The multi-replication protein A (RPA) system--a new perspective.

PubMed

Sakaguchi, Kengo; Ishibashi, Toyotaka; Uchiyama, Yukinobu; Iwabata, Kazuki

2009-02-01

Replication protein A (RPA) complex has been shown, using both in vivo and in vitro approaches, to be required for most aspects of eukaryotic DNA metabolism: replication, repair, telomere maintenance and homologous recombination. Here, we review recent data concerning the function and biological importance of the multi-RPA complex. There are distinct complexes of RPA found in the biological kingdoms, although for a long time only one type of RPA complex was believed to be present in eukaryotes. Each complex probably serves a different role. In higher plants, three distinct large and medium subunits are present, but only one species of the smallest subunit. Each of these protein subunits forms stable complexes with their respective partners. They are paralogs as complex. Humans possess two paralogs and one analog of RPA. The multi-RPA system can be regarded as universal in eukaryotes. Among eukaryotic kingdoms, paralogs, orthologs, analogs and heterologs of many DNA synthesis-related factors, including RPA, are ubiquitous. Convergent evolution seems to be ubiquitous in these processes. Using recent findings, we review the composition and biological functions of RPA complexes.

RRW: repeated random walks on genome-scale protein networks for local cluster discovery

PubMed Central

Macropol, Kathy; Can, Tolga; Singh, Ambuj K

2009-01-01

Background We propose an efficient and biologically sensitive algorithm based on repeated random walks (RRW) for discovering functional modules, e.g., complexes and pathways, within large-scale protein networks. Compared to existing cluster identification techniques, RRW implicitly makes use of network topology, edge weights, and long range interactions between proteins. Results We apply the proposed technique on a functional network of yeast genes and accurately identify statistically significant clusters of proteins. We validate the biological significance of the results using known complexes in the MIPS complex catalogue database and well-characterized biological processes. We find that 90% of the created clusters have the majority of their catalogued proteins belonging to the same MIPS complex, and about 80% have the majority of their proteins involved in the same biological process. We compare our method to various other clustering techniques, such as the Markov Clustering Algorithm (MCL), and find a significant improvement in the RRW clusters' precision and accuracy values. Conclusion RRW, which is a technique that exploits the topology of the network, is more precise and robust in finding local clusters. In addition, it has the added flexibility of being able to find multi-functional proteins by allowing overlapping clusters. PMID:19740439

The BioPlex Network: A Systematic Exploration of the Human Interactome.

PubMed

Huttlin, Edward L; Ting, Lily; Bruckner, Raphael J; Gebreab, Fana; Gygi, Melanie P; Szpyt, John; Tam, Stanley; Zarraga, Gabriela; Colby, Greg; Baltier, Kurt; Dong, Rui; Guarani, Virginia; Vaites, Laura Pontano; Ordureau, Alban; Rad, Ramin; Erickson, Brian K; Wühr, Martin; Chick, Joel; Zhai, Bo; Kolippakkam, Deepak; Mintseris, Julian; Obar, Robert A; Harris, Tim; Artavanis-Tsakonas, Spyros; Sowa, Mathew E; De Camilli, Pietro; Paulo, Joao A; Harper, J Wade; Gygi, Steven P

2015-07-16

Protein interactions form a network whose structure drives cellular function and whose organization informs biological inquiry. Using high-throughput affinity-purification mass spectrometry, we identify interacting partners for 2,594 human proteins in HEK293T cells. The resulting network (BioPlex) contains 23,744 interactions among 7,668 proteins with 86% previously undocumented. BioPlex accurately depicts known complexes, attaining 80%-100% coverage for most CORUM complexes. The network readily subdivides into communities that correspond to complexes or clusters of functionally related proteins. More generally, network architecture reflects cellular localization, biological process, and molecular function, enabling functional characterization of thousands of proteins. Network structure also reveals associations among thousands of protein domains, suggesting a basis for examining structurally related proteins. Finally, BioPlex, in combination with other approaches, can be used to reveal interactions of biological or clinical significance. For example, mutations in the membrane protein VAPB implicated in familial amyotrophic lateral sclerosis perturb a defined community of interactors. Copyright © 2015 Elsevier Inc. All rights reserved.

The BioPlex Network: A Systematic Exploration of the Human Interactome

PubMed Central

Huttlin, Edward L.; Ting, Lily; Bruckner, Raphael J.; Gebreab, Fana; Gygi, Melanie P.; Szpyt, John; Tam, Stanley; Zarraga, Gabriela; Colby, Greg; Baltier, Kurt; Dong, Rui; Guarani, Virginia; Vaites, Laura Pontano; Ordureau, Alban; Rad, Ramin; Erickson, Brian K.; Wühr, Martin; Chick, Joel; Zhai, Bo; Kolippakkam, Deepak; Mintseris, Julian; Obar, Robert A.; Harris, Tim; Artavanis-Tsakonas, Spyros; Sowa, Mathew E.; DeCamilli, Pietro; Paulo, Joao A.; Harper, J. Wade; Gygi, Steven P.

2015-01-01

SUMMARY Protein interactions form a network whose structure drives cellular function and whose organization informs biological inquiry. Using high-throughput affinity-purification mass spectrometry, we identify interacting partners for 2,594 human proteins in HEK293T cells. The resulting network (BioPlex) contains 23,744 interactions among 7,668 proteins with 86% previously undocumented. BioPlex accurately depicts known complexes, attaining 80-100% coverage for most CORUM complexes. The network readily subdivides into communities that correspond to complexes or clusters of functionally related proteins. More generally, network architecture reflects cellular localization, biological process, and molecular function, enabling functional characterization of thousands of proteins. Network structure also reveals associations among thousands of protein domains, suggesting a basis for examining structurally-related proteins. Finally, BioPlex, in combination with other approaches can be used to reveal interactions of biological or clinical significance. For example, mutations in the membrane protein VAPB implicated in familial Amyotrophic Lateral Sclerosis perturb a defined community of interactors. PMID:26186194

Proteomics-Based Analysis of Protein Complexes in Pluripotent Stem Cells and Cancer Biology.

PubMed

Sudhir, Putty-Reddy; Chen, Chung-Hsuan

2016-03-22

A protein complex consists of two or more proteins that are linked together through protein-protein interactions. The proteins show stable/transient and direct/indirect interactions within the protein complex or between the protein complexes. Protein complexes are involved in regulation of most of the cellular processes and molecular functions. The delineation of protein complexes is important to expand our knowledge on proteins functional roles in physiological and pathological conditions. The genetic yeast-2-hybrid method has been extensively used to characterize protein-protein interactions. Alternatively, a biochemical-based affinity purification coupled with mass spectrometry (AP-MS) approach has been widely used to characterize the protein complexes. In the AP-MS method, a protein complex of a target protein of interest is purified using a specific antibody or an affinity tag (e.g., DYKDDDDK peptide (FLAG) and polyhistidine (His)) and is subsequently analyzed by means of MS. Tandem affinity purification, a two-step purification system, coupled with MS has been widely used mainly to reduce the contaminants. We review here a general principle for AP-MS-based characterization of protein complexes and we explore several protein complexes identified in pluripotent stem cell biology and cancer biology as examples.

Proteomics-Based Analysis of Protein Complexes in Pluripotent Stem Cells and Cancer Biology

PubMed Central

Sudhir, Putty-Reddy; Chen, Chung-Hsuan

2016-01-01

A protein complex consists of two or more proteins that are linked together through protein–protein interactions. The proteins show stable/transient and direct/indirect interactions within the protein complex or between the protein complexes. Protein complexes are involved in regulation of most of the cellular processes and molecular functions. The delineation of protein complexes is important to expand our knowledge on proteins functional roles in physiological and pathological conditions. The genetic yeast-2-hybrid method has been extensively used to characterize protein-protein interactions. Alternatively, a biochemical-based affinity purification coupled with mass spectrometry (AP-MS) approach has been widely used to characterize the protein complexes. In the AP-MS method, a protein complex of a target protein of interest is purified using a specific antibody or an affinity tag (e.g., DYKDDDDK peptide (FLAG) and polyhistidine (His)) and is subsequently analyzed by means of MS. Tandem affinity purification, a two-step purification system, coupled with MS has been widely used mainly to reduce the contaminants. We review here a general principle for AP-MS-based characterization of protein complexes and we explore several protein complexes identified in pluripotent stem cell biology and cancer biology as examples. PMID:27011181

A Synthetic Biology Framework for Programming Eukaryotic Transcription Functions

PubMed Central

Khalil, Ahmad S.; Lu, Timothy K.; Bashor, Caleb J.; Ramirez, Cherie L.; Pyenson, Nora C.; Joung, J. Keith; Collins, James J.

2013-01-01

SUMMARY Eukaryotic transcription factors (TFs) perform complex and combinatorial functions within transcriptional networks. Here, we present a synthetic framework for systematically constructing eukaryotic transcription functions using artificial zinc fingers, modular DNA-binding domains found within many eukaryotic TFs. Utilizing this platform, we construct a library of orthogonal synthetic transcription factors (sTFs) and use these to wire synthetic transcriptional circuits in yeast. We engineer complex functions, such as tunable output strength and transcriptional cooperativity, by rationally adjusting a decomposed set of key component properties, e.g., DNA specificity, affinity, promoter design, protein-protein interactions. We show that subtle perturbations to these properties can transform an individual sTF between distinct roles (activator, cooperative factor, inhibitory factor) within a transcriptional complex, thus drastically altering the signal processing behavior of multi-input systems. This platform provides new genetic components for synthetic biology and enables bottom-up approaches to understanding the design principles of eukaryotic transcriptional complexes and networks. PMID:22863014

An integrative approach to inferring biologically meaningful gene modules

PubMed Central

2011-01-01

Background The ability to construct biologically meaningful gene networks and modules is critical for contemporary systems biology. Though recent studies have demonstrated the power of using gene modules to shed light on the functioning of complex biological systems, most modules in these networks have shown little association with meaningful biological function. We have devised a method which directly incorporates gene ontology (GO) annotation in construction of gene modules in order to gain better functional association. Results We have devised a method, Semantic Similarity-Integrated approach for Modularization (SSIM) that integrates various gene-gene pairwise similarity values, including information obtained from gene expression, protein-protein interactions and GO annotations, in the construction of modules using affinity propagation clustering. We demonstrated the performance of the proposed method using data from two complex biological responses: 1. the osmotic shock response in Saccharomyces cerevisiae, and 2. the prion-induced pathogenic mouse model. In comparison with two previously reported algorithms, modules identified by SSIM showed significantly stronger association with biological functions. Conclusions The incorporation of semantic similarity based on GO annotation with gene expression and protein-protein interaction data can greatly enhance the functional relevance of inferred gene modules. In addition, the SSIM approach can also reveal the hierarchical structure of gene modules to gain a broader functional view of the biological system. Hence, the proposed method can facilitate comprehensive and in-depth analysis of high throughput experimental data at the gene network level. PMID:21791051

A new multi-scale method to reveal hierarchical modular structures in biological networks.

PubMed

Jiao, Qing-Ju; Huang, Yan; Shen, Hong-Bin

2016-11-15

Biological networks are effective tools for studying molecular interactions. Modular structure, in which genes or proteins may tend to be associated with functional modules or protein complexes, is a remarkable feature of biological networks. Mining modular structure from biological networks enables us to focus on a set of potentially important nodes, which provides a reliable guide to future biological experiments. The first fundamental challenge in mining modular structure from biological networks is that the quality of the observed network data is usually low owing to noise and incompleteness in the obtained networks. The second problem that poses a challenge to existing approaches to the mining of modular structure is that the organization of both functional modules and protein complexes in networks is far more complicated than was ever thought. For instance, the sizes of different modules vary considerably from each other and they often form multi-scale hierarchical structures. To solve these problems, we propose a new multi-scale protocol for mining modular structure (named ISIMB) driven by a node similarity metric, which works in an iteratively converged space to reduce the effects of the low data quality of the observed network data. The multi-scale node similarity metric couples both the local and the global topology of the network with a resolution regulator. By varying this resolution regulator to give different weightings to the local and global terms in the metric, the ISIMB method is able to fit the shape of modules and to detect them on different scales. Experiments on protein-protein interaction and genetic interaction networks show that our method can not only mine functional modules and protein complexes successfully, but can also predict functional modules from specific to general and reveal the hierarchical organization of protein complexes.

