Live Cell Genomics: RNA Exon-Specific RNA-Binding Protein Isolation.

PubMed

Bell, Thomas J; Eberwine, James

2015-01-01

RNA-binding proteins (RBPs) are essential regulatory proteins that control all modes of RNA processing and regulation. New experimental approaches to isolate these indispensable proteins under in vivo conditions are needed to advance the field of RBP biology. Historically, in vitro biochemical approaches to isolate RBP complexes have been useful and productive, but biological relevance of the identified RBP complexes can be imprecise or erroneous. Here we review an inventive experimental to isolate RBPs under the in vivo conditions. The method is called peptide nucleic acid (PNA)-assisted identification of RBP (PAIR) technology and it uses cell-penetrating peptides (CPPs) to deliver photo-activatible RBP-capture molecule to the cytoplasm of the live cells. The PAIR methodology provides two significant advantages over the most commonly used approaches: (1) it overcomes the in vitro limitation of standard biochemical approaches and (2) the PAIR RBP-capture molecule is highly selective and adaptable which allows investigators to isolate exon-specific RBP complexes. Most importantly, the in vivo capture conditions and selectivity of the RBP-capture molecule yield biologically accurate and relevant RBP data.

Systems Biology Approaches to the Study of Biological Networks Underlying Alzheimer's Disease: Role of miRNAs.

PubMed

Roth, Wera; Hecker, David; Fava, Eugenio

2016-01-01

MicroRNAs (miRNAs) are emerging as significant regulators of mRNA complexity in the human central nervous system (CNS) thereby controlling distinct gene expression profiles in a spatio-temporal manner during development, neuronal plasticity, aging and (age-related) neurodegeneration, including Alzheimer's disease (AD). Increasing effort is expended towards dissecting and deciphering the molecular and genetic mechanisms of neurobiological and pathological functions of these brain-enriched miRNAs. Along these lines, recent data pinpoint distinct miRNAs and miRNA networks being linked to APP splicing, processing and Aβ pathology (Lukiw et al., Front Genet 3:327, 2013), and furthermore, to the regulation of tau and its cellular subnetworks (Lau et al., EMBO Mol Med 5:1613, 2013), altogether underlying the onset and propagation of Alzheimer's disease. MicroRNA profiling studies in Alzheimer's disease suffer from poor consensus which is an acknowledged concern in the field, and constitutes one of the current technical challenges. Hence, a strong demand for experimental and computational systems biology approaches arises, to incorporate and integrate distinct levels of information and scientific knowledge into a complex system of miRNA networks in the context of the transcriptome, proteome and metabolome in a given cellular environment. Here, we will discuss the state-of-the-art technologies and computational approaches on hand that may lead to a deeper understanding of the complex biological networks underlying the pathogenesis of Alzheimer's disease.

Pinpointing the level of isolation between two cryptic species sharing the same microhabitat: a case study with a scarabaeid species complex

USDA-ARS?s Scientific Manuscript database

We explored biological processes underlying speciation within dung beetles belonging to the vacca species complex (Scarabaeidae: Onthophagus). The two taxa of this complex, O. vacca and O. medius, not only are known to have a large overlapping Palearctic distribution range but also share the same co...

Biological robustness.

PubMed

Kitano, Hiroaki

2004-11-01

Robustness is a ubiquitously observed property of biological systems. It is considered to be a fundamental feature of complex evolvable systems. It is attained by several underlying principles that are universal to both biological organisms and sophisticated engineering systems. Robustness facilitates evolvability and robust traits are often selected by evolution. Such a mutually beneficial process is made possible by specific architectural features observed in robust systems. But there are trade-offs between robustness, fragility, performance and resource demands, which explain system behaviour, including the patterns of failure. Insights into inherent properties of robust systems will provide us with a better understanding of complex diseases and a guiding principle for therapy design.

Synthesis, structural elucidation, biological, antioxidant and nuclease activities of some 5-Fluorouracil-amino acid mixed ligand complexes

NASA Astrophysics Data System (ADS)

Shobana, Sutha; Subramaniam, Perumal; Mitu, Liviu; Dharmaraja, Jeyaprakash; Arvind Narayan, Sundaram

2015-01-01

Some biologically active mixed ligand complexes (1-9) have been synthesized from 5-Fluorouracil (5-FU; A) and amino acids (B) such as glycine (gly), L-alanine (ala) and L-valine (val) with Ni(II), Cu(II) and Zn(II) ions. The synthesized mixed ligand complexes (1-9) were characterized by various physico-chemical, spectral, thermal and morphological studies. 5-Fluorouracil and its mixed ligand complexes have been tested for their in vitro biological activities against some pathogenic bacterial and fungal species by the agar well diffusion method. The in vitro antioxidant activities of 5-Fluorouracil and its complexes have also been investigated by using the DPPH assay method. The results demonstrate that Cu(II) mixed ligand complexes (4-6) exhibit potent biological as well as antioxidant activities compared to 5-Fluorouracil and Ni(II) (1-3) and Zn(II) (7-9) mixed ligand complexes. Further, the cleaving activities of CT DNA under aerobic conditions show moderate activity with the synthesized Cu(II) and Ni(II) mixed ligand complexes (1-6) while no activity is seen with Zn(II) complexes (7-9). Binding studies of CT DNA with these complexes show a decrease in intensity of the charge transfer band to the extent of 5-15% along with a minor red shift. The free energy change values (Δ‡G) calculated from intrinsic binding constants indicate that the interaction between mixed ligand complex and DNA is spontaneous.

Accomplishment Summary 1968-1969. Biological Computer Laboratory.

ERIC Educational Resources Information Center

Von Foerster, Heinz; And Others

This report summarizes theoretical, applied, and experimental studies in the areas of computational principles in complex intelligent systems, cybernetics, multivalued logic, and the mechanization of cognitive processes. This work is summarized under the following topic headings: properties of complex dynamic systems; computers and the language…

Deconstructing the core dynamics from a complex time-lagged regulatory biological circuit.

PubMed

Eriksson, O; Brinne, B; Zhou, Y; Björkegren, J; Tegnér, J

2009-03-01

Complex regulatory dynamics is ubiquitous in molecular networks composed of genes and proteins. Recent progress in computational biology and its application to molecular data generate a growing number of complex networks. Yet, it has been difficult to understand the governing principles of these networks beyond graphical analysis or extensive numerical simulations. Here the authors exploit several simplifying biological circumstances which thereby enable to directly detect the underlying dynamical regularities driving periodic oscillations in a dynamical nonlinear computational model of a protein-protein network. System analysis is performed using the cell cycle, a mathematically well-described complex regulatory circuit driven by external signals. By introducing an explicit time delay and using a 'tearing-and-zooming' approach the authors reduce the system to a piecewise linear system with two variables that capture the dynamics of this complex network. A key step in the analysis is the identification of functional subsystems by identifying the relations between state-variables within the model. These functional subsystems are referred to as dynamical modules operating as sensitive switches in the original complex model. By using reduced mathematical representations of the subsystems the authors derive explicit conditions on how the cell cycle dynamics depends on system parameters, and can, for the first time, analyse and prove global conditions for system stability. The approach which includes utilising biological simplifying conditions, identification of dynamical modules and mathematical reduction of the model complexity may be applicable to other well-characterised biological regulatory circuits. [Includes supplementary material].

Mapping complex traits as a dynamic system

PubMed Central

Sun, Lidan; Wu, Rongling

2017-01-01

Despite increasing emphasis on the genetic study of quantitative traits, we are still far from being able to chart a clear picture of their genetic architecture, given an inherent complexity involved in trait formation. A competing theory for studying such complex traits has emerged by viewing their phenotypic formation as a “system” in which a high-dimensional group of interconnected components act and interact across different levels of biological organization from molecules through cells to whole organisms. This system is initiated by a machinery of DNA sequences that regulate a cascade of biochemical pathways to synthesize endophenotypes and further assemble these endophenotypes toward the end-point phenotype in virtue of various developmental changes. This review focuses on a conceptual framework for genetic mapping of complex traits by which to delineate the underlying components, interactions and mechanisms that govern the system according to biological principles and understand how these components function synergistically under the control of quantitative trait loci (QTLs) to comprise a unified whole. This framework is built by a system of differential equations that quantifies how alterations of different components lead to the global change of trait development and function, and provides a quantitative and testable platform for assessing the multiscale interplay between QTLs and development. The method will enable geneticists to shed light on the genetic complexity of any biological system and predict, alter or engineer its physiological and pathological states. PMID:25772476

ADAM: Analysis of Discrete Models of Biological Systems Using Computer Algebra

PubMed Central

2011-01-01

Background Many biological systems are modeled qualitatively with discrete models, such as probabilistic Boolean networks, logical models, Petri nets, and agent-based models, to gain a better understanding of them. The computational complexity to analyze the complete dynamics of these models grows exponentially in the number of variables, which impedes working with complex models. There exist software tools to analyze discrete models, but they either lack the algorithmic functionality to analyze complex models deterministically or they are inaccessible to many users as they require understanding the underlying algorithm and implementation, do not have a graphical user interface, or are hard to install. Efficient analysis methods that are accessible to modelers and easy to use are needed. Results We propose a method for efficiently identifying attractors and introduce the web-based tool Analysis of Dynamic Algebraic Models (ADAM), which provides this and other analysis methods for discrete models. ADAM converts several discrete model types automatically into polynomial dynamical systems and analyzes their dynamics using tools from computer algebra. Specifically, we propose a method to identify attractors of a discrete model that is equivalent to solving a system of polynomial equations, a long-studied problem in computer algebra. Based on extensive experimentation with both discrete models arising in systems biology and randomly generated networks, we found that the algebraic algorithms presented in this manuscript are fast for systems with the structure maintained by most biological systems, namely sparseness and robustness. For a large set of published complex discrete models, ADAM identified the attractors in less than one second. Conclusions Discrete modeling techniques are a useful tool for analyzing complex biological systems and there is a need in the biological community for accessible efficient analysis tools. ADAM provides analysis methods based on mathematical algorithms as a web-based tool for several different input formats, and it makes analysis of complex models accessible to a larger community, as it is platform independent as a web-service and does not require understanding of the underlying mathematics. PMID:21774817

Biological Applications of FM-AFM in Liquid Environment

NASA Astrophysics Data System (ADS)

Fukuma, Takeshi; Jarvis, Suzanne P.

Atomic force microscopy (AFM) was noted for its potential to study biological materials shortly after its first development in 1986 due to its ability to image insulators in liquid environments. The subsequent application of AFM to biology has included lateral characterization via imaging, unraveling of molecules under a tensile load and application of a force either to measure mechanical properties under the tip or to instigate a biochemical response in living cells. To date, the application of frequency modulation AFM (FM-AFM) specifically to biological materials has been limited to relatively few research groups when compared to the extensive application of AFM to biological materials. This is probably due to the perceived complexity of the technique both by researchers in the life sciences and those manufacturing liquid AFMs for biological research. In this chapter, we aim to highlight the advantages of applying the technique to biological materials.

Microwave gallium-68 radiochemistry for kinetically stable bis(thiosemicarbazone) complexes: structural investigations and cellular uptake under hypoxia.

PubMed

Alam, Israt S; Arrowsmith, Rory L; Cortezon-Tamarit, Fernando; Twyman, Frazer; Kociok-Köhn, Gabriele; Botchway, Stanley W; Dilworth, Jonathan R; Carroll, Laurence; Aboagye, Eric O; Pascu, Sofia I

2016-01-07

We report the microwave synthesis of several bis(thiosemicarbazones) and the rapid gallium-68 incorporation to give the corresponding metal complexes. These proved kinetically stable under 'cold' and 'hot' biological assays and were investigated using laser scanning confocal microscopy, flow cytometry and radioactive cell retention studies under normoxia and hypoxia. (68)Ga complex retention was found to be 34% higher in hypoxic cells than in normoxic cells over 30 min, further increasing to 53% at 120 min. Our data suggests that this class of gallium complexes show hypoxia selectivity suitable for imaging in living cells and in vivo tests by microPET in nude athymic mice showed that they are excreted within 1 h of their administration.

The interplay of biology and technology

PubMed Central

Fields, Stanley

2001-01-01

Technologies for biological research arise in multiple ways—through serendipity, through inspired insights, and through incremental advances—and they are tightly coupled to progress in engineering. Underlying the complex dynamics of technology and biology are the different motivations of those who work in the two realms. Consideration of how methodologies emerge has implications for the planning of interdisciplinary centers and the training of the next generation of scientists. PMID:11517346

The diverse and expanding role of mass spectrometry in structural and molecular biology.

PubMed

Lössl, Philip; van de Waterbeemd, Michiel; Heck, Albert Jr

2016-12-15

The emergence of proteomics has led to major technological advances in mass spectrometry (MS). These advancements not only benefitted MS-based high-throughput proteomics but also increased the impact of mass spectrometry on the field of structural and molecular biology. Here, we review how state-of-the-art MS methods, including native MS, top-down protein sequencing, cross-linking-MS, and hydrogen-deuterium exchange-MS, nowadays enable the characterization of biomolecular structures, functions, and interactions. In particular, we focus on the role of mass spectrometry in integrated structural and molecular biology investigations of biological macromolecular complexes and cellular machineries, highlighting work on CRISPR-Cas systems and eukaryotic transcription complexes. © 2016 The Authors. Published under the terms of the CC BY NC ND 4.0 license.

Reduction of N2 by supported tungsten clusters gives a model of the process by nitrogenase

PubMed Central

Murakami, Junichi; Yamaguchi, Wataru

2012-01-01

Metalloenzymes catalyze difficult chemical reactions under mild conditions. Mimicking their functions is a challenging task and it has been investigated using homogeneous systems containing metal complexes. The nitrogenase that converts N2 to NH3 under mild conditions is one of such enzymes. Efforts to realize the biological function have continued for more than four decades, which has resulted in several reports of reduction of N2, ligated to metal complexes in solutions, to NH3 by protonation under mild conditions. Here, we show that seemingly distinct supported small tungsten clusters in a dry environment reduce N2 under mild conditions like the nitrogenase. N2 is reduced to NH3 via N2H4 by addition of neutral H atoms, which agrees with the mechanism recently proposed for the N2 reduction on the active site of nitrogenase. The process on the supported clusters gives a model of the biological N2 reduction. PMID:22586517

The effects of morphological irregularity on the mechanical behavior of interdigitated biological sutures under tension.

PubMed

Liu, Lei; Jiang, Yunyao; Boyce, Mary; Ortiz, Christine; Baur, Jeffery; Song, Juha; Li, Yaning

2017-06-14

Irregular interdigitated morphology is prevalent in biological sutures in nature. Suture complexity index has long been recognized as the most important morphological parameter to govern the mechanical properties of biological sutures. However, the suture complexity index alone does not reflect all aspects of suture morphology. The goal of this investigation was to determine that besides suture complexity index, whether the degree of morphological irregularity of biological sutures has influences on the mechanical properties, and if there is any, how to quantify these influences. To explore these issues, theoretical and finite element (FE) suture models with the same suture complexity index but different levels of morphological irregularity were developed. The quasi-static stiffness, strength for damage initiation and post-failure process of irregular sutures were studied. It was shown that for the same suture complexity index, when the level of morphological irregularity increases, the overall strain to failure will increase while tensile stiffness is retained; also, the total energy to fracture increases with a sacrifice in strength to damage initiation. These results reveal that morphological irregularity is another important independent parameter to govern and balance the mechanical properties of biological sutures. Therefore, from the mechanics point of view, the prevalence of irregular suture morphology in nature is a merit, not a defect. Copyright © 2017 Elsevier Ltd. All rights reserved.

Cardiac Arrhythmia: In vivo screening in the zebrafish to overcome complexity in drug discovery.

PubMed

Macrae, Calum A

2010-07-01

IMPORTANCE OF THE FIELD: Cardiac arrhythmias remain a major challenge for modern drug discovery. Clinical events are paroxysmal, often rare and may be asymptomatic until a highly morbid complication. Target selection is often based on limited information and though highly specific agents are identified in screening, the final efficacy is often compromised by unanticipated systemic responses, a narrow therapeutic index and substantial toxicities. AREAS COVERED IN THIS REVIEW: Our understanding of complexity of arrhythmogenesis has grown dramatically over the last two decades, and the range of potential disease mechanisms now includes pathways previously thought only tangentially involved in arrhythmia. This review surveys the literature on arrhythmia mechanisms from 1965 to the present day, outlines the complex biology underlying potentially each and every rhythm disturbance, and highlights the problems for rational target identification. The rationale for in vivo screening is described and the utility of the zebrafish for this approach and for complementary work in functional genomics is discussed. Current limitations of the model in this setting and the need for careful validation in new disease areas are also described. WHAT THE READER WILL GAIN: An overview of the complex mechanisms underlying most clinical arrhythmias, and insight into the limits of ion channel conductances as drug targets. An introduction to the zebrafish as a model organism, in particular for cardiovascular biology. Potential approaches to overcoming the hurdles to drug discovery in the face of complex biology including in vivo screening of zebrafish genetic disease models. TAKE HOME MESSAGE: In vivo screening in faithful disease models allows the effects of drugs on integrative physiology and disease biology to be captured during the screening process, in a manner agnostic to potential drug target or targets. This systematic strategy bypasses current gaps in our understanding of disease biology, but emphasizes the importance of the rigor of the disease model.

The Biophysics Microgravity Initiative

NASA Technical Reports Server (NTRS)

Gorti, S.

2016-01-01

Biophysical microgravity research on the International Space Station using biological materials has been ongoing for several decades. The well-documented substantive effects of long duration microgravity include the facilitation of the assembly of biological macromolecules into large structures, e.g., formation of large protein crystals under micro-gravity. NASA is invested not only in understanding the possible physical mechanisms of crystal growth, but also promoting two flight investigations to determine the influence of µ-gravity on protein crystal quality. In addition to crystal growth, flight investigations to determine the effects of shear on nucleation and subsequent formation of complex structures (e.g., crystals, fibrils, etc.) are also supported. It is now considered that long duration microgravity research aboard the ISS could also make possible the formation of large complex biological and biomimetic materials. Investigations of various materials undergoing complex structure formation in microgravity will not only strengthen NASA science programs, but may also provide invaluable insight towards the construction of large complex tissues, organs, or biomimetic materials on Earth.

Systems genetics approaches to understand complex traits

PubMed Central

Civelek, Mete; Lusis, Aldons J.

2014-01-01

Systems genetics is an approach to understand the flow of biological information that underlies complex traits. It uses a range of experimental and statistical methods to quantitate and integrate intermediate phenotypes, such as transcript, protein or metabolite levels, in populations that vary for traits of interest. Systems genetics studies have provided the first global view of the molecular architecture of complex traits and are useful for the identification of genes, pathways and networks that underlie common human diseases. Given the urgent need to understand how the thousands of loci that have been identified in genome-wide association studies contribute to disease susceptibility, systems genetics is likely to become an increasingly important approach to understanding both biology and disease. PMID:24296534

Connections Matter: Social Networks and Lifespan Health in Primate Translational Models

PubMed Central

McCowan, Brenda; Beisner, Brianne; Bliss-Moreau, Eliza; Vandeleest, Jessica; Jin, Jian; Hannibal, Darcy; Hsieh, Fushing

2016-01-01

Humans live in societies full of rich and complex relationships that influence health. The ability to improve human health requires a detailed understanding of the complex interplay of biological systems that contribute to disease processes, including the mechanisms underlying the influence of social contexts on these biological systems. A longitudinal computational systems science approach provides methods uniquely suited to elucidate the mechanisms by which social systems influence health and well-being by investigating how they modulate the interplay among biological systems across the lifespan. In the present report, we argue that nonhuman primate social systems are sufficiently complex to serve as model systems allowing for the development and refinement of both analytical and theoretical frameworks linking social life to health. Ultimately, developing systems science frameworks in nonhuman primate models will speed discovery of the mechanisms that subserve the relationship between social life and human health. PMID:27148103

Is Self-organization a Rational Expectation?

NASA Astrophysics Data System (ADS)

Luediger, Heinz

Over decades and under varying names the study of biology-inspired algorithms applied to non-living systems has been the subject of a small and somewhat exotic research community. Only the recent coincidence of a growing inability to master the design, development and operation of increasingly intertwined systems and processes, and an accelerated trend towards a naïve if not romanticizing view of nature in the sciences, has led to the adoption of biology-inspired algorithmic research by a wider range of sciences. Adaptive systems, as we apparently observe in nature, are meanwhile viewed as a promising way out of the complexity trap and, propelled by a long list of ‘self’ catchwords, complexity research has become an influential stream in the science community. This paper presents four provocative theses that cast doubt on the strategic potential of complexity research and the viability of large scale deployment of biology-inspired algorithms in an expectation driven world.

Synchronization in complex networks

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

Arenas, A.; Diaz-Guilera, A.; Moreno, Y.

Synchronization processes in populations of locally interacting elements are in the focus of intense research in physical, biological, chemical, technological and social systems. The many efforts devoted to understand synchronization phenomena in natural systems take now advantage of the recent theory of complex networks. In this review, we report the advances in the comprehension of synchronization phenomena when oscillating elements are constrained to interact in a complex network topology. We also overview the new emergent features coming out from the interplay between the structure and the function of the underlying pattern of connections. Extensive numerical work as well as analyticalmore » approaches to the problem are presented. Finally, we review several applications of synchronization in complex networks to different disciplines: biological systems and neuroscience, engineering and computer science, and economy and social sciences.« less

Biology Diagrams: Tools To Think With.

ERIC Educational Resources Information Center

Kindfield, Ann C. H.

Subcellular processes like meiosis are frequently problematic for learners because they are complex and, except for the extent that they can be observed under a light microscope, occur outside of our direct experience. More detailed characterization of what underlies various degrees of student understanding of a process is required to more fully…

Pattern dynamics of the reaction-diffusion immune system.

PubMed

Zheng, Qianqian; Shen, Jianwei; Wang, Zhijie

2018-01-01

In this paper, we will investigate the effect of diffusion, which is ubiquitous in nature, on the immune system using a reaction-diffusion model in order to understand the dynamical behavior of complex patterns and control the dynamics of different patterns. Through control theory and linear stability analysis of local equilibrium, we obtain the optimal condition under which the system loses stability and a Turing pattern occurs. By combining mathematical analysis and numerical simulation, we show the possible patterns and how these patterns evolve. In addition, we establish a bridge between the complex patterns and the biological mechanism using the results from a previous study in Nature Cell Biology. The results in this paper can help us better understand the biological significance of the immune system.

Deciphering the Interdependence between Ecological and Evolutionary Networks.

PubMed

Melián, Carlos J; Matthews, Blake; de Andreazzi, Cecilia S; Rodríguez, Jorge P; Harmon, Luke J; Fortuna, Miguel A

2018-05-24

Biological systems consist of elements that interact within and across hierarchical levels. For example, interactions among genes determine traits of individuals, competitive and cooperative interactions among individuals influence population dynamics, and interactions among species affect the dynamics of communities and ecosystem processes. Such systems can be represented as hierarchical networks, but can have complex dynamics when interdependencies among levels of the hierarchy occur. We propose integrating ecological and evolutionary processes in hierarchical networks to explore interdependencies in biological systems. We connect gene networks underlying predator-prey trait distributions to food webs. Our approach addresses longstanding questions about how complex traits and intraspecific trait variation affect the interdependencies among biological levels and the stability of meta-ecosystems. Copyright © 2018 Elsevier Ltd. All rights reserved.

The Contribution of Novel Brain Imaging Techniques to Understanding the Neurobiology of Mental Retardation and Developmental Disabilities

ERIC Educational Resources Information Center

Gothelf, Doron; Furfaro, Joyce A.; Penniman, Lauren C.; Glover, Gary H.; Reiss, Allan L.

2005-01-01

Studying the biological mechanisms underlying mental retardation and developmental disabilities (MR/DD) is a very complex task. This is due to the wide heterogeneity of etiologies and pathways that lead to MR/DD. Breakthroughs in genetics and molecular biology and the development of sophisticated brain imaging techniques during the last decades…

A Unifying Mathematical Framework for Genetic Robustness, Environmental Robustness, Network Robustness and their Trade-offs on Phenotype Robustness in Biological Networks. Part III: Synthetic Gene Networks in Synthetic Biology

PubMed Central

Chen, Bor-Sen; Lin, Ying-Po

2013-01-01

Robust stabilization and environmental disturbance attenuation are ubiquitous systematic properties that are observed in biological systems at many different levels. The underlying principles for robust stabilization and environmental disturbance attenuation are universal to both complex biological systems and sophisticated engineering systems. In many biological networks, network robustness should be large enough to confer: intrinsic robustness for tolerating intrinsic parameter fluctuations; genetic robustness for buffering genetic variations; and environmental robustness for resisting environmental disturbances. Network robustness is needed so phenotype stability of biological network can be maintained, guaranteeing phenotype robustness. Synthetic biology is foreseen to have important applications in biotechnology and medicine; it is expected to contribute significantly to a better understanding of functioning of complex biological systems. This paper presents a unifying mathematical framework for investigating the principles of both robust stabilization and environmental disturbance attenuation for synthetic gene networks in synthetic biology. Further, from the unifying mathematical framework, we found that the phenotype robustness criterion for synthetic gene networks is the following: if intrinsic robustness + genetic robustness + environmental robustness ≦ network robustness, then the phenotype robustness can be maintained in spite of intrinsic parameter fluctuations, genetic variations, and environmental disturbances. Therefore, the trade-offs between intrinsic robustness, genetic robustness, environmental robustness, and network robustness in synthetic biology can also be investigated through corresponding phenotype robustness criteria from the systematic point of view. Finally, a robust synthetic design that involves network evolution algorithms with desired behavior under intrinsic parameter fluctuations, genetic variations, and environmental disturbances, is also proposed, together with a simulation example. PMID:23515190

A Unifying Mathematical Framework for Genetic Robustness, Environmental Robustness, Network Robustness and their Trade-offs on Phenotype Robustness in Biological Networks. Part III: Synthetic Gene Networks in Synthetic Biology.

PubMed

Chen, Bor-Sen; Lin, Ying-Po

2013-01-01

Robust stabilization and environmental disturbance attenuation are ubiquitous systematic properties that are observed in biological systems at many different levels. The underlying principles for robust stabilization and environmental disturbance attenuation are universal to both complex biological systems and sophisticated engineering systems. In many biological networks, network robustness should be large enough to confer: intrinsic robustness for tolerating intrinsic parameter fluctuations; genetic robustness for buffering genetic variations; and environmental robustness for resisting environmental disturbances. Network robustness is needed so phenotype stability of biological network can be maintained, guaranteeing phenotype robustness. Synthetic biology is foreseen to have important applications in biotechnology and medicine; it is expected to contribute significantly to a better understanding of functioning of complex biological systems. This paper presents a unifying mathematical framework for investigating the principles of both robust stabilization and environmental disturbance attenuation for synthetic gene networks in synthetic biology. Further, from the unifying mathematical framework, we found that the phenotype robustness criterion for synthetic gene networks is the following: if intrinsic robustness + genetic robustness + environmental robustness ≦ network robustness, then the phenotype robustness can be maintained in spite of intrinsic parameter fluctuations, genetic variations, and environmental disturbances. Therefore, the trade-offs between intrinsic robustness, genetic robustness, environmental robustness, and network robustness in synthetic biology can also be investigated through corresponding phenotype robustness criteria from the systematic point of view. Finally, a robust synthetic design that involves network evolution algorithms with desired behavior under intrinsic parameter fluctuations, genetic variations, and environmental disturbances, is also proposed, together with a simulation example.

Identifying Specific Genes Controlling Complex Traits Through A Genome-Wide Screen For cis-Acting Regulatory Elements - An Example Using Marek's Disease

USDA-ARS?s Scientific Manuscript database

The identification of specific genes underlying phenotypic variation of complex traits remains one of the greatest challenges in biology despite having genome sequences and more powerful tools. Most genome-wide screens lack sufficient resolving power as they typically depend on linkage. One altern...

Hierarchical thinking in network biology: the unbiased modularization of biochemical networks.

PubMed

Papin, Jason A; Reed, Jennifer L; Palsson, Bernhard O

2004-12-01

As reconstructed biochemical reaction networks continue to grow in size and scope, there is a growing need to describe the functional modules within them. Such modules facilitate the study of biological processes by deconstructing complex biological networks into conceptually simple entities. The definition of network modules is often based on intuitive reasoning. As an alternative, methods are being developed for defining biochemical network modules in an unbiased fashion. These unbiased network modules are mathematically derived from the structure of the whole network under consideration.

Translational Systems Biology and Voice Pathophysiology

PubMed Central

Li, Nicole Y. K.; Abbott, Katherine Verdolini; Rosen, Clark; An, Gary; Hebda, Patricia A.; Vodovotz, Yoram

2011-01-01

Objectives/Hypothesis Personalized medicine has been called upon to tailor healthcare to an individual's needs. Evidence-based medicine (EBM) has advocated using randomized clinical trials with large populations to evaluate treatment effects. However, due to large variations across patients, the results are likely not to apply to an individual patient. We suggest that a complementary, systems biology approach using computational modeling may help tackle biological complexity in order to improve ultimate patient care. The purpose of the article is: 1) to review the pros and cons of EBM, and 2) to discuss the alternative systems biology method and present its utility in clinical voice research. Study Design Tutorial Methods Literature review and discussion. Results We propose that translational systems biology can address many of the limitations of EBM pertinent to voice and other health care domains, and thus complement current health research models. In particular, recent work using mathematical modeling suggests that systems biology has the ability to quantify the highly complex biologic processes underlying voice pathophysiology. Recent data support the premise that this approach can be applied specifically in the case of phonotrauma and surgically induced vocal fold trauma, and may have particular power to address personalized medicine. Conclusions We propose that evidence around vocal health and disease be expanded beyond a population-based method to consider more fully issues of complexity and systems interactions, especially in implementing personalized medicine in voice care and beyond. PMID:20025041

Root Systems Biology: Integrative Modeling across Scales, from Gene Regulatory Networks to the Rhizosphere1

PubMed Central

Hill, Kristine; Porco, Silvana; Lobet, Guillaume; Zappala, Susan; Mooney, Sacha; Draye, Xavier; Bennett, Malcolm J.

2013-01-01

Genetic and genomic approaches in model organisms have advanced our understanding of root biology over the last decade. Recently, however, systems biology and modeling have emerged as important approaches, as our understanding of root regulatory pathways has become more complex and interpreting pathway outputs has become less intuitive. To relate root genotype to phenotype, we must move beyond the examination of interactions at the genetic network scale and employ multiscale modeling approaches to predict emergent properties at the tissue, organ, organism, and rhizosphere scales. Understanding the underlying biological mechanisms and the complex interplay between systems at these different scales requires an integrative approach. Here, we describe examples of such approaches and discuss the merits of developing models to span multiple scales, from network to population levels, and to address dynamic interactions between plants and their environment. PMID:24143806

25 Years of Tension over Actin Binding to the Cadherin Cell Adhesion Complex: The Devil is in the Details.

PubMed

Nelson, W James; Weis, William I

2016-07-01

Over the past 25 years, there has been a conceptual (re)evolution in understanding how the cadherin cell adhesion complex, which contains F-actin-binding proteins, binds to the actin cytoskeleton. There is now good synergy between structural, biochemical, and cell biological results that the cadherin-catenin complex binds to F-actin under force. Copyright © 2016 Elsevier Ltd. All rights reserved.

Resource recovery from wastewater: application of meta-omics to phosphorus and carbon management.

PubMed

Sales, Christopher M; Lee, Patrick K H

2015-06-01

A growing trend at wastewater treatment plants is the recovery of resources and energy from wastewater. Enhanced biological phosphorus removal and anaerobic digestion are two established biotechnology approaches for the recovery of phosphorus and carbon, respectively. Meta-omics approaches (meta-genomics, transcriptomics, proteomics, and metabolomics) are providing novel biological insights into these complex biological systems. In particular, genome-centric metagenomics analyses are revealing the function and physiology of individual community members. Querying transcripts, proteins and metabolites are emerging techniques that can inform the cellular responses under different conditions. Overall, meta-omics approaches are shedding light into complex microbial communities once regarded as 'blackboxes', but challenges remain to integrate information from meta-omics into engineering design and operation guidelines. Copyright © 2015 Elsevier Ltd. All rights reserved.

Towards a comprehensive understanding of emerging dynamics and function of pancreatic islets: A complex network approach. Comment on "Network science of biological systems at different scales: A review" by Gosak et al.

NASA Astrophysics Data System (ADS)

Loppini, Alessandro

2018-03-01

Complex network theory represents a comprehensive mathematical framework to investigate biological systems, ranging from sub-cellular and cellular scales up to large-scale networks describing species interactions and ecological systems. In their exhaustive and comprehensive work [1], Gosak et al. discuss several scenarios in which the network approach was able to uncover general properties and underlying mechanisms of cells organization and regulation, tissue functions and cell/tissue failure in pathology, by the study of chemical reaction networks, structural networks and functional connectivities.

A new theoretical approach to analyze complex processes in cytoskeleton proteins.

PubMed

Li, Xin; Kolomeisky, Anatoly B

2014-03-20

Cytoskeleton proteins are filament structures that support a large number of important biological processes. These dynamic biopolymers exist in nonequilibrium conditions stimulated by hydrolysis chemical reactions in their monomers. Current theoretical methods provide a comprehensive picture of biochemical and biophysical processes in cytoskeleton proteins. However, the description is only qualitative under biologically relevant conditions because utilized theoretical mean-field models neglect correlations. We develop a new theoretical method to describe dynamic processes in cytoskeleton proteins that takes into account spatial correlations in the chemical composition of these biopolymers. Our approach is based on analysis of probabilities of different clusters of subunits. It allows us to obtain exact analytical expressions for a variety of dynamic properties of cytoskeleton filaments. By comparing theoretical predictions with Monte Carlo computer simulations, it is shown that our method provides a fully quantitative description of complex dynamic phenomena in cytoskeleton proteins under all conditions.

Multi-level and hybrid modelling approaches for systems biology.

PubMed

Bardini, R; Politano, G; Benso, A; Di Carlo, S

2017-01-01

During the last decades, high-throughput techniques allowed for the extraction of a huge amount of data from biological systems, unveiling more of their underling complexity. Biological systems encompass a wide range of space and time scales, functioning according to flexible hierarchies of mechanisms making an intertwined and dynamic interplay of regulations. This becomes particularly evident in processes such as ontogenesis, where regulative assets change according to process context and timing, making structural phenotype and architectural complexities emerge from a single cell, through local interactions. The information collected from biological systems are naturally organized according to the functional levels composing the system itself. In systems biology, biological information often comes from overlapping but different scientific domains, each one having its own way of representing phenomena under study. That is, the different parts of the system to be modelled may be described with different formalisms. For a model to have improved accuracy and capability for making a good knowledge base, it is good to comprise different system levels, suitably handling the relative formalisms. Models which are both multi-level and hybrid satisfy both these requirements, making a very useful tool in computational systems biology. This paper reviews some of the main contributions in this field.

Vibrational spectroscopy for imaging single microbial cells in complex biological samples

DOE PAGES

Harrison, Jesse P.; Berry, David

2017-04-13

Here, vibrational spectroscopy is increasingly used for the rapid and non-destructive imaging of environmental and medical samples. Both Raman and Fourier-transform infrared (FT-IR) imaging have been applied to obtain detailed information on the chemical composition of biological materials, ranging from single microbial cells to tissues. Due to its compatibility with methods such as stable isotope labeling for the monitoring of cellular activities, vibrational spectroscopy also holds considerable power as a tool in microbial ecology. Chemical imaging of undisturbed biological systems (such as live cells in their native habitats) presents unique challenges due to the physical and chemical complexity of themore » samples, potential for spectral interference, and frequent need for real-time measurements. This Mini Review provides a critical synthesis of recent applications of Raman and FT-IR spectroscopy for characterizing complex biological samples, with a focus on developments in single-cell imaging. We also discuss how new spectroscopic methods could be used to overcome current limitations of singlecell analyses. Given the inherent complementarity of Raman and FT-IR spectroscopic methods, we discuss how combining these approaches could enable us to obtain new insights into biological activities either in situ or under conditions that simulate selected properties of the natural environment.« less

Vibrational spectroscopy for imaging single microbial cells in complex biological samples

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

Harrison, Jesse P.; Berry, David

Here, vibrational spectroscopy is increasingly used for the rapid and non-destructive imaging of environmental and medical samples. Both Raman and Fourier-transform infrared (FT-IR) imaging have been applied to obtain detailed information on the chemical composition of biological materials, ranging from single microbial cells to tissues. Due to its compatibility with methods such as stable isotope labeling for the monitoring of cellular activities, vibrational spectroscopy also holds considerable power as a tool in microbial ecology. Chemical imaging of undisturbed biological systems (such as live cells in their native habitats) presents unique challenges due to the physical and chemical complexity of themore » samples, potential for spectral interference, and frequent need for real-time measurements. This Mini Review provides a critical synthesis of recent applications of Raman and FT-IR spectroscopy for characterizing complex biological samples, with a focus on developments in single-cell imaging. We also discuss how new spectroscopic methods could be used to overcome current limitations of singlecell analyses. Given the inherent complementarity of Raman and FT-IR spectroscopic methods, we discuss how combining these approaches could enable us to obtain new insights into biological activities either in situ or under conditions that simulate selected properties of the natural environment.« less

A Novel Hydrogel-Based Biosampling Approach

DTIC Science & Technology

2016-03-01

MONITORING AGENCY NAME(S) AND ADDRESS(ES) U.S. Army Edgewood Chemical Biological Center Seedling Program, APG, MD 21010-5424 10. SPONSOR/MONITOR’S...Std. Z39.18 ii Blank   iii PREFACE The work described in this report was authorized under the U.S. Army Edgewood Chemical Biological...a complex area of intensive, ongoing research. After a biorelease event, sampling is at the core of all pre- and post- decontamination analyses

Identifying gene networks underlying the neurobiology of ethanol and alcoholism.

PubMed

Wolen, Aaron R; Miles, Michael F

2012-01-01

For complex disorders such as alcoholism, identifying the genes linked to these diseases and their specific roles is difficult. Traditional genetic approaches, such as genetic association studies (including genome-wide association studies) and analyses of quantitative trait loci (QTLs) in both humans and laboratory animals already have helped identify some candidate genes. However, because of technical obstacles, such as the small impact of any individual gene, these approaches only have limited effectiveness in identifying specific genes that contribute to complex diseases. The emerging field of systems biology, which allows for analyses of entire gene networks, may help researchers better elucidate the genetic basis of alcoholism, both in humans and in animal models. Such networks can be identified using approaches such as high-throughput molecular profiling (e.g., through microarray-based gene expression analyses) or strategies referred to as genetical genomics, such as the mapping of expression QTLs (eQTLs). Characterization of gene networks can shed light on the biological pathways underlying complex traits and provide the functional context for identifying those genes that contribute to disease development.

A System-Level Pathway-Phenotype Association Analysis Using Synthetic Feature Random Forest

PubMed Central

Pan, Qinxin; Hu, Ting; Malley, James D.; Andrew, Angeline S.; Karagas, Margaret R.; Moore, Jason H.

2015-01-01

As the cost of genome-wide genotyping decreases, the number of genome-wide association studies (GWAS) has increased considerably. However, the transition from GWAS findings to the underlying biology of various phenotypes remains challenging. As a result, due to its system-level interpretability, pathway analysis has become a popular tool for gaining insights on the underlying biology from high-throughput genetic association data. In pathway analyses, gene sets representing particular biological processes are tested for significant associations with a given phenotype. Most existing pathway analysis approaches rely on single-marker statistics and assume that pathways are independent of each other. As biological systems are driven by complex biomolecular interactions, embracing the complex relationships between single-nucleotide polymorphisms (SNPs) and pathways needs to be addressed. To incorporate the complexity of gene-gene interactions and pathway-pathway relationships, we propose a system-level pathway analysis approach, synthetic feature random forest (SF-RF), which is designed to detect pathway-phenotype associations without making assumptions about the relationships among SNPs or pathways. In our approach, the genotypes of SNPs in a particular pathway are aggregated into a synthetic feature representing that pathway via Random Forest (RF). Multiple synthetic features are analyzed using RF simultaneously and the significance of a synthetic feature indicates the significance of the corresponding pathway. We further complement SF-RF with pathway-based Statistical Epistasis Network (SEN) analysis that evaluates interactions among pathways. By investigating the pathway SEN, we hope to gain additional insights into the genetic mechanisms contributing to the pathway-phenotype association. We apply SF-RF to a population-based genetic study of bladder cancer and further investigate the mechanisms that help explain the pathway-phenotype associations using SEN. The bladder cancer associated pathways we found are both consistent with existing biological knowledge and reveal novel and plausible hypotheses for future biological validations. PMID:24535726

Module-based multiscale simulation of angiogenesis in skeletal muscle

PubMed Central

2011-01-01

Background Mathematical modeling of angiogenesis has been gaining momentum as a means to shed new light on the biological complexity underlying blood vessel growth. A variety of computational models have been developed, each focusing on different aspects of the angiogenesis process and occurring at different biological scales, ranging from the molecular to the tissue levels. Integration of models at different scales is a challenging and currently unsolved problem. Results We present an object-oriented module-based computational integration strategy to build a multiscale model of angiogenesis that links currently available models. As an example case, we use this approach to integrate modules representing microvascular blood flow, oxygen transport, vascular endothelial growth factor transport and endothelial cell behavior (sensing, migration and proliferation). Modeling methodologies in these modules include algebraic equations, partial differential equations and agent-based models with complex logical rules. We apply this integrated model to simulate exercise-induced angiogenesis in skeletal muscle. The simulation results compare capillary growth patterns between different exercise conditions for a single bout of exercise. Results demonstrate how the computational infrastructure can effectively integrate multiple modules by coordinating their connectivity and data exchange. Model parameterization offers simulation flexibility and a platform for performing sensitivity analysis. Conclusions This systems biology strategy can be applied to larger scale integration of computational models of angiogenesis in skeletal muscle, or other complex processes in other tissues under physiological and pathological conditions. PMID:21463529

BiNA: A Visual Analytics Tool for Biological Network Data

PubMed Central

Gerasch, Andreas; Faber, Daniel; Küntzer, Jan; Niermann, Peter; Kohlbacher, Oliver; Lenhof, Hans-Peter; Kaufmann, Michael

2014-01-01

Interactive visual analysis of biological high-throughput data in the context of the underlying networks is an essential task in modern biomedicine with applications ranging from metabolic engineering to personalized medicine. The complexity and heterogeneity of data sets require flexible software architectures for data analysis. Concise and easily readable graphical representation of data and interactive navigation of large data sets are essential in this context. We present BiNA - the Biological Network Analyzer - a flexible open-source software for analyzing and visualizing biological networks. Highly configurable visualization styles for regulatory and metabolic network data offer sophisticated drawings and intuitive navigation and exploration techniques using hierarchical graph concepts. The generic projection and analysis framework provides powerful functionalities for visual analyses of high-throughput omics data in the context of networks, in particular for the differential analysis and the analysis of time series data. A direct interface to an underlying data warehouse provides fast access to a wide range of semantically integrated biological network databases. A plugin system allows simple customization and integration of new analysis algorithms or visual representations. BiNA is available under the 3-clause BSD license at http://bina.unipax.info/. PMID:24551056

Enzyme Biosensors for Biomedical Applications: Strategies for Safeguarding Analytical Performances in Biological Fluids

PubMed Central

Rocchitta, Gaia; Spanu, Angela; Babudieri, Sergio; Latte, Gavinella; Madeddu, Giordano; Galleri, Grazia; Nuvoli, Susanna; Bagella, Paola; Demartis, Maria Ilaria; Fiore, Vito; Manetti, Roberto; Serra, Pier Andrea

2016-01-01

Enzyme-based chemical biosensors are based on biological recognition. In order to operate, the enzymes must be available to catalyze a specific biochemical reaction and be stable under the normal operating conditions of the biosensor. Design of biosensors is based on knowledge about the target analyte, as well as the complexity of the matrix in which the analyte has to be quantified. This article reviews the problems resulting from the interaction of enzyme-based amperometric biosensors with complex biological matrices containing the target analyte(s). One of the most challenging disadvantages of amperometric enzyme-based biosensor detection is signal reduction from fouling agents and interference from chemicals present in the sample matrix. This article, therefore, investigates the principles of functioning of enzymatic biosensors, their analytical performance over time and the strategies used to optimize their performance. Moreover, the composition of biological fluids as a function of their interaction with biosensing will be presented. PMID:27249001

Genes under weaker stabilizing selection increase network evolvability and rapid regulatory adaptation to an environmental shift.

PubMed

Laarits, T; Bordalo, P; Lemos, B

2016-08-01

Regulatory networks play a central role in the modulation of gene expression, the control of cellular differentiation, and the emergence of complex phenotypes. Regulatory networks could constrain or facilitate evolutionary adaptation in gene expression levels. Here, we model the adaptation of regulatory networks and gene expression levels to a shift in the environment that alters the optimal expression level of a single gene. Our analyses show signatures of natural selection on regulatory networks that both constrain and facilitate rapid evolution of gene expression level towards new optima. The analyses are interpreted from the standpoint of neutral expectations and illustrate the challenge to making inferences about network adaptation. Furthermore, we examine the consequence of variable stabilizing selection across genes on the strength and direction of interactions in regulatory networks and in their subsequent adaptation. We observe that directional selection on a highly constrained gene previously under strong stabilizing selection was more efficient when the gene was embedded within a network of partners under relaxed stabilizing selection pressure. The observation leads to the expectation that evolutionarily resilient regulatory networks will contain optimal ratios of genes whose expression is under weak and strong stabilizing selection. Altogether, our results suggest that the variable strengths of stabilizing selection across genes within regulatory networks might itself contribute to the long-term adaptation of complex phenotypes. © 2016 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2016 European Society For Evolutionary Biology.

New insights into pancreatic cancer biology.

PubMed

Hidalgo, M

2012-09-01

Pancreatic cancer remains a devastating disease. Over the last few years, there have been important advances in the molecular and biological understanding of pancreatic cancer. This included understanding of the genomic complexity of the disease, the role of pancreatic cancer stem cells, the relevance of the tumor microenvironment, and the unique metabolic adaptation of pancreas cancer cells to obtain nutrients under hypoxic environment. In this paper, we review the most salient developments in these few areas.

Thermo-Responsive Complexes of c-Myc Antisense Oligonucleotide with Block Copolymer of Poly(OEGMA) and Quaternized Poly(4-Vinylpyridine).

PubMed

Topuzogullari, Murat; Elalmis, Yeliz Basaran; Isoglu, Sevil Dincer

2017-04-01

Solution behavior of thermo-responsive polymers and their complexes with biological macromolecules may be affected by environmental conditions, such as the concentration of macromolecular components, pH, ion concentration, etc. Therefore, a thermo-responsive polymer and its complexes should be characterized in detail to observe their responses against possible environments under physiological conditions before biological applications. To briefly indicate this important issue, thermo-responsive block copolymer of quaternized poly(4-vinylpyridine) and poly(oligoethyleneglycol methyl ether methacrylate) as a potential nonviral vector has been synthesized. Polyelectrolyte complexes of this copolymer with the antisense oligonucleotide of c-Myc oncogene are also thermo-responsive but, have lower LCST (lower critical solution temperature) values compared to individual copolymer. LCST values of complexes decrease with molar ratio of macromolecular components and presence of salt. Dilution of solutions also affects solution behavior of complexes and causes a significant decrease in size and an increase in LCST, which indicates possible effects of severe dilutions in the blood stream. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Clinical features and pathophysiology of Complex Regional Pain Syndrome – current state of the art

PubMed Central

Marinus, Johan; Moseley, G. Lorimer; Birklein, Frank; Baron, Ralf; Maihöfner, Christian; Kingery, Wade S.; van Hilten, Jacobus J.

2017-01-01

That a minor injury can trigger a complex regional pain syndrome (CRPS) - multiple system dysfunction, severe and often chronic pain and disability - has fascinated scientists and perplexed clinicians for decades. However, substantial advances across several medical disciplines have recently increased our understanding of CRPS. Compelling evidence implicates biological pathways that underlie aberrant inflammation, vasomotor dysfunction, and maladaptive neuroplasticity in the clinical features of CRPS. Collectively, the evidence points to CRPS being a multifactorial disorder that is associated with an aberrant host response to tissue injury. Varying susceptibility to perturbed regulation of any of the underlying biological pathways probably accounts for the clinical heterogeneity of CRPS. PMID:21683929

Towards the understanding of network information processing in biology

NASA Astrophysics Data System (ADS)

Singh, Vijay

Living organisms perform incredibly well in detecting a signal present in the environment. This information processing is achieved near optimally and quite reliably, even though the sources of signals are highly variable and complex. The work in the last few decades has given us a fair understanding of how individual signal processing units like neurons and cell receptors process signals, but the principles of collective information processing on biological networks are far from clear. Information processing in biological networks, like the brain, metabolic circuits, cellular-signaling circuits, etc., involves complex interactions among a large number of units (neurons, receptors). The combinatorially large number of states such a system can exist in makes it impossible to study these systems from the first principles, starting from the interactions between the basic units. The principles of collective information processing on such complex networks can be identified using coarse graining approaches. This could provide insights into the organization and function of complex biological networks. Here I study models of biological networks using continuum dynamics, renormalization, maximum likelihood estimation and information theory. Such coarse graining approaches identify features that are essential for certain processes performed by underlying biological networks. We find that long-range connections in the brain allow for global scale feature detection in a signal. These also suppress the noise and remove any gaps present in the signal. Hierarchical organization with long-range connections leads to large-scale connectivity at low synapse numbers. Time delays can be utilized to separate a mixture of signals with temporal scales. Our observations indicate that the rules in multivariate signal processing are quite different from traditional single unit signal processing.

Agent-based model of angiogenesis simulates capillary sprout initiation in multicellular networks

PubMed Central

Walpole, J.; Chappell, J.C.; Cluceru, J.G.; Mac Gabhann, F.; Bautch, V.L.; Peirce, S. M.

2015-01-01

Many biological processes are controlled by both deterministic and stochastic influences. However, efforts to model these systems often rely on either purely stochastic or purely rule-based methods. To better understand the balance between stochasticity and determinism in biological processes a computational approach that incorporates both influences may afford additional insight into underlying biological mechanisms that give rise to emergent system properties. We apply a combined approach to the simulation and study of angiogenesis, the growth of new blood vessels from existing networks. This complex multicellular process begins with selection of an initiating endothelial cell, or tip cell, which sprouts from the parent vessels in response to stimulation by exogenous cues. We have constructed an agent-based model of sprouting angiogenesis to evaluate endothelial cell sprout initiation frequency and location, and we have experimentally validated it using high-resolution time-lapse confocal microscopy. ABM simulations were then compared to a Monte Carlo model, revealing that purely stochastic simulations could not generate sprout locations as accurately as the rule-informed agent-based model. These findings support the use of rule-based approaches for modeling the complex mechanisms underlying sprouting angiogenesis over purely stochastic methods. PMID:26158406

Agent-based model of angiogenesis simulates capillary sprout initiation in multicellular networks.

PubMed

Walpole, J; Chappell, J C; Cluceru, J G; Mac Gabhann, F; Bautch, V L; Peirce, S M

2015-09-01

Many biological processes are controlled by both deterministic and stochastic influences. However, efforts to model these systems often rely on either purely stochastic or purely rule-based methods. To better understand the balance between stochasticity and determinism in biological processes a computational approach that incorporates both influences may afford additional insight into underlying biological mechanisms that give rise to emergent system properties. We apply a combined approach to the simulation and study of angiogenesis, the growth of new blood vessels from existing networks. This complex multicellular process begins with selection of an initiating endothelial cell, or tip cell, which sprouts from the parent vessels in response to stimulation by exogenous cues. We have constructed an agent-based model of sprouting angiogenesis to evaluate endothelial cell sprout initiation frequency and location, and we have experimentally validated it using high-resolution time-lapse confocal microscopy. ABM simulations were then compared to a Monte Carlo model, revealing that purely stochastic simulations could not generate sprout locations as accurately as the rule-informed agent-based model. These findings support the use of rule-based approaches for modeling the complex mechanisms underlying sprouting angiogenesis over purely stochastic methods.

The complexity of silk under the spotlight of synthetic biology.

PubMed

Vollrath, Fritz

2016-08-15

For centuries silkworm filaments have been the focus of R&D innovation centred on textile manufacture with high added value. Most recently, silk research has focused on more fundamental issues concerning bio-polymer structure-property-function relationships. This essay outlines the complexity and fundamentals of silk spinning, and presents arguments for establishing this substance as an interesting and important subject at the interface of systems biology (discovery) and synthetic biology (translation). It is argued that silk is a generic class of materials where each type of silk presents a different embodiment of emergent properties that combine genetically determined (anticipatory) and environmentally responsive components. In spiders' webs the various silks have evolved to form the interactive components of an intricate fabric that provides an extended phenotype to the spider's body morphology. © 2016 The Author(s). published by Portland Press Limited on behalf of the Biochemical Society.

Systems Proteomics for Translational Network Medicine

PubMed Central

Arrell, D. Kent; Terzic, Andre

2012-01-01

Universal principles underlying network science, and their ever-increasing applications in biomedicine, underscore the unprecedented capacity of systems biology based strategies to synthesize and resolve massive high throughput generated datasets. Enabling previously unattainable comprehension of biological complexity, systems approaches have accelerated progress in elucidating disease prediction, progression, and outcome. Applied to the spectrum of states spanning health and disease, network proteomics establishes a collation, integration, and prioritization algorithm to guide mapping and decoding of proteome landscapes from large-scale raw data. Providing unparalleled deconvolution of protein lists into global interactomes, integrative systems proteomics enables objective, multi-modal interpretation at molecular, pathway, and network scales, merging individual molecular components, their plurality of interactions, and functional contributions for systems comprehension. As such, network systems approaches are increasingly exploited for objective interpretation of cardiovascular proteomics studies. Here, we highlight network systems proteomic analysis pipelines for integration and biological interpretation through protein cartography, ontological categorization, pathway and functional enrichment and complex network analysis. PMID:22896016

Ranking Enzyme Structures in the PDB by Bound Ligand Similarity to Biological Substrates.

PubMed

Tyzack, Jonathan D; Fernando, Laurent; Ribeiro, Antonio J M; Borkakoti, Neera; Thornton, Janet M

2018-04-03

There are numerous applications that use the structures of protein-ligand complexes from the PDB, such as 3D pharmacophore identification, virtual screening, and fragment-based drug design. The structures underlying these applications are potentially much more informative if they contain biologically relevant bound ligands, with high similarity to the cognate ligands. We present a study of ligand-enzyme complexes that compares the similarity of bound and cognate ligands, enabling the best matches to be identified. We calculate the molecular similarity scores using a method called PARITY (proportion of atoms residing in identical topology), which can conveniently be combined to give a similarity score for all cognate reactants or products in the reaction. Thus, we generate a rank-ordered list of related PDB structures, according to the biological similarity of the ligands bound in the structures. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

Searching and Mining Visually Observed Phenotypes of Maize Mutants

USDA-ARS?s Scientific Manuscript database

There are thousands of maize mutants, which are invaluable resources for plant research. Geneticists use them to study underlying mechanisms of biochemistry, cell biology, cell development, and cell physiology. To streamline the understanding of such complex processes, researchers need the most curr...

Human cumulative culture: a comparative perspective.

PubMed

Dean, Lewis G; Vale, Gill L; Laland, Kevin N; Flynn, Emma; Kendal, Rachel L

2014-05-01

Many animals exhibit social learning and behavioural traditions, but human culture exhibits unparalleled complexity and diversity, and is unambiguously cumulative in character. These similarities and differences have spawned a debate over whether animal traditions and human culture are reliant on homologous or analogous psychological processes. Human cumulative culture combines high-fidelity transmission of cultural knowledge with beneficial modifications to generate a 'ratcheting' in technological complexity, leading to the development of traits far more complex than one individual could invent alone. Claims have been made for cumulative culture in several species of animals, including chimpanzees, orangutans and New Caledonian crows, but these remain contentious. Whilst initial work on the topic of cumulative culture was largely theoretical, employing mathematical methods developed by population biologists, in recent years researchers from a wide range of disciplines, including psychology, biology, economics, biological anthropology, linguistics and archaeology, have turned their attention to the experimental investigation of cumulative culture. We review this literature, highlighting advances made in understanding the underlying processes of cumulative culture and emphasising areas of agreement and disagreement amongst investigators in separate fields. © 2013 The Authors. Biological Reviews © 2013 Cambridge Philosophical Society.

Near-optimal experimental design for model selection in systems biology.

PubMed

Busetto, Alberto Giovanni; Hauser, Alain; Krummenacher, Gabriel; Sunnåker, Mikael; Dimopoulos, Sotiris; Ong, Cheng Soon; Stelling, Jörg; Buhmann, Joachim M

2013-10-15

Biological systems are understood through iterations of modeling and experimentation. Not all experiments, however, are equally valuable for predictive modeling. This study introduces an efficient method for experimental design aimed at selecting dynamical models from data. Motivated by biological applications, the method enables the design of crucial experiments: it determines a highly informative selection of measurement readouts and time points. We demonstrate formal guarantees of design efficiency on the basis of previous results. By reducing our task to the setting of graphical models, we prove that the method finds a near-optimal design selection with a polynomial number of evaluations. Moreover, the method exhibits the best polynomial-complexity constant approximation factor, unless P = NP. We measure the performance of the method in comparison with established alternatives, such as ensemble non-centrality, on example models of different complexity. Efficient design accelerates the loop between modeling and experimentation: it enables the inference of complex mechanisms, such as those controlling central metabolic operation. Toolbox 'NearOED' available with source code under GPL on the Machine Learning Open Source Software Web site (mloss.org).

Microwave gallium-68 radiochemistry for kinetically stable bis(thiosemicarbazone) complexes: structural investigations and cellular uptake under hypoxia† †Electronic supplementary information (ESI) available. CCDC 1001632–1001634. For ESI and crystallographic data in CIF or other electronic format see DOI: 10.1039/c5dt02537k Click here for additional data file. Click here for additional data file.

PubMed Central

Alam, Israt S.; Arrowsmith, Rory L.; Cortezon-Tamarit, Fernando; Twyman, Frazer; Kociok-Köhn, Gabriele; Botchway, Stanley W.; Dilworth, Jonathan R.

2016-01-01

We report the microwave synthesis of several bis(thiosemicarbazones) and the rapid gallium-68 incorporation to give the corresponding metal complexes. These proved kinetically stable under ‘cold’ and ‘hot’ biological assays and were investigated using laser scanning confocal microscopy, flow cytometry and radioactive cell retention studies under normoxia and hypoxia. 68Ga complex retention was found to be 34% higher in hypoxic cells than in normoxic cells over 30 min, further increasing to 53% at 120 min. Our data suggests that this class of gallium complexes show hypoxia selectivity suitable for imaging in living cells and in vivo tests by microPET in nude athymic mice showed that they are excreted within 1 h of their administration. PMID:26583314

Directional Bleb Formation in Spherical Cells under Temperature Gradient

PubMed Central

Oyama, Kotaro; Arai, Tomomi; Isaka, Akira; Sekiguchi, Taku; Itoh, Hideki; Seto, Yusuke; Miyazaki, Makito; Itabashi, Takeshi; Ohki, Takashi; Suzuki, Madoka; Ishiwata, Shin'ichi

2015-01-01

Living cells sense absolute temperature and temporal changes in temperature using biological thermosensors such as ion channels. Here, we reveal, to our knowledge, a novel mechanism of sensing spatial temperature gradients within single cells. Spherical mitotic cells form directional membrane extensions (polar blebs) under sharp temperature gradients (≥∼0.065°C μm−1; 1.3°C temperature difference within a cell), which are created by local heating with a focused 1455-nm laser beam under an optical microscope. On the other hand, multiple nondirectional blebs are formed under gradual temperature gradients or uniform heating. During heating, the distribution of actomyosin complexes becomes inhomogeneous due to a break in the symmetry of its contractile force, highlighting the role of the actomyosin complex as a sensor of local temperature gradients. PMID:26200871

Asymmetric vinylogous Mukaiyama aldol reaction of isatins under bifunctional organocatalysis: enantioselective synthesis of substituted 3-hydroxy-2-oxindoles.

PubMed

Laina-Martín, Víctor; Humbrías-Martín, Jorge; Fernández-Salas, José A; Alemán, José

2018-03-13

A highly enantioselective organocatalytic vinylogous Mukaiyama aldol reaction of silyloxy dienes and isatins under bifunctional organocatalysis is presented. Substituted 3-hydroxy-2-oxindoles are synthesised in good yields and enantioselectivities. These synthetic intermediates are used for the construction of more complex molecules with biological properties such as the formal synthesis of a CB2 agonist presented.

Deconstructing sexual orientation: understanding the phenomena of sexual orientation.

PubMed

Stein, T S

1997-01-01

The very terms of a debate about whether or not sexual orientation is primarily a biological phenomenon fail to consider the complex origins of the phenomenon. Deconstruction of the term "homosexuality" shows that it refers to multiple factors which cannot be studied as or subsumed under a unitary concept. Adequate understanding of sexual orientation must consider the developmental, interpersonal, experiential, and cultural dimensions of sexuality, as well as any biological contributions to sexual attraction, behavior, and identity.

Complex of solonetzes and vertic chestnut soils in the manych-gudilo depression

NASA Astrophysics Data System (ADS)

Kovda, I. V.; Morgun, E. P.; Il'ina, L. P.

2013-01-01

Morphological, physicochemical, and isotopic properties of a two-member soil complex developed under dry steppe have been studied in the central part of the Manych Depression. The soils are formed on chocolate-colored clayey sediments, and have pronounced microrelief and the complex vegetation pattern. A specific feature of the studied soil complex is the inverse position of its components: vertic chestnut soil occupies the microhigh, while solonetz is in the microlow. The formation of such complexes is explained by the biological factor, i.e., by the destruction of the solonetzic horizon under the impact of vegetation and earth-burrowing animals with further transformation under steppe plants and dealkalinization of the soil in the microhighs. The manifestation of vertic features and shrink-swell process in soils of the complex developing in dry steppe are compared with those in the vertic soils of the Central Pre-Caucasus formed under more humid environment. It is supposed that slickensides in the investigated vertic chestnut soil are relict feature inherited from the former wetter stage of the soil development and are subjected to a gradual degradation at present. In the modern period, vertic processes are weak and cannot be distinctly diagnosed. However, their activation may take place upon an increase of precipitation or the rise in the groundwater level.

Atypical behavior in the electron capture induced dissociation of biologically relevant transition metal ion complexes of the peptide hormone oxytocin

NASA Astrophysics Data System (ADS)

Kleinnijenhuis, Anne J.; Mihalca, Romulus; Heeren, Ron M. A.; Heck, Albert J. R.

2006-07-01

Doubly protonated ions of the disulfide bond containing nonapeptide hormone oxytocin and oxytocin complexes with different transition metal ions, that have biological relevance under physiological conditions, were subjected to electron capture dissociation (ECD) to probe their structural features in the gas phase. Although, all the ECD spectra were strikingly different, typical ECD behavior was observed for complexes of the nonapeptide hormone oxytocin with Ni2+, Co2+ and Zn2+, i.e., abundant c/z' and a'/y backbone cleavages and ECD characteristic S-S and S-C bond cleavages were observed. We propose that, although in the oxytocin-transition metal ion complexes the metal ions serve as the main initial capture site, the captured electron is transferred to other sites in the complex to form a hydrogen radical, which drives the subsequent typical ECD fragmentations. The complex of oxytocin with Cu2+ displayed noticeably different ECD behavior. The fragment ions were similar to fragment ions typically observed with low-energy collision induced dissociation (CID). We propose that the electrons captured by the oxytocin-Cu2+ complex might be favorably involved in reducing the Cu2+ metal ion to Cu+. Subsequent energy redistribution would explain the observed low-energy CID-type fragmentations. Electron capture resulted also in quite different specific cleavage sites for the complexes of oxytocin with Ni2+, Co2+ and Zn2+. This is an indication for structural differences in these complexes possibly linked to their significantly different biological effects on oxytocin-receptor binding, and suggests that ECD may be used to study subtle structural differences in transition metal ion-peptide complexes.

Biological Recovery of Platinum Complexes from Diluted Aqueous Streams by Axenic Cultures

PubMed Central

Maes, Synthia; Props, Ruben; Fitts, Jeffrey P.; De Smet, Rebecca; Vanhaecke, Frank; Boon, Nico; Hennebel, Tom

2017-01-01

The widespread use of platinum in high-tech and catalytic applications has led to the production of diverse Pt loaded wastewaters. Effective recovery strategies are needed for the treatment of low concentrated waste streams to prevent pollution and to stimulate recovery of this precious resource. The biological recovery of five common environmental Pt-complexes was studied under acidic conditions; the chloro-complexes PtCl42- and PtCl62-, the amine-complex Pt(NH3)4Cl2 and the pharmaceutical complexes cisplatin and carboplatin. Five bacterial species were screened on their platinum recovery potential; the Gram-negative species Shewanella oneidensis MR-1, Cupriavidus metallidurans CH34, Geobacter metallireducens, and Pseudomonas stutzeri, and the Gram-positive species Bacillus toyonensis. Overall, PtCl42- and PtCl62- were completely recovered by all bacterial species while only S. oneidensis and C. metallidurans were able to recover cisplatin quantitatively (99%), all in the presence of H2 as electron donor at pH 2. Carboplatin was only partly recovered (max. 25% at pH 7), whereas no recovery was observed in the case of the Pt-tetraamine complex. Transmission electron microscopy (TEM) revealed the presence of both intra- and extracellular platinum particles. Flow cytometry based microbial viability assessment demonstrated the decrease in number of intact bacterial cells during platinum reduction and indicated C. metallidurans to be the most resistant species. This study showed the effective and complete biological recovery of three common Pt-complexes, and estimated the fate and transport of the Pt-complexes in wastewater treatment plants and the natural environment. PMID:28046131

Biological Recovery of Platinum Complexes from Diluted Aqueous Streams by Axenic Cultures.

PubMed

Maes, Synthia; Props, Ruben; Fitts, Jeffrey P; De Smet, Rebecca; Vanhaecke, Frank; Boon, Nico; Hennebel, Tom

2017-01-01

The widespread use of platinum in high-tech and catalytic applications has led to the production of diverse Pt loaded wastewaters. Effective recovery strategies are needed for the treatment of low concentrated waste streams to prevent pollution and to stimulate recovery of this precious resource. The biological recovery of five common environmental Pt-complexes was studied under acidic conditions; the chloro-complexes PtCl42- and PtCl62-, the amine-complex Pt(NH3)4Cl2 and the pharmaceutical complexes cisplatin and carboplatin. Five bacterial species were screened on their platinum recovery potential; the Gram-negative species Shewanella oneidensis MR-1, Cupriavidus metallidurans CH34, Geobacter metallireducens, and Pseudomonas stutzeri, and the Gram-positive species Bacillus toyonensis. Overall, PtCl42- and PtCl62- were completely recovered by all bacterial species while only S. oneidensis and C. metallidurans were able to recover cisplatin quantitatively (99%), all in the presence of H2 as electron donor at pH 2. Carboplatin was only partly recovered (max. 25% at pH 7), whereas no recovery was observed in the case of the Pt-tetraamine complex. Transmission electron microscopy (TEM) revealed the presence of both intra- and extracellular platinum particles. Flow cytometry based microbial viability assessment demonstrated the decrease in number of intact bacterial cells during platinum reduction and indicated C. metallidurans to be the most resistant species. This study showed the effective and complete biological recovery of three common Pt-complexes, and estimated the fate and transport of the Pt-complexes in wastewater treatment plants and the natural environment.

Ammonia formation by a thiolate-bridged diiron amide complex as a nitrogenase mimic

NASA Astrophysics Data System (ADS)

Li, Yang; Li, Ying; Wang, Baomin; Luo, Yi; Yang, Dawei; Tong, Peng; Zhao, Jinfeng; Luo, Lun; Zhou, Yuhan; Chen, Si; Cheng, Fang; Qu, Jingping

2013-04-01

Although nitrogenase enzymes routinely convert molecular nitrogen into ammonia under ambient temperature and pressure, this reaction is currently carried out industrially using the Haber-Bosch process, which requires extreme temperatures and pressures to activate dinitrogen. Biological fixation occurs through dinitrogen and reduced NxHy species at multi-iron centres of compounds bearing sulfur ligands, but it is difficult to elucidate the mechanistic details and to obtain stable model intermediate complexes for further investigation. Metal-based synthetic models have been applied to reveal partial details, although most models involve a mononuclear system. Here, we report a diiron complex bridged by a bidentate thiolate ligand that can accommodate HN=NH. Following reductions and protonations, HN=NH is converted to NH3 through pivotal intermediate complexes bridged by N2H3- and NH2- species. Notably, the final ammonia release was effected with water as the proton source. Density functional theory calculations were carried out, and a pathway of biological nitrogen fixation is proposed.

Design, synthesis, and biological evaluation of air-stable nafuredin-γ analogs as complex I inhibitors.

PubMed

Ohtawa, Masaki; Matsunaga, Mari; Fukunaga, Keiko; Shimizu, Risa; Shimizu, Eri; Arima, Shiho; Ohmori, Junko; Kita, Kiyoshi; Shiomi, Kazuro; Omura, Satoshi; Nagamitsu, Tohru

2015-03-01

Nafuredin-γ (2), converted from nafuredin (1) under mild basic conditions, demonstrates potent and selective inhibitory activity against helminth complex I. However, 2 is unstable in air because the conjugated dienes are oxygen-labile. To address this, we designed and synthesized air-stable nafuredin-γ analogs. Although the complex I inhibitory activities of all the new nafuredin-γ analogs were lower than that of 2, all were in the high nM range (IC50: 300-820nM). Copyright © 2015 Elsevier Ltd. All rights reserved.

Evolutionary Models for Simple Biosystems

NASA Astrophysics Data System (ADS)

Bagnoli, Franco

The concept of evolutionary development of structures constituted a real revolution in biology: it was possible to understand how the very complex structures of life can arise in an out-of-equilibrium system. The investigation of such systems has shown that indeed, systems under a flux of energy or matter can self-organize into complex patterns, think for instance to Rayleigh-Bernard convection, Liesegang rings, patterns formed by granular systems under shear. Following this line, one could characterize life as a state of matter, characterized by the slow, continuous process that we call evolution. In this paper we try to identify the organizational level of life, that spans several orders of magnitude from the elementary constituents to whole ecosystems. Although similar structures can be found in other contexts like ideas (memes) in neural systems and self-replicating elements (computer viruses, worms, etc.) in computer systems, we shall concentrate on biological evolutionary structure, and try to put into evidence the role and the emergence of network structure in such systems.

Demonstration of correlative atomic force and transmission electron microscopy using actin cytoskeleton

PubMed Central

Yamada, Yutaro; Konno, Hiroki; Shimabukuro, Katsuya

2017-01-01

In this study, we present a new technique called correlative atomic force and transmission electron microscopy (correlative AFM/TEM) in which a targeted region of a sample can be observed under AFM and TEM. The ultimate goal of developing this new technique is to provide a technical platform to expand the fields of AFM application to complex biological systems such as cell extracts. Recent advances in the time resolution of AFM have enabled detailed observation of the dynamic nature of biomolecules. However, specifying molecular species, by AFM alone, remains a challenge. Here, we demonstrate correlative AFM/TEM, using actin filaments as a test sample, and further show that immuno-electron microscopy (immuno-EM), to specify molecules, can be integrated into this technique. Therefore, it is now possible to specify molecules, captured under AFM, by subsequent observation using immuno-EM. In conclusion, correlative AFM/TEM can be a versatile method to investigate complex biological systems at the molecular level. PMID:28828286

Biological control of appetite: A daunting complexity.

PubMed

MacLean, Paul S; Blundell, John E; Mennella, Julie A; Batterham, Rachel L

2017-03-01

This review summarizes a portion of the discussions of an NIH Workshop (Bethesda, MD, 2015) titled "Self-Regulation of Appetite-It's Complicated," which focused on the biological aspects of appetite regulation. This review summarizes the key biological inputs of appetite regulation and their implications for body weight regulation. These discussions offer an update of the long-held, rigid perspective of an "adipocentric" biological control, taking a broader view that also includes important inputs from the digestive tract, from lean mass, and from the chemical sensory systems underlying taste and smell. It is only beginning to be understood how these biological systems are integrated and how this integrated input influences appetite and food eating behaviors. The relevance of these biological inputs was discussed primarily in the context of obesity and the problem of weight regain, touching on topics related to the biological predisposition for obesity and the impact that obesity treatments (dieting, exercise, bariatric surgery, etc.) might have on appetite and weight loss maintenance. Finally considered is a common theme that pervaded the workshop discussions, which was individual variability. It is this individual variability in the predisposition for obesity and in the biological response to weight loss that makes the biological component of appetite regulation so complicated. When this individual biological variability is placed in the context of the diverse environmental and behavioral pressures that also influence food eating behaviors, it is easy to appreciate the daunting complexities that arise with the self-regulation of appetite. © 2017 The Obesity Society.

