrophobicity and cell adhesion to soil particles by bacterial strains previously characterized as able to use benzene, toluene or xilenes as carbon and energy sources. The strains LBBMA 18-T (non-identified), Arthrobacter aurescens LBBMA 98, Arthrobacter oxydans LBBMA 201, and Klebsiella sp. LBBMA 204–1 were used in the experiments. Cultivation of the cells in nitrogen-deficient medium caused a significant reduction of the adhesion to soil particles by all the four strains. Nitrogen starvation also reduced significantly the strength of cell adhesion to the soil particles, except for Klebsiella sp. LBBMA 204–1. Two of the four strains showed significant reduction in cell surface hydrophobicity. It is inferred that the efficiency of bacterial transport through soils might be potentially increased by nitrogen starvation. PMID:24031246

Mass Fluxes of Ice and Oxygen Across the Entire Lid of Lake Vostok from Observations of Englacial Radiowave Attenuation

NASA Astrophysics Data System (ADS)

Winebrenner, D. P.; Kintner, P. M. S.; MacGregor, J. A.

2017-12-01

Over deep Antarctic subglacial lakes, spatially varying ice thickness and the pressure-dependent melting point of ice result in areas of melting and accretion at the ice-water interface, i.e., the lake lid. These ice mass fluxes drive lake circulation and, because basal Antarctic ice contains air-clathrate, affect the input of oxygen to the lake, with implications for subglacial life. Inferences of melting and accretion from radar-layer tracking and geodesy are limited in spatial coverage and resolution. Here we develop a new method to estimate rates of accretion, melting, and the resulting oxygen input at a lake lid, using airborne radar data over Lake Vostok together with ice-temperature and chemistry data from the Vostok ice core. Because the lake lid is a coherent reflector of known reflectivity (at our radar frequency), we can infer depth-averaged radiowave attenuation in the ice, with spatial resolution 1 km along flight lines. Spatial variation in attenuation depends mostly on variation in ice temperature near the lid, which in turn varies strongly with ice mass flux at the lid. We model ice temperature versus depth with ice mass flux as a parameter, thus linking that flux to (observed) depth-averaged attenuation. The resulting map of melt- and accretion-rates independently reproduces features known from earlier studies, but now covers the entire lid. We find that accretion is dominant when integrated over the lid, with an ice imbalance of 0.05 to 0.07 km3 a-1, which is robust against uncertainties.

Measuring soil moisture content non-invasively at intermediate spatial scale using cosmic-ray neutrons 1986

USDA-ARS?s Scientific Manuscript database

Soil moisture content on a horizontal scale of hectometers and at depths of decimeters can be inferred from measurements of low-energy cosmic-ray neutrons that are generated within soil, moderated mainly by hydrogen atoms, and diffused back to the atmosphere. These neutrons are sensitive to water co...

Scale dependent inference in landscape genetics

Treesearch

Samuel A. Cushman; Erin L. Landguth

2010-01-01

Ecological relationships between patterns and processes are highly scale dependent. This paper reports the first formal exploration of how changing scale of research away from the scale of the processes governing gene flow affects the results of landscape genetic analysis. We used an individual-based, spatially explicit simulation model to generate patterns of genetic...

The assembly of ecological communities inferred from taxonomic and functional composition

Treesearch

Eric R. Sokol; E.F. Benfield; Lisa K. Belden; H. Maurice. Valett

2011-01-01

Among-site variation in metacommunities (beta diversity) is typically correlated with the distance separating the sites (spatial lag). This distance decay in similarity pattern has been linked to both niche-based and dispersal-based community assembly hypotheses. Here we show that beta diversity patterns in community composition, when supplemented with functional-trait...

Assessing Clark's nutcracker seed-caching flights using maternally inherited mitochondrial DNA of whitebark pine

Treesearch

Bryce A. Richardson; Ned B. Klopfenstein; Steven J. Brunsfeld

2002-01-01

Maternally inherited mitochondrial DNA haplotypes in whitebark pine (Pinus albicaulis Engelm.) were used to examine the maternal genetic structure at three hierarchical spatial scales: fine scale, coarse scale, and interpopulation. These data were used to draw inferences into Clark’s nutcracker (Nucifraga columbiana Wilson)...

Mars ozone: Mariner 9 revisited

NASA Technical Reports Server (NTRS)

Lindner, Bernhard Lee

1994-01-01

The efficacy of the UV spectroscopy technique used by Mariner 9 to remotely measure ozone abundance at Mars is discussed. Previously-inferred ozone abundances could be underestimated by as much as a factor of 3, and much of the observed variability in the ozone abundance could be due to temporal and spatial variability in cloud and dust amount.