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].

The Network Organization of Cancer-associated Protein Complexes in Human Tissues

PubMed Central

Zhao, Jing; Lee, Sang Hoon; Huss, Mikael; Holme, Petter

2013-01-01

Differential gene expression profiles for detecting disease genes have been studied intensively in systems biology. However, it is known that various biological functions achieved by proteins follow from the ability of the protein to form complexes by physically binding to each other. In other words, the functional units are often protein complexes rather than individual proteins. Thus, we seek to replace the perspective of disease-related genes by disease-related complexes, exemplifying with data on 39 human solid tissue cancers and their original normal tissues. To obtain the differential abundance levels of protein complexes, we apply an optimization algorithm to genome-wide differential expression data. From the differential abundance of complexes, we extract tissue- and cancer-selective complexes, and investigate their relevance to cancer. The method is supported by a clustering tendency of bipartite cancer-complex relationships, as well as a more concrete and realistic approach to disease-related proteomics. PMID:23567845

Functional Genomics Assistant (FUGA): a toolbox for the analysis of complex biological networks

PubMed Central

2011-01-01

Background Cellular constituents such as proteins, DNA, and RNA form a complex web of interactions that regulate biochemical homeostasis and determine the dynamic cellular response to external stimuli. It follows that detailed understanding of these patterns is critical for the assessment of fundamental processes in cell biology and pathology. Representation and analysis of cellular constituents through network principles is a promising and popular analytical avenue towards a deeper understanding of molecular mechanisms in a system-wide context. Findings We present Functional Genomics Assistant (FUGA) - an extensible and portable MATLAB toolbox for the inference of biological relationships, graph topology analysis, random network simulation, network clustering, and functional enrichment statistics. In contrast to conventional differential expression analysis of individual genes, FUGA offers a framework for the study of system-wide properties of biological networks and highlights putative molecular targets using concepts of systems biology. Conclusion FUGA offers a simple and customizable framework for network analysis in a variety of systems biology applications. It is freely available for individual or academic use at http://code.google.com/p/fuga. PMID:22035155

Modeling biology with HDL languages: a first step toward a genetic design automation tool inspired from microelectronics.

PubMed

Gendrault, Yves; Madec, Morgan; Lallement, Christophe; Haiech, Jacques

2014-04-01

Nowadays, synthetic biology is a hot research topic. Each day, progresses are made to improve the complexity of artificial biological functions in order to tend to complex biodevices and biosystems. Up to now, these systems are handmade by bioengineers, which require strong technical skills and leads to nonreusable development. Besides, scientific fields that share the same design approach, such as microelectronics, have already overcome several issues and designers succeed in building extremely complex systems with many evolved functions. On the other hand, in systems engineering and more specifically in microelectronics, the development of the domain has been promoted by both the improvement of technological processes and electronic design automation tools. The work presented in this paper paves the way for the adaptation of microelectronics design tools to synthetic biology. Considering the similarities and differences between the synthetic biology and microelectronics, the milestones of this adaptation are described. The first one concerns the modeling of biological mechanisms. To do so, a new formalism is proposed, based on an extension of the generalized Kirchhoff laws to biology. This way, a description of all biological mechanisms can be made with languages widely used in microelectronics. Our approach is therefore successfully validated on specific examples drawn from the literature.

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.

Synthetic biology: new engineering rules for an emerging discipline

PubMed Central

Andrianantoandro, Ernesto; Basu, Subhayu; Karig, David K; Weiss, Ron

2006-01-01

Synthetic biologists engineer complex artificial biological systems to investigate natural biological phenomena and for a variety of applications. We outline the basic features of synthetic biology as a new engineering discipline, covering examples from the latest literature and reflecting on the features that make it unique among all other existing engineering fields. We discuss methods for designing and constructing engineered cells with novel functions in a framework of an abstract hierarchy of biological devices, modules, cells, and multicellular systems. The classical engineering strategies of standardization, decoupling, and abstraction will have to be extended to take into account the inherent characteristics of biological devices and modules. To achieve predictability and reliability, strategies for engineering biology must include the notion of cellular context in the functional definition of devices and modules, use rational redesign and directed evolution for system optimization, and focus on accomplishing tasks using cell populations rather than individual cells. The discussion brings to light issues at the heart of designing complex living systems and provides a trajectory for future development. PMID:16738572

Synthetic biology: new engineering rules for an emerging discipline.

PubMed

Andrianantoandro, Ernesto; Basu, Subhayu; Karig, David K; Weiss, Ron

2006-01-01

Synthetic biologists engineer complex artificial biological systems to investigate natural biological phenomena and for a variety of applications. We outline the basic features of synthetic biology as a new engineering discipline, covering examples from the latest literature and reflecting on the features that make it unique among all other existing engineering fields. We discuss methods for designing and constructing engineered cells with novel functions in a framework of an abstract hierarchy of biological devices, modules, cells, and multicellular systems. The classical engineering strategies of standardization, decoupling, and abstraction will have to be extended to take into account the inherent characteristics of biological devices and modules. To achieve predictability and reliability, strategies for engineering biology must include the notion of cellular context in the functional definition of devices and modules, use rational redesign and directed evolution for system optimization, and focus on accomplishing tasks using cell populations rather than individual cells. The discussion brings to light issues at the heart of designing complex living systems and provides a trajectory for future development.

[Application of microelectronics CAD tools to synthetic biology].

PubMed

Madec, Morgan; Haiech, Jacques; Rosati, Élise; Rezgui, Abir; Gendrault, Yves; Lallement, Christophe

2017-02-01

Synthetic biology is an emerging science that aims to create new biological functions that do not exist in nature, based on the knowledge acquired in life science over the last century. Since the beginning of this century, several projects in synthetic biology have emerged. The complexity of the developed artificial bio-functions is relatively low so that empirical design methods could be used for the design process. Nevertheless, with the increasing complexity of biological circuits, this is no longer the case and a large number of computer aided design softwares have been developed in the past few years. These tools include languages for the behavioral description and the mathematical modelling of biological systems, simulators at different levels of abstraction, libraries of biological devices and circuit design automation algorithms. All of these tools already exist in other fields of engineering sciences, particularly in microelectronics. This is the approach that is put forward in this paper. © 2017 médecine/sciences – Inserm.

Adaptive landscape and functional diversity of Neotropical cichlids: implications for the ecology and evolution of Cichlinae (Cichlidae; Cichliformes).

PubMed

Arbour, J H; López-Fernández, H

2014-11-01

Morphological, lineage and ecological diversity can vary substantially even among closely related lineages. Factors that influence morphological diversification, especially in functionally relevant traits, can help to explain the modern distribution of disparity across phylogenies and communities. Multivariate axes of feeding functional morphology from 75 species of Neotropical cichlid and a stepwise-AIC algorithm were used to estimate the adaptive landscape of functional morphospace in Cichlinae. Adaptive landscape complexity and convergence, as well as the functional diversity of Cichlinae, were compared with expectations under null evolutionary models. Neotropical cichlid feeding function varied primarily between traits associated with ram feeding vs. suction feeding/biting and secondarily with oral jaw muscle size and pharyngeal crushing capacity. The number of changes in selective regimes and the amount of convergence between lineages was higher than expected under a null model of evolution, but convergence was not higher than expected under a similarly complex adaptive landscape. Functional disparity was compatible with an adaptive landscape model, whereas the distribution of evolutionary change through morphospace corresponded with a process of evolution towards a single adaptive peak. The continentally distributed Neotropical cichlids have evolved relatively rapidly towards a number of adaptive peaks in functional trait space. Selection in Cichlinae functional morphospace is more complex than expected under null evolutionary models. The complexity of selective constraints in feeding morphology has likely been a significant contributor to the diversity of feeding ecology in this clade. © 2014 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2014 European Society For Evolutionary Biology.

Harnessing glycomics technologies: integrating structure with function for glycan characterization

PubMed Central

Robinson, Luke N.; Artpradit, Charlermchai; Raman, Rahul; Shriver, Zachary H.; Ruchirawat, Mathuros; Sasisekharan, Ram

2013-01-01

Glycans, or complex carbohydrates, are a ubiquitous class of biological molecules which impinge on a variety of physiological processes ranging from signal transduction to tissue development and microbial pathogenesis. In comparison to DNA and proteins, glycans present unique challenges to the study of their structure and function owing to their complex and heterogeneous structures and the dominant role played by multivalency in their sequence-specific biological interactions. Arising from these challenges, there is a need to integrate information from multiple complementary methods to decode structure-function relationships. Focusing on acidic glycans, we describe here key glycomics technologies for characterizing their structural attributes, including linkage, modifications, and topology, as well as for elucidating their role in biological processes. Two cases studies, one involving sialylated branched glycans and the other sulfated glycosaminoglycans, are used to highlight how integration of orthogonal information from diverse datasets enables rapid convergence of glycan characterization for development of robust structure-function relationships. PMID:22522536

A program code generator for multiphysics biological simulation using markup languages.

PubMed

Amano, Akira; Kawabata, Masanari; Yamashita, Yoshiharu; Rusty Punzalan, Florencio; Shimayoshi, Takao; Kuwabara, Hiroaki; Kunieda, Yoshitoshi

2012-01-01

To cope with the complexity of the biological function simulation models, model representation with description language is becoming popular. However, simulation software itself becomes complex in these environment, thus, it is difficult to modify the simulation conditions, target computation resources or calculation methods. In the complex biological function simulation software, there are 1) model equations, 2) boundary conditions and 3) calculation schemes. Use of description model file is useful for first point and partly second point, however, third point is difficult to handle for various calculation schemes which is required for simulation models constructed from two or more elementary models. We introduce a simulation software generation system which use description language based description of coupling calculation scheme together with cell model description file. By using this software, we can easily generate biological simulation code with variety of coupling calculation schemes. To show the efficiency of our system, example of coupling calculation scheme with three elementary models are shown.

Optimizing Nutrient Uptake in Biological Transport Networks

NASA Astrophysics Data System (ADS)

Ronellenfitsch, Henrik; Katifori, Eleni

2013-03-01

Many biological systems employ complex networks of vascular tubes to facilitate transport of solute nutrients, examples include the vascular system of plants (phloem), some fungi, and the slime-mold Physarum. It is believed that such networks are optimized through evolution for carrying out their designated task. We propose a set of hydrodynamic governing equations for solute transport in a complex network, and obtain the optimal network architecture for various classes of optimizing functionals. We finally discuss the topological properties and statistical mechanics of the resulting complex networks, and examine correspondence of the obtained networks to those found in actual biological systems.

Interrogation of Mammalian Protein Complex Structure, Function, and Membership Using Genome-Scale Fitness Screens. | Office of Cancer Genomics

Cancer.gov

Protein complexes are assemblies of subunits that have co-evolved to execute one or many coordinated functions in the cellular environment. Functional annotation of mammalian protein complexes is critical to understanding biological processes, as well as disease mechanisms. Here, we used genetic co-essentiality derived from genome-scale RNAi- and CRISPR-Cas9-based fitness screens performed across hundreds of human cancer cell lines to assign measures of functional similarity.

Inflammasome complexes: emerging mechanisms and effector functions

PubMed Central

Rathinam, Vijay A. K.; Fitzgerald, Katherine A.

2017-01-01

Canonical activation of the inflammasome is critical to promote caspase-1-dependent maturation of the proinflammatory cytokines IL-1β and IL-18, as well as to induce pyroptotic cell death in response to pathogens and endogenous danger signals. Recent discoveries, however, are beginning to unveil new components of the inflammasome machinery, and the full spectrum of inflammasome functions, extending their influence beyond canonical functions, to regulation of eicosanoid storm, autophagy and metabolism. In addition, the receptor components of the inflammasome can also regulate diverse biological processes, such as cellular proliferation, gene transcription and tumorigenesis, all of which are independent of their inflammasome complex-forming capabilities. Here, we review these recent advances that are shaping our understanding of the complex biology of the inflammasome and its constituents. PMID:27153493

Thiol/disulfide redox states in signaling and sensing

PubMed Central

Go, Young-Mi; Jones, Dean P.