Biological Control of Appetite: A Daunting Complexity

PubMed Central

MacLean, Paul S.; Blundell, John E.; Mennella, Julie A.; Batterham, Rachel L.

2017-01-01

Objective This review summarizes a portion of the discussions of an NIH Workshop (Bethesda, MD, 2015) entitled, “Self-Regulation of Appetite, It's Complicated,” which focused on the biological aspects of appetite regulation. Methods Here we summarize the key biological inputs of appetite regulation and their implications for body weight regulation. Results These discussions offer an update of the long-held, rigid perspective of an “adipocentric” biological control, taking a broader view that also includes important inputs from the digestive tract, from lean mass, and from the chemical sensory systems underlying taste and smell. We are only beginning to understand how these biological systems are integrated and how this integrated input influences appetite and food eating behaviors. The relevance of these biological inputs was discussed primarily in the context of obesity and the problem of weight regain, touching on topics related to the biological predisposition for obesity and the impact that obesity treatments (dieting, exercise, bariatric surgery, etc.) might have on appetite and weight loss maintenance. Finally, we consider a common theme that pervaded the workshop discussions, which was individual variability. Conclusions It is this individual variability in the predisposition for obesity and in the biological response to weight loss that makes the biological component of appetite regulation so complicated. When this individual biological variability is placed in the context of the diverse environmental and behavioral pressures that also influence food eating behaviors, it is easy to appreciate the daunting complexities that arise with the self-regulation of appetite. PMID:28229538

Mercury reduction and complexation by natural organic matter in anoxic environments.

PubMed

Gu, Baohua; Bian, Yongrong; Miller, Carrie L; Dong, Wenming; Jiang, Xin; Liang, Liyuan

2011-01-25

Mercuric Hg(II) species form complexes with natural dissolved organic matter (DOM) such as humic acid (HA), and this binding is known to affect the chemical and biological transformation and cycling of mercury in aquatic environments. Dissolved elemental mercury, Hg(0), is also widely observed in sediments and water. However, reactions between Hg(0) and DOM have rarely been studied in anoxic environments. Here, under anoxic dark conditions we show strong interactions between reduced HA and Hg(0) through thiolate ligand-induced oxidative complexation with an estimated binding capacity of ~3.5 μmol Hg/g HA and a partitioning coefficient >10(6) mL/g. We further demonstrate that Hg(II) can be effectively reduced to Hg(0) in the presence of as little as 0.2 mg/L reduced HA, whereas production of Hg(0) is inhibited by complexation as HA concentration increases. This dual role played by DOM in the reduction and complexation of mercury is likely widespread in anoxic sediments and water and can be expected to significantly influence the mercury species transformations and biological uptake that leads to the formation of toxic methylmercury.

Information processing in bacteria: memory, computation, and statistical physics: a key issues review

NASA Astrophysics Data System (ADS)

Lan, Ganhui; Tu, Yuhai

2016-05-01

Living systems have to constantly sense their external environment and adjust their internal state in order to survive and reproduce. Biological systems, from as complex as the brain to a single E. coli cell, have to process these data in order to make appropriate decisions. How do biological systems sense external signals? How do they process the information? How do they respond to signals? Through years of intense study by biologists, many key molecular players and their interactions have been identified in different biological machineries that carry out these signaling functions. However, an integrated, quantitative understanding of the whole system is still lacking for most cellular signaling pathways, not to say the more complicated neural circuits. To study signaling processes in biology, the key thing to measure is the input-output relationship. The input is the signal itself, such as chemical concentration, external temperature, light (intensity and frequency), and more complex signals such as the face of a cat. The output can be protein conformational changes and covalent modifications (phosphorylation, methylation, etc), gene expression, cell growth and motility, as well as more complex output such as neuron firing patterns and behaviors of higher animals. Due to the inherent noise in biological systems, the measured input-output dependence is often noisy. These noisy data can be analysed by using powerful tools and concepts from information theory such as mutual information, channel capacity, and the maximum entropy hypothesis. This information theory approach has been successfully used to reveal the underlying correlations between key components of biological networks, to set bounds for network performance, and to understand possible network architecture in generating observed correlations. Although the information theory approach provides a general tool in analysing noisy biological data and may be used to suggest possible network architectures in preserving information, it does not reveal the underlying mechanism that leads to the observed input-output relationship, nor does it tell us much about which information is important for the organism and how biological systems use information to carry out specific functions. To do that, we need to develop models of the biological machineries, e.g. biochemical networks and neural networks, to understand the dynamics of biological information processes. This is a much more difficult task. It requires deep knowledge of the underlying biological network—the main players (nodes) and their interactions (links)—in sufficient detail to build a model with predictive power, as well as quantitative input-output measurements of the system under different perturbations (both genetic variations and different external conditions) to test the model predictions to guide further development of the model. Due to the recent growth of biological knowledge thanks in part to high throughput methods (sequencing, gene expression microarray, etc) and development of quantitative in vivo techniques such as various florescence technology, these requirements are starting to be realized in different biological systems. The possible close interaction between quantitative experimentation and theoretical modeling has made systems biology an attractive field for physicists interested in quantitative biology. In this review, we describe some of the recent work in developing a quantitative predictive model of bacterial chemotaxis, which can be considered as the hydrogen atom of systems biology. Using statistical physics approaches, such as the Ising model and Langevin equation, we study how bacteria, such as E. coli, sense and amplify external signals, how they keep a working memory of the stimuli, and how they use these data to compute the chemical gradient. In particular, we will describe how E. coli cells avoid cross-talk in a heterogeneous receptor cluster to keep a ligand-specific memory. We will also study the thermodynamic costs of adaptation for cells to maintain an accurate memory. The statistical physics based approach described here should be useful in understanding design principles for cellular biochemical circuits in general.

Information processing in bacteria: memory, computation, and statistical physics: a key issues review.

PubMed

Lan, Ganhui; Tu, Yuhai

2016-05-01

Living systems have to constantly sense their external environment and adjust their internal state in order to survive and reproduce. Biological systems, from as complex as the brain to a single E. coli cell, have to process these data in order to make appropriate decisions. How do biological systems sense external signals? How do they process the information? How do they respond to signals? Through years of intense study by biologists, many key molecular players and their interactions have been identified in different biological machineries that carry out these signaling functions. However, an integrated, quantitative understanding of the whole system is still lacking for most cellular signaling pathways, not to say the more complicated neural circuits. To study signaling processes in biology, the key thing to measure is the input-output relationship. The input is the signal itself, such as chemical concentration, external temperature, light (intensity and frequency), and more complex signals such as the face of a cat. The output can be protein conformational changes and covalent modifications (phosphorylation, methylation, etc), gene expression, cell growth and motility, as well as more complex output such as neuron firing patterns and behaviors of higher animals. Due to the inherent noise in biological systems, the measured input-output dependence is often noisy. These noisy data can be analysed by using powerful tools and concepts from information theory such as mutual information, channel capacity, and the maximum entropy hypothesis. This information theory approach has been successfully used to reveal the underlying correlations between key components of biological networks, to set bounds for network performance, and to understand possible network architecture in generating observed correlations. Although the information theory approach provides a general tool in analysing noisy biological data and may be used to suggest possible network architectures in preserving information, it does not reveal the underlying mechanism that leads to the observed input-output relationship, nor does it tell us much about which information is important for the organism and how biological systems use information to carry out specific functions. To do that, we need to develop models of the biological machineries, e.g. biochemical networks and neural networks, to understand the dynamics of biological information processes. This is a much more difficult task. It requires deep knowledge of the underlying biological network-the main players (nodes) and their interactions (links)-in sufficient detail to build a model with predictive power, as well as quantitative input-output measurements of the system under different perturbations (both genetic variations and different external conditions) to test the model predictions to guide further development of the model. Due to the recent growth of biological knowledge thanks in part to high throughput methods (sequencing, gene expression microarray, etc) and development of quantitative in vivo techniques such as various florescence technology, these requirements are starting to be realized in different biological systems. The possible close interaction between quantitative experimentation and theoretical modeling has made systems biology an attractive field for physicists interested in quantitative biology. In this review, we describe some of the recent work in developing a quantitative predictive model of bacterial chemotaxis, which can be considered as the hydrogen atom of systems biology. Using statistical physics approaches, such as the Ising model and Langevin equation, we study how bacteria, such as E. coli, sense and amplify external signals, how they keep a working memory of the stimuli, and how they use these data to compute the chemical gradient. In particular, we will describe how E. coli cells avoid cross-talk in a heterogeneous receptor cluster to keep a ligand-specific memory. We will also study the thermodynamic costs of adaptation for cells to maintain an accurate memory. The statistical physics based approach described here should be useful in understanding design principles for cellular biochemical circuits in general.

Developing optimal input design strategies in cancer systems biology with applications to microfluidic device engineering.

PubMed

Menolascina, Filippo; Bellomo, Domenico; Maiwald, Thomas; Bevilacqua, Vitoantonio; Ciminelli, Caterina; Paradiso, Angelo; Tommasi, Stefania

2009-10-15

Mechanistic models are becoming more and more popular in Systems Biology; identification and control of models underlying biochemical pathways of interest in oncology is a primary goal in this field. Unfortunately the scarce availability of data still limits our understanding of the intrinsic characteristics of complex pathologies like cancer: acquiring information for a system understanding of complex reaction networks is time consuming and expensive. Stimulus response experiments (SRE) have been used to gain a deeper insight into the details of biochemical mechanisms underlying cell life and functioning. Optimisation of the input time-profile, however, still remains a major area of research due to the complexity of the problem and its relevance for the task of information retrieval in systems biology-related experiments. We have addressed the problem of quantifying the information associated to an experiment using the Fisher Information Matrix and we have proposed an optimal experimental design strategy based on evolutionary algorithm to cope with the problem of information gathering in Systems Biology. On the basis of the theoretical results obtained in the field of control systems theory, we have studied the dynamical properties of the signals to be used in cell stimulation. The results of this study have been used to develop a microfluidic device for the automation of the process of cell stimulation for system identification. We have applied the proposed approach to the Epidermal Growth Factor Receptor pathway and we observed that it minimises the amount of parametric uncertainty associated to the identified model. A statistical framework based on Monte-Carlo estimations of the uncertainty ellipsoid confirmed the superiority of optimally designed experiments over canonical inputs. The proposed approach can be easily extended to multiobjective formulations that can also take advantage of identifiability analysis. Moreover, the availability of fully automated microfluidic platforms explicitly developed for the task of biochemical model identification will hopefully reduce the effects of the 'data rich--data poor' paradox in Systems Biology.

Using protein-protein interactions for refining gene networks estimated from microarray data by Bayesian networks.

PubMed

Nariai, N; Kim, S; Imoto, S; Miyano, S

2004-01-01

We propose a statistical method to estimate gene networks from DNA microarray data and protein-protein interactions. Because physical interactions between proteins or multiprotein complexes are likely to regulate biological processes, using only mRNA expression data is not sufficient for estimating a gene network accurately. Our method adds knowledge about protein-protein interactions to the estimation method of gene networks under a Bayesian statistical framework. In the estimated gene network, a protein complex is modeled as a virtual node based on principal component analysis. We show the effectiveness of the proposed method through the analysis of Saccharomyces cerevisiae cell cycle data. The proposed method improves the accuracy of the estimated gene networks, and successfully identifies some biological facts.

New and improved proteomics technologies for understanding complex biological systems: Addressing a grand challenge in the life sciences

PubMed Central

Hood, Leroy E.; Omenn, Gilbert S.; Moritz, Robert L.; Aebersold, Ruedi; Yamamoto, Keith R.; Amos, Michael; Hunter-Cevera, Jennie; Locascio, Laurie

2014-01-01

This White Paper sets out a Life Sciences Grand Challenge for Proteomics Technologies to enhance our understanding of complex biological systems, link genomes with phenotypes, and bring broad benefits to the biosciences and the US economy. The paper is based on a workshop hosted by the National Institute of Standards and Technology (NIST) in Gaithersburg, MD, 14–15 February 2011, with participants from many federal R&D agencies and research communities, under the aegis of the US National Science and Technology Council (NSTC). Opportunities are identified for a coordinated R&D effort to achieve major technology-based goals and address societal challenges in health, agriculture, nutrition, energy, environment, national security, and economic development. PMID:22807061

Systems Biology-Driven Hypotheses Tested In Vivo: The Need to Advancing Molecular Imaging Tools.

PubMed

Verma, Garima; Palombo, Alessandro; Grigioni, Mauro; La Monaca, Morena; D'Avenio, Giuseppe

2018-01-01

Processing and interpretation of biological images may provide invaluable insights on complex, living systems because images capture the overall dynamics as a "whole." Therefore, "extraction" of key, quantitative morphological parameters could be, at least in principle, helpful in building a reliable systems biology approach in understanding living objects. Molecular imaging tools for system biology models have attained widespread usage in modern experimental laboratories. Here, we provide an overview on advances in the computational technology and different instrumentations focused on molecular image processing and analysis. Quantitative data analysis through various open source software and algorithmic protocols will provide a novel approach for modeling the experimental research program. Besides this, we also highlight the predictable future trends regarding methods for automatically analyzing biological data. Such tools will be very useful to understand the detailed biological and mathematical expressions under in-silico system biology processes with modeling properties.

Shared activity patterns arising at genetic susceptibility loci reveal underlying genomic and cellular architecture of human disease.

PubMed

Baillie, J Kenneth; Bretherick, Andrew; Haley, Christopher S; Clohisey, Sara; Gray, Alan; Neyton, Lucile P A; Barrett, Jeffrey; Stahl, Eli A; Tenesa, Albert; Andersson, Robin; Brown, J Ben; Faulkner, Geoffrey J; Lizio, Marina; Schaefer, Ulf; Daub, Carsten; Itoh, Masayoshi; Kondo, Naoto; Lassmann, Timo; Kawai, Jun; Mole, Damian; Bajic, Vladimir B; Heutink, Peter; Rehli, Michael; Kawaji, Hideya; Sandelin, Albin; Suzuki, Harukazu; Satsangi, Jack; Wells, Christine A; Hacohen, Nir; Freeman, Thomas C; Hayashizaki, Yoshihide; Carninci, Piero; Forrest, Alistair R R; Hume, David A

2018-03-01

Genetic variants underlying complex traits, including disease susceptibility, are enriched within the transcriptional regulatory elements, promoters and enhancers. There is emerging evidence that regulatory elements associated with particular traits or diseases share similar patterns of transcriptional activity. Accordingly, shared transcriptional activity (coexpression) may help prioritise loci associated with a given trait, and help to identify underlying biological processes. Using cap analysis of gene expression (CAGE) profiles of promoter- and enhancer-derived RNAs across 1824 human samples, we have analysed coexpression of RNAs originating from trait-associated regulatory regions using a novel quantitative method (network density analysis; NDA). For most traits studied, phenotype-associated variants in regulatory regions were linked to tightly-coexpressed networks that are likely to share important functional characteristics. Coexpression provides a new signal, independent of phenotype association, to enable fine mapping of causative variants. The NDA coexpression approach identifies new genetic variants associated with specific traits, including an association between the regulation of the OCT1 cation transporter and genetic variants underlying circulating cholesterol levels. NDA strongly implicates particular cell types and tissues in disease pathogenesis. For example, distinct groupings of disease-associated regulatory regions implicate two distinct biological processes in the pathogenesis of ulcerative colitis; a further two separate processes are implicated in Crohn's disease. Thus, our functional analysis of genetic predisposition to disease defines new distinct disease endotypes. We predict that patients with a preponderance of susceptibility variants in each group are likely to respond differently to pharmacological therapy. Together, these findings enable a deeper biological understanding of the causal basis of complex traits.

Shared activity patterns arising at genetic susceptibility loci reveal underlying genomic and cellular architecture of human disease

PubMed Central

Gray, Alan; Neyton, Lucile P. A.; Barrett, Jeffrey; Stahl, Eli A.; Tenesa, Albert; Andersson, Robin; Brown, J. Ben; Faulkner, Geoffrey J.; Lizio, Marina; Schaefer, Ulf; Daub, Carsten; Kondo, Naoto; Lassmann, Timo; Kawai, Jun; Kawaji, Hideya; Suzuki, Harukazu; Satsangi, Jack; Wells, Christine A.; Hacohen, Nir; Freeman, Thomas C.; Hayashizaki, Yoshihide; Forrest, Alistair R. R.; Hume, David A.

2018-01-01

Genetic variants underlying complex traits, including disease susceptibility, are enriched within the transcriptional regulatory elements, promoters and enhancers. There is emerging evidence that regulatory elements associated with particular traits or diseases share similar patterns of transcriptional activity. Accordingly, shared transcriptional activity (coexpression) may help prioritise loci associated with a given trait, and help to identify underlying biological processes. Using cap analysis of gene expression (CAGE) profiles of promoter- and enhancer-derived RNAs across 1824 human samples, we have analysed coexpression of RNAs originating from trait-associated regulatory regions using a novel quantitative method (network density analysis; NDA). For most traits studied, phenotype-associated variants in regulatory regions were linked to tightly-coexpressed networks that are likely to share important functional characteristics. Coexpression provides a new signal, independent of phenotype association, to enable fine mapping of causative variants. The NDA coexpression approach identifies new genetic variants associated with specific traits, including an association between the regulation of the OCT1 cation transporter and genetic variants underlying circulating cholesterol levels. NDA strongly implicates particular cell types and tissues in disease pathogenesis. For example, distinct groupings of disease-associated regulatory regions implicate two distinct biological processes in the pathogenesis of ulcerative colitis; a further two separate processes are implicated in Crohn’s disease. Thus, our functional analysis of genetic predisposition to disease defines new distinct disease endotypes. We predict that patients with a preponderance of susceptibility variants in each group are likely to respond differently to pharmacological therapy. Together, these findings enable a deeper biological understanding of the causal basis of complex traits. PMID:29494619

CPTC and NIST-sponsored Yeast Reference Material Now Publicly Available | Office of Cancer Clinical Proteomics Research

Cancer.gov

The yeast protein extract (RM8323) developed by National Institute of Standards and Technology (NIST) under the auspices of NCI's CPTC initiative is currently available to the public at https://www-s.nist.gov/srmors/view_detail.cfm?srm=8323. The yeast proteome offers researchers a unique biological reference material. RM8323 is the most extensively characterized complex biological proteome and the only one associated with several large-scale studies to estimate protein abundance across a wide concentration range.

Bayesian approach to MSD-based analysis of particle motion in live cells.

PubMed

Monnier, Nilah; Guo, Syuan-Ming; Mori, Masashi; He, Jun; Lénárt, Péter; Bathe, Mark

2012-08-08

Quantitative tracking of particle motion using live-cell imaging is a powerful approach to understanding the mechanism of transport of biological molecules, organelles, and cells. However, inferring complex stochastic motion models from single-particle trajectories in an objective manner is nontrivial due to noise from sampling limitations and biological heterogeneity. Here, we present a systematic Bayesian approach to multiple-hypothesis testing of a general set of competing motion models based on particle mean-square displacements that automatically classifies particle motion, properly accounting for sampling limitations and correlated noise while appropriately penalizing model complexity according to Occam's Razor to avoid over-fitting. We test the procedure rigorously using simulated trajectories for which the underlying physical process is known, demonstrating that it chooses the simplest physical model that explains the observed data. Further, we show that computed model probabilities provide a reliability test for the downstream biological interpretation of associated parameter values. We subsequently illustrate the broad utility of the approach by applying it to disparate biological systems including experimental particle trajectories from chromosomes, kinetochores, and membrane receptors undergoing a variety of complex motions. This automated and objective Bayesian framework easily scales to large numbers of particle trajectories, making it ideal for classifying the complex motion of large numbers of single molecules and cells from high-throughput screens, as well as single-cell-, tissue-, and organism-level studies. Copyright © 2012 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Nanomaterial-microbe cross-talk: physicochemical principles and (patho)biological consequences.

PubMed

Westmeier, D; Hahlbrock, A; Reinhardt, C; Fröhlich-Nowoisky, J; Wessler, S; Vallet, C; Pöschl, U; Knauer, S K; Stauber, R H

2018-05-17

The applications of nanoparticles (NPs) are increasing exponentially in consumer products, biotechnology and biomedicine, and humans, as well as the environment, are increasingly being exposed to NPs. Analogously, various (pathogenic) microorganisms are present at all the major exposure and entry sites for NPs in the human body as well as in environmental habitats. However, the field has just started to explore the complex interplay between NPs and microbes and the (patho)biological consequences. Based on recent insights, herein, we critically reviewed the available knowledge about the interaction of NPs with microbes and the analytical investigations including the latest intravital imaging tools. We have commented on how the NPs' characteristics influence complex formation with microorganisms, presented the underlying physicochemical forces, and provided examples of how this knowledge can be used to rationally control the NP-microbe interaction. We concluded by discussing the role of the biomolecule corona in NP-microbe crosstalk and speculated the impact of NP-microbe complex formation on the (patho)biological outcome and fate of microbial pathogens. The presented insights will not only support the field in engineering NPs with improved anti-microbial activity but also stimulate research on the biomedical and toxicological relevance of nanomaterial-microbiome complex formation for the anthropocene in general.

The Electronic Guinea Pig.

ERIC Educational Resources Information Center

Angier, Natalie

1983-01-01

Scientists are designing computer models of biological systems, and of compounds with complex molecules, that can be used to get answers once obtainable only by sacrificing laboratory animals. Although most programs are still under development, some are in use by industrial/pharmaceutical companies. The programs and experiments they simulate are…

Hierarchical coordinate systems for understanding complexity and its evolution, with applications to genetic regulatory networks.

PubMed

Egri-Nagy, Attila; Nehaniv, Chrystopher L

2008-01-01

Beyond complexity measures, sometimes it is worthwhile in addition to investigate how complexity changes structurally, especially in artificial systems where we have complete knowledge about the evolutionary process. Hierarchical decomposition is a useful way of assessing structural complexity changes of organisms modeled as automata, and we show how recently developed computational tools can be used for this purpose, by computing holonomy decompositions and holonomy complexity. To gain insight into the evolution of complexity, we investigate the smoothness of the landscape structure of complexity under minimal transitions. As a proof of concept, we illustrate how the hierarchical complexity analysis reveals symmetries and irreversible structure in biological networks by applying the methods to the lac operon mechanism in the genetic regulatory network of Escherichia coli.

Concept Maps for Improved Science Reasoning and Writing: Complexity Isn't Everything.

PubMed

Dowd, Jason E; Duncan, Tanya; Reynolds, Julie A

2015-01-01

A pervasive notion in the literature is that complex concept maps reflect greater knowledge and/or more expert-like thinking than less complex concept maps. We show that concept maps used to structure scientific writing and clarify scientific reasoning do not adhere to this notion. In an undergraduate course for thesis writers, students use concept maps instead of traditional outlines to define the boundaries and scope of their research and to construct an argument for the significance of their research. Students generate maps at the beginning of the semester, revise after peer review, and revise once more at the end of the semester. Although some students revised their maps to make them more complex, a significant proportion of students simplified their maps. We found no correlation between increased complexity and improved scientific reasoning and writing skills, suggesting that sometimes students simplify their understanding as they develop more expert-like thinking. These results suggest that concept maps, when used as an intervention, can meet the varying needs of a diverse population of student writers. © 2015 J. E. Dowd et al. CBE—Life Sciences Education © 2015 The American Society for Cell Biology. This article is distributed by The American Society for Cell Biology under license from the author(s). It is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

Convolving engineering and medical pedagogies for training of tomorrow's health care professionals.

PubMed

Lee, Raphael C

2013-03-01

Several fundamental benefits justify why biomedical engineering and medicine should form a more convergent alliance, especially for the training of tomorrow's physicians and biomedical engineers. Herein, we review the rationale underlying the benefits. Biological discovery has advanced beyond the era of molecular biology well into today's era of molecular systems biology, which focuses on understanding the rules that govern the behavior of complex living systems. This has important medical implications. To realize cost-effective personalized medicine, it is necessary to translate the advances in molecular systems biology to higher levels of biological organization (organ, system, and organismal levels) and then to develop new medical therapeutics based on simulation and medical informatics analysis. Higher education in biological and medical sciences must adapt to a new set of training objectives. This will involve a shifting away from reductionist problem solving toward more integrative, continuum, and predictive modeling approaches which traditionally have been more associated with engineering science. Future biomedical engineers and MDs must be able to predict clinical response to therapeutic intervention. Medical education will involve engineering pedagogies, wherein basic governing rules of complex system behavior and skill sets in manipulating these systems to achieve a practical desired outcome are taught. Similarly, graduate biomedical engineering programs will include more practical exposure to clinical problem solving.

A biochemical network can control formation of a synthetic material by sensing numerous specific stimuli

NASA Astrophysics Data System (ADS)

Hun Yeon, Ju; Chan, Karen Y. T.; Wong, Ting-Chia; Chan, Kelvin; Sutherland, Michael R.; Ismagilov, Rustem F.; Pryzdial, Edward L. G.; Kastrup, Christian J.

2015-05-01

Developing bio-compatible smart materials that assemble in response to environmental cues requires strategies that can discriminate multiple specific stimuli in a complex milieu. Synthetic materials have yet to achieve this level of sensitivity, which would emulate the highly evolved and tailored reaction networks of complex biological systems. Here we show that the output of a naturally occurring network can be replaced with a synthetic material. Exploiting the blood coagulation system as an exquisite biological sensor, the fibrin clot end-product was replaced with a synthetic material under the biological control of a precisely regulated cross-linking enzyme. The functions of the coagulation network remained intact when the material was incorporated. Clot-like polymerization was induced in indirect response to distinct small molecules, phospholipids, enzymes, cells, viruses, an inorganic solid, a polyphenol, a polysaccharide, and a membrane protein. This strategy demonstrates for the first time that an existing stimulus-responsive biological network can be used to control the formation of a synthetic material by diverse classes of physiological triggers.

A Systems Biology Approach to Iron Metabolism

PubMed Central

Chifman, J.; Laubenbacher, R.; Torti, S.V.

2015-01-01

Iron is critical to the survival of almost all living organisms. However, inappropriately low or high levels of iron are detrimental and contribute to a wide range of diseases. Recent advances in the study of iron metabolism have revealed multiple intricate pathways that are essential to the maintenance of iron homeostasis. Further, iron regulation involves processes at several scales, ranging from the subcellular to the organismal. This complexity makes a systems biology approach crucial, with its enabling technology of computational models based on a mathematical description of regulatory systems. Systems biology may represent a new strategy for understanding imbalances in iron metabolism and their underlying causes. PMID:25480643

Osteosarcoma Genetics and Epigenetics: Emerging Biology and Candidate Therapies

PubMed Central

Morrow, James J.; Khanna, Chand

2016-01-01

Osteosarcoma is the most common primary malignancy of bone, typically presenting in the first or second decade of life. Unfortunately, clinical outcomes for osteosarcoma patients have not substantially improved in over 30 years. This stagnation in therapeutic advances is perhaps explained by the genetic, epigenetic, and biological complexities of this rare tumor. In this review we provide a general background on the biology of osteosarcoma and the clinical status quo. We go on to enumerate the genetic and epigenetic defects identified in osteosarcoma. Finally, we discuss ongoing large-scale studies in the field and potential new therapies that are currently under investigation. PMID:26349415

Biological Networks for Cancer Candidate Biomarkers Discovery

PubMed Central

Yan, Wenying; Xue, Wenjin; Chen, Jiajia; Hu, Guang

2016-01-01

Due to its extraordinary heterogeneity and complexity, cancer is often proposed as a model case of a systems biology disease or network disease. There is a critical need of effective biomarkers for cancer diagnosis and/or outcome prediction from system level analyses. Methods based on integrating omics data into networks have the potential to revolutionize the identification of cancer biomarkers. Deciphering the biological networks underlying cancer is undoubtedly important for understanding the molecular mechanisms of the disease and identifying effective biomarkers. In this review, the networks constructed for cancer biomarker discovery based on different omics level data are described and illustrated from recent advances in the field. PMID:27625573

Toward a Biology-Driven Treatment Strategy for Peripheral T-cell Lymphoma

PubMed Central

Hildyard, CAT; Shiekh, S; Browning, JAB; Collins, GP

2017-01-01

T-cell and natural killer–cell lymphomas are a relatively rare and heterogeneous group of diseases that are difficult to treat and usually have poor outcomes. To date, therapeutic interventions are of limited efficacy and there is a pressing need to find better treatments. In recent years, advances in molecular biology have helped to elucidate the underlying genetic complexity of this group of diseases and to identify mutations and signaling pathways involved in lymphomagenesis. In this review, we highlight the unique biological characteristics of some of the different subtypes and discuss how these may be targeted to provide more individualized and effective treatment approaches. PMID:28579857

Physical and biological mechanisms of nanosecond- and microsecond-pulsed FE-DBD plasma interaction with biological objects

NASA Astrophysics Data System (ADS)

Dobrynin, Danil

2013-09-01

Mechanisms of plasma interaction with living tissues and cells can be quite complex, owing to the complexity of both the plasma and the tissue. Thus, unification of all the mechanisms under one umbrella might not be possible. Here, analysis of interaction of floating electrode dielectric barrier discharge (FE-DBD) with living tissues and cells is presented and biological and physical mechanisms are discussed. In physical mechanisms, charged species are identified as the major contributors to the desired effect and a mechanism of this interaction is proposed. Biological mechanisms are also addressed and a hypothesis of plasma selectivity and its effects is offered. Spatially uniform nanosecond and sub-nanosecond short-pulsed dielectric barrier discharge plasmas are gaining popularity in biological and medical applications due to their increased uniformity, lower plasma temperature, lower surface power density, and higher concentration of the active species produced. In this presentation we will compare microsecond pulsed plasmas with nanosecond driven systems and their applications in biology and medicine with specific focus on wound healing and tissue regeneration. Transition from negative to positive streamer will be discussed with proposed hypothesis of uniformity mechanisms of positive streamer and the reduced dependence on morphology and surface chemistry of the second electrode (human body) being treated. Uniform plasma offers a more uniform delivery of active species to the tissue/surface being treated thus leading to better control over the biological results.

Identification of gene networks underlying dystocia in dairy cattle

USDA-ARS?s Scientific Manuscript database

Dystocia is a trait with a high impact in the dairy industry. Among its risk factors are calf weight, gestation length, breed and conformation. Biological networks have been proposed to capture the genetic architecture of complex traits, where GWAS show limitations. The objective of this study was t...

On the search for design principles in biological systems.

PubMed

Poyatos, Juan F

2012-01-01

The search for basic concepts and underlying principles was at the core of the systems approach to science and technology. This approach was somehow abandoned in mainstream biology after its initial proposal, due to the rise and success of molecular biology. This situation has changed. The accumulated knowledge of decades of molecular studies in combination with new technological advances, while further highlighting the intricacies of natural systems, is also bringing back the quest-for-principles research program. Here, I present two lessons that I derived from my own quest: the importance of studying biological information processing to identify common principles in seemingly unrelated contexts and the adequacy of using known design principles at one level of biological organization as a valuable tool to help recognizing principles at an alternative one. These and additional lessons should contribute to the ultimate goal of establishing principles able to integrate the many scales of biological complexity.

Extracting biomarkers of commitment to cancer development: potential role of vibrational spectroscopy in systems biology.

PubMed

Theophilou, Georgios; Paraskevaidi, Maria; Lima, Kássio M G; Kyrgiou, Maria; Martin-Hirsch, Pierre L; Martin, Francis L

2015-05-01

The complex processes driving cancer have so far impeded the discovery of dichotomous biomarkers associated with its initiation and progression. Reductionist approaches utilizing 'omics' technologies have met some success in identifying molecular alterations associated with carcinogenesis. Systems biology is an emerging science that combines high-throughput investigation techniques to define the dynamic interplay between regulatory biological systems in response to internal and external cues. Vibrational spectroscopy has the potential to play an integral role within systems biology research approaches. It is capable of examining global models of carcinogenesis by scrutinizing chemical bond alterations within molecules. The application of infrared or Raman spectroscopic approaches coupled with computational analysis under the systems biology umbrella can assist the transition of biomarker research from the molecular level to the system level. The comprehensive representation of carcinogenesis as a multilevel biological process will inevitably revolutionize cancer-related healthcare by personalizing risk prediction and prevention.

What is the evidence for the use of biologic or biosynthetic meshes in abdominal wall reconstruction?

PubMed

Köckerling, F; Alam, N N; Antoniou, S A; Daniels, I R; Famiglietti, F; Fortelny, R H; Heiss, M M; Kallinowski, F; Kyle-Leinhase, I; Mayer, F; Miserez, M; Montgomery, A; Morales-Conde, S; Muysoms, F; Narang, S K; Petter-Puchner, A; Reinpold, W; Scheuerlein, H; Smietanski, M; Stechemesser, B; Strey, C; Woeste, G; Smart, N J

2018-04-01

Although many surgeons have adopted the use of biologic and biosynthetic meshes in complex abdominal wall hernia repair, others have questioned the use of these products. Criticism is addressed in several review articles on the poor standard of studies reporting on the use of biologic meshes for different abdominal wall repairs. The aim of this consensus review is to conduct an evidence-based analysis of the efficacy of biologic and biosynthetic meshes in predefined clinical situations. A European working group, "BioMesh Study Group", composed of invited surgeons with a special interest in surgical meshes, formulated key questions, and forwarded them for processing in subgroups. In January 2016, a workshop was held in Berlin where the findings were presented, discussed, and voted on for consensus. Findings were set out in writing by the subgroups followed by consensus being reached. For the review, 114 studies and background analyses were used. The cumulative data regarding biologic mesh under contaminated conditions do not support the claim that it is better than synthetic mesh. Biologic mesh use should be avoided when bridging is needed. In inguinal hernia repair biologic and biosynthetic meshes do not have a clear advantage over the synthetic meshes. For prevention of incisional or parastomal hernias, there is no evidence to support the use of biologic/biosynthetic meshes. In complex abdominal wall hernia repairs (incarcerated hernia, parastomal hernia, infected mesh, open abdomen, enterocutaneous fistula, and component separation technique), biologic and biosynthetic meshes do not provide a superior alternative to synthetic meshes. The routine use of biologic and biosynthetic meshes cannot be recommended.

Darwinian evolution in the light of genomics

PubMed Central

Koonin, Eugene V.

2009-01-01

Comparative genomics and systems biology offer unprecedented opportunities for testing central tenets of evolutionary biology formulated by Darwin in the Origin of Species in 1859 and expanded in the Modern Synthesis 100 years later. Evolutionary-genomic studies show that natural selection is only one of the forces that shape genome evolution and is not quantitatively dominant, whereas non-adaptive processes are much more prominent than previously suspected. Major contributions of horizontal gene transfer and diverse selfish genetic elements to genome evolution undermine the Tree of Life concept. An adequate depiction of evolution requires the more complex concept of a network or ‘forest’ of life. There is no consistent tendency of evolution towards increased genomic complexity, and when complexity increases, this appears to be a non-adaptive consequence of evolution under weak purifying selection rather than an adaptation. Several universals of genome evolution were discovered including the invariant distributions of evolutionary rates among orthologous genes from diverse genomes and of paralogous gene family sizes, and the negative correlation between gene expression level and sequence evolution rate. Simple, non-adaptive models of evolution explain some of these universals, suggesting that a new synthesis of evolutionary biology might become feasible in a not so remote future. PMID:19213802

Disease signatures for schizophrenia and bipolar disorder using patient-derived induced pluripotent stem cells.

PubMed

Watmuff, Bradley; Berkovitch, Shaunna S; Huang, Joanne H; Iaconelli, Jonathan; Toffel, Steven; Karmacharya, Rakesh

2016-06-01

Schizophrenia and bipolar disorder are complex psychiatric disorders that present unique challenges in the study of disease biology. There are no objective biological phenotypes for these disorders, which are characterized by complex genetics and prominent roles for gene-environment interactions. The study of the neurobiology underlying these severe psychiatric disorders has been hindered by the lack of access to the tissue of interest - neurons from patients. The advent of reprogramming methods that enable generation of induced pluripotent stem cells (iPSCs) from patient fibroblasts and peripheral blood mononuclear cells has opened possibilities for new approaches to study relevant disease biology using iPSC-derived neurons. While early studies with patient iPSCs have led to promising and intriguing leads, significant hurdles remain in our attempts to capture the complexity of these disorders in vitro. We present here an overview of studies to date of schizophrenia and bipolar disorder using iPSC-derived neuronal cells and discuss potential future directions that can result in the identification of robust and valid cellular phenotypes that in turn can lay the groundwork for meaningful clinical advances. Copyright © 2016 Elsevier Inc. All rights reserved.

Protonation free energy levels in complex molecular systems.

PubMed

Antosiewicz, Jan M

2008-04-01

All proteins, nucleic acids, and other biomolecules contain residues capable of exchanging protons with their environment. These proton transfer phenomena lead to pH sensitivity of many molecular processes underlying biological phenomena. In the course of biological evolution, Nature has invented some mechanisms to use pH gradients to regulate biomolecular processes inside cells or in interstitial fluids. Therefore, an ability to model protonation equilibria in molecular systems accurately would be of enormous value for our understanding of biological processes and for possible rational influence on them, like in developing pH dependent drugs to treat particular diseases. This work presents a derivation, by thermodynamic and statistical mechanical methods, of an expression for the free energy of a complex molecular system at arbitrary ionization state of its titratable residues. This constitutes one of the elements of modeling protonation equilibria. Starting from a consideration of a simple acid-base equilibrium of a model compound with a single tritratable group, we arrive at an expression which is of general validity for complex systems. The only approximation used in this derivation is the postulating that the interaction energy between any pair of titratable sites does not depend on the protonation states of all the remaining ionizable groups.

Network Approach to Disease Diagnosis

NASA Astrophysics Data System (ADS)

Sharma, Amitabh; Bashan, Amir; Barabasi, Alber-Laszlo

2014-03-01

Human diseases could be viewed as perturbations of the underlying biological system. A thorough understanding of the topological and dynamical properties of the biological system is crucial to explain the mechanisms of many complex diseases. Recently network-based approaches have provided a framework for integrating multi-dimensional biological data that results in a better understanding of the pathophysiological state of complex diseases. Here we provide a network-based framework to improve the diagnosis of complex diseases. This framework is based on the integration of transcriptomics and the interactome. We analyze the overlap between the differentially expressed (DE) genes and disease genes (DGs) based on their locations in the molecular interaction network (''interactome''). Disease genes and their protein products tend to be much more highly connected than random, hence defining a disease sub-graph (called disease module) in the interactome. DE genes, even though different from the known set of DGs, may be significantly associated with the disease when considering their closeness to the disease module in the interactome. This new network approach holds the promise to improve the diagnosis of patients who cannot be diagnosed using conventional tools. Support was provided by HL066289 and HL105339 grants from the U.S. National Institutes of Health.

Proteomics and Systems Biology: Current and Future Applications in the Nutritional Sciences1

PubMed Central

Moore, J. Bernadette; Weeks, Mark E.

2011-01-01

In the last decade, advances in genomics, proteomics, and metabolomics have yielded large-scale datasets that have driven an interest in global analyses, with the objective of understanding biological systems as a whole. Systems biology integrates computational modeling and experimental biology to predict and characterize the dynamic properties of biological systems, which are viewed as complex signaling networks. Whereas the systems analysis of disease-perturbed networks holds promise for identification of drug targets for therapy, equally the identified critical network nodes may be targeted through nutritional intervention in either a preventative or therapeutic fashion. As such, in the context of the nutritional sciences, it is envisioned that systems analysis of normal and nutrient-perturbed signaling networks in combination with knowledge of underlying genetic polymorphisms will lead to a future in which the health of individuals will be improved through predictive and preventative nutrition. Although high-throughput transcriptomic microarray data were initially most readily available and amenable to systems analysis, recent technological and methodological advances in MS have contributed to a linear increase in proteomic investigations. It is now commonplace for combined proteomic technologies to generate complex, multi-faceted datasets, and these will be the keystone of future systems biology research. This review will define systems biology, outline current proteomic methodologies, highlight successful applications of proteomics in nutrition research, and discuss the challenges for future applications of systems biology approaches in the nutritional sciences. PMID:22332076

Methods of information geometry in computational system biology (consistency between chemical and biological evolution).

PubMed

Astakhov, Vadim

2009-01-01

Interest in simulation of large-scale metabolic networks, species development, and genesis of various diseases requires new simulation techniques to accommodate the high complexity of realistic biological networks. Information geometry and topological formalisms are proposed to analyze information processes. We analyze the complexity of large-scale biological networks as well as transition of the system functionality due to modification in the system architecture, system environment, and system components. The dynamic core model is developed. The term dynamic core is used to define a set of causally related network functions. Delocalization of dynamic core model provides a mathematical formalism to analyze migration of specific functions in biosystems which undergo structure transition induced by the environment. The term delocalization is used to describe these processes of migration. We constructed a holographic model with self-poetic dynamic cores which preserves functional properties under those transitions. Topological constraints such as Ricci flow and Pfaff dimension were found for statistical manifolds which represent biological networks. These constraints can provide insight on processes of degeneration and recovery which take place in large-scale networks. We would like to suggest that therapies which are able to effectively implement estimated constraints, will successfully adjust biological systems and recover altered functionality. Also, we mathematically formulate the hypothesis that there is a direct consistency between biological and chemical evolution. Any set of causal relations within a biological network has its dual reimplementation in the chemistry of the system environment.

New and improved proteomics technologies for understanding complex biological systems: addressing a grand challenge in the life sciences.

PubMed

Hood, Leroy E; Omenn, Gilbert S; Moritz, Robert L; Aebersold, Ruedi; Yamamoto, Keith R; Amos, Michael; Hunter-Cevera, Jennie; Locascio, Laurie

2012-09-01

This White Paper sets out a Life Sciences Grand Challenge for Proteomics Technologies to enhance our understanding of complex biological systems, link genomes with phenotypes, and bring broad benefits to the biosciences and the US economy. The paper is based on a workshop hosted by the National Institute of Standards and Technology (NIST) in Gaithersburg, MD, 14-15 February 2011, with participants from many federal R&D agencies and research communities, under the aegis of the US National Science and Technology Council (NSTC). Opportunities are identified for a coordinated R&D effort to achieve major technology-based goals and address societal challenges in health, agriculture, nutrition, energy, environment, national security, and economic development. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Systems Biology Approaches for Discovering Biomarkers for Traumatic Brain Injury

PubMed Central

Feala, Jacob D.; AbdulHameed, Mohamed Diwan M.; Yu, Chenggang; Dutta, Bhaskar; Yu, Xueping; Schmid, Kara; Dave, Jitendra; Tortella, Frank

2013-01-01

Abstract The rate of traumatic brain injury (TBI) in service members with wartime injuries has risen rapidly in recent years, and complex, variable links have emerged between TBI and long-term neurological disorders. The multifactorial nature of TBI secondary cellular response has confounded attempts to find cellular biomarkers for its diagnosis and prognosis or for guiding therapy for brain injury. One possibility is to apply emerging systems biology strategies to holistically probe and analyze the complex interweaving molecular pathways and networks that mediate the secondary cellular response through computational models that integrate these diverse data sets. Here, we review available systems biology strategies, databases, and tools. In addition, we describe opportunities for applying this methodology to existing TBI data sets to identify new biomarker candidates and gain insights about the underlying molecular mechanisms of TBI response. As an exemplar, we apply network and pathway analysis to a manually compiled list of 32 protein biomarker candidates from the literature, recover known TBI-related mechanisms, and generate hypothetical new biomarker candidates. PMID:23510232

KRAS Mouse Models

PubMed Central

O’Hagan, Rónán C.; Heyer, Joerg

2011-01-01

KRAS is a potent oncogene and is mutated in about 30% of all human cancers. However, the biological context of KRAS-dependent oncogenesis is poorly understood. Genetically engineered mouse models of cancer provide invaluable tools to study the oncogenic process, and insights from KRAS-driven models have significantly increased our understanding of the genetic, cellular, and tissue contexts in which KRAS is competent for oncogenesis. Moreover, variation among tumors arising in mouse models can provide insight into the mechanisms underlying response or resistance to therapy in KRAS-dependent cancers. Hence, it is essential that models of KRAS-driven cancers accurately reflect the genetics of human tumors and recapitulate the complex tumor-stromal intercommunication that is manifest in human cancers. Here, we highlight the progress made in modeling KRAS-dependent cancers and the impact that these models have had on our understanding of cancer biology. In particular, the development of models that recapitulate the complex biology of human cancers enables translational insights into mechanisms of therapeutic intervention in KRAS-dependent cancers. PMID:21779503

Capillary zone electrophoresis for analysis of phytochelatins and other thiol peptides in complex biological samples derivatized with monobromobimane.

PubMed

Perez-Rama, Mónica; Torres Vaamonde, Enrique; Abalde Alonso, Julio

2005-02-01

A new method to improve the analysis of phytochelatins and their precursors (cysteine, gamma-Glu-Cys, and glutathione) derivatized with monobromobimane (mBrB) in complex biological samples by capillary zone electrophoresis is described. The effects of the background electrolyte pH, concentration, and different organic additives (acetonitrile, methanol, and trifluoroethanol) on the separation were studied to achieve optimum resolution and number of theoretical plates of the analyzed compounds in the electropherograms. Optimum separation of the thiol peptides was obtained with 150 mM phosphate buffer at pH 1.60. Separation efficiency was improved when 2.5% v/v methanol was added to the background electrolyte. The electrophoretic conditions were 13 kV and capillary dimensions with 30 cm length from the inlet to the detector (38 cm total length) and 50 microm inner diameter. The injection was by pressure at 50 mbar for 17 s. Under these conditions, the separation between desglycyl-peptides and phytochelatins was also achieved. We also describe the optimum conditions for the derivatization of biological samples with mBrB to increase electrophoretic sensitivity and number of theoretical plates. The improved method was shown to be simple, reproducible, selective, and accurate in measuring thiol peptides in complex biological samples, the detection limit being 2.5 microM glutathione at a wavelength of 390 nm.

URDME: a modular framework for stochastic simulation of reaction-transport processes in complex geometries.

PubMed

Drawert, Brian; Engblom, Stefan; Hellander, Andreas

2012-06-22

Experiments in silico using stochastic reaction-diffusion models have emerged as an important tool in molecular systems biology. Designing computational software for such applications poses several challenges. Firstly, realistic lattice-based modeling for biological applications requires a consistent way of handling complex geometries, including curved inner- and outer boundaries. Secondly, spatiotemporal stochastic simulations are computationally expensive due to the fast time scales of individual reaction- and diffusion events when compared to the biological phenomena of actual interest. We therefore argue that simulation software needs to be both computationally efficient, employing sophisticated algorithms, yet in the same time flexible in order to meet present and future needs of increasingly complex biological modeling. We have developed URDME, a flexible software framework for general stochastic reaction-transport modeling and simulation. URDME uses Unstructured triangular and tetrahedral meshes to resolve general geometries, and relies on the Reaction-Diffusion Master Equation formalism to model the processes under study. An interface to a mature geometry and mesh handling external software (Comsol Multiphysics) provides for a stable and interactive environment for model construction. The core simulation routines are logically separated from the model building interface and written in a low-level language for computational efficiency. The connection to the geometry handling software is realized via a Matlab interface which facilitates script computing, data management, and post-processing. For practitioners, the software therefore behaves much as an interactive Matlab toolbox. At the same time, it is possible to modify and extend URDME with newly developed simulation routines. Since the overall design effectively hides the complexity of managing the geometry and meshes, this means that newly developed methods may be tested in a realistic setting already at an early stage of development. In this paper we demonstrate, in a series of examples with high relevance to the molecular systems biology community, that the proposed software framework is a useful tool for both practitioners and developers of spatial stochastic simulation algorithms. Through the combined efforts of algorithm development and improved modeling accuracy, increasingly complex biological models become feasible to study through computational methods. URDME is freely available at http://www.urdme.org.

ViSEN: methodology and software for visualization of statistical epistasis networks

PubMed Central

Hu, Ting; Chen, Yuanzhu; Kiralis, Jeff W.; Moore, Jason H.

2013-01-01

The non-linear interaction effect among multiple genetic factors, i.e. epistasis, has been recognized as a key component in understanding the underlying genetic basis of complex human diseases and phenotypic traits. Due to the statistical and computational complexity, most epistasis studies are limited to interactions with an order of two. We developed ViSEN to analyze and visualize epistatic interactions of both two-way and three-way. ViSEN not only identifies strong interactions among pairs or trios of genetic attributes, but also provides a global interaction map that shows neighborhood and clustering structures. This visualized information could be very helpful to infer the underlying genetic architecture of complex diseases and to generate plausible hypotheses for further biological validations. ViSEN is implemented in Java and freely available at https://sourceforge.net/projects/visen/. PMID:23468157

E-Index for Differentiating Complex Dynamic Traits

PubMed Central

Qi, Jiandong; Sun, Jianfeng; Wang, Jianxin

2016-01-01

While it is a daunting challenge in current biology to understand how the underlying network of genes regulates complex dynamic traits, functional mapping, a tool for mapping quantitative trait loci (QTLs) and single nucleotide polymorphisms (SNPs), has been applied in a variety of cases to tackle this challenge. Though useful and powerful, functional mapping performs well only when one or more model parameters are clearly responsible for the developmental trajectory, typically being a logistic curve. Moreover, it does not work when the curves are more complex than that, especially when they are not monotonic. To overcome this inadaptability, we therefore propose a mathematical-biological concept and measurement, E-index (earliness-index), which cumulatively measures the earliness degree to which a variable (or a dynamic trait) increases or decreases its value. Theoretical proofs and simulation studies show that E-index is more general than functional mapping and can be applied to any complex dynamic traits, including those with logistic curves and those with nonmonotonic curves. Meanwhile, E-index vector is proposed as well to capture more subtle differences of developmental patterns. PMID:27064292

Coevolution at protein complex interfaces can be detected by the complementarity trace with important impact for predictive docking

PubMed Central

Madaoui, Hocine; Guerois, Raphaël

2008-01-01

Protein surfaces are under significant selection pressure to maintain interactions with their partners throughout evolution. Capturing how selection pressure acts at the interfaces of protein–protein complexes is a fundamental issue with high interest for the structural prediction of macromolecular assemblies. We tackled this issue under the assumption that, throughout evolution, mutations should minimally disrupt the physicochemical compatibility between specific clusters of interacting residues. This constraint drove the development of the so-called Surface COmplementarity Trace in Complex History score (SCOTCH), which was found to discriminate with high efficiency the structure of biological complexes. SCOTCH performances were assessed not only with respect to other evolution-based approaches, such as conservation and coevolution analyses, but also with respect to statistically based scoring methods. Validated on a set of 129 complexes of known structure exhibiting both permanent and transient intermolecular interactions, SCOTCH appears as a robust strategy to guide the prediction of protein–protein complex structures. Of particular interest, it also provides a basic framework to efficiently track how protein surfaces could evolve while keeping their partners in contact. PMID:18511568

Conceptual Foundations of Systems Biology Explaining Complex Cardiac Diseases.

PubMed

Louridas, George E; Lourida, Katerina G

2017-02-21

Systems biology is an important concept that connects molecular biology and genomics with computing science, mathematics and engineering. An endeavor is made in this paper to associate basic conceptual ideas of systems biology with clinical medicine. Complex cardiac diseases are clinical phenotypes generated by integration of genetic, molecular and environmental factors. Basic concepts of systems biology like network construction, modular thinking, biological constraints (downward biological direction) and emergence (upward biological direction) could be applied to clinical medicine. Especially, in the field of cardiology, these concepts can be used to explain complex clinical cardiac phenotypes like chronic heart failure and coronary artery disease. Cardiac diseases are biological complex entities which like other biological phenomena can be explained by a systems biology approach. The above powerful biological tools of systems biology can explain robustness growth and stability during disease process from modulation to phenotype. The purpose of the present review paper is to implement systems biology strategy and incorporate some conceptual issues raised by this approach into the clinical field of complex cardiac diseases. Cardiac disease process and progression can be addressed by the holistic realistic approach of systems biology in order to define in better terms earlier diagnosis and more effective therapy.

Complexity Variability Assessment of Nonlinear Time-Varying Cardiovascular Control

NASA Astrophysics Data System (ADS)

Valenza, Gaetano; Citi, Luca; Garcia, Ronald G.; Taylor, Jessica Noggle; Toschi, Nicola; Barbieri, Riccardo

2017-02-01

The application of complex systems theory to physiology and medicine has provided meaningful information about the nonlinear aspects underlying the dynamics of a wide range of biological processes and their disease-related aberrations. However, no studies have investigated whether meaningful information can be extracted by quantifying second-order moments of time-varying cardiovascular complexity. To this extent, we introduce a novel mathematical framework termed complexity variability, in which the variance of instantaneous Lyapunov spectra estimated over time serves as a reference quantifier. We apply the proposed methodology to four exemplary studies involving disorders which stem from cardiology, neurology and psychiatry: Congestive Heart Failure (CHF), Major Depression Disorder (MDD), Parkinson’s Disease (PD), and Post-Traumatic Stress Disorder (PTSD) patients with insomnia under a yoga training regime. We show that complexity assessments derived from simple time-averaging are not able to discern pathology-related changes in autonomic control, and we demonstrate that between-group differences in measures of complexity variability are consistent across pathologies. Pathological states such as CHF, MDD, and PD are associated with an increased complexity variability when compared to healthy controls, whereas wellbeing derived from yoga in PTSD is associated with lower time-variance of complexity.

Beyond disease susceptibility-Leveraging genome-wide association studies for new insights into complex disease biology.

PubMed

Lee, J C

2017-12-01

Genetic studies in complex diseases have been highly successful, but have also been largely one-dimensional: predominantly focusing on the genetic contribution to disease susceptibility. While this is undoubtedly important-indeed it is a pre-requisite for understanding the mechanisms underlying disease development-there are many other important aspects of disease biology that have received comparatively little attention. In this review, I will discuss how existing genetic data can be leveraged to provide new insights into other aspects of disease biology, why such insights could change the way we think about complex disease, and how this could provide opportunities for better therapies and/or facilitate personalised medicine. To do this, I will use the example of Crohn's disease-a chronic form of inflammatory bowel disease that has been one of the main success stories in complex disease genetics. Indeed, thanks to genetic studies, we now have a much more detailed understanding of the processes involved in Crohn's disease development, but still know relatively little about what determines the subsequent disease course (prognosis) and why this differs so considerably between individuals. I will discuss how we came to realise that genetic variation plays an important role in determining disease prognosis and how this has changed the way we think about Crohn's disease genetics. This will illustrate how phenotypic data can be used to leverage new insights from genetic data and will provide a broadly applicable framework that could yield new insights into the biology of multiple diseases. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Protein Delivery into Plant Cells: Toward In vivo Structural Biology

PubMed Central

Cedeño, Cesyen; Pauwels, Kris; Tompa, Peter

2017-01-01

Understanding the biologically relevant structural and functional behavior of proteins inside living plant cells is only possible through the combination of structural biology and cell biology. The state-of-the-art structural biology techniques are typically applied to molecules that are isolated from their native context. Although most experimental conditions can be easily controlled while dealing with an isolated, purified protein, a serious shortcoming of such in vitro work is that we cannot mimic the extremely complex intracellular environment in which the protein exists and functions. Therefore, it is highly desirable to investigate proteins in their natural habitat, i.e., within live cells. This is the major ambition of in-cell NMR, which aims to approach structure-function relationship under true in vivo conditions following delivery of labeled proteins into cells under physiological conditions. With a multidisciplinary approach that includes recombinant protein production, confocal fluorescence microscopy, nuclear magnetic resonance (NMR) spectroscopy and different intracellular protein delivery strategies, we explore the possibility to develop in-cell NMR studies in living plant cells. While we provide a comprehensive framework to set-up in-cell NMR, we identified the efficient intracellular introduction of isotope-labeled proteins as the major bottleneck. Based on experiments with the paradigmatic intrinsically disordered proteins (IDPs) Early Response to Dehydration protein 10 and 14, we also established the subcellular localization of ERD14 under abiotic stress. PMID:28469623

Mercury reduction and complexation by natural organic matter in anoxic environments

PubMed Central

Gu, Baohua; Bian, Yongrong; Miller, Carrie L.; Dong, Wenming; Jiang, Xin; Liang, Liyuan

2011-01-01

Mercuric Hg(II) species form complexes with natural dissolved organic matter (DOM) such as humic acid (HA), and this binding is known to affect the chemical and biological transformation and cycling of mercury in aquatic environments. Dissolved elemental mercury, Hg(0), is also widely observed in sediments and water. However, reactions between Hg(0) and DOM have rarely been studied in anoxic environments. Here, under anoxic dark conditions we show strong interactions between reduced HA and Hg(0) through thiolate ligand-induced oxidative complexation with an estimated binding capacity of ~3.5 μmol Hg/g HA and a partitioning coefficient >106 mL/g. We further demonstrate that Hg(II) can be effectively reduced to Hg(0) in the presence of as little as 0.2 mg/L reduced HA, whereas production of Hg(0) is inhibited by complexation as HA concentration increases. This dual role played by DOM in the reduction and complexation of mercury is likely widespread in anoxic sediments and water and can be expected to significantly influence the mercury species transformations and biological uptake that leads to the formation of toxic methylmercury. PMID:21220311

Synthesis, characterization and biological evaluation of a novel "3 + 1" mixed ligand 99mTc complex having an aliphatic thiol as coligand.

PubMed

Rey, A; Papadopoulos, M; Leon, E; Mallo, L; Pirmettis, Y; Manta, E; Raptopoulou, C; Chiotellis, E; Leon, A

2001-03-01

A novel "3 + 1" mixed ligand 99mTc complex with N,N-bis(2-mercaptoethyl)-N'N'-diethyl-ethilenediamine as ligand and 1-octanethiol as coligand was prepared and evaluated as potential brain radiopharmaceutical. Preparation at tracer level was accomplished by substitution, using 99mTc-glucoheptonate as precursor and a coligand/ligand ratio of 5. Under these conditions the labeling yield was over 80% and a major product with radiochemical purity >80% was isolated by HPLC methods and used for biological evaluation. Chemical characterization at carrier level was developed using the corresponding rhenium and 99gTc complexes. Results were consistent with the expected "3 + 1" structure and X-ray diffraction study demonstrated that the complex adopted a distorted trigonal bipyramidal geometry. All sulphur atoms underwent ionization leading to the formation of a neutral compound. Biodistribution in mice demonstrated early brain uptake, fast blood clearance and excretion through hepatobiliary system. Although brain/blood ratio increased significantly with time, this novel 99mTc complex did not exhibit ideal properties as brain perfusion radiopharmaceutical since brain uptake was too low.

New insights into the coordination chemistry of Schiff bases derived from amino acids: Planar [Ni4] complexes with tyrosine side-chains

NASA Astrophysics Data System (ADS)

Muche, Simon; Hołyńska, Małgorzata

2017-08-01

Structure and properties of a rare metal complex of the chiral Schiff base ligand derived from ortho-vanillin and L-tyrosine are presented. This study is a continuation of research on ligands containing biologically compatible moieties. The ligand is also fully characterized in form of a sodium salt, in particular in solution, for the first time. The metal complex contains a unique bowl-shaped [Ni4] core. Its structure is investigated both in solution (ESI-MS, NMR) and in solid state (X-ray diffraction studies). Under certain conditions the complex can be isolated as crystalline DMF solvate which is studied in solid state.

ESEA: Discovering the Dysregulated Pathways based on Edge Set Enrichment Analysis

PubMed Central

Han, Junwei; Shi, Xinrui; Zhang, Yunpeng; Xu, Yanjun; Jiang, Ying; Zhang, Chunlong; Feng, Li; Yang, Haixiu; Shang, Desi; Sun, Zeguo; Su, Fei; Li, Chunquan; Li, Xia

2015-01-01

Pathway analyses are playing an increasingly important role in understanding biological mechanism, cellular function and disease states. Current pathway-identification methods generally focus on only the changes of gene expression levels; however, the biological relationships among genes are also the fundamental components of pathways, and the dysregulated relationships may also alter the pathway activities. We propose a powerful computational method, Edge Set Enrichment Analysis (ESEA), for the identification of dysregulated pathways. This provides a novel way of pathway analysis by investigating the changes of biological relationships of pathways in the context of gene expression data. Simulation studies illustrate the power and performance of ESEA under various simulated conditions. Using real datasets from p53 mutation, Type 2 diabetes and lung cancer, we validate effectiveness of ESEA in identifying dysregulated pathways. We further compare our results with five other pathway enrichment analysis methods. With these analyses, we show that ESEA is able to help uncover dysregulated biological pathways underlying complex traits and human diseases via specific use of the dysregulated biological relationships. We develop a freely available R-based tool of ESEA. Currently, ESEA can support pathway analysis of the seven public databases (KEGG; Reactome; Biocarta; NCI; SPIKE; HumanCyc; Panther). PMID:26267116

A Biologically Realistic Cortical Model of Eye Movement Control in Reading

ERIC Educational Resources Information Center

Heinzle, Jakob; Hepp, Klaus; Martin, Kevan A. C.

2010-01-01

Reading is a highly complex task involving a precise integration of vision, attention, saccadic eye movements, and high-level language processing. Although there is a long history of psychological research in reading, it is only recently that imaging studies have identified some neural correlates of reading. Thus, the underlying neural mechanisms…

Optimization Techniques for Analysis of Biological and Social Networks

DTIC Science & Technology

2012-03-28

analyzing a new metaheuristic technique, variable objective search. 3. Experimentation and application: Implement the proposed algorithms , test and fine...alternative mathematical programming formulations, their theoretical analysis, the development of exact algorithms , and heuristics. Originally, clusters...systematic fashion under a unifying theoretical and algorithmic framework. Optimization, Complex Networks, Social Network Analysis, Computational

Essential Properties of Language, or, Why Language Is Not a Code

ERIC Educational Resources Information Center

Kravchenko, Alexander V.

2007-01-01

Despite a strong tradition of viewing "coded equivalence" as the underlying principle of linguistic semiotics, it lacks the power needed to understand and explain language as an empirical phenomenon characterized by complex dynamics. Applying the biology of cognition to the nature of the human cognitive/linguistic capacity as rooted in the…

Evidence for polyphosphate accumulating organism (PAO)-mediated phosphorus cycling in stream biofilms under alternating aerobic/anaerobic conditions

USDA-ARS?s Scientific Manuscript database

Phosphorus (P) is often a limiting nutrient in freshwater ecosystems and excessive inputs can lead to eutrophication. In-stream cycling of P involves complex biological, chemical, and physical processes that are not fully understood. Microbial metabolisms are suspected to control oxygen-dependent up...

Comprehensive Genome-wide Screen for Genes with Cis-acting Regulatory Elements That Respond to Marek's Disease Virus Infection

USDA-ARS?s Scientific Manuscript database

The comprehensive identification of genes underlying phenotypic variation of complex traits such as disease resistance remains one of the greatest challenges in biology despite having genome sequences and more powerful tools. Most genome-wide screens lack sufficient resolving power as they typically...

NADPH OXIDASE: STRUCTURE AND ACTIVATION MECHANISMS (REVIEW). NOTE I.

PubMed

Filip-Ciubotaru, Florina; Manciuc, Carmen; Stoleriu, Gabriela; Foia, Liliana

2016-01-01

NADPH oxidase (nicotinamide adenine dinucleotide phosphate-oxidase), with its generically termed NOX isoforms, is the major source of ROS (reactive oxigen species) in biological systems. ROS are small oxygen-derived molecules with an important role in various biological processes (physiological or pathological). If under physiological conditions some processes are beneficial and necessary for life, under pathophysiological conditions they are noxious, harmful. NADPH oxidases are present in phagocytes and in a wide variety of nonphagocytic cells. The enzyme generates superoxide by transferring electrons from NADPH inside the cell across the membrane and coupling them to molecular oxygen to produce superoxide anion, a reactive free-radical. Structurally, NADPH oxidase is a multicomponent enzyme which includes two integral membrane proteins, glycoprotein gp9 1 Phox and adaptor protein p22(phox), which together form the heterodimeric flavocytochrome b558 that constitutes the core of the enzyme. During the resting state, the multidomain regulatory subunits p40P(phox), p47(phox), p67(Phox) are located in the cytosol organized as a complex. The activation of phagocytic NADPH oxidase occurs through a complex series of protein interactions.

Making the invisible visible.

PubMed

van Steensel, Maurice A M

2016-04-01

In this review, I will discuss how careful scrutiny of genetic skin disorders could help us to understand human biology. Like other organs, the skin and its appendages, such as hairs and teeth, experience fundamental biological processes ranging from lipid metabolism to vesicular transport and cellular migration. However, in contrast to other organ systems, they are accessible and can be studied with relative ease. By visually revealing the functional consequences of single gene defects, genetic skin diseases offer a unique opportunity to study human biology. Here, I will illustrate this concept by discussing how human genetic disorders of skin pigmentation reflect the mechanisms underlying this complex and vital process. Copyright © 2016 Elsevier Ltd. All rights reserved.

Systems biology approach to bioremediation

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

Chakraborty, Romy; Wu, Cindy H.; Hazen, Terry C.

2012-06-01

Bioremediation has historically been approached as a ‘black box’ in terms of our fundamental understanding. Thus it succeeds and fails, seldom without a complete understanding of why. Systems biology is an integrated research approach to study complex biological systems, by investigating interactions and networks at the molecular, cellular, community, and ecosystem level. The knowledge of these interactions within individual components is fundamental to understanding the dynamics of the ecosystem under investigation. Finally, understanding and modeling functional microbial community structure and stress responses in environments at all levels have tremendous implications for our fundamental understanding of hydrobiogeochemical processes and the potentialmore » for making bioremediation breakthroughs and illuminating the ‘black box’.« less

KENNEDY SPACE CENTER, FLA. - Dr. Grant Gilmore, Dynamac Corp., utilizes a laptop computer to explain aspects of the underwater acoustic research under way in the Launch Complex 39 turn basin. Several government agencies, including NASA, NOAA, the Navy, the Coast Guard, and the Florida Fish and Wildlife Commission are involved in the testing. The research involves demonstrations of passive and active sensor technologies, with applications in fields ranging from marine biological research to homeland security. The work is also serving as a pilot project to assess the cooperation between the agencies involved. Equipment under development includes a passive acoustic monitor developed by NASA’s Jet Propulsion Laboratory, and mobile robotic sensors from the Navy’s Mobile Diving and Salvage Unit.

NASA Image and Video Library

2003-08-18

KENNEDY SPACE CENTER, FLA. - Dr. Grant Gilmore, Dynamac Corp., utilizes a laptop computer to explain aspects of the underwater acoustic research under way in the Launch Complex 39 turn basin. Several government agencies, including NASA, NOAA, the Navy, the Coast Guard, and the Florida Fish and Wildlife Commission are involved in the testing. The research involves demonstrations of passive and active sensor technologies, with applications in fields ranging from marine biological research to homeland security. The work is also serving as a pilot project to assess the cooperation between the agencies involved. Equipment under development includes a passive acoustic monitor developed by NASA’s Jet Propulsion Laboratory, and mobile robotic sensors from the Navy’s Mobile Diving and Salvage Unit.

Designing and testing a classroom curriculum to teach preschoolers about the biology of physical activity: The respiration system as an underlying biological causal mechanism

NASA Astrophysics Data System (ADS)

Ewing, Tracy S.

The present study examined young children's understanding of respiration and oxygen as a source of vital energy underlying physical activity. Specifically, the purpose of the study was to explore whether a coherent biological theory, characterized by an understanding that bodily parts (heart and lungs) and processes (oxygen in respiration) as part of a biological system, can be taught as a foundational concept to reason about physical activity. The effects of a biology-based intervention curriculum designed to teach preschool children about bodily functions as a part of the respiratory system, the role of oxygen as a vital substance and how physical activity acts an energy source were examined. Participants were recruited from three private preschool classrooms (two treatment; 1 control) in Southern California and included a total of 48 four-year-old children (30 treatment; 18 control). Findings from this study suggested that young children could be taught relevant biological concepts about the role of oxygen in respiratory processes. Children who received biology-based intervention curriculum made significant gains in their understanding of the biology of respiration, identification of physical and sedentary activities. In addition these children demonstrated that coherence of conceptual knowledge was correlated with improved accuracy at activity identification and reasoning about the inner workings of the body contributing to endurance. Findings from this study provided evidence to support the benefits of providing age appropriate but complex coherent biological instruction to children in early childhood settings.

Deciphering deterioration mechanisms of complex diseases based on the construction of dynamic networks and systems analysis

NASA Astrophysics Data System (ADS)

Li, Yuanyuan; Jin, Suoqin; Lei, Lei; Pan, Zishu; Zou, Xiufen

2015-03-01

The early diagnosis and investigation of the pathogenic mechanisms of complex diseases are the most challenging problems in the fields of biology and medicine. Network-based systems biology is an important technique for the study of complex diseases. The present study constructed dynamic protein-protein interaction (PPI) networks to identify dynamical network biomarkers (DNBs) and analyze the underlying mechanisms of complex diseases from a systems level. We developed a model-based framework for the construction of a series of time-sequenced networks by integrating high-throughput gene expression data into PPI data. By combining the dynamic networks and molecular modules, we identified significant DNBs for four complex diseases, including influenza caused by either H3N2 or H1N1, acute lung injury and type 2 diabetes mellitus, which can serve as warning signals for disease deterioration. Function and pathway analyses revealed that the identified DNBs were significantly enriched during key events in early disease development. Correlation and information flow analyses revealed that DNBs effectively discriminated between different disease processes and that dysfunctional regulation and disproportional information flow may contribute to the increased disease severity. This study provides a general paradigm for revealing the deterioration mechanisms of complex diseases and offers new insights into their early diagnoses.

Conformal piezoelectric systems for clinical and experimental characterization of soft tissue biomechanics

NASA Astrophysics Data System (ADS)

Dagdeviren, Canan; Shi, Yan; Joe, Pauline; Ghaffari, Roozbeh; Balooch, Guive; Usgaonkar, Karan; Gur, Onur; Tran, Phat L.; Crosby, Jessi R.; Meyer, Marcin; Su, Yewang; Chad Webb, R.; Tedesco, Andrew S.; Slepian, Marvin J.; Huang, Yonggang; Rogers, John A.

2015-07-01

Mechanical assessment of soft biological tissues and organs has broad relevance in clinical diagnosis and treatment of disease. Existing characterization methods are invasive, lack microscale spatial resolution, and are tailored only for specific regions of the body under quasi-static conditions. Here, we develop conformal and piezoelectric devices that enable in vivo measurements of soft tissue viscoelasticity in the near-surface regions of the epidermis. These systems achieve conformal contact with the underlying complex topography and texture of the targeted skin, as well as other organ surfaces, under both quasi-static and dynamic conditions. Experimental and theoretical characterization of the responses of piezoelectric actuator-sensor pairs laminated on a variety of soft biological tissues and organ systems in animal models provide information on the operation of the devices. Studies on human subjects establish the clinical significance of these devices for rapid and non-invasive characterization of skin mechanical properties.

Novel insights into an old disease: recent developments in scabies mite biology.

PubMed

Holt, Deborah C; Fischer, Katja

2013-04-01

Scabies is a serious disease of both humans and other animals caused by infestation of the skin with the ectoparasitic mite Sarcoptes scabiei. Our current understanding of scabies mite biology and disease processes is far outweighed by the significant, worldwide impact of the disease. This review summarizes the recent data which furthers our knowledge of mite biology, host specificity and parasite host evasion mechanisms. Recent data concords with the previous work demonstrating limited gene flow between different host-associated populations of scabies mites. This evidence of the host specificity of scabies mites has important implications for disease control programmes. Other studies have begun to decipher the molecular basis of the complex host-parasite interactions underlying scabies infestations. Scabies mites have developed complex mechanisms to interfere with the host defence processes that may also enhance the survival of the associated skin microbiome, consistent with the epidemiological evidence. Recently developed natural host models of scabies are valuable tools to further study the disease processes and to trial novel therapeutic agents. Although significant progress has been made, further research is needed to understand the biology, host-parasite interactions and pathogenesis of this ubiquitous parasite.