LATERAL ROOT DISTRIBUTION OF TREES IN AN OLD-GROWTH DOUGLAS-FIR FOREST INFERRED FROM UPTAKE OF TRACER 15N

EPA Science Inventory

Belowground competition for nutrients and water is considered a key factor affecting spatial organization and productivity of individual stems within forest stands, yet there are almost no data describing the lateral extent and overlap of competing root systems. We quantified th...

Tracking and Inferring Spatial Rotation by Children and Great Apes

ERIC Educational Resources Information Center

Okamoto-Barth; Sanae; Call, Josep

2008-01-01

Finding hidden objects in space is a fundamental ability that has received considerable research attention from both a developmental and a comparative perspective. Tracking the rotational displacements of containers and hidden objects is a particularly challenging task. This study investigated the ability of 3-, 5-, 7-, and 9-year-old children and…

Using StreamCat and the NHDPlus framework to model and map the biological condition of USA streams and rivers

EPA Science Inventory

The US EPA’s National River and Stream Assessment (NRSA) uses spatially balanced sampling to estimate the proportion of streams within the conterminous US (CONUS) that deviate from least-disturbed biological condition (BC). These assessments do not infer BC at un-sampled streams,...

Air Quality and Early-Life Mortality: Evidence from Indonesia's Wildfires

ERIC Educational Resources Information Center

Jayachandran, Seema

2009-01-01

Smoke from massive wildfires blanketed Indonesia in late 1997. This paper examines the impact that this air pollution (particulate matter) had on fetal, infant, and child mortality. Exploiting the sharp timing and spatial patterns of the pollution and inferring deaths from "missing children" in the 2000 Indonesian Census, I find that the…

Towards national mapping of aquatic condition (II): Predicting the probable biological condition of USA streams and rivers

EPA Science Inventory

The US EPA’s National River and Stream Assessment (NRSA) uses spatially balanced sampling to estimate the proportion of streams within the conterminous US (CONUS) that deviate from least-disturbed biological condition (BC). These assessments do not infer BC at un-sampled st...

Microscale Effects from Global Hot Plasma Imagery

NASA Technical Reports Server (NTRS)

Moore, T. E.; Fok, M.-C.; Perez, J. D.; Keady, J. P.

1995-01-01

We have used a three-dimensional model of recovery phase storm hot plasmas to explore the signatures of pitch angle distributions (PADS) in global fast atom imagery of the magnetosphere. The model computes mass, energy, and position-dependent PADs based on drift effects, charge exchange losses, and Coulomb drag. The hot plasma PAD strongly influences both the storm current system carried by the hot plasma and its time evolution. In turn, the PAD is strongly influenced by plasma waves through pitch angle diffusion, a microscale effect. We report the first simulated neutral atom images that account for anisotropic PADs within the hot plasma. They exhibit spatial distribution features that correspond directly to the PADs along the lines of sight. We investigate the use of image brightness distributions along tangent-shell field lines to infer equatorial PADS. In tangent-shell regions with minimal spatial gradients, reasonably accurate PADs are inferred from simulated images. They demonstrate the importance of modeling PADs for image inversion and show that comparisons of models with real storm plasma images will reveal the global effects of these microscale processes.

Comment on “Models of stochastic, spatially varying stress in the crust compatible with focal‐mechanism data, and how stress inversions can be biased toward the stress rate” by Deborah Elaine Smith and Thomas H. Heaton

USGS Publications Warehouse

Hardebeck, Jeanne L.

2015-01-01

This model makes specific predictions about the orientations and heterogeneity of earthquake focal mechanisms. Smith and Heaton (2011) attempt to validate this heterogeneous stress model using observations of earthquake focal‐mechanism variability from Hardebeck (2006). They then demonstrate that the model predicts a bias in the orientations of earthquake focal mechanisms, which are biased away from the background stress and toward the stressing rate. They suggest the focal‐mechanism bias in this model invalidates the large body of work over the last several decades, that has inferred stress orientations from the inversion of earthquake focal mechanisms. The question of whether or not the Smith and Heaton (2011) model is applicable to the real Earth is therefore important not only for understanding spatial stress variability but also for evaluating the numerous studies that have inferred crustal stress orientations from earthquake focal mechanisms (e.g., as compiled by Heidbach et al., 2008).