2015-01-01

Rapid advances in redox systems biology are creating new opportunities to understand complexities of human disease and contributions of environmental exposures. New understanding of thiol-disulfide systems have occurred during the past decade as a consequence of the discoveries that thiol and disulfide systems are maintained in kinetically controlled steady-states displaced from thermodynamic equilibrium, that a widely distributed family of NADPH oxidases produces oxidants that function in cell signaling, and that a family of peroxiredoxins utilize thioredoxin as a reductant to complement the well-studied glutathione antioxidant system for peroxide elimination and redox regulation. This review focuses on thiol/disulfide redox state in biologic systems and the knowledge base available to support development of integrated redox systems biology models to better understand the function and dysfunction of thiol-disulfide redox systems. In particular, central principles have emerged concerning redox compartmentalization and utility of thiol/disulfide redox measures as indicators of physiologic function. Advances in redox proteomics show that, in addition to functioning in protein active sites and cell signaling, cysteine residues also serve as redox sensors to integrate biologic functions. These advances provide a framework for translation of redox systems biology concepts to practical use in understanding and treating human disease. Biological responses to cadmium, a widespread environmental agent, are used to illustrate the utility of these advances to the understanding of complex pleiotropic toxicities. PMID:23356510

Biological roles of glycans

PubMed Central

Varki, Ajit

2017-01-01

Abstract Simple and complex carbohydrates (glycans) have long been known to play major metabolic, structural and physical roles in biological systems. Targeted microbial binding to host glycans has also been studied for decades. But such biological roles can only explain some of the remarkable complexity and organismal diversity of glycans in nature. Reviewing the subject about two decades ago, one could find very few clear-cut instances of glycan-recognition-specific biological roles of glycans that were of intrinsic value to the organism expressing them. In striking contrast there is now a profusion of examples, such that this updated review cannot be comprehensive. Instead, a historical overview is presented, broad principles outlined and a few examples cited, representing diverse types of roles, mediated by various glycan classes, in different evolutionary lineages. What remains unchanged is the fact that while all theories regarding biological roles of glycans are supported by compelling evidence, exceptions to each can be found. In retrospect, this is not surprising. Complex and diverse glycans appear to be ubiquitous to all cells in nature, and essential to all life forms. Thus, >3 billion years of evolution consistently generated organisms that use these molecules for many key biological roles, even while sometimes coopting them for minor functions. In this respect, glycans are no different from other major macromolecular building blocks of life (nucleic acids, proteins and lipids), simply more rapidly evolving and complex. It is time for the diverse functional roles of glycans to be fully incorporated into the mainstream of biological sciences. PMID:27558841

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.

Life under the Microscope: Single-Molecule Fluorescence Highlights the RNA World.

PubMed

Ray, Sujay; Widom, Julia R; Walter, Nils G

2018-04-25

The emergence of single-molecule (SM) fluorescence techniques has opened up a vast new toolbox for exploring the molecular basis of life. The ability to monitor individual biomolecules in real time enables complex, dynamic folding pathways to be interrogated without the averaging effect of ensemble measurements. In parallel, modern biology has been revolutionized by our emerging understanding of the many functions of RNA. In this comprehensive review, we survey SM fluorescence approaches and discuss how the application of these tools to RNA and RNA-containing macromolecular complexes in vitro has yielded significant insights into the underlying biology. Topics covered include the three-dimensional folding landscapes of a plethora of isolated RNA molecules, their assembly and interactions in RNA-protein complexes, and the relation of these properties to their biological functions. In all of these examples, the use of SM fluorescence methods has revealed critical information beyond the reach of ensemble averages.

Challenges and complexity of functionality evaluation of flavan-3-ol derivatives.

PubMed

Saito, Akiko

2017-06-01

Flavan-3-ol derivatives are common plant-derived bioactive compounds. In particular, (-)-epigallocatechin-3-O-gallate shows various moderate biological activities without severe toxicity, and its health-promoting effects have been widely studied because it is a main ingredient in green tea and is commercially available at low cost. Although various biologically active flavan-3-ol derivatives are present as minor constituents in plants as well as in green tea, their biological activities have yet to be revealed, mainly due to their relative unavailability. Here, I outline the major factors contributing to the complexity of functionality studies of flavan-3-ol derivatives, including proanthocyanidins and oligomeric flavan-3-ols. I emphasize the importance of conducting structure-activity relationship studies using synthesized flavan-3-ol derivatives that are difficult to obtain from plant extracts in pure form to overcome this challenge. Further discovery of these minor constituents showing strong biological activities is expected to produce useful information for the development of functional health foods.

Evolutionary cell biology: functional insight from "endless forms most beautiful".

PubMed

Richardson, Elisabeth; Zerr, Kelly; Tsaousis, Anastasios; Dorrell, Richard G; Dacks, Joel B

2015-12-15

In animal and fungal model organisms, the complexities of cell biology have been analyzed in exquisite detail and much is known about how these organisms function at the cellular level. However, the model organisms cell biologists generally use include only a tiny fraction of the true diversity of eukaryotic cellular forms. The divergent cellular processes observed in these more distant lineages are still largely unknown in the general scientific community. Despite the relative obscurity of these organisms, comparative studies of them across eukaryotic diversity have had profound implications for our understanding of fundamental cell biology in all species and have revealed the evolution and origins of previously observed cellular processes. In this Perspective, we will discuss the complexity of cell biology found across the eukaryotic tree, and three specific examples of where studies of divergent cell biology have altered our understanding of key functional aspects of mitochondria, plastids, and membrane trafficking. © 2015 Richardson 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).

A toolbox for discrete modelling of cell signalling dynamics.

PubMed

Paterson, Yasmin Z; Shorthouse, David; Pleijzier, Markus W; Piterman, Nir; Bendtsen, Claus; Hall, Benjamin A; Fisher, Jasmin

2018-06-18

In an age where the volume of data regarding biological systems exceeds our ability to analyse it, many researchers are looking towards systems biology and computational modelling to help unravel the complexities of gene and protein regulatory networks. In particular, the use of discrete modelling allows generation of signalling networks in the absence of full quantitative descriptions of systems, which are necessary for ordinary differential equation (ODE) models. In order to make such techniques more accessible to mainstream researchers, tools such as the BioModelAnalyzer (BMA) have been developed to provide a user-friendly graphical interface for discrete modelling of biological systems. Here we use the BMA to build a library of discrete target functions of known canonical molecular interactions, translated from ordinary differential equations (ODEs). We then show that these BMA target functions can be used to reconstruct complex networks, which can correctly predict many known genetic perturbations. This new library supports the accessibility ethos behind the creation of BMA, providing a toolbox for the construction of complex cell signalling models without the need for extensive experience in computer programming or mathematical modelling, and allows for construction and simulation of complex biological systems with only small amounts of quantitative data.

Comparative Network-Based Recovery Analysis and Proteomic Profiling of Neurological Changes in Valproic Acid-Treated Mice

PubMed Central

2013-01-01

Despite its prominence for characterization of complex mixtures, LC–MS/MS frequently fails to identify many proteins. Network-based analysis methods, based on protein–protein interaction networks (PPINs), biological pathways, and protein complexes, are useful for recovering non-detected proteins, thereby enhancing analytical resolution. However, network-based analysis methods do come in varied flavors for which the respective efficacies are largely unknown. We compare the recovery performance and functional insights from three distinct instances of PPIN-based approaches, viz., Proteomics Expansion Pipeline (PEP), Functional Class Scoring (FCS), and Maxlink, in a test scenario of valproic acid (VPA)-treated mice. We find that the most comprehensive functional insights, as well as best non-detected protein recovery performance, are derived from FCS utilizing real biological complexes. This outstrips other network-based methods such as Maxlink or Proteomics Expansion Pipeline (PEP). From FCS, we identified known biological complexes involved in epigenetic modifications, neuronal system development, and cytoskeletal rearrangements. This is congruent with the observed phenotype where adult mice showed an increase in dendritic branching to allow the rewiring of visual cortical circuitry and an improvement in their visual acuity when tested behaviorally. In addition, PEP also identified a novel complex, comprising YWHAB, NR1, NR2B, ACTB, and TJP1, which is functionally related to the observed phenotype. Although our results suggest different network analysis methods can produce different results, on the whole, the findings are mutually supportive. More critically, the non-overlapping information each provides can provide greater holistic understanding of complex phenotypes. PMID:23557376

Petri net modelling of biological networks.

PubMed

Chaouiya, Claudine

2007-07-01

Mathematical modelling is increasingly used to get insights into the functioning of complex biological networks. In this context, Petri nets (PNs) have recently emerged as a promising tool among the various methods employed for the modelling and analysis of molecular networks. PNs come with a series of extensions, which allow different abstraction levels, from purely qualitative to more complex quantitative models. Noteworthily, each of these models preserves the underlying graph, which depicts the interactions between the biological components. This article intends to present the basics of the approach and to foster the potential role PNs could play in the development of the computational systems biology.

Implementation of Complex Biological Logic Circuits Using Spatially Distributed Multicellular Consortia

PubMed Central

Urrios, Arturo; de Nadal, Eulàlia; Solé, Ricard; Posas, Francesc

2016-01-01

Engineered synthetic biological devices have been designed to perform a variety of functions from sensing molecules and bioremediation to energy production and biomedicine. Notwithstanding, a major limitation of in vivo circuit implementation is the constraint associated to the use of standard methodologies for circuit design. Thus, future success of these devices depends on obtaining circuits with scalable complexity and reusable parts. Here we show how to build complex computational devices using multicellular consortia and space as key computational elements. This spatial modular design grants scalability since its general architecture is independent of the circuit’s complexity, minimizes wiring requirements and allows component reusability with minimal genetic engineering. The potential use of this approach is demonstrated by implementation of complex logical functions with up to six inputs, thus demonstrating the scalability and flexibility of this method. The potential implications of our results are outlined. PMID:26829588

Network science of biological systems at different scales: A review

NASA Astrophysics Data System (ADS)

Gosak, Marko; Markovič, Rene; Dolenšek, Jurij; Slak Rupnik, Marjan; Marhl, Marko; Stožer, Andraž; Perc, Matjaž

2018-03-01

Network science is today established as a backbone for description of structure and function of various physical, chemical, biological, technological, and social systems. Here we review recent advances in the study of complex biological systems that were inspired and enabled by methods of network science. First, we present

Dynamics driving function: new insights from electron transferring flavoproteins and partner complexes.

PubMed

Toogood, Helen S; Leys, David; Scrutton, Nigel S

2007-11-01

Electron transferring flavoproteins (ETFs) are soluble heterodimeric FAD-containing proteins that function primarily as soluble electron carriers between various flavoprotein dehydrogenases. ETF is positioned at a key metabolic branch point, responsible for transferring electrons from up to 10 primary dehydrogenases to the membrane-bound respiratory chain. Clinical mutations of ETF result in the often fatal disease glutaric aciduria type II. Structural and biophysical studies of ETF in complex with partner proteins have shown that ETF partitions the functions of partner binding and electron transfer between (a) a 'recognition loop', which acts as a static anchor at the ETF-partner interface, and (b) a highly mobile redox-active FAD domain. Together, this enables the FAD domain of ETF to sample a range of conformations, some compatible with fast interprotein electron transfer. This 'conformational sampling' enables ETF to recognize structurally distinct partners, whilst also maintaining a degree of specificity. Complex formation triggers mobility of the FAD domain, an 'induced disorder' mechanism contrasting with the more generally accepted models of protein-protein interaction by induced fit mechanisms. We discuss the implications of the highly dynamic nature of ETFs in biological interprotein electron transfer. ETF complexes point to mechanisms of electron transfer in which 'dynamics drive function', a feature that is probably widespread in biology given the modular assembly and flexible nature of biological electron transfer systems.

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.

Intrinsic disorder mediates the diverse regulatory functions of the Cdk inhibitor p21

PubMed Central

Wang, Yuefeng; Fisher, John C.; Mathew, Rose; Ou, Li; Otieno, Steve; Sublett, Jack; Xiao, Limin; Chen, Jianhan; Roussel, Martine F.; Kriwacki, Richard W.