Mechanisms of bacterial morphogenesis: evolutionary cell biology approaches provide new insights.

PubMed

Jiang, Chao; Caccamo, Paul D; Brun, Yves V

2015-04-01

How Darwin's "endless forms most beautiful" have evolved remains one of the most exciting questions in biology. The significant variety of bacterial shapes is most likely due to the specific advantages they confer with respect to the diverse environments they occupy. While our understanding of the mechanisms generating relatively simple shapes has improved tremendously in the last few years, the molecular mechanisms underlying the generation of complex shapes and the evolution of shape diversity are largely unknown. The emerging field of bacterial evolutionary cell biology provides a novel strategy to answer this question in a comparative phylogenetic framework. This relatively novel approach provides hypotheses and insights into cell biological mechanisms, such as morphogenesis, and their evolution that would have been difficult to obtain by studying only model organisms. We discuss the necessary steps, challenges, and impact of integrating "evolutionary thinking" into bacterial cell biology in the genomic era. © 2015 WILEY Periodicals, Inc.

Light microscopy applications in systems biology: opportunities and challenges

PubMed Central

2013-01-01

Biological systems present multiple scales of complexity, ranging from molecules to entire populations. Light microscopy is one of the least invasive techniques used to access information from various biological scales in living cells. The combination of molecular biology and imaging provides a bottom-up tool for direct insight into how molecular processes work on a cellular scale. However, imaging can also be used as a top-down approach to study the behavior of a system without detailed prior knowledge about its underlying molecular mechanisms. In this review, we highlight the recent developments on microscopy-based systems analyses and discuss the complementary opportunities and different challenges with high-content screening and high-throughput imaging. Furthermore, we provide a comprehensive overview of the available platforms that can be used for image analysis, which enable community-driven efforts in the development of image-based systems biology. PMID:23578051

A systems biology model of the regulatory network in Populus leaves reveals interacting regulators and conserved regulation

PubMed Central

2011-01-01

Background Green plant leaves have always fascinated biologists as hosts for photosynthesis and providers of basic energy to many food webs. Today, comprehensive databases of gene expression data enable us to apply increasingly more advanced computational methods for reverse-engineering the regulatory network of leaves, and to begin to understand the gene interactions underlying complex emergent properties related to stress-response and development. These new systems biology methods are now also being applied to organisms such as Populus, a woody perennial tree, in order to understand the specific characteristics of these species. Results We present a systems biology model of the regulatory network of Populus leaves. The network is reverse-engineered from promoter information and expression profiles of leaf-specific genes measured over a large set of conditions related to stress and developmental. The network model incorporates interactions between regulators, such as synergistic and competitive relationships, by evaluating increasingly more complex regulatory mechanisms, and is therefore able to identify new regulators of leaf development not found by traditional genomics methods based on pair-wise expression similarity. The approach is shown to explain available gene function information and to provide robust prediction of expression levels in new data. We also use the predictive capability of the model to identify condition-specific regulation as well as conserved regulation between Populus and Arabidopsis. Conclusions We outline a computationally inferred model of the regulatory network of Populus leaves, and show how treating genes as interacting, rather than individual, entities identifies new regulators compared to traditional genomics analysis. Although systems biology models should be used with care considering the complexity of regulatory programs and the limitations of current genomics data, methods describing interactions can provide hypotheses about the underlying cause of emergent properties and are needed if we are to identify target genes other than those constituting the "low hanging fruit" of genomic analysis. PMID:21232107

Potentiometric and spectroscopic study of the interaction of 3d transition metal ions with inositol hexakisphosphate

NASA Astrophysics Data System (ADS)

Veiga, Nicolás; Macho, Israel; Gómez, Kerman; González, Gabriel; Kremer, Carlos; Torres, Julia

2015-10-01

Among myo-inositol phosphates, the most abundant in nature is the myo-inositol hexakisphosphate, InsP6. Although it is known to be vital to cell functioning, the biochemical research into its metabolism needs chemical and structural analysis of all the protonation, complexation and precipitation processes that it undergoes in the biological media. In view of its high negative charge at physiological level, our group has been leading a thorough research into the InsP6 chemical and structural behavior in the presence of the alkali and alkaline earth metal ions essential for life. The aim of this article is to extend these studies, dealing with the chemical and structural features of the InsP6 interaction with biologically relevant 3d transition metal ions (Fe(II), Fe(III), Mn(II), Co(II), Ni(II), Cu(II) and Zn(II)), in a non-interacting medium and under simulated physiological conditions. The metal-complex stability constants were determined by potentiometry, showing under ligand-excess conditions the formation of mononuclear species in different protonation states. Under metal ion excess, polymetallic species were detected for Fe(II), Fe(III), Zn(II) and Cu(II). Additionally, the 31P NMR and UV-vis spectroscopic studies provided interesting structural aspects of the strong metal ion-InsP6 interaction.

Biological and protein-binding studies of newly synthesized polymer-cobalt(III) complexes.

PubMed

Vignesh, G; Pradeep, I; Arunachalam, S; Vignesh, S; Arthur James, R; Arun, R; Premkumar, K

2016-03-01

The polymer-cobalt(III) complexes, [Co(bpy)(dien)BPEI]Cl3 · 4H2O (bpy = 2,2'-bipyridine, dien = diethylentriamine, BPEI = branched polyethyleneimine) were synthesized and characterized. The interaction of these complexes with human serum albumin (HSA) and bovine serum albumin (BSA) was investigated under physiological conditions using various physico-chemical techniques. The results reveal that the fluorescence quenching of serum albumins by polymer-cobalt(III) complexes took place through static quenching. The binding of these complexes changed the molecular conformation of the protein considerably. The polymer-cobalt(III) complex with x = 0.365 shows antimicrobial activity against several human pathogens. This complex also induces cytotoxicity against MCF-7 through apoptotic induction. However, further studies are needed to decipher the molecular mode of action of polymer-cobalt(III) complex and for its possible utilization in anticancer therapy. Copyright © 2015 John Wiley & Sons, Ltd.

Biotinylated platinum(IV) complexes designed to target cancer cells.

PubMed

Zhao, Jian; Hua, Wuyang; Xu, Gang; Gou, Shaohua

2017-11-01

Three biotinylated platinum(IV) complexes (1-3) were designed and synthesized. The resulting platinum(IV) complexes exhibited effective cytotoxicity against the tested cancer cell lines, especially complex 1, which was 2.0-9.6-fold more potent than cisplatin. These complexes were found to be rapidly reduced to their activated platinum(II) counterparts by glutathione or ascorbic acid under biologically relevant condition. Additional molecular docking studies revealed that the biotin moieties of all Pt(IV) complexes can effectively bind with the streptavidin through the noncovalent interactions. Besides, introduction of the biotin group can obviously promote the cancer cell uptake of platinum when treated with complex 1, particularly in cisplatin-resistant SGC-7901/Cis cancer cells. Further mechanistic studies on complex 1 indicated that it activated the expression of Bax, and induced cytochrome c release from the mitochondria, and finally activated caspase-3. Copyright © 2017 Elsevier Inc. All rights reserved.

What do we gain from simplicity versus complexity in species distribution models?

USGS Publications Warehouse

Merow, Cory; Smith, Matthew J.; Edwards, Thomas C.; Guisan, Antoine; McMahon, Sean M.; Normand, Signe; Thuiller, Wilfried; Wuest, Rafael O.; Zimmermann, Niklaus E.; Elith, Jane

2014-01-01

Species distribution models (SDMs) are widely used to explain and predict species ranges and environmental niches. They are most commonly constructed by inferring species' occurrence–environment relationships using statistical and machine-learning methods. The variety of methods that can be used to construct SDMs (e.g. generalized linear/additive models, tree-based models, maximum entropy, etc.), and the variety of ways that such models can be implemented, permits substantial flexibility in SDM complexity. Building models with an appropriate amount of complexity for the study objectives is critical for robust inference. We characterize complexity as the shape of the inferred occurrence–environment relationships and the number of parameters used to describe them, and search for insights into whether additional complexity is informative or superfluous. By building ‘under fit’ models, having insufficient flexibility to describe observed occurrence–environment relationships, we risk misunderstanding the factors shaping species distributions. By building ‘over fit’ models, with excessive flexibility, we risk inadvertently ascribing pattern to noise or building opaque models. However, model selection can be challenging, especially when comparing models constructed under different modeling approaches. Here we argue for a more pragmatic approach: researchers should constrain the complexity of their models based on study objective, attributes of the data, and an understanding of how these interact with the underlying biological processes. We discuss guidelines for balancing under fitting with over fitting and consequently how complexity affects decisions made during model building. Although some generalities are possible, our discussion reflects differences in opinions that favor simpler versus more complex models. We conclude that combining insights from both simple and complex SDM building approaches best advances our knowledge of current and future species ranges.

The RNA-induced silencing complex: a versatile gene-silencing machine.

PubMed

Pratt, Ashley J; MacRae, Ian J

2009-07-03

RNA interference is a powerful mechanism of gene silencing that underlies many aspects of eukaryotic biology. On the molecular level, RNA interference is mediated by a family of ribonucleoprotein complexes called RNA-induced silencing complexes (RISCs), which can be programmed to target virtually any nucleic acid sequence for silencing. The ability of RISC to locate target RNAs has been co-opted by evolution many times to generate a broad spectrum of gene-silencing pathways. Here, we review the fundamental biochemical and biophysical properties of RISC that facilitate gene targeting and describe the various mechanisms of gene silencing known to exploit RISC activity.

Systems Medicine: Sketching the Landscape.

PubMed

Kirschner, Marc

2016-01-01

To understand the meaning of the term Systems Medicine and to distinguish it from seemingly related other expressions currently in use, such as precision, personalized, -omics, or big data medicine, its underlying history and development into present time needs to be highlighted. Having this development in mind, it becomes evident that Systems Medicine is a genuine concept as well as a novel way of tackling the manifold complexity that occurs in nowadays clinical medicine-and not just a rebranding of what has previously been done in the past. So looking back it seems clear to many in the field that Systems Medicine has its origin in an integrative method to unravel biocomplexity, namely, Systems Biology. Here scientist by now gained useful experience that is on the verge toward implementation in clinical research and practice.Systems Medicine and Systems Biology have the same underlying theoretical principle in systems-based thinking-a methodology to understand complexity that can be traced back to ancient Greece. During the last decade, however, and due to a rapid methodological development in the life sciences and computing/IT technologies, Systems Biology has evolved from a scientific concept into an independent discipline most competent to tackle key questions of biocomplexity-with the potential to transform medicine and how it will be practiced in the future. To understand this process in more detail, the following section will thus give a short summary of the foundation of systems-based thinking and the different developmental stages including systems theory, the development of modern Systems Biology, and its transition into clinical practice. These are the components to pave the way toward Systems Medicine.

Examining ion channel properties using free-energy methods.

PubMed

Domene, Carmen; Furini, Simone

2009-01-01

Recent advances in structural biology have revealed the architecture of a number of transmembrane channels, allowing for these complex biological systems to be understood in atomistic detail. Computational simulations are a powerful tool by which the dynamic and energetic properties, and thereby the function of these protein architectures, can be investigated. The experimentally observable properties of a system are often determined more by energetic than dynamics, and therefore understanding the underlying free energy (FE) of biophysical processes is of crucial importance. Critical to the accurate evaluation of FE values are the problems of obtaining accurate sampling of complex biological energy landscapes, and of obtaining accurate representations of the potential energy of a system, this latter problem having been addressed through the development of molecular force fields. While these challenges are common to all FE methods, depending on the system under study, and the questions being asked of it, one technique for FE calculation may be preferable to another, the choice of method and simulation protocol being crucial to achieve efficiency. Applied in a correct manner, FE calculations represent a predictive and affordable computational tool with which to make relevant contact with experiments. This chapter, therefore, aims to give an overview of the most widely implemented computational methods used to calculate the FE associated with particular biochemical or biophysical events, and to highlight their recent applications to ion channels. Copyright © 2009 Elsevier Inc. All rights reserved.

78 FR 58311 - Complex Issues in Developing Drug and Biological Products for Rare Diseases; Public Workshop...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-09-23

...] Complex Issues in Developing Drug and Biological Products for Rare Diseases; Public Workshop; Request for... Issues in Developing Drug and Biological Products for Rare Diseases.'' The purpose of the public workshop is twofold: To discuss complex issues in clinical trials for developing drug and biological products...

[Sanitary-hygienic assessment of microbial biofertilizer].

PubMed

Arkhipchenko, N A; Akhtemava, G A; Lebedeva, T V; Voronina, A A; Makhan'kova, T I; Pavlova, M M; Shteĭntsaĭg, T A

1991-10-01

Biological treatment of sewage from pig-breeding complexes allowed to produce microbial biomass and primary sediments. The mixture of these components (1:1) after rendering harmless and drying out become the high effective biofertilizer. The results of chronic experiment on sanitary status of soil (microbial and helminthological indexes) under this biofertilizer usage are discussed, and the harmlessness of it is demonstrated.

Malthus under a Microscope: Using the Soil Nematode "Coenorhabditis elegans" to Test Darwin's Premises about Populations

ERIC Educational Resources Information Center

Mueller, Melinda M.

2007-01-01

Biological evolution is one of the over-arching concepts recommended for student learning by the "National Science Education Standards." As with all such complex concepts, student understanding of evolution is improved when instruction includes hands-on, inquiry-based activities. However, even authors writing in strong support of teaching…

From Purines to Basic Biochemical Concepts: Experiments for High School Students

ERIC Educational Resources Information Center

Marini, Isabella; Ipata, Piero Luigi

2007-01-01

Many high school biology courses address mainly the molecular and cellular basis of life. The complexity that underlies the most essential processes is often difficult for the students to understand; possibly, in part, because of the inability to see and explore them. Six simple practical experiments on purine catabolism as a part of a…

Advance Planning Briefing for Industry. Technology Requirements Briefings

DTIC Science & Technology

2009-02-17

procedure drills through complex multiplayer interactions representative of a motorcade under heavy attack. The tool shall provide a first-person...Integrated Munitions Effect Assessment IMI Interactive Multimedia Instruction IP Internet Protocol IPE Intelligence Preparation of the Environment IR...CTTSO Programs and Mission Areas/Subgroups 13 Requirement Descriptions Blast Effects and Mitigation (BX) 16 Chemical, Biological, Radiological, and

Challenges and opportunities in absorption, distribution, metabolism, and excretion studies of therapeutic biologics.

PubMed

Xu, Xin; Vugmeyster, Yulia

2012-12-01

With the advancement of biotechnology in the last two decades, optimized and novel modalities and platforms of biologic moieties have emerged rapidly in drug discovery pipelines. In addition, new technologies for delivering therapeutic biologics (e.g., needle-free devices, nanoparticle complexes), as well as novel approaches for disease treatments (e.g., stem cell therapy, individualized medicine), continue to be developed. While pharmacokinetic studies are routinely carried out for therapeutic biologics, experiments that elucidate underlying mechanisms for clearance and biodistribution or identify key factors that govern absorption, distribution, metabolism, and excretion (ADME) of biologics often are not thoroughly conducted. Realizing the importance of biologics as therapeutic agents, pharmaceutical industry has recently begun to move the research focus from small molecules only to a blended portfolio consisting of both small molecules and biologics. This trend brings many opportunities for scientists working in the drug disposition research field. In anticipation of these opportunities and associated challenges, this review highlights impact of ADME studies on clinical and commercial success of biologics, with a particular focus on emerging applications and technologies and linkage with mechanistic pharmacokinetic/pharmacodynamic modeling and biomarker research.

An easy-to-build and re-usable microfluidic system for live-cell imaging.

PubMed

Babic, Julien; Griscom, Laurent; Cramer, Jeremy; Coudreuse, Damien

2018-06-20

Real-time monitoring of cellular responses to dynamic changes in their environment or to specific treatments has become central to cell biology. However, when coupled to live-cell imaging, such strategies are difficult to implement with precision and high time resolution, and the simultaneous alteration of multiple parameters is a major challenge. Recently, microfluidics has provided powerful solutions for such analyses, bringing an unprecedented level of control over the conditions and the medium in which cells under microscopic observation are grown. However, such technologies have remained under-exploited, largely as a result of the complexity associated with microfabrication procedures. In this study, we have developed simple but powerful microfluidic devices dedicated to live-cell imaging. These microsystems take advantage of a robust elastomer that is readily available to researchers and that presents excellent bonding properties, in particular to microscopy-grade glass coverslips. Importantly, the chips are easy-to-build without sophisticated equipment, and they are compatible with the integration of complex, customized fluidic networks as well as with the multiplexing of independent assays on a single device. We show that the chips are re-usable, a significant advantage for the popularization of microfluidics in cell biology. Moreover, we demonstrate that they allow for the dynamic, accurate and simultaneous control of multiple parameters of the cellular environment. While they do not possess all the features of the microdevices that are built using complex and costly procedures, the simplicity and versatility of the chips that we have developed make them an attractive alternative for a range of applications. The emergence of such devices, which can be fabricated and used by any laboratory, will provide the possibility for a larger number of research teams to take full advantage of these new methods for investigating cell biology.

The receptive field is dead. Long live the receptive field?

PubMed Central

Fairhall, Adrienne

2014-01-01

Advances in experimental techniques, including behavioral paradigms using rich stimuli under closed loop conditions and the interfacing of neural systems with external inputs and outputs, reveal complex dynamics in the neural code and require a revisiting of standard concepts of representation. High-throughput recording and imaging methods along with the ability to observe and control neuronal subpopulations allow increasingly detailed access to the neural circuitry that subserves these representations and the computations they support. How do we harness theory to build biologically grounded models of complex neural function? PMID:24618227

Network-based analysis of differentially expressed genes in cerebrospinal fluid (CSF) and blood reveals new candidate genes for multiple sclerosis

PubMed Central

Safari-Alighiarloo, Nahid; Taghizadeh, Mohammad; Tabatabaei, Seyyed Mohammad; Namaki, Saeed

2016-01-01

Background The involvement of multiple genes and missing heritability, which are dominant in complex diseases such as multiple sclerosis (MS), entail using network biology to better elucidate their molecular basis and genetic factors. We therefore aimed to integrate interactome (protein–protein interaction (PPI)) and transcriptomes data to construct and analyze PPI networks for MS disease. Methods Gene expression profiles in paired cerebrospinal fluid (CSF) and peripheral blood mononuclear cells (PBMCs) samples from MS patients, sampled in relapse or remission and controls, were analyzed. Differentially expressed genes which determined only in CSF (MS vs. control) and PBMCs (relapse vs. remission) separately integrated with PPI data to construct the Query-Query PPI (QQPPI) networks. The networks were further analyzed to investigate more central genes, functional modules and complexes involved in MS progression. Results The networks were analyzed and high centrality genes were identified. Exploration of functional modules and complexes showed that the majority of high centrality genes incorporated in biological pathways driving MS pathogenesis. Proteasome and spliceosome were also noticeable in enriched pathways in PBMCs (relapse vs. remission) which were identified by both modularity and clique analyses. Finally, STK4, RB1, CDKN1A, CDK1, RAC1, EZH2, SDCBP genes in CSF (MS vs. control) and CDC37, MAP3K3, MYC genes in PBMCs (relapse vs. remission) were identified as potential candidate genes for MS, which were the more central genes involved in biological pathways. Discussion This study showed that network-based analysis could explicate the complex interplay between biological processes underlying MS. Furthermore, an experimental validation of candidate genes can lead to identification of potential therapeutic targets. PMID:28028462

Nitrogen reduction and functionalization by a multimetallic uranium nitride complex

NASA Astrophysics Data System (ADS)

Falcone, Marta; Chatelain, Lucile; Scopelliti, Rosario; Živković, Ivica; Mazzanti, Marinella

2017-07-01

Molecular nitrogen (N2) is cheap and widely available, but its unreactive nature is a challenge when attempting to functionalize it under mild conditions with other widely available substrates (such as carbon monoxide, CO) to produce value-added compounds. Biological N2 fixation can do this, but the industrial Haber-Bosch process for ammonia production operates under harsh conditions (450 degrees Celsius and 300 bar), even though both processes are thought to involve multimetallic catalytic sites. And although molecular complexes capable of binding and even reducing N2 under mild conditions are known, with co-operativity between metal centres considered crucial for the N2 reduction step, the multimetallic species involved are usually not well defined, and further transformation of N2-binding complexes to achieve N-H or N-C bond formation is rare. Haber noted, before an iron-based catalyst was adopted for the industrial Haber-Bosch process, that uranium and uranium nitride materials are very effective heterogeneous catalysts for ammonia production from N2. However, few examples of uranium complexes binding N2 are known, and soluble uranium complexes capable of transforming N2 into ammonia or organonitrogen compounds have not yet been identified. Here we report the four-electron reduction of N2 under ambient conditions by a fully characterized complex with two UIII ions and three K+ centres held together by a nitride group and a flexible metalloligand framework. The addition of H2 and/or protons, or CO to the resulting complex results in the complete cleavage of N2 with concomitant N2 functionalization through N-H or N-C bond-forming reactions. These observations establish that a molecular uranium complex can promote the stoichiometric transformation of N2 into NH3 or cyanate, and that a flexible, electron-rich, multimetallic, nitride-bridged core unit is a promising starting point for the design of molecular complexes capable of cleaving and functionalizing N2 under mild conditions.

Vitronectin--master controller or micromanager?

PubMed

Leavesley, David I; Kashyap, Abhishek S; Croll, Tristan; Sivaramakrishnan, Manaswini; Shokoohmand, Ali; Hollier, Brett G; Upton, Zee

2013-10-01

The concept that the mammalian glycoprotein vitronectin acts as a biological 'glue' and key controller of mammalian tissue repair and remodelling activity is emerging from nearly 50 years of experimental in vitro and in vivo data. Unexpectedly, the vitronectin-knockout (VN-KO) mouse was found to be viable and to have largely normal phenotype. However, diligent observation revealed that the VN-KO animal exhibits delayed coagulation and poor wound healing. This is interpreted to indicate that VN occupies a role in the earliest events of thrombogenesis and tissue repair. VN is the foundation upon which the thrombus grows in an organised structure. In addition to sealing the wound, the thrombus also serves to protect the underlying tissue from oxidation, is a reservoir of mitogens and tissue repair mediators, and provides a provisional scaffold for the repairing tissue. In the absence of VN (e.g., VN-KO animal), this cascade is disrupted before it begins. A wide variety of biologically active species associate with VN. Although initial studies were focused on mitogens, other classes of bioactives (e.g., glycosaminoglycans and metalloproteinases) are now also known to specifically interact with VN. Although some interactions are transient, others are long-lived and often result in multi-protein complexes. Multi-protein complexes provide several advantages: prolonging molecular interactions, sustaining local concentrations, facilitating co-stimulation of cell surface receptors and thereby enhancing cellular/biological responses. We contend that these, or equivalent, multi-protein complexes facilitate VN polyfunctionality in vivo. It is also likely that many of the species demonstrated to associate with VN in vitro, also associate with VN in vivo in similar multi-protein complexes. Thus, the predominant biological function of VN is that of a master controller of the extracellular environment; informing, and possibly instructing cells 'where' to behave, 'when' to behave and 'how' to behave (i.e., appropriately for the current circumstance). © 2013 International Union of Biochemistry and Molecular Biology.

The Carnegie Department of Embryology at 100: Looking Forward.

PubMed

Spradling, Allan C

2016-01-01

Biological research has a realistic chance within the next 50 years of discovering the basic mechanisms by which metazoan genomes encode the complex morphological structures and capabilities that characterize life as we know it. However, achieving those goals is now threatened by researchers who advocate an end to basic research on nonmammalian organisms. For the sake of society, medicine, and the science of biology, the focus of biomedical research should place more emphasis on basic studies guided by the underlying evolutionary commonality of all major animals, as manifested in their genes, pathways, cells, and organs. © 2016 Elsevier Inc. All rights reserved.

Accounting for the contribution of vitamin B to Canada's WWII effort.

PubMed

Braun, Robyn

2010-01-01

Canada began to fortify its flour and bread with vitamin B when it entered the Second World War. The decision was informed by the biology of vitamin B and therefore I suggest that the complexity of this political maneuver can best be understood by considering the specificity of the biochemistry of vitamin B. In this paper I will show that the specific biology of vitamin B allowed the Canadian government the possibility of a healthier population under wartime conditions but also allowed the government a variety of means by which to develop and organize food processing practices to this end.

Understanding the mechanism of DNA deactivation in ion therapy of cancer cells: hydrogen peroxide action*

NASA Astrophysics Data System (ADS)

Piatnytskyi, Dmytro V.; Zdorevskyi, Oleksiy O.; Perepelytsya, Sergiy M.; Volkov, Sergey N.

2015-11-01

Changes in the medium of biological cells under ion beam irradiation has been considered as a possible cause of cell function disruption in the living body. The interaction of hydrogen peroxide, a long-lived molecular product of water radiolysis, with active sites of DNA macromolecule was studied, and the formation of stable DNA-peroxide complexes was considered. The phosphate groups of the macromolecule backbone were picked out among the atomic groups of DNA double helix as a probable target for interaction with hydrogen peroxide molecules. Complexes consisting of combinations including: the DNA phosphate group, H2O2 and H2O molecules, and Na+ counterion, were considered. The counterions have been taken into consideration insofar as under the natural conditions they neutralise DNA sugar-phosphate backbone. The energy of the complexes have been determined by considering the electrostatic and the Van der Waals interactions within the framework of atom-atom potential functions. As a result, the stability of various configurations of molecular complexes was estimated. It was shown that DNA phosphate groups and counterions can form stable complexes with hydrogen peroxide molecules, which are as stable as the complexes with water molecules. It has been demonstrated that the formation of stable complexes of H2O2-Na+-PO4- may be detected experimentally by observing specific vibrations in the low-frequency Raman spectra. The interaction of H2O2 molecule with phosphate group of the double helix backbone can disrupt DNA biological function and induce the deactivation of the cell genetic apparatus. Thus, the production of hydrogen peroxide molecules in the nucleus of living cells can be considered as an additional mechanism by which high-energy ion beams destroy tumour cells during ion beam therapy. Contribution to the Topical Issue "COST Action Nano-IBCT: Nano-scale Processes Behind Ion-Beam Cancer Therapy", edited by Andrey Solov'yov, Nigel Mason, Gustavo García, Eugene Surdutovich.

Efficient interrupting skills of amino acid metallointercalators with DNA at physiological pH: Evaluation of biological assays

NASA Astrophysics Data System (ADS)

Raman, Natarajan; Selvaganapathy, Muthusamy; Radhakrishnan, Srinivasan

2014-06-01

The 4-aminoantipyrine derivatives (sbnd NO2, sbnd OCH3) and their mixed-ligand complexes with amino acids have been synthesized and investigated for their binding with CT DNA using UV-visible spectroscopy, cyclic voltammetry, and viscosity measurements under physiological conditions of pH (stomach 4.7; blood 7.4). The results from all techniques i.e. binding constant (Kb), and free energy change (ΔG) were in good agreement and inferred spontaneous compound-DNA complexes formation via intercalation. Among all the compounds 1 and 4 showed comparatively greater binding at pH 7.4 as evident from its greater Kb values. All the complexes exhibit oxidative cleavage of supercoiled (SC) pBR322 plasmid DNA in the presence of H2O2 as an activator. It is remarkable that at 25 μM concentration 1 and 4 completely degrade SC DNA into undetectable minor fragments and thus they act as efficient chemical nucleases. Among the new complexes, complexes 1 and 4 have highest potential against all the microorganisms tested. The results of the above biological experiments also reveal that the choice of different metal ions has little influence on the DNA binding, DNA cleavage and antimicrobial assay.

A novel algorithm for finding optimal driver nodes to target control complex networks and its applications for drug targets identification.

PubMed

Guo, Wei-Feng; Zhang, Shao-Wu; Shi, Qian-Qian; Zhang, Cheng-Ming; Zeng, Tao; Chen, Luonan

2018-01-19

The advances in target control of complex networks not only can offer new insights into the general control dynamics of complex systems, but also be useful for the practical application in systems biology, such as discovering new therapeutic targets for disease intervention. In many cases, e.g. drug target identification in biological networks, we usually require a target control on a subset of nodes (i.e., disease-associated genes) with minimum cost, and we further expect that more driver nodes consistent with a certain well-selected network nodes (i.e., prior-known drug-target genes). Therefore, motivated by this fact, we pose and address a new and practical problem called as target control problem with objectives-guided optimization (TCO): how could we control the interested variables (or targets) of a system with the optional driver nodes by minimizing the total quantity of drivers and meantime maximizing the quantity of constrained nodes among those drivers. Here, we design an efficient algorithm (TCOA) to find the optional driver nodes for controlling targets in complex networks. We apply our TCOA to several real-world networks, and the results support that our TCOA can identify more precise driver nodes than the existing control-fucus approaches. Furthermore, we have applied TCOA to two bimolecular expert-curate networks. Source code for our TCOA is freely available from http://sysbio.sibcb.ac.cn/cb/chenlab/software.htm or https://github.com/WilfongGuo/guoweifeng . In the previous theoretical research for the full control, there exists an observation and conclusion that the driver nodes tend to be low-degree nodes. However, for target control the biological networks, we find interestingly that the driver nodes tend to be high-degree nodes, which is more consistent with the biological experimental observations. Furthermore, our results supply the novel insights into how we can efficiently target control a complex system, and especially many evidences on the practical strategic utility of TCOA to incorporate prior drug information into potential drug-target forecasts. Thus applicably, our method paves a novel and efficient way to identify the drug targets for leading the phenotype transitions of underlying biological networks.

A Novel c-Jun N-terminal Kinase (JNK) Signaling Complex Involved in Neuronal Migration during Brain Development.

PubMed

Zhang, Feng; Yu, Jingwen; Yang, Tao; Xu, Dan; Chi, Zhixia; Xia, Yanheng; Xu, Zhiheng

2016-05-27

Disturbance of neuronal migration may cause various neurological disorders. Both the transforming growth factor-β (TGF-β) signaling and microcephaly-associated protein WDR62 are important for neuronal migration during brain development; however, the underlying molecular mechanisms involved remain unclear. We show here that knock-out or knockdown of Tak1 (TGFβ-activated kinase 1) and Jnk2 (c-Jun N-terminal kinase 2) perturbs neuronal migration during cortical development and that the migration defects incurred by knock-out and/or knockdown of Tβr2 (type II TGF-β receptor) or Tak1 can be partially rescued by expression of TAK1 and JNK2, respectively. Furthermore, TAK1 forms a protein complex with RAC1 and two scaffold proteins of the JNK pathway, the microcephaly-associated protein WDR62 and the RAC1-interacting protein POSH (plenty of Src homology). Components of the complex coordinate with each other in the regulation of TAK1 as well as JNK activities. We suggest that unique JNK protein complexes are involved in the diversified biological and pathological functions during brain development and pathogenesis of diseases. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.

Fractal morphometry of cell complexity.

PubMed

Losa, Gabriele A

2002-01-01

Irregularity and self-similarity under scale changes are the main attributes of the morphological complexity of both normal and abnormal cells and tissues. In other words, the shape of a self-similar object does not change when the scale of measurement changes, because each part of it looks similar to the original object. However, the size and geometrical parameters of an irregular object do differ when it is examined at increasing resolution, which reveals more details. Significant progress has been made over the past three decades in understanding how irregular shapes and structures in the physical and biological sciences can be analysed. Dominant influences have been the discovery of a new practical geometry of Nature, now known as fractal geometry, and the continuous improvements in computation capabilities. Unlike conventional Euclidean geometry, which was developed to describe regular and ideal geometrical shapes which are practically unknown in nature, fractal geometry can be used to measure the fractal dimension, contour length, surface area and other dimension parameters of almost all irregular and complex biological tissues. We have used selected examples to illustrate the application of the fractal principle to measuring irregular and complex membrane ultrastructures of cells at specific functional and pathological stage.

The RNA-binding complex ESCRT-II in Xenopus laevis eggs recognizes purine-rich sequences through its subunit Vps25.

PubMed

Emerman, Amy B; Blower, Michael

2018-06-14

RNA-binding proteins (RBPs) are critical regulators of gene expression. Recent studies have uncovered hundreds of mRNA-binding proteins that do not contain annotated RNA-binding domains and have well-established roles in other cellular processes. Investigation of these nonconventional RBPs is critical for revealing novel RNA-binding domains and may disclose connections between RNA regulation and other aspects of cell biology. Endosomal sorting complex required for transport II (ESCRT-II) is a nonconventional RNA-binding complex that has a canonical role in multivesicular body formation. ESCRT-II previously has been identified as an RNA-binding complex in Drosophila oocytes, but whether its RNA-binding properties extend beyond Drosophila is unknown. In this study, we found that the RNA-binding properties of ESCRT-II are conserved in Xenopus eggs, where ESCRT-II interacted with hundreds of mRNAs. Using a UV-crosslinking approach, we demonstrated that ESCRT-II binds directly to RNA through its subunit Vps25. UV-crosslinking and immunoprecipitation (CLIP)-Seq revealed that Vps25 specifically recognizes a polypurine (i.e. GA-rich) motif in RNA. Using purified components, we could reconstitute the selective Vps25-mediated binding of the polypurine motif in vitro. Our results provide insight into the mechanism by which ESCRT-II selectively binds to mRNAs and also suggest an unexpected link between endosome biology and RNA regulation. Published under license by The American Society for Biochemistry and Molecular Biology, Inc.

Nanoscale Structure and Interaction of Compact Assemblies of Carbon Nano-Materials

NASA Astrophysics Data System (ADS)

Timsina, Raju; Qiu, Xiangyun

Carbon-based nano-materials (CNM) are a diverse family of multi-functional materials under research and development world wide. Our work is further motivated by the predictive power of the physical understanding of the underlying structure-interaction-function relationships. Here we present results form recent studies of the condensed phases of several model CNMs in complexation with biologically derived molecules. Specifically, we employ X-ray diffraction (XRD) to determine nanoscale structures and use the osmotic stress method to quantify their interactions. The systems under investigation are dsDNA-dispersed carbon nanotubes (dsDNA-CNT), bile-salt-dispersed carbon nanotubes, and surfactant-assisted assemblies of graphene oxides. We found that salt and molecular crowding are both effective in condensing CNMs but the resultant structures show disparate phase behaviors. The molecular interactions driving the condensation/assembly sensitively depend on the nature of CNM complex surface chemistry and range from hydrophobic to electrostatic to entropic forces.

Chemistry meets biology in colitis-associated carcinogenesis

PubMed Central

Mangerich, Aswin; Dedon, Peter C.; Fox, James G.; Tannenbaum, Steven R.; Wogan, Gerald N.

2015-01-01

The intestine comprises an exceptional venue for a dynamic and complex interplay of numerous chemical and biological processes. Here, multiple chemical and biological systems, including the intestinal tissue itself, its associated immune system, the gut microbiota, xenobiotics, and metabolites meet and interact to form a sophisticated and tightly regulated state of tissue homoeostasis. Disturbance of this homeostasis can cause inflammatory bowel disease (IBD) – a chronic disease of multifactorial etiology that is strongly associated with increased risk for cancer development. This review addresses recent developments in research into chemical and biological mechanisms underlying the etiology of inflammation-induced colon cancer. Beginning with a general overview of reactive chemical species generated during colonic inflammation, the mechanistic interplay between chemical and biological mediators of inflammation, the role of genetic toxicology and microbial pathogenesis in disease development are discussed. When possible, we systematically compare evidence from studies utilizing human IBD patients with experimental investigations in mice. The comparison reveals that many strong pathological and mechanistic correlates exist between mouse models of colitis-associated cancer, and the clinically relevant situation in humans. We also summarize several emerging issues in the field, such as the carcinogenic potential of novel inflammation-related DNA adducts and genotoxic microbial factors, the systemic dimension of inflammation-induced genotoxicity, and the complex role of genome maintenance mechanisms during these processes. Taken together, current evidence points to the induction of genetic and epigenetic alterations by chemical and biological inflammatory stimuli ultimately leading to cancer formation. PMID:23926919

Theory for the Emergence of Modularity in Complex Systems

NASA Astrophysics Data System (ADS)

Deem, Michael; Park, Jeong-Man

2013-03-01

Biological systems are modular, and this modularity evolves over time and in different environments. A number of observations have been made of increased modularity in biological systems under increased environmental pressure. We here develop a theory for the dynamics of modularity in these systems. We find a principle of least action for the evolved modularity at long times. In addition, we find a fluctuation dissipation relation for the rate of change of modularity at short times. We discuss a number of biological and social systems that can be understood with this framework. The modularity of the protein-protein interaction network increases when yeast are exposed to heat shock, and the modularity of the protein-protein networks in both yeast and E. coli appears to have increased over evolutionary time. Food webs in low-energy, stressful environments are more modular than those in plentiful environments, arid ecologies are more modular during droughts, and foraging of sea otters is more modular when food is limiting. The modularity of social networks changes over time: stock brokers instant messaging networks are more modular under stressful market conditions, criminal networks are more modular under increased police pressure, and world trade network modularity has decreased

Bridging the gap between biologic, individual, and macroenvironmental factors in cancer: a multilevel approach.

PubMed

Lynch, Shannon M; Rebbeck, Timothy R

2013-04-01

To address the complex nature of cancer occurrence and outcomes, approaches have been developed to simultaneously assess the role of two or more etiologic agents within hierarchical levels including the: (i) macroenvironment level (e.g., health care policy, neighborhood, or family structure); (ii) individual level (e.g., behaviors, carcinogenic exposures, socioeconomic factors, and psychologic responses); and (iii) biologic level (e.g., cellular biomarkers and inherited susceptibility variants). Prior multilevel approaches tend to focus on social and environmental hypotheses, and are thus limited in their ability to integrate biologic factors into a multilevel framework. This limited integration may be related to the limited translation of research findings into the clinic. We propose a "Multi-level Biologic and Social Integrative Construct" (MBASIC) to integrate macroenvironment and individual factors with biology. The goal of this framework is to help researchers identify relationships among factors that may be involved in the multifactorial, complex nature of cancer etiology, to aid in appropriate study design, to guide the development of statistical or mechanistic models to study these relationships, and to position the results of these studies for improved intervention, translation, and implementation. MBASIC allows researchers from diverse fields to develop hypotheses of interest under a common conceptual framework, to guide transdisciplinary collaborations, and to optimize the value of multilevel studies for clinical and public health activities.

Use of biological priors enhances understanding of genetic architecture and genomic prediction of complex traits within and between dairy cattle breeds.

PubMed

Fang, Lingzhao; Sahana, Goutam; Ma, Peipei; Su, Guosheng; Yu, Ying; Zhang, Shengli; Lund, Mogens Sandø; Sørensen, Peter

2017-08-10

A better understanding of the genetic architecture underlying complex traits (e.g., the distribution of causal variants and their effects) may aid in the genomic prediction. Here, we hypothesized that the genomic variants of complex traits might be enriched in a subset of genomic regions defined by genes grouped on the basis of "Gene Ontology" (GO), and that incorporating this independent biological information into genomic prediction models might improve their predictive ability. Four complex traits (i.e., milk, fat and protein yields, and mastitis) together with imputed sequence variants in Holstein (HOL) and Jersey (JER) cattle were analysed. We first carried out a post-GWAS analysis in a HOL training population to assess the degree of enrichment of the association signals in the gene regions defined by each GO term. We then extended the genomic best linear unbiased prediction model (GBLUP) to a genomic feature BLUP (GFBLUP) model, including an additional genomic effect quantifying the joint effect of a group of variants located in a genomic feature. The GBLUP model using a single random effect assumes that all genomic variants contribute to the genomic relationship equally, whereas GFBLUP attributes different weights to the individual genomic relationships in the prediction equation based on the estimated genomic parameters. Our results demonstrate that the immune-relevant GO terms were more associated with mastitis than milk production, and several biologically meaningful GO terms improved the prediction accuracy with GFBLUP for the four traits, as compared with GBLUP. The improvement of the genomic prediction between breeds (the average increase across the four traits was 0.161) was more apparent than that it was within the HOL (the average increase across the four traits was 0.020). Our genomic feature modelling approaches provide a framework to simultaneously explore the genetic architecture and genomic prediction of complex traits by taking advantage of independent biological knowledge.

Structure and Dynamics of Type III Secretion Effector Protein ExoU As determined by SDSL-EPR Spectroscopy in Conjunction with De Novo Protein Folding

PubMed Central

2017-01-01

ExoU is a 74 kDa cytotoxin that undergoes substantial conformational changes as part of its function, that is, it has multiple thermodynamically stable conformations that interchange depending on its environment. Such flexible proteins pose unique challenges to structural biology: (1) not only is it often difficult to determine structures by X-ray crystallography for all biologically relevant conformations because of the flat energy landscape (2) but also experimental conditions can easily perturb the biologically relevant conformation. The first challenge can be overcome by applying orthogonal structural biology techniques that are capable of observing alternative, biologically relevant conformations. The second challenge can be addressed by determining the structure in the same biological state with two independent techniques under different experimental conditions. If both techniques converge to the same structural model, the confidence that an unperturbed biologically relevant conformation is observed increases. To this end, we determine the structure of the C-terminal domain of the effector protein, ExoU, from data obtained by electron paramagnetic resonance spectroscopy in conjunction with site-directed spin labeling and in silico de novo structure determination. Our protocol encompasses a multimodule approach, consisting of low-resolution topology sampling, clustering, and high-resolution refinement. The resulting model was compared with an ExoU model in complex with its chaperone SpcU obtained previously by X-ray crystallography. The two models converged to a minimal RMSD100 of 3.2 Å, providing evidence that the unbound structure of ExoU matches the fold observed in complex with SpcU. PMID:28691114

Live-cell imaging of invasion and intravasation in an artificial microvessel platform.

PubMed

Wong, Andrew D; Searson, Peter C

2014-09-01

Methods to visualize metastasis exist, but additional tools to better define the biologic and physical processes underlying invasion and intravasation are still needed. One difficulty in studying metastasis stems from the complexity of the interface between the tumor microenvironment and the vascular system. Here, we report the development of an investigational platform that positions tumor cells next to an artificial vessel embedded in an extracellular matrix. On this platform, we used live-cell fluorescence microscopy to analyze the complex interplay between metastatic cancer cells and a functional artificial microvessel that was lined with endothelial cells. The platform recapitulated known interactions, and its use demonstrated the capabilities for a systematic study of novel physical and biologic parameters involved in invasion and intravasation. In summary, our work offers an important new tool to advance knowledge about metastasis and candidate antimetastatic therapies. ©2014 American Association for Cancer Research.

Quantification of the interceptor action of caffeine on the in vitro biological effect of the anti-tumour agent topotecan.

PubMed

Evstigneev, M P; Mosunov, A A; Evstigneev, V P; Parkes, H G; Davies, D B

2011-08-01

Using published in vitro data on the dependence of the percentage of apoptosis induced by the anti-cancer drug topotecan in a leukaemia cell line on the concentration of added caffeine, and a general model of competitive binding in a system containing two aromatic drugs and DNA, it has been shown to be possible to quantify the relative change in the biological effect just using a set of component concentrations and equilibrium constants of the complexation of the drugs. It is also proposed that a general model of competitive binding and parameterization of that model may potentially be applied to any system of DNA-targeting aromatic drugs under in vitro conditions. The main reasons underpinning the proposal are the general feature of the complexation of aromatic drugs with DNA and their interaction in physiological media via hetero-association.

Modeling Complex Biological Flows in Multi-Scale Systems using the APDEC Framework

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

Trebotich, D

We have developed advanced numerical algorithms to model biological fluids in multiscale flow environments using the software framework developed under the SciDAC APDEC ISIC. The foundation of our computational effort is an approach for modeling DNA-laden fluids as ''bead-rod'' polymers whose dynamics are fully coupled to an incompressible viscous solvent. The method is capable of modeling short range forces and interactions between particles using soft potentials and rigid constraints. Our methods are based on higher-order finite difference methods in complex geometry with adaptivity, leveraging algorithms and solvers in the APDEC Framework. Our Cartesian grid embedded boundary approach to incompressible viscousmore » flow in irregular geometries has also been interfaced to a fast and accurate level-sets method within the APDEC Framework for extracting surfaces from volume renderings of medical image data and used to simulate cardio-vascular and pulmonary flows in critical anatomies.« less

Modeling complex biological flows in multi-scale systems using the APDEC framework

NASA Astrophysics Data System (ADS)

Trebotich, David

2006-09-01

We have developed advanced numerical algorithms to model biological fluids in multiscale flow environments using the software framework developed under the SciDAC APDEC ISIC. The foundation of our computational effort is an approach for modeling DNA laden fluids as ''bead-rod'' polymers whose dynamics are fully coupled to an incompressible viscous solvent. The method is capable of modeling short range forces and interactions between particles using soft potentials and rigid constraints. Our methods are based on higher-order finite difference methods in complex geometry with adaptivity, leveraging algorithms and solvers in the APDEC Framework. Our Cartesian grid embedded boundary approach to incompressible viscous flow in irregular geometries has also been interfaced to a fast and accurate level-sets method within the APDEC Framework for extracting surfaces from volume renderings of medical image data and used to simulate cardio-vascular and pulmonary flows in critical anatomies.

Trifluoromethyl-Substituted Iridium(III) Complexes: From Photophysics to Photooxidation of a Biological Target.

PubMed

Bevernaegie, Robin; Marcélis, Lionel; Laramée-Milette, Baptiste; De Winter, Julien; Robeyns, Koen; Gerbaux, Pascal; Hanan, Garry S; Elias, Benjamin

2018-02-05

Photodynamic therapeutic agents are of key interest in developing new strategies to develop more specific and efficient anticancer treatments. In comparison to classical chemotherapeutic agents, the activity of photodynamic therapeutic compounds can be finely controlled thanks to the light triggering of their photoreactivity. The development of type I photosensitizing agents, which do not rely on the production of ROS, is highly desirable. In this context, we developed new iridium(III) complexes which are able to photoreact with biomolecules; namely, our Ir(III) complexes can oxidize guanine residues under visible light irradiation. We report the synthesis and extensive photophysical characterization of four new Ir(III) complexes, [Ir(ppyCF 3 ) 2 (N^N)] + [ppyCF 3 = 2-(3,5-bis(trifluoromethyl)phenyl)pyridine) and N^N = 2,2'-dipyridyl (bpy); 2-(pyridin-2-yl)pyrazine (pzpy); 2,2'-bipyrazine (bpz); 1,4,5,8-tetraazaphenanthrene (TAP)]. In addition to an extensive experimental and theoretical study of the photophysics of these complexes, we characterize their photoreactivity toward model redox-active targets and the relevant biological target, the guanine base. We demonstrate that photoinduced electron transfer takes place between the excited Ir(III) complex and guanine which leads to the formation of stable photoproducts, indicating that the targeted guanine is irreversibly damaged. These results pave the way to the elaboration of new type I photosensitizers for targeting cancerous cells.

Complexity reduction of biochemical rate expressions.

PubMed

Schmidt, Henning; Madsen, Mads F; Danø, Sune; Cedersund, Gunnar

2008-03-15

The current trend in dynamical modelling of biochemical systems is to construct more and more mechanistically detailed and thus complex models. The complexity is reflected in the number of dynamic state variables and parameters, as well as in the complexity of the kinetic rate expressions. However, a greater level of complexity, or level of detail, does not necessarily imply better models, or a better understanding of the underlying processes. Data often does not contain enough information to discriminate between different model hypotheses, and such overparameterization makes it hard to establish the validity of the various parts of the model. Consequently, there is an increasing demand for model reduction methods. We present a new reduction method that reduces complex rational rate expressions, such as those often used to describe enzymatic reactions. The method is a novel term-based identifiability analysis, which is easy to use and allows for user-specified reductions of individual rate expressions in complete models. The method is one of the first methods to meet the classical engineering objective of improved parameter identifiability without losing the systems biology demand of preserved biochemical interpretation. The method has been implemented in the Systems Biology Toolbox 2 for MATLAB, which is freely available from http://www.sbtoolbox2.org. The Supplementary Material contains scripts that show how to use it by applying the method to the example models, discussed in this article.

Biological pattern formation: from basic mechanisms to complex structures

NASA Astrophysics Data System (ADS)

Koch, A. J.; Meinhardt, H.

1994-10-01

The reliable development of highly complex organisms is an intriguing and fascinating problem. The genetic material is, as a rule, the same in each cell of an organism. How then do cells, under the influence of their common genes, produce spatial patterns? Simple models are discussed that describe the generation of patterns out of an initially nearly homogeneous state. They are based on nonlinear interactions of at least two chemicals and on their diffusion. The concepts of local autocatalysis and of long-range inhibition play a fundamental role. Numerical simulations show that the models account for many basic biological observations such as the regeneration of a pattern after excision of tissue or the production of regular (or nearly regular) arrays of organs during (or after) completion of growth. Very complex patterns can be generated in a reproducible way by hierarchical coupling of several such elementary reactions. Applications to animal coats and to the generation of polygonally shaped patterns are provided. It is further shown how to generate a strictly periodic pattern of units that themselves exhibit a complex and polar fine structure. This is illustrated by two examples: the assembly of photoreceptor cells in the eye of Drosophila and the positioning of leaves and axillary buds in a growing shoot. In both cases, the substructures have to achieve an internal polarity under the influence of some primary pattern-forming system existing in the fly's eye or in the plant. The fact that similar models can describe essential steps in organisms as distantly related as animals and plants suggests that they reveal some universal mechanisms.

Human Platelet Lipidomics: Variance, Visualization, Flux, and Fuel.

PubMed

FitzGerald, Garret A

2016-05-10

The cardioprotection afforded by low-dose aspirin reflects the biological importance of the platelet lipid thromboxane A2. In this issue of Cell Metabolism, Slatter et al. (2016) illuminate the breadth, complexity, and variability of the human platelet lipidome under conditions of thrombin activation and aspirin suppression, potentially facilitating the pursuit of precision medicine. Copyright © 2016 Elsevier Inc. All rights reserved.

Generation of Diverse Biological Forms through Combinatorial Interactions between Tissue Polarity and Growth

PubMed Central

Kennaway, Richard; Coen, Enrico; Green, Amelia; Bangham, Andrew

2011-01-01

A major problem in biology is to understand how complex tissue shapes may arise through growth. In many cases this process involves preferential growth along particular orientations raising the question of how these orientations are specified. One view is that orientations are specified through stresses in the tissue (axiality-based system). Another possibility is that orientations can be specified independently of stresses through molecular signalling (polarity-based system). The axiality-based system has recently been explored through computational modelling. Here we develop and apply a polarity-based system which we call the Growing Polarised Tissue (GPT) framework. Tissue is treated as a continuous material within which regionally expressed factors under genetic control may interact and propagate. Polarity is established by signals that propagate through the tissue and is anchored in regions termed tissue polarity organisers that are also under genetic control. Rates of growth parallel or perpendicular to the local polarity may then be specified through a regulatory network. The resulting growth depends on how specified growth patterns interact within the constraints of mechanically connected tissue. This constraint leads to the emergence of features such as curvature that were not directly specified by the regulatory networks. Resultant growth feeds back to influence spatial arrangements and local orientations of tissue, allowing complex shapes to emerge from simple rules. Moreover, asymmetries may emerge through interactions between polarity fields. We illustrate the value of the GPT-framework for understanding morphogenesis by applying it to a growing Snapdragon flower and indicate how the underlying hypotheses may be tested by computational simulation. We propose that combinatorial intractions between orientations and rates of growth, which are a key feature of polarity-based systems, have been exploited during evolution to generate a range of observed biological shapes. PMID:21698124

KENNEDY SPACE CENTER, FLA. - Researchers conduct underwater acoustic research in the Launch Complex 39 turn basin. Several government agencies, including NASA, NOAA, the Navy, the Coast Guard, and the Florida Fish and Wildlife Commission are involved in the testing. The research involves demonstrations of passive and active sensor technologies, with applications in fields ranging from marine biological research to homeland security. The work is also serving as a pilot project to assess the cooperation between the agencies involved. Equipment under development includes a passive acoustic monitor developed by NASA’s Jet Propulsion Laboratory, and mobile robotic sensors from the Navy’s Mobile Diving and Salvage Unit.

NASA Image and Video Library

2003-08-18

KENNEDY SPACE CENTER, FLA. - Researchers conduct underwater acoustic research in the Launch Complex 39 turn basin. Several government agencies, including NASA, NOAA, the Navy, the Coast Guard, and the Florida Fish and Wildlife Commission are involved in the testing. The research involves demonstrations of passive and active sensor technologies, with applications in fields ranging from marine biological research to homeland security. The work is also serving as a pilot project to assess the cooperation between the agencies involved. Equipment under development includes a passive acoustic monitor developed by NASA’s Jet Propulsion Laboratory, and mobile robotic sensors from the Navy’s Mobile Diving and Salvage Unit.

Principles of assembly reveal a periodic table of protein complexes.

PubMed

Ahnert, Sebastian E; Marsh, Joseph A; Hernández, Helena; Robinson, Carol V; Teichmann, Sarah A

2015-12-11

Structural insights into protein complexes have had a broad impact on our understanding of biological function and evolution. In this work, we sought a comprehensive understanding of the general principles underlying quaternary structure organization in protein complexes. We first examined the fundamental steps by which protein complexes can assemble, using experimental and structure-based characterization of assembly pathways. Most assembly transitions can be classified into three basic types, which can then be used to exhaustively enumerate a large set of possible quaternary structure topologies. These topologies, which include the vast majority of observed protein complex structures, enable a natural organization of protein complexes into a periodic table. On the basis of this table, we can accurately predict the expected frequencies of quaternary structure topologies, including those not yet observed. These results have important implications for quaternary structure prediction, modeling, and engineering. Copyright © 2015, American Association for the Advancement of Science.

Comprehensive Characterization of Minichromosome Maintenance Complex (MCM) Protein Interactions Using Affinity and Proximity Purifications Coupled to Mass Spectrometry.

PubMed

Dubois, Marie-Line; Bastin, Charlotte; Lévesque, Dominique; Boisvert, François-Michel

2016-09-02

The extensive identification of protein-protein interactions under different conditions is an important challenge to understand the cellular functions of proteins. Here we use and compare different approaches including affinity purification and purification by proximity coupled to mass spectrometry to identify protein complexes. We explore the complete interactome of the minichromosome maintenance (MCM) complex by using both approaches for all of the different MCM proteins. Overall, our analysis identified unique and shared interaction partners and proteins enriched for distinct biological processes including DNA replication, DNA repair, and cell cycle regulation. Furthermore, we mapped the changes in protein interactions of the MCM complex in response to DNA damage, identifying a new role for this complex in DNA repair. In summary, we demonstrate the complementarity of these approaches for the characterization of protein interactions within the MCM complex.

Emergence of life: Physical chemistry changes the paradigm.

PubMed

Spitzer, Jan; Pielak, Gary J; Poolman, Bert

2015-06-10

Origin of life research has been slow to advance not only because of its complex evolutionary nature (Franklin Harold: In Search of Cell History, 2014) but also because of the lack of agreement on fundamental concepts, including the question of 'what is life?'. To re-energize the research and define a new experimental paradigm, we advance four premises to better understand the physicochemical complexities of life's emergence: (1) Chemical and Darwinian (biological) evolutions are distinct, but become continuous with the appearance of heredity. (2) Earth's chemical evolution is driven by energies of cycling (diurnal) disequilibria and by energies of hydrothermal vents. (3) Earth's overall chemical complexity must be high at the origin of life for a subset of (complex) chemicals to phase separate and evolve into living states. (4) Macromolecular crowding in aqueous electrolytes under confined conditions enables evolution of molecular recognition and cellular self-organization. We discuss these premises in relation to current 'constructive' (non-evolutionary) paradigm of origins research - the process of complexification of chemical matter 'from the simple to the complex'. This paradigm artificially avoids planetary chemical complexity and the natural tendency of molecular compositions toward maximum disorder embodied in the second law of thermodynamics. Our four premises suggest an empirical program of experiments involving complex chemical compositions under cycling gradients of temperature, water activity and electromagnetic radiation.

Thermodynamic characterization of the multivalent interactions underlying rapid and selective translocation through the nuclear pore complex

PubMed Central

Hayama, Ryo; Sparks, Samuel; Hecht, Lee M.; Dutta, Kaushik; Karp, Jerome M.; Cabana, Christina M.; Rout, Michael P.; Cowburn, David

2018-01-01

Intrinsically disordered proteins (IDPs) play important roles in many biological systems. Given the vast conformational space that IDPs can explore, the thermodynamics of the interactions with their partners is closely linked to their biological functions. Intrinsically disordered regions of Phe–Gly nucleoporins (FG Nups) that contain multiple phenylalanine–glycine repeats are of particular interest, as their interactions with transport factors (TFs) underlie the paradoxically rapid yet also highly selective transport of macromolecules mediated by the nuclear pore complex. Here, we used NMR and isothermal titration calorimetry to thermodynamically characterize these multivalent interactions. These analyses revealed that a combination of low per-FG motif affinity and the enthalpy–entropy balance prevents high-avidity interaction between FG Nups and TFs, whereas the large number of FG motifs promotes frequent FG–TF contacts, resulting in enhanced selectivity. Our thermodynamic model underlines the importance of functional disorder of FG Nups. It helps explain the rapid and selective translocation of TFs through the nuclear pore complex and further expands our understanding of the mechanisms of “fuzzy” interactions involving IDPs. PMID:29374059

Diffusion Geometry Unravels the Emergence of Functional Clusters in Collective Phenomena.

PubMed

De Domenico, Manlio

2017-04-21

Collective phenomena emerge from the interaction of natural or artificial units with a complex organization. The interplay between structural patterns and dynamics might induce functional clusters that, in general, are different from topological ones. In biological systems, like the human brain, the overall functionality is often favored by the interplay between connectivity and synchronization dynamics, with functional clusters that do not coincide with anatomical modules in most cases. In social, sociotechnical, and engineering systems, the quest for consensus favors the emergence of clusters. Despite the unquestionable evidence for mesoscale organization of many complex systems and the heterogeneity of their interconnectivity, a way to predict and identify the emergence of functional modules in collective phenomena continues to elude us. Here, we propose an approach based on random walk dynamics to define the diffusion distance between any pair of units in a networked system. Such a metric allows us to exploit the underlying diffusion geometry to provide a unifying framework for the intimate relationship between metastable synchronization, consensus, and random search dynamics in complex networks, pinpointing the functional mesoscale organization of synthetic and biological systems.

Diffusion Geometry Unravels the Emergence of Functional Clusters in Collective Phenomena

NASA Astrophysics Data System (ADS)

De Domenico, Manlio

2017-04-01

Collective phenomena emerge from the interaction of natural or artificial units with a complex organization. The interplay between structural patterns and dynamics might induce functional clusters that, in general, are different from topological ones. In biological systems, like the human brain, the overall functionality is often favored by the interplay between connectivity and synchronization dynamics, with functional clusters that do not coincide with anatomical modules in most cases. In social, sociotechnical, and engineering systems, the quest for consensus favors the emergence of clusters. Despite the unquestionable evidence for mesoscale organization of many complex systems and the heterogeneity of their interconnectivity, a way to predict and identify the emergence of functional modules in collective phenomena continues to elude us. Here, we propose an approach based on random walk dynamics to define the diffusion distance between any pair of units in a networked system. Such a metric allows us to exploit the underlying diffusion geometry to provide a unifying framework for the intimate relationship between metastable synchronization, consensus, and random search dynamics in complex networks, pinpointing the functional mesoscale organization of synthetic and biological systems.

Towards physical principles of biological evolution

NASA Astrophysics Data System (ADS)

Katsnelson, Mikhail I.; Wolf, Yuri I.; Koonin, Eugene V.

2018-03-01

Biological systems reach organizational complexity that far exceeds the complexity of any known inanimate objects. Biological entities undoubtedly obey the laws of quantum physics and statistical mechanics. However, is modern physics sufficient to adequately describe, model and explain the evolution of biological complexity? Detailed parallels have been drawn between statistical thermodynamics and the population-genetic theory of biological evolution. Based on these parallels, we outline new perspectives on biological innovation and major transitions in evolution, and introduce a biological equivalent of thermodynamic potential that reflects the innovation propensity of an evolving population. Deep analogies have been suggested to also exist between the properties of biological entities and processes, and those of frustrated states in physics, such as glasses. Such systems are characterized by frustration whereby local state with minimal free energy conflict with the global minimum, resulting in ‘emergent phenomena’. We extend such analogies by examining frustration-type phenomena, such as conflicts between different levels of selection, in biological evolution. These frustration effects appear to drive the evolution of biological complexity. We further address evolution in multidimensional fitness landscapes from the point of view of percolation theory and suggest that percolation at level above the critical threshold dictates the tree-like evolution of complex organisms. Taken together, these multiple connections between fundamental processes in physics and biology imply that construction of a meaningful physical theory of biological evolution might not be a futile effort. However, it is unrealistic to expect that such a theory can be created in one scoop; if it ever comes to being, this can only happen through integration of multiple physical models of evolutionary processes. Furthermore, the existing framework of theoretical physics is unlikely to suffice for adequate modeling of the biological level of complexity, and new developments within physics itself are likely to be required.

Additive manufacturing of biologically-inspired materials.

PubMed

Studart, André R

2016-01-21

Additive manufacturing (AM) technologies offer an attractive pathway towards the fabrication of functional materials featuring complex heterogeneous architectures inspired by biological systems. In this paper, recent research on the use of AM approaches to program the local chemical composition, structure and properties of biologically-inspired materials is reviewed. A variety of structural motifs found in biological composites have been successfully emulated in synthetic systems using inkjet-based, direct-writing, stereolithography and slip casting technologies. The replication in synthetic systems of design principles underlying such structural motifs has enabled the fabrication of lightweight cellular materials, strong and tough composites, soft robots and autonomously shaping structures with unprecedented properties and functionalities. Pushing the current limits of AM technologies in future research should bring us closer to the manufacturing capabilities of living organisms, opening the way for the digital fabrication of advanced materials with superior performance, lower environmental impact and new functionalities.

Leaf LIMS: A Flexible Laboratory Information Management System with a Synthetic Biology Focus.

PubMed

Craig, Thomas; Holland, Richard; D'Amore, Rosalinda; Johnson, James R; McCue, Hannah V; West, Anthony; Zulkower, Valentin; Tekotte, Hille; Cai, Yizhi; Swan, Daniel; Davey, Robert P; Hertz-Fowler, Christiane; Hall, Anthony; Caddick, Mark

2017-12-15

This paper presents Leaf LIMS, a flexible laboratory information management system (LIMS) designed to address the complexity of synthetic biology workflows. At the project's inception there was a lack of a LIMS designed specifically to address synthetic biology processes, with most systems focused on either next generation sequencing or biobanks and clinical sample handling. Leaf LIMS implements integrated project, item, and laboratory stock tracking, offering complete sample and construct genealogy, materials and lot tracking, and modular assay data capture. Hence, it enables highly configurable task-based workflows and supports data capture from project inception to completion. As such, in addition to it supporting synthetic biology it is ideal for many laboratory environments with multiple projects and users. The system is deployed as a web application through Docker and is provided under a permissive MIT license. It is freely available for download at https://leaflims.github.io .

Directed evolution and synthetic biology applications to microbial systems.

PubMed

Bassalo, Marcelo C; Liu, Rongming; Gill, Ryan T

2016-06-01

Biotechnology applications require engineering complex multi-genic traits. The lack of knowledge on the genetic basis of complex phenotypes restricts our ability to rationally engineer them. However, complex phenotypes can be engineered at the systems level, utilizing directed evolution strategies that drive whole biological systems toward desired phenotypes without requiring prior knowledge of the genetic basis of the targeted trait. Recent developments in the synthetic biology field accelerates the directed evolution cycle, facilitating engineering of increasingly complex traits in biological systems. In this review, we summarize some of the most recent advances in directed evolution and synthetic biology that allows engineering of complex traits in microbial systems. Then, we discuss applications that can be achieved through engineering at the systems level. Copyright © 2016 Elsevier Ltd. All rights reserved.

Metabolomic Analysis in Brain Research: Opportunities and Challenges

PubMed Central

Vasilopoulou, Catherine G.; Margarity, Marigoula; Klapa, Maria I.

2016-01-01

Metabolism being a fundamental part of molecular physiology, elucidating the structure and regulation of metabolic pathways is crucial for obtaining a comprehensive perspective of cellular function and understanding the underlying mechanisms of its dysfunction(s). Therefore, quantifying an accurate metabolic network activity map under various physiological conditions is among the major objectives of systems biology in the context of many biological applications. Especially for CNS, metabolic network activity analysis can substantially enhance our knowledge about the complex structure of the mammalian brain and the mechanisms of neurological disorders, leading to the design of effective therapeutic treatments. Metabolomics has emerged as the high-throughput quantitative analysis of the concentration profile of small molecular weight metabolites, which act as reactants and products in metabolic reactions and as regulatory molecules of proteins participating in many biological processes. Thus, the metabolic profile provides a metabolic activity fingerprint, through the simultaneous analysis of tens to hundreds of molecules of pathophysiological and pharmacological interest. The application of metabolomics is at its standardization phase in general, and the challenges for paving a standardized procedure are even more pronounced in brain studies. In this review, we support the value of metabolomics in brain research. Moreover, we demonstrate the challenges of designing and setting up a reliable brain metabolomic study, which, among other parameters, has to take into consideration the sex differentiation and the complexity of brain physiology manifested in its regional variation. We finally propose ways to overcome these challenges and design a study that produces reproducible and consistent results. PMID:27252656

Analysis of diffusion in curved surfaces and its application to tubular membranes.

PubMed

Klaus, Colin James Stockdale; Raghunathan, Krishnan; DiBenedetto, Emmanuele; Kenworthy, Anne K

2016-12-01

Diffusion of particles in curved surfaces is inherently complex compared with diffusion in a flat membrane, owing to the nonplanarity of the surface. The consequence of such nonplanar geometry on diffusion is poorly understood but is highly relevant in the case of cell membranes, which often adopt complex geometries. To address this question, we developed a new finite element approach to model diffusion on curved membrane surfaces based on solutions to Fick's law of diffusion and used this to study the effects of geometry on the entry of surface-bound particles into tubules by diffusion. We show that variations in tubule radius and length can distinctly alter diffusion gradients in tubules over biologically relevant timescales. In addition, we show that tubular structures tend to retain concentration gradients for a longer time compared with a comparable flat surface. These findings indicate that sorting of particles along the surfaces of tubules can arise simply as a geometric consequence of the curvature without any specific contribution from the membrane environment. Our studies provide a framework for modeling diffusion in curved surfaces and suggest that biological regulation can emerge purely from membrane geometry. © 2016 Klaus, Raghunathan, et al. This article is distributed by The American Society for Cell Biology under license from the author(s). Two months after publication it is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

Studying mechanism of radical reactions: From radiation to nitroxides as research tools

NASA Astrophysics Data System (ADS)

Maimon, Eric; Samuni, Uri; Goldstein, Sara

2018-02-01

Radicals are part of the chemistry of life, and ionizing radiation chemistry serves as an indispensable research tool for elucidation of the mechanism(s) underlying their reactions. The ever-increasing understanding of their involvement in diverse physiological and pathological processes has expanded the search for compounds that can diminish radical-induced damage. This review surveys the areas of research focusing on radical reactions and particularly with stable cyclic nitroxide radicals, which demonstrate unique antioxidative activities. Unlike common antioxidants that are progressively depleted under oxidative stress and yield secondary radicals, nitroxides are efficient radical scavengers yielding in most cases their respective oxoammonium cations, which are readily reduced back in the tissue to the nitroxide thus continuously being recycled. Nitroxides, which not only protect enzymes, cells, and laboratory animals from diverse kinds of biological injury, but also modify the catalytic activity of heme enzymes, could be utilized in chemical and biological systems serving as a research tool for elucidating mechanisms underlying complex chemical and biochemical processes.

From bacteria to mollusks: the principles underlying the biomineralization of iron oxide materials.

PubMed

Faivre, Damien; Godec, Tina Ukmar

2015-04-13

Various organisms possess a genetic program that enables the controlled formation of a mineral, a process termed biomineralization. The variety of biological material architectures is mind-boggling and arises from the ability of organisms to exert control over crystal nucleation and growth. The structure and composition of biominerals equip biomineralizing organisms with properties and functionalities that abiotically formed materials, made of the same mineral, usually lack. Therefore, elucidating the mechanisms underlying biomineralization and morphogenesis is of interdisciplinary interest to extract design principles that will enable the biomimetic formation of functional materials with similar capabilities. Herein, we summarize what is known about iron oxides formed by bacteria and mollusks for their magnetic and mechanical properties. We describe the chemical and biological machineries that are involved in controlling mineral precipitation and organization and show how these organisms are able to form highly complex structures under physiological conditions. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Comparative systems biology between human and animal models based on next-generation sequencing methods.

PubMed

Zhao, Yu-Qi; Li, Gong-Hua; Huang, Jing-Fei

2013-04-01

Animal models provide myriad benefits to both experimental and clinical research. Unfortunately, in many situations, they fall short of expected results or provide contradictory results. In part, this can be the result of traditional molecular biological approaches that are relatively inefficient in elucidating underlying molecular mechanism. To improve the efficacy of animal models, a technological breakthrough is required. The growing availability and application of the high-throughput methods make systematic comparisons between human and animal models easier to perform. In the present study, we introduce the concept of the comparative systems biology, which we define as "comparisons of biological systems in different states or species used to achieve an integrated understanding of life forms with all their characteristic complexity of interactions at multiple levels". Furthermore, we discuss the applications of RNA-seq and ChIP-seq technologies to comparative systems biology between human and animal models and assess the potential applications for this approach in the future studies.

Harnessing QbD, Programming Languages, and Automation for Reproducible Biology.

PubMed

Sadowski, Michael I; Grant, Chris; Fell, Tim S

2016-03-01

Building robust manufacturing processes from biological components is a task that is highly complex and requires sophisticated tools to describe processes, inputs, and measurements and administrate management of knowledge, data, and materials. We argue that for bioengineering to fully access biological potential, it will require application of statistically designed experiments to derive detailed empirical models of underlying systems. This requires execution of large-scale structured experimentation for which laboratory automation is necessary. This requires development of expressive, high-level languages that allow reusability of protocols, characterization of their reliability, and a change in focus from implementation details to functional properties. We review recent developments in these areas and identify what we believe is an exciting trend that promises to revolutionize biotechnology. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

On Wiener polarity index of bicyclic networks.

PubMed

Ma, Jing; Shi, Yongtang; Wang, Zhen; Yue, Jun

2016-01-11

Complex networks are ubiquitous in biological, physical and social sciences. Network robustness research aims at finding a measure to quantify network robustness. A number of Wiener type indices have recently been incorporated as distance-based descriptors of complex networks. Wiener type indices are known to depend both on the network's number of nodes and topology. The Wiener polarity index is also related to the cluster coefficient of networks. In this paper, based on some graph transformations, we determine the sharp upper bound of the Wiener polarity index among all bicyclic networks. These bounds help to understand the underlying quantitative graph measures in depth.

M≡E and M=E Complexes of Iron and Cobalt that Emphasize Three-fold Symmetry (E = O, N, NR)

PubMed Central

Saouma, Caroline T.; Peters, Jonas C.

2011-01-01

Mid-to-late transition metal complexes that feature terminal, multiply bonded ligands such as oxos, imides, and nitrides have been invoked as intermediates in several catalytic transformations of synthetic and biological significance. Until about ten years ago, isolable examples of such species were virtually unknown. Over the past decade or so, numerous chemically well-defined examples of such species have been discovered. In this context, the presentreview summarizes the development of 4- and 5-coordinate Fe(E) and Co(E) species under local three-fold symmetry. PMID:21625302

CamOptimus: a tool for exploiting complex adaptive evolution to optimize experiments and processes in biotechnology.