A Bayesian Surrogate for Regional Skew in Flood Frequency Analysis

NASA Astrophysics Data System (ADS)

Kuczera, George

1983-06-01

The problem of how to best utilize site and regional flood data to infer the shape parameter of a flood distribution is considered. One approach to this problem is given in Bulletin 17B of the U.S. Water Resources Council (1981) for the log-Pearson distribution. Here a lesser known distribution is considered, namely, the power normal which fits flood data as well as the log-Pearson and has a shape parameter denoted by λ derived from a Box-Cox power transformation. The problem of regionalizing λ is considered from an empirical Bayes perspective where site and regional flood data are used to infer λ. The distortive effects of spatial correlation and heterogeneity of site sampling variance of λ are explicitly studied with spatial correlation being found to be of secondary importance. The end product of this analysis is the posterior distribution of the power normal parameters expressing, in probabilistic terms, what is known about the parameters given site flood data and regional information on λ. This distribution can be used to provide the designer with several types of information. The posterior distribution of the T-year flood is derived. The effect of nonlinearity in λ on inference is illustrated. Because uncertainty in λ is explicitly allowed for, the understatement in confidence limits due to fixing λ (analogous to fixing log skew) is avoided. Finally, it is shown how to obtain the marginal flood distribution which can be used to select a design flood with specified exceedance probability.

Causal Inference for Spatial Constancy across Saccades

PubMed Central

Atsma, Jeroen; Maij, Femke; Koppen, Mathieu; Irwin, David E.; Medendorp, W. Pieter

2016-01-01

Our ability to interact with the environment hinges on creating a stable visual world despite the continuous changes in retinal input. To achieve visual stability, the brain must distinguish the retinal image shifts caused by eye movements and shifts due to movements of the visual scene. This process appears not to be flawless: during saccades, we often fail to detect whether visual objects remain stable or move, which is called saccadic suppression of displacement (SSD). How does the brain evaluate the memorized information of the presaccadic scene and the actual visual feedback of the postsaccadic visual scene in the computations for visual stability? Using a SSD task, we test how participants localize the presaccadic position of the fixation target, the saccade target or a peripheral non-foveated target that was displaced parallel or orthogonal during a horizontal saccade, and subsequently viewed for three different durations. Results showed different localization errors of the three targets, depending on the viewing time of the postsaccadic stimulus and its spatial separation from the presaccadic location. We modeled the data through a Bayesian causal inference mechanism, in which at the trial level an optimal mixing of two possible strategies, integration vs. separation of the presaccadic memory and the postsaccadic sensory signals, is applied. Fits of this model generally outperformed other plausible decision strategies for producing SSD. Our findings suggest that humans exploit a Bayesian inference process with two causal structures to mediate visual stability. PMID:26967730

Individual based simulations of bacterial growth on agar plates

NASA Astrophysics Data System (ADS)

Ginovart, M.; López, D.; Valls, J.; Silbert, M.

2002-03-01

The individual based simulator, INDividual DIScrete SIMulations (INDISIM) has been used to study the behaviour of the growth of bacterial colonies on a finite dish. The simulations reproduce the qualitative trends of pattern formation that appear during the growth of Bacillus subtilis on an agar plate under different initial conditions of nutrient peptone concentration, the amount of agar on the plate, and the temperature. The simulations are carried out by imposing closed boundary conditions on a square lattice divided into square spatial cells. The simulator studies the temporal evolution of the bacterial population possible by setting rules of behaviour for each bacterium, such as its uptake, metabolism and reproduction, as well as rules for the medium in which the bacterial cells grow, such as concentration of nutrient particles and their diffusion. The determining factors that characterize the structure of the bacterial colony patterns in the presents simulations, are the initial concentrations of nutrient particles, that mimic the amount of peptone in the experiments, and the set of values for the microscopic diffusion parameter related, in the experiments, to the amount of the agar medium.

Different bacterial communities in ectomycorrhizae and surrounding soil

PubMed Central

Vik, Unni; Logares, Ramiro; Blaalid, Rakel; Halvorsen, Rune; Carlsen, Tor; Bakke, Ingrid; Kolstø, Anne-Brit; Økstad, Ole Andreas; Kauserud, Håvard

2013-01-01

Several eukaryotic symbioses have shown to host a rich diversity of prokaryotes that interact with their hosts. Here, we study bacterial communities associated with ectomycorrhizal root systems of Bistorta vivipara compared to bacterial communities in bulk soil using pyrosequencing of 16S rRNA amplicons. A high richness of Operational Taxonomic Units (OTUs) was found in plant roots (3,571 OTUs) and surrounding soil (3,476 OTUs). The community composition differed markedly between these two environments. Actinobacteria, Armatimonadetes, Chloroflexi and OTUs unclassified at phylum level were significantly more abundant in plant roots than in soil. A large proportion of the OTUs, especially those in plant roots, presented low similarity to Sanger 16S rRNA reference sequences, suggesting novel bacterial diversity in ectomycorrhizae. Furthermore, the bacterial communities of the plant roots were spatially structured up to a distance of 60 cm, which may be explained by bacteria using fungal hyphae as a transport vector. The analyzed ectomycorrhizae presents a distinct microbiome, which likely influence the functioning of the plant-fungus symbiosis. PMID:24326907