2011-01-01

Traditionally, well-defined three-dimensional structure was thought to be essential for protein function. However, myriad biological functions are performed by highly dynamic, intrinsically disordered proteins (IDPs). IDPs often fold upon binding their biological targets and frequently exhibit “binding diversity” by targeting multiple ligands. We sought to understand the physical basis of IDP binding diversity and herein report that the cyclin-dependent kinase (Cdk) inhibitor, p21Cip1, adaptively binds to and inhibits the various Cdk/cyclin complexes that regulate eukaryotic cell division. Based on results from NMR spectroscopy, and biochemical and cellular assays, we show that structural adaptability of a helical sub-domain within p21 termed LH enables two other sub-domains termed D1 and D2 to specifically bind conserved surface features of the cyclin and Cdk subunits, respectively, within otherwise structurally distinct Cdk/cyclin complexes. Adaptive folding upon binding is likely to mediate the diverse biological functions of the thousands of IDPs present in eukaryotes. PMID:21358637

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

Coupled Analysis of In Vitro and Histology Tissue Samples to Quantify Structure-Function Relationship

PubMed Central

Acar, Evrim; Plopper, George E.; Yener, Bülent

2012-01-01

The structure/function relationship is fundamental to our understanding of biological systems at all levels, and drives most, if not all, techniques for detecting, diagnosing, and treating disease. However, at the tissue level of biological complexity we encounter a gap in the structure/function relationship: having accumulated an extraordinary amount of detailed information about biological tissues at the cellular and subcellular level, we cannot assemble it in a way that explains the correspondingly complex biological functions these structures perform. To help close this information gap we define here several quantitative temperospatial features that link tissue structure to its corresponding biological function. Both histological images of human tissue samples and fluorescence images of three-dimensional cultures of human cells are used to compare the accuracy of in vitro culture models with their corresponding human tissues. To the best of our knowledge, there is no prior work on a quantitative comparison of histology and in vitro samples. Features are calculated from graph theoretical representations of tissue structures and the data are analyzed in the form of matrices and higher-order tensors using matrix and tensor factorization methods, with a goal of differentiating between cancerous and healthy states of brain, breast, and bone tissues. We also show that our techniques can differentiate between the structural organization of native tissues and their corresponding in vitro engineered cell culture models. PMID:22479315

Foreword to 'Multiscale structural biology: biophysical principles and mechanisms underlying the action of bio-nanomachines', a special issue in Honour of Fumio Arisaka's 70th birthday.

PubMed

Hall, Damien; Takagi, Junichi; Nakamura, Haruki

2018-04-01

This issue of Biophysical Reviews, titled 'Multiscale structural biology: biophysical principles and mechanisms underlying the action of bio-nanomachines', is a collection of articles dedicated in honour of Professor Fumio Arisaka's 70th birthday. Initially, working in the fields of haemocyanin and actin filament assembly, Fumio went on to publish important work on the elucidation of structural and functional aspects of T4 phage biology. As his career has transitioned levels of complexity from proteins (hemocyanin) to large protein complexes (actin) to even more massive bio-nanomachinery (phage), it is fitting that the subject of this special issue is similarly reflective of his multiscale approach to structural biology. This festschrift contains articles spanning biophysical structure and function from the bio-molecular through to the bio-nanomachine level.

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.

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.

Integrative systems and synthetic biology of cell-matrix adhesion sites.

PubMed

Zamir, Eli

2016-09-02

The complexity of cell-matrix adhesion convolves its roles in the development and functioning of multicellular organisms and their evolutionary tinkering. Cell-matrix adhesion is mediated by sites along the plasma membrane that anchor the actin cytoskeleton to the matrix via a large number of proteins, collectively called the integrin adhesome. Fundamental challenges for understanding how cell-matrix adhesion sites assemble and function arise from their multi-functionality, rapid dynamics, large number of components and molecular diversity. Systems biology faces these challenges in its strive to understand how the integrin adhesome gives rise to functional adhesion sites. Synthetic biology enables engineering intracellular modules and circuits with properties of interest. In this review I discuss some of the fundamental questions in systems biology of cell-matrix adhesion and how synthetic biology can help addressing them.

Statistical Techniques Complement UML When Developing Domain Models of Complex Dynamical Biosystems.

PubMed

Williams, Richard A; Timmis, Jon; Qwarnstrom, Eva E

2016-01-01

Computational modelling and simulation is increasingly being used to complement traditional wet-lab techniques when investigating the mechanistic behaviours of complex biological systems. In order to ensure computational models are fit for purpose, it is essential that the abstracted view of biology captured in the computational model, is clearly and unambiguously defined within a conceptual model of the biological domain (a domain model), that acts to accurately represent the biological system and to document the functional requirements for the resultant computational model. We present a domain model of the IL-1 stimulated NF-κB signalling pathway, which unambiguously defines the spatial, temporal and stochastic requirements for our future computational model. Through the development of this model, we observe that, in isolation, UML is not sufficient for the purpose of creating a domain model, and that a number of descriptive and multivariate statistical techniques provide complementary perspectives, in particular when modelling the heterogeneity of dynamics at the single-cell level. We believe this approach of using UML to define the structure and interactions within a complex system, along with statistics to define the stochastic and dynamic nature of complex systems, is crucial for ensuring that conceptual models of complex dynamical biosystems, which are developed using UML, are fit for purpose, and unambiguously define the functional requirements for the resultant computational model.

Statistical Techniques Complement UML When Developing Domain Models of Complex Dynamical Biosystems

PubMed Central

Timmis, Jon; Qwarnstrom, Eva E.

2016-01-01

Computational modelling and simulation is increasingly being used to complement traditional wet-lab techniques when investigating the mechanistic behaviours of complex biological systems. In order to ensure computational models are fit for purpose, it is essential that the abstracted view of biology captured in the computational model, is clearly and unambiguously defined within a conceptual model of the biological domain (a domain model), that acts to accurately represent the biological system and to document the functional requirements for the resultant computational model. We present a domain model of the IL-1 stimulated NF-κB signalling pathway, which unambiguously defines the spatial, temporal and stochastic requirements for our future computational model. Through the development of this model, we observe that, in isolation, UML is not sufficient for the purpose of creating a domain model, and that a number of descriptive and multivariate statistical techniques provide complementary perspectives, in particular when modelling the heterogeneity of dynamics at the single-cell level. We believe this approach of using UML to define the structure and interactions within a complex system, along with statistics to define the stochastic and dynamic nature of complex systems, is crucial for ensuring that conceptual models of complex dynamical biosystems, which are developed using UML, are fit for purpose, and unambiguously define the functional requirements for the resultant computational model. PMID:27571414

Discovery of a new method for potent drug development using power function of stoichiometry ofhomomeric biocomplexes or biological nanomotors

PubMed Central

Pi, Fengmei; Vieweger, Mario; Zhao, Zhengyi; Wang, Shaoying; Guo, Peixuan

2015-01-01

Introduction Multidrug resistance and the appearance of incurable diseases inspire the quest for potent therapeutics. Areas Covered We review a new methodology in designing potent drugs by targeting multi-subunit homomeric biological motors, machines, or complexes with Z>1 and K=1, where Z is the stoichiometry of the target, and K is the number of drugged subunits required to block the function of the complex. The condition is similar to a series, electrical circuit of Christmas decorations; failure of one light bulb causes the entire lighting system to lose power. In most multisubunit, homomeric biological systems, a sequential coordination or cooperative action mechanism is utilized, thus K equals 1. Drug inhibition depends on the ratio of drugged to nondrugged complexes. When K=1, and Z>1, the inhibition effect follows a power law with respect to Z, leading to enhanced drug potency. The hypothesis that the potency of drug inhibition depends on the stoichiometry of the targeted biological complexes was recently quantified by Yang-Hui's Triangle (or binomial distribution), and proved using a highly sensitive in vitro phi29 viral DNA packaging system. Examples of targeting homomeric bio-complexes with high stoichiometry for potent drug discovery are discussed. Expert Opinion Biomotors with multiple subunits are widespread in viruses, bacteria, and cells, making this approach generally applicable in the development of inhibition drugs with high efficiency. PMID:26307193

Interrogation of Mammalian Protein Complex Structure, Function, and Membership Using Genome-Scale Fitness Screens.

PubMed

Pan, Joshua; Meyers, Robin M; Michel, Brittany C; Mashtalir, Nazar; Sizemore, Ann E; Wells, Jonathan N; Cassel, Seth H; Vazquez, Francisca; Weir, Barbara A; Hahn, William C; Marsh, Joseph A; Tsherniak, Aviad; Kadoch, Cigall

2018-05-23

Protein complexes are assemblies of subunits that have co-evolved to execute one or many coordinated functions in the cellular environment. Functional annotation of mammalian protein complexes is critical to understanding biological processes, as well as disease mechanisms. Here, we used genetic co-essentiality derived from genome-scale RNAi- and CRISPR-Cas9-based fitness screens performed across hundreds of human cancer cell lines to assign measures of functional similarity. From these measures, we systematically built and characterized functional similarity networks that recapitulate known structural and functional features of well-studied protein complexes and resolve novel functional modules within complexes lacking structural resolution, such as the mammalian SWI/SNF complex. Finally, by integrating functional networks with large protein-protein interaction networks, we discovered novel protein complexes involving recently evolved genes of unknown function. Taken together, these findings demonstrate the utility of genetic perturbation screens alone, and in combination with large-scale biophysical data, to enhance our understanding of mammalian protein complexes in normal and disease states. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Joining Forces: Integrating Proteomics and Cross-linking with the Mass Spectrometry of Intact Complexes*

PubMed Central

Stengel, Florian; Aebersold, Ruedi; Robinson, Carol V.

2012-01-01

Protein assemblies are critical for cellular function and understanding their physical organization is the key aim of structural biology. However, applying conventional structural biology approaches is challenging for transient, dynamic, or polydisperse assemblies. There is therefore a growing demand for hybrid technologies that are able to complement classical structural biology methods and thereby broaden our arsenal for the study of these important complexes. Exciting new developments in the field of mass spectrometry and proteomics have added a new dimension to the study of protein-protein interactions and protein complex architecture. In this review, we focus on how complementary mass spectrometry-based techniques can greatly facilitate structural understanding of protein assemblies. PMID:22180098

Developments in the Tools and Methodologies of Synthetic Biology

PubMed Central

Kelwick, Richard; MacDonald, James T.; Webb, Alexander J.; Freemont, Paul

2014-01-01

Synthetic biology is principally concerned with the rational design and engineering of biologically based parts, devices, or systems. However, biological systems are generally complex and unpredictable, and are therefore, intrinsically difficult to engineer. In order to address these fundamental challenges, synthetic biology is aiming to unify a “body of knowledge” from several foundational scientific fields, within the context of a set of engineering principles. This shift in perspective is enabling synthetic biologists to address complexity, such that robust biological systems can be designed, assembled, and tested as part of a biological design cycle. The design cycle takes a forward-design approach in which a biological system is specified, modeled, analyzed, assembled, and its functionality tested. At each stage of the design cycle, an expanding repertoire of tools is being developed. In this review, we highlight several of these tools in terms of their applications and benefits to the synthetic biology community. PMID:25505788

Programmable chemical reaction networks: emulating regulatory functions in living cells using a bottom-up approach.

PubMed

van Roekel, Hendrik W H; Rosier, Bas J H M; Meijer, Lenny H H; Hilbers, Peter A J; Markvoort, Albert J; Huck, Wilhelm T S; de Greef, Tom F A

2015-11-07

Living cells are able to produce a wide variety of biological responses when subjected to biochemical stimuli. It has become apparent that these biological responses are regulated by complex chemical reaction networks (CRNs). Unravelling the function of these circuits is a key topic of both systems biology and synthetic biology. Recent progress at the interface of chemistry and biology together with the realisation that current experimental tools are insufficient to quantitatively understand the molecular logic of pathways inside living cells has triggered renewed interest in the bottom-up development of CRNs. This builds upon earlier work of physical chemists who extensively studied inorganic CRNs and showed how a system of chemical reactions can give rise to complex spatiotemporal responses such as oscillations and pattern formation. Using purified biochemical components, in vitro synthetic biologists have started to engineer simplified model systems with the goal of mimicking biological responses of intracellular circuits. Emulation and reconstruction of system-level properties of intracellular networks using simplified circuits are able to reveal key design principles and molecular programs that underlie the biological function of interest. In this Tutorial Review, we present an accessible overview of this emerging field starting with key studies on inorganic CRNs followed by a discussion of recent work involving purified biochemical components. Finally, we review recent work showing the versatility of programmable biochemical reaction networks (BRNs) in analytical and diagnostic applications.