PubMed

Cankorur-Cetinkaya, Ayca; Dias, Joao M L; Kludas, Jana; Slater, Nigel K H; Rousu, Juho; Oliver, Stephen G; Dikicioglu, Duygu

2017-06-01

Multiple interacting factors affect the performance of engineered biological systems in synthetic biology projects. The complexity of these biological systems means that experimental design should often be treated as a multiparametric optimization problem. However, the available methodologies are either impractical, due to a combinatorial explosion in the number of experiments to be performed, or are inaccessible to most experimentalists due to the lack of publicly available, user-friendly software. Although evolutionary algorithms may be employed as alternative approaches to optimize experimental design, the lack of simple-to-use software again restricts their use to specialist practitioners. In addition, the lack of subsidiary approaches to further investigate critical factors and their interactions prevents the full analysis and exploitation of the biotechnological system. We have addressed these problems and, here, provide a simple-to-use and freely available graphical user interface to empower a broad range of experimental biologists to employ complex evolutionary algorithms to optimize their experimental designs. Our approach exploits a Genetic Algorithm to discover the subspace containing the optimal combination of parameters, and Symbolic Regression to construct a model to evaluate the sensitivity of the experiment to each parameter under investigation. We demonstrate the utility of this method using an example in which the culture conditions for the microbial production of a bioactive human protein are optimized. CamOptimus is available through: (https://doi.org/10.17863/CAM.10257).

Ribosome profiling reveals the what, when, where and how of protein synthesis.

PubMed

Brar, Gloria A; Weissman, Jonathan S

2015-11-01

Ribosome profiling, which involves the deep sequencing of ribosome-protected mRNA fragments, is a powerful tool for globally monitoring translation in vivo. The method has facilitated discovery of the regulation of gene expression underlying diverse and complex biological processes, of important aspects of the mechanism of protein synthesis, and even of new proteins, by providing a systematic approach for experimental annotation of coding regions. Here, we introduce the methodology of ribosome profiling and discuss examples in which this approach has been a key factor in guiding biological discovery, including its prominent role in identifying thousands of novel translated short open reading frames and alternative translation products.

High-throughput screening for bioactive components from traditional Chinese medicine.

PubMed

Zhu, Yanhui; Zhang, Zhiyun; Zhang, Meng; Mais, Dale E; Wang, Ming-Wei

2010-12-01

Throughout the centuries, traditional Chinese medicine has been a rich resource in the development of new drugs. Modern drug discovery, which relies increasingly on automated high throughput screening and quick hit-to-lead development, however, is confronted with the challenges of the chemical complexity associated with natural products. New technologies for biological screening as well as library building are in great demand in order to meet the requirements. Here we review the developments in these techniques under the perspective of their applicability in natural product drug discovery. Methods in library building, component characterizing, biological evaluation, and other screening methods including NMR and X-ray diffraction are discussed.

Investigating Processes of Materials Formation via Liquid Phase and Cryogenic TEM

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

De Yoreo, James J.; Sommerdijk, Nico

2016-06-14

The formation of materials in solutions is a widespread phenomenon in synthetic, biological and geochemical systems, occurring through dynamic processes of nucleation, self-assembly, crystal growth, and coarsening. The recent advent of liquid phase TEM and advances in cryogenic TEM are transforming our understanding of these phenomena by providing new insights into the underlying physical and chemical mechanisms. The techniques have been applied to metallic and semiconductor nanoparticles, geochemical and biological minerals, electrochemical systems, macromolecular complexes, and selfassembling systems, both organic and inorganic. New instrumentation and methodologies currently on the horizon promise new opportunities for advancing the science of materials synthesis.

Living matter—nexus of physics and biology in the 21st century

PubMed Central

Gardel, Margaret L.

2012-01-01

Cells are made up of complex assemblies of cytoskeletal proteins that facilitate force transmission from the molecular to cellular scale to regulate cell shape and force generation. The “living matter” formed by the cytoskeleton facilitates versatile and robust behaviors of cells, including their migration, adhesion, division, and morphology, that ultimately determine tissue architecture and mechanics. Elucidating the underlying physical principles of such living matter provides great opportunities in both biology and physics. For physicists, the cytoskeleton provides an exceptional toolbox to study materials far from equilibrium. For biologists, these studies will provide new understanding of how molecular-scale processes determine cell morphological changes. PMID:23112229

Spectral characterization, cyclic voltammetry, morphology, biological activities and DNA cleaving studies of amino acid Schiff base metal(II) complexes

NASA Astrophysics Data System (ADS)

Neelakantan, M. A.; Rusalraj, F.; Dharmaraja, J.; Johnsonraja, S.; Jeyakumar, T.; Sankaranarayana Pillai, M.

2008-12-01

Metal complexes are synthesized with Schiff bases derived from o-phthalaldehyde (opa) and amino acids viz., glycine (gly) L-alanine (ala), L-phenylalanine (pal). Metal ions coordinate in a tetradentate or hexadentate manner with these N 2O 2 donor ligands, which are characterized by elemental analysis, molar conductance, magnetic moments, IR, electronic, 1H NMR and EPR spectral studies. The elemental analysis suggests the stoichiometry to be 1:1 (metal:ligand). Based on EPR studies, spin-Hamiltonian and bonding parameters have been calculated. The g-values calculated for copper complexes at 300 K and in frozen DMSO (77 K) indicate the presence of the unpaired electron in the d orbital. The evaluated metal-ligand bonding parameters showed strong in-plane σ- and π-bonding. X-ray diffraction (XRD) and scanning electron micrography (SEM) analysis provide the crystalline nature and the morphology of the metal complexes. The cyclic voltammograms of the Cu(II)/Mn(II)/VO(II) complexes investigated in DMSO solution exhibit metal centered electroactivity in the potential range -1.5 to +1.5 V. The electrochemical data obtained for Cu(II) complexes explains the change of structural arrangement of the ligand around Cu(II) ions. The biological activity of the complexes has been tested on eight bacteria and three fungi. Cu(II) and Ni(II) complexes show an increased activity in comparison to the controls. The metal complexes of opapal Schiff base were evaluated for their DNA cleaving activities with calf-thymus DNA (CT DNA) under aerobic conditions. Cu(II) and VO(II) complexes show more pronounced activity in presence of the oxidant.

When physics is not "just physics": complexity science invites new measurement frames for exploring the physics of cognitive and biological development.

PubMed

Kelty-Stephen, Damian; Dixon, James A

2012-01-01

The neurobiological sciences have struggled to resolve the physical foundations for biological and cognitive phenomena with a suspicion that biological and cognitive systems, capable of exhibiting and contributing to structure within themselves and through their contexts, are fundamentally distinct or autonomous from purely physical systems. Complexity science offers new physics-based approaches to explaining biological and cognitive phenomena. In response to controversy over whether complexity science might seek to "explain away" biology and cognition as "just physics," we propose that complexity science serves as an application of recent advances in physics to phenomena in biology and cognition without reducing or undermining the integrity of the phenomena to be explained. We highlight that physics is, like the neurobiological sciences, an evolving field and that the threat of reduction is overstated. We propose that distinctions between biological and cognitive systems from physical systems are pretheoretical and thus optional. We review our own work applying insights from post-classical physics regarding turbulence and fractal fluctuations to the problems of developing cognitive structure. Far from hoping to reduce biology and cognition to "nothing but" physics, we present our view that complexity science offers new explanatory frameworks for considering physical foundations of biological and cognitive phenomena.

Multilayer network modeling of integrated biological systems. Comment on "Network science of biological systems at different scales: A review" by Gosak et al.

NASA Astrophysics Data System (ADS)

De Domenico, Manlio

2018-03-01

Biological systems, from a cell to the human brain, are inherently complex. A powerful representation of such systems, described by an intricate web of relationships across multiple scales, is provided by complex networks. Recently, several studies are highlighting how simple networks - obtained by aggregating or neglecting temporal or categorical description of biological data - are not able to account for the richness of information characterizing biological systems. More complex models, namely multilayer networks, are needed to account for interdependencies, often varying across time, of biological interacting units within a cell, a tissue or parts of an organism.

Standardization in synthetic biology: an engineering discipline coming of age.

PubMed

Decoene, Thomas; De Paepe, Brecht; Maertens, Jo; Coussement, Pieter; Peters, Gert; De Maeseneire, Sofie L; De Mey, Marjan

2018-08-01

Leaping DNA read-and-write technologies, and extensive automation and miniaturization are radically transforming the field of biological experimentation by providing the tools that enable the cost-effective high-throughput required to address the enormous complexity of biological systems. However, standardization of the synthetic biology workflow has not kept abreast with dwindling technical and resource constraints, leading, for example, to the collection of multi-level and multi-omics large data sets that end up disconnected or remain under- or even unexploited. In this contribution, we critically evaluate the various efforts, and the (limited) success thereof, in order to introduce standards for defining, designing, assembling, characterizing, and sharing synthetic biology parts. The causes for this success or the lack thereof, as well as possible solutions to overcome these, are discussed. Akin to other engineering disciplines, extensive standardization will undoubtedly speed-up and reduce the cost of bioprocess development. In this respect, further implementation of synthetic biology standards will be crucial for the field in order to redeem its promise, i.e. to enable predictable forward engineering.

Organometallic compounds: an opportunity for chemical biology?

PubMed

Patra, Malay; Gasser, Gilles

2012-06-18

Organometallic compounds are renowned for their remarkable applications in the field of catalysis, but much less is known about their potential in chemical biology. Indeed, such compounds have long been considered to be either unstable under physiological conditions or cytotoxic. As a consequence, little attention has been paid to their possible utilisation for biological purposes. Because of their outstanding physicochemical properties, which include chemical stability, structural diversity and unique photo- and electrochemical properties, however, organometallic compounds have the ability to play a leading role in the field of chemical biology. Indeed, remarkable examples of the use of such compounds-notably as enzyme inhibitors and as luminescent agents-have recently been reported. Here we summarise recent advances in the use of organometallic compounds for chemical biology purposes, an area that we define as "organometallic chemical biology". We also demonstrate that these recent discoveries are only a beginning and that many other organometallic complexes are likely to be found useful in this field of research in the near future. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A Series of Zn(II) Terpyridine-Based Nitrate Complexes as Two-Photon Fluorescent Probe for Identifying Apoptotic and Living Cells via Subcellular Immigration.

PubMed

Liu, Dandan; Zhang, Mingzhu; Du, Wei; Hu, Lei; Li, Fei; Tian, Xiaohe; Wang, Aidong; Zhang, Qiong; Zhang, Zhongping; Wu, Jieying; Tian, Yupeng

2018-06-19

Two-photon active probe to label apoptotic cells plays a significant role in biological systems. However, discrimination of live/apoptotic cells at subcellular level under microscopy remains unachieved. Here, three novel Zn(II) terpyridine-based nitrate complexes (C1-C3) containing different pull/push units were designed. The structures of the ligands and their corresponding Zn(II) complexes were confirmed by single-crystal X-ray diffraction analysis. On the basis of the comprehensive comparison, C3 had a suitable two-photon absorption cross section in the near-infrared wavelength and good biocompatibility. Under two-photon confocal microscopy and transmission electron microscopy, it is found that C3 could target mitochondria in living cells but immigrate into the nucleolus during the apoptotic process. This dual-functional probe (C3) not only offers a valuable image tool but also acts as an indicator for cell mortality at subcellular level in a real-time manner.

Genetic interactions underlying hybrid male sterility in the Drosophila bipectinata species complex.

PubMed

Mishra, Paras Kumar; Singh, Bashisth Narayan

2006-06-01

Understanding genetic mechanisms underlying hybrid male sterility is one of the most challenging problems in evolutionary biology especially speciation. By using the interspecific hybridization method roles of Y chromosome, Major Hybrid Sterility (MHS) genes and cytoplasm in sterility of hybrid males have been investigated in a promising group, the Drosophila bipectinata species complex that consists of four closely related species: D. pseudoananassae, D. bipectinata, D. parabipectinata and D. malerkotliana. The interspecific introgression analyses show that neither cytoplasm nor MHS genes are involved but X-Y interactions may be playing major role in hybrid male sterility between D. pseudoananassae and the other three species. The results of interspecific introgression analyses also show considerable decrease in the number of males in the backcross offspring and all males have atrophied testes. There is a significant positive correlation between sex - ratio distortion and severity of sterility in backcross males. These findings provide evidence that D. pseudoananassae is remotely related with other three species of the D. bipectinata species complex.

Molecular and physiological manifestations and measurement of aging in humans.

PubMed

Khan, Sadiya S; Singer, Benjamin D; Vaughan, Douglas E

2017-08-01

Biological aging is associated with a reduction in the reparative and regenerative potential in tissues and organs. This reduction manifests as a decreased physiological reserve in response to stress (termed homeostenosis) and a time-dependent failure of complex molecular mechanisms that cumulatively create disorder. Aging inevitably occurs with time in all organisms and emerges on a molecular, cellular, organ, and organismal level with genetic, epigenetic, and environmental modulators. Individuals with the same chronological age exhibit differential trajectories of age-related decline, and it follows that we should assess biological age distinctly from chronological age. In this review, we outline mechanisms of aging with attention to well-described molecular and cellular hallmarks and discuss physiological changes of aging at the organ-system level. We suggest methods to measure aging with attention to both molecular biology (e.g., telomere length and epigenetic marks) and physiological function (e.g., lung function and echocardiographic measurements). Finally, we propose a framework to integrate these molecular and physiological data into a composite score that measures biological aging in humans. Understanding the molecular and physiological phenomena that drive the complex and multifactorial processes underlying the variable pace of biological aging in humans will inform how researchers assess and investigate health and disease over the life course. This composite biological age score could be of use to researchers seeking to characterize normal, accelerated, and exceptionally successful aging as well as to assess the effect of interventions aimed at modulating human aging. © 2017 The Authors. Aging Cell published by the Anatomical Society and John Wiley & Sons Ltd.

Transport of gadolinium- and arsenic-based pharmaceuticals in saturated soil under various redox conditions.

PubMed

Menahem, Adi; Dror, Ishai; Berkowitz, Brian

2016-02-01

The release of pharmaceuticals and personal care products (PPCPs) to the soil-water environment necessitates understanding of PPCP transport behavior under conditions that account for dynamic flow and varying redox states. This study investigates the transport of two organometallic PPCPs, Gd-DTPA and roxarsone (arsenic compound) and their metal salts (Gd(NO3)3, AsNaO2); Gd-DTPA is used widely as a contrasting agent for MRI, while roxarsone is applied extensively as a food additive in the broiler poultry industry. Here, we present column experiments using sand and Mediterranean red sandy clay soil, performed under several redox conditions. The metal salts were almost completely immobile. In contrast, transport of Gd-DTPA and roxarsone was affected by the soil type. Roxarsone was also affected by the different redox conditions, showing delayed breakthrough curves as the redox potential became more negative due to biological activity (chemically-strong reducing conditions did not affect the transport). Mechanisms that include adsorptive retardation for aerobic and nitrate-reducing conditions, and non-adsorptive retardation for iron-reducing, sulfate-reducing and biologically-strong reducing conditions, are suggested to explain the roxarsone behavior. Gd-DTPA is found to be a stable complex, with potential for high mobility in groundwater systems, whereas roxarsone transport through groundwater systems is affected by redox environments, demonstrating high mobility under aerobic and nitrate-reducing conditions and delayed transport under iron-reducing, sulfate-reducing and biologically-strong reducing conditions. Copyright © 2015 Elsevier Ltd. All rights reserved.

Insights into Protein–Ligand Interactions: Mechanisms, Models, and Methods

PubMed Central

Du, Xing; Li, Yi; Xia, Yuan-Ling; Ai, Shi-Meng; Liang, Jing; Sang, Peng; Ji, Xing-Lai; Liu, Shu-Qun

2016-01-01

Molecular recognition, which is the process of biological macromolecules interacting with each other or various small molecules with a high specificity and affinity to form a specific complex, constitutes the basis of all processes in living organisms. Proteins, an important class of biological macromolecules, realize their functions through binding to themselves or other molecules. A detailed understanding of the protein–ligand interactions is therefore central to understanding biology at the molecular level. Moreover, knowledge of the mechanisms responsible for the protein-ligand recognition and binding will also facilitate the discovery, design, and development of drugs. In the present review, first, the physicochemical mechanisms underlying protein–ligand binding, including the binding kinetics, thermodynamic concepts and relationships, and binding driving forces, are introduced and rationalized. Next, three currently existing protein-ligand binding models—the “lock-and-key”, “induced fit”, and “conformational selection”—are described and their underlying thermodynamic mechanisms are discussed. Finally, the methods available for investigating protein–ligand binding affinity, including experimental and theoretical/computational approaches, are introduced, and their advantages, disadvantages, and challenges are discussed. PMID:26821017

Learning contextual gene set interaction networks of cancer with condition specificity

PubMed Central

2013-01-01

Background Identifying similarities and differences in the molecular constitutions of various types of cancer is one of the key challenges in cancer research. The appearances of a cancer depend on complex molecular interactions, including gene regulatory networks and gene-environment interactions. This complexity makes it challenging to decipher the molecular origin of the cancer. In recent years, many studies reported methods to uncover heterogeneous depictions of complex cancers, which are often categorized into different subtypes. The challenge is to identify diverse molecular contexts within a cancer, to relate them to different subtypes, and to learn underlying molecular interactions specific to molecular contexts so that we can recommend context-specific treatment to patients. Results In this study, we describe a novel method to discern molecular interactions specific to certain molecular contexts. Unlike conventional approaches to build modular networks of individual genes, our focus is to identify cancer-generic and subtype-specific interactions between contextual gene sets, of which each gene set share coherent transcriptional patterns across a subset of samples, termed contextual gene set. We then apply a novel formulation for quantitating the effect of the samples from each subtype on the calculated strength of interactions observed. Two cancer data sets were analyzed to support the validity of condition-specificity of identified interactions. When compared to an existing approach, the proposed method was much more sensitive in identifying condition-specific interactions even in heterogeneous data set. The results also revealed that network components specific to different types of cancer are related to different biological functions than cancer-generic network components. We found not only the results that are consistent with previous studies, but also new hypotheses on the biological mechanisms specific to certain cancer types that warrant further investigations. Conclusions The analysis on the contextual gene sets and characterization of networks of interaction composed of these sets discovered distinct functional differences underlying various types of cancer. The results show that our method successfully reveals many subtype-specific regions in the identified maps of biological contexts, which well represent biological functions that can be connected to specific subtypes. PMID:23418942

Biologically-Inspired Concepts for Self-Management of Complexity

NASA Technical Reports Server (NTRS)

Sterritt, Roy; Hinchey, G.

2006-01-01

Inherent complexity in large-scale applications may be impossible to eliminate or even ameliorate despite a number of promising advances. In such cases, the complexity must be tolerated and managed. Such management may be beyond the abilities of humans, or require such overhead as to make management by humans unrealistic. A number of initiatives inspired by concepts in biology have arisen for self-management of complex systems. We present some ideas and techniques we have been experimenting with, inspired by lesser-known concepts in biology that show promise in protecting complex systems and represent a step towards self-management of complexity.

Mosaic, self-similarity logic, and biological attraction principles: three explanatory instruments in biology.

PubMed

Agnati, Luigi F; Baluska, Frantisek; Barlow, Peter W; Guidolin, Diego

2009-11-01

From a structural standpoint, living organisms are organized like a nest of Russian matryoshka dolls, in which structures are buried within one another. From a temporal point of view, this type of organization is the result of a history comprised of a set of time backcloths which have accompanied the passage of living matter from its origins up to the present day. The aim of the present paper is to indicate a possible course of this 'passage through time, and suggest how today's complexity has been reached by living organisms. This investigation will employ three conceptual tools, namely the Mosaic, Self-Similarity Logic, and the Biological Attraction principles. Self-Similarity Logic indicates the self-consistency by which elements of a living system interact, irrespective of the spatiotemporal level under consideration. The term Mosaic indicates how, from the same set of elements assembled according to different patterns, it is possible to arrive at completely different constructions: hence, each system becomes endowed with different emergent properties. The Biological Attraction principle states that there is an inherent drive for association and merging of compatible elements at all levels of biological complexity. By analogy with the gravitation law in physics, biological attraction is based on the evidence that each living organism creates an attractive field around itself. This field acts as a sphere of influence that actively attracts similar fields of other biological systems, thereby modifying salient features of the interacting organisms. Three specific organizational levels of living matter, namely the molecular, cellular, and supracellular levels, have been considered in order to analyse and illustrate the interpretative as well as the predictive roles of each of these three explanatory principles.

Discrete Cu(i) complexes for azide-alkyne annulations of small molecules inside mammalian cells.

PubMed

Miguel-Ávila, Joan; Tomás-Gamasa, María; Olmos, Andrea; Pérez, Pedro J; Mascareñas, José L

2018-02-21

The archetype reaction of "click" chemistry, namely, the copper-promoted azide-alkyne cycloaddition (CuAAC), has found an impressive number of applications in biological chemistry. However, methods for promoting intermolecular annulations of exogenous, small azides and alkynes in the complex interior of mammalian cells, are essentially unknown. Herein we demonstrate that isolated, well-defined copper(i)-tris(triazolyl) complexes featuring designed ligands can readily enter mammalian cells and promote intracellular CuAAC annulations of small, freely diffusible molecules. In addition to simplifying protocols and avoiding the addition of "non-innocent" reductants, the use of these premade copper complexes leads to more efficient processes than with the alternative, in situ made copper species prepared from Cu(ii) sources, tris(triazole) ligands and sodium ascorbate. Under the reaction conditions, the well-defined copper complexes exhibit very good cell penetration properties, and do not present significant toxicities.

Abundance and Temperature Dependency of Protein-Protein Interaction Revealed by Interface Structure Analysis and Stability Evolution

PubMed Central

He, Yi-Ming; Ma, Bin-Guang

2016-01-01

Protein complexes are major forms of protein-protein interactions and implement essential biological functions. The subunit interface in a protein complex is related to its thermostability. Though the roles of interface properties in thermal adaptation have been investigated for protein complexes, the relationship between the interface size and the expression level of the subunits remains unknown. In the present work, we studied this relationship and found a positive correlation in thermophiles rather than mesophiles. Moreover, we found that the protein interaction strength in complexes is not only temperature-dependent but also abundance-dependent. The underlying mechanism for the observed correlation was explored by simulating the evolution of protein interface stability, which highlights the avoidance of misinteraction. Our findings make more complete the picture of the mechanisms for protein complex thermal adaptation and provide new insights into the principles of protein-protein interactions. PMID:27220911

Abundance and Temperature Dependency of Protein-Protein Interaction Revealed by Interface Structure Analysis and Stability Evolution

NASA Astrophysics Data System (ADS)

He, Yi-Ming; Ma, Bin-Guang

2016-05-01

Protein complexes are major forms of protein-protein interactions and implement essential biological functions. The subunit interface in a protein complex is related to its thermostability. Though the roles of interface properties in thermal adaptation have been investigated for protein complexes, the relationship between the interface size and the expression level of the subunits remains unknown. In the present work, we studied this relationship and found a positive correlation in thermophiles rather than mesophiles. Moreover, we found that the protein interaction strength in complexes is not only temperature-dependent but also abundance-dependent. The underlying mechanism for the observed correlation was explored by simulating the evolution of protein interface stability, which highlights the avoidance of misinteraction. Our findings make more complete the picture of the mechanisms for protein complex thermal adaptation and provide new insights into the principles of protein-protein interactions.

Synthesis, spectroscopic characterization, thermal studies, catalytic epoxidation and biological activity of chromium and molybdenum hexacarbonyl bound to a novel N 2O 2 Schiff base

NASA Astrophysics Data System (ADS)

Abdel Aziz, Ayman A.

2010-08-01

Complexes of M(CO) 6 (M = Cr and Mo) with novel Schiff base N,N'-bis(salicylidene)4,5-dichloro-1,2-phenylenediamine (H 2L) were prepared in benzene in two different conditions: (i) under reduced pressure resulting the dicarbonyl precursors [Cr(CO) 2(H 2L)] and [Mo(CO) 2(L)] and (ii) in air resulting the oxo complex [Cr(O)(L)] and the dioxo complex [Mo(O) 2(L)]. The complexes were characterized by elemental analysis, IR, 1H NMR, mass spectrometry, and magnetic measurement. Thermal behaviors of the complexes were also studied by using thermogravimetric analysis (TGA). The catalytic activity of the novel complexes in the epoxidation of cyclooctene, cyclohexene, 1-octene and 1-hexene with tert-butyl-hydroperoxide (TBHP) in methylene chloride was investigated. The antimicrobial activities of the ligand and their complexes have been screened against various strains of bacteria and fungi and the results have been compared with some known antibiotics.

How do precision medicine and system biology response to human body's complex adaptability?

PubMed

Yuan, Bing

2016-12-01

In the field of life sciences, although system biology and "precision medicine" introduce some complex scientifific methods and techniques, it is still based on the "analysis-reconstruction" of reductionist theory as a whole. Adaptability of complex system increase system behaviour uncertainty as well as the difficulties of precise identifification and control. It also put systems biology research into trouble. To grasp the behaviour and characteristics of organism fundamentally, systems biology has to abandon the "analysis-reconstruction" concept. In accordance with the guidelines of complexity science, systems biology should build organism model from holistic level, just like the Chinese medicine did in dealing with human body and disease. When we study the living body from the holistic level, we will fifind the adaptability of complex system is not the obstacle that increases the diffificulty of problem solving. It is the "exceptional", "right-hand man" that helping us to deal with the complexity of life more effectively.

Tracking down the links between charged particles and biological response: A UK perspective

NASA Astrophysics Data System (ADS)

Hill, Mark A.

2013-07-01

The UK has a long history of radiobiology research into charged particles, with interest likely to expand in the coming years following the recent government announcement of £250 million to build two proton beam therapy facilities in the UK. A brief overview of research and facilities past and present with respect to radiation protection and oncology along with biological consequences and underlying mechanisms will be presented and discussed. Increased knowledge of the mechanisms underpinning the radiation action on biological systems is important in understanding, not only the risks associated with exposure, but also in optimising radiotherapy treatment of cancer. Ionizing radiation is always in the form of structure tracks which are a unique characteristic of ionizing radiation alone producing damage grossly different and far more biologically effective than endogenous damage. The track structure is the prime determinant of biological response to DNA, with charged particles of increasing LET leading to an increase in the frequency and complexity of clustered DNA damage. High-LET particles will also produce non-homogeneous dose distribution through a cell nucleus resulting in correlated DNA breaks along the path of the particle and an increase in the probability of complex chromosomal rearrangements. However it is now well established that there is variety of phenomena that do not conform to the conventional paradigm of targeted radiobiology, but there is insufficient evidence to assess the implications of these non-targeted effects for radiotherapy or relevance to risk for human health.

Evaluation of hierarchical models for integrative genomic analyses.

PubMed

Denis, Marie; Tadesse, Mahlet G

2016-03-01

Advances in high-throughput technologies have led to the acquisition of various types of -omic data on the same biological samples. Each data type gives independent and complementary information that can explain the biological mechanisms of interest. While several studies performing independent analyses of each dataset have led to significant results, a better understanding of complex biological mechanisms requires an integrative analysis of different sources of data. Flexible modeling approaches, based on penalized likelihood methods and expectation-maximization (EM) algorithms, are studied and tested under various biological relationship scenarios between the different molecular features and their effects on a clinical outcome. The models are applied to genomic datasets from two cancer types in the Cancer Genome Atlas project: glioblastoma multiforme and ovarian serous cystadenocarcinoma. The integrative models lead to improved model fit and predictive performance. They also provide a better understanding of the biological mechanisms underlying patients' survival. Source code implementing the integrative models is freely available at https://github.com/mgt000/IntegrativeAnalysis along with example datasets and sample R script applying the models to these data. The TCGA datasets used for analysis are publicly available at https://tcga-data.nci.nih.gov/tcga/tcgaDownload.jsp marie.denis@cirad.fr or mgt26@georgetown.edu Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

No longer "if," but "when": the coming abbreviated approval pathway for follow-on biologics.

PubMed

Kelly, Jeremiah J; David, Michael

2009-01-01

Abbreviated approval of follow-on biologics involves answering complex scientific, legal, and policy questions. The Food and Drug Administration (FDA or the Agency) asserts that it lacks the statutory authority to approve follow-on versions of biologics licensed under Section 351 of the Public Health Service Act (PHSA). Despite persuasive arguments to the contrary the one hundred and tenth Congress entertained four legislative proposals to give FDA this authority, each markedly different. It is no longer a question of "if," but "when" FDA will receive authority to review and license abbreviated applications for follow-on biologics. Any legislation in the one hundred and eleventh Congress must determine: (1) if FDA should be granted authority to develop an abbreviated pathway through rulemaking or guidance; (2) if human clinical trials should be mandatory or discretionary; (3) the feasibility of interchangeability determinations in light of patient safety concerns; (4) the duration of marketing exclusivity for associated products; (5) which products are eligible for follow-on approval; and (6) the degree to which uniformity is achievable between the FD&C Act and the PHSA. This paper recommends the one hundred and eleventh Congress strike a balance between patient safety, incentives for product innovation, price competition, and the need for a flexible, transparent process that capitalizes on FDA's growing expertise with follow-on biologics approvals under Section 505(b)(2) of the FD&C Act.

Introductory Biology Students' Use of Enhanced Answer Keys and Reflection Questions to Engage in Metacognition and Enhance Understanding.

PubMed

Sabel, Jaime L; Dauer, Joseph T; Forbes, Cory T

2017-01-01

Providing feedback to students as they learn to integrate individual concepts into complex systems is an important way to help them to develop robust understanding, but it is challenging in large, undergraduate classes for instructors to provide feedback that is frequent and directed enough to help individual students. Various scaffolds can be used to help students engage in self-regulated learning and generate internal feedback to improve their learning. This study examined the use of enhanced answer keys with added reflection questions and instruction as scaffolds for engaging undergraduate students in self-regulated learning within an introductory biology course. Study findings show that both the enhanced answer keys and reflection questions helped students to engage in metacognition and develop greater understanding of biological concepts. Further, students who received additional instruction on the use of the scaffolds changed how they used them and, by the end of the semester, were using the scaffolds in significantly different ways and showed significantly higher learning gains than students who did not receive the instruction. These findings provide evidence for the benefit of designing scaffolds within biology courses that will support students in engaging in metacognition and enhancing their understanding of biological concepts. © 2017 J. L. Sabel et al. CBE—Life Sciences Education © 2017 The American Society for Cell Biology. This article is distributed by The American Society for Cell Biology under license from the author(s). It is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

Development of the Central Dogma Concept Inventory (CDCI) Assessment Tool.

PubMed

Newman, Dina L; Snyder, Christopher W; Fisk, J Nick; Wright, L Kate

2016-01-01

Scientific teaching requires scientifically constructed, field-tested instruments to accurately evaluate student thinking and gauge teacher effectiveness. We have developed a 23-question, multiple select-format assessment of student understanding of the essential concepts of the central dogma of molecular biology that is appropriate for all levels of undergraduate biology. Questions for the Central Dogma Concept Inventory (CDCI) tool were developed and iteratively revised based on student language and review by experts. The ability of the CDCI to discriminate between levels of understanding of the central dogma is supported by field testing (N= 54), and large-scale beta testing (N= 1733). Performance on the assessment increased with experience in biology; scores covered a broad range and showed no ceiling effect, even with senior biology majors, and pre/posttesting of a single class focused on the central dogma showed significant improvement. The multiple-select format reduces the chances of correct answers by random guessing, allows students at different levels to exhibit the extent of their knowledge, and provides deeper insight into the complexity of student thinking on each theme. To date, the CDCI is the first tool dedicated to measuring student thinking about the central dogma of molecular biology, and version 5 is ready to use. © 2016 D. L. Newman et al. CBE—Life Sciences Education © 2016 The American Society for Cell Biology. This article is distributed by The American Society for Cell Biology under license from the author(s). It is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

[The vanadium compounds: chemistry, synthesis, insulinomimetic properties].

PubMed

Fedorova, E V; Buriakina, A V; Vorob'eva, N M; Baranova, N I

2014-01-01

The review considers the biological role of vanadium, its participation in various processes in humans and other mammals, and the anti-diabetic effect of its compounds. Vanadium salts have persistent hypoglycemic and antihyperlipidemic effects and reduce the probability of secondary complications in animals with experimental diabetes. The review contains a detailed description of all major synthesized vanadium complexes having antidiabetic activity. Currently, vanadium complexes with organic ligands are more effective and safer than the inorganic salts. Despite the proven efficacy of these compounds as the anti-diabetic agents in animal models, only one organic complex of vanadium is currently under the second phase of clinical trials. All of the considered data suggest that vanadium compound are a new promising class of drugs in modern pharmacotherapy of diabetes.

Reactome graph database: Efficient access to complex pathway data

PubMed Central

Korninger, Florian; Viteri, Guilherme; Marin-Garcia, Pablo; Ping, Peipei; Wu, Guanming; Stein, Lincoln; D’Eustachio, Peter

2018-01-01

Reactome is a free, open-source, open-data, curated and peer-reviewed knowledgebase of biomolecular pathways. One of its main priorities is to provide easy and efficient access to its high quality curated data. At present, biological pathway databases typically store their contents in relational databases. This limits access efficiency because there are performance issues associated with queries traversing highly interconnected data. The same data in a graph database can be queried more efficiently. Here we present the rationale behind the adoption of a graph database (Neo4j) as well as the new ContentService (REST API) that provides access to these data. The Neo4j graph database and its query language, Cypher, provide efficient access to the complex Reactome data model, facilitating easy traversal and knowledge discovery. The adoption of this technology greatly improved query efficiency, reducing the average query time by 93%. The web service built on top of the graph database provides programmatic access to Reactome data by object oriented queries, but also supports more complex queries that take advantage of the new underlying graph-based data storage. By adopting graph database technology we are providing a high performance pathway data resource to the community. The Reactome graph database use case shows the power of NoSQL database engines for complex biological data types. PMID:29377902

oGNM: online computation of structural dynamics using the Gaussian Network Model

PubMed Central

Yang, Lee-Wei; Rader, A. J.; Liu, Xiong; Jursa, Cristopher Jon; Chen, Shann Ching; Karimi, Hassan A.; Bahar, Ivet

2006-01-01

An assessment of the equilibrium dynamics of biomolecular systems, and in particular their most cooperative fluctuations accessible under native state conditions, is a first step towards understanding molecular mechanisms relevant to biological function. We present a web-based system, oGNM that enables users to calculate online the shape and dispersion of normal modes of motion for proteins, oligonucleotides and their complexes, or associated biological units, using the Gaussian Network Model (GNM). Computations with the new engine are 5–6 orders of magnitude faster than those using conventional normal mode analyses. Two cases studies illustrate the utility of oGNM. The first shows that the thermal fluctuations predicted for 1250 non-homologous proteins correlate well with X-ray crystallographic data over a broad range [7.3–15 Å] of inter-residue interaction cutoff distances and the correlations improve with increasing observation temperatures. The second study, focused on 64 oligonucleotides and oligonucleotide–protein complexes, shows that good agreement with experiments is achieved by representing each nucleotide by three GNM nodes (as opposed to one-node-per-residue in proteins) along with uniform interaction ranges for all components of the complexes. These results open the way to a rapid assessment of the dynamics of DNA/RNA-containing complexes. The server can be accessed at . PMID:16845002

Conceptual Demand of Practical Work in Science Curricula. A Methodological Approach

NASA Astrophysics Data System (ADS)

Ferreira, Sílvia; Morais, Ana M.

2014-02-01

This article addresses the issue of the level of complexity of practical work in science curricula and is focused on the discipline of Biology and Geology at high school. The level of complexity is seen in terms of the emphasis on and types of practical work and, most importantly, in terms of its level of conceptual demand as given by the complexity of scientific knowledge, the degree of inter-relation between knowledges, and the complexity of cognitive skills. The study also analyzes recontextualizing processes that may occur within the official recontextualizing field. The study is psychologically and sociologically grounded, particularly on Bernstein's theory of pedagogic discourse. It uses a mixed methodology. The results show that practical work is poorly represented in the curriculum, particularly in the case of laboratory work. The level of conceptual demand of practical work varies according to the text under analysis, between the two subjects Biology and Geology, and, within each of them, between general and specific guidelines. Aspects studied are not clearly explicated to curriculum receivers (teachers and textbooks authors). The meaning of these findings is discussed in the article. In methodological terms, the study explores assumptions used in the analysis of the level of conceptual demand and presents innovative instruments constructed for developing this analysis.

An analytical platform for mass spectrometry-based identification and chemical analysis of RNA in ribonucleoprotein complexes.

PubMed

Taoka, Masato; Yamauchi, Yoshio; Nobe, Yuko; Masaki, Shunpei; Nakayama, Hiroshi; Ishikawa, Hideaki; Takahashi, Nobuhiro; Isobe, Toshiaki

2009-11-01

We describe here a mass spectrometry (MS)-based analytical platform of RNA, which combines direct nano-flow reversed-phase liquid chromatography (RPLC) on a spray tip column and a high-resolution LTQ-Orbitrap mass spectrometer. Operating RPLC under a very low flow rate with volatile solvents and MS in the negative mode, we could estimate highly accurate mass values sufficient to predict the nucleotide composition of a approximately 21-nucleotide small interfering RNA, detect post-transcriptional modifications in yeast tRNA, and perform collision-induced dissociation/tandem MS-based structural analysis of nucleolytic fragments of RNA at a sub-femtomole level. Importantly, the method allowed the identification and chemical analysis of small RNAs in ribonucleoprotein (RNP) complex, such as the pre-spliceosomal RNP complex, which was pulled down from cultured cells with a tagged protein cofactor as bait. We have recently developed a unique genome-oriented database search engine, Ariadne, which allows tandem MS-based identification of RNAs in biological samples. Thus, the method presented here has broad potential for automated analysis of RNA; it complements conventional molecular biology-based techniques and is particularly suited for simultaneous analysis of the composition, structure, interaction, and dynamics of RNA and protein components in various cellular RNP complexes.

[Detection of nitrite and nitrosocompounds in chemical systems and biological liquids by the calorimetric method].

PubMed

Titov, V Iu; Petrenko, Iu M; Vanin, A F; Stepuro, I I

2010-01-01

The capacity of nitrite, S-nitrosothiols (RS-NO), dinitrosyl iron complexes (DNICs) with thiol-containing ligands, and nitrosoamines to inhibit catalase has been used for the selective determination of these compounds in purely chemical systems and biological liquids: cow milk and colostram. The limiting sensitivity of the method is 50 nM. A comparison of the results of the determinations of RS-NO, DNIC, and nitrite by the catalase method and the Greese method conventionally used for nitrite detection showed that, firstly, Greese reagents decompose DNIC and RS-NO to form nitrite. Therefore, the Greese method cannot be used for nitrite determination in solutions of these substances. Secondly, Greese reagents interact with complexes of mercury ions with RS-NO, inducing the release of nitrosonium ions from the complex followed by the hydrolysis of nitrosonium to nitrite. Thus, the proposition about the spontaneous decay of the complexes of mercury ions with RS-NO is incorrect. Keeping in mind a high sensitivity of the method, the use of catalase as an enzyme detector of nitrosocompounds allows one to detect these compounds in neutral medium without prior purification of the object, thereby preventing artificial effects due to noncontrolled modifications of the compounds under study.

Reactome graph database: Efficient access to complex pathway data.

PubMed

Fabregat, Antonio; Korninger, Florian; Viteri, Guilherme; Sidiropoulos, Konstantinos; Marin-Garcia, Pablo; Ping, Peipei; Wu, Guanming; Stein, Lincoln; D'Eustachio, Peter; Hermjakob, Henning

2018-01-01

Reactome is a free, open-source, open-data, curated and peer-reviewed knowledgebase of biomolecular pathways. One of its main priorities is to provide easy and efficient access to its high quality curated data. At present, biological pathway databases typically store their contents in relational databases. This limits access efficiency because there are performance issues associated with queries traversing highly interconnected data. The same data in a graph database can be queried more efficiently. Here we present the rationale behind the adoption of a graph database (Neo4j) as well as the new ContentService (REST API) that provides access to these data. The Neo4j graph database and its query language, Cypher, provide efficient access to the complex Reactome data model, facilitating easy traversal and knowledge discovery. The adoption of this technology greatly improved query efficiency, reducing the average query time by 93%. The web service built on top of the graph database provides programmatic access to Reactome data by object oriented queries, but also supports more complex queries that take advantage of the new underlying graph-based data storage. By adopting graph database technology we are providing a high performance pathway data resource to the community. The Reactome graph database use case shows the power of NoSQL database engines for complex biological data types.

Addressing current challenges in cancer immunotherapy with mathematical and computational modelling.

PubMed

Konstorum, Anna; Vella, Anthony T; Adler, Adam J; Laubenbacher, Reinhard C

2017-06-01

The goal of cancer immunotherapy is to boost a patient's immune response to a tumour. Yet, the design of an effective immunotherapy is complicated by various factors, including a potentially immunosuppressive tumour microenvironment, immune-modulating effects of conventional treatments and therapy-related toxicities. These complexities can be incorporated into mathematical and computational models of cancer immunotherapy that can then be used to aid in rational therapy design. In this review, we survey modelling approaches under the umbrella of the major challenges facing immunotherapy development, which encompass tumour classification, optimal treatment scheduling and combination therapy design. Although overlapping, each challenge has presented unique opportunities for modellers to make contributions using analytical and numerical analysis of model outcomes, as well as optimization algorithms. We discuss several examples of models that have grown in complexity as more biological information has become available, showcasing how model development is a dynamic process interlinked with the rapid advances in tumour-immune biology. We conclude the review with recommendations for modellers both with respect to methodology and biological direction that might help keep modellers at the forefront of cancer immunotherapy development. © 2017 The Author(s).

Climate change and occupational allergies: an overview on biological pollution, exposure and prevention.

PubMed

D'Ovidio, Maria Concetta; Annesi-Maesano, Isabella; D'Amato, Gennaro; Cecchi, Lorenzo

2016-01-01

Climate change, air pollution, temperature increase and other environmental variables are modifying air quality, contributing to the increase of prevalence of allergic respiratory diseases. Allergies are complex diseases characterized by multilevel interactions between individual susceptibility, response to immune modulation and environmental exposures to physical, chemical and biological agents. Occupational allergies introduce a further complexity to these relationships by adding occupational exposure to both the indoor and outdoor ones in the living environment. The aim of this paper is to overview climate-related allergy affecting environmental and occupational health, as literature data are scanty in this regard, and to suggest a management model of this risk based on a multidisciplinary approach, taking the case of biological pollution, with details on exposure and prevention. The management of climate-related occupational allergy should take into account preventive health strategies, environmental, public and occupational interventions, as well as to develop, implement, evaluate, and improve guidelines and standards protecting workers health under changing climatic conditions; new tools and strategies based on local conditions will have to be developed. Experimental studies and acquisition of environmental and personal data have to be matched to derive useful information for the scope of occupational health and safety.

Hierarchical Bayesian Markov switching models with application to predicting spawning success of shovelnose sturgeon

USGS Publications Warehouse

Holan, S.H.; Davis, G.M.; Wildhaber, M.L.; DeLonay, A.J.; Papoulias, D.M.

2009-01-01

The timing of spawning in fish is tightly linked to environmental factors; however, these factors are not very well understood for many species. Specifically, little information is available to guide recruitment efforts for endangered species such as the sturgeon. Therefore, we propose a Bayesian hierarchical model for predicting the success of spawning of the shovelnose sturgeon which uses both biological and behavioural (longitudinal) data. In particular, we use data that were produced from a tracking study that was conducted in the Lower Missouri River. The data that were produced from this study consist of biological variables associated with readiness to spawn along with longitudinal behavioural data collected by using telemetry and archival data storage tags. These high frequency data are complex both biologically and in the underlying behavioural process. To accommodate such complexity we developed a hierarchical linear regression model that uses an eigenvalue predictor, derived from the transition probability matrix of a two-state Markov switching model with generalized auto-regressive conditional heteroscedastic dynamics. Finally, to minimize the computational burden that is associated with estimation of this model, a parallel computing approach is proposed. ?? Journal compilation 2009 Royal Statistical Society.

Stability of polymer encapsulated quantum dots in cell culture media

NASA Astrophysics Data System (ADS)

Ojea-Jiménez, I.; Piella, J.; Nguyen, T.-L.; Bestetti, A.; Ryan, A. D.; Puntes, V.

2013-04-01

The unique optical properties of Quantum Dots have attracted a great interest to use these nanomaterials in diverse biological applications. The synthesis of QDs by methods from the literature permits one to obtain nanocrystals coated by hydrophobic alkyl coordinating ligands and soluble in most of the cases in organic solvents. The ideal biocompatible QD must be homogeneously dispersed and colloidally stable in aqueous solvents, exhibit pH and salt stability, show low levels of nonspecific binding to biological components, maintain a high quantum yield, and have a small hydrodynamic diameter. Polymer encapsulation represents an excellent scaffold on which to build additional biological function, allowing for a wide range of grafting approaches for biological ligands. As these QD are functionalized with poly(ethylene)glycol (PEG) derivatives on their surface, they show long term stability without any significant change in the optical properties, and they are also highly stable in the most common buffer solutions such as Phosphate Buffer Saline (PBS) or borate. However, as biological studies are normally done in more complex biological media which contain a mixture of amino acids, salts, glucose and vitamins, it is essential to determine the stability of our synthesized QDs under these conditions before tackling biological studies.

Generative mechanistic explanation building in undergraduate molecular and cellular biology

NASA Astrophysics Data System (ADS)

Southard, Katelyn M.; Espindola, Melissa R.; Zaepfel, Samantha D.; Bolger, Molly S.

2017-09-01

When conducting scientific research, experts in molecular and cellular biology (MCB) use specific reasoning strategies to construct mechanistic explanations for the underlying causal features of molecular phenomena. We explored how undergraduate students applied this scientific practice in MCB. Drawing from studies of explanation building among scientists, we created and applied a theoretical framework to explore the strategies students use to construct explanations for 'novel' biological phenomena. Specifically, we explored how students navigated the multi-level nature of complex biological systems using generative mechanistic reasoning. Interviews were conducted with introductory and upper-division biology students at a large public university in the United States. Results of qualitative coding revealed key features of students' explanation building. Students used modular thinking to consider the functional subdivisions of the system, which they 'filled in' to varying degrees with mechanistic elements. They also hypothesised the involvement of mechanistic entities and instantiated abstract schema to adapt their explanations to unfamiliar biological contexts. Finally, we explored the flexible thinking that students used to hypothesise the impact of mutations on multi-leveled biological systems. Results revealed a number of ways that students drew mechanistic connections between molecules, functional modules (sets of molecules with an emergent function), cells, tissues, organisms and populations.

Systems genetics: a paradigm to improve discovery of candidate genes and mechanisms underlying complex traits.

PubMed

Feltus, F Alex

2014-06-01

Understanding the control of any trait optimally requires the detection of causal genes, gene interaction, and mechanism of action to discover and model the biochemical pathways underlying the expressed phenotype. Functional genomics techniques, including RNA expression profiling via microarray and high-throughput DNA sequencing, allow for the precise genome localization of biological information. Powerful genetic approaches, including quantitative trait locus (QTL) and genome-wide association study mapping, link phenotype with genome positions, yet genetics is less precise in localizing the relevant mechanistic information encoded in DNA. The coupling of salient functional genomic signals with genetically mapped positions is an appealing approach to discover meaningful gene-phenotype relationships. Techniques used to define this genetic-genomic convergence comprise the field of systems genetics. This short review will address an application of systems genetics where RNA profiles are associated with genetically mapped genome positions of individual genes (eQTL mapping) or as gene sets (co-expression network modules). Both approaches can be applied for knowledge independent selection of candidate genes (and possible control mechanisms) underlying complex traits where multiple, likely unlinked, genomic regions might control specific complex traits. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Multiscale entropy-based methods for heart rate variability complexity analysis

NASA Astrophysics Data System (ADS)

Silva, Luiz Eduardo Virgilio; Cabella, Brenno Caetano Troca; Neves, Ubiraci Pereira da Costa; Murta Junior, Luiz Otavio

2015-03-01

Physiologic complexity is an important concept to characterize time series from biological systems, which associated to multiscale analysis can contribute to comprehension of many complex phenomena. Although multiscale entropy has been applied to physiological time series, it measures irregularity as function of scale. In this study we purpose and evaluate a set of three complexity metrics as function of time scales. Complexity metrics are derived from nonadditive entropy supported by generation of surrogate data, i.e. SDiffqmax, qmax and qzero. In order to access accuracy of proposed complexity metrics, receiver operating characteristic (ROC) curves were built and area under the curves was computed for three physiological situations. Heart rate variability (HRV) time series in normal sinus rhythm, atrial fibrillation, and congestive heart failure data set were analyzed. Results show that proposed metric for complexity is accurate and robust when compared to classic entropic irregularity metrics. Furthermore, SDiffqmax is the most accurate for lower scales, whereas qmax and qzero are the most accurate when higher time scales are considered. Multiscale complexity analysis described here showed potential to assess complex physiological time series and deserves further investigation in wide context.

Fundamental Challenges in Mechanistic Enzymology: Progress toward Understanding the Rate Enhancements of Enzymes

PubMed Central

Herschlag, Daniel; Natarajan, Aditya

2013-01-01

Enzymes are remarkable catalysts that lie at the heart of biology, accelerating chemical reactions to an astounding extent with extraordinary specificity. Enormous progress in understanding the chemical basis of enzymatic transformations and the basic mechanisms underlying rate enhancements over the past decades is apparent. Nevertheless, it has been difficult to achieve a quantitative understanding of how the underlying mechanisms account for the energetics of catalysis, because of the complexity of enzyme systems and the absence of underlying energetic additivity. We review case studies from our own work that illustrate the power of precisely defined and clearly articulated questions when dealing with such complex and multi-faceted systems, and we also use this approach to evaluate our current ability to design enzymes. We close by highlighting a series of questions that help frame some of what remains to be understood, and we encourage the reader to define additional questions and directions that will deepen and broaden our understanding of enzymes and their catalysis. PMID:23488725

Fundamental challenges in mechanistic enzymology: progress toward understanding the rate enhancements of enzymes.

PubMed

Herschlag, Daniel; Natarajan, Aditya

2013-03-26

Enzymes are remarkable catalysts that lie at the heart of biology, accelerating chemical reactions to an astounding extent with extraordinary specificity. Enormous progress in understanding the chemical basis of enzymatic transformations and the basic mechanisms underlying rate enhancements over the past decades is apparent. Nevertheless, it has been difficult to achieve a quantitative understanding of how the underlying mechanisms account for the energetics of catalysis, because of the complexity of enzyme systems and the absence of underlying energetic additivity. We review case studies from our own work that illustrate the power of precisely defined and clearly articulated questions when dealing with such complex and multifaceted systems, and we also use this approach to evaluate our current ability to design enzymes. We close by highlighting a series of questions that help frame some of what remains to be understood, and we encourage the reader to define additional questions and directions that will deepen and broaden our understanding of enzymes and their catalysis.

Bayesian selection of Markov models for symbol sequences: application to microsaccadic eye movements.

PubMed

Bettenbühl, Mario; Rusconi, Marco; Engbert, Ralf; Holschneider, Matthias

2012-01-01

Complex biological dynamics often generate sequences of discrete events which can be described as a Markov process. The order of the underlying Markovian stochastic process is fundamental for characterizing statistical dependencies within sequences. As an example for this class of biological systems, we investigate the Markov order of sequences of microsaccadic eye movements from human observers. We calculate the integrated likelihood of a given sequence for various orders of the Markov process and use this in a Bayesian framework for statistical inference on the Markov order. Our analysis shows that data from most participants are best explained by a first-order Markov process. This is compatible with recent findings of a statistical coupling of subsequent microsaccade orientations. Our method might prove to be useful for a broad class of biological systems.

KENNEDY SPACE CENTER, FLA. - Research team members work with acoustic cable during underwater acoustic research being conducted in the Launch Complex 39 turn basin. Several government agencies, including NASA, NOAA, the Navy, the Coast Guard, and the Florida Fish and Wildlife Commission are involved in the testing. The research involves demonstrations of passive and active sensor technologies, with applications in fields ranging from marine biological research to homeland security. The work is also serving as a pilot project to assess the cooperation between the agencies involved. Equipment under development includes a passive acoustic monitor developed by NASA’s Jet Propulsion Laboratory, and mobile robotic sensors from the Navy’s Mobile Diving and Salvage Unit.

NASA Image and Video Library

2003-08-18

KENNEDY SPACE CENTER, FLA. - Research team members work with acoustic cable during underwater acoustic research being conducted in the Launch Complex 39 turn basin. Several government agencies, including NASA, NOAA, the Navy, the Coast Guard, and the Florida Fish and Wildlife Commission are involved in the testing. The research involves demonstrations of passive and active sensor technologies, with applications in fields ranging from marine biological research to homeland security. The work is also serving as a pilot project to assess the cooperation between the agencies involved. Equipment under development includes a passive acoustic monitor developed by NASA’s Jet Propulsion Laboratory, and mobile robotic sensors from the Navy’s Mobile Diving and Salvage Unit.

KENNEDY SPACE CENTER, FLA. - Researchers utilize several types of watercraft to conduct underwater acoustic research in the Launch Complex 39 turn basin. Several government agencies, including NASA, NOAA, the Navy, the Coast Guard, and the Florida Fish and Wildlife Commission are involved in the testing. The research involves demonstrations of passive and active sensor technologies, with applications in fields ranging from marine biological research to homeland security. The work is also serving as a pilot project to assess the cooperation between the agencies involved. Equipment under development includes a passive acoustic monitor developed by NASA’s Jet Propulsion Laboratory, and mobile robotic sensors from the Navy’s Mobile Diving and Salvage Unit.

NASA Image and Video Library

2003-08-18

KENNEDY SPACE CENTER, FLA. - Researchers utilize several types of watercraft to conduct underwater acoustic research in the Launch Complex 39 turn basin. Several government agencies, including NASA, NOAA, the Navy, the Coast Guard, and the Florida Fish and Wildlife Commission are involved in the testing. The research involves demonstrations of passive and active sensor technologies, with applications in fields ranging from marine biological research to homeland security. The work is also serving as a pilot project to assess the cooperation between the agencies involved. Equipment under development includes a passive acoustic monitor developed by NASA’s Jet Propulsion Laboratory, and mobile robotic sensors from the Navy’s Mobile Diving and Salvage Unit.

Topological Principles of Control in Dynamical Networks

NASA Astrophysics Data System (ADS)

Kim, Jason; Pasqualetti, Fabio; Bassett, Danielle

Networked biological systems, such as the brain, feature complex patterns of interactions. To predict and correct the dynamic behavior of such systems, it is imperative to understand how the underlying topological structure affects and limits the function of the system. Here, we use network control theory to extract topological features that favor or prevent network controllability, and to understand the network-wide effect of external stimuli on large-scale brain systems. Specifically, we treat each brain region as a dynamic entity with real-valued state, and model the time evolution of all interconnected regions using linear, time-invariant dynamics. We propose a simplified feed-forward scheme where the effect of upstream regions (drivers) on the connected downstream regions (non-drivers) is characterized in closed-form. Leveraging this characterization of the simplified model, we derive topological features that predict the controllability properties of non-simplified networks. We show analytically and numerically that these predictors are accurate across a large range of parameters. Among other contributions, our analysis shows that heterogeneity in the network weights facilitate controllability, and allows us to implement targeted interventions that profoundly improve controllability. By assuming an underlying dynamical mechanism, we are able to understand the complex topology of networked biological systems in a functionally meaningful way.

Evolutionary Connectionism: Algorithmic Principles Underlying the Evolution of Biological Organisation in Evo-Devo, Evo-Eco and Evolutionary Transitions.

PubMed

Watson, Richard A; Mills, Rob; Buckley, C L; Kouvaris, Kostas; Jackson, Adam; Powers, Simon T; Cox, Chris; Tudge, Simon; Davies, Adam; Kounios, Loizos; Power, Daniel

2016-01-01

The mechanisms of variation, selection and inheritance, on which evolution by natural selection depends, are not fixed over evolutionary time. Current evolutionary biology is increasingly focussed on understanding how the evolution of developmental organisations modifies the distribution of phenotypic variation, the evolution of ecological relationships modifies the selective environment, and the evolution of reproductive relationships modifies the heritability of the evolutionary unit. The major transitions in evolution, in particular, involve radical changes in developmental, ecological and reproductive organisations that instantiate variation, selection and inheritance at a higher level of biological organisation. However, current evolutionary theory is poorly equipped to describe how these organisations change over evolutionary time and especially how that results in adaptive complexes at successive scales of organisation (the key problem is that evolution is self-referential, i.e. the products of evolution change the parameters of the evolutionary process). Here we first reinterpret the central open questions in these domains from a perspective that emphasises the common underlying themes. We then synthesise the findings from a developing body of work that is building a new theoretical approach to these questions by converting well-understood theory and results from models of cognitive learning. Specifically, connectionist models of memory and learning demonstrate how simple incremental mechanisms, adjusting the relationships between individually-simple components, can produce organisations that exhibit complex system-level behaviours and improve the adaptive capabilities of the system. We use the term "evolutionary connectionism" to recognise that, by functionally equivalent processes, natural selection acting on the relationships within and between evolutionary entities can result in organisations that produce complex system-level behaviours in evolutionary systems and modify the adaptive capabilities of natural selection over time. We review the evidence supporting the functional equivalences between the domains of learning and of evolution, and discuss the potential for this to resolve conceptual problems in our understanding of the evolution of developmental, ecological and reproductive organisations and, in particular, the major evolutionary transitions.

Proteins Encoded in Genomic Regions Associated with Immune-Mediated Disease Physically Interact and Suggest Underlying Biology

PubMed Central

Rossin, Elizabeth J.; Lage, Kasper; Raychaudhuri, Soumya; Xavier, Ramnik J.; Tatar, Diana; Benita, Yair

2011-01-01

Genome-wide association studies (GWAS) have defined over 150 genomic regions unequivocally containing variation predisposing to immune-mediated disease. Inferring disease biology from these observations, however, hinges on our ability to discover the molecular processes being perturbed by these risk variants. It has previously been observed that different genes harboring causal mutations for the same Mendelian disease often physically interact. We sought to evaluate the degree to which this is true of genes within strongly associated loci in complex disease. Using sets of loci defined in rheumatoid arthritis (RA) and Crohn's disease (CD) GWAS, we build protein–protein interaction (PPI) networks for genes within associated loci and find abundant physical interactions between protein products of associated genes. We apply multiple permutation approaches to show that these networks are more densely connected than chance expectation. To confirm biological relevance, we show that the components of the networks tend to be expressed in similar tissues relevant to the phenotypes in question, suggesting the network indicates common underlying processes perturbed by risk loci. Furthermore, we show that the RA and CD networks have predictive power by demonstrating that proteins in these networks, not encoded in the confirmed list of disease associated loci, are significantly enriched for association to the phenotypes in question in extended GWAS analysis. Finally, we test our method in 3 non-immune traits to assess its applicability to complex traits in general. We find that genes in loci associated to height and lipid levels assemble into significantly connected networks but did not detect excess connectivity among Type 2 Diabetes (T2D) loci beyond chance. Taken together, our results constitute evidence that, for many of the complex diseases studied here, common genetic associations implicate regions encoding proteins that physically interact in a preferential manner, in line with observations in Mendelian disease. PMID:21249183

Colobopsis explodens sp. n., model species for studies on “exploding ants” (Hymenoptera, Formicidae), with biological notes and first illustrations of males of the Colobopsis cylindrica group

PubMed Central

Laciny, Alice; Zettel, Herbert; Kopchinskiy, Alexey; Pretzer, Carina; Pal, Anna; Salim, Kamariah Abu; Rahimi, Mohammad Javad; Hoenigsberger, Michaela; Lim, Linda; Jaitrong, Weeyawat; Druzhinina, Irina S.

2018-01-01

Abstract A taxonomic description of all castes of Colobopsis explodens Laciny & Zettel, sp. n. from Borneo, Thailand, and Malaysia is provided, which serves as a model species for biological studies on “exploding ants” in Southeast Asia. The new species is a member of the Colobopsis cylindrica (COCY) group and falls into a species complex that has been repeatedly summarized under the name Colobopsis saundersi (Emery, 1889) (formerly Camponotus saundersi). The COCY species group is known under its vernacular name “exploding ants” for a unique behaviour: during territorial combat, workers of some species sacrifice themselves by rupturing their gaster and releasing sticky and irritant contents of their hypertrophied mandibular gland reservoirs to kill or repel rivals. This study includes first illustrations and morphometric characterizations of males of the COCY group: Colobopsis explodens Laciny & Zettel, sp. n. and Colobopsis badia (Smith, 1857). Characters of male genitalia and external morphology are compared with other selected taxa of Camponotini. Preliminary notes on the biology of C. explodens Laciny & Zettel, sp. n. are provided. To fix the species identity of the closely related C. badia, a lectotype from Singapore is designated. The following taxonomic changes within the C. saundersi complex are proposed: Colobopsis solenobia (Menozzi, 1926), syn. n. and Colobopsis trieterica (Menozzi, 1926), syn. n. are synonymized with Colobopsis corallina Roger, 1863, a common endemic species of the Philippines. Colobopsis saginata Stitz, 1925, stat. n., hitherto a subspecies of C. badia, is raised to species level. PMID:29706783

Colobopsis explodens sp. n., model species for studies on "exploding ants" (Hymenoptera, Formicidae), with biological notes and first illustrations of males of the Colobopsis cylindrica group.

PubMed

Laciny, Alice; Zettel, Herbert; Kopchinskiy, Alexey; Pretzer, Carina; Pal, Anna; Salim, Kamariah Abu; Rahimi, Mohammad Javad; Hoenigsberger, Michaela; Lim, Linda; Jaitrong, Weeyawat; Druzhinina, Irina S

2018-01-01

A taxonomic description of all castes of Colobopsis explodens Laciny & Zettel, sp. n. from Borneo, Thailand, and Malaysia is provided, which serves as a model species for biological studies on "exploding ants" in Southeast Asia. The new species is a member of the Colobopsis cylindrica (COCY) group and falls into a species complex that has been repeatedly summarized under the name Colobopsis saundersi (Emery, 1889) (formerly Camponotus saundersi ). The COCY species group is known under its vernacular name "exploding ants" for a unique behaviour: during territorial combat, workers of some species sacrifice themselves by rupturing their gaster and releasing sticky and irritant contents of their hypertrophied mandibular gland reservoirs to kill or repel rivals. This study includes first illustrations and morphometric characterizations of males of the COCY group: Colobopsis explodens Laciny & Zettel, sp. n. and Colobopsis badia (Smith, 1857). Characters of male genitalia and external morphology are compared with other selected taxa of Camponotini. Preliminary notes on the biology of C. explodens Laciny & Zettel, sp. n. are provided. To fix the species identity of the closely related C. badia , a lectotype from Singapore is designated. The following taxonomic changes within the C. saundersi complex are proposed: Colobopsis solenobia (Menozzi, 1926), syn. n. and Colobopsis trieterica (Menozzi, 1926), syn. n. are synonymized with Colobopsis corallina Roger, 1863, a common endemic species of the Philippines. Colobopsis saginata Stitz, 1925, stat. n ., hitherto a subspecies of C. badia , is raised to species level.

Tephritid Integrative Taxonomy: Where We Are Now, with a Focus on the Resolution of Three Tropical Fruit Fly Species Complexes.

PubMed

Schutze, Mark K; Virgilio, Massimiliano; Norrbom, Allen; Clarke, Anthony R

2017-01-31

Accurate species delimitation underpins good taxonomy. Formalization of integrative taxonomy in the past decade has provided a framework for using multidisciplinary data to make species delimitation hypotheses more rigorous. We address the current state of integrative taxonomy by using as a case study an international project targeted at resolving three important tephritid species complexes: Bactrocera dorsalis complex, Anastrepha fraterculus complex, and Ceratitis FAR (C. fasciventris, C. anonae, C. rosa) complex. The integrative taxonomic approach has helped deliver significant advances in resolving these complexes: It has been used to identify some taxa as belonging to the same biological species as well as to confirm hidden cryptic diversity under a single taxonomic name. Nevertheless, the general application of integrative taxonomy has not been without issue, revealing challenges that must be considered when undertaking an integrative taxonomy project. Scrutiny of this international case study provides a unique opportunity to document lessons learned for the benefit of not only tephritid taxonomists, but also the wider taxonomic community.

Age-Related Macular Degeneration: Genetics and Biology Coming Together

PubMed Central

Fritsche, Lars G.; Fariss, Robert N.; Stambolian, Dwight; Abecasis, Gonçalo R.; Curcio, Christine A.

2014-01-01

Genetic and genomic studies have enhanced our understanding of complex neurodegenerative diseases that exert a devastating impact on individuals and society. One such disease, age-related macular degeneration (AMD), is a major cause of progressive and debilitating visual impairment. Since the pioneering discovery in 2005 of complement factor H (CFH) as a major AMD susceptibility gene, extensive investigations have confirmed 19 additional genetic risk loci, and more are anticipated. In addition to common variants identified by now-conventional genome-wide association studies, targeted genomic sequencing and exome-chip analyses are uncovering rare variant alleles of high impact. Here, we provide a critical review of the ongoing genetic studies and of common and rare risk variants at a total of 20 susceptibility loci, which together explain 40–60% of the disease heritability but provide limited power for diagnostic testing of disease risk. Identification of these susceptibility loci has begun to untangle the complex biological pathways underlying AMD pathophysiology, pointing to new testable paradigms for treatment. PMID:24773320

Platform construction and extraction mechanism study of magnetic mixed hemimicelles solid-phase extraction

NASA Astrophysics Data System (ADS)

Xiao, Deli; Zhang, Chan; He, Jia; Zeng, Rong; Chen, Rong; He, Hua

2016-12-01

Simple, accurate and high-throughput pretreatment method would facilitate large-scale studies of trace analysis in complex samples. Magnetic mixed hemimicelles solid-phase extraction has the power to become a key pretreatment method in biological, environmental and clinical research. However, lacking of experimental predictability and unsharpness of extraction mechanism limit the development of this promising method. Herein, this work tries to establish theoretical-based experimental designs for extraction of trace analytes from complex samples using magnetic mixed hemimicelles solid-phase extraction. We selected three categories and six sub-types of compounds for systematic comparative study of extraction mechanism, and comprehensively illustrated the roles of different force (hydrophobic interaction, π-π stacking interactions, hydrogen-bonding interaction, electrostatic interaction) for the first time. What’s more, the application guidelines for supporting materials, surfactants and sample matrix were also summarized. The extraction mechanism and platform established in the study render its future promising for foreseeable and efficient pretreatment under theoretical based experimental design for trace analytes from environmental, biological and clinical samples.

Fighting Cancer with Mathematics and Viruses.

PubMed

Santiago, Daniel N; Heidbuechel, Johannes P W; Kandell, Wendy M; Walker, Rachel; Djeu, Julie; Engeland, Christine E; Abate-Daga, Daniel; Enderling, Heiko

2017-08-23

After decades of research, oncolytic virotherapy has recently advanced to clinical application, and currently a multitude of novel agents and combination treatments are being evaluated for cancer therapy. Oncolytic agents preferentially replicate in tumor cells, inducing tumor cell lysis and complex antitumor effects, such as innate and adaptive immune responses and the destruction of tumor vasculature. With the availability of different vector platforms and the potential of both genetic engineering and combination regimens to enhance particular aspects of safety and efficacy, the identification of optimal treatments for patient subpopulations or even individual patients becomes a top priority. Mathematical modeling can provide support in this arena by making use of experimental and clinical data to generate hypotheses about the mechanisms underlying complex biology and, ultimately, predict optimal treatment protocols. Increasingly complex models can be applied to account for therapeutically relevant parameters such as components of the immune system. In this review, we describe current developments in oncolytic virotherapy and mathematical modeling to discuss the benefit of integrating different modeling approaches into biological and clinical experimentation. Conclusively, we propose a mutual combination of these research fields to increase the value of the preclinical development and the therapeutic efficacy of the resulting treatments.

Journey into Bone Models: A Review

PubMed Central

Scheinpflug, Julia; Pfeiffenberger, Moritz; Damerau, Alexandra; Schwarz, Franziska; Textor, Martin; Lang, Annemarie

2018-01-01

Bone is a complex tissue with a variety of functions, such as providing mechanical stability for locomotion, protection of the inner organs, mineral homeostasis and haematopoiesis. To fulfil these diverse roles in the human body, bone consists of a multitude of different cells and an extracellular matrix that is mechanically stable, yet flexible at the same time. Unlike most tissues, bone is under constant renewal facilitated by a coordinated interaction of bone-forming and bone-resorbing cells. It is thus challenging to recreate bone in its complexity in vitro and most current models rather focus on certain aspects of bone biology that are of relevance for the research question addressed. In addition, animal models are still regarded as the gold-standard in the context of bone biology and pathology, especially for the development of novel treatment strategies. However, species-specific differences impede the translation of findings from animal models to humans. The current review summarizes and discusses the latest developments in bone tissue engineering and organoid culture including suitable cell sources, extracellular matrices and microfluidic bioreactor systems. With available technology in mind, a best possible bone model will be hypothesized. Furthermore, the future need and application of such a complex model will be discussed. PMID:29748516

Fighting Cancer with Mathematics and Viruses

PubMed Central

Santiago, Daniel N.; Heidbuechel, Johannes P. W.; Kandell, Wendy M.; Walker, Rachel; Djeu, Julie; Abate-Daga, Daniel; Enderling, Heiko

2017-01-01

After decades of research, oncolytic virotherapy has recently advanced to clinical application, and currently a multitude of novel agents and combination treatments are being evaluated for cancer therapy. Oncolytic agents preferentially replicate in tumor cells, inducing tumor cell lysis and complex antitumor effects, such as innate and adaptive immune responses and the destruction of tumor vasculature. With the availability of different vector platforms and the potential of both genetic engineering and combination regimens to enhance particular aspects of safety and efficacy, the identification of optimal treatments for patient subpopulations or even individual patients becomes a top priority. Mathematical modeling can provide support in this arena by making use of experimental and clinical data to generate hypotheses about the mechanisms underlying complex biology and, ultimately, predict optimal treatment protocols. Increasingly complex models can be applied to account for therapeutically relevant parameters such as components of the immune system. In this review, we describe current developments in oncolytic virotherapy and mathematical modeling to discuss the benefit of integrating different modeling approaches into biological and clinical experimentation. Conclusively, we propose a mutual combination of these research fields to increase the value of the preclinical development and the therapeutic efficacy of the resulting treatments. PMID:28832539

Journey into Bone Models: A Review.

PubMed

Scheinpflug, Julia; Pfeiffenberger, Moritz; Damerau, Alexandra; Schwarz, Franziska; Textor, Martin; Lang, Annemarie; Schulze, Frank

2018-05-10

Bone is a complex tissue with a variety of functions, such as providing mechanical stability for locomotion, protection of the inner organs, mineral homeostasis and haematopoiesis. To fulfil these diverse roles in the human body, bone consists of a multitude of different cells and an extracellular matrix that is mechanically stable, yet flexible at the same time. Unlike most tissues, bone is under constant renewal facilitated by a coordinated interaction of bone-forming and bone-resorbing cells. It is thus challenging to recreate bone in its complexity in vitro and most current models rather focus on certain aspects of bone biology that are of relevance for the research question addressed. In addition, animal models are still regarded as the gold-standard in the context of bone biology and pathology, especially for the development of novel treatment strategies. However, species-specific differences impede the translation of findings from animal models to humans. The current review summarizes and discusses the latest developments in bone tissue engineering and organoid culture including suitable cell sources, extracellular matrices and microfluidic bioreactor systems. With available technology in mind, a best possible bone model will be hypothesized. Furthermore, the future need and application of such a complex model will be discussed.

A Multilevel Gamma-Clustering Layout Algorithm for Visualization of Biological Networks

PubMed Central

Hruz, Tomas; Lucas, Christoph; Laule, Oliver; Zimmermann, Philip

2013-01-01

Visualization of large complex networks has become an indispensable part of systems biology, where organisms need to be considered as one complex system. The visualization of the corresponding network is challenging due to the size and density of edges. In many cases, the use of standard visualization algorithms can lead to high running times and poorly readable visualizations due to many edge crossings. We suggest an approach that analyzes the structure of the graph first and then generates a new graph which contains specific semantic symbols for regular substructures like dense clusters. We propose a multilevel gamma-clustering layout visualization algorithm (MLGA) which proceeds in three subsequent steps: (i) a multilevel γ-clustering is used to identify the structure of the underlying network, (ii) the network is transformed to a tree, and (iii) finally, the resulting tree which shows the network structure is drawn using a variation of a force-directed algorithm. The algorithm has a potential to visualize very large networks because it uses modern clustering heuristics which are optimized for large graphs. Moreover, most of the edges are removed from the visual representation which allows keeping the overview over complex graphs with dense subgraphs. PMID:23864855

Interdisciplinary and physics challenges of network theory

NASA Astrophysics Data System (ADS)

Bianconi, Ginestra

2015-09-01

Network theory has unveiled the underlying structure of complex systems such as the Internet or the biological networks in the cell. It has identified universal properties of complex networks, and the interplay between their structure and dynamics. After almost twenty years of the field, new challenges lie ahead. These challenges concern the multilayer structure of most of the networks, the formulation of a network geometry and topology, and the development of a quantum theory of networks. Making progress on these aspects of network theory can open new venues to address interdisciplinary and physics challenges including progress on brain dynamics, new insights into quantum technologies, and quantum gravity.