Selecting a Separable Parametric Spatiotemporal Covariance Structure for Longitudinal Imaging Data

PubMed Central

George, Brandon; Aban, Inmaculada

2014-01-01

Longitudinal imaging studies allow great insight into how the structure and function of a subject’s internal anatomy changes over time. Unfortunately, the analysis of longitudinal imaging data is complicated by inherent spatial and temporal correlation: the temporal from the repeated measures, and the spatial from the outcomes of interest being observed at multiple points in a patients body. We propose the use of a linear model with a separable parametric spatiotemporal error structure for the analysis of repeated imaging data. The model makes use of spatial (exponential, spherical, and Matérn) and temporal (compound symmetric, autoregressive-1, Toeplitz, and unstructured) parametric correlation functions. A simulation study, inspired by a longitudinal cardiac imaging study on mitral regurgitation patients, compared different information criteria for selecting a particular separable parametric spatiotemporal correlation structure as well as the effects on Type I and II error rates for inference on fixed effects when the specified model is incorrect. Information criteria were found to be highly accurate at choosing between separable parametric spatiotemporal correlation structures. Misspecification of the covariance structure was found to have the ability to inflate the Type I error or have an overly conservative test size, which corresponded to decreased power. An example with clinical data is given illustrating how the covariance structure procedure can be done in practice, as well as how covariance structure choice can change inferences about fixed effects. PMID:25293361

Epidemiological study of hazelnut bacterial blight in central Italy by using laboratory analysis and geostatistics.

PubMed

Lamichhane, Jay Ram; Fabi, Alfredo; Ridolfi, Roberto; Varvaro, Leonardo

2013-01-01

Incidence of Xanthomonas arboricola pv. corylina, the causal agent of hazelnut bacterial blight, was analyzed spatially in relation to the pedoclimatic factors. Hazelnut grown in twelve municipalities situated in the province of Viterbo, central Italy was studied. A consistent number of bacterial isolates were obtained from the infected tissues of hazelnut collected in three years (2010-2012). The isolates, characterized by phenotypic tests, did not show any difference among them. Spatial patterns of pedoclimatic data, analyzed by geostatistics showed a strong positive correlation of disease incidence with higher values of rainfall, thermal shock and soil nitrogen; a weak positive correlation with soil aluminium content and a strong negative correlation with the values of Mg/K ratio. No correlation of the disease incidence was found with soil pH. Disease incidence ranged from very low (<1%) to very high (almost 75%) across the orchards. Young plants (4-year old) were the most affected by the disease confirming a weak negative correlation of the disease incidence with plant age. Plant cultivars did not show any difference in susceptibility to the pathogen. Possible role of climate change on the epidemiology of the disease is discussed. Improved management practices are recommended for effective control of the disease.

Epidemiological Study of Hazelnut Bacterial Blight in Central Italy by Using Laboratory Analysis and Geostatistics

PubMed Central

Lamichhane, Jay Ram; Fabi, Alfredo; Ridolfi, Roberto; Varvaro, Leonardo

2013-01-01

Incidence of Xanthomonas arboricola pv. corylina, the causal agent of hazelnut bacterial blight, was analyzed spatially in relation to the pedoclimatic factors. Hazelnut grown in twelve municipalities situated in the province of Viterbo, central Italy was studied. A consistent number of bacterial isolates were obtained from the infected tissues of hazelnut collected in three years (2010–2012). The isolates, characterized by phenotypic tests, did not show any difference among them. Spatial patterns of pedoclimatic data, analyzed by geostatistics showed a strong positive correlation of disease incidence with higher values of rainfall, thermal shock and soil nitrogen; a weak positive correlation with soil aluminium content and a strong negative correlation with the values of Mg/K ratio. No correlation of the disease incidence was found with soil pH. Disease incidence ranged from very low (<1%) to very high (almost 75%) across the orchards. Young plants (4-year old) were the most affected by the disease confirming a weak negative correlation of the disease incidence with plant age. Plant cultivars did not show any difference in susceptibility to the pathogen. Possible role of climate change on the epidemiology of the disease is discussed. Improved management practices are recommended for effective control of the disease. PMID:23424654