Multi-agent-based bio-network for systems biology: protein-protein interaction network as an example.

PubMed

Ren, Li-Hong; Ding, Yong-Sheng; Shen, Yi-Zhen; Zhang, Xiang-Feng

2008-10-01

Recently, a collective effort from multiple research areas has been made to understand biological systems at the system level. This research requires the ability to simulate particular biological systems as cells, organs, organisms, and communities. In this paper, a novel bio-network simulation platform is proposed for system biology studies by combining agent approaches. We consider a biological system as a set of active computational components interacting with each other and with an external environment. Then, we propose a bio-network platform for simulating the behaviors of biological systems and modelling them in terms of bio-entities and society-entities. As a demonstration, we discuss how a protein-protein interaction (PPI) network can be seen as a society of autonomous interactive components. From interactions among small PPI networks, a large PPI network can emerge that has a remarkable ability to accomplish a complex function or task. We also simulate the evolution of the PPI networks by using the bio-operators of the bio-entities. Based on the proposed approach, various simulators with different functions can be embedded in the simulation platform, and further research can be done from design to development, including complexity validation of the biological system.

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.

Advances and Computational Tools towards Predictable Design in Biological Engineering

PubMed Central

2014-01-01

The design process of complex systems in all the fields of engineering requires a set of quantitatively characterized components and a method to predict the output of systems composed by such elements. This strategy relies on the modularity of the used components or the prediction of their context-dependent behaviour, when parts functioning depends on the specific context. Mathematical models usually support the whole process by guiding the selection of parts and by predicting the output of interconnected systems. Such bottom-up design process cannot be trivially adopted for biological systems engineering, since parts function is hard to predict when components are reused in different contexts. This issue and the intrinsic complexity of living systems limit the capability of synthetic biologists to predict the quantitative behaviour of biological systems. The high potential of synthetic biology strongly depends on the capability of mastering this issue. This review discusses the predictability issues of basic biological parts (promoters, ribosome binding sites, coding sequences, transcriptional terminators, and plasmids) when used to engineer simple and complex gene expression systems in Escherichia coli. A comparison between bottom-up and trial-and-error approaches is performed for all the discussed elements and mathematical models supporting the prediction of parts behaviour are illustrated. PMID:25161694

Prokaryotic Gene Clusters: A Rich Toolbox for Synthetic Biology

PubMed Central

Fischbach, Michael; Voigt, Christopher A.

2014-01-01

Bacteria construct elaborate nanostructures, obtain nutrients and energy from diverse sources, synthesize complex molecules, and implement signal processing to react to their environment. These complex phenotypes require the coordinated action of multiple genes, which are often encoded in a contiguous region of the genome, referred to as a gene cluster. Gene clusters sometimes contain all of the genes necessary and sufficient for a particular function. As an evolutionary mechanism, gene clusters facilitate the horizontal transfer of the complete function between species. Here, we review recent work on a number of clusters whose functions are relevant to biotechnology. Engineering these clusters has been hindered by their regulatory complexity, the need to balance the expression of many genes, and a lack of tools to design and manipulate DNA at this scale. Advances in synthetic biology will enable the large-scale bottom-up engineering of the clusters to optimize their functions, wake up cryptic clusters, or to transfer them between organisms. Understanding and manipulating gene clusters will move towards an era of genome engineering, where multiple functions can be “mixed-and-matched” to create a designer organism. PMID:21154668

Synthetic analog computation in living cells.

PubMed

Daniel, Ramiz; Rubens, Jacob R; Sarpeshkar, Rahul; Lu, Timothy K

2013-05-30

A central goal of synthetic biology is to achieve multi-signal integration and processing in living cells for diagnostic, therapeutic and biotechnology applications. Digital logic has been used to build small-scale circuits, but other frameworks may be needed for efficient computation in the resource-limited environments of cells. Here we demonstrate that synthetic analog gene circuits can be engineered to execute sophisticated computational functions in living cells using just three transcription factors. Such synthetic analog gene circuits exploit feedback to implement logarithmically linear sensing, addition, ratiometric and power-law computations. The circuits exhibit Weber's law behaviour as in natural biological systems, operate over a wide dynamic range of up to four orders of magnitude and can be designed to have tunable transfer functions. Our circuits can be composed to implement higher-order functions that are well described by both intricate biochemical models and simple mathematical functions. By exploiting analog building-block functions that are already naturally present in cells, this approach efficiently implements arithmetic operations and complex functions in the logarithmic domain. Such circuits may lead to new applications for synthetic biology and biotechnology that require complex computations with limited parts, need wide-dynamic-range biosensing or would benefit from the fine control of gene expression.

A Graph Approach to Mining Biological Patterns in the Binding Interfaces.

PubMed

Cheng, Wen; Yan, Changhui

2017-01-01

Protein-RNA interactions play important roles in the biological systems. Searching for regular patterns in the Protein-RNA binding interfaces is important for understanding how protein and RNA recognize each other and bind to form a complex. Herein, we present a graph-mining method for discovering biological patterns in the protein-RNA interfaces. We represented known protein-RNA interfaces using graphs and then discovered graph patterns enriched in the interfaces. Comparison of the discovered graph patterns with UniProt annotations showed that the graph patterns had a significant overlap with residue sites that had been proven crucial for the RNA binding by experimental methods. Using 200 patterns as input features, a support vector machine method was able to classify protein surface patches into RNA-binding sites and non-RNA-binding sites with 84.0% accuracy and 88.9% precision. We built a simple scoring function that calculated the total number of the graph patterns that occurred in a protein-RNA interface. That scoring function was able to discriminate near-native protein-RNA complexes from docking decoys with a performance comparable with that of a state-of-the-art complex scoring function. Our work also revealed possible patterns that might be important for binding affinity.

Functional complexity and ecosystem stability: an experimental approach

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

Van Voris, P.; O'Neill, R.V.; Shugart, H.H.

1978-01-01

The complexity-stability hypothesis was experimentally tested using intact terrestrial microcosms. Functional complexity was defined as the number and significance of component interactions (i.e., population interactions, physical-chemical reactions, biological turnover rates) influenced by nonlinearities, feedbacks, and time delays. It was postulated that functional complexity could be nondestructively measured through analysis of a signal generated from the system. Power spectral analysis of hourly CO/sub 2/ efflux, from eleven old-field microcosms, was analyzed for the number of low frequency peaks and used to rank the functional complexity of each system. Ranking of ecosystem stability was based on the capacity of the system tomore » retain essential nutrients and was measured by net loss of Ca after the system was stressed. Rank correlation supported the hypothesis that increasing ecosystem functional complexity leads to increasing ecosystem stability. The results indicated that complex functional dynamics can serve to stabilize the system. The results also demonstrated that microcosms are useful tools for system-level investigations.« less

Epigenomics and the concept of degeneracy in biological systems

PubMed Central

Mason, Paul H.; Barron, Andrew B.

2014-01-01

Researchers in the field of epigenomics are developing more nuanced understandings of biological complexity, and exploring the multiple pathways that lead to phenotypic expression. The concept of degeneracy—referring to the multiple pathways that a system recruits to achieve functional plasticity—is an important conceptual accompaniment to the growing body of knowledge in epigenomics. Distinct from degradation, redundancy and dilapidation; degeneracy refers to the plasticity of traits whose function overlaps in some environments, but diverges in others. While a redundant system is composed of repeated identical elements performing the same function, a degenerate system is composed of different elements performing similar or overlapping functions. Here, we describe the degenerate structure of gene regulatory systems from the basic genetic code to flexible epigenomic modifications, and discuss how these structural features have contributed to organism complexity, robustness, plasticity and evolvability. PMID:24335757

Engineering and control of biological systems: A new way to tackle complex diseases.

PubMed

Menolascina, Filippo; Siciliano, Velia; di Bernardo, Diego

2012-07-16

The ongoing merge between engineering and biology has contributed to the emerging field of synthetic biology. The defining features of this new discipline are abstraction and standardisation of biological parts, decoupling between parts to prevent undesired cross-talking, and the application of quantitative modelling of synthetic genetic circuits in order to guide their design. Most of the efforts in the field of synthetic biology in the last decade have been devoted to the design and development of functional gene circuits in prokaryotes and unicellular eukaryotes. Researchers have used synthetic biology not only to engineer new functions in the cell, but also to build simpler models of endogenous gene regulatory networks to gain knowledge of the "rules" governing their wiring diagram. However, the need for innovative approaches to study and modify complex signalling and regulatory networks in mammalian cells and multicellular organisms has prompted advances of synthetic biology also in these species, thus contributing to develop innovative ways to tackle human diseases. In this work, we will review the latest progress in synthetic biology and the most significant developments achieved so far, both in unicellular and multicellular organisms, with emphasis on human health. Copyright © 2012 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.

The Mediator Complex and Lipid Metabolism.

PubMed

Zhang, Yi; Xiaoli; Zhao, Xiaoping; Yang, Fajun

2013-03-01

The precise control of gene expression is essential for all biological processes. In addition to DNA-binding transcription factors, numerous transcription cofactors contribute another layer of regulation of gene transcription in eukaryotic cells. One of such transcription cofactors is the highly conserved Mediator complex, which has multiple subunits and is involved in various biological processes through directly interacting with relevant transcription factors. Although the current understanding on the biological functions of Mediator remains incomplete, research in the past decade has revealed an important role of Mediator in regulating lipid metabolism. Such function of Mediator is dependent on specific transcription factors, including peroxisome proliferator-activated receptor-gamma (PPARγ) and sterol regulatory element-binding proteins (SREBPs), which represent the master regulators of lipid metabolism. The medical significance of these findings is apparent, as aberrant lipid metabolism is intimately linked to major human diseases, such as type 2 diabetes and cardiovascular disease. Here, we briefly review the functions and molecular mechanisms of Mediator in regulation of lipid metabolism.

Thinking on building the network cardiovasology of Chinese medicine.

PubMed

Yu, Gui; Wang, Jie

2012-11-01

With advances in complex network theory, the thinking and methods regarding complex systems have changed revolutionarily. Network biology and network pharmacology were built by applying network-based approaches in biomedical research. The cardiovascular system may be regarded as a complex network, and cardiovascular diseases may be taken as the damage of structure and function of the cardiovascular network. Although Chinese medicine (CM) is effective in treating cardiovascular diseases, its mechanisms are still unclear. With the guidance of complex network theory, network biology and network pharmacology, network-based approaches could be used in the study of CM in preventing and treating cardiovascular diseases. A new discipline-network cardiovasology of CM was, therefore, developed. In this paper, complex network theory, network biology and network pharmacology were introduced and the connotation of "disease-syndrome-formula-herb" was illustrated from the network angle. Network biology could be used to analyze cardiovascular diseases and syndromes and network pharmacology could be used to analyze CM formulas and herbs. The "network-network"-based approaches could provide a new view for elucidating the mechanisms of CM treatment.

In Silico Analysis for the Study of Botulinum Toxin Structure

NASA Astrophysics Data System (ADS)

Suzuki, Tomonori; Miyazaki, Satoru

2010-01-01

Protein-protein interactions play many important roles in biological function. Knowledge of protein-protein complex structure is required for understanding the function. The determination of protein-protein complex structure by experimental studies remains difficult, therefore computational prediction of protein structures by structure modeling and docking studies is valuable method. In addition, MD simulation is also one of the most popular methods for protein structure modeling and characteristics. Here, we attempt to predict protein-protein complex structure and property using some of bioinformatic methods, and we focus botulinum toxin complex as target structure.

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

A versatile petri net based architecture for modeling and simulation of complex biological processes.