Recent advances in the chemistry of Rh carbenoids: multicomponent reactions of diazocarbonyl compounds

NASA Astrophysics Data System (ADS)

Medvedev, J. J.; Nikolaev, V. A.

2015-07-01

Multicomponent reactions of diazo compounds catalyzed by RhII complexes become a powerful tool for organic synthesis. They enable three- or four-step processes to be carried out as one-pot procedures (actually as one step) with high stereoselectivity to give complex organic molecules, including biologically active compounds. This review addresses recent results in the chemistry of Rh-catalyzed multicomponent reactions of diazocarbonyl compounds with the intermediate formation of N-, O- and C=O-ylides. The diastereo- and enantioselectivity of these reactions and the possibility of using various co-catalysts to increase the efficiency of the processes under consideration are discussed. The bibliography includes 120 references.

[New materia medica project: synthetic biology based bioactive metabolites research in medicinal plant].

PubMed

Wang, Yong

2017-03-25

In the last decade, synthetic biology research has been gradually transited from monocellular parts or devices toward more complex multicellular systems. The emerging plant synthetic biology is regarded as the "next chapter" of synthetic biology. The complex and diverse plant metabolism as the entry point, plant synthetic biology research not only helps us understand how real life is working, but also facilitates us to learn how to design and construct more complex artificial life. Bioactive compounds innovation and large-scale production are expected to be breakthrough with the redesigned plant metabolism as well. In this review, we discuss the research progress in plant synthetic biology and propose the new materia medica project to lift the level of traditional Chinese herbal medicine research.

Biology and genetic engineering of fruit maturation for enhanced quality and shelf-life.

PubMed

Matas, Antonio J; Gapper, Nigel E; Chung, Mi-Young; Giovannoni, James J; Rose, Jocelyn K C

2009-04-01

Commercial regulation of ripening is currently achieved through early harvest, by controlling the postharvest storage atmosphere and genetic selection for slow or late ripening varieties. Although these approaches are often effective, they are not universally applicable and often result in acceptable, but poor quality, products. With increased understanding of the molecular biology underlying ripening and the advent of genetic engineering technologies, researchers have pursued new strategies to address problems in fruit shelf-life and quality. These have been guided by recent insights into mechanisms by which ethylene and a complex network of transcription factors regulate ripening, and by an increased appreciation of factors that contribute to shelf-life, such as the fruit cuticle.

Parallel Molecular Distributed Detection With Brownian Motion.

PubMed

Rogers, Uri; Koh, Min-Sung

2016-12-01

This paper explores the in vivo distributed detection of an undesired biological agent's (BAs) biomarkers by a group of biological sized nanomachines in an aqueous medium under drift. The term distributed, indicates that the system information relative to the BAs presence is dispersed across the collection of nanomachines, where each nanomachine possesses limited communication, computation, and movement capabilities. Using Brownian motion with drift, a probabilistic detection and optimal data fusion framework, coined molecular distributed detection, will be introduced that combines theory from both molecular communication and distributed detection. Using the optimal data fusion framework as a guide, simulation indicates that a sub-optimal fusion method exists, allowing for a significant reduction in implementation complexity while retaining BA detection accuracy.

Concepts in Cancer Modeling: A Brief History

PubMed Central

Thomas, Renee M.; Van Dyke, Terry; Merlino, Glenn; Day, Chi-Ping

2016-01-01

Modeling, an experimental approach to investigate complex biological systems, has significantly contributed to our understanding of cancer. While extensive cancer research has been conducted utilizing animal models for elucidating mechanisms and developing therapeutics, the concepts in a good model design and its application have not been well elaborated. In this review, we discuss the theory underlying biological modeling and the process of producing a valuable and relevant animal model. Several renowned examples in the history of cancer research will be used to illustrate how modeling can be translatable to clinical applications. Finally, we will also discuss how the advances in cancer genomics and cancer modeling will influence each other going forward. PMID:27694601

Integrative Chemical-Biological Read-Across Approach for Chemical Hazard Classification

PubMed Central

Low, Yen; Sedykh, Alexander; Fourches, Denis; Golbraikh, Alexander; Whelan, Maurice; Rusyn, Ivan; Tropsha, Alexander

2013-01-01

Traditional read-across approaches typically rely on the chemical similarity principle to predict chemical toxicity; however, the accuracy of such predictions is often inadequate due to the underlying complex mechanisms of toxicity. Here we report on the development of a hazard classification and visualization method that draws upon both chemical structural similarity and comparisons of biological responses to chemicals measured in multiple short-term assays (”biological” similarity). The Chemical-Biological Read-Across (CBRA) approach infers each compound's toxicity from those of both chemical and biological analogs whose similarities are determined by the Tanimoto coefficient. Classification accuracy of CBRA was compared to that of classical RA and other methods using chemical descriptors alone, or in combination with biological data. Different types of adverse effects (hepatotoxicity, hepatocarcinogenicity, mutagenicity, and acute lethality) were classified using several biological data types (gene expression profiling and cytotoxicity screening). CBRA-based hazard classification exhibited consistently high external classification accuracy and applicability to diverse chemicals. Transparency of the CBRA approach is aided by the use of radial plots that show the relative contribution of analogous chemical and biological neighbors. Identification of both chemical and biological features that give rise to the high accuracy of CBRA-based toxicity prediction facilitates mechanistic interpretation of the models. PMID:23848138

Mathematics for understanding disease.

PubMed

Bies, R R; Gastonguay, M R; Schwartz, S L

2008-06-01

The application of mathematical models to reflect the organization and activity of biological systems can be viewed as a continuum of purpose. The far left of the continuum is solely the prediction of biological parameter values, wherein an understanding of the underlying biological processes is irrelevant to the purpose. At the far right of the continuum are mathematical models, the purposes of which are a precise understanding of those biological processes. No models in present use fall at either end of the continuum. Without question, however, the emphasis in regards to purpose has been on prediction, e.g., clinical trial simulation and empirical disease progression modeling. Clearly the model that ultimately incorporates a universal understanding of biological organization will also precisely predict biological events, giving the continuum the logical form of a tautology. Currently that goal lies at an immeasurable distance. Nonetheless, the motive here is to urge movement in the direction of that goal. The distance traveled toward understanding naturally depends upon the nature of the scientific question posed with respect to comprehending and/or predicting a particular disease process. A move toward mathematical models implies a move away from static empirical modeling and toward models that focus on systems biology, wherein modeling entails the systematic study of the complex pattern of organization inherent in biological systems.

Bioelectrical Impedance and The Frequency Dependent Current Conduction Through Biological Tissues: A Short Review

NASA Astrophysics Data System (ADS)

Kanti Bera, Tushar

2018-03-01

Biological tissues are developed with biological cells which exhibit complex electrical impedance called electrical bioimpedance. Under an alternating electrical excitation the bioimpedance varies with the tissue anatomy, composition and the signal frequency. The current penetration and conduction paths vary with frequency of the applied signal. Bioimpedance spectroscopy is used to study the frequency response of the electrical impedance of biological materials noninvasively. In bioimpedance spectroscopy, a low amplitude electrical signal is injected to the tissue sample or body parts to characterization the sample in terms of its bioimpedance. The electrical current conduction phenomena, which is highly influenced by the tissue impedance and the signal frequency, is an important phenomena which should be studied to understand the bioimpedance techniques like bioelectrical impedance analysis (BIA), EIS, or else. In this paper the origin of bioelectrical impedance and current conduction phenomena has been reviewed to present a brief summary of bioelectrical impedance and the frequency dependent current conduction through biological tissues. Simulation studies are conducted with alternation current injection through a two dimensional model of biological tissues containing finite number of biological cells suspended in extracellular fluid. The paper demonstrates the simulation of alternating current conduction through biological tissues conducted by COMSOL Multiphysics. Simulation studies also show the frequency response of the tissue impedance for different tissue compositions.

CamOptimus: a tool for exploiting complex adaptive evolution to optimize experiments and processes in biotechnology

PubMed Central

Cankorur-Cetinkaya, Ayca; Dias, Joao M. L.; Kludas, Jana; Slater, Nigel K. H.; Rousu, Juho; Dikicioglu, Duygu

2017-01-01

Multiple interacting factors affect the performance of engineered biological systems in synthetic biology projects. The complexity of these biological systems means that experimental design should often be treated as a multiparametric optimization problem. However, the available methodologies are either impractical, due to a combinatorial explosion in the number of experiments to be performed, or are inaccessible to most experimentalists due to the lack of publicly available, user-friendly software. Although evolutionary algorithms may be employed as alternative approaches to optimize experimental design, the lack of simple-to-use software again restricts their use to specialist practitioners. In addition, the lack of subsidiary approaches to further investigate critical factors and their interactions prevents the full analysis and exploitation of the biotechnological system. We have addressed these problems and, here, provide a simple‐to‐use and freely available graphical user interface to empower a broad range of experimental biologists to employ complex evolutionary algorithms to optimize their experimental designs. Our approach exploits a Genetic Algorithm to discover the subspace containing the optimal combination of parameters, and Symbolic Regression to construct a model to evaluate the sensitivity of the experiment to each parameter under investigation. We demonstrate the utility of this method using an example in which the culture conditions for the microbial production of a bioactive human protein are optimized. CamOptimus is available through: (https://doi.org/10.17863/CAM.10257). PMID:28635591

Behavioural system identification of visual flight speed control in Drosophila melanogaster

PubMed Central

Rohrseitz, Nicola; Fry, Steven N.

2011-01-01

Behavioural control in many animals involves complex mechanisms with intricate sensory-motor feedback loops. Modelling allows functional aspects to be captured without relying on a description of the underlying complex, and often unknown, mechanisms. A wide range of engineering techniques are available for modelling, but their ability to describe time-continuous processes is rarely exploited to describe sensory-motor control mechanisms in biological systems. We performed a system identification of visual flight speed control in the fruitfly Drosophila, based on an extensive dataset of open-loop responses previously measured under free flight conditions. We identified a second-order under-damped control model with just six free parameters that well describes both the transient and steady-state characteristics of the open-loop data. We then used the identified control model to predict flight speed responses after a visual perturbation under closed-loop conditions and validated the model with behavioural measurements performed in free-flying flies under the same closed-loop conditions. Our system identification of the fruitfly's flight speed response uncovers the high-level control strategy of a fundamental flight control reflex without depending on assumptions about the underlying physiological mechanisms. The results are relevant for future investigations of the underlying neuromotor processing mechanisms, as well as for the design of biomimetic robots, such as micro-air vehicles. PMID:20525744

Behavioural system identification of visual flight speed control in Drosophila melanogaster.

PubMed

Rohrseitz, Nicola; Fry, Steven N

2011-02-06

Behavioural control in many animals involves complex mechanisms with intricate sensory-motor feedback loops. Modelling allows functional aspects to be captured without relying on a description of the underlying complex, and often unknown, mechanisms. A wide range of engineering techniques are available for modelling, but their ability to describe time-continuous processes is rarely exploited to describe sensory-motor control mechanisms in biological systems. We performed a system identification of visual flight speed control in the fruitfly Drosophila, based on an extensive dataset of open-loop responses previously measured under free flight conditions. We identified a second-order under-damped control model with just six free parameters that well describes both the transient and steady-state characteristics of the open-loop data. We then used the identified control model to predict flight speed responses after a visual perturbation under closed-loop conditions and validated the model with behavioural measurements performed in free-flying flies under the same closed-loop conditions. Our system identification of the fruitfly's flight speed response uncovers the high-level control strategy of a fundamental flight control reflex without depending on assumptions about the underlying physiological mechanisms. The results are relevant for future investigations of the underlying neuromotor processing mechanisms, as well as for the design of biomimetic robots, such as micro-air vehicles.

Reactivity pathways for nitric oxide and nitrosonium with iron complexes in biologically relevant sulfur coordination spheres.

PubMed

Harrop, Todd C; Song, Datong; Lippard, Stephen J

2007-11-01

The interaction of nitric oxide (NO) with iron-sulfur cluster proteins results in the formation of dinitrosyl iron complexes (DNICs) coordinated by cysteine residues from the peptide backbone or with low molecular weight sulfur-containing molecules like glutathione. Such DNICs are among the modes available in biology to store, transport, and deliver NO to its relevant targets. In order to elucidate the fundamental chemistry underlying the formation of DNICs and to characterize possible intermediates in the process, we have investigated the interaction of NO (g) and NO(+) with iron-sulfur complexes having the formula [Fe(SR)(4)](2-), where R=(t)Bu, Ph, or benzyl, chosen to mimic sulfur-rich iron sites in biology. The reaction of NO (g) with [Fe(S(t)Bu)(4)](2-) or [Fe(SBz)(4)](2-) cleanly affords the mononitrosyl complexes (MNICs), [Fe(S(t)Bu)(3)(NO)](-) (1) and [Fe(SBz)(3)(NO)](-) (3), respectively, by ligand displacement. Mononitrosyl species of this kind were previously unknown. These complexes further react with NO (g) to generate the corresponding DNICs, [Fe(SPh)(2)(NO)(2)](-) (4) and [Fe(SBz)(2)(NO)(2)](-) (5), with concomitant reductive elimination of the coordinated thiolate donors. Reaction of [Fe(SR)(4)](2-) complexes with NO(+) proceeds by a different pathway to yield the corresponding dinitrosyl S-bridged Roussin red ester complexes, [Fe(2)(mu-S(t)Bu)(2)(NO)(4)] (2), [Fe(2)(mu-SPh)(2)(NO)(4)] (7) and [Fe(2)(mu-SBz)(2)(NO)(4)] (8). The NO/NO(+) reactivity of an Fe(II) complex with a mixed nitrogen/sulfur coordination sphere was also investigated. The DNIC and red ester species, [Fe(S-o-NH(2)C(6)H(4))(2)(NO)(2)](-) (6) and [Fe(2)(mu-S-o-NH(2)C(6)H(4))(2)(NO)(4)] (9), were generated. The structures of 8 and 9 were verified by X-ray crystallography. The MNIC complex 1 can efficiently deliver NO to iron-porphyrin complexes like [Fe(TPP)Cl], a reaction that is aided by light. Removal of the coordinated NO ligand of 1 by photolysis and addition of elemental sulfur generates higher nuclearity Fe/S clusters.

Web-based applications for building, managing and analysing kinetic models of biological systems.

PubMed

Lee, Dong-Yup; Saha, Rajib; Yusufi, Faraaz Noor Khan; Park, Wonjun; Karimi, Iftekhar A

2009-01-01

Mathematical modelling and computational analysis play an essential role in improving our capability to elucidate the functions and characteristics of complex biological systems such as metabolic, regulatory and cell signalling pathways. The modelling and concomitant simulation render it possible to predict the cellular behaviour of systems under various genetically and/or environmentally perturbed conditions. This motivates systems biologists/bioengineers/bioinformaticians to develop new tools and applications, allowing non-experts to easily conduct such modelling and analysis. However, among a multitude of systems biology tools developed to date, only a handful of projects have adopted a web-based approach to kinetic modelling. In this report, we evaluate the capabilities and characteristics of current web-based tools in systems biology and identify desirable features, limitations and bottlenecks for further improvements in terms of usability and functionality. A short discussion on software architecture issues involved in web-based applications and the approaches taken by existing tools is included for those interested in developing their own simulation applications.

Characterizing Strain Variation in Engineered E. coli Using a Multi-Omics-Based Workflow

DOE PAGES

Brunk, Elizabeth; George, Kevin W.; Alonso-Gutierrez, Jorge; ...

2016-05-19

Understanding the complex interactions that occur between heterologous and native biochemical pathways represents a major challenge in metabolic engineering and synthetic biology. We present a workflow that integrates metabolomics, proteomics, and genome-scale models of Escherichia coli metabolism to study the effects of introducing a heterologous pathway into a microbial host. This workflow incorporates complementary approaches from computational systems biology, metabolic engineering, and synthetic biology; provides molecular insight into how the host organism microenvironment changes due to pathway engineering; and demonstrates how biological mechanisms underlying strain variation can be exploited as an engineering strategy to increase product yield. As a proofmore » of concept, we present the analysis of eight engineered strains producing three biofuels: isopentenol, limonene, and bisabolene. Application of this workflow identified the roles of candidate genes, pathways, and biochemical reactions in observed experimental phenomena and facilitated the construction of a mutant strain with improved productivity. The contributed workflow is available as an open-source tool in the form of iPython notebooks.« less

Precision phenotyping, panomics, and system-level bioinformatics to delineate complex biologies of atherosclerosis: rationale and design of the "Genetic Loci and the Burden of Atherosclerotic Lesions" study.

PubMed

Voros, Szilard; Maurovich-Horvat, Pal; Marvasty, Idean B; Bansal, Aruna T; Barnes, Michael R; Vazquez, Gustavo; Murray, Sarah S; Voros, Viktor; Merkely, Bela; Brown, Bradley O; Warnick, G Russell

2014-01-01

Complex biological networks of atherosclerosis are largely unknown. The main objective of the Genetic Loci and the Burden of Atherosclerotic Lesions study is to assemble comprehensive biological networks of atherosclerosis using advanced cardiovascular imaging for phenotyping, a panomic approach to identify underlying genomic, proteomic, metabolomic, and lipidomic underpinnings, analyzed by systems biology-driven bioinformatics. By design, this is a hypothesis-free unbiased discovery study collecting a large number of biologically related factors to examine biological associations between genomic, proteomic, metabolomic, lipidomic, and phenotypic factors of atherosclerosis. The Genetic Loci and the Burden of Atherosclerotic Lesions study (NCT01738828) is a prospective, multicenter, international observational study of atherosclerotic coronary artery disease. Approximately 7500 patients are enrolled and undergo non-contrast-enhanced coronary calcium scanning by CT for the detection and quantification of coronary artery calcium, as well as coronary artery CT angiography for the detection and quantification of plaque, stenosis, and overall coronary artery disease burden. In addition, patients undergo whole genome sequencing, DNA methylation, whole blood-based transcriptome sequencing, unbiased proteomics based on mass spectrometry, as well as metabolomics and lipidomics on a mass spectrometry platform. The study is analyzed in 3 subsequent phases, and each phase consists of a discovery cohort and an independent validation cohort. For the primary analysis, the primary phenotype will be the presence of any atherosclerotic plaque, as detected by cardiac CT. Additional phenotypic analyses will include per patient maximal luminal stenosis defined as 50% and 70% diameter stenosis. Single-omic and multi-omic associations will be examined for each phenotype; putative biomarkers will be assessed for association, calibration, discrimination, and reclassification. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.

Mosaic, Self-Similarity Logic, and Biological Attraction principles

PubMed Central

Baluška, František; Barlow, Peter W; Guidolin, Diego

2009-01-01

From a structural standpoint, living organisms are organized like a nest of Russian matryoshka dolls, in which structures are buried within one another. From a temporal point of view, this type of organization is the result of a history comprised of a set of time backcloths which have accompanied the passage of living matter from its origins up to the present day. The aim of the present paper is to indicate a possible course of this ‘passage through time, and suggest how today’s complexity has been reached by living organisms. This investigation will employ three conceptual tools, namely the Mosaic, Self-Similarity Logic, and the Biological Attraction principles. Self-Similarity Logic indicates the self-consistency by which elements of a living system interact, irrespective of the spatiotemporal level under consideration. The term Mosaic indicates how, from the same set of elements assembled according to different patterns, it is possible to arrive at completely different constructions: hence, each system becomes endowed with different emergent properties. The Biological Attraction principle states that there is an inherent drive for association and merging of compatible elements at all levels of biological complexity. By analogy with the gravitation law in physics, biological attraction is based on the evidence that each living organism creates an attractive field around itself. This field acts as a sphere of influence that actively attracts similar fields of other biological systems, thereby modifying salient features of the interacting organisms. Three specific organizational levels of living matter, namely the molecular, cellular, and supracellular levels, have been considered in order to analyse and illustrate the interpretative as well as the predictive roles of each of these three explanatory principles. PMID:20195461

MORE: mixed optimization for reverse engineering--an application to modeling biological networks response via sparse systems of nonlinear differential equations.

PubMed

Sambo, Francesco; de Oca, Marco A Montes; Di Camillo, Barbara; Toffolo, Gianna; Stützle, Thomas

2012-01-01

Reverse engineering is the problem of inferring the structure of a network of interactions between biological variables from a set of observations. In this paper, we propose an optimization algorithm, called MORE, for the reverse engineering of biological networks from time series data. The model inferred by MORE is a sparse system of nonlinear differential equations, complex enough to realistically describe the dynamics of a biological system. MORE tackles separately the discrete component of the problem, the determination of the biological network topology, and the continuous component of the problem, the strength of the interactions. This approach allows us both to enforce system sparsity, by globally constraining the number of edges, and to integrate a priori information about the structure of the underlying interaction network. Experimental results on simulated and real-world networks show that the mixed discrete/continuous optimization approach of MORE significantly outperforms standard continuous optimization and that MORE is competitive with the state of the art in terms of accuracy of the inferred networks.

Mirror me: Imitative responses in adults with autism.

PubMed

Schunke, Odette; Schöttle, Daniel; Vettorazzi, Eik; Brandt, Valerie; Kahl, Ursula; Bäumer, Tobias; Ganos, Christos; David, Nicole; Peiker, Ina; Engel, Andreas K; Brass, Marcel; Münchau, Alexander

2016-02-01

Dysfunctions of the human mirror neuron system have been postulated to underlie some deficits in autism spectrum disorders including poor imitative performance and impaired social skills. Using three reaction time experiments addressing mirror neuron system functions under simple and complex conditions, we examined 20 adult autism spectrum disorder participants and 20 healthy controls matched for age, gender and education. Participants performed simple finger-lifting movements in response to (1) biological finger and non-biological dot movement stimuli, (2) acoustic stimuli and (3) combined visual-acoustic stimuli with different contextual (compatible/incompatible) and temporal (simultaneous/asynchronous) relation. Mixed model analyses revealed slower reaction times in autism spectrum disorder. Both groups responded faster to biological compared to non-biological stimuli (Experiment 1) implying intact processing advantage for biological stimuli in autism spectrum disorder. In Experiment 3, both groups had similar 'interference effects' when stimuli were presented simultaneously. However, autism spectrum disorder participants had abnormally slow responses particularly when incompatible stimuli were presented consecutively. Our results suggest imitative control deficits rather than global imitative system impairments. © The Author(s) 2015.

A Unifying Mathematical Framework for Genetic Robustness, Environmental Robustness, Network Robustness and their Trade-off on Phenotype Robustness in Biological Networks Part I: Gene Regulatory Networks in Systems and Evolutionary Biology

PubMed Central

Chen, Bor-Sen; Lin, Ying-Po

2013-01-01

Robust stabilization and environmental disturbance attenuation are ubiquitous systematic properties observed in biological systems at different levels. The underlying principles for robust stabilization and environmental disturbance attenuation are universal to both complex biological systems and sophisticated engineering systems. In many biological networks, network robustness should be enough to confer intrinsic robustness in order to tolerate intrinsic parameter fluctuations, genetic robustness for buffering genetic variations, and environmental robustness for resisting environmental disturbances. With this, the phenotypic stability of biological network can be maintained, thus guaranteeing phenotype robustness. This paper presents a survey on biological systems and then develops a unifying mathematical framework for investigating the principles of both robust stabilization and environmental disturbance attenuation in systems and evolutionary biology. Further, from the unifying mathematical framework, it was discovered that the phenotype robustness criterion for biological networks at different levels relies upon intrinsic robustness + genetic robustness + environmental robustness ≦ network robustness. When this is true, the phenotype robustness can be maintained in spite of intrinsic parameter fluctuations, genetic variations, and environmental disturbances. Therefore, the trade-offs between intrinsic robustness, genetic robustness, environmental robustness, and network robustness in systems and evolutionary biology can also be investigated through their corresponding phenotype robustness criterion from the systematic point of view. PMID:23515240

A Unifying Mathematical Framework for Genetic Robustness, Environmental Robustness, Network Robustness and their Trade-off on Phenotype Robustness in Biological Networks Part I: Gene Regulatory Networks in Systems and Evolutionary Biology.

PubMed

Chen, Bor-Sen; Lin, Ying-Po

2013-01-01

Robust stabilization and environmental disturbance attenuation are ubiquitous systematic properties observed in biological systems at different levels. The underlying principles for robust stabilization and environmental disturbance attenuation are universal to both complex biological systems and sophisticated engineering systems. In many biological networks, network robustness should be enough to confer intrinsic robustness in order to tolerate intrinsic parameter fluctuations, genetic robustness for buffering genetic variations, and environmental robustness for resisting environmental disturbances. With this, the phenotypic stability of biological network can be maintained, thus guaranteeing phenotype robustness. This paper presents a survey on biological systems and then develops a unifying mathematical framework for investigating the principles of both robust stabilization and environmental disturbance attenuation in systems and evolutionary biology. Further, from the unifying mathematical framework, it was discovered that the phenotype robustness criterion for biological networks at different levels relies upon intrinsic robustness + genetic robustness + environmental robustness ≦ network robustness. When this is true, the phenotype robustness can be maintained in spite of intrinsic parameter fluctuations, genetic variations, and environmental disturbances. Therefore, the trade-offs between intrinsic robustness, genetic robustness, environmental robustness, and network robustness in systems and evolutionary biology can also be investigated through their corresponding phenotype robustness criterion from the systematic point of view.

Luminescent Rhenium(I) and Iridium(III) Polypyridine Complexes as Biological Probes, Imaging Reagents, and Photocytotoxic Agents.

PubMed

Lo, Kenneth Kam-Wing

2015-12-15

Although the interactions of transition metal complexes with biological molecules have been extensively studied, the use of luminescent transition metal complexes as intracellular sensors and bioimaging reagents has not been a focus of research until recently. The main advantages of luminescent transition metal complexes are their high photostability, long-lived phosphorescence that allows time-resolved detection, and large Stokes shifts that can minimize the possible self-quenching effect. Also, by the use of transition metal complexes, the degree of cellular uptake can be readily determined using inductively coupled plasma mass spectrometry. For more than a decade, we have been interested in the development of luminescent transition metal complexes as covalent labels and noncovalent probes for biological molecules. We argue that many transition metal polypyridine complexes display triplet charge transfer ((3)CT) emission that is highly sensitive to the local environment of the complexes. Hence, the biological labeling and binding interactions can be readily reflected by changes in the photophysical properties of the complexes. In this laboratory, we have modified luminescent tricarbonylrhenium(I) and bis-cyclometalated iridium(III) polypyridine complexes of general formula [Re(bpy-R(1))(CO)3(py-R(2))](+) and [Ir(ppy-R(3))2(bpy-R(4))](+), respectively, with reactive functional groups and used them to label the amine and sulfhydryl groups of biomolecules such as oligonucleotides, amino acids, peptides, and proteins. Additionally, using a range of biological substrates such as biotin, estradiol, and indole, we have designed luminescent rhenium(I) and iridium(III) polypyridine complexes as noncovalent probes for biological receptors. The interesting results generated from these studies have prompted us to investigate the possible applications of luminescent transition metal complexes in intracellular systems. Thus, in the past few years, we have developed an interest in the cytotoxic activity, cellular uptake, and bioimaging applications of these complexes. Additionally, we and other research groups have demonstrated that many transition metal complexes have facile cellular uptake and organelle-localization properties and that their cytotoxic activity can be readily controlled. For example, complexes that can target the nucleus, nucleolus, mitochondria, lysosomes, endoplasmic reticulum, and Golgi apparatus have been identified. We anticipate that this selective localization property can be utilized in the development of intracellular sensors and bioimaging reagents. Thus, we have functionalized luminescent rhenium(I) and iridium(III) polypyridine complexes with various pendants, including molecule-binding moieties, sugar molecules, bioorthogonal functional groups, and polymeric chains such as poly(ethylene glycol) and polyethylenimine, and examined their potentials as biological reagents. This Account describes our design of luminescent rhenium(I) and iridium(III) polypyridine complexes and explains how they can serve as a new generation of biological reagents for diagnostic and therapeutic applications.

Modeling of Heavy Metal Transformation in Soil Ecosystem

NASA Astrophysics Data System (ADS)

Kalinichenko, Kira; Nikovskaya, Galina N.

2017-04-01

The intensification of industrial activity leads to an increase in heavy metals pollution of soils. In our opinion, sludge from biological treatment of municipal waste water, stabilized under aerobic-anaerobic conditions (commonly known as biosolid), may be considered as concentrate of natural soil. In their chemical, physical and chemical and biological properties these systems are similar gel-like nanocomposites. These contain microorganisms, humic substances, clay, clusters of nanoparticles of heavy metal compounds, and so on involved into heteropolysaccharides matrix. It is known that microorganisms play an important role in the transformation of different nature substances in soil and its health maintenance. The regularities of transformation of heavy metal compounds in soil ecosystem were studied at the model of biosolid. At biosolid swelling its structure changing (gel-sol transition, weakening of coagulation contacts between metal containing nanoparticles, microbial cells and metabolites, loosening and even destroying of the nanocomposite structure) can occur [1, 2]. The promotion of the sludge heterotrophic microbial activities leads to solubilization of heavy metal compounds in the system. The microbiological process can be realized in alcaligeneous or acidogeneous regimes in dependence on the type of carbon source and followed by the synthesis of metabolites with the properties of flocculants and heavy metals extragents [3]. In this case the heavy metals solubilization (bioleaching) in the form of nanoparticles of hydroxycarbonate complexes or water soluble complexes with oxycarbonic acids is observed. Under the action of biosolid microorganisms the heavy metals-oxycarbonic acids complexes can be transformed (catabolised) into nano-sizing heavy metals- hydroxycarbonates complexes. These ecologically friendly complexes and microbial heteropolysaccharides are able to interact with soil colloids, stay in the top soil profile, and improve soil structure due to the formation of water-stable aggregates. The alkaligeneous microbiological process in natural ecosystems by co-metabolism of appropriate carbon source is more advantages for environment. Thus the possibility of solubilization of heavy metal compounds in the soil due to stimulating its biological activities of native microorganisms is proved. The studies on the interactions in the system of sludge solid has allowed to develop the "green" biotechnological process of heavy metals solubilization in contaminated soils and sludges. 1. Kalinichenko KV, Nikovskaya GN, and Ulberg ZR (2012) Bioextraction of heavy metals from colloidal sludge systems. Colloid Journ. 74(5) : 553-557. 2. Kalinichenko KV, Nikovskaya GN, and Ulberg ZR (2013) Changes in the surface properties and stability of biocolloids of a sludge system upon extraction of heavy metals. Colloid Journ. 75(3) : 274-278. 3. Nikovskaya GN, Kalinichenko KV (2013) Bioleaching of heavy metals from sludge after biological treatment of municipal effluent. Journ. of Water Chem. and Techn. 35(2) : 80-85.

Agent-based modeling of autophagy reveals emergent regulatory behavior of spatio-temporal autophagy dynamics.

PubMed

Börlin, Christoph S; Lang, Verena; Hamacher-Brady, Anne; Brady, Nathan R

2014-09-10

Autophagy is a vesicle-mediated pathway for lysosomal degradation, essential under basal and stressed conditions. Various cellular components, including specific proteins, protein aggregates, organelles and intracellular pathogens, are targets for autophagic degradation. Thereby, autophagy controls numerous vital physiological and pathophysiological functions, including cell signaling, differentiation, turnover of cellular components and pathogen defense. Moreover, autophagy enables the cell to recycle cellular components to metabolic substrates, thereby permitting prolonged survival under low nutrient conditions. Due to the multi-faceted roles for autophagy in maintaining cellular and organismal homeostasis and responding to diverse stresses, malfunction of autophagy contributes to both chronic and acute pathologies. We applied a systems biology approach to improve the understanding of this complex cellular process of autophagy. All autophagy pathway vesicle activities, i.e. creation, movement, fusion and degradation, are highly dynamic, temporally and spatially, and under various forms of regulation. We therefore developed an agent-based model (ABM) to represent individual components of the autophagy pathway, subcellular vesicle dynamics and metabolic feedback with the cellular environment, thereby providing a framework to investigate spatio-temporal aspects of autophagy regulation and dynamic behavior. The rules defining our ABM were derived from literature and from high-resolution images of autophagy markers under basal and activated conditions. Key model parameters were fit with an iterative method using a genetic algorithm and a predefined fitness function. From this approach, we found that accurate prediction of spatio-temporal behavior required increasing model complexity by implementing functional integration of autophagy with the cellular nutrient state. The resulting model is able to reproduce short-term autophagic flux measurements (up to 3 hours) under basal and activated autophagy conditions, and to measure the degree of cell-to-cell variability. Moreover, we experimentally confirmed two model predictions, namely (i) peri-nuclear concentration of autophagosomes and (ii) inhibitory lysosomal feedback on mTOR signaling. Agent-based modeling represents a novel approach to investigate autophagy dynamics, function and dysfunction with high biological realism. Our model accurately recapitulates short-term behavior and cell-to-cell variability under basal and activated conditions of autophagy. Further, this approach also allows investigation of long-term behaviors emerging from biologically-relevant alterations to vesicle trafficking and metabolic state.

Analyzing indirect secondary electron contrast of unstained bacteriophage T4 based on SEM images and Monte Carlo simulations

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

Ogura, Toshihiko, E-mail: t-ogura@aist.go.jp

2009-03-06

The indirect secondary electron contrast (ISEC) condition of the scanning electron microscopy (SEM) produces high contrast detection with minimal damage of unstained biological samples mounted under a thin carbon film. The high contrast image is created by a secondary electron signal produced under the carbon film by a low acceleration voltage. Here, we show that ISEC condition is clearly able to detect unstained bacteriophage T4 under a thin carbon film (10-15 nm) by using high-resolution field emission (FE) SEM. The results show that FE-SEM provides higher resolution than thermionic emission SEM. Furthermore, we investigated the scattered electron area within themore » carbon film under ISEC conditions using Monte Carlo simulation. The simulations indicated that the image resolution difference is related to the scattering width in the carbon film and the electron beam spot size. Using ISEC conditions on unstained virus samples would produce low electronic damage, because the electron beam does not directly irradiate the sample. In addition to the routine analysis, this method can be utilized for structural analysis of various biological samples like viruses, bacteria, and protein complexes.« less

Topics in Complexity: Dynamical Patterns in the Cyberworld

NASA Astrophysics Data System (ADS)

Qi, Hong

Quantitative understanding of mechanism in complex systems is a common "difficult" problem across many fields such as physical, biological, social and economic sciences. Investigation on underlying dynamics of complex systems and building individual-based models have recently been fueled by big data resulted from advancing information technology. This thesis investigates complex systems in social science, focusing on civil unrests on streets and relevant activities online. Investigation consists of collecting data of unrests from open digital source, featuring dynamical patterns underlying, making predictions and constructing models. A simple law governing the progress of two-sided confrontations is proposed with data of activities at micro-level. Unraveling the connections between activity of organizing online and outburst of unrests on streets gives rise to a further meso-level pattern of human behavior, through which adversarial groups evolve online and hyper-escalate ahead of real-world uprisings. Based on the patterns found, noticeable improvement of prediction of civil unrests is achieved. Meanwhile, novel model created from combination of mobility dynamics in the cyberworld and a traditional contagion model can better capture the characteristics of modern civil unrests and other contagion-like phenomena than the original one.

Interlaboratory Study Characterizing a Yeast Performance Standard for Benchmarking LC-MS Platform Performance*

PubMed Central

Paulovich, Amanda G.; Billheimer, Dean; Ham, Amy-Joan L.; Vega-Montoto, Lorenzo; Rudnick, Paul A.; Tabb, David L.; Wang, Pei; Blackman, Ronald K.; Bunk, David M.; Cardasis, Helene L.; Clauser, Karl R.; Kinsinger, Christopher R.; Schilling, Birgit; Tegeler, Tony J.; Variyath, Asokan Mulayath; Wang, Mu; Whiteaker, Jeffrey R.; Zimmerman, Lisa J.; Fenyo, David; Carr, Steven A.; Fisher, Susan J.; Gibson, Bradford W.; Mesri, Mehdi; Neubert, Thomas A.; Regnier, Fred E.; Rodriguez, Henry; Spiegelman, Cliff; Stein, Stephen E.; Tempst, Paul; Liebler, Daniel C.

2010-01-01

Optimal performance of LC-MS/MS platforms is critical to generating high quality proteomics data. Although individual laboratories have developed quality control samples, there is no widely available performance standard of biological complexity (and associated reference data sets) for benchmarking of platform performance for analysis of complex biological proteomes across different laboratories in the community. Individual preparations of the yeast Saccharomyces cerevisiae proteome have been used extensively by laboratories in the proteomics community to characterize LC-MS platform performance. The yeast proteome is uniquely attractive as a performance standard because it is the most extensively characterized complex biological proteome and the only one associated with several large scale studies estimating the abundance of all detectable proteins. In this study, we describe a standard operating protocol for large scale production of the yeast performance standard and offer aliquots to the community through the National Institute of Standards and Technology where the yeast proteome is under development as a certified reference material to meet the long term needs of the community. Using a series of metrics that characterize LC-MS performance, we provide a reference data set demonstrating typical performance of commonly used ion trap instrument platforms in expert laboratories; the results provide a basis for laboratories to benchmark their own performance, to improve upon current methods, and to evaluate new technologies. Additionally, we demonstrate how the yeast reference, spiked with human proteins, can be used to benchmark the power of proteomics platforms for detection of differentially expressed proteins at different levels of concentration in a complex matrix, thereby providing a metric to evaluate and minimize preanalytical and analytical variation in comparative proteomics experiments. PMID:19858499

Studying the dynamics of interbeat interval time series of healthy and congestive heart failure subjects using scale based symbolic entropy analysis

PubMed Central

Awan, Imtiaz; Aziz, Wajid; Habib, Nazneen; Alowibdi, Jalal S.; Saeed, Sharjil; Nadeem, Malik Sajjad Ahmed; Shah, Syed Ahsin Ali

2018-01-01

Considerable interest has been devoted for developing a deeper understanding of the dynamics of healthy biological systems and how these dynamics are affected due to aging and disease. Entropy based complexity measures have widely been used for quantifying the dynamics of physical and biological systems. These techniques have provided valuable information leading to a fuller understanding of the dynamics of these systems and underlying stimuli that are responsible for anomalous behavior. The single scale based traditional entropy measures yielded contradictory results about the dynamics of real world time series data of healthy and pathological subjects. Recently the multiscale entropy (MSE) algorithm was introduced for precise description of the complexity of biological signals, which was used in numerous fields since its inception. The original MSE quantified the complexity of coarse-grained time series using sample entropy. The original MSE may be unreliable for short signals because the length of the coarse-grained time series decreases with increasing scaling factor τ, however, MSE works well for long signals. To overcome the drawback of original MSE, various variants of this method have been proposed for evaluating complexity efficiently. In this study, we have proposed multiscale normalized corrected Shannon entropy (MNCSE), in which instead of using sample entropy, symbolic entropy measure NCSE has been used as an entropy estimate. The results of the study are compared with traditional MSE. The effectiveness of the proposed approach is demonstrated using noise signals as well as interbeat interval signals from healthy and pathological subjects. The preliminary results of the study indicate that MNCSE values are more stable and reliable than original MSE values. The results show that MNCSE based features lead to higher classification accuracies in comparison with the MSE based features. PMID:29771977

Studying the dynamics of interbeat interval time series of healthy and congestive heart failure subjects using scale based symbolic entropy analysis.

PubMed

Awan, Imtiaz; Aziz, Wajid; Shah, Imran Hussain; Habib, Nazneen; Alowibdi, Jalal S; Saeed, Sharjil; Nadeem, Malik Sajjad Ahmed; Shah, Syed Ahsin Ali

2018-01-01

Considerable interest has been devoted for developing a deeper understanding of the dynamics of healthy biological systems and how these dynamics are affected due to aging and disease. Entropy based complexity measures have widely been used for quantifying the dynamics of physical and biological systems. These techniques have provided valuable information leading to a fuller understanding of the dynamics of these systems and underlying stimuli that are responsible for anomalous behavior. The single scale based traditional entropy measures yielded contradictory results about the dynamics of real world time series data of healthy and pathological subjects. Recently the multiscale entropy (MSE) algorithm was introduced for precise description of the complexity of biological signals, which was used in numerous fields since its inception. The original MSE quantified the complexity of coarse-grained time series using sample entropy. The original MSE may be unreliable for short signals because the length of the coarse-grained time series decreases with increasing scaling factor τ, however, MSE works well for long signals. To overcome the drawback of original MSE, various variants of this method have been proposed for evaluating complexity efficiently. In this study, we have proposed multiscale normalized corrected Shannon entropy (MNCSE), in which instead of using sample entropy, symbolic entropy measure NCSE has been used as an entropy estimate. The results of the study are compared with traditional MSE. The effectiveness of the proposed approach is demonstrated using noise signals as well as interbeat interval signals from healthy and pathological subjects. The preliminary results of the study indicate that MNCSE values are more stable and reliable than original MSE values. The results show that MNCSE based features lead to higher classification accuracies in comparison with the MSE based features.

Network analysis reveals the recognition mechanism for complex formation of mannose-binding lectins

NASA Astrophysics Data System (ADS)

Jian, Yiren; Zhao, Yunjie; Zeng, Chen

The specific carbohydrate binding of lectin makes the protein a powerful molecular tool for various applications including cancer cell detection due to its glycoprotein profile on the cell surface. Most biologically active lectins are dimeric. To understand the structure-function relation of lectin complex, it is essential to elucidate the short- and long-range driving forces behind the dimer formation. Here we report our molecular dynamics simulations and associated dynamical network analysis on a particular lectin, i.e., the mannose-binding lectin from garlic. Our results, further supported by sequence coevolution analysis, shed light on how different parts of the complex communicate with each other. We propose a general framework for deciphering the recognition mechanism underlying protein-protein interactions that may have potential applications in signaling pathways.

Computational Complexity and Human Decision-Making.

PubMed

Bossaerts, Peter; Murawski, Carsten

2017-12-01

The rationality principle postulates that decision-makers always choose the best action available to them. It underlies most modern theories of decision-making. The principle does not take into account the difficulty of finding the best option. Here, we propose that computational complexity theory (CCT) provides a framework for defining and quantifying the difficulty of decisions. We review evidence showing that human decision-making is affected by computational complexity. Building on this evidence, we argue that most models of decision-making, and metacognition, are intractable from a computational perspective. To be plausible, future theories of decision-making will need to take into account both the resources required for implementing the computations implied by the theory, and the resource constraints imposed on the decision-maker by biology. Copyright © 2017 Elsevier Ltd. All rights reserved.

What I got wrong about shelterin.

PubMed

de Lange, Titia

2018-05-24

The ASBMB 2018 Bert and Natalie Vallee award in Biomedical Sciences honors our work on shelterin, a protein complex that helps cells distinguish the chromosome ends from sites of DNA damage. Shelterin protects telomeres from all aspects of the DNA damage response, including ATM and ATR serine/threonine kinase signaling and several forms of double-strand break repair. Today, this six-subunit protein complex could easily be identified in one single proteomics step. But it took us more than 15 years to piece the entire shelterin complex together, one protein at a time. Although we did a lot of things right, here I tell the story of shelterin's discovery with an emphasis on the things that I got wrong along the way. Published under license by The American Society for Biochemistry and Molecular Biology, Inc.

The DNA Triangle and Its Application to Learning Meiosis.

PubMed

Wright, L Kate; Catavero, Christina M; Newman, Dina L

2017-01-01

Although instruction on meiosis is repeated many times during the undergraduate curriculum, many students show poor comprehension even as upper-level biology majors. We propose that the difficulty lies in the complexity of understanding DNA, which we explain through a new model, the DNA triangle The DNA triangle integrates three distinct scales at which one can think about DNA: chromosomal , molecular , and informational Through analysis of interview and survey data from biology faculty and students through the lens of the DNA triangle, we illustrate important differences in how novices and experts are able to explain the concepts of ploidy , homology , and mechanism of homologous pairing Similarly, analysis of passages from 16 different biology textbooks shows a large divide between introductory and advanced material, with introductory books omitting explanations of meiosis-linked concepts at the molecular level of DNA. Finally, backed by textbook findings and feedback from biology experts, we show that the DNA triangle can be applied to teaching and learning meiosis. By applying the DNA triangle to topics on meiosis we present a new framework for educators and researchers that ties concepts of ploidy, homology, and mechanism of homologous pairing to knowledge about DNA on the chromosomal, molecular, and informational levels. © 2017 L. K. Wright et al. CBE—Life Sciences Education © 2017 The American Society for Cell Biology. This article is distributed by The American Society for Cell Biology under license from the author(s). It is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

The structure of a gene co-expression network reveals biological functions underlying eQTLs.

PubMed

Villa-Vialaneix, Nathalie; Liaubet, Laurence; Laurent, Thibault; Cherel, Pierre; Gamot, Adrien; SanCristobal, Magali

2013-01-01

What are the commonalities between genes, whose expression level is partially controlled by eQTL, especially with regard to biological functions? Moreover, how are these genes related to a phenotype of interest? These issues are particularly difficult to address when the genome annotation is incomplete, as is the case for mammalian species. Moreover, the direct link between gene expression and a phenotype of interest may be weak, and thus difficult to handle. In this framework, the use of a co-expression network has proven useful: it is a robust approach for modeling a complex system of genetic regulations, and to infer knowledge for yet unknown genes. In this article, a case study was conducted with a mammalian species. It showed that the use of a co-expression network based on partial correlation, combined with a relevant clustering of nodes, leads to an enrichment of biological functions of around 83%. Moreover, the use of a spatial statistics approach allowed us to superimpose additional information related to a phenotype; this lead to highlighting specific genes or gene clusters that are related to the network structure and the phenotype. Three main results are worth noting: first, key genes were highlighted as a potential focus for forthcoming biological experiments; second, a set of biological functions, which support a list of genes under partial eQTL control, was set up by an overview of the global structure of the gene expression network; third, pH was found correlated with gene clusters, and then with related biological functions, as a result of a spatial analysis of the network topology.

PeTTSy: a computational tool for perturbation analysis of complex systems biology models.

PubMed

Domijan, Mirela; Brown, Paul E; Shulgin, Boris V; Rand, David A

2016-03-10

Over the last decade sensitivity analysis techniques have been shown to be very useful to analyse complex and high dimensional Systems Biology models. However, many of the currently available toolboxes have either used parameter sampling, been focused on a restricted set of model observables of interest, studied optimisation of a objective function, or have not dealt with multiple simultaneous model parameter changes where the changes can be permanent or temporary. Here we introduce our new, freely downloadable toolbox, PeTTSy (Perturbation Theory Toolbox for Systems). PeTTSy is a package for MATLAB which implements a wide array of techniques for the perturbation theory and sensitivity analysis of large and complex ordinary differential equation (ODE) based models. PeTTSy is a comprehensive modelling framework that introduces a number of new approaches and that fully addresses analysis of oscillatory systems. It examines sensitivity analysis of the models to perturbations of parameters, where the perturbation timing, strength, length and overall shape can be controlled by the user. This can be done in a system-global setting, namely, the user can determine how many parameters to perturb, by how much and for how long. PeTTSy also offers the user the ability to explore the effect of the parameter perturbations on many different types of outputs: period, phase (timing of peak) and model solutions. PeTTSy can be employed on a wide range of mathematical models including free-running and forced oscillators and signalling systems. To enable experimental optimisation using the Fisher Information Matrix it efficiently allows one to combine multiple variants of a model (i.e. a model with multiple experimental conditions) in order to determine the value of new experiments. It is especially useful in the analysis of large and complex models involving many variables and parameters. PeTTSy is a comprehensive tool for analysing large and complex models of regulatory and signalling systems. It allows for simulation and analysis of models under a variety of environmental conditions and for experimental optimisation of complex combined experiments. With its unique set of tools it makes a valuable addition to the current library of sensitivity analysis toolboxes. We believe that this software will be of great use to the wider biological, systems biology and modelling communities.

The portable UNIX programming system (PUPS) and CANTOR: a computational environment for dynamical representation and analysis of complex neurobiological data.

PubMed

O'Neill, M A; Hilgetag, C C

2001-08-29

Many problems in analytical biology, such as the classification of organisms, the modelling of macromolecules, or the structural analysis of metabolic or neural networks, involve complex relational data. Here, we describe a software environment, the portable UNIX programming system (PUPS), which has been developed to allow efficient computational representation and analysis of such data. The system can also be used as a general development tool for database and classification applications. As the complexity of analytical biology problems may lead to computation times of several days or weeks even on powerful computer hardware, the PUPS environment gives support for persistent computations by providing mechanisms for dynamic interaction and homeostatic protection of processes. Biological objects and their interrelations are also represented in a homeostatic way in PUPS. Object relationships are maintained and updated by the objects themselves, thus providing a flexible, scalable and current data representation. Based on the PUPS environment, we have developed an optimization package, CANTOR, which can be applied to a wide range of relational data and which has been employed in different analyses of neuroanatomical connectivity. The CANTOR package makes use of the PUPS system features by modifying candidate arrangements of objects within the system's database. This restructuring is carried out via optimization algorithms that are based on user-defined cost functions, thus providing flexible and powerful tools for the structural analysis of the database content. The use of stochastic optimization also enables the CANTOR system to deal effectively with incomplete and inconsistent data. Prototypical forms of PUPS and CANTOR have been coded and used successfully in the analysis of anatomical and functional mammalian brain connectivity, involving complex and inconsistent experimental data. In addition, PUPS has been used for solving multivariate engineering optimization problems and to implement the digital identification system (DAISY), a system for the automated classification of biological objects. PUPS is implemented in ANSI-C under the POSIX.1 standard and is to a great extent architecture- and operating-system independent. The software is supported by systems libraries that allow multi-threading (the concurrent processing of several database operations), as well as the distribution of the dynamic data objects and library operations over clusters of computers. These attributes make the system easily scalable, and in principle allow the representation and analysis of arbitrarily large sets of relational data. PUPS and CANTOR are freely distributed (http://www.pups.org.uk) as open-source software under the GNU license agreement.

The portable UNIX programming system (PUPS) and CANTOR: a computational environment for dynamical representation and analysis of complex neurobiological data.

PubMed Central

O'Neill, M A; Hilgetag, C C

2001-01-01

Many problems in analytical biology, such as the classification of organisms, the modelling of macromolecules, or the structural analysis of metabolic or neural networks, involve complex relational data. Here, we describe a software environment, the portable UNIX programming system (PUPS), which has been developed to allow efficient computational representation and analysis of such data. The system can also be used as a general development tool for database and classification applications. As the complexity of analytical biology problems may lead to computation times of several days or weeks even on powerful computer hardware, the PUPS environment gives support for persistent computations by providing mechanisms for dynamic interaction and homeostatic protection of processes. Biological objects and their interrelations are also represented in a homeostatic way in PUPS. Object relationships are maintained and updated by the objects themselves, thus providing a flexible, scalable and current data representation. Based on the PUPS environment, we have developed an optimization package, CANTOR, which can be applied to a wide range of relational data and which has been employed in different analyses of neuroanatomical connectivity. The CANTOR package makes use of the PUPS system features by modifying candidate arrangements of objects within the system's database. This restructuring is carried out via optimization algorithms that are based on user-defined cost functions, thus providing flexible and powerful tools for the structural analysis of the database content. The use of stochastic optimization also enables the CANTOR system to deal effectively with incomplete and inconsistent data. Prototypical forms of PUPS and CANTOR have been coded and used successfully in the analysis of anatomical and functional mammalian brain connectivity, involving complex and inconsistent experimental data. In addition, PUPS has been used for solving multivariate engineering optimization problems and to implement the digital identification system (DAISY), a system for the automated classification of biological objects. PUPS is implemented in ANSI-C under the POSIX.1 standard and is to a great extent architecture- and operating-system independent. The software is supported by systems libraries that allow multi-threading (the concurrent processing of several database operations), as well as the distribution of the dynamic data objects and library operations over clusters of computers. These attributes make the system easily scalable, and in principle allow the representation and analysis of arbitrarily large sets of relational data. PUPS and CANTOR are freely distributed (http://www.pups.org.uk) as open-source software under the GNU license agreement. PMID:11545702

Responses of antennal olfactory receptors in the yellow fever mosquito Aedes aegypti to human body odours.

PubMed

Pappenberger, B; Geier, M; Boeckh, J

1996-01-01

Recent behavioural studies have demonstrated that human body odours which female Aedes aegypti find attractive exert their effects as complex mixtures of synergistically acting components. We have attempted to clarify the sensory mechanisms underlying the perception of these complex host odours by studying the responses of sensory cells underneath the A3-type sensilla of the mosquito antenna to both a human skin wash extract and the extract's active chromatographic fractions. The reaction patterns show that the host stimuli elicit responses from several types of receptor cells in a typical across-fibre pattern mode. It seems as if this is another case where the essential message in a biologically significant odour consists of a complex pattern of compounds that is encoded in an according complex response pattern by a cooperating set of primary sensory neurons of different odour specificities.

The topological requirements for robust perfect adaptation in networks of any size.

PubMed

Araujo, Robyn P; Liotta, Lance A

2018-05-01

Robustness, and the ability to function and thrive amid changing and unfavorable environments, is a fundamental requirement for living systems. Until now it has been an open question how large and complex biological networks can exhibit robust behaviors, such as perfect adaptation to a variable stimulus, since complexity is generally associated with fragility. Here we report that all networks that exhibit robust perfect adaptation (RPA) to a persistent change in stimulus are decomposable into well-defined modules, of which there exist two distinct classes. These two modular classes represent a topological basis for all RPA-capable networks, and generate the full set of topological realizations of the internal model principle for RPA in complex, self-organizing, evolvable bionetworks. This unexpected result supports the notion that evolutionary processes are empowered by simple and scalable modular design principles that promote robust performance no matter how large or complex the underlying networks become.

Cancer initiation and progression: an unsimplifiable complexity

PubMed Central

Grizzi, Fabio; Di Ieva, Antonio; Russo, Carlo; Frezza, Eldo E; Cobos, Everardo; Muzzio, Pier Carlo; Chiriva-Internati, Maurizio

2006-01-01

Background Cancer remains one of the most complex diseases affecting humans and, despite the impressive advances that have been made in molecular and cell biology, how cancer cells progress through carcinogenesis and acquire their metastatic ability is still widely debated. Conclusion There is no doubt that human carcinogenesis is a dynamic process that depends on a large number of variables and is regulated at multiple spatial and temporal scales. Viewing cancer as a system that is dynamically complex in time and space will, however, probably reveal more about its underlying behavioural characteristics. It is encouraging that mathematicians, biologists and clinicians continue to contribute together towards a common quantitative understanding of cancer complexity. This way of thinking may further help to clarify concepts, interpret new and old experimental data, indicate alternative experiments and categorize the acquired knowledge on the basis of the similarities and/or shared behaviours of very different tumours. PMID:17044918

Seeking unique and common biological themes in multiple gene lists or datasets: pathway pattern extraction pipeline for pathway-level comparative analysis.

PubMed

Yi, Ming; Mudunuri, Uma; Che, Anney; Stephens, Robert M

2009-06-29

One of the challenges in the analysis of microarray data is to integrate and compare the selected (e.g., differential) gene lists from multiple experiments for common or unique underlying biological themes. A common way to approach this problem is to extract common genes from these gene lists and then subject these genes to enrichment analysis to reveal the underlying biology. However, the capacity of this approach is largely restricted by the limited number of common genes shared by datasets from multiple experiments, which could be caused by the complexity of the biological system itself. We now introduce a new Pathway Pattern Extraction Pipeline (PPEP), which extends the existing WPS application by providing a new pathway-level comparative analysis scheme. To facilitate comparing and correlating results from different studies and sources, PPEP contains new interfaces that allow evaluation of the pathway-level enrichment patterns across multiple gene lists. As an exploratory tool, this analysis pipeline may help reveal the underlying biological themes at both the pathway and gene levels. The analysis scheme provided by PPEP begins with multiple gene lists, which may be derived from different studies in terms of the biological contexts, applied technologies, or methodologies. These lists are then subjected to pathway-level comparative analysis for extraction of pathway-level patterns. This analysis pipeline helps to explore the commonality or uniqueness of these lists at the level of pathways or biological processes from different but relevant biological systems using a combination of statistical enrichment measurements, pathway-level pattern extraction, and graphical display of the relationships of genes and their associated pathways as Gene-Term Association Networks (GTANs) within the WPS platform. As a proof of concept, we have used the new method to analyze many datasets from our collaborators as well as some public microarray datasets. This tool provides a new pathway-level analysis scheme for integrative and comparative analysis of data derived from different but relevant systems. The tool is freely available as a Pathway Pattern Extraction Pipeline implemented in our existing software package WPS, which can be obtained at http://www.abcc.ncifcrf.gov/wps/wps_index.php.

Prefrontal cortex, dopamine, and jealousy endophenotype.

PubMed

Marazziti, Donatella; Poletti, Michele; Dell'Osso, Liliana; Baroni, Stefano; Bonuccelli, Ubaldo

2013-02-01

Jealousy is a complex emotion characterized by the perception of a threat of loss of something that the person values,particularly in reference to a relationship with a loved one, which includes affective, cognitive, and behavioral components. Neural systems and cognitive processes underlying jealousy are relatively unclear, and only a few neuroimaging studies have investigated them. The current article discusses recent empirical findings on delusional jealousy, which is the most severe form of this feeling, in neurodegenerative diseases. After reviewing empirical findings on neurological and psychiatric disorders with delusional jealousy, and after considering its high prevalence in patients with Parkinson's disease under dopamine agonist treatment, we propose a core neural network and core cognitive processes at the basis of (delusional) jealousy, characterizing this symptom as possible endophenotype. In any case,empirical investigation of the neural bases of jealousy is just beginning, and further studies are strongly needed to elucidate the biological roots of this complex emotion.

Stability and dynamical properties of material flow systems on random networks

NASA Astrophysics Data System (ADS)

Anand, K.; Galla, T.

2009-04-01

The theory of complex networks and of disordered systems is used to study the stability and dynamical properties of a simple model of material flow networks defined on random graphs. In particular we address instabilities that are characteristic of flow networks in economic, ecological and biological systems. Based on results from random matrix theory, we work out the phase diagram of such systems defined on extensively connected random graphs, and study in detail how the choice of control policies and the network structure affects stability. We also present results for more complex topologies of the underlying graph, focussing on finitely connected Erdös-Réyni graphs, Small-World Networks and Barabási-Albert scale-free networks. Results indicate that variability of input-output matrix elements, and random structures of the underlying graph tend to make the system less stable, while fast price dynamics or strong responsiveness to stock accumulation promote stability.

Enzyme-catalyzed cationic epoxide rearrangements in quinolone alkaloid biosynthesis.

PubMed

Zou, Yi; Garcia-Borràs, Marc; Tang, Mancheng C; Hirayama, Yuichiro; Li, Dehai H; Li, Li; Watanabe, Kenji; Houk, K N; Tang, Yi

2017-03-01

Epoxides are highly useful synthons and biosynthons for the construction of complex natural products during total synthesis and biosynthesis, respectively. Among enzyme-catalyzed epoxide transformations, a reaction that is notably missing, in regard to the synthetic toolbox, is cationic rearrangement that takes place under strong acid. This is a challenging transformation for enzyme catalysis, as stabilization of the carbocation intermediate upon epoxide cleavage is required. Here, we discovered two Brønsted acid enzymes that can catalyze two unprecedented epoxide transformations in biology. PenF from the penigequinolone pathway catalyzes a cationic epoxide rearrangement under physiological conditions to generate a quaternary carbon center, while AsqO from the aspoquinolone pathway catalyzes a 3-exo-tet cyclization to forge a cyclopropane-tetrahydrofuran ring system. The discovery of these new epoxide-modifying enzymes further highlights the versatility of epoxides in complexity generation during natural product biosynthesis.

Optical imaging of localized chemical events using programmable diamond quantum nanosensors

NASA Astrophysics Data System (ADS)

Rendler, Torsten; Neburkova, Jitka; Zemek, Ondrej; Kotek, Jan; Zappe, Andrea; Chu, Zhiqin; Cigler, Petr; Wrachtrup, Jörg

2017-03-01

Development of multifunctional nanoscale sensors working under physiological conditions enables monitoring of intracellular processes that are important for various biological and medical applications. By attaching paramagnetic gadolinium complexes to nanodiamonds (NDs) with nitrogen-vacancy (NV) centres through surface engineering, we developed a hybrid nanoscale sensor that can be adjusted to directly monitor physiological species through a proposed sensing scheme based on NV spin relaxometry. We adopt a single-step method to measure spin relaxation rates enabling time-dependent measurements on changes in pH or redox potential at a submicrometre-length scale in a microfluidic channel that mimics cellular environments. Our experimental data are reproduced by numerical simulations of the NV spin interaction with gadolinium complexes covering the NDs. Considering the versatile engineering options provided by polymer chemistry, the underlying mechanism can be expanded to detect a variety of physiologically relevant species and variables.

Discovering hidden relationships between renal diseases and regulated genes through 3D network visualizations

PubMed Central

2010-01-01

Background In a recent study, two-dimensional (2D) network layouts were used to visualize and quantitatively analyze the relationship between chronic renal diseases and regulated genes. The results revealed complex relationships between disease type, gene specificity, and gene regulation type, which led to important insights about the underlying biological pathways. Here we describe an attempt to extend our understanding of these complex relationships by reanalyzing the data using three-dimensional (3D) network layouts, displayed through 2D and 3D viewing methods. Findings The 3D network layout (displayed through the 3D viewing method) revealed that genes implicated in many diseases (non-specific genes) tended to be predominantly down-regulated, whereas genes regulated in a few diseases (disease-specific genes) tended to be up-regulated. This new global relationship was quantitatively validated through comparison to 1000 random permutations of networks of the same size and distribution. Our new finding appeared to be the result of using specific features of the 3D viewing method to analyze the 3D renal network. Conclusions The global relationship between gene regulation and gene specificity is the first clue from human studies that there exist common mechanisms across several renal diseases, which suggest hypotheses for the underlying mechanisms. Furthermore, the study suggests hypotheses for why the 3D visualization helped to make salient a new regularity that was difficult to detect in 2D. Future research that tests these hypotheses should enable a more systematic understanding of when and how to use 3D network visualizations to reveal complex regularities in biological networks. PMID:21070623

Describing the complexity of systems: multivariable "set complexity" and the information basis of systems biology.

PubMed

Galas, David J; Sakhanenko, Nikita A; Skupin, Alexander; Ignac, Tomasz

2014-02-01

Context dependence is central to the description of complexity. Keying on the pairwise definition of "set complexity," we use an information theory approach to formulate general measures of systems complexity. We examine the properties of multivariable dependency starting with the concept of interaction information. We then present a new measure for unbiased detection of multivariable dependency, "differential interaction information." This quantity for two variables reduces to the pairwise "set complexity" previously proposed as a context-dependent measure of information in biological systems. We generalize it here to an arbitrary number of variables. Critical limiting properties of the "differential interaction information" are key to the generalization. This measure extends previous ideas about biological information and provides a more sophisticated basis for the study of complexity. The properties of "differential interaction information" also suggest new approaches to data analysis. Given a data set of system measurements, differential interaction information can provide a measure of collective dependence, which can be represented in hypergraphs describing complex system interaction patterns. We investigate this kind of analysis using simulated data sets. The conjoining of a generalized set complexity measure, multivariable dependency analysis, and hypergraphs is our central result. While our focus is on complex biological systems, our results are applicable to any complex system.

Uncompetitive Inhibition of Yeast Alcohol Dehydrogenase by Diacetoxyscirpenol.

DTIC Science & Technology

1986-10-01

PREFACE The work described in this report was authorized under Project No. 1L161102A71A, Research in Chemical & Biological Defense, Biotechnology . This...Epoxytrichothecenes are the major components of the Fusarium myco- toxins identified as the causative agents for the epidemic outbreak of the alimentary ...The quaternary complex may have the structure such as NAD ~A EtOH ADS 14 LITERATURE CITED 1. Joffe, A.Z. Alimentary Toxic Aleukia. In Microbial Toxins

Analysis of Biophysical, Optical and Genetic Diversity of DoD Coral Reef Communities Using Advanced Fluorescence and Molecular Biology Techniques (Addendum)

DTIC Science & Technology

2011-08-01

light- harvesting antennae, the photochemistry in Photosystem II (PSII), and the photosynthetic electron transport to carbon fixation. Because these...energy transfer within the photosynthetic light- harvesting antennae is compromised under the heavy metal stress, leading to decline in the energy...photosynthetic reactions stimulates accumulation of triplet states in light- harvesting complexes that will be evident from the triplet quenching of

Integrated Post-GWAS Analysis Sheds New Light on the Disease Mechanisms of Schizophrenia

PubMed Central

Lin, Jhih-Rong; Cai, Ying; Zhang, Quanwei; Zhang, Wen; Nogales-Cadenas, Rubén; Zhang, Zhengdong D.

2016-01-01

Schizophrenia is a severe mental disorder with a large genetic component. Recent genome-wide association studies (GWAS) have identified many schizophrenia-associated common variants. For most of the reported associations, however, the underlying biological mechanisms are not clear. The critical first step for their elucidation is to identify the most likely disease genes as the source of the association signals. Here, we describe a general computational framework of post-GWAS analysis for complex disease gene prioritization. We identify 132 putative schizophrenia risk genes in 76 risk regions spanning 120 schizophrenia-associated common variants, 78 of which have not been recognized as schizophrenia disease genes by previous GWAS. Even more significantly, 29 of them are outside the risk regions, likely under regulation of transcriptional regulatory elements contained therein. These putative schizophrenia risk genes are transcriptionally active in both brain and the immune system, and highly enriched among cellular pathways, consistent with leading pathophysiological hypotheses about the pathogenesis of schizophrenia. With their involvement in distinct biological processes, these putative schizophrenia risk genes, with different association strengths, show distinctive temporal expression patterns, and play specific biological roles during brain development. PMID:27754856

Photoinduced catalytic synthesis of biologically important metabolites from formaldehyde and ammonia under plausible "prebiotic" conditions

NASA Astrophysics Data System (ADS)

Delidovich, I. V.; Taran, O. P.; Simonov, A. N.; Matvienko, L. G.; Parmon, V. N.

2011-08-01

The article analyzes new and previously reported data on several catalytic and photochemical processes yielding biologically important molecules. UV-irradiation of formaldehyde aqueous solution yields acetaldehyde, glyoxal, glycolaldehyde and glyceraldehyde, which can serve as precursors of more complex biochemically relevant compounds. Photolysis of aqueous solution of acetaldehyde and ammonium nitrate results in formation of alanine and pyruvic acid. Dehydration of glyceraldehyde catalyzed by zeolite HZSM-5-17 yields pyruvaldehyde. Monosaccharides are formed in the course of the phosphate-catalyzed aldol condensation reactions of glycolaldehyde, glyceraldehyde and formaldehyde. The possibility of the direct synthesis of tetroses, keto- and aldo-pentoses from pure formaldehyde due to the combination of the photochemical production of glycolahyde and phosphate-catalyzed carbohydrate chain growth is demonstrated. Erythrulose and 3-pentulose are the main products of such combined synthesis with selectivity up to 10%. Biologically relevant aldotetroses, aldo- and ketopentoses are more resistant to the photochemical destruction owing to the stabilization in hemiacetal cyclic forms. They are formed as products of isomerization of erythrulose and 3-pentulose. The conjugation of the concerned reactions results in a plausible route to the formation of sugars, amino and organic acids from formaldehyde and ammonia under presumed 'prebiotic' conditions.

Translational applications of evaluating physiologic variability in human endotoxemia

PubMed Central

Scheff, Jeremy D.; Mavroudis, Panteleimon D.; Calvano, Steve E.; Androulakis, Ioannis P.

2012-01-01

Dysregulation of the inflammatory response is a critical component of many clinically challenging disorders such as sepsis. Inflammation is a biological process designed to lead to healing and recovery, ultimately restoring homeostasis; however, the failure to fully achieve those beneficial results can leave a patient in a dangerous persistent inflammatory state. One of the primary challenges in developing novel therapies in this area is that inflammation is comprised of a complex network of interacting pathways. Here, we discuss our approaches towards addressing this problem through computational systems biology, with a particular focus on how the presence of biological rhythms and the disruption of these rhythms in inflammation may be applied in a translational context. By leveraging the information content embedded in physiologic variability, ranging in scale from oscillations in autonomic activity driving short-term heart rate variability (HRV) to circadian rhythms in immunomodulatory hormones, there is significant potential to gain insight into the underlying physiology. PMID:23203205

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

Hartmann, Anja, E-mail: hartmann@ipk-gatersleben.de; Schreiber, Falk; Martin-Luther-University Halle-Wittenberg, Halle

The characterization of biological systems with respect to their behavior and functionality based on versatile biochemical interactions is a major challenge. To understand these complex mechanisms at systems level modeling approaches are investigated. Different modeling formalisms allow metabolic models to be analyzed depending on the question to be solved, the biochemical knowledge and the availability of experimental data. Here, we describe a method for an integrative analysis of the structure and dynamics represented by qualitative and quantitative metabolic models. Using various formalisms, the metabolic model is analyzed from different perspectives. Determined structural and dynamic properties are visualized in the contextmore » of the metabolic model. Interaction techniques allow the exploration and visual analysis thereby leading to a broader understanding of the behavior and functionality of the underlying biological system. The System Biology Metabolic Model Framework (SBM{sup 2} – Framework) implements the developed method and, as an example, is applied for the integrative analysis of the crop plant potato.« less

A systems biology-led insight into the role of the proteome in neurodegenerative diseases.

PubMed

Fasano, Mauro; Monti, Chiara; Alberio, Tiziana

2016-09-01

Multifactorial disorders are the result of nonlinear interactions of several factors; therefore, a reductionist approach does not appear to be appropriate. Proteomics is a global approach that can be efficiently used to investigate pathogenetic mechanisms of neurodegenerative diseases. Here, we report a general introduction about the systems biology approach and mechanistic insights recently obtained by over-representation analysis of proteomics data of cellular and animal models of Alzheimer's disease, Parkinson's disease and other neurodegenerative disorders, as well as of affected human tissues. Expert commentary: As an inductive method, proteomics is based on unbiased observations that further require validation of generated hypotheses. Pathway databases and over-representation analysis tools allow researchers to assign an expectation value to pathogenetic mechanisms linked to neurodegenerative diseases. The systems biology approach based on omics data may be the key to unravel the complex mechanisms underlying neurodegeneration.

Fluorescence dynamics of biological systems using synchrotron radiation

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

Gratton, E.; Mantulin, W.W.; Weber, G.

1996-09-01

A beamline for time-resolved fluorescence spectroscopy of biological systems is under construction at the Synchrotron Radiation Center. The fluorometer, operating in the frequency domain, will take advantage of the time structure of the synchrotron radiation light pulses to determine fluorescence lifetimes. Using frequency-domain techniques, the instrument can achieve an ultimate time resolution on the order of picoseconds. Preliminary experiments have shown that reducing the intensity of one of the fifteen electron bunches in the storage ring allows measurement of harmonic frequencies equivalent to the single-bunch mode. This mode of operation of the synchrotron significantly extends the range of lifetimes thatmore » can be measured. The wavelength range (encompassing the visible and ultraviolet), the range of measurable lifetimes, and the stability and reproducibility of the storage ring pulses should make this beamline a versatile tool for the investigation of the complex fluorescence decay of biological systems. {copyright} {ital 1996 American Institute of Physics.}« less

Tongue and Taste Organ Biology and Function: Homeostasis Maintained by Hedgehog Signaling.

PubMed

Mistretta, Charlotte M; Kumari, Archana

2017-02-10

The tongue is an elaborate complex of heterogeneous tissues with taste organs of diverse embryonic origins. The lingual taste organs are papillae, composed of an epithelium that includes specialized taste buds, the basal lamina, and a lamina propria core with matrix molecules, fibroblasts, nerves, and vessels. Because taste organs are dynamic in cell biology and sensory function, homeostasis requires tight regulation in specific compartments or niches. Recently, the Hedgehog (Hh) pathway has emerged as an essential regulator that maintains lingual taste papillae, taste bud and progenitor cell proliferation and differentiation, and neurophysiological function. Activating or suppressing Hh signaling, with genetic models or pharmacological agents used in cancer treatments, disrupts taste papilla and taste bud integrity and can eliminate responses from taste nerves to chemical stimuli but not to touch or temperature. Understanding Hh regulation of taste organ homeostasis contributes knowledge about the basic biology underlying taste disruptions in patients treated with Hh pathway inhibitors.