PubMed

Nagasaki, Masao; Doi, Atsushi; Matsuno, Hiroshi; Miyano, Satoru

2004-01-01

The research on modeling and simulation of complex biological systems is getting more important in Systems Biology. In this respect, we have developed Hybrid Function Petri net (HFPN) that was newly developed from existing Petri net because of their intuitive graphical representation and their capabilities for mathematical analyses. However, in the process of modeling metabolic, gene regulatory or signal transduction pathways with the architecture, we have realized three extensions of HFPN, (i) an entity should be extended to contain more than one value, (ii) an entity should be extended to handle other primitive types, e.g. boolean, string, (iii) an entity should be extended to handle more advanced type called object that consists of variables and methods, are necessary for modeling biological systems with Petri net based architecture. To deal with it, we define a new enhanced Petri net called hybrid functional Petri net with extension (HFPNe). To demonstrate the effectiveness of the enhancements, we model and simulate with HFPNe four biological processes that are diffcult to represent with the previous architecture HFPN.

End-to-end automated microfluidic platform for synthetic biology: from design to functional analysis

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

Linshiz, Gregory; Jensen, Erik; Stawski, Nina

Synthetic biology aims to engineer biological systems for desired behaviors. The construction of these systems can be complex, often requiring genetic reprogramming, extensive de novo DNA synthesis, and functional screening. Here, we present a programmable, multipurpose microfluidic platform and associated software and apply the platform to major steps of the synthetic biology research cycle: design, construction, testing, and analysis. We show the platform’s capabilities for multiple automated DNA assembly methods, including a new method for Isothermal Hierarchical DNA Construction, and for Escherichia coli and Saccharomyces cerevisiae transformation. The platform enables the automated control of cellular growth, gene expression induction, andmore » proteogenic and metabolic output analysis. Finally, taken together, we demonstrate the microfluidic platform’s potential to provide end-to-end solutions for synthetic biology research, from design to functional analysis.« less

End-to-end automated microfluidic platform for synthetic biology: from design to functional analysis

DOE PAGES

Linshiz, Gregory; Jensen, Erik; Stawski, Nina; ...

2016-02-02

Synthetic biology aims to engineer biological systems for desired behaviors. The construction of these systems can be complex, often requiring genetic reprogramming, extensive de novo DNA synthesis, and functional screening. Here, we present a programmable, multipurpose microfluidic platform and associated software and apply the platform to major steps of the synthetic biology research cycle: design, construction, testing, and analysis. We show the platform’s capabilities for multiple automated DNA assembly methods, including a new method for Isothermal Hierarchical DNA Construction, and for Escherichia coli and Saccharomyces cerevisiae transformation. The platform enables the automated control of cellular growth, gene expression induction, andmore » proteogenic and metabolic output analysis. Finally, taken together, we demonstrate the microfluidic platform’s potential to provide end-to-end solutions for synthetic biology research, from design to functional analysis.« less

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

Modelling protein functional domains in signal transduction using Maude

NASA Technical Reports Server (NTRS)

Sriram, M. G.

2003-01-01

Modelling of protein-protein interactions in signal transduction is receiving increased attention in computational biology. This paper describes recent research in the application of Maude, a symbolic language founded on rewriting logic, to the modelling of functional domains within signalling proteins. Protein functional domains (PFDs) are a critical focus of modern signal transduction research. In general, Maude models can simulate biological signalling networks and produce specific testable hypotheses at various levels of abstraction. Developing symbolic models of signalling proteins containing functional domains is important because of the potential to generate analyses of complex signalling networks based on structure-function relationships.

Chemometric strategy for modeling metabolic biological space along the gastrointestinal tract and assessing microbial influences.

PubMed

Martin, François-Pierre J; Montoliu, Ivan; Kochhar, Sunil; Rezzi, Serge

2010-12-01

Over the past decade, the analysis of metabolic data with advanced chemometric techniques has offered the potential to explore functional relationships among biological compartments in relation to the structure and function of the intestine. However, the employed methodologies, generally based on regression modeling techniques, have given emphasis to region-specific metabolic patterns, while providing only limited insights into the spatiotemporal metabolic features of the complex gastrointestinal system. Hence, novel approaches are needed to analyze metabolic data to reconstruct the metabolic biological space associated with the evolving structures and functions of an organ such as the gastrointestinal tract. Here, we report the application of multivariate curve resolution (MCR) methodology to model metabolic relationships along the gastrointestinal compartments in relation to its structure and function using data from our previous metabonomic analysis. The method simultaneously summarizes metabolite occurrence and contribution to continuous metabolic signatures of the different biological compartments of the gut tract. This methodology sheds new light onto the complex web of metabolic interactions with gut symbionts that modulate host cell metabolism in surrounding gut tissues. In the future, such an approach will be key to provide new insights into the dynamic onset of metabolic deregulations involved in region-specific gastrointestinal disorders, such as Crohn's disease or ulcerative colitis.

The Impact of Different Environmental Conditions on Cognitive Function: A Focused Review

PubMed Central

Taylor, Lee; Watkins, Samuel L.; Marshall, Hannah; Dascombe, Ben J.; Foster, Josh

2016-01-01

Cognitive function defines performance in objective tasks that require conscious mental effort. Extreme environments, namely heat, hypoxia, and cold can all alter human cognitive function due to a variety of psychological and/or biological processes. The aims of this Focused Review were to discuss; (1) the current state of knowledge on the effects of heat, hypoxic and cold stress on cognitive function, (2) the potential mechanisms underpinning these alterations, and (3) plausible interventions that may maintain cognitive function upon exposure to each of these environmental stressors. The available evidence suggests that the effects of heat, hypoxia, and cold stress on cognitive function are both task and severity dependent. Complex tasks are particularly vulnerable to extreme heat stress, whereas both simple and complex task performance appear to be vulnerable at even at moderate altitudes. Cold stress also appears to negatively impact both simple and complex task performance, however, the research in this area is sparse in comparison to heat and hypoxia. In summary, this focused review provides updated knowledge regarding the effects of extreme environmental stressors on cognitive function and their biological underpinnings. Tyrosine supplementation may help individuals maintain cognitive function in very hot, hypoxic, and/or cold conditions. However, more research is needed to clarify these and other postulated interventions. PMID:26779029

An integrative model of evolutionary covariance: a symposium on body shape in fishes.

PubMed

Walker, Jeffrey A

2010-12-01

A major direction of current and future biological research is to understand how multiple, interacting functional systems coordinate in producing a body that works. This understanding is complicated by the fact that organisms need to work well in multiple environments, with both predictable and unpredictable environmental perturbations. Furthermore, organismal design reflects a history of past environments and not a plan for future environments. How complex, interacting functional systems evolve, then, is a truly grand challenge. In accepting the challenge, an integrative model of evolutionary covariance is developed. The model combines quantitative genetics, functional morphology/physiology, and functional ecology. The model is used to convene scientists ranging from geneticists, to physiologists, to ecologists, to engineers to facilitate the emergence of body shape in fishes as a model system for understanding how complex, interacting functional systems develop and evolve. Body shape of fish is a complex morphology that (1) results from many developmental paths and (2) functions in many different behaviors. Understanding the coordination and evolution of the many paths from genes to body shape, body shape to function, and function to a working fish body in a dynamic environment is now possible given new technologies from genetics to engineering and new theoretical models that integrate the different levels of biological organization (from genes to ecology).

A Framework for Understanding the Characteristics of Complexity in Biology

ERIC Educational Resources Information Center

Dauer, Joseph; Dauer, Jenny

2016-01-01

Understanding the functioning of natural systems is not easy, although there is general agreement that understanding complex systems is an important goal for science education. Defining what makes a natural system complex will assist in identifying gaps in research on student reasoning about systems. The goal of this commentary is to propose a…

Genetic code expansion for multiprotein complex engineering.

PubMed

Koehler, Christine; Sauter, Paul F; Wawryszyn, Mirella; Girona, Gemma Estrada; Gupta, Kapil; Landry, Jonathan J M; Fritz, Markus Hsi-Yang; Radic, Ksenija; Hoffmann, Jan-Erik; Chen, Zhuo A; Zou, Juan; Tan, Piau Siong; Galik, Bence; Junttila, Sini; Stolt-Bergner, Peggy; Pruneri, Giancarlo; Gyenesei, Attila; Schultz, Carsten; Biskup, Moritz Bosse; Besir, Hueseyin; Benes, Vladimir; Rappsilber, Juri; Jechlinger, Martin; Korbel, Jan O; Berger, Imre; Braese, Stefan; Lemke, Edward A

2016-12-01

We present a baculovirus-based protein engineering method that enables site-specific introduction of unique functionalities in a eukaryotic protein complex recombinantly produced in insect cells. We demonstrate the versatility of this efficient and robust protein production platform, 'MultiBacTAG', (i) for the fluorescent labeling of target proteins and biologics using click chemistries, (ii) for glycoengineering of antibodies, and (iii) for structure-function studies of novel eukaryotic complexes using single-molecule Förster resonance energy transfer as well as site-specific crosslinking strategies.

RNA and RNP as Building Blocks for Nanotechnology and Synthetic Biology.

PubMed

Ohno, Hirohisa; Saito, Hirohide

2016-01-01

Recent technologies that aimed to elucidate cellular function have revealed essential roles for RNA molecules in living systems. Our knowledge concerning functional and structural information of naturally occurring RNA and RNA-protein (RNP) complexes is increasing rapidly. RNA and RNP interaction motifs are structural units that function as building blocks to constitute variety of complex structures. RNA-central synthetic biology and nanotechnology are constructive approaches that employ the accumulated information and build synthetic RNA (RNP)-based circuits and nanostructures. Here, we describe how to design and construct synthetic RNA (RNP)-based devices and structures at the nanometer-scale for biological and future therapeutic applications. RNA/RNP nanostructures can also be utilized as the molecular scaffold to control the localization or interactions of target molecule(s). Moreover, RNA motifs recognized by RNA-binding proteins can be applied to make protein-responsive translational "switches" that can turn gene expression "on" or "off" depending on the intracellular environment. This "synthetic RNA and RNP world" will expand tools for nanotechnology and synthetic biology. In addition, these reconstructive approaches would lead to a greater understanding of building principle in naturally occurring RNA/RNP molecules and systems. Copyright © 2016 Elsevier Inc. All rights reserved.

Quantification of Degeneracy in Biological Systems for Characterization of Functional Interactions Between Modules

PubMed Central

Li, Yao; Dwivedi, Gaurav; Huang, Wen; Yi, Yingfei

2012-01-01

There is an evolutionary advantage in having multiple components with overlapping functionality (i.e degeneracy) in organisms. While theoretical considerations of degeneracy have been well established in neural networks using information theory, the same concepts have not been developed for differential systems, which form the basis of many biochemical reaction network descriptions in systems biology. Here we establish mathematical definitions of degeneracy, complexity and robustness that allow for the quantification of these properties in a system. By exciting a dynamical system with noise, the mutual information associated with a selected observable output and the interacting subspaces of input components can be used to define both complexity and degeneracy. The calculation of degeneracy in a biological network is a useful metric for evaluating features such as the sensitivity of a biological network to environmental evolutionary pressure. Using a two-receptor signal transduction network, we find that redundant components will not yield high degeneracy whereas compensatory mechanisms established by pathway crosstalk will. This form of analysis permits interrogation of large-scale differential systems for non-identical, functionally equivalent features that have evolved to maintain homeostasis during disruption of individual components. PMID:22619750

Molecular dynamics simulations of large macromolecular complexes.

PubMed

Perilla, Juan R; Goh, Boon Chong; Cassidy, C Keith; Liu, Bo; Bernardi, Rafael C; Rudack, Till; Yu, Hang; Wu, Zhe; Schulten, Klaus

2015-04-01

Connecting dynamics to structural data from diverse experimental sources, molecular dynamics simulations permit the exploration of biological phenomena in unparalleled detail. Advances in simulations are moving the atomic resolution descriptions of biological systems into the million-to-billion atom regime, in which numerous cell functions reside. In this opinion, we review the progress, driven by large-scale molecular dynamics simulations, in the study of viruses, ribosomes, bioenergetic systems, and other diverse applications. These examples highlight the utility of molecular dynamics simulations in the critical task of relating atomic detail to the function of supramolecular complexes, a task that cannot be achieved by smaller-scale simulations or existing experimental approaches alone. Copyright © 2015 Elsevier Ltd. All rights reserved.

Short-term bioassay of complex organic mixtures. Part II. Mutagenicity testing

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

Epler, J.L.; Clark, B.R.; Ho, C.