Mathematics, structuralism and biology.

PubMed

Saunders, P T

1988-01-01

A new approach is gaining ground in biology, one that has much in common with the structuralist tradition in other fields. It is very much in the spirit of an earlier view of biology and indeed of science in general. It is also, though this is not generally recognized, in the spirit of twentieth century physics. As in modern physics, however, it is not a question of ignoring all the progress that has been made within the former paradigm. On the contrary, the aim is to use it as a basis for setting out in a somewhat different direction. Complex phenomena do not generally lend themselves to reductionist analyses which seek explanation only in terms of detailed mechanisms, but a proper scientific discussion of structure must make full use of what we have already learned - by whatever means - about the processes that underly the phenomena we are trying to understand.

Escalating role of piezosurgery in dental therapeutics.

PubMed

Agarwal, Esha; Masamatti, Sujata Surendra; Kumar, Ashish

2014-10-01

Dentistry, an art in science and tranquilizer in medicine, has seen a lot of changing concepts over a decade and one such novel innovation is piezosurgery. Piezosurgery is a true revolution in bone surgery as it fulfils both biological and technical criteria. It has a variety of applications ranging from minor surgical procedures to complex implantology, plastic and reconstructive surgeries. Piezosurgery uses a low frequency modulated ultrasonic insert which produces microvibrations in the range of 60-200micro meter/sec and leads to safe and precise bony incision without damaging underlying vital structures like nerves, mucosa and vessels. It overcomes technical difficulties such as visibility by producing bloodless field during surgery and removes debris simultaneously through internal irrigation mechanism. The soft tissues remain safe and biological factors like release of certain cytokines promote bone healing and enhance patients recovery. This critical review outweighs piezosurgery over traditional tools and emphasizes on its clinical and biological aspects contributing to beneficial dental health.

Effect of Ocean Acidification on Organic and Inorganic Speciation of Trace Metals.

PubMed

Stockdale, Anthony; Tipping, Edward; Lofts, Stephen; Mortimer, Robert J G

2016-02-16

Rising concentrations of atmospheric carbon dioxide are causing acidification of the oceans. This results in changes to the concentrations of key chemical species such as hydroxide, carbonate and bicarbonate ions. These changes will affect the distribution of different forms of trace metals. Using IPCC data for pCO2 and pH under four future emissions scenarios (to the year 2100) we use a chemical speciation model to predict changes in the distribution of organic and inorganic forms of trace metals. Under a scenario where emissions peak after the year 2100, predicted free ion Al, Fe, Cu, and Pb concentrations increase by factors of up to approximately 21, 2.4, 1.5, and 2.0 respectively. Concentrations of organically complexed metal typically have a lower sensitivity to ocean acidification induced changes. Concentrations of organically complexed Mn, Cu, Zn, and Cd fall by up to 10%, while those of organically complexed Fe, Co, and Ni rise by up to 14%. Although modest, these changes may have significance for the biological availability of metals given the close adaptation of marine microorganisms to their environment.

In Vitro Studies on Space Radiation-Induced Delayed Genetic Responses: Shielding Effects

NASA Technical Reports Server (NTRS)

Kadhim, Munira A.; Green, Lora M.; Gridley, Daila S.; Murray, Deborah K.; Tran, Da Thao; Andres, Melba; Pocock, Debbie; Macdonald, Denise; Goodhead, Dudley T.; Moyers, Michael F.

2003-01-01

Understanding the radiation risks involved in spaceflight is of considerable importance, especially with the long-term occupation of ISS and the planned crewed exploration missions. Several independent causes may contribute to the overall risk to astronauts exposed to the complex space environment, such as exposure to GCR as well as SPES. Protons and high-Z energetic particles comprise the GCR spectrum and may exert considerable biological effects even at low fluence. There are also considerable uncertainties associated with secondary particle effects (e.g. HZE fragments, neutrons etc.). The interaction of protons and high-LET particles with biological materials at all levels of biological organization needs to be investigated fully in order to establish a scientific basis for risk assessment. The results of these types of investigation will foster the development of appropriately directed countermeasures. In this study, we compared the biological responses to proton irradiation presented to the target cells as a monoenergetic beam of particles of complex composition delivered to cells outside or inside a tissue phantom head placed in the United States EVA space suit helmet. Measurements of chromosome aberrations, apoptosis, and the induction of key proteins were made in bone marrow from CBA/CaJ and C57BL/6 mice at early and late times post exposure to radiation at 0, 0.5, 1 and 2 Gy while inside or outside of the helmet. The data showed that proton irradiation induced transmissible chromosomal/genomic instability in haematopoietic stem cells in both strains of mice under both irradiation conditions and especially at low doses. Although differences were noted between the mouse strains in the degree and kinetics of transforming growth factor-beta 1 and tumor necrosis factor-alpha secretion, there were no significant differences observed in the level of the induced instability under either radiation condition, or for both strains of mice. Consequently, when normalized to physical dose, the monoenergetic proton field present inside the helmet-protected phantom produced equivalent biological responses, when compared to unshielded cells, as measured by the induction of delayed genetic effects in murine haematopoietic stem cells.

The trajectory of life. Decreasing physiological network complexity through changing fractal patterns

PubMed Central

Sturmberg, Joachim P.; Bennett, Jeanette M.; Picard, Martin; Seely, Andrew J. E.

2015-01-01

In this position paper, we submit a synthesis of theoretical models based on physiology, non-equilibrium thermodynamics, and non-linear time-series analysis. Based on an understanding of the human organism as a system of interconnected complex adaptive systems, we seek to examine the relationship between health, complexity, variability, and entropy production, as it might be useful to help understand aging, and improve care for patients. We observe the trajectory of life is characterized by the growth, plateauing and subsequent loss of adaptive function of organ systems, associated with loss of functioning and coordination of systems. Understanding development and aging requires the examination of interdependence among these organ systems. Increasing evidence suggests network interconnectedness and complexity can be captured/measured/associated with the degree and complexity of healthy biologic rhythm variability (e.g., heart and respiratory rate variability). We review physiological mechanisms linking the omics, arousal/stress systems, immune function, and mitochondrial bioenergetics; highlighting their interdependence in normal physiological function and aging. We argue that aging, known to be characterized by a loss of variability, is manifested at multiple scales, within functional units at the small scale, and reflected by diagnostic features at the larger scale. While still controversial and under investigation, it appears conceivable that the integrity of whole body complexity may be, at least partially, reflected in the degree and variability of intrinsic biologic rhythms, which we believe are related to overall system complexity that may be a defining feature of health and it's loss through aging. Harnessing this information for the development of therapeutic and preventative strategies may hold an opportunity to significantly improve the health of our patients across the trajectory of life. PMID:26082722

On the holistic approach in cellular and cancer biology: nonlinearity, complexity, and quasi-determinism of the dynamic cellular network.

PubMed

Waliszewski, P; Molski, M; Konarski, J

1998-06-01

A keystone of the molecular reductionist approach to cellular biology is a specific deductive strategy relating genotype to phenotype-two distinct categories. This relationship is based on the assumption that the intermediary cellular network of actively transcribed genes and their regulatory elements is deterministic (i.e., a link between expression of a gene and a phenotypic trait can always be identified, and evolution of the network in time is predetermined). However, experimental data suggest that the relationship between genotype and phenotype is nonbijective (i.e., a gene can contribute to the emergence of more than just one phenotypic trait or a phenotypic trait can be determined by expression of several genes). This implies nonlinearity (i.e., lack of the proportional relationship between input and the outcome), complexity (i.e. emergence of the hierarchical network of multiple cross-interacting elements that is sensitive to initial conditions, possesses multiple equilibria, organizes spontaneously into different morphological patterns, and is controlled in dispersed rather than centralized manner), and quasi-determinism (i.e., coexistence of deterministic and nondeterministic events) of the network. Nonlinearity within the space of the cellular molecular events underlies the existence of a fractal structure within a number of metabolic processes, and patterns of tissue growth, which is measured experimentally as a fractal dimension. Because of its complexity, the same phenotype can be associated with a number of alternative sequences of cellular events. Moreover, the primary cause initiating phenotypic evolution of cells such as malignant transformation can be favored probabilistically, but not identified unequivocally. Thermodynamic fluctuations of energy rather than gene mutations, the material traits of the fluctuations alter both the molecular and informational structure of the network. Then, the interplay between deterministic chaos, complexity, self-organization, and natural selection drives formation of malignant phenotype. This concept offers a novel perspective for investigation of tumorigenesis without invalidating current molecular findings. The essay integrates the ideas of the sciences of complexity in a biological context.

Biological and nonbiological complex drugs for multiple sclerosis in Latin America: regulations and risk management.

PubMed

Carrá, Adriana; Macías Islas, Miguel Angel; Tarulla, Adriana; Bichuetti, Denis Bernardi; Finkelsztejn, Alessandro; Fragoso, Yara Dadalti; Árcega-Revilla, Raul; Cárcamo Rodríguez, Claudia; Durán, Juan Carlos; Bonitto, Juan García; León, Rosalba; Oehninger Gatti, Carlos; Orozco, Geraldine; Vizcarra Escobar, Darwin

2015-06-01

Biological drugs and nonbiological complex drugs with expired patents are followed by biosimilars and follow-on drugs that are supposedly similar and comparable with the reference product in terms of quality, safety and efficacy. Unlike simple molecules that can be copied and reproduced, biosimilars and follow-on complex drugs are heterogeneous and need specific regulations from health and pharmacovigilance agencies. A panel of 14 Latin American experts on multiple sclerosis from nine different countries met to discuss the recommendations regarding biosimilars and follow-on complex drugs for treating multiple sclerosis. Specific measures relating to manufacturing, therapeutic equivalence assessment and pharmacovigilance reports need to be implemented before commercialization. Physical, chemical, biological and immunogenic characterizations of the new product need to be available before clinical trials start. The new product must maintain the same immunogenicity as the original. Automatic substitution of biological and complex drugs poses unacceptable risks to the patient.

A Method for Predicting Protein Complexes from Dynamic Weighted Protein-Protein Interaction Networks.

PubMed

Liu, Lizhen; Sun, Xiaowu; Song, Wei; Du, Chao

2018-06-01

Predicting protein complexes from protein-protein interaction (PPI) network is of great significance to recognize the structure and function of cells. A protein may interact with different proteins under different time or conditions. Existing approaches only utilize static PPI network data that may lose much temporal biological information. First, this article proposed a novel method that combines gene expression data at different time points with traditional static PPI network to construct different dynamic subnetworks. Second, to further filter out the data noise, the semantic similarity based on gene ontology is regarded as the network weight together with the principal component analysis, which is introduced to deal with the weight computing by three traditional methods. Third, after building a dynamic PPI network, a predicting protein complexes algorithm based on "core-attachment" structural feature is applied to detect complexes from each dynamic subnetworks. Finally, it is revealed from the experimental results that our method proposed in this article performs well on detecting protein complexes from dynamic weighted PPI networks.

Discrete Cu(i) complexes for azide–alkyne annulations of small molecules inside mammalian cells† †Electronic supplementary information (ESI) available. See DOI: 10.1039/c7sc04643j

PubMed Central

Miguel-Ávila, Joan; Tomás-Gamasa, María; Olmos, Andrea

2018-01-01

The archetype reaction of “click” chemistry, namely, the copper-promoted azide–alkyne cycloaddition (CuAAC), has found an impressive number of applications in biological chemistry. However, methods for promoting intermolecular annulations of exogenous, small azides and alkynes in the complex interior of mammalian cells, are essentially unknown. Herein we demonstrate that isolated, well-defined copper(i)–tris(triazolyl) complexes featuring designed ligands can readily enter mammalian cells and promote intracellular CuAAC annulations of small, freely diffusible molecules. In addition to simplifying protocols and avoiding the addition of “non-innocent” reductants, the use of these premade copper complexes leads to more efficient processes than with the alternative, in situ made copper species prepared from Cu(ii) sources, tris(triazole) ligands and sodium ascorbate. Under the reaction conditions, the well-defined copper complexes exhibit very good cell penetration properties, and do not present significant toxicities. PMID:29675241

Using an Adoption–Biological Family Design to Examine Associations Between Maternal Trauma, Maternal Depressive Symptoms, and Child Internalizing and Externalizing Behaviors

PubMed Central

Grabow, Aleksandria Perez; Khurana, Atika; Natsuaki, Misaki N.; Neiderhiser, Jenae M.; Harold, Gordon T.; Shaw, Daniel S.; Ganiban, Jody M.; Reiss, David; Leve, Leslie D.

2017-01-01

Maternal trauma is a complex risk factor that has been linked to adverse child outcomes, yet the mechanisms underlying this association are not well understood. This study, which included adoptive and biological families, examined the heritable and environmental mechanisms by which maternal trauma and associated depressive symptoms are linked to child internalizing and externalizing behaviors. Path analyses were used to analyze data from 541 adoptive mother–adopted child (AM–AC) dyads and 126 biological mother–biological child (BM–BC) dyads; the two family types were linked through the same biological mother. Rearing mother’s trauma was associated with child internalizing and externalizing behaviors in AM–AC and BM–BC dyads, and this association was mediated by rearing mothers’ depressive symptoms, with the exception of biological child externalizing behavior, for which biological mother trauma had a direct influence only. Significant associations between maternal trauma and child behavior in dyads that share only environment (i.e., AM–AC dyads) suggest an environmental mechanism of influence for maternal trauma. Significant associations were also observed between maternal depressive symptoms and child internalizing and externalizing behavior in dyads that were only genetically related, with no shared environment (i.e., BM–AC dyads), suggesting a heritable pathway of influence via maternal depressive symptoms. PMID:29162177

Using an adoption-biological family design to examine associations between maternal trauma, maternal depressive symptoms, and child internalizing and externalizing behaviors.

PubMed

Grabow, Aleksandria Perez; Khurana, Atika; Natsuaki, Misaki N; Neiderhiser, Jenae M; Harold, Gordon T; Shaw, Daniel S; Ganiban, Jody M; Reiss, David; Leve, Leslie D

2017-12-01

Maternal trauma is a complex risk factor that has been linked to adverse child outcomes, yet the mechanisms underlying this association are not well understood. This study, which included adoptive and biological families, examined the heritable and environmental mechanisms by which maternal trauma and associated depressive symptoms are linked to child internalizing and externalizing behaviors. Path analyses were used to analyze data from 541 adoptive mother-adopted child (AM-AC) dyads and 126 biological mother-biological child (BM-BC) dyads; the two family types were linked through the same biological mother. Rearing mother's trauma was associated with child internalizing and externalizing behaviors in AM-AC and BM-BC dyads, and this association was mediated by rearing mothers' depressive symptoms, with the exception of biological child externalizing behavior, for which biological mother trauma had a direct influence only. Significant associations between maternal trauma and child behavior in dyads that share only environment (i.e., AM-AC dyads) suggest an environmental mechanism of influence for maternal trauma. Significant associations were also observed between maternal depressive symptoms and child internalizing and externalizing behavior in dyads that were only genetically related, with no shared environment (i.e., BM-AC dyads), suggesting a heritable pathway of influence via maternal depressive symptoms.

Diversified Control Paths: A Significant Way Disease Genes Perturb the Human Regulatory Network

PubMed Central

Wang, Bingbo; Gao, Lin; Zhang, Qingfang; Li, Aimin; Deng, Yue; Guo, Xingli

2015-01-01

Background The complexity of biological systems motivates us to use the underlying networks to provide deep understanding of disease etiology and the human diseases are viewed as perturbations of dynamic properties of networks. Control theory that deals with dynamic systems has been successfully used to capture systems-level knowledge in large amount of quantitative biological interactions. But from the perspective of system control, the ways by which multiple genetic factors jointly perturb a disease phenotype still remain. Results In this work, we combine tools from control theory and network science to address the diversified control paths in complex networks. Then the ways by which the disease genes perturb biological systems are identified and quantified by the control paths in a human regulatory network. Furthermore, as an application, prioritization of candidate genes is presented by use of control path analysis and gene ontology annotation for definition of similarities. We use leave-one-out cross-validation to evaluate the ability of finding the gene-disease relationship. Results have shown compatible performance with previous sophisticated works, especially in directed systems. Conclusions Our results inspire a deeper understanding of molecular mechanisms that drive pathological processes. Diversified control paths offer a basis for integrated intervention techniques which will ultimately lead to the development of novel therapeutic strategies. PMID:26284649

Sequence capture by hybridization to explore modern and ancient genomic diversity in model and nonmodel organisms

PubMed Central

Gasc, Cyrielle; Peyretaillade, Eric

2016-01-01

Abstract The recent expansion of next-generation sequencing has significantly improved biological research. Nevertheless, deep exploration of genomes or metagenomic samples remains difficult because of the sequencing depth and the associated costs required. Therefore, different partitioning strategies have been developed to sequence informative subsets of studied genomes. Among these strategies, hybridization capture has proven to be an innovative and efficient tool for targeting and enriching specific biomarkers in complex DNA mixtures. It has been successfully applied in numerous areas of biology, such as exome resequencing for the identification of mutations underlying Mendelian or complex diseases and cancers, and its usefulness has been demonstrated in the agronomic field through the linking of genetic variants to agricultural phenotypic traits of interest. Moreover, hybridization capture has provided access to underexplored, but relevant fractions of genomes through its ability to enrich defined targets and their flanking regions. Finally, on the basis of restricted genomic information, this method has also allowed the expansion of knowledge of nonreference species and ancient genomes and provided a better understanding of metagenomic samples. In this review, we present the major advances and discoveries permitted by hybridization capture and highlight the potency of this approach in all areas of biology. PMID:27105841

Scale relativity theory and integrative systems biology: 1. Founding principles and scale laws.

PubMed

Auffray, Charles; Nottale, Laurent

2008-05-01

In these two companion papers, we provide an overview and a brief history of the multiple roots, current developments and recent advances of integrative systems biology and identify multiscale integration as its grand challenge. Then we introduce the fundamental principles and the successive steps that have been followed in the construction of the scale relativity theory, and discuss how scale laws of increasing complexity can be used to model and understand the behaviour of complex biological systems. In scale relativity theory, the geometry of space is considered to be continuous but non-differentiable, therefore fractal (i.e., explicitly scale-dependent). One writes the equations of motion in such a space as geodesics equations, under the constraint of the principle of relativity of all scales in nature. To this purpose, covariant derivatives are constructed that implement the various effects of the non-differentiable and fractal geometry. In this first review paper, the scale laws that describe the new dependence on resolutions of physical quantities are obtained as solutions of differential equations acting in the scale space. This leads to several possible levels of description for these laws, from the simplest scale invariant laws to generalized laws with variable fractal dimensions. Initial applications of these laws to the study of species evolution, embryogenesis and cell confinement are discussed.

Sequence capture by hybridization to explore modern and ancient genomic diversity in model and nonmodel organisms.

PubMed

Gasc, Cyrielle; Peyretaillade, Eric; Peyret, Pierre

2016-06-02

The recent expansion of next-generation sequencing has significantly improved biological research. Nevertheless, deep exploration of genomes or metagenomic samples remains difficult because of the sequencing depth and the associated costs required. Therefore, different partitioning strategies have been developed to sequence informative subsets of studied genomes. Among these strategies, hybridization capture has proven to be an innovative and efficient tool for targeting and enriching specific biomarkers in complex DNA mixtures. It has been successfully applied in numerous areas of biology, such as exome resequencing for the identification of mutations underlying Mendelian or complex diseases and cancers, and its usefulness has been demonstrated in the agronomic field through the linking of genetic variants to agricultural phenotypic traits of interest. Moreover, hybridization capture has provided access to underexplored, but relevant fractions of genomes through its ability to enrich defined targets and their flanking regions. Finally, on the basis of restricted genomic information, this method has also allowed the expansion of knowledge of nonreference species and ancient genomes and provided a better understanding of metagenomic samples. In this review, we present the major advances and discoveries permitted by hybridization capture and highlight the potency of this approach in all areas of biology. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

A morphospace for synthetic organs and organoids: the possible and the actual.

PubMed

Ollé-Vila, Aina; Duran-Nebreda, Salva; Conde-Pueyo, Núria; Montañez, Raúl; Solé, Ricard

2016-04-18

Efforts in evolutionary developmental biology have shed light on how organs are developed and why evolution has selected some structures instead of others. These advances in the understanding of organogenesis along with the most recent techniques of organotypic cultures, tissue bioprinting and synthetic biology provide the tools to hack the physical and genetic constraints in organ development, thus opening new avenues for research in the form of completely designed or merely altered settings. Here we propose a unifying framework that connects the concept of morphospace (i.e. the space of possible structures) with synthetic biology and tissue engineering. We aim for a synthesis that incorporates our understanding of both evolutionary and architectural constraints and can be used as a guide for exploring alternative design principles to build artificial organs and organoids. We present a three-dimensional morphospace incorporating three key features associated to organ and organoid complexity. The axes of this space include the degree of complexity introduced by developmental mechanisms required to build the structure, its potential to store and react to information and the underlying physical state. We suggest that a large fraction of this space is empty, and that the void might offer clues for alternative ways of designing and even inventing new organs.

The physical and biological basis of quantitative parameters derived from diffusion MRI

PubMed Central

2012-01-01

Diffusion magnetic resonance imaging is a quantitative imaging technique that measures the underlying molecular diffusion of protons. Diffusion-weighted imaging (DWI) quantifies the apparent diffusion coefficient (ADC) which was first used to detect early ischemic stroke. However this does not take account of the directional dependence of diffusion seen in biological systems (anisotropy). Diffusion tensor imaging (DTI) provides a mathematical model of diffusion anisotropy and is widely used. Parameters, including fractional anisotropy (FA), mean diffusivity (MD), parallel and perpendicular diffusivity can be derived to provide sensitive, but non-specific, measures of altered tissue structure. They are typically assessed in clinical studies by voxel-based or region-of-interest based analyses. The increasing recognition of the limitations of the diffusion tensor model has led to more complex multi-compartment models such as CHARMED, AxCaliber or NODDI being developed to estimate microstructural parameters including axonal diameter, axonal density and fiber orientations. However these are not yet in routine clinical use due to lengthy acquisition times. In this review, I discuss how molecular diffusion may be measured using diffusion MRI, the biological and physical bases for the parameters derived from DWI and DTI, how these are used in clinical studies and the prospect of more complex tissue models providing helpful micro-structural information. PMID:23289085

A theory for protein dynamics: Global anisotropy and a normal mode approach to local complexity

NASA Astrophysics Data System (ADS)

Copperman, Jeremy; Romano, Pablo; Guenza, Marina

2014-03-01

We propose a novel Langevin equation description for the dynamics of biological macromolecules by projecting the solvent and all atomic degrees of freedom onto a set of coarse-grained sites at the single residue level. We utilize a multi-scale approach where molecular dynamic simulations are performed to obtain equilibrium structural correlations input to a modified Rouse-Zimm description which can be solved analytically. The normal mode solution provides a minimal basis set to account for important properties of biological polymers such as the anisotropic global structure, and internal motion on a complex free-energy surface. This multi-scale modeling method predicts the dynamics of both global rotational diffusion and constrained internal motion from the picosecond to the nanosecond regime, and is quantitative when compared to both simulation trajectory and NMR relaxation times. Utilizing non-equilibrium sampling techniques and an explicit treatment of the free-energy barriers in the mode coordinates, the model is extended to include biologically important fluctuations in the microsecond regime, such as bubble and fork formation in nucleic acids, and protein domain motion. This work supported by the NSF under the Graduate STEM Fellows in K-12 Education (GK-12) program, grant DGE-0742540 and NSF grant DMR-0804145, computational support from XSEDE and ACISS.

Use of Graph Database for the Integration of Heterogeneous Biological Data.

PubMed

Yoon, Byoung-Ha; Kim, Seon-Kyu; Kim, Seon-Young

2017-03-01

Understanding complex relationships among heterogeneous biological data is one of the fundamental goals in biology. In most cases, diverse biological data are stored in relational databases, such as MySQL and Oracle, which store data in multiple tables and then infer relationships by multiple-join statements. Recently, a new type of database, called the graph-based database, was developed to natively represent various kinds of complex relationships, and it is widely used among computer science communities and IT industries. Here, we demonstrate the feasibility of using a graph-based database for complex biological relationships by comparing the performance between MySQL and Neo4j, one of the most widely used graph databases. We collected various biological data (protein-protein interaction, drug-target, gene-disease, etc.) from several existing sources, removed duplicate and redundant data, and finally constructed a graph database containing 114,550 nodes and 82,674,321 relationships. When we tested the query execution performance of MySQL versus Neo4j, we found that Neo4j outperformed MySQL in all cases. While Neo4j exhibited a very fast response for various queries, MySQL exhibited latent or unfinished responses for complex queries with multiple-join statements. These results show that using graph-based databases, such as Neo4j, is an efficient way to store complex biological relationships. Moreover, querying a graph database in diverse ways has the potential to reveal novel relationships among heterogeneous biological data.

Use of Graph Database for the Integration of Heterogeneous Biological Data

PubMed Central

Yoon, Byoung-Ha; Kim, Seon-Kyu

2017-01-01

Understanding complex relationships among heterogeneous biological data is one of the fundamental goals in biology. In most cases, diverse biological data are stored in relational databases, such as MySQL and Oracle, which store data in multiple tables and then infer relationships by multiple-join statements. Recently, a new type of database, called the graph-based database, was developed to natively represent various kinds of complex relationships, and it is widely used among computer science communities and IT industries. Here, we demonstrate the feasibility of using a graph-based database for complex biological relationships by comparing the performance between MySQL and Neo4j, one of the most widely used graph databases. We collected various biological data (protein-protein interaction, drug-target, gene-disease, etc.) from several existing sources, removed duplicate and redundant data, and finally constructed a graph database containing 114,550 nodes and 82,674,321 relationships. When we tested the query execution performance of MySQL versus Neo4j, we found that Neo4j outperformed MySQL in all cases. While Neo4j exhibited a very fast response for various queries, MySQL exhibited latent or unfinished responses for complex queries with multiple-join statements. These results show that using graph-based databases, such as Neo4j, is an efficient way to store complex biological relationships. Moreover, querying a graph database in diverse ways has the potential to reveal novel relationships among heterogeneous biological data. PMID:28416946

CytoCluster: A Cytoscape Plugin for Cluster Analysis and Visualization of Biological Networks.

PubMed

Li, Min; Li, Dongyan; Tang, Yu; Wu, Fangxiang; Wang, Jianxin

2017-08-31

Nowadays, cluster analysis of biological networks has become one of the most important approaches to identifying functional modules as well as predicting protein complexes and network biomarkers. Furthermore, the visualization of clustering results is crucial to display the structure of biological networks. Here we present CytoCluster, a cytoscape plugin integrating six clustering algorithms, HC-PIN (Hierarchical Clustering algorithm in Protein Interaction Networks), OH-PIN (identifying Overlapping and Hierarchical modules in Protein Interaction Networks), IPCA (Identifying Protein Complex Algorithm), ClusterONE (Clustering with Overlapping Neighborhood Expansion), DCU (Detecting Complexes based on Uncertain graph model), IPC-MCE (Identifying Protein Complexes based on Maximal Complex Extension), and BinGO (the Biological networks Gene Ontology) function. Users can select different clustering algorithms according to their requirements. The main function of these six clustering algorithms is to detect protein complexes or functional modules. In addition, BinGO is used to determine which Gene Ontology (GO) categories are statistically overrepresented in a set of genes or a subgraph of a biological network. CytoCluster can be easily expanded, so that more clustering algorithms and functions can be added to this plugin. Since it was created in July 2013, CytoCluster has been downloaded more than 9700 times in the Cytoscape App store and has already been applied to the analysis of different biological networks. CytoCluster is available from http://apps.cytoscape.org/apps/cytocluster.

CytoCluster: A Cytoscape Plugin for Cluster Analysis and Visualization of Biological Networks

PubMed Central

Li, Min; Li, Dongyan; Tang, Yu; Wang, Jianxin

2017-01-01

Nowadays, cluster analysis of biological networks has become one of the most important approaches to identifying functional modules as well as predicting protein complexes and network biomarkers. Furthermore, the visualization of clustering results is crucial to display the structure of biological networks. Here we present CytoCluster, a cytoscape plugin integrating six clustering algorithms, HC-PIN (Hierarchical Clustering algorithm in Protein Interaction Networks), OH-PIN (identifying Overlapping and Hierarchical modules in Protein Interaction Networks), IPCA (Identifying Protein Complex Algorithm), ClusterONE (Clustering with Overlapping Neighborhood Expansion), DCU (Detecting Complexes based on Uncertain graph model), IPC-MCE (Identifying Protein Complexes based on Maximal Complex Extension), and BinGO (the Biological networks Gene Ontology) function. Users can select different clustering algorithms according to their requirements. The main function of these six clustering algorithms is to detect protein complexes or functional modules. In addition, BinGO is used to determine which Gene Ontology (GO) categories are statistically overrepresented in a set of genes or a subgraph of a biological network. CytoCluster can be easily expanded, so that more clustering algorithms and functions can be added to this plugin. Since it was created in July 2013, CytoCluster has been downloaded more than 9700 times in the Cytoscape App store and has already been applied to the analysis of different biological networks. CytoCluster is available from http://apps.cytoscape.org/apps/cytocluster. PMID:28858211

Multiple complexes of nitrogen assimilatory enzymes in spinach chloroplasts: possible mechanisms for the regulation of enzyme function.

PubMed

Kimata-Ariga, Yoko; Hase, Toshiharu

2014-01-01

Assimilation of nitrogen is an essential biological process for plant growth and productivity. Here we show that three chloroplast enzymes involved in nitrogen assimilation, glutamate synthase (GOGAT), nitrite reductase (NiR) and glutamine synthetase (GS), separately assemble into distinct protein complexes in spinach chloroplasts, as analyzed by western blots under blue native electrophoresis (BN-PAGE). GOGAT and NiR were present not only as monomers, but also as novel complexes with a discrete size (730 kDa) and multiple sizes (>120 kDa), respectively, in the stromal fraction of chloroplasts. These complexes showed the same mobility as each monomer on two-dimensional (2D) SDS-PAGE after BN-PAGE. The 730 kDa complex containing GOGAT dissociated into monomers, and multiple complexes of NiR reversibly converted into monomers, in response to the changes in the pH of the stromal solvent. On the other hand, the bands detected by anti-GS antibody were present not only in stroma as a conventional decameric holoenzyme complex of 420 kDa, but also in thylakoids as a novel complex of 560 kDa. The polypeptide in the 560 kDa complex showed slower mobility than that of the 420 kDa complex on the 2D SDS-PAGE, implying the assembly of distinct GS isoforms or a post-translational modification of the same GS protein. The function of these multiple complexes was evaluated by in-gel GS activity under native conditions and by the binding ability of NiR and GOGAT with their physiological electron donor, ferredoxin. The results indicate that these multiplicities in size and localization of the three nitrogen assimilatory enzymes may be involved in the physiological regulation of their enzyme function, in a similar way as recently described cases of carbon assimilatory enzymes.

Synthetic biology: insights into biological computation.

PubMed

Manzoni, Romilde; Urrios, Arturo; Velazquez-Garcia, Silvia; de Nadal, Eulàlia; Posas, Francesc

2016-04-18

Organisms have evolved a broad array of complex signaling mechanisms that allow them to survive in a wide range of environmental conditions. They are able to sense external inputs and produce an output response by computing the information. Synthetic biology attempts to rationally engineer biological systems in order to perform desired functions. Our increasing understanding of biological systems guides this rational design, while the huge background in electronics for building circuits defines the methodology. In this context, biocomputation is the branch of synthetic biology aimed at implementing artificial computational devices using engineered biological motifs as building blocks. Biocomputational devices are defined as biological systems that are able to integrate inputs and return outputs following pre-determined rules. Over the last decade the number of available synthetic engineered devices has increased exponentially; simple and complex circuits have been built in bacteria, yeast and mammalian cells. These devices can manage and store information, take decisions based on past and present inputs, and even convert a transient signal into a sustained response. The field is experiencing a fast growth and every day it is easier to implement more complex biological functions. This is mainly due to advances in in vitro DNA synthesis, new genome editing tools, novel molecular cloning techniques, continuously growing part libraries as well as other technological advances. This allows that digital computation can now be engineered and implemented in biological systems. Simple logic gates can be implemented and connected to perform novel desired functions or to better understand and redesign biological processes. Synthetic biological digital circuits could lead to new therapeutic approaches, as well as new and efficient ways to produce complex molecules such as antibiotics, bioplastics or biofuels. Biological computation not only provides possible biomedical and biotechnological applications, but also affords a greater understanding of biological systems.

Characterizing informative sequence descriptors and predicting binding affinities of heterodimeric protein complexes.

PubMed

Srinivasulu, Yerukala Sathipati; Wang, Jyun-Rong; Hsu, Kai-Ti; Tsai, Ming-Ju; Charoenkwan, Phasit; Huang, Wen-Lin; Huang, Hui-Ling; Ho, Shinn-Ying

2015-01-01

Protein-protein interactions (PPIs) are involved in various biological processes, and underlying mechanism of the interactions plays a crucial role in therapeutics and protein engineering. Most machine learning approaches have been developed for predicting the binding affinity of protein-protein complexes based on structure and functional information. This work aims to predict the binding affinity of heterodimeric protein complexes from sequences only. This work proposes a support vector machine (SVM) based binding affinity classifier, called SVM-BAC, to classify heterodimeric protein complexes based on the prediction of their binding affinity. SVM-BAC identified 14 of 580 sequence descriptors (physicochemical, energetic and conformational properties of the 20 amino acids) to classify 216 heterodimeric protein complexes into low and high binding affinity. SVM-BAC yielded the training accuracy, sensitivity, specificity, AUC and test accuracy of 85.80%, 0.89, 0.83, 0.86 and 83.33%, respectively, better than existing machine learning algorithms. The 14 features and support vector regression were further used to estimate the binding affinities (Pkd) of 200 heterodimeric protein complexes. Prediction performance of a Jackknife test was the correlation coefficient of 0.34 and mean absolute error of 1.4. We further analyze three informative physicochemical properties according to their contribution to prediction performance. Results reveal that the following properties are effective in predicting the binding affinity of heterodimeric protein complexes: apparent partition energy based on buried molar fractions, relations between chemical structure and biological activity in principal component analysis IV, and normalized frequency of beta turn. The proposed sequence-based prediction method SVM-BAC uses an optimal feature selection method to identify 14 informative features to classify and predict binding affinity of heterodimeric protein complexes. The characterization analysis revealed that the average numbers of beta turns and hydrogen bonds at protein-protein interfaces in high binding affinity complexes are more than those in low binding affinity complexes.

Characterizing informative sequence descriptors and predicting binding affinities of heterodimeric protein complexes

PubMed Central

2015-01-01

Background Protein-protein interactions (PPIs) are involved in various biological processes, and underlying mechanism of the interactions plays a crucial role in therapeutics and protein engineering. Most machine learning approaches have been developed for predicting the binding affinity of protein-protein complexes based on structure and functional information. This work aims to predict the binding affinity of heterodimeric protein complexes from sequences only. Results This work proposes a support vector machine (SVM) based binding affinity classifier, called SVM-BAC, to classify heterodimeric protein complexes based on the prediction of their binding affinity. SVM-BAC identified 14 of 580 sequence descriptors (physicochemical, energetic and conformational properties of the 20 amino acids) to classify 216 heterodimeric protein complexes into low and high binding affinity. SVM-BAC yielded the training accuracy, sensitivity, specificity, AUC and test accuracy of 85.80%, 0.89, 0.83, 0.86 and 83.33%, respectively, better than existing machine learning algorithms. The 14 features and support vector regression were further used to estimate the binding affinities (Pkd) of 200 heterodimeric protein complexes. Prediction performance of a Jackknife test was the correlation coefficient of 0.34 and mean absolute error of 1.4. We further analyze three informative physicochemical properties according to their contribution to prediction performance. Results reveal that the following properties are effective in predicting the binding affinity of heterodimeric protein complexes: apparent partition energy based on buried molar fractions, relations between chemical structure and biological activity in principal component analysis IV, and normalized frequency of beta turn. Conclusions The proposed sequence-based prediction method SVM-BAC uses an optimal feature selection method to identify 14 informative features to classify and predict binding affinity of heterodimeric protein complexes. The characterization analysis revealed that the average numbers of beta turns and hydrogen bonds at protein-protein interfaces in high binding affinity complexes are more than those in low binding affinity complexes. PMID:26681483

Modular and Orthogonal Synthesis of Hybrid Polymers and Networks

PubMed Central

Liu, Shuang; Dicker, Kevin T.; Jia, Xinqiao

2015-01-01

Biomaterials scientists strive to develop polymeric materials with distinct chemical make-up, complex molecular architectures, robust mechanical properties and defined biological functions by drawing inspirations from biological systems. Salient features of biological designs include (1) repetitive presentation of basic motifs; and (2) efficient integration of diverse building blocks. Thus, an appealing approach to biomaterials synthesis is to combine synthetic and natural building blocks in a modular fashion employing novel chemical methods. Over the past decade, orthogonal chemistries have become powerful enabling tools for the modular synthesis of advanced biomaterials. These reactions require building blocks with complementary functionalities, occur under mild conditions in the presence of biological molecules and living cells and proceed with high yield and exceptional selectivity. These chemistries have facilitated the construction of complex polymers and networks in a step-growth fashion, allowing facile modulation of materials properties by simple variations of the building blocks. In this review, we first summarize features of several types of orthogonal chemistries. We then discuss recent progress in the synthesis of step growth linear polymers, dendrimers and networks that find application in drug delivery, 3D cell culture and tissue engineering. Overall, orthogonal reactions and modulular synthesis have not only minimized the steps needed for the desired chemical transformations but also maximized the diversity and functionality of the final products. The modular nature of the design, combined with the potential synergistic effect of the hybrid system, will likely result in novel hydrogel matrices with robust structures and defined functions. PMID:25572255

The Fur-Iron Complex Modulates Expression of the Quorum-Sensing Master Regulator, SmcR, To Control Expression of Virulence Factors in Vibrio vulnificus

PubMed Central

Kim, In Hwang; Wen, Yancheng; Son, Jee-Soo; Lee, Kyu-Ho

2013-01-01

The gene vvpE, encoding the virulence factor elastase, is a member of the quorum-sensing regulon in Vibrio vulnificus and displays enhanced expression at high cell density. We observed that this gene was repressed under iron-rich conditions and that the repression was due to a Fur (ferric uptake regulator)-dependent repression of smcR, a gene encoding a quorum-sensing master regulator with similarity to luxR in Vibrio harveyi. A gel mobility shift assay and a footprinting experiment demonstrated that the Fur-iron complex binds directly to two regions upstream of smcR (−82 to −36 and −2 to +27, with respect to the transcription start site) with differing affinities. However, binding of the Fur-iron complex is reversible enough to allow expression of smcR to be induced by quorum sensing at high cell density under iron-rich conditions. Under iron-limiting conditions, Fur fails to bind either region and the expression of smcR is regulated solely by quorum sensing. These results suggest that two biologically important environmental signals, iron and quorum sensing, converge to direct the expression of smcR, which then coordinates the expression of virulence factors. PMID:23716618

InFlo: a novel systems biology framework identifies cAMP-CREB1 axis as a key modulator of platinum resistance in ovarian cancer.

PubMed

Dimitrova, N; Nagaraj, A B; Razi, A; Singh, S; Kamalakaran, S; Banerjee, N; Joseph, P; Mankovich, A; Mittal, P; DiFeo, A; Varadan, V

2017-04-27

Characterizing the complex interplay of cellular processes in cancer would enable the discovery of key mechanisms underlying its development and progression. Published approaches to decipher driver mechanisms do not explicitly model tissue-specific changes in pathway networks and the regulatory disruptions related to genomic aberrations in cancers. We therefore developed InFlo, a novel systems biology approach for characterizing complex biological processes using a unique multidimensional framework integrating transcriptomic, genomic and/or epigenomic profiles for any given cancer sample. We show that InFlo robustly characterizes tissue-specific differences in activities of signalling networks on a genome scale using unique probabilistic models of molecular interactions on a per-sample basis. Using large-scale multi-omics cancer datasets, we show that InFlo exhibits higher sensitivity and specificity in detecting pathway networks associated with specific disease states when compared to published pathway network modelling approaches. Furthermore, InFlo's ability to infer the activity of unmeasured signalling network components was also validated using orthogonal gene expression signatures. We then evaluated multi-omics profiles of primary high-grade serous ovarian cancer tumours (N=357) to delineate mechanisms underlying resistance to frontline platinum-based chemotherapy. InFlo was the only algorithm to identify hyperactivation of the cAMP-CREB1 axis as a key mechanism associated with resistance to platinum-based therapy, a finding that we subsequently experimentally validated. We confirmed that inhibition of CREB1 phosphorylation potently sensitized resistant cells to platinum therapy and was effective in killing ovarian cancer stem cells that contribute to both platinum-resistance and tumour recurrence. Thus, we propose InFlo to be a scalable and widely applicable and robust integrative network modelling framework for the discovery of evidence-based biomarkers and therapeutic targets.

Ecosystem and immune systems: Hierarchial response provides resilience against invasions

USGS Publications Warehouse

Allen, Craig R.

2001-01-01

Janssen (2001) provides the stimulus for thoughtful comparison and consideration of the ranges of responses exhibited by immune systems and ecological systems in the face of perturbations such as biological invasions. It may indeed be informative to consider the similarities of the responses to invasions exhibited by immune systems and ecological systems. Clearly, both types of systems share a general organizational structure with all other complex hierarchical systems. Their organization provides these systems with resilience. However, when describing the response of ecological-economic systems to invasions, Janssen emphasizes the human-economic response. I would like to expand on his comparison by focusing on how resilience is maintained in complex systems under the threat of invasion.

The hydroxyl functionality and a rigid proximal N are required for forming a novel non-covalent quinine-heme complex.

PubMed

Alumasa, John N; Gorka, Alexander P; Casabianca, Leah B; Comstock, Erica; de Dios, Angel C; Roepe, Paul D

2011-03-01

Quinoline antimalarial drugs bind both monomeric and dimeric forms of free heme, with distinct preferences depending on the chemical environment. Under biological conditions, chloroquine (CQ) appears to prefer to bind to μ-oxo dimeric heme, while quinine (QN) preferentially binds monomer. To further explore this important distinction, we study three newly synthesized and several commercially available QN analogues lacking various functional groups. We find that removal of the QN hydroxyl lowers heme affinity, hemozoin (Hz) inhibition efficiency, and antiplasmodial activity. Elimination of the rigid quinuclidyl ring has similar effects, but elimination of either the vinyl or methoxy group does not. Replacing the quinuclidyl N with a less rigid tertiary aliphatic N only partially restores activity. To further study these trends, we probe drug-heme interactions via NMR studies with both Fe and Zn protoporphyrin IX (FPIX, ZnPIX) for QN, dehydroxyQN (DHQN), dequinuclidylQN (DQQN), and deamino-dequinuclidylQN (DADQQN). Magnetic susceptibility measurements in the presence of FPIX demonstrate that these compounds differentially perturb FPIX monomer-dimer equilibrium. We also isolate the QN-FPIX complex formed under mild aqueous conditions and analyze it by mass spectrometry, as well as fluorescence, vibrational, and solid-state NMR spectroscopies. The data elucidate key features of QN pharmacology and allow us to propose a refined model for the preferred binding of QN to monomeric FPIX under biologically relevant conditions. With this model in hand, we also propose how QN, CQ, and amodiaquine (AQ) differ in their ability to inhibit Hz formation. Copyright © 2010 Elsevier Inc. All rights reserved.

ICGC PedBrain: Dissecting the genomic complexity underlying medulloblastoma

PubMed Central

Jones, David TW; Jäger, Natalie; Kool, Marcel; Zichner, Thomas; Hutter, Barbara; Sultan, Marc; Cho, Yoon-Jae; Pugh, Trevor J; Hovestadt, Volker; Stütz, Adrian M; Rausch, Tobias; Warnatz, Hans-Jörg; Ryzhova, Marina; Bender, Sebastian; Sturm, Dominik; Pleier, Sabrina; Cin, Huriye; Pfaff, Elke; Sieber, Laura; Wittmann, Andrea; Remke, Marc; Witt, Hendrik; Hutter, Sonja; Tzaridis, Theophilos; Weischenfeldt, Joachim; Raeder, Benjamin; Avci, Meryem; Amstislavskiy, Vyacheslav; Zapatka, Marc; Weber, Ursula D; Wang, Qi; Lasitschka, Bärbel; Bartholomae, Cynthia C; Schmidt, Manfred; von Kalle, Christof; Ast, Volker; Lawerenz, Chris; Eils, Jürgen; Kabbe, Rolf; Benes, Vladimir; van Sluis, Peter; Koster, Jan; Volckmann, Richard; Shih, David; Betts, Matthew J; Russell, Robert B; Coco, Simona; Tonini, Gian Paolo; Schüller, Ulrich; Hans, Volkmar; Graf, Norbert; Kim, Yoo-Jin; Monoranu, Camelia; Roggendorf, Wolfgang; Unterberg, Andreas; Herold-Mende, Christel; Milde, Till; Kulozik, Andreas E; von Deimling, Andreas; Witt, Olaf; Maass, Eberhard; Rössler, Jochen; Ebinger, Martin; Schuhmann, Martin U; Frühwald, Michael C; Hasselblatt, Martin; Jabado, Nada; Rutkowski, Stefan; von Bueren, André O; Williamson, Dan; Clifford, Steven C; McCabe, Martin G; Collins, V. Peter; Wolf, Stephan; Wiemann, Stefan; Lehrach, Hans; Brors, Benedikt; Scheurlen, Wolfram; Felsberg, Jörg; Reifenberger, Guido; Northcott, Paul A; Taylor, Michael D; Meyerson, Matthew; Pomeroy, Scott L; Yaspo, Marie-Laure; Korbel, Jan O; Korshunov, Andrey; Eils, Roland; Pfister, Stefan M; Lichter, Peter

2013-01-01

Summary Medulloblastoma is an aggressively-growing tumour, arising in the cerebellum or medulla/brain stem. It is the most common malignant brain tumour in children, and displays tremendous biological and clinical heterogeneity1. Despite recent treatment advances, approximately 40% of children experience tumour recurrence, and 30% will die from their disease. Those who survive often have a significantly reduced quality of life. Four tumour subgroups with distinct clinical, biological and genetic profiles are currently discriminated2,3. WNT tumours, displaying activated wingless pathway signalling, carry a favourable prognosis under current treatment regimens4. SHH tumours show hedgehog pathway activation, and have an intermediate prognosis2. Group 3 & 4 tumours are molecularly less well-characterised, and also present the greatest clinical challenges2,3,5. The full repertoire of genetic events driving this distinction, however, remains unclear. Here we describe an integrative deep-sequencing analysis of 125 tumour-normal pairs. Tetraploidy was identified as a frequent early event in Group 3 & 4 tumours, and a positive correlation between patient age and mutation rate was observed. Several recurrent mutations were identified, both in known medulloblastoma-related genes (CTNNB1, PTCH1, MLL2, SMARCA4) and in genes not previously linked to this tumour (DDX3X, CTDNEP1, KDM6A, TBR1), often in subgroup-specific patterns. RNA-sequencing confirmed these alterations, and revealed the expression of the first medulloblastoma fusion genes. Chromatin modifiers were frequently altered across all subgroups. These findings enhance our understanding of the genomic complexity and heterogeneity underlying medulloblastoma, and provide several potential targets for new therapeutics, especially for Group 3 & 4 patients. PMID:22832583

Detection and characterization of gene-gene and gene-environment interactions in common human diseases and complex clinical endpoints

EPA Science Inventory

Biological organisms are complex systems that dynamically integrate inputs from a multitude of physiological and environmental factors. Therefore, in addressing questions concerning the etiology of complex health outcomes, it is essential that the systemic nature of biology be ta...

Using Simple Manipulatives to Improve Student Comprehension of a Complex Biological Process: Protein Synthesis

ERIC Educational Resources Information Center

Guzman, Karen; Bartlett, John

2012-01-01

Biological systems and living processes involve a complex interplay of biochemicals and macromolecular structures that can be challenging for undergraduate students to comprehend and, thus, misconceptions abound. Protein synthesis, or translation, is an example of a biological process for which students often hold many misconceptions. This article…

Effects of model structural uncertainty on carbon cycle projections: biological nitrogen fixation as a case study

NASA Astrophysics Data System (ADS)

Wieder, William R.; Cleveland, Cory C.; Lawrence, David M.; Bonan, Gordon B.

2015-04-01

Uncertainties in terrestrial carbon (C) cycle projections increase uncertainty of potential climate feedbacks. Efforts to improve model performance often include increased representation of biogeochemical processes, such as coupled carbon-nitrogen (N) cycles. In doing so, models are becoming more complex, generating structural uncertainties in model form that reflect incomplete knowledge of how to represent underlying processes. Here, we explore structural uncertainties associated with biological nitrogen fixation (BNF) and quantify their effects on C cycle projections. We find that alternative plausible structures to represent BNF result in nearly equivalent terrestrial C fluxes and pools through the twentieth century, but the strength of the terrestrial C sink varies by nearly a third (50 Pg C) by the end of the twenty-first century under a business-as-usual climate change scenario representative concentration pathway 8.5. These results indicate that actual uncertainty in future C cycle projections may be larger than previously estimated, and this uncertainty will limit C cycle projections until model structures can be evaluated and refined.

Combined LIBS-Raman for remote detection and characterization of biological samples

DOE PAGES

Anderson, Aaron S.; Mukundan, Harshini; Mcinroy, Rhonda E.; ...

2015-02-07

Laser-Induced Breakdown Spectroscopy (LIBS) and Raman Spectroscopy have rich histories in the analysis of a wide variety of samples in both in situ and remote configurations. Our team is working on building a deployable, integrated Raman and LIBS spectrometer (RLS) for the parallel elucidation of elemental and molecular signatures under Earth and Martian surface conditions. Herein, results from remote LIBS and Raman analysis of biological samples such as amino acids, small peptides, mono- and disaccharides, and nucleic acids acquired under terrestrial and Mars conditions are reported, giving rise to some interesting differences. A library of spectra and peaks of interestmore » were compiled, and will be used to inform the analysis of more complex systems, such as large peptides, dried bacterial spores, and biofilms. Lastly, these results will be presented and future applications will be discussed, including the assembly of a combined RLS spectroscopic system and stand-off detection in a variety of environments.« less

Computational Modeling of Aerosol Hazard Arising from the Opening of an Anthrax Letter in an Open-Office Complex

NASA Astrophysics Data System (ADS)

Lien, F. S.; Ji, H.; Yee, E.

Early experimental work, conducted at Defence R&D Canada — Suffield, measured and characterized the personal and environmental contamination associated with the simulated opening of anthrax-tainted letters under a number of different scenarios. A better understanding of the physical and biological processes is considerably significant for detecting, assessing, and formulating potential mitigation strategies for managing these risks. These preliminary experimental investigations have been extended to simulate the contamination from the opening of anthrax-tainted letters in an Open-Office environment using Computational Fluid Dynamics (CFD). Bacillus globigii (BG) was used as a biological simulant for anthrax, with 0.1 gram of the simulant released from opened letters in the experiments conducted. The accuracy of the model for prediction of the spatial distribution of BG spores in the office is first assessed quantitatively by comparison with measured SF6 concentrations (the baseline experiment), and then qualitatively by comparison with measured BG concentrations obtained under a number of scenarios, some involving people moving within various offices.

7th Annual Systems Biology Symposium: Systems Biology and Engineering

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

Galitski, Timothy P.

2008-04-01

Systems biology recognizes the complex multi-scale organization of biological systems, from molecules to ecosystems. The International Symposium on Systems Biology has been hosted by the Institute for Systems Biology in Seattle, Washington, since 2002. The annual two-day event gathers the most influential researchers transforming biology into an integrative discipline investingating complex systems. Engineering and application of new technology is a central element of systems biology. Genome-scale, or very small-scale, biological questions drive the enigneering of new technologies, which enable new modes of experimentation and computational analysis, leading to new biological insights and questions. Concepts and analytical methods in engineering aremore » now finding direct applications in biology. Therefore, the 2008 Symposium, funded in partnership with the Department of Energy, featured global leaders in "Systems Biology and Engineering."« less

Linking Microbiota to Human Diseases: A Systems Biology Perspective.

PubMed

Wu, Hao; Tremaroli, Valentina; Bäckhed, Fredrik

2015-12-01

The human gut microbiota encompasses a densely populated ecosystem that provides essential functions for host development, immune maturation, and metabolism. Alterations to the gut microbiota have been observed in numerous diseases, including human metabolic diseases such as obesity, type 2 diabetes (T2D), and irritable bowel syndrome, and some animal experiments have suggested causality. However, few studies have validated causality in humans and the underlying mechanisms remain largely to be elucidated. We discuss how systems biology approaches combined with new experimental technologies may disentangle some of the mechanistic details in the complex interactions of diet, microbiota, and host metabolism and may provide testable hypotheses for advancing our current understanding of human-microbiota interaction. Copyright © 2015 Elsevier Ltd. All rights reserved.

A Neurogenetic Approach to Impulsivity

PubMed Central

Congdon, Eliza; Canli, Turhan

2008-01-01

Impulsivity is a complex and multidimensional trait that is of interest to both personality psychologists and to clinicians. For investigators seeking the biological basis of personality traits, the use of neuroimaging techniques such as positron emission tomography (PET) and functional magnetic resonance imaging (fMRI) revolutionized personality psychology in less than a decade. Now, another revolution is under way, and it originates from molecular biology. Specifically, new findings in molecular genetics, the detailed mapping and the study of the function of genes, have shown that individual differences in personality traits can be related to individual differences within specific genes. In this article, we will review the current state of the field with respect to the neural and genetic basis of trait impulsivity. PMID:19012655

Evolution of biological complexity

PubMed Central

Adami, Christoph; Ofria, Charles; Collier, Travis C.

2000-01-01

To make a case for or against a trend in the evolution of complexity in biological evolution, complexity needs to be both rigorously defined and measurable. A recent information-theoretic (but intuitively evident) definition identifies genomic complexity with the amount of information a sequence stores about its environment. We investigate the evolution of genomic complexity in populations of digital organisms and monitor in detail the evolutionary transitions that increase complexity. We show that, because natural selection forces genomes to behave as a natural “Maxwell Demon,” within a fixed environment, genomic complexity is forced to increase. PMID:10781045

Efficient biological conversion of carbon monoxide (CO) to carbon dioxide (CO2) and for utilization in bioplastic production by Ralstonia eutropha through the display of an enzyme complex on the cell surface.

PubMed

Hyeon, Jeong Eun; Kim, Seung Wook; Park, Chulhwan; Han, Sung Ok

2015-06-25

An enzyme complex for biological conversion of CO to CO2 was anchored on the cell surface of the CO2-utilizing Ralstonia eutropha and successfully resulted in a 3.3-fold increase in conversion efficiency. These results suggest that this complexed system may be a promising strategy for CO2 utilization as a biological tool for the production of bioplastics.

Differential Multiscale Modeling of Chemically Complex Materials under Heavy Deformation: Biological, Bioinspired and Synthetic Hierarchical Materials

DTIC Science & Technology

2010-06-01

Buehler, “Meso- Origami : Folding Multilayer Graphene Sheets”, Applied Physics Letters, Vol. 95, paper #: 123121, 2009 D. Sen and M.J. Buehler, “Size and... geometry effects on flow stress in bioinspired de novo metal-matrix nanocomposites”, Advanced Engineering Materials, Vol. 11(10), pp. 774-781, 2009...behavior is recovered. Second, a subset of all geometries shows the inverse banana curve behavior. Interestingly, only 2% of all structures give the

KENNEDY SPACE CENTER, FLA. - Researchers are positioned on one of the watercraft being utilized to conduct underwater acoustic research in the Launch Complex 39 turn basin. Several government agencies, including NASA, NOAA, the Navy, the Coast Guard, and the Florida Fish and Wildlife Commission are involved in the testing. The research involves demonstrations of passive and active sensor technologies, with applications in fields ranging from marine biological research to homeland security. The work is also serving as a pilot project to assess the cooperation between the agencies involved. Equipment under development includes a passive acoustic monitor developed by NASA’s Jet Propulsion Laboratory, and mobile robotic sensors from the Navy’s Mobile Diving and Salvage Unit.

NASA Image and Video Library

2003-08-19

KENNEDY SPACE CENTER, FLA. - Researchers are positioned on one of the watercraft being utilized to conduct underwater acoustic research in the Launch Complex 39 turn basin. Several government agencies, including NASA, NOAA, the Navy, the Coast Guard, and the Florida Fish and Wildlife Commission are involved in the testing. The research involves demonstrations of passive and active sensor technologies, with applications in fields ranging from marine biological research to homeland security. The work is also serving as a pilot project to assess the cooperation between the agencies involved. Equipment under development includes a passive acoustic monitor developed by NASA’s Jet Propulsion Laboratory, and mobile robotic sensors from the Navy’s Mobile Diving and Salvage Unit.

Characteristics of the Freshwater Cyanobacterium Microcystis aeruginosa Grown in Iron-Limited Continuous Culture

PubMed Central

Dang, T. C.; Fujii, M.; Rose, A. L.; Bligh, M.

2012-01-01

A continuous culturing system (chemostat) made of metal-free materials was successfully developed and used to maintain Fe-limited cultures of Microcystis aeruginosa PCC7806 at nanomolar iron (Fe) concentrations (20 to 50 nM total Fe). EDTA was used to maintain Fe in solution, with bioavailable Fe controlled by absorption of light by the ferric EDTA complex and resultant reduction of Fe(III) to Fe(II). A kinetic model describing Fe transformations and biological uptake was applied to determine the biologically available form of Fe (i.e., unchelated ferrous iron) that is produced by photoreductive dissociation of the ferric EDTA complex. Prediction by chemostat theory modified to account for the light-mediated formation of bioavailable Fe rather than total Fe was in good agreement with growth characteristics of M. aeruginosa under Fe limitation. The cellular Fe quota increased with increasing dilution rates in a manner consistent with the Droop theory. Short-term Fe uptake assays using cells maintained at steady state indicated that M. aeruginosa cells vary their maximum Fe uptake rate (ρmax) depending on the degree of Fe stress. The rate of Fe uptake was lower for cells grown under conditions of lower Fe availability (i.e., lower dilution rate), suggesting that cells in the continuous cultures adjusted to Fe limitation by decreasing ρmax while maintaining a constant affinity for Fe. PMID:22210212

Thyrotropin-releasing hormone controls mitochondrial biology in human epidermis.

PubMed

Knuever, Jana; Poeggeler, Burkhard; Gáspár, Erzsébet; Klinger, Matthias; Hellwig-Burgel, Thomas; Hardenbicker, Celine; Tóth, Balázs I; Bíró, Tamás; Paus, Ralf

2012-03-01

Mitochondrial capacity and metabolic potential are under the control of hormones, such as thyroid hormones. The most proximal regulator of the hypothalamic-pituitary-thyroid (HPT) axis, TRH, is the key hypothalamic integrator of energy metabolism via its impact on thyroid hormone secretion. Here, we asked whether TRH directly modulates mitochondrial functions in normal, TRH-receptor-positive human epidermis. Organ-cultured human skin was treated with TRH (5-100 ng/ml) for 12-48 h. TRH significantly increased epidermal immunoreactivity for the mitochondria-selective subunit I of respiratory chain complex IV (MTCO1). This resulted from an increased MTCO1 transcription and protein synthesis and a stimulation of mitochondrial biogenesis as demonstrated by transmission electron microscopy and TRH-enhanced mitochondrial DNA synthesis. TRH also significantly stimulated the transcription of several other mitochondrial key genes (TFAM, HSP60, and BMAL1), including the master regulator of mitochondrial biogenesis (PGC-1α). TRH significantly enhanced mitochondrial complex I and IV enzyme activity and enhanced the oxygen consumption of human skin samples, which shows that the stimulated mitochondria are fully vital because the main source for cellular oxygen consumption is mitochondrial endoxidation. These findings identify TRH as a potent, novel neuroendocrine stimulator of mitochondrial activity and biogenesis in human epidermal keratinocytes in situ. Thus, human epidermis offers an excellent model for dissecting neuroendocrine controls of human mitochondrial biology under physiologically relevant conditions and for exploring corresponding clinical applications.

Deconstructing breast cancer heterogeneity: clinical implications for women with Basal-like tumors.

PubMed

Rattani, Nabila S; Swift-Scanlan, Theresa

2014-11-01

To compare and contrast the molecular and environmental factors contributing to basal-like breast cancer and highlight the clinical implications for women with this phenotype. CINAHL® and PubMed databases, journals, and citation indices were searched using the key word basal-like in combination with breast cancer, epigenetic, treatment, subtype, risk factor, and BRCA1 to synthesize the literature on the multiple underpinnings of basal-like breast cancer. Research findings related to the molecular foundation of basal-like breast cancer were integrated with knowledge of nongenetic contributing risk factors. Approved therapies and those under development were summarized with the goal of improving understanding for research and practice. Of the five subtypes of breast cancer, the basal-like subtype has the shortest survival and poorest prognosis. The development of gene expression assays with epigenetic studies has enabled reliable identification of the basal-like subtype and has shed light on novel therapeutic possibilities. Clinical trials for basal-like breast cancer are underway, and the potential for individualized treatments for women with this subtype show promise. The main difficulties with basal-like breast cancer are its aggressive course, treatment refractory nature, and complex biology, all of which pose real challenges for clinical management and patient education. Oncology nurses play a pivotal role in providing holistic care and patient support. Therefore, nurses must understand the complexity of the clinical presentation and the underlying biology of this cancer subtype.

KENNEDY SPACE CENTER, FLA. - Researchers utilize several types of watercraft to conduct underwater acoustic research in the Launch Complex 39 turn basin near Launch Pad 39A. Several government agencies, including NASA, NOAA, the Navy, the Coast Guard, and the Florida Fish and Wildlife Commission are involved in the testing. The research involves demonstrations of passive and active sensor technologies, with applications in fields ranging from marine biological research to homeland security. The work is also serving as a pilot project to assess the cooperation between the agencies involved. Equipment under development includes a passive acoustic monitor developed by NASA’s Jet Propulsion Laboratory, and mobile robotic sensors from the Navy’s Mobile Diving and Salvage Unit.

NASA Image and Video Library

2003-08-18

KENNEDY SPACE CENTER, FLA. - Researchers utilize several types of watercraft to conduct underwater acoustic research in the Launch Complex 39 turn basin near Launch Pad 39A. Several government agencies, including NASA, NOAA, the Navy, the Coast Guard, and the Florida Fish and Wildlife Commission are involved in the testing. The research involves demonstrations of passive and active sensor technologies, with applications in fields ranging from marine biological research to homeland security. The work is also serving as a pilot project to assess the cooperation between the agencies involved. Equipment under development includes a passive acoustic monitor developed by NASA’s Jet Propulsion Laboratory, and mobile robotic sensors from the Navy’s Mobile Diving and Salvage Unit.

KENNEDY SPACE CENTER, FLA. - Dr. Grant Gilmore (left), Dynamac Corp., talks to another member of the research team conducting underwater acoustic research in the Launch Complex 39 turn basin. Several government agencies, including NASA, NOAA, the Navy, the Coast Guard, and the Florida Fish and Wildlife Commission are involved in the testing. The research involves demonstrations of passive and active sensor technologies, with applications in fields ranging from marine biological research to homeland security. The work is also serving as a pilot project to assess the cooperation between the agencies involved. Equipment under development includes a passive acoustic monitor developed by NASA’s Jet Propulsion Laboratory, and mobile robotic sensors from the Navy’s Mobile Diving and Salvage Unit.

NASA Image and Video Library

2003-08-18

KENNEDY SPACE CENTER, FLA. - Dr. Grant Gilmore (left), Dynamac Corp., talks to another member of the research team conducting underwater acoustic research in the Launch Complex 39 turn basin. Several government agencies, including NASA, NOAA, the Navy, the Coast Guard, and the Florida Fish and Wildlife Commission are involved in the testing. The research involves demonstrations of passive and active sensor technologies, with applications in fields ranging from marine biological research to homeland security. The work is also serving as a pilot project to assess the cooperation between the agencies involved. Equipment under development includes a passive acoustic monitor developed by NASA’s Jet Propulsion Laboratory, and mobile robotic sensors from the Navy’s Mobile Diving and Salvage Unit.

KENNEDY SPACE CENTER, FLA. - Research team members roll out acoustic cable to the water's edge during underwater acoustic research being conducted in the Launch Complex 39 turn basin. Several government agencies, including NASA, NOAA, the Navy, the Coast Guard, and the Florida Fish and Wildlife Commission are involved in the testing. The research involves demonstrations of passive and active sensor technologies, with applications in fields ranging from marine biological research to homeland security. The work is also serving as a pilot project to assess the cooperation between the agencies involved. Equipment under development includes a passive acoustic monitor developed by NASA’s Jet Propulsion Laboratory, and mobile robotic sensors from the Navy’s Mobile Diving and Salvage Unit.

NASA Image and Video Library

2003-08-18

KENNEDY SPACE CENTER, FLA. - Research team members roll out acoustic cable to the water's edge during underwater acoustic research being conducted in the Launch Complex 39 turn basin. Several government agencies, including NASA, NOAA, the Navy, the Coast Guard, and the Florida Fish and Wildlife Commission are involved in the testing. The research involves demonstrations of passive and active sensor technologies, with applications in fields ranging from marine biological research to homeland security. The work is also serving as a pilot project to assess the cooperation between the agencies involved. Equipment under development includes a passive acoustic monitor developed by NASA’s Jet Propulsion Laboratory, and mobile robotic sensors from the Navy’s Mobile Diving and Salvage Unit.

KENNEDY SPACE CENTER, FLA. - Joe Bartoszek, NASA, is a member of the research team conducting underwater acoustic research in the Launch Complex 39 turn basin near Launch Pad 39A. Several government agencies, including NASA, NOAA, the Navy, the Coast Guard, and the Florida Fish and Wildlife Commission are involved in the testing. The research involves demonstrations of passive and active sensor technologies, with applications in fields ranging from marine biological research to homeland security. The work is also serving as a pilot project to assess the cooperation between the agencies involved. Equipment under development includes a passive acoustic monitor developed by NASA’s Jet Propulsion Laboratory, and mobile robotic sensors from the Navy’s Mobile Diving and Salvage Unit.

NASA Image and Video Library

2003-08-18

KENNEDY SPACE CENTER, FLA. - Joe Bartoszek, NASA, is a member of the research team conducting underwater acoustic research in the Launch Complex 39 turn basin near Launch Pad 39A. Several government agencies, including NASA, NOAA, the Navy, the Coast Guard, and the Florida Fish and Wildlife Commission are involved in the testing. The research involves demonstrations of passive and active sensor technologies, with applications in fields ranging from marine biological research to homeland security. The work is also serving as a pilot project to assess the cooperation between the agencies involved. Equipment under development includes a passive acoustic monitor developed by NASA’s Jet Propulsion Laboratory, and mobile robotic sensors from the Navy’s Mobile Diving and Salvage Unit.

KENNEDY SPACE CENTER, FLA. - Research team members take their places on one of the watercraft being utilized to conduct underwater acoustic research in the Launch Complex 39 turn basin. Several government agencies, including NASA, NOAA, the Navy, the Coast Guard, and the Florida Fish and Wildlife Commission are involved in the testing. The research involves demonstrations of passive and active sensor technologies, with applications in fields ranging from marine biological research to homeland security. The work is also serving as a pilot project to assess the cooperation between the agencies involved. Equipment under development includes a passive acoustic monitor developed by NASA’s Jet Propulsion Laboratory, and mobile robotic sensors from the Navy’s Mobile Diving and Salvage Unit.

NASA Image and Video Library

2003-08-19

KENNEDY SPACE CENTER, FLA. - Research team members take their places on one of the watercraft being utilized to conduct underwater acoustic research in the Launch Complex 39 turn basin. Several government agencies, including NASA, NOAA, the Navy, the Coast Guard, and the Florida Fish and Wildlife Commission are involved in the testing. The research involves demonstrations of passive and active sensor technologies, with applications in fields ranging from marine biological research to homeland security. The work is also serving as a pilot project to assess the cooperation between the agencies involved. Equipment under development includes a passive acoustic monitor developed by NASA’s Jet Propulsion Laboratory, and mobile robotic sensors from the Navy’s Mobile Diving and Salvage Unit.

Spectroscopic, cyclic voltammetric and biological studies of transition metal complexes with mixed nitrogen-sulphur (NS) donor macrocyclic ligand derived from thiosemicarbazide

NASA Astrophysics Data System (ADS)

Chandra, Sulekh; Gupta, Lokesh Kumar; Sangeetika

2005-11-01

The complexation of new mixed thia-aza-oxa macrocycle viz., 2,12-dithio-5,9,14,18-tetraoxo-7,16-dithia-1,3,4,10,11,13-hexaazacyclooctadecane containing thiosemicarba-zone unit with a series of transition metals Co(II), Ni(II) and Cu(II) has been investigated, by different spectroscopic techniques. The structural features of the ligand have been studied by EI-mass, 1H NMR and IR spectral techniques. Elemental analyses, magnetic moment susceptibility, molar conductance, IR, electronic, and EPR spectral studies characterized the complexes. Electronic absorption and IR spectra of the complexes indicate octahedral geometry for chloro, nitrato, thiocyanato or acetato complexes. The dimeric and neutral nature of the sulphato complexes are confirmed from magnetic susceptibility and low conductance values. Electronic spectra suggests square-planar geometry for all sulphato complexes. The redox behaviour was studied by cyclic voltammetry, show metal-centered reduction processes for all complexes. The complexes of copper show both oxidation and reduction process. The redox potentials depend on the conformation of central atom in the macrocyclic complexes. Newly synthesized macrocyclic ligand and its transition metal complexes show markedly growth inhibitory activity against pathogenic bacterias and plant pathogenic fungi under study. Most of the complexes have higher activity than that of the metal free ligand.

Noise induced quantum effects in photosynthetic complexes

NASA Astrophysics Data System (ADS)

Dorfman, Konstantin; Voronine, Dmitri; Mukamel, Shaul; Scully, Marlan

2012-02-01

Recent progress in coherent multidimensional optical spectroscopy revealed effects of quantum coherence coupled to population leading to population oscillations as evidence of quantum transport. Their description requires reevaluation of the currently used methods and approximations. We identify couplings between coherences and populations as the noise-induced cross-terms in the master equation generated via Agarwal-Fano interference that have been shown earlier to enhance the quantum yield in a photocell. We investigated a broad range of typical parameter regimes, which may be applied to a variety of photosynthetic complexes. We demonstrate that quantum coherence may be induced in photosynthetic complexes under natural conditions of incoherent light from the sun. This demonstrates that a photosynthetic reaction center may be viewed as a biological quantum heat engine that transforms high-energy thermal photon radiation into low entropy electron flux.

Stepping into the omics era: Opportunities and challenges for biomaterials science and engineering.

PubMed

Groen, Nathalie; Guvendiren, Murat; Rabitz, Herschel; Welsh, William J; Kohn, Joachim; de Boer, Jan

2016-04-01

The research paradigm in biomaterials science and engineering is evolving from using low-throughput and iterative experimental designs towards high-throughput experimental designs for materials optimization and the evaluation of materials properties. Computational science plays an important role in this transition. With the emergence of the omics approach in the biomaterials field, referred to as materiomics, high-throughput approaches hold the promise of tackling the complexity of materials and understanding correlations between material properties and their effects on complex biological systems. The intrinsic complexity of biological systems is an important factor that is often oversimplified when characterizing biological responses to materials and establishing property-activity relationships. Indeed, in vitro tests designed to predict in vivo performance of a given biomaterial are largely lacking as we are not able to capture the biological complexity of whole tissues in an in vitro model. In this opinion paper, we explain how we reached our opinion that converging genomics and materiomics into a new field would enable a significant acceleration of the development of new and improved medical devices. The use of computational modeling to correlate high-throughput gene expression profiling with high throughput combinatorial material design strategies would add power to the analysis of biological effects induced by material properties. We believe that this extra layer of complexity on top of high-throughput material experimentation is necessary to tackle the biological complexity and further advance the biomaterials field. In this opinion paper, we postulate that converging genomics and materiomics into a new field would enable a significant acceleration of the development of new and improved medical devices. The use of computational modeling to correlate high-throughput gene expression profiling with high throughput combinatorial material design strategies would add power to the analysis of biological effects induced by material properties. We believe that this extra layer of complexity on top of high-throughput material experimentation is necessary to tackle the biological complexity and further advance the biomaterials field. Copyright © 2016. Published by Elsevier Ltd.