1978-01-01

The feasibility of using short-term mutagenicity assays to predict the potential biohazard of various crude and complex test materials has been examined in a coupled chemical and biological approach. The principal focus of the research has involved the preliminary chemical characterizatiion and preparation for bioassay, followed by testing in the Salmonella histidine reversion assay system. The mutagenicity tests are intended to act as predictors of profound long-range health effects such as mutagenesis and/or carcinogenesis; act as a mechanism to rapidly isolate and identify a hazardous agent in a complex mixture; and function as a measure of biological activity correlating baselinemore » data with changes in process conditions. Since complex mixtures can be fractionated and approached in these short-term assays, information reflecting on the actual compounds responsible for the biological effect may be accumulated.« less

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.

Selenistasis: Epistatic Effects of Selenium on Cardiovascular Phenotype

PubMed Central

Joseph, Jacob; Loscalzo, Joseph

2013-01-01

Although selenium metabolism is intricately linked to cardiovascular biology and function, and deficiency of selenium is associated with cardiac pathology, utilization of selenium in the prevention and treatment of cardiovascular disease remains an elusive goal. From a reductionist standpoint, the major function of selenium in vivo is antioxidant defense via its incorporation as selenocysteine into enzyme families such as glutathione peroxidases and thioredoxin reductases. In addition, selenium compounds are heterogeneous and have complex metabolic fates resulting in effects that are not entirely dependent on selenoprotein expression. This complex biology of selenium in vivo may underlie the fact that beneficial effects of selenium supplementation demonstrated in preclinical studies using models of oxidant stress-induced cardiovascular dysfunction, such as ischemia-reperfusion injury and myocardial infarction, have not been consistently observed in clinical trials. In fact, recent studies have yielded data that suggest that unselective supplementation of selenium may, indeed, be harmful. Interesting biologic actions of selenium are its simultaneous effects on redox balance and methylation status, a combination that may influence gene expression. These combined actions may explain some of the biphasic effects seen with low and high doses of selenium, the potentially harmful effects seen in normal individuals, and the beneficial effects noted in preclinical studies of disease. Given the complexity of selenium biology, systems biology approaches may be necessary to reach the goal of optimization of selenium status to promote health and prevent disease. PMID:23434902

[Physico-chemical features of dinitrosyl iron complexes with natural thiol-containing ligands underlying biological activities of these complexes].

PubMed

Vanin, A F; Borodulin, R R; Kubrina, L N; Mikoian, V D; Burbaev, D Sh

2013-01-01

Current notions and new experimental data of the authors on physico-chemical features of dinitrosyl iron complexes with natural thiol-containing ligands (glutathione or cysteine), underlying the ability of the complexes to act as NO molecule and nitrosonium ion donors, are considered. This ability determines various biological activities of dinitrosyl iron complexes--inducing long-lasting vasodilation and thereby long-lasting hypotension in human and animals, inhibiting pellet aggregation, increasing red blood cell elasticity, thereby stimulating microcirculation, and reducing necrotic zone in animals with myocardial infarction. Moreover, dinitrosyl iron complexes are capable of accelerating skin wound healing, improving the function of penile cavernous tissue, blocking apoptosis development in cell cultures. When decomposed dinitrosyl iron complexes can exert cytotoxic effect that can be used for curing infectious and carcinogenic pathologies.

Structure-Based Characterization of Multiprotein Complexes

PubMed Central

Wiederstein, Markus; Gruber, Markus; Frank, Karl; Melo, Francisco; Sippl, Manfred J.

2014-01-01

Summary Multiprotein complexes govern virtually all cellular processes. Their 3D structures provide important clues to their biological roles, especially through structural correlations among protein molecules and complexes. The detection of such correlations generally requires comprehensive searches in databases of known protein structures by means of appropriate structure-matching techniques. Here, we present a high-speed structure search engine capable of instantly matching large protein oligomers against the complete and up-to-date database of biologically functional assemblies of protein molecules. We use this tool to reveal unseen structural correlations on the level of protein quaternary structure and demonstrate its general usefulness for efficiently exploring complex structural relationships among known protein assemblies. PMID:24954616

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

Design and control strategies for CELSS - Integrating mechanistic paradigms and biological complexities

NASA Technical Reports Server (NTRS)

Moore, B., III; Kaufmann, R.; Reinhold, C.

1981-01-01

Systems analysis and control theory consideration are given to simulations of both individual components and total systems, in order to develop a reliable control strategy for a Controlled Ecological Life Support System (CELSS) which includes complex biological components. Because of the numerous nonlinearities and tight coupling within the biological component, classical control theory may be inadequate and the statistical analysis of factorial experiments more useful. The range in control characteristics of particular species may simplify the overall task by providing an appropriate balance of stability and controllability to match species function in the overall design. The ultimate goal of this research is the coordination of biological and mechanical subsystems in order to achieve a self-supporting environment.

Directed Evolution as a Powerful Synthetic Biology Tool

PubMed Central

Cobb, Ryan E.; Sun, Ning; Zhao, Huimin

2012-01-01

At the heart of synthetic biology lies the goal of rationally engineering a complete biological system to achieve a specific objective, such as bioremediation and synthesis of a valuable drug, chemical, or biofuel molecule. However, the inherent complexity of natural biological systems has heretofore precluded generalized application of this approach. Directed evolution, a process which mimics Darwinian selection on a laboratory scale, has allowed significant strides to be made in the field of synthetic biology by allowing rapid identification of desired properties from large libraries of variants. Improvement in biocatalyst activity and stability, engineering of biosynthetic pathways, tuning of functional regulatory systems and logic circuits, and development of desired complex phenotypes in industrial host organisms have all been achieved by way of directed evolution. Here, we review recent contributions of directed evolution to synthetic biology at the protein, pathway, network, and whole cell levels. PMID:22465795

Physics Meets Biology (LBNL Summer Lecture Series)

ScienceCinema

Chu, Steven

2018-05-09

Summer Lecture Series 2006: If scientists could take advantage of the awesomely complex and beautiful functioning of biology's natural molecular machines, their potential for application in many disciplines would be incalculable. Nobel Laureate and Director of the Lawrence Berkeley National Laboratory Steve Chu explores Possible solutions to global warming and its consequences.

The cell biology of inflammasomes: Mechanisms of inflammasome activation and regulation

PubMed Central

2016-01-01

Over the past decade, numerous advances have been made in the role and regulation of inflammasomes during pathogenic and sterile insults. An inflammasome complex comprises a sensor, an adaptor, and a zymogen procaspase-1. The functional output of inflammasome activation includes secretion of cytokines, IL-1β and IL-18, and induction of an inflammatory form of cell death called pyroptosis. Recent studies have highlighted the intersection of this inflammatory response with fundamental cellular processes. Novel modulators and functions of inflammasome activation conventionally associated with the maintenance of homeostatic biological functions have been uncovered. In this review, we discuss the biological processes involved in the activation and regulation of the inflammasome. PMID:27325789

Mathematical and numerical challenges in living biological materials

NASA Astrophysics Data System (ADS)

Forest, M. Gregory; Vasquez, Paula A.

2013-10-01

The proclaimed Century of Biology is rapidly leading to the realization of how starkly different and more complex biological materials are than the materials that underpinned the industrial and technological revolution. These differences arise, in part, because biological matter exhibits both viscous and elastic behavior. Moreover, this behavior varies across the frequency, wavelength and amplitude spectrum of forcing. This broadclass of responsesin biological matter requires multiple frequency-dependent functions to specify material behavior, instead of a discrete set of parameters that relate to either viscosity or elasticity. This complexity prevails even if the biological matter is assumed to be spatially homogeneous, which is rarely true. However, very little progress has been made on the characterization of heterogeneity and how to build that information into constitutive laws and predictive models. In addition, most biological matter is non-stationary, which motivates the term "living". Biomaterials typically are in an active state in order to perform certain functions, and they often are modified or replenished on the basis of external stimuli. It has become popular in materials engineering to try to duplicate some of the functionality of biomaterials, e.g., a lot of effort has gone into the design of self-assembling, self-healing and shape shifting materials. These distinguishing features of biomaterials require significantly more degrees of freedom than traditional composites and many of the molecular species and their roles in functionality have yet to be determined. A typical biological material includes small molecule biochemical species that react and diffuse within larger species. These large molecular weightspecies provide the primary structural and biophysical properties of the material. The small molecule binding and unbinding kinetics serves to modulate material properties, and typical small molecule production and release are governed by external stimuli (e.g., stress). The bottom line is that the mathematical and numerical tools of 20th Century materials science are often insufficient for describing biological materials and for predicting their behavior both in vitro and in vivo.

Creating biomaterials with spatially organized functionality.

PubMed

Chow, Lesley W; Fischer, Jacob F

2016-05-01

Biomaterials for tissue engineering provide scaffolds to support cells and guide tissue regeneration. Despite significant advances in biomaterials design and fabrication techniques, engineered tissue constructs remain functionally inferior to native tissues. This is largely due to the inability to recreate the complex and dynamic hierarchical organization of the extracellular matrix components, which is intimately linked to a tissue's biological function. This review discusses current state-of-the-art strategies to control the spatial presentation of physical and biochemical cues within a biomaterial to recapitulate native tissue organization and function. © 2016 by the Society for Experimental Biology and Medicine.

A Comprehensive Database and Analysis Framework To Incorporate Multiscale Data Types and Enable Integrated Analysis of Bioactive Polyphenols.

PubMed

Ho, Lap; Cheng, Haoxiang; Wang, Jun; Simon, James E; Wu, Qingli; Zhao, Danyue; Carry, Eileen; Ferruzzi, Mario G; Faith, Jeremiah; Valcarcel, Breanna; Hao, Ke; Pasinetti, Giulio M

2018-03-05

The development of a given botanical preparation for eventual clinical application requires extensive, detailed characterizations of the chemical composition, as well as the biological availability, biological activity, and safety profiles of the botanical. These issues are typically addressed using diverse experimental protocols and model systems. Based on this consideration, in this study we established a comprehensive database and analysis framework for the collection, collation, and integrative analysis of diverse, multiscale data sets. Using this framework, we conducted an integrative analysis of heterogeneous data from in vivo and in vitro investigation of a complex bioactive dietary polyphenol-rich preparation (BDPP) and built an integrated network linking data sets generated from this multitude of diverse experimental paradigms. We established a comprehensive database and analysis framework as well as a systematic and logical means to catalogue and collate the diverse array of information gathered, which is securely stored and added to in a standardized manner to enable fast query. We demonstrated the utility of the database in (1) a statistical ranking scheme to prioritize response to treatments and (2) in depth reconstruction of functionality studies. By examination of these data sets, the system allows analytical querying of heterogeneous data and the access of information related to interactions, mechanism of actions, functions, etc., which ultimately provide a global overview of complex biological responses. Collectively, we present an integrative analysis framework that leads to novel insights on the biological activities of a complex botanical such as BDPP that is based on data-driven characterizations of interactions between BDPP-derived phenolic metabolites and their mechanisms of action, as well as synergism and/or potential cancellation of biological functions. Out integrative analytical approach provides novel means for a systematic integrative analysis of heterogeneous data types in the development of complex botanicals such as polyphenols for eventual clinical and translational applications.

A top-level ontology of functions and its application in the Open Biomedical Ontologies.

PubMed

Burek, Patryk; Hoehndorf, Robert; Loebe, Frank; Visagie, Johann; Herre, Heinrich; Kelso, Janet

2006-07-15

A clear understanding of functions in biology is a key component in accurate modelling of molecular, cellular and organismal biology. Using the existing biomedical ontologies it has been impossible to capture the complexity of the community's knowledge about biological functions. We present here a top-level ontological framework for representing knowledge about biological functions. This framework lends greater accuracy, power and expressiveness to biomedical ontologies by providing a means to capture existing functional knowledge in a more formal manner. An initial major application of the ontology of functions is the provision of a principled way in which to curate functional knowledge and annotations in biomedical ontologies. Further potential applications include the facilitation of ontology interoperability and automated reasoning. A major advantage of the proposed implementation is that it is an extension to existing biomedical ontologies, and can be applied without substantial changes to these domain ontologies. The Ontology of Functions (OF) can be downloaded in OWL format from http://onto.eva.mpg.de/. Additionally, a UML profile and supplementary information and guides for using the OF can be accessed from the same website.