Robustness and structure of complex networks

NASA Astrophysics Data System (ADS)

Shao, Shuai

This dissertation covers the two major parts of my PhD research on statistical physics and complex networks: i) modeling a new type of attack -- localized attack, and investigating robustness of complex networks under this type of attack; ii) discovering the clustering structure in complex networks and its influence on the robustness of coupled networks. Complex networks appear in every aspect of our daily life and are widely studied in Physics, Mathematics, Biology, and Computer Science. One important property of complex networks is their robustness under attacks, which depends crucially on the nature of attacks and the structure of the networks themselves. Previous studies have focused on two types of attack: random attack and targeted attack, which, however, are insufficient to describe many real-world damages. Here we propose a new type of attack -- localized attack, and study the robustness of complex networks under this type of attack, both analytically and via simulation. On the other hand, we also study the clustering structure in the network, and its influence on the robustness of a complex network system. In the first part, we propose a theoretical framework to study the robustness of complex networks under localized attack based on percolation theory and generating function method. We investigate the percolation properties, including the critical threshold of the phase transition pc and the size of the giant component Pinfinity. We compare localized attack with random attack and find that while random regular (RR) networks are more robust against localized attack, Erdoḧs-Renyi (ER) networks are equally robust under both types of attacks. As for scale-free (SF) networks, their robustness depends crucially on the degree exponent lambda. The simulation results show perfect agreement with theoretical predictions. We also test our model on two real-world networks: a peer-to-peer computer network and an airline network, and find that the real-world networks are much more vulnerable to localized attack compared with random attack. In the second part, we extend the tree-like generating function method to incorporating clustering structure in complex networks. We study the robustness of a complex network system, especially a network of networks (NON) with clustering structure in each network. We find that the system becomes less robust as we increase the clustering coefficient of each network. For a partially dependent network system, we also find that the influence of the clustering coefficient on network robustness decreases as we decrease the coupling strength, and the critical coupling strength qc, at which the first-order phase transition changes to second-order, increases as we increase the clustering coefficient.

Fiber optic-based biosensor

NASA Technical Reports Server (NTRS)

Ligler, Frances S.

1991-01-01

The NRL fiber optic biosensor is a device which measures the formation of a fluorescent complex at the surface of an optical fiber. Antibodies and DNA binding proteins provide the mechanism for recognizing an analyze and immobilizing a fluorescent complex on the fiber surface. The fiber optic biosensor is fast, sensitive, and permits analysis of hazardous materials remote from the instrumentation. The fiber optic biosensor is described in terms of the device configuration, chemistry for protein immobilization, and assay development. A lab version is being used for assay development and performance characterization while a portable device is under development. Antibodies coated on the fiber are stable for up to two years of storage prior to use. The fiber optic biosensor was used to measure concentration of toxins in the parts per billion (ng/ml) range in under a minute. Immunoassays for small molecules and whole bacteria are under development. Assays using DNA probes as the detection element can also be used with the fiber optic sensor, which is currently being developed to detect biological warfare agents, explosives, pathogens, and toxic materials which pollute the environment.

Chromatin immunoprecipitation with fixed animal tissues and preparation for high-throughput sequencing.

PubMed

Cotney, Justin L; Noonan, James P

2015-02-02

Chromatin immunoprecipitation coupled with high-throughput sequencing (ChIP-Seq) is a powerful method used to identify genome-wide binding patterns of transcription factors and distribution of various histone modifications associated with different chromatin states. In most published studies, ChIP-Seq has been performed on cultured cells grown under controlled conditions, allowing generation of large amounts of material in a homogeneous biological state. Although such studies have provided great insight into the dynamic landscapes of animal genomes, they do not allow the examination of transcription factor binding and chromatin states in adult tissues, developing embryonic structures, or tumors. Such knowledge is critical to understanding the information required to create and maintain a complex biological tissue and to identify noncoding regions of the genome directly involved in tissues affected by complex diseases such as autism. Studying these tissue types with ChIP-Seq can be challenging due to the limited availability of tissues and the lack of complex biological states able to be achieved in culture. These inherent differences require alterations of standard cross-linking and chromatin extraction typically used in cell culture. Here we describe a general approach for using small amounts of animal tissue to perform ChIP-Seq directed at histone modifications and transcription factors. Tissue is homogenized before treatment with formaldehyde to ensure proper cross-linking, and a two-step nuclear isolation is performed to increase extraction of soluble chromatin. Small amounts of soluble chromatin are then used for immunoprecipitation (IP) and prepared for multiplexed high-throughput sequencing. © 2015 Cold Spring Harbor Laboratory Press.

Current Understanding of Usher Syndrome Type II

PubMed Central

Yang, Jun; Wang, Le; Song, Hongman; Sokolov, Maxim

2012-01-01

Usher syndrome is the most common deafness-blindness caused by genetic mutations. To date, three genes have been identified underlying the most prevalent form of Usher syndrome, the type II form (USH2). The proteins encoded by these genes are demonstrated to form a complex in vivo. This complex is localized mainly at the periciliary membrane complex in photoreceptors and the ankle-link of the stereocilia in hair cells. Many proteins have been found to interact with USH2 proteins in vitro, suggesting that they are potential additional components of this USH2 complex and that the genes encoding these proteins may be the candidate USH2 genes. However, further investigations are critical to establish their existence in the USH2 complex in vivo. Based on the predicted functional domains in USH2 proteins, their cellular localizations in photoreceptors and hair cells, the observed phenotypes in USH2 mutant mice, and the known knowledge about diseases similar to USH2, putative biological functions of the USH2 complex have been proposed. Finally, therapeutic approaches for this group of diseases are now being actively explored. PMID:22201796

Entropy in molecular recognition by proteins

PubMed Central

Caro, José A.; Harpole, Kyle W.; Kasinath, Vignesh; Lim, Jackwee; Granja, Jeffrey; Valentine, Kathleen G.; Sharp, Kim A.

2017-01-01

Molecular recognition by proteins is fundamental to molecular biology. Dissection of the thermodynamic energy terms governing protein–ligand interactions has proven difficult, with determination of entropic contributions being particularly elusive. NMR relaxation measurements have suggested that changes in protein conformational entropy can be quantitatively obtained through a dynamical proxy, but the generality of this relationship has not been shown. Twenty-eight protein–ligand complexes are used to show a quantitative relationship between measures of fast side-chain motion and the underlying conformational entropy. We find that the contribution of conformational entropy can range from favorable to unfavorable, which demonstrates the potential of this thermodynamic variable to modulate protein–ligand interactions. For about one-quarter of these complexes, the absence of conformational entropy would render the resulting affinity biologically meaningless. The dynamical proxy for conformational entropy or “entropy meter” also allows for refinement of the contributions of solvent entropy and the loss in rotational-translational entropy accompanying formation of high-affinity complexes. Furthermore, structure-based application of the approach can also provide insight into long-lived specific water–protein interactions that escape the generic treatments of solvent entropy based simply on changes in accessible surface area. These results provide a comprehensive and unified view of the general role of entropy in high-affinity molecular recognition by proteins. PMID:28584100

Doing molecular biophysics: finding, naming, and picturing signal within complexity.

PubMed

Richardson, Jane S; Richardson, David C

2013-01-01

A macromolecular structure, as measured data or as a list of coordinates or even on-screen as a full atomic model, is an extremely complex and confusing object. The underlying rules of how it folds, moves, and interacts as a biological entity are even less evident or intuitive to the human mind. To do science on such molecules, or to relate them usefully to higher levels of biology, we need to start with a natural history that names their features in meaningful ways and with multiple representations (visual or algebraic) that show some aspect of their organizing principles. The two of us have jointly enjoyed a highly varied and engrossing career in biophysical research over nearly 50 years. Our frequent changes of emphasis are tied together by two threads: first, by finding the right names, visualizations, and methods to help both ourselves and others to better understand the 3D structures of protein and RNA molecules, and second, by redefining the boundary between signal and noise for complex data, in both directions-sometimes identifying and promoting real signal up out of what seemed just noise, and sometimes demoting apparent signal into noise or systematic error. Here we relate parts of our scientific and personal lives, including ups and downs, influences, anecdotes, and guiding principles such as the title theme.

Sedimentation Velocity Analysis of Large Oligomeric Chromatin Complexes Using Interference Detection.

PubMed

Rogge, Ryan A; Hansen, Jeffrey C

2015-01-01

Sedimentation velocity experiments measure the transport of molecules in solution under centrifugal force. Here, we describe a method for monitoring the sedimentation of very large biological molecular assemblies using the interference optical systems of the analytical ultracentrifuge. The mass, partial-specific volume, and shape of macromolecules in solution affect their sedimentation rates as reflected in the sedimentation coefficient. The sedimentation coefficient is obtained by measuring the solute concentration as a function of radial distance during centrifugation. Monitoring the concentration can be accomplished using interference optics, absorbance optics, or the fluorescence detection system, each with inherent advantages. The interference optical system captures data much faster than these other optical systems, allowing for sedimentation velocity analysis of extremely large macromolecular complexes that sediment rapidly at very low rotor speeds. Supramolecular oligomeric complexes produced by self-association of 12-mer chromatin fibers are used to illustrate the advantages of the interference optics. Using interference optics, we show that chromatin fibers self-associate at physiological divalent salt concentrations to form structures that sediment between 10,000 and 350,000S. The method for characterizing chromatin oligomers described in this chapter will be generally useful for characterization of any biological structures that are too large to be studied by the absorbance optical system. © 2015 Elsevier Inc. All rights reserved.

Entropy in molecular recognition by proteins.

PubMed

Caro, José A; Harpole, Kyle W; Kasinath, Vignesh; Lim, Jackwee; Granja, Jeffrey; Valentine, Kathleen G; Sharp, Kim A; Wand, A Joshua

2017-06-20

Molecular recognition by proteins is fundamental to molecular biology. Dissection of the thermodynamic energy terms governing protein-ligand interactions has proven difficult, with determination of entropic contributions being particularly elusive. NMR relaxation measurements have suggested that changes in protein conformational entropy can be quantitatively obtained through a dynamical proxy, but the generality of this relationship has not been shown. Twenty-eight protein-ligand complexes are used to show a quantitative relationship between measures of fast side-chain motion and the underlying conformational entropy. We find that the contribution of conformational entropy can range from favorable to unfavorable, which demonstrates the potential of this thermodynamic variable to modulate protein-ligand interactions. For about one-quarter of these complexes, the absence of conformational entropy would render the resulting affinity biologically meaningless. The dynamical proxy for conformational entropy or "entropy meter" also allows for refinement of the contributions of solvent entropy and the loss in rotational-translational entropy accompanying formation of high-affinity complexes. Furthermore, structure-based application of the approach can also provide insight into long-lived specific water-protein interactions that escape the generic treatments of solvent entropy based simply on changes in accessible surface area. These results provide a comprehensive and unified view of the general role of entropy in high-affinity molecular recognition by proteins.

Responses to olfactory signals reflect network structure of flower-visitor interactions.

PubMed

Junker, Robert R; Höcherl, Nicole; Blüthgen, Nico

2010-07-01

1. Network analyses provide insights into the diversity and complexity of ecological interactions and have motivated conclusions about community stability and co-evolution. However, biological traits and mechanisms such as chemical signals regulating the interactions between individual species--the microstructure of a network--are poorly understood. 2. We linked the responses of receivers (flower visitors) towards signals (flower scent) to the structure of a highly diverse natural flower-insect network. For each interaction, we define link temperature--a newly developed metric--as the deviation of the observed interaction strength from neutrality, assuming that animals randomly interact with flowers. 3. Link temperature was positively correlated to the specific visitors' responses to floral scents, experimentally examined in a mobile olfactometer. Thus, communication between plants and consumers via phytochemical signals reflects a significant part of the microstructure in a complex network. Negative as well as positive responses towards floral scents contributed to these results, where individual experience was important apart from innate behaviour. 4. Our results indicate that: (1) biological mechanisms have a profound impact on the microstructure of complex networks that underlies the outcome of aggregate statistics, and (2) floral scents act as a filter, promoting the visitation of some flower visitors, but also inhibiting the visitation of others.

Mathematical and Computational Modeling in Complex Biological Systems

PubMed Central

Li, Wenyang; Zhu, Xiaoliang

2017-01-01

The biological process and molecular functions involved in the cancer progression remain difficult to understand for biologists and clinical doctors. Recent developments in high-throughput technologies urge the systems biology to achieve more precise models for complex diseases. Computational and mathematical models are gradually being used to help us understand the omics data produced by high-throughput experimental techniques. The use of computational models in systems biology allows us to explore the pathogenesis of complex diseases, improve our understanding of the latent molecular mechanisms, and promote treatment strategy optimization and new drug discovery. Currently, it is urgent to bridge the gap between the developments of high-throughput technologies and systemic modeling of the biological process in cancer research. In this review, we firstly studied several typical mathematical modeling approaches of biological systems in different scales and deeply analyzed their characteristics, advantages, applications, and limitations. Next, three potential research directions in systems modeling were summarized. To conclude, this review provides an update of important solutions using computational modeling approaches in systems biology. PMID:28386558

Mathematical and Computational Modeling in Complex Biological Systems.

PubMed

Ji, Zhiwei; Yan, Ke; Li, Wenyang; Hu, Haigen; Zhu, Xiaoliang

2017-01-01

The biological process and molecular functions involved in the cancer progression remain difficult to understand for biologists and clinical doctors. Recent developments in high-throughput technologies urge the systems biology to achieve more precise models for complex diseases. Computational and mathematical models are gradually being used to help us understand the omics data produced by high-throughput experimental techniques. The use of computational models in systems biology allows us to explore the pathogenesis of complex diseases, improve our understanding of the latent molecular mechanisms, and promote treatment strategy optimization and new drug discovery. Currently, it is urgent to bridge the gap between the developments of high-throughput technologies and systemic modeling of the biological process in cancer research. In this review, we firstly studied several typical mathematical modeling approaches of biological systems in different scales and deeply analyzed their characteristics, advantages, applications, and limitations. Next, three potential research directions in systems modeling were summarized. To conclude, this review provides an update of important solutions using computational modeling approaches in systems biology.

Stepping into the omics era: Opportunities and challenges for biomaterials science and engineering☆

PubMed Central

Rabitz, Herschel; Welsh, William J.; Kohn, Joachim; de Boer, Jan

2016-01-01

The research paradigm in biomaterials science and engineering is evolving from using low-throughput and iterative experimental designs towards high-throughput experimental designs for materials optimization and the evaluation of materials properties. Computational science plays an important role in this transition. With the emergence of the omics approach in the biomaterials field, referred to as materiomics, high-throughput approaches hold the promise of tackling the complexity of materials and understanding correlations between material properties and their effects on complex biological systems. The intrinsic complexity of biological systems is an important factor that is often oversimplified when characterizing biological responses to materials and establishing property-activity relationships. Indeed, in vitro tests designed to predict in vivo performance of a given biomaterial are largely lacking as we are not able to capture the biological complexity of whole tissues in an in vitro model. In this opinion paper, we explain how we reached our opinion that converging genomics and materiomics into a new field would enable a significant acceleration of the development of new and improved medical devices. The use of computational modeling to correlate high-throughput gene expression profiling with high throughput combinatorial material design strategies would add power to the analysis of biological effects induced by material properties. We believe that this extra layer of complexity on top of high-throughput material experimentation is necessary to tackle the biological complexity and further advance the biomaterials field. PMID:26876875

The BEL information extraction workflow (BELIEF): evaluation in the BioCreative V BEL and IAT track

PubMed Central

Madan, Sumit; Hodapp, Sven; Senger, Philipp; Ansari, Sam; Szostak, Justyna; Hoeng, Julia; Peitsch, Manuel; Fluck, Juliane

2016-01-01

Network-based approaches have become extremely important in systems biology to achieve a better understanding of biological mechanisms. For network representation, the Biological Expression Language (BEL) is well designed to collate findings from the scientific literature into biological network models. To facilitate encoding and biocuration of such findings in BEL, a BEL Information Extraction Workflow (BELIEF) was developed. BELIEF provides a web-based curation interface, the BELIEF Dashboard, that incorporates text mining techniques to support the biocurator in the generation of BEL networks. The underlying UIMA-based text mining pipeline (BELIEF Pipeline) uses several named entity recognition processes and relationship extraction methods to detect concepts and BEL relationships in literature. The BELIEF Dashboard allows easy curation of the automatically generated BEL statements and their context annotations. Resulting BEL statements and their context annotations can be syntactically and semantically verified to ensure consistency in the BEL network. In summary, the workflow supports experts in different stages of systems biology network building. Based on the BioCreative V BEL track evaluation, we show that the BELIEF Pipeline automatically extracts relationships with an F-score of 36.4% and fully correct statements can be obtained with an F-score of 30.8%. Participation in the BioCreative V Interactive task (IAT) track with BELIEF revealed a systems usability scale (SUS) of 67. Considering the complexity of the task for new users—learning BEL, working with a completely new interface, and performing complex curation—a score so close to the overall SUS average highlights the usability of BELIEF. Database URL: BELIEF is available at http://www.scaiview.com/belief/ PMID:27694210

Biomedical text mining and its applications in cancer research.

PubMed

Zhu, Fei; Patumcharoenpol, Preecha; Zhang, Cheng; Yang, Yang; Chan, Jonathan; Meechai, Asawin; Vongsangnak, Wanwipa; Shen, Bairong

2013-04-01

Cancer is a malignant disease that has caused millions of human deaths. Its study has a long history of well over 100years. There have been an enormous number of publications on cancer research. This integrated but unstructured biomedical text is of great value for cancer diagnostics, treatment, and prevention. The immense body and rapid growth of biomedical text on cancer has led to the appearance of a large number of text mining techniques aimed at extracting novel knowledge from scientific text. Biomedical text mining on cancer research is computationally automatic and high-throughput in nature. However, it is error-prone due to the complexity of natural language processing. In this review, we introduce the basic concepts underlying text mining and examine some frequently used algorithms, tools, and data sets, as well as assessing how much these algorithms have been utilized. We then discuss the current state-of-the-art text mining applications in cancer research and we also provide some resources for cancer text mining. With the development of systems biology, researchers tend to understand complex biomedical systems from a systems biology viewpoint. Thus, the full utilization of text mining to facilitate cancer systems biology research is fast becoming a major concern. To address this issue, we describe the general workflow of text mining in cancer systems biology and each phase of the workflow. We hope that this review can (i) provide a useful overview of the current work of this field; (ii) help researchers to choose text mining tools and datasets; and (iii) highlight how to apply text mining to assist cancer systems biology research. Copyright © 2012 Elsevier Inc. All rights reserved.

The BEL information extraction workflow (BELIEF): evaluation in the BioCreative V BEL and IAT track.

PubMed

Madan, Sumit; Hodapp, Sven; Senger, Philipp; Ansari, Sam; Szostak, Justyna; Hoeng, Julia; Peitsch, Manuel; Fluck, Juliane

2016-01-01

Network-based approaches have become extremely important in systems biology to achieve a better understanding of biological mechanisms. For network representation, the Biological Expression Language (BEL) is well designed to collate findings from the scientific literature into biological network models. To facilitate encoding and biocuration of such findings in BEL, a BEL Information Extraction Workflow (BELIEF) was developed. BELIEF provides a web-based curation interface, the BELIEF Dashboard, that incorporates text mining techniques to support the biocurator in the generation of BEL networks. The underlying UIMA-based text mining pipeline (BELIEF Pipeline) uses several named entity recognition processes and relationship extraction methods to detect concepts and BEL relationships in literature. The BELIEF Dashboard allows easy curation of the automatically generated BEL statements and their context annotations. Resulting BEL statements and their context annotations can be syntactically and semantically verified to ensure consistency in the BEL network. In summary, the workflow supports experts in different stages of systems biology network building. Based on the BioCreative V BEL track evaluation, we show that the BELIEF Pipeline automatically extracts relationships with an F-score of 36.4% and fully correct statements can be obtained with an F-score of 30.8%. Participation in the BioCreative V Interactive task (IAT) track with BELIEF revealed a systems usability scale (SUS) of 67. Considering the complexity of the task for new users-learning BEL, working with a completely new interface, and performing complex curation-a score so close to the overall SUS average highlights the usability of BELIEF.Database URL: BELIEF is available at http://www.scaiview.com/belief/. © The Author(s) 2016. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

A Network Biology Approach Identifies Molecular Cross-Talk between Normal Prostate Epithelial and Prostate Carcinoma Cells

PubMed Central

Trevino, Victor; Cassese, Alberto; Nagy, Zsuzsanna; Zhuang, Xiaodong; Herbert, John; Antzack, Philipp; Clarke, Kim; Davies, Nicholas; Rahman, Ayesha; Campbell, Moray J.; Bicknell, Roy; Vannucci, Marina; Falciani, Francesco

2016-01-01

Abstract The advent of functional genomics has enabled the genome-wide characterization of the molecular state of cells and tissues, virtually at every level of biological organization. The difficulty in organizing and mining this unprecedented amount of information has stimulated the development of computational methods designed to infer the underlying structure of regulatory networks from observational data. These important developments had a profound impact in biological sciences since they triggered the development of a novel data-driven investigative approach. In cancer research, this strategy has been particularly successful. It has contributed to the identification of novel biomarkers, to a better characterization of disease heterogeneity and to a more in depth understanding of cancer pathophysiology. However, so far these approaches have not explicitly addressed the challenge of identifying networks representing the interaction of different cell types in a complex tissue. Since these interactions represent an essential part of the biology of both diseased and healthy tissues, it is of paramount importance that this challenge is addressed. Here we report the definition of a network reverse engineering strategy designed to infer directional signals linking adjacent cell types within a complex tissue. The application of this inference strategy to prostate cancer genome-wide expression profiling data validated the approach and revealed that normal epithelial cells exert an anti-tumour activity on prostate carcinoma cells. Moreover, by using a Bayesian hierarchical model integrating genetics and gene expression data and combining this with survival analysis, we show that the expression of putative cell communication genes related to focal adhesion and secretion is affected by epistatic gene copy number variation and it is predictive of patient survival. Ultimately, this study represents a generalizable approach to the challenge of deciphering cell communication networks in a wide spectrum of biological systems. PMID:27124473

A Network Biology Approach Identifies Molecular Cross-Talk between Normal Prostate Epithelial and Prostate Carcinoma Cells.

PubMed

Trevino, Victor; Cassese, Alberto; Nagy, Zsuzsanna; Zhuang, Xiaodong; Herbert, John; Antczak, Philipp; Clarke, Kim; Davies, Nicholas; Rahman, Ayesha; Campbell, Moray J; Guindani, Michele; Bicknell, Roy; Vannucci, Marina; Falciani, Francesco

2016-04-01

The advent of functional genomics has enabled the genome-wide characterization of the molecular state of cells and tissues, virtually at every level of biological organization. The difficulty in organizing and mining this unprecedented amount of information has stimulated the development of computational methods designed to infer the underlying structure of regulatory networks from observational data. These important developments had a profound impact in biological sciences since they triggered the development of a novel data-driven investigative approach. In cancer research, this strategy has been particularly successful. It has contributed to the identification of novel biomarkers, to a better characterization of disease heterogeneity and to a more in depth understanding of cancer pathophysiology. However, so far these approaches have not explicitly addressed the challenge of identifying networks representing the interaction of different cell types in a complex tissue. Since these interactions represent an essential part of the biology of both diseased and healthy tissues, it is of paramount importance that this challenge is addressed. Here we report the definition of a network reverse engineering strategy designed to infer directional signals linking adjacent cell types within a complex tissue. The application of this inference strategy to prostate cancer genome-wide expression profiling data validated the approach and revealed that normal epithelial cells exert an anti-tumour activity on prostate carcinoma cells. Moreover, by using a Bayesian hierarchical model integrating genetics and gene expression data and combining this with survival analysis, we show that the expression of putative cell communication genes related to focal adhesion and secretion is affected by epistatic gene copy number variation and it is predictive of patient survival. Ultimately, this study represents a generalizable approach to the challenge of deciphering cell communication networks in a wide spectrum of biological systems.

Towards Engineering Biological Systems in a Broader Context.

PubMed

Venturelli, Ophelia S; Egbert, Robert G; Arkin, Adam P

2016-02-27

Significant advances have been made in synthetic biology to program information processing capabilities in cells. While these designs can function predictably in controlled laboratory environments, the reliability of these devices in complex, temporally changing environments has not yet been characterized. As human society faces global challenges in agriculture, human health and energy, synthetic biology should develop predictive design principles for biological systems operating in complex environments. Natural biological systems have evolved mechanisms to overcome innumerable and diverse environmental challenges. Evolutionary design rules should be extracted and adapted to engineer stable and predictable ecological function. We highlight examples of natural biological responses spanning the cellular, population and microbial community levels that show promise in synthetic biology contexts. We argue that synthetic circuits embedded in host organisms or designed ecologies informed by suitable measurement of biotic and abiotic environmental parameters could be used as engineering substrates to achieve target functions in complex environments. Successful implementation of these methods will broaden the context in which synthetic biological systems can be applied to solve important problems. Copyright © 2015 Elsevier Ltd. All rights reserved.

Structures and physical properties of gaseous metal cationized biological ions.

PubMed

Burt, Michael B; Fridgen, Travis D

2012-01-01

Metal chelation can alter the activity of free biomolecules by modifying their structures or stabilizing higher energy tautomers. In recent years, mass spectrometric techniques have been used to investigate the effects of metal complexation with proteins, nucleobases and nucleotides, where small conformational changes can have significant physiological consequences. In particular, infrared multiple photon dissociation spectroscopy has emerged as an important tool for determining the structure and reactivity of gas-phase ions. Unlike other mass spectrometric approaches, this method is able to directly resolve structural isomers using characteristic vibrational signatures. Other activation and dissociation methods, such as blackbody infrared radiative dissociation or collision-induced dissociation can also reveal information about the thermochemistry and dissociative pathways of these biological ions. This information can then be used to provide information about the structures of the ionic complexes under study. In this article, we review the use of gas-phase techniques in characterizing metal-bound biomolecules. Particular attention will be given to our own contributions, which detail the ability of metal cations to disrupt nucleobase pairs, direct the self-assembly of nucleobase clusters and stabilize non-canonical isomers of amino acids.

Platform construction and extraction mechanism study of magnetic mixed hemimicelles solid-phase extraction

PubMed Central

Xiao, Deli; Zhang, Chan; He, Jia; Zeng, Rong; Chen, Rong; He, Hua

2016-01-01

Simple, accurate and high-throughput pretreatment method would facilitate large-scale studies of trace analysis in complex samples. Magnetic mixed hemimicelles solid-phase extraction has the power to become a key pretreatment method in biological, environmental and clinical research. However, lacking of experimental predictability and unsharpness of extraction mechanism limit the development of this promising method. Herein, this work tries to establish theoretical-based experimental designs for extraction of trace analytes from complex samples using magnetic mixed hemimicelles solid-phase extraction. We selected three categories and six sub-types of compounds for systematic comparative study of extraction mechanism, and comprehensively illustrated the roles of different force (hydrophobic interaction, π-π stacking interactions, hydrogen-bonding interaction, electrostatic interaction) for the first time. What’s more, the application guidelines for supporting materials, surfactants and sample matrix were also summarized. The extraction mechanism and platform established in the study render its future promising for foreseeable and efficient pretreatment under theoretical based experimental design for trace analytes from environmental, biological and clinical samples. PMID:27924944

Spontaneous switching of frequency-locking by periodic stimulus in oscillators of plasmodium of the true slime mold.

PubMed

Takamatsu, A; Yamamoto, T; Fujii, T

2004-01-01

Microfabrication technique was used to construct a model system with a living cell of plasmodium of the true slime mold, Physarum polycephalum, a living coupled oscillator system. Its parameters can be systematically controlled as in computer simulations, so that results are directly comparable to those of general mathematical models. As the first step, we investigated responses in oscillatory cells, the oscillators of the plasmodium, to periodic stimuli by temperature changes to elucidate characteristics of the cells as nonlinear systems whose internal dynamics are unknown because of their complexity. We observed that the forced oscillator of the plasmodium show 1:1, 2:1, 3:1 frequency locking inside so-called Arnold tongues regions as well as in other nonlinear systems such as chemical systems and other biological systems. In addition, we found spontaneous switching behavior from certain frequency locking states to other states, even under certain fixed parameters. This technique can be applied to more complex systems with multiple elements, such as coupled oscillator systems, and would be useful to investigate complicated phenomena in biological systems such as information processing.

Dermatoglyphics--a possible biomarker in the neurodevelopmental model for the origin of mental disorders.

PubMed

Ahmed-Popova, Ferihan M; Mantarkov, Mladen J; Sivkov, Stefan T; Akabaliev, Valentin H

2014-01-01

Dermatoglyphic pattern formation and differentiation are complex processes which have been in the focus of research interest ever since dermatoglyphics became a science. The patterns' early differentiation and genetic uniqueness as well as the relatively simple methods used to obtain and store fingerprints make it possible to study the relationship between certain dermatoglyphic characteristics and the underlying pathological processes in a number of diseases, including mental disorders. The present review reports published data from fundamental and clinical studies on dermatoglyphics primarily in schizophrenia and bipolar disorder to lend additional support for the neurodevelopmental hypothesis in the etiology of these disorders. Following an analysis of the theories of dermatoglyphics formation and the complex association between ridge patterns and central nervous system in early embryogenesis, an attempt is made to present dermatoglyphics as possible biological markers of impaired neurodevelopment. The contradictory data in the literature on dermatoglyphics in mental disorders suggest the need for further studies on these biological markers in order to identify their place in the neurodevelopmental etiological model of these diseases.

Network biology: Describing biological systems by complex networks. Comment on "Network science of biological systems at different scales: A review" by M. Gosak et al.

NASA Astrophysics Data System (ADS)

Jalili, Mahdi

2018-03-01

I enjoyed reading Gosak et al. review on analysing biological systems from network science perspective [1]. Network science, first started within Physics community, is now a mature multidisciplinary field of science with many applications ranging from Ecology to biology, medicine, social sciences, engineering and computer science. Gosak et al. discussed how biological systems can be modelled and described by complex network theory which is an important application of network science. Although there has been considerable progress in network biology over the past two decades, this is just the beginning and network science has a great deal to offer to biology and medical sciences.

Molecular Signatures of Membrane Protein Complexes Underlying Muscular Dystrophy*

PubMed Central

Turk, Rolf; Hsiao, Jordy J.; Smits, Melinda M.; Ng, Brandon H.; Pospisil, Tyler C.; Jones, Kayla S.; Campbell, Kevin P.; Wright, Michael E.

2016-01-01

Mutations in genes encoding components of the sarcolemmal dystrophin-glycoprotein complex (DGC) are responsible for a large number of muscular dystrophies. As such, molecular dissection of the DGC is expected to both reveal pathological mechanisms, and provides a biological framework for validating new DGC components. Establishment of the molecular composition of plasma-membrane protein complexes has been hampered by a lack of suitable biochemical approaches. Here we present an analytical workflow based upon the principles of protein correlation profiling that has enabled us to model the molecular composition of the DGC in mouse skeletal muscle. We also report our analysis of protein complexes in mice harboring mutations in DGC components. Bioinformatic analyses suggested that cell-adhesion pathways were under the transcriptional control of NFκB in DGC mutant mice, which is a finding that is supported by previous studies that showed NFκB-regulated pathways underlie the pathophysiology of DGC-related muscular dystrophies. Moreover, the bioinformatic analyses suggested that inflammatory and compensatory mechanisms were activated in skeletal muscle of DGC mutant mice. Additionally, this proteomic study provides a molecular framework to refine our understanding of the DGC, identification of protein biomarkers of neuromuscular disease, and pharmacological interrogation of the DGC in adult skeletal muscle https://www.mda.org/disease/congenital-muscular-dystrophy/research. PMID:27099343

Exponential evolution: implications for intelligent extraterrestrial life.

PubMed

Russell, D A

1983-01-01

Some measures of biologic complexity, including maximal levels of brain development, are exponential functions of time through intervals of 10(6) to 10(9) yrs. Biological interactions apparently stimulate evolution but physical conditions determine the time required to achieve a given level of complexity. Trends in brain evolution suggest that other organisms could attain human levels within approximately 10(7) yrs. The number (N) and longevity (L) terms in appropriate modifications of the Drake Equation, together with trends in the evolution of biological complexity on Earth, could provide rough estimates of the prevalence of life forms at specified levels of complexity within the Galaxy. If life occurs throughout the cosmos, exponential evolutionary processes imply that higher intelligence will soon (10(9) yrs) become more prevalent than it now is. Changes in the physical universe become less rapid as time increases from the Big Bang. Changes in biological complexity may be most rapid at such later times. This lends a unique and symmetrical importance to early and late universal times.

Probing the modulated formation of gold nanoparticles-beta-lactoglobulin corona complexes and their applications.

PubMed

Yang, Jiang; Wang, Bo; You, Youngsang; Chang, Woo-Jin; Tang, Ke; Wang, Yi-Cheng; Zhang, Wenzhao; Ding, Feng; Gunasekaran, Sundaram

2017-11-23

Understanding the interactions between proteins and nanoparticles (NPs) along with the underlying structural and dynamic information is of utmost importance to exploit nanotechnology for biomedical applications. Upon adsorption onto a NP surface, proteins form a well-organized layer, termed the corona, that dictates the identity of the NP-protein complex and governs its biological pathways. Given its high biological relevance, in-depth molecular investigations and applications of NPs-protein corona complexes are still scarce, especially since different proteins form unique corona patterns, making identification of the biomolecular motifs at the interface critical. In this work, we provide molecular insights and structural characterizations of the bio-nano interface of a popular food-based protein, namely bovine beta-lactoglobulin (β-LG), with gold nanoparticles (AuNPs) and report on our investigations of the formation of corona complexes by combined molecular simulations and complementary experiments. Two major binding sites in β-LG were identified as being driven by citrate-mediated electrostatic interactions, while the associated binding kinetics and conformational changes in the secondary structures were also characterized. More importantly, the superior stability of the corona led us to further explore its biomedical applications, such as in the smartphone-based point-of-care biosensing of Escherichia coli (E. coli) and in the computed tomography (CT) of the gastrointestinal (GI) tract through oral administration to probe GI tolerance and functions. Considering their biocompatibility, edible nature, and efficient excretion through defecation, AuNPs-β-LG corona complexes have shown promising perspectives for future in vitro and in vivo clinical settings.

Radiation damage to nucleoprotein complexes in macromolecular crystallography

DOE PAGES

Bury, Charles; Garman, Elspeth F.; Ginn, Helen Mary; ...

2015-01-30

Significant progress has been made in macromolecular crystallography over recent years in both the understanding and mitigation of X-ray induced radiation damage when collecting diffraction data from crystalline proteins. Despite the large field that is productively engaged in the study of radiation chemistry of nucleic acids, particularly of DNA, there are currently very few X-ray crystallographic studies on radiation damage mechanisms in nucleic acids. Quantitative comparison of damage to protein and DNA crystals separately is challenging, but many of the issues are circumvented by studying pre-formed biological nucleoprotein complexes where direct comparison of each component can be made under themore » same controlled conditions. A model protein–DNA complex C.Esp1396I is employed to investigate specific damage mechanisms for protein and DNA in a biologically relevant complex over a large dose range (2.07–44.63 MGy). In order to allow a quantitative analysis of radiation damage sites from a complex series of macromolecular diffraction data, a computational method has been developed that is generally applicable to the field. Typical specific damage was observed for both the protein on particular amino acids and for the DNA on, for example, the cleavage of base-sugar N 1—C and sugar-phosphate C—O bonds. Strikingly the DNA component was determined to be far more resistant to specific damage than the protein for the investigated dose range. We observed the protein at low doses and found that they were susceptible to radiation damage while the DNA was far more resistant, damage only being observed at significantly higher doses.« less

The cosmological model of eternal inflation and the transition from chance to biological evolution in the history of life

PubMed Central

Koonin, Eugene V

2007-01-01

Background Recent developments in cosmology radically change the conception of the universe as well as the very notions of "probable" and "possible". The model of eternal inflation implies that all macroscopic histories permitted by laws of physics are repeated an infinite number of times in the infinite multiverse. In contrast to the traditional cosmological models of a single, finite universe, this worldview provides for the origin of an infinite number of complex systems by chance, even as the probability of complexity emerging in any given region of the multiverse is extremely low. This change in perspective has profound implications for the history of any phenomenon, and life on earth cannot be an exception. Hypothesis Origin of life is a chicken and egg problem: for biological evolution that is governed, primarily, by natural selection, to take off, efficient systems for replication and translation are required, but even barebones cores of these systems appear to be products of extensive selection. The currently favored (partial) solution is an RNA world without proteins in which replication is catalyzed by ribozymes and which serves as the cradle for the translation system. However, the RNA world faces its own hard problems as ribozyme-catalyzed RNA replication remains a hypothesis and the selective pressures behind the origin of translation remain mysterious. Eternal inflation offers a viable alternative that is untenable in a finite universe, i.e., that a coupled system of translation and replication emerged by chance, and became the breakthrough stage from which biological evolution, centered around Darwinian selection, took off. A corollary of this hypothesis is that an RNA world, as a diverse population of replicating RNA molecules, might have never existed. In this model, the stage for Darwinian selection is set by anthropic selection of complex systems that rarely but inevitably emerge by chance in the infinite universe (multiverse). Conclusion The plausibility of different models for the origin of life on earth directly depends on the adopted cosmological scenario. In an infinite universe (multiverse), emergence of highly complex systems by chance is inevitable. Therefore, under this cosmology, an entity as complex as a coupled translation-replication system should be considered a viable breakthrough stage for the onset of biological evolution. Reviewers This article was reviewed by Eric Bapteste, David Krakauer, Sergei Maslov, and Itai Yanai. PMID:17540027

The cosmological model of eternal inflation and the transition from chance to biological evolution in the history of life.

PubMed

Koonin, Eugene V

2007-05-31

Recent developments in cosmology radically change the conception of the universe as well as the very notions of "probable" and "possible". The model of eternal inflation implies that all macroscopic histories permitted by laws of physics are repeated an infinite number of times in the infinite multiverse. In contrast to the traditional cosmological models of a single, finite universe, this worldview provides for the origin of an infinite number of complex systems by chance, even as the probability of complexity emerging in any given region of the multiverse is extremely low. This change in perspective has profound implications for the history of any phenomenon, and life on earth cannot be an exception. Origin of life is a chicken and egg problem: for biological evolution that is governed, primarily, by natural selection, to take off, efficient systems for replication and translation are required, but even barebones cores of these systems appear to be products of extensive selection. The currently favored (partial) solution is an RNA world without proteins in which replication is catalyzed by ribozymes and which serves as the cradle for the translation system. However, the RNA world faces its own hard problems as ribozyme-catalyzed RNA replication remains a hypothesis and the selective pressures behind the origin of translation remain mysterious. Eternal inflation offers a viable alternative that is untenable in a finite universe, i.e., that a coupled system of translation and replication emerged by chance, and became the breakthrough stage from which biological evolution, centered around Darwinian selection, took off. A corollary of this hypothesis is that an RNA world, as a diverse population of replicating RNA molecules, might have never existed. In this model, the stage for Darwinian selection is set by anthropic selection of complex systems that rarely but inevitably emerge by chance in the infinite universe (multiverse). The plausibility of different models for the origin of life on earth directly depends on the adopted cosmological scenario. In an infinite universe (multiverse), emergence of highly complex systems by chance is inevitable. Therefore, under this cosmology, an entity as complex as a coupled translation-replication system should be considered a viable breakthrough stage for the onset of biological evolution. This article was reviewed by Eric Bapteste, David Krakauer, Sergei Maslov, and Itai Yanai.

Characterization of Fe-leonardite complexes as novel natural iron fertilizers.

PubMed

Kovács, Krisztina; Czech, Viktória; Fodor, Ferenc; Solti, Adam; Lucena, Juan J; Santos-Rosell, Sheila; Hernández-Apaolaza, Lourdes

2013-12-18

Water-soluble humic substances (denoted by LN) extracted at alkaline pH from leonardite are proposed to be used as complexing agents to overcome micronutrient deficiencies in plants such as iron chlorosis. LN presents oxidized functional groups that can bind Fe(2+) and Fe(3+). The knowledge of the environment of Fe in the Fe-LN complexes is a key point in the studies on their efficacy as Fe fertilizers. The aim of this work was to study the Fe(2+)/Fe(3+) species formed in Fe-LN complexes with (57)Fe Mössbauer spectroscopy under different experimental conditions in relation to the Fe-complexing capacities, chemical characteristics, and efficiency to provide iron in hydroponics. A high oxidation rate of Fe(2+) to Fe(3+) was found when samples were prepared with Fe(2+), although no well-crystalline magnetically ordered ferric oxide formation could be observed in slightly acidic or neutral media. It seems to be the case that the formation of Fe(3+)-LN compounds is favored over Fe(2+)-LN compounds, although at acidic pH no complex formation between Fe(3+) and LN occurred. The Fe(2+)/Fe(3+) speciation provided by the Mössbauer data showed that Fe(2+)-LN could be efficient in hydroponics while Fe(3+)-LN is suggested to be used more effectively under calcareous soil conditions. However, according to the biological assay, Fe(3+)-LN proved to be effective as a chlorosis corrector applied to iron-deficient cucumber in nutrient solution.

Generalizing Gillespie’s Direct Method to Enable Network-Free Simulations

DOE PAGES

Suderman, Ryan T.; Mitra, Eshan David; Lin, Yen Ting; ...

2018-03-28

Gillespie’s direct method for stochastic simulation of chemical kinetics is a staple of computational systems biology research. However, the algorithm requires explicit enumeration of all reactions and all chemical species that may arise in the system. In many cases, this is not feasible due to the combinatorial explosion of reactions and species in biological networks. Rule-based modeling frameworks provide a way to exactly represent networks containing such combinatorial complexity, and generalizations of Gillespie’s direct method have been developed as simulation engines for rule-based modeling languages. Here, we provide both a high-level description of the algorithms underlying the simulation engines, termedmore » network-free simulation algorithms, and how they have been applied in systems biology research. We also define a generic rule-based modeling framework and describe a number of technical details required for adapting Gillespie’s direct method for network-free simulation. Lastly, we briefly discuss potential avenues for advancing network-free simulation and the role they continue to play in modeling dynamical systems in biology.« less

Protein aggregates as depots for the release of biologically active compounds.

PubMed

Artemova, Natalya V; Kasakov, Alexei S; Bumagina, Zoya M; Lyutova, Elena M; Gurvits, Bella Ya

2008-12-12

Protein misfolding and aggregation is one of the most serious problems in cell biology, molecular medicine, and biotechnology. Misfolded proteins interact with each other or with other proteins in non-productive or damaging ways. However, a new paradigm arises that protein aggregation may be exploited by nature to perform specific functions in different biological contexts. From this consideration, acceleration of stress-induced protein aggregation triggered by any factor resulting in the formation of soluble aggregates may have paradoxical positive consequences. Here, we suggest that amorphous aggregates can act as a source for the release of biologically active proteins after removal of stress conditions. To address this concept, we investigated the kinetics of thermal aggregation in vitro of yeast alcohol dehydrogenase (ADH) as a model substrate in the presence of two amphiphilic peptides: Arg-Phe or Ala-Phe-Lys. Using dynamic light scattering (DLS) and turbidimetry, we have demonstrated that under mild stress conditions the concentration-dependent acceleration of ADH aggregation by these peptides results in formation of large but soluble complexes of proteins prone to refolding.

Treatment of waste metalworking fluid by a hybrid ozone-biological process.

PubMed

Jagadevan, Sheeja; Graham, Nigel J; Thompson, Ian P

2013-01-15

In metal machining processes, the regulation of heat generation and lubrication at the contact point are achieved by application of a fluid referred to as metalworking fluid (MWF). MWFs inevitably become operationally exhausted with age and intensive use, which leads to compromised properties, thereby necessitating their safe disposal. Disposal of this waste through a biological route is an increasingly attractive option, since it is effective with relatively low energy demands. However, successful biological treatment is challenging since MWFs are chemically complex, and include biocides specifically to retard microbial deterioration whilst the fluids are operational. In this study remediation of the recalcitrant component of a semi-synthetic MWF by a novel hybrid ozone-bacteriological treatment, was investigated. The hybrid treatment proved to be effective and reduced the chemical oxygen demand by 72% (26.9% and 44.9% reduction after ozonation and biological oxidation respectively). Furthermore, a near-complete degradation of three non-biodegradable compounds (viz. benzotriazole, monoethanolamine, triethanolamine), commonly added as biocides and corrosion inhibitors in MWF formulations, under ozonation was observed. Copyright © 2012 Elsevier B.V. All rights reserved.

Generalizing Gillespie’s Direct Method to Enable Network-Free Simulations

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

Suderman, Ryan T.; Mitra, Eshan David; Lin, Yen Ting

Gillespie’s direct method for stochastic simulation of chemical kinetics is a staple of computational systems biology research. However, the algorithm requires explicit enumeration of all reactions and all chemical species that may arise in the system. In many cases, this is not feasible due to the combinatorial explosion of reactions and species in biological networks. Rule-based modeling frameworks provide a way to exactly represent networks containing such combinatorial complexity, and generalizations of Gillespie’s direct method have been developed as simulation engines for rule-based modeling languages. Here, we provide both a high-level description of the algorithms underlying the simulation engines, termedmore » network-free simulation algorithms, and how they have been applied in systems biology research. We also define a generic rule-based modeling framework and describe a number of technical details required for adapting Gillespie’s direct method for network-free simulation. Lastly, we briefly discuss potential avenues for advancing network-free simulation and the role they continue to play in modeling dynamical systems in biology.« less

The dual role of tumor necrosis factor (TNF) in cancer biology.

PubMed

Bertazza, Loris; Mocellin, Simone

2010-01-01

Tumor necrosis factor (TNF) is a cytokine with well known anticancer properties and is being utilized as anticancer agent for the treatment of patients with locally advanced solid tumors. However, TNF role in cancer biology is debated. In fact, in spite of the wealth of evidence supporting its antitumor activity, the cascade of molecular events underlying TNF-mediated tumor regression observed in vivo is still incompletely elucidated. Furthermore, some preclinical findings suggest that TNF may even promote cancer development and progression. With this work we intend to summarize the molecular biology of TNF (with particular regard to its tumor-related activities) and review the experimental and clinical evidence currently available describing the complex and sometime apparently conflicting relationship between this cytokine, cancer biology and antitumor therapy. We also propose a model to explain the dual effect of TNF based on the exposure time and cytokine levels reached within the tumor microenvironment. Finally, we overview recent research findings that might lead to new ways for exploiting the anticancer potential of TNF in the clinical setting.

Mix-and-match nanobiosensor design: Logical and spatial programming of biosensors using self-assembled DNA nanostructures.

PubMed

Liu, Ying; Kumar, Sriram; Taylor, Rebecca E

2018-04-06

The evergrowing need to understand and engineer biological and biochemical mechanisms has led to the emergence of the field of nanobiosensing. Structural DNA nanotechnology, encompassing methods such as DNA origami and single-stranded tiles, involves the base pairing-driven knitting of DNA into discrete one-, two-, and three-dimensional shapes at nanoscale. Such nanostructures enable a versatile design and fabrication of nanobiosensors. These systems benefit from DNA's programmability, inherent biocompatibility, and the ability to incorporate and organize functional materials such as proteins and metallic nanoparticles. In this review, we present a mix-and-match taxonomy and approach to designing nanobiosensors in which the choices of bioanalyte and transduction mechanism are fully independent of each other. We also highlight opportunities for greater complexity and programmability of these systems that are built using structural DNA nanotechnology. This article is categorized under: Implantable Materials and Surgical Technologies > Nanomaterials and Implants Diagnostic Tools > Biosensing Biology-Inspired Nanomaterials > Nucleic Acid-Based Structures Nanotechnology Approaches to Biology > Nanoscale Systems in Biology. © 2018 Wiley Periodicals, Inc.

Why genes don't count (for racial differences in health).

PubMed Central

Goodman, A H

2000-01-01

There is a paradoxical relationship between "race" and genetics. Whereas genetic data were first used to prove the validity of race, since the early 1970s they have been used to illustrate the invalidity of biological races. Indeed, race does not account for human genetic variation, which is continuous, complexly structured, constantly changing, and predominantly within "races." Despite the disproof of race-as-biology, genetic variation continues to be used to explain racial differences. Such explanations require the acceptance of 2 disproved assumptions: that genetic variation explains variation in disease and that genetic variation explains racial variation in disease. While the former is a form of geneticization, the notion that genes are the primary determinants of biology and behavior, the latter represents a form of racialization, an exaggeration of the salience of race. Using race as a proxy for genetic differences limits understandings of the complex interactions among political-economic processes, lived experiences, and human biologies. By moving beyond studies of racialized genetics, we can clarify the processes by which varied and interwoven forms of racialization and racism affect individuals "under the skin." PMID:11076233

Why genes don't count (for racial differences in health).

PubMed

Goodman, A H

2000-11-01

There is a paradoxical relationship between "race" and genetics. Whereas genetic data were first used to prove the validity of race, since the early 1970s they have been used to illustrate the invalidity of biological races. Indeed, race does not account for human genetic variation, which is continuous, complexly structured, constantly changing, and predominantly within "races." Despite the disproof of race-as-biology, genetic variation continues to be used to explain racial differences. Such explanations require the acceptance of 2 disproved assumptions: that genetic variation explains variation in disease and that genetic variation explains racial variation in disease. While the former is a form of geneticization, the notion that genes are the primary determinants of biology and behavior, the latter represents a form of racialization, an exaggeration of the salience of race. Using race as a proxy for genetic differences limits understandings of the complex interactions among political-economic processes, lived experiences, and human biologies. By moving beyond studies of racialized genetics, we can clarify the processes by which varied and interwoven forms of racialization and racism affect individuals "under the skin."

Circadian systems biology in Metazoa.

PubMed

Lin, Li-Ling; Huang, Hsuan-Cheng; Juan, Hsueh-Fen

2015-11-01

Systems biology, which can be defined as integrative biology, comprises multistage processes that can be used to understand components of complex biological systems of living organisms and provides hierarchical information to decoding life. Using systems biology approaches such as genomics, transcriptomics and proteomics, it is now possible to delineate more complicated interactions between circadian control systems and diseases. The circadian rhythm is a multiscale phenomenon existing within the body that influences numerous physiological activities such as changes in gene expression, protein turnover, metabolism and human behavior. In this review, we describe the relationships between the circadian control system and its related genes or proteins, and circadian rhythm disorders in systems biology studies. To maintain and modulate circadian oscillation, cells possess elaborative feedback loops composed of circadian core proteins that regulate the expression of other genes through their transcriptional activities. The disruption of these rhythms has been reported to be associated with diseases such as arrhythmia, obesity, insulin resistance, carcinogenesis and disruptions in natural oscillations in the control of cell growth. This review demonstrates that lifestyle is considered as a fundamental factor that modifies circadian rhythm, and the development of dysfunctions and diseases could be regulated by an underlying expression network with multiple circadian-associated signals. © The Author 2015. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Temperature-controlled micro-TLC: a versatile green chemistry and fast analytical tool for separation and preliminary screening of steroids fraction from biological and environmental samples.

PubMed

Zarzycki, Paweł K; Slączka, Magdalena M; Zarzycka, Magdalena B; Bartoszuk, Małgorzata A; Włodarczyk, Elżbieta; Baran, Michał J

2011-11-01

This paper is a continuation of our previous research focusing on development of micro-TLC methodology under temperature-controlled conditions. The main goal of present paper is to demonstrate separation and detection capability of micro-TLC technique involving simple analytical protocols without multi-steps sample pre-purification. One of the advantages of planar chromatography over its column counterpart is that each TLC run can be performed using non-previously used stationary phase. Therefore, it is possible to fractionate or separate complex samples characterized by heavy biological matrix loading. In present studies components of interest, mainly steroids, were isolated from biological samples like fish bile using single pre-treatment steps involving direct organic liquid extraction and/or deproteinization by freeze-drying method. Low-molecular mass compounds with polarity ranging from estetrol to progesterone derived from the environmental samples (lake water, untreated and treated sewage waters) were concentrated using optimized solid-phase extraction (SPE). Specific bands patterns for samples derived from surface water of the Middle Pomerania in northern part of Poland can be easily observed on obtained micro-TLC chromatograms. This approach can be useful as simple and non-expensive complementary method for fast control and screening of treated sewage water discharged by the municipal wastewater treatment plants. Moreover, our experimental results show the potential of micro-TLC as an efficient tool for retention measurements of a wide range of steroids under reversed-phase (RP) chromatographic conditions. These data can be used for further optimalization of SPE or HPLC systems working under RP conditions. Furthermore, we also demonstrated that micro-TLC based analytical approach can be applied as an effective method for the internal standard (IS) substance search. Generally, described methodology can be applied for fast fractionation or screening of the whole range of target substances as well as chemo-taxonomic studies and fingerprinting of complex mixtures, which are present in biological or environmental samples. Due to low consumption of eluent (usually 0.3-1mL/run) mainly composed of water-alcohol binary mixtures, this method can be considered as environmentally friendly and green chemistry focused analytical tool, supplementary to analytical protocols involving column chromatography or planar micro-fluidic devices. Copyright © 2011 Elsevier Ltd. All rights reserved.

Apoptotic cell death during Drosophila oogenesis is differentially increased by electromagnetic radiation depending on modulation, intensity and duration of exposure.

PubMed

Sagioglou, Niki E; Manta, Areti K; Giannarakis, Ioannis K; Skouroliakou, Aikaterini S; Margaritis, Lukas H

2016-01-01

Present generations are being repeatedly exposed to different types and doses of non-ionizing radiation (NIR) from wireless technologies (FM radio, TETRA and TV stations, GSM and UMTS phones/base stations, Wi-Fi networks, DECT phones). Although there is controversy on the published data regarding the non-thermal effects of NIR, studies have convincingly demonstrated bioeffects. Their results indicate that modulation, intensity, exposure duration and model system are important factors determining the biological response to irradiation. Attempting to address the dependence of NIR bioeffectiveness on these factors, apoptosis in the model biological system Drosophila melanogaster was studied under different exposure protocols. A signal generator was used operating alternatively under Continuous Wave (CW) or Frequency Modulation (FM) emission modes, at three power output values (10 dB, 0, -10 dB), under four carrier frequencies (100, 395, 682, 900 MHz). Newly emerged flies were exposed either acutely (6 min or 60 min on the 6th day), or repeatedly (6 min or 60 min daily for the first 6 days of their life). All exposure protocols resulted in an increase of apoptotic cell death (ACD) observed in egg chambers, even at very low electric field strengths. FM waves seem to have a stronger effect in ACD than continuous waves. Regarding intensity and temporal exposure pattern, EMF-biological tissue interaction is not linear in response. Intensity threshold for the induction of biological effects depends on frequency, modulation and temporal exposure pattern with unknown so far mechanisms. Given this complexity, translating such experimental data into possible human exposure guidelines is yet arbitrary.

Growth control of the eukaryote cell: a systems biology study in yeast.

PubMed

Castrillo, Juan I; Zeef, Leo A; Hoyle, David C; Zhang, Nianshu; Hayes, Andrew; Gardner, David Cj; Cornell, Michael J; Petty, June; Hakes, Luke; Wardleworth, Leanne; Rash, Bharat; Brown, Marie; Dunn, Warwick B; Broadhurst, David; O'Donoghue, Kerry; Hester, Svenja S; Dunkley, Tom Pj; Hart, Sarah R; Swainston, Neil; Li, Peter; Gaskell, Simon J; Paton, Norman W; Lilley, Kathryn S; Kell, Douglas B; Oliver, Stephen G

2007-01-01

Cell growth underlies many key cellular and developmental processes, yet a limited number of studies have been carried out on cell-growth regulation. Comprehensive studies at the transcriptional, proteomic and metabolic levels under defined controlled conditions are currently lacking. Metabolic control analysis is being exploited in a systems biology study of the eukaryotic cell. Using chemostat culture, we have measured the impact of changes in flux (growth rate) on the transcriptome, proteome, endometabolome and exometabolome of the yeast Saccharomyces cerevisiae. Each functional genomic level shows clear growth-rate-associated trends and discriminates between carbon-sufficient and carbon-limited conditions. Genes consistently and significantly upregulated with increasing growth rate are frequently essential and encode evolutionarily conserved proteins of known function that participate in many protein-protein interactions. In contrast, more unknown, and fewer essential, genes are downregulated with increasing growth rate; their protein products rarely interact with one another. A large proportion of yeast genes under positive growth-rate control share orthologs with other eukaryotes, including humans. Significantly, transcription of genes encoding components of the TOR complex (a major controller of eukaryotic cell growth) is not subject to growth-rate regulation. Moreover, integrative studies reveal the extent and importance of post-transcriptional control, patterns of control of metabolic fluxes at the level of enzyme synthesis, and the relevance of specific enzymatic reactions in the control of metabolic fluxes during cell growth. This work constitutes a first comprehensive systems biology study on growth-rate control in the eukaryotic cell. The results have direct implications for advanced studies on cell growth, in vivo regulation of metabolic fluxes for comprehensive metabolic engineering, and for the design of genome-scale systems biology models of the eukaryotic cell.

Growth control of the eukaryote cell: a systems biology study in yeast

PubMed Central

Castrillo, Juan I; Zeef, Leo A; Hoyle, David C; Zhang, Nianshu; Hayes, Andrew; Gardner, David CJ; Cornell, Michael J; Petty, June; Hakes, Luke; Wardleworth, Leanne; Rash, Bharat; Brown, Marie; Dunn, Warwick B; Broadhurst, David; O'Donoghue, Kerry; Hester, Svenja S; Dunkley, Tom PJ; Hart, Sarah R; Swainston, Neil; Li, Peter; Gaskell, Simon J; Paton, Norman W; Lilley, Kathryn S; Kell, Douglas B; Oliver, Stephen G

2007-01-01

Background Cell growth underlies many key cellular and developmental processes, yet a limited number of studies have been carried out on cell-growth regulation. Comprehensive studies at the transcriptional, proteomic and metabolic levels under defined controlled conditions are currently lacking. Results Metabolic control analysis is being exploited in a systems biology study of the eukaryotic cell. Using chemostat culture, we have measured the impact of changes in flux (growth rate) on the transcriptome, proteome, endometabolome and exometabolome of the yeast Saccharomyces cerevisiae. Each functional genomic level shows clear growth-rate-associated trends and discriminates between carbon-sufficient and carbon-limited conditions. Genes consistently and significantly upregulated with increasing growth rate are frequently essential and encode evolutionarily conserved proteins of known function that participate in many protein-protein interactions. In contrast, more unknown, and fewer essential, genes are downregulated with increasing growth rate; their protein products rarely interact with one another. A large proportion of yeast genes under positive growth-rate control share orthologs with other eukaryotes, including humans. Significantly, transcription of genes encoding components of the TOR complex (a major controller of eukaryotic cell growth) is not subject to growth-rate regulation. Moreover, integrative studies reveal the extent and importance of post-transcriptional control, patterns of control of metabolic fluxes at the level of enzyme synthesis, and the relevance of specific enzymatic reactions in the control of metabolic fluxes during cell growth. Conclusion This work constitutes a first comprehensive systems biology study on growth-rate control in the eukaryotic cell. The results have direct implications for advanced studies on cell growth, in vivo regulation of metabolic fluxes for comprehensive metabolic engineering, and for the design of genome-scale systems biology models of the eukaryotic cell. PMID:17439666

How can we improve problem solving in undergraduate biology? Applying lessons from 30 years of physics education research.

PubMed

Hoskinson, A-M; Caballero, M D; Knight, J K

2013-06-01

If students are to successfully grapple with authentic, complex biological problems as scientists and citizens, they need practice solving such problems during their undergraduate years. Physics education researchers have investigated student problem solving for the past three decades. Although physics and biology problems differ in structure and content, the instructional purposes align closely: explaining patterns and processes in the natural world and making predictions about physical and biological systems. In this paper, we discuss how research-supported approaches developed by physics education researchers can be adopted by biologists to enhance student problem-solving skills. First, we compare the problems that biology students are typically asked to solve with authentic, complex problems. We then describe the development of research-validated physics curricula emphasizing process skills in problem solving. We show that solving authentic, complex biology problems requires many of the same skills that practicing physicists and biologists use in representing problems, seeking relationships, making predictions, and verifying or checking solutions. We assert that acquiring these skills can help biology students become competent problem solvers. Finally, we propose how biology scholars can apply lessons from physics education in their classrooms and inspire new studies in biology education research.

Structure theorems and the dynamics of nitrogen catabolite repression in yeast

PubMed Central

Boczko, Erik M.; Cooper, Terrance G.; Gedeon, Tomas; Mischaikow, Konstantin; Murdock, Deborah G.; Pratap, Siddharth; Wells, K. Sam

2005-01-01

By using current biological understanding, a conceptually simple, but mathematically complex, model is proposed for the dynamics of the gene circuit responsible for regulating nitrogen catabolite repression (NCR) in yeast. A variety of mathematical “structure” theorems are described that allow one to determine the asymptotic dynamics of complicated systems under very weak hypotheses. It is shown that these theorems apply to several subcircuits of the full NCR circuit, most importantly to the URE2–GLN3 subcircuit that is independent of the other constituents but governs the switching behavior of the full NCR circuit under changes in nitrogen source. Under hypotheses that are fully consistent with biological data, it is proven that the dynamics of this subcircuit is simple periodic behavior in synchrony with the cell cycle. Although the current mathematical structure theorems do not apply to the full NCR circuit, extensive simulations suggest that the dynamics is constrained in much the same way as that of the URE2–GLN3 subcircuit. This finding leads to the proposal that mathematicians study genetic circuits to find new geometries for which structure theorems may exist. PMID:15814615

The Impact of Organo-Mineral Complexation on Mineral Weathering in the Soil Zone under Unsaturated Conditions

NASA Astrophysics Data System (ADS)

Michael, H. A.; Tan, F.; Yoo, K.; Imhoff, P. T.

2017-12-01

While organo-mineral complexes can protect organic matter (OM) from biodegradation, their impact on soil mineral weathering is not clear. Previous bench-scale experiments that focused on specific OM and minerals showed that the adsorption of OM to mineral surfaces accelerates the dissolution of some minerals. However, the impact of natural organo-mineral complexes on mineral dissolution under unsaturated conditions is not well known. In this study, soil samples prepared from an undisturbed forest site were used to determine mineral weathering rates under differing conditions of OM sorption to minerals. Two types of soil samples were generated: 1) soil with OM (C horizon soil from 84-100cm depth), and 2) soil without OM (the same soil as in 1) but with OM removed by heating to 350°for 24 h). Soil samples were column-packed and subjected to intermittent infiltration and drainage to mimic natural rainfall events. Each soil sample type was run in duplicate. The unsaturated condition was created by applying gas pressure to the column, and the unsaturated chemical weathering rates during each cycle were calculated from the effluent concentrations. During a single cycle, when applying the same gas pressure, soils with OM retained more moisture than OM-removed media, indicating increased water retention capacity under the impact of OM. This is consistent with the water retention data measured by evaporation experiments (HYPROP) and the dew point method (WP4C Potential Meter). Correspondingly, silicon (Si) denudation rates indicated that dissolution of silicate minerals was 2-4 times higher in OM soils, suggesting that organo-mineral complexes accelerate mineral dissolution under unsaturated conditions. When combining data from all cycles, the results showed that Si denudation rates were positively related to soil water content: denundation rate increased with increasing water content. Therefore, natural mineral chemical weathering under unsaturated conditions, while widely considered to be facilitated by biological and chemical activities, may also be affected by soil retention properties.

Spectroscopic studies and biological evaluation of some transition metal complexes of azo Schiff-base ligand derived from (1-phenyl-2,3-dimethyl-4-aminopyrazol-5-one) and 5-((4-chlorophenyl)diazenyl)-2-hydroxybenzaldehyde

NASA Astrophysics Data System (ADS)

Anitha, C.; Sheela, C. D.; Tharmaraj, P.; Sumathi, S.

2012-10-01

A series of metal(II) complexes of VO(II), Co(II), Ni(II), Cu(II) and Zn(II) have been synthesized from the azo Schiff base ligand 4-((E)-4-((E)-(4-chlorophenyl)diazenyl)-2-hydroxybenzylideneamino)-1,5-dimethyl-2-phenyl-1H-pyrazol-3(2H)-one (CDHBAP) and characterized by elemental analysis, spectral (IR, UV-Vis, 1H NMR, ESR and EI-mass), magnetic moment measurements, molar conductance, DNA, SEM, X-ray crystallography and fluorescence studies. The electronic absorption spectra and magnetic susceptibility measurements of the complexes indicate square pyramidal geometry for VO(II) and octahedral geometry for all the other complexes. The important infrared (IR) spectral bands corresponding to the active groups in the ligand and the solid complexes under investigation were studied and implies that CDHBAP is coordinated to the metal ions in a neutral tridentate manner. The redox behavior of copper(II) and vanadyl(II) complexes have been studied by cyclic voltammetry. The nuclease activity of the above metal(II) complexes shows that the complexes cleave DNA. All the synthesized complexes can serve as potential photoactive materials as indicated from their characteristic fluorescence properties. The antibacterial and antifungal activities of the synthesized ligand and its metal complexes were screened against bacterial species (Staphylococcus aureus, Salmonella typhi, Escherichia coli, Bacillus subtilis, Shigella sonnie) and fungi (Candida albicans, Aspergillus niger, Rhizoctonia bataicola). Amikacin and Ketoconozole were used as references for antibacterial and antifungal studies. The activity data show that the metal complexes have a promising biological activity comparable with the parent Schiff base ligand against bacterial and fungal species. The second harmonic generation (SHG) efficiency of the ligand was measured and the NLO (non-linear optical) properties of the ligand are expected to result in the realization of advanced optical devices in optical fiber communication (OFC) and optical computing. The SEM image of the copper(II) complex implies that the size of the particles is 1 μm.

Blood Sampling and Preparation Procedures for Proteomic Biomarker Studies of Psychiatric Disorders.

PubMed

Guest, Paul C; Rahmoune, Hassan

2017-01-01

A major challenge in proteomic biomarker discovery and validation for psychiatric diseases is the inherent biological complexity underlying these conditions. There are also many technical issues which hinder this process such as the lack of standardization in sampling, processing and storage of bio-samples in preclinical and clinical settings. This chapter describes a reproducible procedure for sampling blood serum and plasma that is specifically designed for maximizing data quality output in two-dimensional gel electrophoresis, multiplex immunoassay and mass spectrometry profiling studies.

Complex genetic diseases: controversy over the Croesus code.

PubMed

Wright, A F; Hastie, N D

2001-01-01

The polarization of views on how best to exploit new information from the Human Genome Project for medicine reflects our ignorance of the genetic architecture underlying common diseases: are susceptibility alleles common or rare, neutral or deleterious, few or many? Single-nucleotide polymorphism (SNP) technology is almost in place to dissect such diseases and to create a personalized medicine, but success is critically dependent on the biology and "Nature to be commanded must be obeyed" (Francis Bacon, 1620, Novum Organum).

New Directions in X-Ray Light Sources or Fiat Lux: what's under the dome and watching atoms with x-rays (LBNL Summer Lecture Series)

ScienceCinema

Falcone, Roger [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Advanced Light Source (ALS); Univ. of California, Berkeley, CA (United States). Dept. of Physics

2018-05-04

Summer Lecture Series 2008: Molecular movies of chemical reactions and material phase transformations need a strobe of x-rays, the penetrating light that reveals how atoms and molecules assemble in chemical and biological systems and complex materials. Roger Falcone, Director of the Advanced Light Source,will discuss a new generation of x ray sources that will enable a new science of atomic dynamics on ultrafast timescales.

Psychological models of suicide.

PubMed

Barzilay, Shira; Apter, Alan

2014-01-01

Suicidal behavior is highly complex and multifaceted. Consequent to the pioneering work of Durkheim and Freud, theoreticians have attempted to explain the biological, social, and psychological nature of suicide. The present work presents an overview and critical discussion of the most influential theoretical models of the psychological mechanisms underlying the development of suicidal behavior. All have been tested to varying degrees and have important implications for the development of therapeutic and preventive interventions. Broader and more in-depth approaches are still needed to further our understanding of suicidal phenomena.

Biological design in science classrooms

PubMed Central

Scott, Eugenie C.; Matzke, Nicholas J.

2007-01-01

Although evolutionary biology is replete with explanations for complex biological structures, scientists concerned about evolution education have been forced to confront “intelligent design” (ID), which rejects a natural origin for biological complexity. The content of ID is a subset of the claims made by the older “creation science” movement. Both creationist views contend that highly complex biological adaptations and even organisms categorically cannot result from natural causes but require a supernatural creative agent. Historically, ID arose from efforts to produce a form of creationism that would be less vulnerable to legal challenges and that would not overtly rely upon biblical literalism. Scientists do not use ID to explain nature, but because it has support from outside the scientific community, ID is nonetheless contributing substantially to a long-standing assault on the integrity of science education. PMID:17494747

The Limitations of Model-Based Experimental Design and Parameter Estimation in Sloppy Systems.

PubMed

White, Andrew; Tolman, Malachi; Thames, Howard D; Withers, Hubert Rodney; Mason, Kathy A; Transtrum, Mark K

2016-12-01

We explore the relationship among experimental design, parameter estimation, and systematic error in sloppy models. We show that the approximate nature of mathematical models poses challenges for experimental design in sloppy models. In many models of complex biological processes it is unknown what are the relevant physical mechanisms that must be included to explain system behaviors. As a consequence, models are often overly complex, with many practically unidentifiable parameters. Furthermore, which mechanisms are relevant/irrelevant vary among experiments. By selecting complementary experiments, experimental design may inadvertently make details that were ommitted from the model become relevant. When this occurs, the model will have a large systematic error and fail to give a good fit to the data. We use a simple hyper-model of model error to quantify a model's discrepancy and apply it to two models of complex biological processes (EGFR signaling and DNA repair) with optimally selected experiments. We find that although parameters may be accurately estimated, the discrepancy in the model renders it less predictive than it was in the sloppy regime where systematic error is small. We introduce the concept of a sloppy system-a sequence of models of increasing complexity that become sloppy in the limit of microscopic accuracy. We explore the limits of accurate parameter estimation in sloppy systems and argue that identifying underlying mechanisms controlling system behavior is better approached by considering a hierarchy of models of varying detail rather than focusing on parameter estimation in a single model.

Network-based integration of systems genetics data reveals pathways associated with lignocellulosic biomass accumulation and processing

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

Mizrachi, Eshchar; Verbeke, Lieven; Christie, Nanette

As a consequence of their remarkable adaptability, fast growth, and superior wood properties, eucalypt tree plantations have emerged as key renewable feedstocks (over 20 million ha globally) for the production of pulp, paper, bioenergy, and other lignocellulosic products. However, most biomass properties such as growth, wood density, and wood chemistry are complex traits that are hard to improve in long-lived perennials. Systems genetics, a process of harnessing multiple levels of component trait information (e.g., transcript, protein, and metabolite variation) in populations that vary in complex traits, has proven effective for dissecting the genetics and biology of such traits. We havemore » applied a network-based data integration (NBDI) method for a systems-level analysis of genes, processes and pathways underlying biomass and bioenergy-related traits using a segregating Eucalyptus hybrid population. We show that the integrative approach can link biologically meaningful sets of genes to complex traits and at the same time reveal the molecular basis of trait variation. Gene sets identified for related woody biomass traits were found to share regulatory loci, cluster in network neighborhoods, and exhibit enrichment for molecular functions such as xylan metabolism and cell wall development. These findings offer a framework for identifying the molecular underpinnings of complex biomass and bioprocessing-related traits. Furthermore, a more thorough understanding of the molecular basis of plant biomass traits should provide additional opportunities for the establishment of a sustainable bio-based economy.« less

Network-based integration of systems genetics data reveals pathways associated with lignocellulosic biomass accumulation and processing

DOE PAGES

Mizrachi, Eshchar; Verbeke, Lieven; Christie, Nanette; ...

2017-01-17

As a consequence of their remarkable adaptability, fast growth, and superior wood properties, eucalypt tree plantations have emerged as key renewable feedstocks (over 20 million ha globally) for the production of pulp, paper, bioenergy, and other lignocellulosic products. However, most biomass properties such as growth, wood density, and wood chemistry are complex traits that are hard to improve in long-lived perennials. Systems genetics, a process of harnessing multiple levels of component trait information (e.g., transcript, protein, and metabolite variation) in populations that vary in complex traits, has proven effective for dissecting the genetics and biology of such traits. We havemore » applied a network-based data integration (NBDI) method for a systems-level analysis of genes, processes and pathways underlying biomass and bioenergy-related traits using a segregating Eucalyptus hybrid population. We show that the integrative approach can link biologically meaningful sets of genes to complex traits and at the same time reveal the molecular basis of trait variation. Gene sets identified for related woody biomass traits were found to share regulatory loci, cluster in network neighborhoods, and exhibit enrichment for molecular functions such as xylan metabolism and cell wall development. These findings offer a framework for identifying the molecular underpinnings of complex biomass and bioprocessing-related traits. Furthermore, a more thorough understanding of the molecular basis of plant biomass traits should provide additional opportunities for the establishment of a sustainable bio-based economy.« less

Development and application of a ruthenium(II) complex-based photoluminescent and electrochemiluminescent dual-signaling probe for nitric oxide.

PubMed

Zhang, Wenzhu; Zhang, Jingmei; Zhang, Hailei; Cao, Liyan; Zhang, Run; Ye, Zhiqiang; Yuan, Jingli

2013-11-15

A ruthenium(II) complex, [Ru(bpy)2(DA-phen)](PF6)2 (bpy: 2,2'-bipyridine; DA-phen: 5,6-diamino-1,10-phenanthroline), has been developed as a photoluminescent (PL) and electrochemiluminescent (ECL) dual-signaling probe for the highly sensitive and selective detection of nitric oxide (NO) in aqueous and biological samples. Due to the presence of electron transfer process from diamino group to the excited-state of the Ru(II) complex, the PL and ECL intensities of the probe are very weak. After the probe was reacted with NO in physiological pH aqueous media under aerobic conditions to afford its triazole derivative, [Ru(bpy)2(TA-phen)](2+) (TA-phen: 5,6-triazole-1,10-phenanthroline), the electron transfer process was inhibited, so that the PL and ECL efficiency of the Ru(II) complex was remarkably increased. The PL and ECL responses of the probe to NO in physiological pH media are highly sensitive with the detection limits at low micromolar concentration level, and highly specific without the interferences of other reactive oxygen/nitrogen species (ROS/RNS) and metal ions. Moreover, the probe has good cell-membrane permeability, and can be rapidly transferred into living cells for trapping the intracellular NO molecules. These features enabled the probe to be successfully used for the monitoring of the endogenous NO production in living biological cell and tissue samples with PL and ECL dual-modes. Copyright © 2013 Elsevier B.V. All rights reserved.

Network-based integration of systems genetics data reveals pathways associated with lignocellulosic biomass accumulation and processing.

PubMed

Mizrachi, Eshchar; Verbeke, Lieven; Christie, Nanette; Fierro, Ana C; Mansfield, Shawn D; Davis, Mark F; Gjersing, Erica; Tuskan, Gerald A; Van Montagu, Marc; Van de Peer, Yves; Marchal, Kathleen; Myburg, Alexander A

2017-01-31

As a consequence of their remarkable adaptability, fast growth, and superior wood properties, eucalypt tree plantations have emerged as key renewable feedstocks (over 20 million ha globally) for the production of pulp, paper, bioenergy, and other lignocellulosic products. However, most biomass properties such as growth, wood density, and wood chemistry are complex traits that are hard to improve in long-lived perennials. Systems genetics, a process of harnessing multiple levels of component trait information (e.g., transcript, protein, and metabolite variation) in populations that vary in complex traits, has proven effective for dissecting the genetics and biology of such traits. We have applied a network-based data integration (NBDI) method for a systems-level analysis of genes, processes and pathways underlying biomass and bioenergy-related traits using a segregating Eucalyptus hybrid population. We show that the integrative approach can link biologically meaningful sets of genes to complex traits and at the same time reveal the molecular basis of trait variation. Gene sets identified for related woody biomass traits were found to share regulatory loci, cluster in network neighborhoods, and exhibit enrichment for molecular functions such as xylan metabolism and cell wall development. These findings offer a framework for identifying the molecular underpinnings of complex biomass and bioprocessing-related traits. A more thorough understanding of the molecular basis of plant biomass traits should provide additional opportunities for the establishment of a sustainable bio-based economy.

The Limitations of Model-Based Experimental Design and Parameter Estimation in Sloppy Systems

PubMed Central

Tolman, Malachi; Thames, Howard D.; Mason, Kathy A.

2016-01-01

We explore the relationship among experimental design, parameter estimation, and systematic error in sloppy models. We show that the approximate nature of mathematical models poses challenges for experimental design in sloppy models. In many models of complex biological processes it is unknown what are the relevant physical mechanisms that must be included to explain system behaviors. As a consequence, models are often overly complex, with many practically unidentifiable parameters. Furthermore, which mechanisms are relevant/irrelevant vary among experiments. By selecting complementary experiments, experimental design may inadvertently make details that were ommitted from the model become relevant. When this occurs, the model will have a large systematic error and fail to give a good fit to the data. We use a simple hyper-model of model error to quantify a model’s discrepancy and apply it to two models of complex biological processes (EGFR signaling and DNA repair) with optimally selected experiments. We find that although parameters may be accurately estimated, the discrepancy in the model renders it less predictive than it was in the sloppy regime where systematic error is small. We introduce the concept of a sloppy system–a sequence of models of increasing complexity that become sloppy in the limit of microscopic accuracy. We explore the limits of accurate parameter estimation in sloppy systems and argue that identifying underlying mechanisms controlling system behavior is better approached by considering a hierarchy of models of varying detail rather than focusing on parameter estimation in a single model. PMID:27923060

Comprehensive inventory of protein complexes in the Protein Data Bank from consistent classification of interfaces.

PubMed

Bordner, Andrew J; Gorin, Andrey A

2008-05-12

Protein-protein interactions are ubiquitous and essential for all cellular processes. High-resolution X-ray crystallographic structures of protein complexes can reveal the details of their function and provide a basis for many computational and experimental approaches. Differentiation between biological and non-biological contacts and reconstruction of the intact complex is a challenging computational problem. A successful solution can provide additional insights into the fundamental principles of biological recognition and reduce errors in many algorithms and databases utilizing interaction information extracted from the Protein Data Bank (PDB). We have developed a method for identifying protein complexes in the PDB X-ray structures by a four step procedure: (1) comprehensively collecting all protein-protein interfaces; (2) clustering similar protein-protein interfaces together; (3) estimating the probability that each cluster is relevant based on a diverse set of properties; and (4) combining these scores for each PDB entry in order to predict the complex structure. The resulting clusters of biologically relevant interfaces provide a reliable catalog of evolutionary conserved protein-protein interactions. These interfaces, as well as the predicted protein complexes, are available from the Protein Interface Server (PInS) website (see Availability and requirements section). Our method demonstrates an almost two-fold reduction of the annotation error rate as evaluated on a large benchmark set of complexes validated from the literature. We also estimate relative contributions of each interface property to the accurate discrimination of biologically relevant interfaces and discuss possible directions for further improving the prediction method.

From the Director: The Joy of Science, the Courage of Research

MedlinePlus

... Dr. Zerhouni , one that combines an appreciation of biological complexity with the fearless search for scientific knowledge. ... techniques for greater understanding of the complexity of biological systems. The one thing that has driven my ...

Cross-Linking and Mass Spectrometry Methodologies to Facilitate Structural Biology: Finding a Path through the Maze

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

Merkley, Eric D.; Cort, John R.; Adkins, Joshua N.

2013-09-01

Multiprotein complexes, rather than individual proteins, make up a large part of the biological macromolecular machinery of a cell. Understanding the structure and organization of these complexes is critical to understanding cellular function. Chemical cross-linking coupled with mass spectrometry is emerging as a complementary technique to traditional structural biology methods and can provide low-resolution structural information for a multitude of purposes, such as distance constraints in computational modeling of protein complexes. In this review, we discuss the experimental considerations for successful application of chemical cross-linking-mass spectrometry in biological studies and highlight three examples of such studies from the recent literature.more » These examples (as well as many others) illustrate the utility of a chemical cross-linking-mass spectrometry approach in facilitating structural analysis of large and challenging complexes.« less

A review of selected pumping systems in nature and engineering--potential biomimetic concepts for improving displacement pumps and pulsation damping.

PubMed

Bach, D; Schmich, F; Masselter, T; Speck, T

2015-09-03

The active transport of fluids by pumps plays an essential role in engineering and biology. Due to increasing energy costs and environmental issues, topics like noise reduction, increase of efficiency and enhanced robustness are of high importance in the development of pumps in engineering. The study compares pumps in biology and engineering and assesses biomimetic potentials for improving man-made pumping systems. To this aim, examples of common challenges, applications and current biomimetic research for state-of-the art pumps are presented. The biomimetic research is helped by the similar configuration of many positive displacement pumping systems in biology and engineering. In contrast, the configuration and underlying pumping principles for fluid dynamic pumps (FDPs) differ to a greater extent in biology and engineering. However, progress has been made for positive displacement as well as for FDPs by developing biomimetic devices with artificial muscles and cilia that improve energetic efficiency and fail-safe operation or reduce noise. The circulatory system of vertebrates holds a high biomimetic potential for the damping of pressure pulsations, a common challenge in engineering. Damping of blood pressure pulsation results from a nonlinear viscoelastic behavior of the artery walls which represent a complex composite material. The transfer of the underlying functional principle could lead to an improvement of existing technical solutions and be used to develop novel biomimetic damping solutions. To enhance efficiency or thrust of man-made fluid transportation systems, research on jet propulsion in biology has shown that a pulsed jet can be tuned to either maximize thrust or efficiency. The underlying principle has already been transferred into biomimetic applications in open channel water systems. Overall there is a high potential to learn from nature in order to improve pumping systems for challenges like the reduction of pressure pulsations, increase of jet propulsion efficiency or the reduction of wear.

Common Origins of Diverse Misconceptions: Cognitive Principles and the Development of Biology Thinking

PubMed Central

Coley, John D.; Tanner, Kimberly D.

2012-01-01

Many ideas in the biological sciences seem especially difficult to understand, learn, and teach successfully. Our goal in this feature is to explore how these difficulties may stem not from the complexity or opacity of the concepts themselves, but from the fact that they may clash with informal, intuitive, and deeply held ways of understanding the world that have been studied for decades by psychologists. We give a brief overview of the field of developmental cognitive psychology. Then, in each of the following sections, we present a number of common challenges faced by students in the biological sciences. These may be in the form of misconceptions, biases, or simply concepts that are difficult to learn and teach, and they occur at all levels of biological analysis (molecular, cellular, organismal, population, and ecosystem). We then introduce the notion of a cognitive construal and discuss specific examples of how these cognitive principles may explain what makes some misconceptions so alluring and some biological concepts so challenging for undergraduates. We will argue that seemingly unrelated misconceptions may have common origins in a single underlying cognitive construal. These ideas emerge from our own ongoing cross-disciplinary conversation, and we think that expanding this conversation to include other biological scientists and educators, as well as other cognitive scientists, could have significant utility in improving biology teaching and learning. PMID:22949417

Common origins of diverse misconceptions: cognitive principles and the development of biology thinking.

PubMed

Coley, John D; Tanner, Kimberly D

2012-01-01

Many ideas in the biological sciences seem especially difficult to understand, learn, and teach successfully. Our goal in this feature is to explore how these difficulties may stem not from the complexity or opacity of the concepts themselves, but from the fact that they may clash with informal, intuitive, and deeply held ways of understanding the world that have been studied for decades by psychologists. We give a brief overview of the field of developmental cognitive psychology. Then, in each of the following sections, we present a number of common challenges faced by students in the biological sciences. These may be in the form of misconceptions, biases, or simply concepts that are difficult to learn and teach, and they occur at all levels of biological analysis (molecular, cellular, organismal, population, and ecosystem). We then introduce the notion of a cognitive construal and discuss specific examples of how these cognitive principles may explain what makes some misconceptions so alluring and some biological concepts so challenging for undergraduates. We will argue that seemingly unrelated misconceptions may have common origins in a single underlying cognitive construal. These ideas emerge from our own ongoing cross-disciplinary conversation, and we think that expanding this conversation to include other biological scientists and educators, as well as other cognitive scientists, could have significant utility in improving biology teaching and learning.

Intracellular Peptide Self-Assembly: A Biomimetic Approach for in Situ Nanodrug Preparation.

PubMed

Du, Wei; Hu, Xiaomu; Wei, Weichen; Liang, Gaolin

2018-04-18

Most nanodrugs are preprepared by encapsulating or loading the drugs with nanocarriers (e.g., dendrimers, liposomes, micelles, and polymeric nanoparticles). However, besides the low bioavailability and fast excretion of the nanodrugs in vivo, nanocarriers often exhibit in vitro and in vivo cytotoxicity, oxidative stress, and inflammation. Self-assembly is a ubiquitous process in biology where it plays important roles and underlies the formation of a wide variety of complex biological structures. Inspired by some cellular nanostructures (e.g., actin filaments, microtubules, vesicles, and micelles) in biological systems which are formed via molecular self-assembly, in recent decades, scientists have utilized self-assembly of oligomeric peptide under specific physiological or pathological environments to in situ construct nanodrugs for lesion-targeted therapies. On one hand, peptide-based nanodrugs always have some excellent intrinsic chemical (specificity, intrinsic bioactivity, biodegradability) and physical (small size, conformation) properties. On the other hand, stimuli-regulated intracellular self-assembly of nanodrugs is quite an efficient way to accumulate the drugs in lesion location and can realize an in situ slow release of the drugs. In this review article, we provided an overview on recent design principles for intracellular peptide self-assembly and illustrate how these principles have been applied for the in situ preparation of nanodrugs at the lesion location. In the last part, we list some challenges underlying this strategy and their possible solutions. Moreover, we envision the future possible theranostic applications of this strategy.

Rhodium complexes as therapeutic agents.

PubMed

Ma, Dik-Lung; Wang, Modi; Mao, Zhifeng; Yang, Chao; Ng, Chan-Tat; Leung, Chung-Hang

2016-02-21

The landscape of inorganic medicinal chemistry has been dominated by the investigation of platinum, and to a lesser extent ruthenium, complexes over the past few decades. Recently, complexes based on other metal centers such as rhodium have attracted attention due to their tunable chemical and biological properties as well as distinct mechanisms of action. This perspective highlights recent examples of rhodium complexes that show diverse biological activities against various targets, including enzymes and protein-protein interactions.

Physicochemical and biological properties of oxovanadium(IV), cobalt(II) and nickel(II) complexes with oxydiacetate anions.

PubMed

Wyrzykowski, Dariusz; Kloska, Anna; Pranczk, Joanna; Szczepańska, Aneta; Tesmar, Aleksandra; Jacewicz, Dagmara; Pilarski, Bogusław; Chmurzyński, Lech

2015-03-01

The potentiometric and conductometric titration methods have been used to characterize the stability of series of VO(IV)-, Co(II)- and Ni(II)-oxydiacetato complexes in DMSO-water solutions containing 0-50 % (v/v) DMSO. The influence of DMSO as a co-solvent on the stability of the complexes as well as the oxydiacetic acid was evaluated. Furthermore, the reactivity of the complexes towards superoxide free radicals was assessed by employing the nitro blue tetrazolium (NBT) assay. The biological properties of the complexes were investigated in relation to their cytoprotective activity against the oxidative damage generated exogenously by using hydrogen peroxide in the Human Dermal Fibroblasts adult (HDFa) cell line as well as to their antimicrobial activity against the bacteria (Bacillus subtilis, Escherichia coli, Enterococcus faecalis, Pseudomonas aeruginosa, Staphylococcus aureus, Staphylococcus epidermidis). The relationship between physicochemical and biological properties of the complexes was discussed.

Using synthetic biology to make cells tomorrow's test tubes.

PubMed

Garcia, Hernan G; Brewster, Robert C; Phillips, Rob

2016-04-18

The main tenet of physical biology is that biological phenomena can be subject to the same quantitative and predictive understanding that physics has afforded in the context of inanimate matter. However, the inherent complexity of many of these biological processes often leads to the derivation of complex theoretical descriptions containing a plethora of unknown parameters. Such complex descriptions pose a conceptual challenge to the establishment of a solid basis for predictive biology. In this article, we present various exciting examples of how synthetic biology can be used to simplify biological systems and distill these phenomena down to their essential features as a means to enable their theoretical description. Here, synthetic biology goes beyond previous efforts to engineer nature and becomes a tool to bend nature to understand it. We discuss various recent and classic experiments featuring applications of this synthetic approach to the elucidation of problems ranging from bacteriophage infection, to transcriptional regulation in bacteria and in developing embryos, to evolution. In all of these examples, synthetic biology provides the opportunity to turn cells into the equivalent of a test tube, where biological phenomena can be reconstituted and our theoretical understanding put to test with the same ease that these same phenomena can be studied in the in vitro setting.

A tree-like Bayesian structure learning algorithm for small-sample datasets from complex biological model systems.

PubMed

Yin, Weiwei; Garimalla, Swetha; Moreno, Alberto; Galinski, Mary R; Styczynski, Mark P

2015-08-28

There are increasing efforts to bring high-throughput systems biology techniques to bear on complex animal model systems, often with a goal of learning about underlying regulatory network structures (e.g., gene regulatory networks). However, complex animal model systems typically have significant limitations on cohort sizes, number of samples, and the ability to perform follow-up and validation experiments. These constraints are particularly problematic for many current network learning approaches, which require large numbers of samples and may predict many more regulatory relationships than actually exist. Here, we test the idea that by leveraging the accuracy and efficiency of classifiers, we can construct high-quality networks that capture important interactions between variables in datasets with few samples. We start from a previously-developed tree-like Bayesian classifier and generalize its network learning approach to allow for arbitrary depth and complexity of tree-like networks. Using four diverse sample networks, we demonstrate that this approach performs consistently better at low sample sizes than the Sparse Candidate Algorithm, a representative approach for comparison because it is known to generate Bayesian networks with high positive predictive value. We develop and demonstrate a resampling-based approach to enable the identification of a viable root for the learned tree-like network, important for cases where the root of a network is not known a priori. We also develop and demonstrate an integrated resampling-based approach to the reduction of variable space for the learning of the network. Finally, we demonstrate the utility of this approach via the analysis of a transcriptional dataset of a malaria challenge in a non-human primate model system, Macaca mulatta, suggesting the potential to capture indicators of the earliest stages of cellular differentiation during leukopoiesis. We demonstrate that by starting from effective and efficient approaches for creating classifiers, we can identify interesting tree-like network structures with significant ability to capture the relationships in the training data. This approach represents a promising strategy for inferring networks with high positive predictive value under the constraint of small numbers of samples, meeting a need that will only continue to grow as more high-throughput studies are applied to complex model systems.

A novel stable 3D luminescent uranyl complex for highly efficient and sensitive recognition of Ru3+ and biomolecules

NASA Astrophysics Data System (ADS)

Tian, Hong-Hong; Chen, Liang-Ting; Zhang, Rong-Lan; Zhao, Jian-She; Liu, Chi-Yang; Weng, Ng Seik

2018-02-01

A novel highly stable 3D luminescent uranyl coordination polymer, namely {[UO2(L)]·DMA}n (1), was assembled with uranyl salt and a glycine-derivative ligand [6-(carboxymethyl-amino)-4-oxo-4,5-dihydro-[1,3,5]triazin-2-ylamino]-acetic acid (H2L) under solvothermal reaction. Besides, It was found that complex 1 possesses excellent luminescent properties, particularly the efficient selectivity and sensitivity in the recognition of Ru3+, biomacromolecule bovine serum albumin (BSA), biological small molecules dopamine (DA), ascorbic acid (AA) and uric acid (UA) in the water solution based on a "turn-off" mechanism. Accordingly, the luminescent explorations also demonstrated that complex 1 could be acted as an efficient luminescent probe with high quenching efficiency and low detection limit for selectively detecting Ru3+ and biomolecules (DA, AA, UA and BSA). It was noted that the framework structure of complex 1 still remains highly stable after quenching, which was verified by powder X-ray diffraction (PXRD).

Socio-Emotional Development Following Very Preterm Birth: Pathways to Psychopathology.

PubMed

Montagna, Anita; Nosarti, Chiara

2016-01-01

Very preterm birth (VPT; < 32 weeks of gestation) has been associated with an increased risk to develop cognitive and socio-emotional problems, as well as with increased vulnerability to psychiatric disorder, both with childhood and adult onset. Socio-emotional impairments that have been described in VPT individuals include diminished social competence and self-esteem, emotional dysregulation, shyness and timidity. However, the etiology of socio-emotional problems in VPT samples and their underlying mechanisms are far from understood. To date, research has focused on the investigation of both biological and environmental risk factors associated with socio-emotional problems, including structural and functional alterations in brain areas involved in processing emotions and social stimuli, perinatal stress and pain and parenting strategies. Considering the complex interplay of the aforementioned variables, the review attempts to elucidate the mechanisms underlying the association between very preterm birth, socio-emotional vulnerability and psychopathology. After a comprehensive overview of the socio-emotional impairments associated with VPT birth, three main models of socio-emotional development are presented and discussed. These focus on biological vulnerability, early life adversities and parenting, respectively. To conclude, a developmental framework is used to consider different pathways linking VPT birth to psychopathology, taking into account the interaction between medical, biological, and psychosocial factors.

Shifting behaviour: epigenetic reprogramming in eusocial insects.

PubMed

Patalano, Solenn; Hore, Timothy A; Reik, Wolf; Sumner, Seirian

2012-06-01

Epigenetic modifications are ancient and widely utilised mechanisms that have been recruited across fungi, plants and animals for diverse but fundamental biological functions, such as cell differentiation. Recently, a functional DNA methylation system was identified in the honeybee, where it appears to underlie queen and worker caste differentiation. This discovery, along with other insights into the epigenetics of social insects, allows provocative analogies to be drawn between insect caste differentiation and cellular differentiation, particularly in mammals. Developing larvae in social insect colonies are totipotent: they retain the ability to specialise as queens or workers, in a similar way to the totipotent cells of early embryos before they differentiate into specific cell lineages. Further, both differentiating cells and insect castes lose phenotypic plasticity by committing to their lineage, losing the ability to be readily reprogrammed. Hence, a comparison of the epigenetic mechanisms underlying lineage differentiation (and reprogramming) between cells and social insects is worthwhile. Here we develop a conceptual model of how loss and regain of phenotypic plasticity might be conserved for individual specialisation in both cells and societies. This framework forges a novel link between two fields of biological research, providing predictions for a unified approach to understanding the molecular mechanisms underlying biological complexity. Copyright © 2012 Elsevier Ltd. All rights reserved.

Concentration Dependent Ion-Protein Interaction Patterns Underlying Protein Oligomerization Behaviours

NASA Astrophysics Data System (ADS)

Batoulis, Helena; Schmidt, Thomas H.; Weber, Pascal; Schloetel, Jan-Gero; Kandt, Christian; Lang, Thorsten

2016-04-01

Salts and proteins comprise two of the basic molecular components of biological materials. Kosmotropic/chaotropic co-solvation and matching ion water affinities explain basic ionic effects on protein aggregation observed in simple solutions. However, it is unclear how these theories apply to proteins in complex biological environments and what the underlying ionic binding patterns are. Using the positive ion Ca2+ and the negatively charged membrane protein SNAP25, we studied ion effects on protein oligomerization in solution, in native membranes and in molecular dynamics (MD) simulations. We find that concentration-dependent ion-induced protein oligomerization is a fundamental chemico-physical principle applying not only to soluble but also to membrane-anchored proteins in their native environment. Oligomerization is driven by the interaction of Ca2+ ions with the carboxylate groups of aspartate and glutamate. From low up to middle concentrations, salt bridges between Ca2+ ions and two or more protein residues lead to increasingly larger oligomers, while at high concentrations oligomers disperse due to overcharging effects. The insights provide a conceptual framework at the interface of physics, chemistry and biology to explain binding of ions to charged protein surfaces on an atomistic scale, as occurring during protein solubilisation, aggregation and oligomerization both in simple solutions and membrane systems.

Socio-Emotional Development Following Very Preterm Birth: Pathways to Psychopathology

PubMed Central

Montagna, Anita; Nosarti, Chiara

2016-01-01

Very preterm birth (VPT; < 32 weeks of gestation) has been associated with an increased risk to develop cognitive and socio-emotional problems, as well as with increased vulnerability to psychiatric disorder, both with childhood and adult onset. Socio-emotional impairments that have been described in VPT individuals include diminished social competence and self-esteem, emotional dysregulation, shyness and timidity. However, the etiology of socio-emotional problems in VPT samples and their underlying mechanisms are far from understood. To date, research has focused on the investigation of both biological and environmental risk factors associated with socio-emotional problems, including structural and functional alterations in brain areas involved in processing emotions and social stimuli, perinatal stress and pain and parenting strategies. Considering the complex interplay of the aforementioned variables, the review attempts to elucidate the mechanisms underlying the association between very preterm birth, socio-emotional vulnerability and psychopathology. After a comprehensive overview of the socio-emotional impairments associated with VPT birth, three main models of socio-emotional development are presented and discussed. These focus on biological vulnerability, early life adversities and parenting, respectively. To conclude, a developmental framework is used to consider different pathways linking VPT birth to psychopathology, taking into account the interaction between medical, biological, and psychosocial factors. PMID:26903895

Physical, chemical, and metabolic state sensors expand the synthetic biology toolbox for Synechocystis sp. PCC 6803.

PubMed

Immethun, Cheryl M; DeLorenzo, Drew M; Focht, Caroline M; Gupta, Dinesh; Johnson, Charles B; Moon, Tae Seok

2017-07-01

Many under-developed organisms possess important traits that can boost the effectiveness and sustainability of microbial biotechnology. Photoautotrophic cyanobacteria can utilize the energy captured from light to fix carbon dioxide for their metabolic needs while living in environments not suited for growing crops. Various value-added compounds have been produced by cyanobacteria in the laboratory; yet, the products' titers and yields are often not industrially relevant and lag behind what have been accomplished in heterotrophic microbes. Genetic tools for biological process control are needed to take advantage of cyanobacteria's beneficial qualities, as tool development also lags behind what has been created in common heterotrophic hosts. To address this problem, we developed a suite of sensors that regulate transcription in the model cyanobacterium Synechocystis sp. PCC 6803 in response to metabolically relevant signals, including light and the cell's nitrogen status, and a family of sensors that respond to the inexpensive chemical, l-arabinose. Increasing the number of available tools enables more complex and precise control of gene expression. Expanding the synthetic biology toolbox for this cyanobacterium also improves our ability to utilize this important under-developed organism in biotechnology. Biotechnol. Bioeng. 2017;114: 1561-1569. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Multi-Dimensional Scaling based grouping of known complexes and intelligent protein complex detection.

PubMed

Rehman, Zia Ur; Idris, Adnan; Khan, Asifullah

2018-06-01

Protein-Protein Interactions (PPI) play a vital role in cellular processes and are formed because of thousands of interactions among proteins. Advancements in proteomics technologies have resulted in huge PPI datasets that need to be systematically analyzed. Protein complexes are the locally dense regions in PPI networks, which extend important role in metabolic pathways and gene regulation. In this work, a novel two-phase protein complex detection and grouping mechanism is proposed. In the first phase, topological and biological features are extracted for each complex, and prediction performance is investigated using Bagging based Ensemble classifier (PCD-BEns). Performance evaluation through cross validation shows improvement in comparison to CDIP, MCode, CFinder and PLSMC methods Second phase employs Multi-Dimensional Scaling (MDS) for the grouping of known complexes by exploring inter complex relations. It is experimentally observed that the combination of topological and biological features in the proposed approach has greatly enhanced prediction performance for protein complex detection, which may help to understand various biological processes, whereas application of MDS based exploration may assist in grouping potentially similar complexes. Copyright © 2018 Elsevier Ltd. All rights reserved.

Selection of Yeasts as Starter Cultures for Table Olives: A Step-by-Step Procedure

PubMed Central

Bevilacqua, Antonio; Corbo, Maria Rosaria; Sinigaglia, Milena

2012-01-01

The selection of yeasts intended as starters for table olives is a complex process, including a characterization step at laboratory level and a validation at lab level and factory-scale. The characterization at lab level deals with the assessment of some technological traits (growth under different temperatures and at alkaline pHs, effect of salt, and for probiotic strains the resistance to preservatives), enzymatic activities, and some new functional properties (probiotic traits, production of vitamin B-complex, biological debittering). The paper reports on these traits, focusing both on their theoretical implications and lab protocols; moreover, there are some details on predictive microbiology for yeasts of table olives and on the use of multivariate approaches to select suitable starters. PMID:22666220

The capuchin monkey as a flight candidate

NASA Technical Reports Server (NTRS)

Winget, C. M.

1977-01-01

The highly evolved nervous system and associated complex behavioral capabilities of the nonhuman primates make them good candidates for certain studies in the space environment since deleterious changes in these more complex aspects of a biological status can only be demonstrated by species which share such highly evolved features with man. Important assets which urge the selection of the capuchin monkey for space experiments include his small size, high intelligence, relative disease resistance, nutritional requirements, and lower volume life support systems. The species is particularly suited for experiments on the nervous system or on process under neural control because of the similarity of capuchin and human blood chemistry profiles and endocrine systems involved in the maintenance of homeostasis and vasomotor tone.

Coherent optimal control of photosynthetic molecules

NASA Astrophysics Data System (ADS)

Caruso, F.; Montangero, S.; Calarco, T.; Huelga, S. F.; Plenio, M. B.

2012-04-01

We demonstrate theoretically that open-loop quantum optimal control techniques can provide efficient tools for the verification of various quantum coherent transport mechanisms in natural and artificial light-harvesting complexes under realistic experimental conditions. To assess the feasibility of possible biocontrol experiments, we introduce the main settings and derive optimally shaped and robust laser pulses that allow for the faithful preparation of specified initial states (such as localized excitation or coherent superposition, i.e., propagating and nonpropagating states) of the photosystem and probe efficiently the subsequent dynamics. With these tools, different transport pathways can be discriminated, which should facilitate the elucidation of genuine quantum dynamical features of photosystems and therefore enhance our understanding of the role that coherent processes may play in actual biological complexes.

Assimilation of cyanide and cyano-derivatives by Pseudomonas pseudoalcaligenes CECT5344: from omic approaches to biotechnological applications

PubMed Central

Cabello, Purificación; Luque-Almagro, Víctor M; Olaya-Abril, Alfonso; Sáez, Lara P; Moreno-Vivián, Conrado; Roldán, M Dolores

2018-01-01

Abstract Mining, jewellery and metal-processing industries use cyanide for extracting gold and other valuable metals, generating large amounts of highly toxic wastewater. Biological treatments may be a clean alternative under the environmental point of view to the conventional physical or chemical processes used to remove cyanide and related compounds from these industrial effluents. Pseudomonas pseudoalcaligenes CECT5344 can grow under alkaline conditions using cyanide, cyanate or different nitriles as the sole nitrogen source, and is able to remove up to 12 mM total cyanide from a jewellery industry wastewater that contains cyanide free and complexed to metals. Complete genome sequencing of this bacterium has allowed the application of transcriptomic and proteomic techniques, providing a holistic view of the cyanide biodegradation process. The complex response to cyanide by the cyanotrophic bacterium P. pseudoalcaligenes CECT5344 and the potential biotechnological applications of this model organism in the bioremediation of cyanide-containing industrial residues are reviewed. PMID:29438505

Assimilation of cyanide and cyano-derivatives by Pseudomonas pseudoalcaligenes CECT5344: from omic approaches to biotechnological applications.

PubMed

Cabello, Purificación; Luque-Almagro, Víctor M; Olaya-Abril, Alfonso; Sáez, Lara P; Moreno-Vivián, Conrado; Roldán, M Dolores

2018-03-01

Mining, jewellery and metal-processing industries use cyanide for extracting gold and other valuable metals, generating large amounts of highly toxic wastewater. Biological treatments may be a clean alternative under the environmental point of view to the conventional physical or chemical processes used to remove cyanide and related compounds from these industrial effluents. Pseudomonas pseudoalcaligenes CECT5344 can grow under alkaline conditions using cyanide, cyanate or different nitriles as the sole nitrogen source, and is able to remove up to 12 mM total cyanide from a jewellery industry wastewater that contains cyanide free and complexed to metals. Complete genome sequencing of this bacterium has allowed the application of transcriptomic and proteomic techniques, providing a holistic view of the cyanide biodegradation process. The complex response to cyanide by the cyanotrophic bacterium P. pseudoalcaligenes CECT5344 and the potential biotechnological applications of this model organism in the bioremediation of cyanide-containing industrial residues are reviewed.

Celiac Disease: Role of the Epithelial Barrier.

PubMed

Schumann, Michael; Siegmund, Britta; Schulzke, Jörg D; Fromm, Michael

2017-03-01

In celiac disease (CD) a T-cell-mediated response to gluten is mounted in genetically predisposed individuals, resulting in a malabsorptive enteropathy histologically highlighted by villous atrophy and crypt hyperplasia. Recent data point to the epithelial layer as an under-rated hot spot in celiac pathophysiology to date. This overview summarizes current functional and genetic evidence on the role of the epithelial barrier in CD, consisting of the cell membranes and the apical junctional complex comprising sealing as well as ion and water channel-forming tight junction proteins and the adherens junction. Moreover, the underlying mechanisms are discussed, including apoptosis of intestinal epithelial cells, biology of intestinal stem cells, alterations in the apical junctional complex, transcytotic uptake of gluten peptides, and possible implications of a defective epithelial polarity. Current research is directed toward new treatment options for CD that are alternatives or complementary therapeutics to a gluten-free diet. Thus, strategies to target an altered epithelial barrier therapeutically also are discussed.

Complex Morphological Variability in Complex Evaporitic Systems: Thermal Spring Snails from the Chihuahuan Desert, Mexico

NASA Astrophysics Data System (ADS)

Tang, Carol M.; Roopnarine, Peter D.

2003-11-01

Thermal springs in evaporitic environments provide a unique biological laboratory in which to study natural selection and evolutionary diversification. These isolated systems may be an analogue for conditions in early Earth or Mars history. One modern example of such a system can be found in the Chihuahuan Desert of north-central Mexico. The Cuatro Cienegas basin hosts a series of thermal springs that form a complex of aquatic ecosystems under a range of environmental conditions. Using landmark-based morphometric techniques, we have quantified an unusually high level of morphological variability in the endemic gastropod Mexipyrgus from Cuatro Cienegas. The differentiation is seen both within and between hydrological systems. Our results suggest that this type of environmental system is capable of producing and maintaining a high level of morphological diversity on small spatial scales, and thus should be a target for future astrobiological research.

Forward design of a complex enzyme cascade reaction

PubMed Central

Hold, Christoph; Billerbeck, Sonja; Panke, Sven

2016-01-01

Enzymatic reaction networks are unique in that one can operate a large number of reactions under the same set of conditions concomitantly in one pot, but the nonlinear kinetics of the enzymes and the resulting system complexity have so far defeated rational design processes for the construction of such complex cascade reactions. Here we demonstrate the forward design of an in vitro 10-membered system using enzymes from highly regulated biological processes such as glycolysis. For this, we adapt the characterization of the biochemical system to the needs of classical engineering systems theory: we combine online mass spectrometry and continuous system operation to apply standard system theory input functions and to use the detailed dynamic system responses to parameterize a model of sufficient quality for forward design. This allows the facile optimization of a 10-enzyme cascade reaction for fine chemical production purposes. PMID:27677244

Synthesis and characterization of ligational behavior of curcumin drug towards some transition metal ions: Chelation effect on their thermal stability and biological activity

NASA Astrophysics Data System (ADS)

Refat, Moamen S.

2013-03-01

Complexes of Cr(III), Mn(II), Fe(III), Co(II), Ni(II), Cu(II) and Zn(II) with curcumin ligand as antitumor activity were synthesized and characterized by elemental analysis, conductometry, magnetic susceptibility, UV-Vis, IR, Raman, ESR, 1H-NMR spectroscopy, X-ray diffraction analysis of powdered samples and thermal analysis, and screened for antimicrobial activity. The IR spectral data suggested that the ligand behaves as a monobasic bidentate ligand towards the central metal ion with an oxygen's donor atoms sequence of both sbnd OH and Cdbnd O groups under keto-enol structure. From the microanalytical data, the stoichiometry of the complexes 1:2 (metal:ligand) was found. The ligand and their metal complexes were screened for antibacterial activity against Escherichia Coli, Staphylococcus aureus, Bacillus subtilis and Pseudomonas aeruginosa and fungicidal activity against Aspergillus flavus and Candida albicans.

Contribution to the meaning and understanding of anticipatory systems

NASA Astrophysics Data System (ADS)

Kljajić, Miroljub

2001-06-01

The present article discusses the cybernetic method in the modelling and understanding of complex systems from the epistemological, semantic as well as psychological point of view. Biological and organisational systems are the most important among complex systems. According to Rosen [1] anticipatory systems is another name for complex systems because, in a way, they function to anticipate the future state in order to preserve its structure and functioning. This paper demonstrates a strong analogy between Rosen's modified definition of anticipatory systems [2] and decision-making through simulation in organisational systems. The possible meaning of several models modified in the anticipatory mode will also be discussed as for example: a) The modified Verhaulst Model and its anticipatory modification in the case of the description of human behavior, b) The Prey-Predator Model, and c) The Evans Market Model under different conditions of the demand and supply function.

The yin and yang of yeast: biodiversity research and systems biology as complementary forces driving innovation in biotechnology.

PubMed

Roberts, Ian N; Oliver, Stephen G

2011-03-01

The aim of this article is to review how yeast has contributed to contemporary biotechnology and to seek underlying principles relevant to its future exploitation for human benefit. Recent advances in systems biology combined with new knowledge of genome diversity promise to make yeast the eukaryotic workhorse of choice for production of everything from probiotics and pharmaceuticals to fuels and chemicals. The ability to engineer new capabilities through introduction of controlled diversity based on a complete understanding of genome complexity and metabolic flux is key. Here, we briefly summarise the history that has led to these apparently simple organisms being employed in such a broad range of commercial applications. Subsequently, we discuss the likely consequences of current yeast research for the future of biotechnological innovation.

Plasma membrane--cortical cytoskeleton interactions: a cell biology approach with biophysical considerations.

PubMed

Kapus, András; Janmey, Paul

2013-07-01

From a biophysical standpoint, the interface between the cell membrane and the cytoskeleton is an intriguing site where a "two-dimensional fluid" interacts with an exceedingly complex three-dimensional protein meshwork. The membrane is a key regulator of the cytoskeleton, which not only provides docking sites for cytoskeletal elements through transmembrane proteins, lipid binding-based, and electrostatic interactions, but also serves as the source of the signaling events and molecules that control cytoskeletal organization and remolding. Conversely, the cytoskeleton is a key determinant of the biophysical and biochemical properties of the membrane, including its shape, tension, movement, composition, as well as the mobility, partitioning, and recycling of its constituents. From a cell biological standpoint, the membrane-cytoskeleton interplay underlies--as a central executor and/or regulator--a multitude of complex processes including chemical and mechanical signal transduction, motility/migration, endo-/exo-/phagocytosis, and other forms of membrane traffic, cell-cell, and cell-matrix adhesion. The aim of this article is to provide an overview of the tight structural and functional coupling between the membrane and the cytoskeleton. As biophysical approaches, both theoretical and experimental, proved to be instrumental for our understanding of the membrane/cytoskeleton interplay, this review will "oscillate" between the cell biological phenomena and the corresponding biophysical principles and considerations. After describing the types of connections between the membrane and the cytoskeleton, we will focus on a few key physical parameters and processes (force generation, curvature, tension, and surface charge) and will discuss how these contribute to a variety of fundamental cell biological functions. © 2013 American Physiological Society.

Weak Ergodicity Breaking of Receptor Motion in Living Cells Stemming from Random Diffusivity

NASA Astrophysics Data System (ADS)

Manzo, Carlo; Torreno-Pina, Juan A.; Massignan, Pietro; Lapeyre, Gerald J.; Lewenstein, Maciej; Garcia Parajo, Maria F.

2015-01-01

Molecular transport in living systems regulates numerous processes underlying biological function. Although many cellular components exhibit anomalous diffusion, only recently has the subdiffusive motion been associated with nonergodic behavior. These findings have stimulated new questions for their implications in statistical mechanics and cell biology. Is nonergodicity a common strategy shared by living systems? Which physical mechanisms generate it? What are its implications for biological function? Here, we use single-particle tracking to demonstrate that the motion of dendritic cell-specific intercellular adhesion molecule 3-grabbing nonintegrin (DC-SIGN), a receptor with unique pathogen-recognition capabilities, reveals nonergodic subdiffusion on living-cell membranes In contrast to previous studies, this behavior is incompatible with transient immobilization, and, therefore, it cannot be interpreted according to continuous-time random-walk theory. We show that the receptor undergoes changes of diffusivity, consistent with the current view of the cell membrane as a highly dynamic and diverse environment. Simulations based on a model of an ordinary random walk in complex media quantitatively reproduce all our observations, pointing toward diffusion heterogeneity as the cause of DC-SIGN behavior. By studying different receptor mutants, we further correlate receptor motion to its molecular structure, thus establishing a strong link between nonergodicity and biological function. These results underscore the role of disorder in cell membranes and its connection with function regulation. Because of its generality, our approach offers a framework to interpret anomalous transport in other complex media where dynamic heterogeneity might play a major role, such as those found, e.g., in soft condensed matter, geology, and ecology.

Joint position statement by “Sociedad Española de Patología Digestiva” (Spanish Society of Gastroenterology) and “Sociedad Española de Farmacología” (Spanish Society of Pharmacology) on biosimilar therapy for inflammatory bowel disease.

PubMed

Argüelles-Arias, Federico; Barreiro-de-Acosta, Manuel; Carballo, Fernando; Hinojosa, Joaquín; Tejerina, Teresa

2013-01-01

Biological drugs or biopharmaceutical products, manufactured with or from living organisms using biotechnology, have represented a therapeutic revolution for the control of inflammatory bowel disease (IBD). At present, in this indication and in our country, only two biological are approved, infliximab (IFX) and adalimumab (ADA), both of them monoclonal antibodies against tumor necrosis factor alpha. Effectiveness data are strong for both therapies, with maximum levels of scientific evidence.The upcoming expiry date for these biologicals´ patents has allowed the potential marketing of so-called biosimilar agents for the IBD indication. While biosimilars are conceptually for biological what generics are for chemical drugs, the structural complexity of biosimilars and their biological and manufacturing variability lead to consider validation processes for these two types in humans as highly differential. Thus, in our setting, under the coverage of "Agencia Española del Medicamento y Productos Sanitarios (AEMPS)" (Spanish Agency of Medicines and Medical Devices), guidelines issued by the European Medicines Agency (EMA) are to be applied, which states that a number of stages or steps must be overcome in order to obtain approval for a biosimilar agent.However, despite the presence of these recommendations by EMA, which must be met by a biosimilar in order to be licensed in our marketplace, relevant uncertainties persist that only future decisions by EMA and AEMPS may clarify. The present stance by our task force is that biosimilar development should be undertaken according to established regulations, thus certifying their efficacy and safety. Similarly, this task force considers that results obtained from studies in rheumatoid arthritis (RA) should not be extrapolated to IBD since the biological variability of these complex structures will not ensure a lack of noticeable changes in efficacy and safety.

NNAlign: A Web-Based Prediction Method Allowing Non-Expert End-User Discovery of Sequence Motifs in Quantitative Peptide Data

PubMed Central

Andreatta, Massimo; Schafer-Nielsen, Claus; Lund, Ole; Buus, Søren; Nielsen, Morten

2011-01-01

Recent advances in high-throughput technologies have made it possible to generate both gene and protein sequence data at an unprecedented rate and scale thereby enabling entirely new “omics”-based approaches towards the analysis of complex biological processes. However, the amount and complexity of data that even a single experiment can produce seriously challenges researchers with limited bioinformatics expertise, who need to handle, analyze and interpret the data before it can be understood in a biological context. Thus, there is an unmet need for tools allowing non-bioinformatics users to interpret large data sets. We have recently developed a method, NNAlign, which is generally applicable to any biological problem where quantitative peptide data is available. This method efficiently identifies underlying sequence patterns by simultaneously aligning peptide sequences and identifying motifs associated with quantitative readouts. Here, we provide a web-based implementation of NNAlign allowing non-expert end-users to submit their data (optionally adjusting method parameters), and in return receive a trained method (including a visual representation of the identified motif) that subsequently can be used as prediction method and applied to unknown proteins/peptides. We have successfully applied this method to several different data sets including peptide microarray-derived sets containing more than 100,000 data points. NNAlign is available online at http://www.cbs.dtu.dk/services/NNAlign. PMID:22073191

NNAlign: a web-based prediction method allowing non-expert end-user discovery of sequence motifs in quantitative peptide data.

PubMed

Andreatta, Massimo; Schafer-Nielsen, Claus; Lund, Ole; Buus, Søren; Nielsen, Morten

2011-01-01

Recent advances in high-throughput technologies have made it possible to generate both gene and protein sequence data at an unprecedented rate and scale thereby enabling entirely new "omics"-based approaches towards the analysis of complex biological processes. However, the amount and complexity of data that even a single experiment can produce seriously challenges researchers with limited bioinformatics expertise, who need to handle, analyze and interpret the data before it can be understood in a biological context. Thus, there is an unmet need for tools allowing non-bioinformatics users to interpret large data sets. We have recently developed a method, NNAlign, which is generally applicable to any biological problem where quantitative peptide data is available. This method efficiently identifies underlying sequence patterns by simultaneously aligning peptide sequences and identifying motifs associated with quantitative readouts. Here, we provide a web-based implementation of NNAlign allowing non-expert end-users to submit their data (optionally adjusting method parameters), and in return receive a trained method (including a visual representation of the identified motif) that subsequently can be used as prediction method and applied to unknown proteins/peptides. We have successfully applied this method to several different data sets including peptide microarray-derived sets containing more than 100,000 data points. NNAlign is available online at http://www.cbs.dtu.dk/services/NNAlign.

Monitoring the Spatiotemporal Activities of miRNAs in Small Animal Models Using Molecular Imaging Modalities

PubMed Central

Baril, Patrick; Ezzine, Safia; Pichon, Chantal

2015-01-01

MicroRNAs (miRNAs) are a class of small non-coding RNAs that regulate gene expression by binding mRNA targets via sequence complementary inducing translational repression and/or mRNA degradation. A current challenge in the field of miRNA biology is to understand the functionality of miRNAs under physiopathological conditions. Recent evidence indicates that miRNA expression is more complex than simple regulation at the transcriptional level. MiRNAs undergo complex post-transcriptional regulations such miRNA processing, editing, accumulation and re-cycling within P-bodies. They are dynamically regulated and have a well-orchestrated spatiotemporal localization pattern. Real-time and spatio-temporal analyses of miRNA expression are difficult to evaluate and often underestimated. Therefore, important information connecting miRNA expression and function can be lost. Conventional miRNA profiling methods such as Northern blot, real-time PCR, microarray, in situ hybridization and deep sequencing continue to contribute to our knowledge of miRNA biology. However, these methods can seldom shed light on the spatiotemporal organization and function of miRNAs in real-time. Non-invasive molecular imaging methods have the potential to address these issues and are thus attracting increasing attention. This paper reviews the state-of-the-art of methods used to detect miRNAs and discusses their contribution in the emerging field of miRNA biology and therapy. PMID:25749473

Monitoring the spatiotemporal activities of miRNAs in small animal models using molecular imaging modalities.

PubMed

Baril, Patrick; Ezzine, Safia; Pichon, Chantal

2015-03-04

MicroRNAs (miRNAs) are a class of small non-coding RNAs that regulate gene expression by binding mRNA targets via sequence complementary inducing translational repression and/or mRNA degradation. A current challenge in the field of miRNA biology is to understand the functionality of miRNAs under physiopathological conditions. Recent evidence indicates that miRNA expression is more complex than simple regulation at the transcriptional level. MiRNAs undergo complex post-transcriptional regulations such miRNA processing, editing, accumulation and re-cycling within P-bodies. They are dynamically regulated and have a well-orchestrated spatiotemporal localization pattern. Real-time and spatio-temporal analyses of miRNA expression are difficult to evaluate and often underestimated. Therefore, important information connecting miRNA expression and function can be lost. Conventional miRNA profiling methods such as Northern blot, real-time PCR, microarray, in situ hybridization and deep sequencing continue to contribute to our knowledge of miRNA biology. However, these methods can seldom shed light on the spatiotemporal organization and function of miRNAs in real-time. Non-invasive molecular imaging methods have the potential to address these issues and are thus attracting increasing attention. This paper reviews the state-of-the-art of methods used to detect miRNAs and discusses their contribution in the emerging field of miRNA biology and therapy.

Dissecting social cell biology and tumors using Drosophila genetics.

PubMed

Pastor-Pareja, José Carlos; Xu, Tian

2013-01-01

Cancer was seen for a long time as a strictly cell-autonomous process in which oncogenes and tumor-suppressor mutations drive clonal cell expansions. Research in the past decade, however, paints a more integrative picture of communication and interplay between neighboring cells in tissues. It is increasingly clear as well that tumors, far from being homogenous lumps of cells, consist of different cell types that function together as complex tissue-level communities. The repertoire of interactive cell behaviors and the quantity of cellular players involved call for a social cell biology that investigates these interactions. Research into this social cell biology is critical for understanding development of normal and tumoral tissues. Such complex social cell biology interactions can be parsed in Drosophila. Techniques in Drosophila for analysis of gene function and clonal behavior allow us to generate tumors and dissect their complex interactive biology with cellular resolution. Here, we review recent Drosophila research aimed at understanding tissue-level biology and social cell interactions in tumors, highlighting the principles these studies reveal.

Self-assembly of polyelectrolyte surfactant complexes using large scale MD simulation

NASA Astrophysics Data System (ADS)

Goswami, Monojoy; Sumpter, Bobby

2014-03-01

Polyelectrolytes (PE) and surfactants are known to form interesting structures with varied properties in aqueous solutions. The morphological details of the PE-surfactant complexes depend on a combination of polymer backbone, electrostatic interactions and hydrophobic interactions. We study the self-assembly of cationic PE and anionic surfactants complexes in dilute condition. The importance of such complexes of PE with oppositely charged surfactants can be found in biological systems, such as immobilization of enzymes in polyelectrolyte complexes or nonspecific association of DNA with protein. Many useful properties of PE surfactant complexes come from the highly ordered structures of surfactant self-assembly inside the PE aggregate which has applications in industry. We do large scale molecular dynamics simulation using LAMMPS to understand the structure and dynamics of PE-surfactant systems. Our investigation shows highly ordered pearl-necklace structures that have been observed experimentally in biological systems. We investigate many different properties of PE-surfactant complexation for different parameter ranges that are useful for pharmaceutical, engineering and biological applications.

Epigenetic Mechanisms Impacting Aging: A Focus on Histone Levels and Telomeres

PubMed Central

Song, Shufei

2018-01-01

Aging and age-related diseases pose some of the most significant and difficult challenges to modern society as well as to the scientific and medical communities. Biological aging is a complex, and, under normal circumstances, seemingly irreversible collection of processes that involves numerous underlying mechanisms. Among these, chromatin-based processes have emerged as major regulators of cellular and organismal aging. These include DNA methylation, histone modifications, nucleosome positioning, and telomere regulation, including how these are influenced by environmental factors such as diet. Here we focus on two interconnected categories of chromatin-based mechanisms impacting aging: those involving changes in the levels of histones or in the functions of telomeres. PMID:29642537

Fine Tuning Gene Expression: The Epigenome

PubMed Central

Mohtat, Davoud; Susztak, Katalin

2011-01-01

An epigenetic trait is a stably inherited phenotype resulting from changes in a chromosome without alterations in the DNA sequence. Epigenetic modifications, such as; DNA methylation, together with covalent modification of histones, are thought to alter chromatin density and accessibility of the DNA to cellular machinery, thereby modulating the transcriptional potential of the underlying DNA sequence. As epigenetic marks under environmental influence, epigenetics provides an added layer of variation that might mediate the relationship between genotype and internal and external environmental factors. Integration of our knowledge in genetics, epigenomics and genomics with the use of systems biology tools may present investigators with new powerful tools to study many complex human diseases such as kidney disease. PMID:21044758

Single molecule data under scrutiny. Comment on "Extracting physics of life at the molecular level: A review of single-molecule data analyses" by W. Colomb & S.K. Sarkar

NASA Astrophysics Data System (ADS)

Wohland, Thorsten

2015-06-01

Single Molecule Detection and Spectroscopy have grown from their first beginnings into mainstream, mature research areas that are widely applied in the biological sciences. However, despite the advances in technology and the application of many single molecule techniques even in in vivo settings, the data analysis of single molecule experiments is complicated by noise, systematic errors, and complex underlying processes that are only incompletely understood. Colomb and Sarkar provide in this issue an overview of single molecule experiments and the accompanying problems in data analysis, which have to be overcome for a proper interpretation of the experiments [1].

Study of solid/liquid and solid/gas interfaces in Cu-isoleucine complex by surface X-ray diffraction

NASA Astrophysics Data System (ADS)

Ferrer, Pilar; Rubio-Zuazo, Juan; Castro, German R.

2013-02-01

The enzymes could be understood like structures formed by amino acids bonded with metals, which act as active sites. The research on the coordination of metal-amino acid complexes will bring light on the behavior of metal enzymes, due to the close relation existing between the atomic structure and the functionality. The Cu-isoleucine bond is considered as a good model system to attain a better insight into the characteristics of naturally occurring copper metalloproteins. The surface structure of metal-amino acid complex could be considered as a more realistic model for real systems under biologic working conditions, since the molecular packing is decreased. In the surface, the structural constrains are reduced, keeping the structural capability of surface complex to change as a function of the surrounding environment. In this work, we present a surface X-ray diffraction study on Cu-isoleucine complex under different ambient conditions. Cu(Ile)2 crystals of about 5 mm × 5 mm × 1 mm have been growth, by seeding method in a supersaturated solution, presenting a surface of high quality. The sample for the surface diffraction study was mounted on a cell specially designed for solid/liquid or solid/gas interface analysis. The Cu-isoleucine crystal was measured under a protective dry N2 gas flow and in contact with a saturated metal amino acid solution. The bulk and the surface signals were compared, showing different atomic structures. In both cases, from surface diffraction data, it is observed that the atomic structure of the top layer undergoes a clear structural deformation. A non-uniform surface relaxation is observed producing an inhomogeneous displacement of the surface atoms towards the surface normal.

Complexity: the organizing principle at the interface of biological (dis)order.

PubMed

Bhat, Ramray; Pally, Dharma

2017-07-01

The term complexity means several things to biologists.When qualifying morphological phenotype, on the one hand, it is used to signify the sheer complicatedness of living systems, especially as a result of the multicomponent aspect of biological form. On the other hand, it has been used to represent the intricate nature of the connections between constituents that make up form: a more process-based explanation. In the context of evolutionary arguments, complexity has been defined, in a quantifiable fashion, as the amount of information, an informatic template such as a sequence of nucleotides or amino acids stores about its environment. In this perspective, we begin with a brief review of the history of complexity theory. We then introduce a developmental and an evolutionary understanding of what it means for biological systems to be complex.We propose that the complexity of living systems can be understood through two interdependent structural properties: multiscalarity of interconstituent mechanisms and excitability of the biological materials. The answer to whether a system becomes more or less complex over time depends on the potential for its constituents to interact in novel ways and combinations to give rise to new structures and functions, as well as on the evolution of excitable properties that would facilitate the exploration of interconstituent organization in the context of their microenvironments and macroenvironments.

Leo Szilard Lectureship Award Talk - Universal Scaling Laws from Cells to Cities; A Physicist's Search for Quantitative, Unified Theories of Biological and Social Structure and Dynamics

NASA Astrophysics Data System (ADS)

West, Geoffrey

2013-04-01

Many of the most challenging, exciting and profound questions facing science and society, from the origins of life to global sustainability, fall under the banner of ``complex adaptive systems.'' This talk explores how scaling can be used to begin to develop physics-inspired quantitative, predictive, coarse-grained theories for understanding their structure, dynamics and organization based on underlying mathematisable principles. Remarkably, most physiological, organisational and life history phenomena in biology and socio-economic systems scale in a simple and ``universal'' fashion: metabolic rate scales approximately as the 3/4-power of mass over 27 orders of magnitude from complex molecules to the largest organisms. Time-scales (such as lifespans and growth-rates) and sizes (such as genome lengths and RNA densities) scale with exponents which are typically simple multiples of 1/4, suggesting that fundamental constraints underlie much of the generic structure and dynamics of living systems. These scaling laws follow from dynamical and geometrical properties of space-filling, fractal-like, hierarchical branching networks, presumed optimised by natural selection. This leads to a general framework that potentially captures essential features of diverse systems including vasculature, ontogenetic growth, cancer, aging and mortality, sleep, cell size, and DNA nucleotide substitution rates. Cities and companies also scale: wages, profits, patents, crime, disease, pollution, road lengths scale similarly across the globe, reflecting underlying universal social network dynamics which point to general principles of organization transcending their individuality. These have dramatic implications for global sustainability: innovation and wealth creation that fuel social systems, left unchecked, potentially sow the seeds for their inevitable collapse.

Super-multiplex vibrational imaging

NASA Astrophysics Data System (ADS)

Wei, Lu; Chen, Zhixing; Shi, Lixue; Long, Rong; Anzalone, Andrew V.; Zhang, Luyuan; Hu, Fanghao; Yuste, Rafael; Cornish, Virginia W.; Min, Wei

2017-04-01

The ability to visualize directly a large number of distinct molecular species inside cells is increasingly essential for understanding complex systems and processes. Even though existing methods have successfully been used to explore structure-function relationships in nervous systems, to profile RNA in situ, to reveal the heterogeneity of tumour microenvironments and to study dynamic macromolecular assembly, it remains challenging to image many species with high selectivity and sensitivity under biological conditions. For instance, fluorescence microscopy faces a ‘colour barrier’, owing to the intrinsically broad (about 1,500 inverse centimetres) and featureless nature of fluorescence spectra that limits the number of resolvable colours to two to five (or seven to nine if using complicated instrumentation and analysis). Spontaneous Raman microscopy probes vibrational transitions with much narrower resonances (peak width of about 10 inverse centimetres) and so does not suffer from this problem, but weak signals make many bio-imaging applications impossible. Although surface-enhanced Raman scattering offers high sensitivity and multiplicity, it cannot be readily used to image specific molecular targets quantitatively inside live cells. Here we use stimulated Raman scattering under electronic pre-resonance conditions to image target molecules inside living cells with very high vibrational selectivity and sensitivity (down to 250 nanomolar with a time constant of 1 millisecond). We create a palette of triple-bond-conjugated near-infrared dyes that each displays a single peak in the cell-silent Raman spectral window; when combined with available fluorescent probes, this palette provides 24 resolvable colours, with the potential for further expansion. Proof-of-principle experiments on neuronal co-cultures and brain tissues reveal cell-type-dependent heterogeneities in DNA and protein metabolism under physiological and pathological conditions, underscoring the potential of this 24-colour (super-multiplex) optical imaging approach for elucidating intricate interactions in complex biological systems.

Super-multiplex vibrational imaging

PubMed Central

Wei, Lu; Chen, Zhixing; Shi, Lixue; Long, Rong; Anzalone, Andrew V.; Zhang, Luyuan; Hu, Fanghao; Yuste, Rafael; Cornish, Virginia W.; Min, Wei

2017-01-01

The ability to directly visualize a large number of distinct molecular species inside cells is increasingly essential for understanding complex systems and processes. Even though existing methods have been used successfully to explore structural-functional relationships in nervous systems, profile RNA in situ, reveal tumor microenvironment heterogeneity or study dynamic macromolecular assembly1–4, it remains challenging to image many species with high selectivity and sensitivity under biological conditions. For instance, fluorescence microscopy faces a “color barrier” due to the intrinsically broad (~1500 cm−1) and featureless nature of fluorescence spectra5 that limits the number of resolvable colors to 2 to 5 (or 7-9 if using complicated instrumentation and analysis)6–8. Spontaneous Raman microscopy probes vibrational transitions with much narrower resonances (peak width ~10 cm−1) and thus doesn’t suffer this problem, but its feeble signals make many demanding bio-imaging applications impossible. And while surface-enhanced Raman scattering offers remarkable sensitivity and multiplicity, it cannot be readily used to quantitatively image specific molecular targets inside live cells9. Here we show that carrying out stimulated Raman scattering under electronic pre-resonance conditions (epr-SRS) enables imaging with exquisite vibrational selectivity and sensitivity (down to 250 nM with 1-ms) in living cells. We also create a palette of triple-bond-conjugated near-infrared dyes that each display a single epr-SRS peak in the cell-silent spectral window, and that with available fluorescent probes give 24 resolvable colors with potential for further expansion. Proof-of-principle experiments on neuronal co-cultures and brain tissues reveal cell-type dependent heterogeneities in DNA and protein metabolism under physiological and pathological conditions, underscoring the potential of this super-multiplex optical imaging approach for untangling intricate interactions in complex biological systems. PMID:28424513

CellTree: an R/bioconductor package to infer the hierarchical structure of cell populations from single-cell RNA-seq data.

PubMed

duVerle, David A; Yotsukura, Sohiya; Nomura, Seitaro; Aburatani, Hiroyuki; Tsuda, Koji

2016-09-13

Single-cell RNA sequencing is fast becoming one the standard method for gene expression measurement, providing unique insights into cellular processes. A number of methods, based on general dimensionality reduction techniques, have been suggested to help infer and visualise the underlying structure of cell populations from single-cell expression levels, yet their models generally lack proper biological grounding and struggle at identifying complex differentiation paths. Here we introduce cellTree: an R/Bioconductor package that uses a novel statistical approach, based on document analysis techniques, to produce tree structures outlining the hierarchical relationship between single-cell samples, while identifying latent groups of genes that can provide biological insights. With cellTree, we provide experimentalists with an easy-to-use tool, based on statistically and biologically-sound algorithms, to efficiently explore and visualise single-cell RNA data. The cellTree package is publicly available in the online Bionconductor repository at: http://bioconductor.org/packages/cellTree/ .

Installing logic-gate responses to a variety of biological substances in supramolecular hydrogel-enzyme hybrids.

PubMed

Ikeda, Masato; Tanida, Tatsuya; Yoshii, Tatsuyuki; Kurotani, Kazuya; Onogi, Shoji; Urayama, Kenji; Hamachi, Itaru

2014-06-01

Soft materials that exhibit stimuli-responsive behaviour under aqueous conditions (such as supramolecular hydrogels composed of self-assembled nanofibres) have many potential biological applications. However, designing a macroscopic response to structurally complex biochemical stimuli in these materials still remains a challenge. Here we show that redox-responsive peptide-based hydrogels have the ability to encapsulate enzymes and still retain their activities. Moreover, cooperative coupling of enzymatic reactions with the gel response enables us to construct unique stimuli-responsive soft materials capable of sensing a variety of disease-related biomarkers. The programmable gel-sol response (even to biological samples) is visible to the naked eye. Furthermore, we built Boolean logic gates (OR and AND) into the hydrogel-enzyme hybrid materials, which were able to sense simultaneously plural specific biochemicals and execute a controlled drug release in accordance with the logic operation. The intelligent soft materials that we have developed may prove valuable in future medical diagnostics or treatments.

Biomimetics: lessons from nature--an overview.

PubMed

Bhushan, Bharat

2009-04-28

Nature has developed materials, objects and processes that function from the macroscale to the nanoscale. These have gone through evolution over 3.8 Gyr. The emerging field of biomimetics allows one to mimic biology or nature to develop nanomaterials, nanodevices and processes. Properties of biological materials and surfaces result from a complex interplay between surface morphology and physical and chemical properties. Hierarchical structures with dimensions of features ranging from the macroscale to the nanoscale are extremely common in nature to provide properties of interest. Molecular-scale devices, superhydrophobicity, self-cleaning, drag reduction in fluid flow, energy conversion and conservation, high adhesion, reversible adhesion, aerodynamic lift, materials and fibres with high mechanical strength, biological self-assembly, antireflection, structural coloration, thermal insulation, self-healing and sensory-aid mechanisms are some of the examples found in nature that are of commercial interest. This paper provides a broad overview of the various objects and processes of interest found in nature and applications under development or available in the marketplace.

Biochemomechanical poroelastic theory of avascular tumor growth

NASA Astrophysics Data System (ADS)

Xue, Shi-Lei; Li, Bo; Feng, Xi-Qiao; Gao, Huajian

2016-09-01

Tumor growth is a complex process involving genetic mutations, biochemical regulations, and mechanical deformations. In this paper, a thermodynamics-based nonlinear poroelastic theory is established to model the coupling among the mechanical, chemical, and biological mechanisms governing avascular tumor growth. A volumetric growth law accounting for mechano-chemo-biological coupled effects is proposed to describe the development of solid tumors. The regulating roles of stresses and nutrient transport in the tumor growth are revealed under different environmental constraints. We show that the mechano-chemo-biological coupling triggers anisotropic and heterogeneous growth, leading to the formation of layered structures in a growing tumor. There exists a steady state in which tumor growth is balanced by resorption. The influence of external confinements on tumor growth is also examined. A phase diagram is constructed to illustrate how the elastic modulus and thickness of the confinements jointly dictate the steady state of tumor volume. Qualitative and quantitative agreements with experimental observations indicate the developed model is capable of capturing the essential features of avascular tumor growth in various environments.

The dynamics of food chains under climate change and nutrient enrichment.

PubMed

Binzer, Amrei; Guill, Christian; Brose, Ulrich; Rall, Björn C

2012-11-05

Warming has profound effects on biological rates such as metabolism, growth, feeding and death of organisms, eventually affecting their ability to survive. Using a nonlinear bioenergetic population-dynamic model that accounts for temperature and body-mass dependencies of biological rates, we analysed the individual and interactive effects of increasing temperature and nutrient enrichment on the dynamics of a three-species food chain. At low temperatures, warming counteracts the destabilizing effects of enrichment by both bottom-up (via the carrying capacity) and top-down (via biological rates) mechanisms. Together with increasing consumer body masses, warming increases the system tolerance to fertilization. Simultaneously, warming increases the risk of starvation for large species in low-fertility systems. This effect can be counteracted by increased fertilization. In combination, therefore, two main drivers of global change and biodiversity loss can have positive and negative effects on food chain stability. Our model incorporates the most recent empirical data and may thus be used as the basis for more complex forecasting models incorporating food-web structure.

Systems medicine: a new approach to clinical practice.

PubMed

Cardinal-Fernández, Pablo; Nin, Nicolás; Ruíz-Cabello, Jesús; Lorente, José A

2014-10-01

Most respiratory diseases are considered complex diseases as their susceptibility and outcomes are determined by the interaction between host-dependent factors (genetic factors, comorbidities, etc.) and environmental factors (exposure to microorganisms or allergens, treatments received, etc.) The reductionist approach in the study of diseases has been of fundamental importance for the understanding of the different components of a system. Systems biology or systems medicine is a complementary approach aimed at analyzing the interactions between the different components within one organizational level (genome, transcriptome, proteome), and then between the different levels. Systems medicine is currently used for the interpretation and understanding of the pathogenesis and pathophysiology of different diseases, biomarker discovery, design of innovative therapeutic targets, and the drawing up of computational models for different biological processes. In this review we discuss the most relevant concepts of the theory underlying systems medicine, as well as its applications in the various biological processes in humans. Copyright © 2013 SEPAR. Published by Elsevier Espana. All rights reserved.

ProtocolNavigator: emulation-based software for the design, documentation and reproduction biological experiments.

PubMed

Khan, Imtiaz A; Fraser, Adam; Bray, Mark-Anthony; Smith, Paul J; White, Nick S; Carpenter, Anne E; Errington, Rachel J

2014-12-01

Experimental reproducibility is fundamental to the progress of science. Irreproducible research decreases the efficiency of basic biological research and drug discovery and impedes experimental data reuse. A major contributing factor to irreproducibility is difficulty in interpreting complex experimental methodologies and designs from written text and in assessing variations among different experiments. Current bioinformatics initiatives either are focused on computational research reproducibility (i.e. data analysis) or laboratory information management systems. Here, we present a software tool, ProtocolNavigator, which addresses the largely overlooked challenges of interpretation and assessment. It provides a biologist-friendly open-source emulation-based tool for designing, documenting and reproducing biological experiments. ProtocolNavigator was implemented in Python 2.7, using the wx module to build the graphical user interface. It is a platform-independent software and freely available from http://protocolnavigator.org/index.html under the GPL v2 license. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Is chondroitin sulfate responsible for the biological effects attributed to the GC protein-derived Macrophage Activating Factor (GcMAF)?

PubMed

Ruggiero, Marco; Reinwald, Heinz; Pacini, Stefania

2016-09-01

We hypothesize that a plasma glycosaminoglycan, chondroitin sulfate, may be responsible for the biological and clinical effects attributed to the Gc protein-derived Macrophage Activating Factor (GcMAF), a protein that is extracted from human blood. Thus, Gc protein binds chondroitin sulfate on the cell surface and such an interaction may occur also in blood, colostrum and milk. This interpretation would solve the inconsistencies encountered in explaining the effects of GcMAF in vitro and in vivo. According to our model, the Gc protein or the GcMAF bind to chondroitin sulfate both on the cell surface and in bodily fluids, and the resulting multimolecular complexes, under the form of oligomers trigger a transmembrane signal or, alternatively, are internalized and convey the signal directly to the nucleus thus eliciting the diverse biological effects observed for both GcMAF and chondroitin sulfate. Copyright © 2016 Elsevier Ltd. All rights reserved.

PyDREAM: high-dimensional parameter inference for biological models in python.

PubMed

Shockley, Erin M; Vrugt, Jasper A; Lopez, Carlos F; Valencia, Alfonso

2018-02-15

Biological models contain many parameters whose values are difficult to measure directly via experimentation and therefore require calibration against experimental data. Markov chain Monte Carlo (MCMC) methods are suitable to estimate multivariate posterior model parameter distributions, but these methods may exhibit slow or premature convergence in high-dimensional search spaces. Here, we present PyDREAM, a Python implementation of the (Multiple-Try) Differential Evolution Adaptive Metropolis [DREAM(ZS)] algorithm developed by Vrugt and ter Braak (2008) and Laloy and Vrugt (2012). PyDREAM achieves excellent performance for complex, parameter-rich models and takes full advantage of distributed computing resources, facilitating parameter inference and uncertainty estimation of CPU-intensive biological models. PyDREAM is freely available under the GNU GPLv3 license from the Lopez lab GitHub repository at http://github.com/LoLab-VU/PyDREAM. c.lopez@vanderbilt.edu. Supplementary data are available at Bioinformatics online. © The Author(s) 2017. Published by Oxford University Press.

Installing logic-gate responses to a variety of biological substances in supramolecular hydrogel-enzyme hybrids

NASA Astrophysics Data System (ADS)

Ikeda, Masato; Tanida, Tatsuya; Yoshii, Tatsuyuki; Kurotani, Kazuya; Onogi, Shoji; Urayama, Kenji; Hamachi, Itaru

2014-06-01

Soft materials that exhibit stimuli-responsive behaviour under aqueous conditions (such as supramolecular hydrogels composed of self-assembled nanofibres) have many potential biological applications. However, designing a macroscopic response to structurally complex biochemical stimuli in these materials still remains a challenge. Here we show that redox-responsive peptide-based hydrogels have the ability to encapsulate enzymes and still retain their activities. Moreover, cooperative coupling of enzymatic reactions with the gel response enables us to construct unique stimuli-responsive soft materials capable of sensing a variety of disease-related biomarkers. The programmable gel-sol response (even to biological samples) is visible to the naked eye. Furthermore, we built Boolean logic gates (OR and AND) into the hydrogel-enzyme hybrid materials, which were able to sense simultaneously plural specific biochemicals and execute a controlled drug release in accordance with the logic operation. The intelligent soft materials that we have developed may prove valuable in future medical diagnostics or treatments.