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

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.

Biomimicry Promotes the Efficiency of a 10-Step Sequential Enzymatic Reaction on Nanoparticles, Converting Glucose to Lactate.

PubMed

Mukai, Chinatsu; Gao, Lizeng; Nelson, Jacquelyn L; Lata, James P; Cohen, Roy; Wu, Lauren; Hinchman, Meleana M; Bergkvist, Magnus; Sherwood, Robert W; Zhang, Sheng; Travis, Alexander J

2017-01-02

For nanobiotechnology to achieve its potential, complex organic-inorganic systems must grow to utilize the sequential functions of multiple biological components. Critical challenges exist: immobilizing enzymes can block substrate-binding sites or prohibit conformational changes, substrate composition can interfere with activity, and multistep reactions risk diffusion of intermediates. As a result, the most complex tethered reaction reported involves only 3 enzymes. Inspired by the oriented immobilization of glycolytic enzymes on the fibrous sheath of mammalian sperm, here we show a complex reaction of 10 enzymes tethered to nanoparticles. Although individual enzyme efficiency was higher in solution, the efficacy of the 10-step pathway measured by conversion of glucose to lactate was significantly higher when tethered. To our knowledge, this is the most complex organic-inorganic system described, and it shows that tethered, multi-step biological pathways can be reconstituted in hybrid systems to carry out functions such as energy production or delivery of molecular cargo. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Biomimicry promotes the efficiency of a 10-step sequential enzymatic reaction on nanoparticles, converting glucose to lactate

PubMed Central

Mukai, Chinatsu; Gao, Lizeng; Nelson, Jacquelyn L.; Lata, James P.; Cohen, Roy; Wu, Lauren; Hinchman, Meleana M.; Bergkvist, Magnus; Sherwood, Robert W.; Zhang, Sheng; Travis, Alexander J.

2016-01-01

For nanobiotechnology to achieve its potential, complex organic-inorganic systems must grow to utilize the sequential functions of multiple biological components. Critical challenges exist: immobilizing enzymes can block substrate-binding sites or prohibit conformational changes, substrate composition can interfere with activity, and multistep reactions risk diffusion of intermediates. As a result, the most complex tethered reaction reported involves only 3 enzymes. Inspired by the oriented immobilization of glycolytic enzymes on the fibrous sheath of mammalian sperm, here we show a complex reaction of 10 enzymes tethered to nanoparticles. Although individual enzyme efficiency was higher in solution, the efficacy of the 10-step pathway measured by conversion of glucose to lactate was significantly higher when tethered. To our knowledge, this is the most complex organic-inorganic system described, and it shows that tethered, multi-step biological pathways can be reconstituted in hybrid systems to carry out functions such as energy production or delivery of molecular cargo. PMID:27901298

Synthetic Genomics and Synthetic Biology Applications Between Hopes and Concerns

PubMed Central

König, Harald; Frank, Daniel; Heil, Reinhard; Coenen, Christopher

2013-01-01

New organisms and biological systems designed to satisfy human needs are among the aims of synthetic genomics and synthetic biology. Synthetic biology seeks to model and construct biological components, functions and organisms that do not exist in nature or to redesign existing biological systems to perform new functions. Synthetic genomics, on the other hand, encompasses technologies for the generation of chemically-synthesized whole genomes or larger parts of genomes, allowing to simultaneously engineer a myriad of changes to the genetic material of organisms. Engineering complex functions or new organisms in synthetic biology are thus progressively becoming dependent on and converging with synthetic genomics. While applications from both areas have been predicted to offer great benefits by making possible new drugs, renewable chemicals or clean energy, they have also given rise to concerns about new safety, environmental and socio-economic risks – stirring an increasingly polarizing debate. Here we intend to provide an overview on recent progress in biomedical and biotechnological applications of synthetic genomics and synthetic biology as well as on arguments and evidence related to their possible benefits, risks and governance implications. PMID:23997647

Micro/nanofabricated environments for synthetic biology.

PubMed

Collier, C Patrick; Simpson, Michael L

2011-08-01

A better understanding of how confinement, crowding and reduced dimensionality modulate reactivity and reaction dynamics will aid in the rational and systematic discovery of functionality in complex biological systems. Artificial microfabricated and nanofabricated structures have helped elucidate the effects of nanoscale spatial confinement and segregation on biological behavior, particularly when integrated with microfluidics, through precise control in both space and time of diffusible signals and binding interactions. Examples of nanostructured interfaces for synthetic biology include the development of cell-like compartments for encapsulating biochemical reactions, nanostructured environments for fundamental studies of diffusion, molecular transport and biochemical reaction kinetics, and regulation of biomolecular interactions as functions of microfabricated and nanofabricated topological constraints. Copyright © 2011 Elsevier Ltd. All rights reserved.

Bayesian uncertainty analysis for complex systems biology models: emulation, global parameter searches and evaluation of gene functions.

PubMed

Vernon, Ian; Liu, Junli; Goldstein, Michael; Rowe, James; Topping, Jen; Lindsey, Keith

2018-01-02

Many mathematical models have now been employed across every area of systems biology. These models increasingly involve large numbers of unknown parameters, have complex structure which can result in substantial evaluation time relative to the needs of the analysis, and need to be compared to observed data of various forms. The correct analysis of such models usually requires a global parameter search, over a high dimensional parameter space, that incorporates and respects the most important sources of uncertainty. This can be an extremely difficult task, but it is essential for any meaningful inference or prediction to be made about any biological system. It hence represents a fundamental challenge for the whole of systems biology. Bayesian statistical methodology for the uncertainty analysis of complex models is introduced, which is designed to address the high dimensional global parameter search problem. Bayesian emulators that mimic the systems biology model but which are extremely fast to evaluate are embeded within an iterative history match: an efficient method to search high dimensional spaces within a more formal statistical setting, while incorporating major sources of uncertainty. The approach is demonstrated via application to a model of hormonal crosstalk in Arabidopsis root development, which has 32 rate parameters, for which we identify the sets of rate parameter values that lead to acceptable matches between model output and observed trend data. The multiple insights into the model's structure that this analysis provides are discussed. The methodology is applied to a second related model, and the biological consequences of the resulting comparison, including the evaluation of gene functions, are described. Bayesian uncertainty analysis for complex models using both emulators and history matching is shown to be a powerful technique that can greatly aid the study of a large class of systems biology models. It both provides insight into model behaviour and identifies the sets of rate parameters of interest.

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

EPR Characterization of Dinitrosyl Iron Complexes with Thiol-Containing Ligands as an Approach to Their Identification in Biological Objects: An Overview.

PubMed

Vanin, Anatoly F

2018-06-01

The overview demonstrates how the use of only one physico-chemical approach, viz., the electron paramagnetic resonance method, allowed detection and identification of dinitrosyl iron complexes with thiol-containing ligands in various animal and bacterial cells. These complexes are formed in biological objects in the paramagnetic (electron paramagnetic resonance-active) mononuclear and diamagnetic (electron paramagnetic resonance-silent) binuclear forms and control the activity of nitrogen monoxide, one of the most universal regulators of metabolic processes in the organism. The analysis of electronic and spatial structures of dinitrosyl iron complex sheds additional light on the mechanism whereby dinitrosyl iron complex with thiol-containing ligands function in human and animal cells as donors of nitrogen monoxide and its ionized form, viz., nitrosonium ions (NO + ).

Pectin in foods

USDA-ARS?s Scientific Manuscript database

Pectin, a complex polysaccharide, is a major component of non-lignified cell walls of dicotyledonous and some monocotyledonous plants. Its food-related technological functions are numerous and mirror many of its biological functions. As a naturally occurring component of raw or processed foods and a...

Regulation of metabolism by the Mediator complex.

PubMed

Youn, Dou Yeon; Xiaoli, Alus M; Pessin, Jeffrey E; Yang, Fajun

2016-01-01

The Mediator complex was originally discovered in yeast, but it is conserved in all eukaryotes. Its best-known function is to regulate RNA polymerase II-dependent gene transcription. Although the mechanisms by which the Mediator complex regulates transcription are often complicated by the context-dependent regulation, this transcription cofactor complex plays a pivotal role in numerous biological pathways. Biochemical, molecular, and physiological studies using cancer cell lines or model organisms have established the current paradigm of the Mediator functions. However, the physiological roles of the mammalian Mediator complex remain poorly defined, but have attracted a great interest in recent years. In this short review, we will summarize some of the reported functions of selective Mediator subunits in the regulation of metabolism. These intriguing findings suggest that the Mediator complex may be an important player in nutrient sensing and energy balance in mammals.

Time dependent-density functional theory (TD-DFT) and experimental studies of UV-Visible spectra and cyclic voltammetry for Cu(II) complex with Et2DTC

NASA Astrophysics Data System (ADS)

Valle, Eliana Maira A.; Maltarollo, Vinicius Gonçalves; Almeida, Michell O.; Honorio, Kathia Maria; dos Santos, Mauro Coelho; Cerchiaro, Giselle

2018-04-01

In this work, we studied the complexation mode between copper(II) ion and the specific ligand investigated as carriers of metals though biological membranes, diethyldithiocarbamate (Et2DTC). It is important to understand how this occurs because it is an important intracellular chelator with potential therapeutic applications. Theoretical and experimental UV visible studies were performed to investigate the complexation mode between copper and the ligand. Electrochemical studies were also performed to complement the spectroscopic analyses. According to the theoretical calculations, using TD-DFT (Time dependent density functional theory), with B3LYP functional and DGDVZP basis set, implemented in Gaussian 03 package, it was observed that the formation of the complex [Cu(Et2DTC)2] is favorable with higher electron density over the sulfur atoms of the ligand. UV/Vis spectra have a charge transfer band at 450 nm, with the DMSO-d6 band shift from 800 to 650 nm. The electrochemical experiments showed the formation of a new redox process, referring to the complex, where the reduction peak potential of copper is displaced to less positive region. Therefore, the results obtained from this study give important insights on possible mechanisms involved in several biological processes related to the studied system.

Linear control theory for gene network modeling.

PubMed

Shin, Yong-Jun; Bleris, Leonidas

2010-09-16

Systems biology is an interdisciplinary field that aims at understanding complex interactions in cells. Here we demonstrate that linear control theory can provide valuable insight and practical tools for the characterization of complex biological networks. We provide the foundation for such analyses through the study of several case studies including cascade and parallel forms, feedback and feedforward loops. We reproduce experimental results and provide rational analysis of the observed behavior. We demonstrate that methods such as the transfer function (frequency domain) and linear state-space (time domain) can be used to predict reliably the properties and transient behavior of complex network topologies and point to specific design strategies for synthetic networks.

Deconstructing and constructing innate immune functions using molecular sensors and actuators

NASA Astrophysics Data System (ADS)

Coutinho, Kester; Inoue, Takanari

2016-05-01

White blood cells such as neutrophils and macrophages are made competent for chemotaxis and phagocytosis -- the dynamic cellular behaviors that are hallmarks of their innate immune functions -- by the reorganization of complex biological circuits during differentiation. Conventional loss-of-function approaches have revealed that more than 100 genes participate in these cellular functions, and we have begun to understand the intricate signaling circuits that are built up from these gene products. We now appreciate: (1) that these circuits come in a variety of flavors -- so that we can make a distinction between genetic circuits, metabolic circuits and signaling circuits; and (2) that they are usually so complex that the assumption of multiple feedback loops, as well as that of crosstalk between seemingly independent pathways, is now routine. It has not escaped our notice, however, that just as physicists and electrical engineers have long been able to disentangle complex electric circuits simply by repetitive cycles of probing and measuring electric currents using a voltmeter, we might similarly be able to dissect these intricate biological circuits by incorporating equivalent approaches in the fields of cell biology and bioengineering. Existing techniques in biology for probing individual circuit components are unfortunately lacking, so that the overarching goal of drawing an exact circuit diagram for the whole cell -- complete with kinetic parameters for connections between individual circuit components -- is not yet in near sight. My laboratory and others have thus begun the development of a new series of molecular tools that can measurably investigate the circuit connectivity inside living cells, as if we were doing so on a silicon board. In these proceedings, I will introduce some of these techniques, provide examples of their implementation, and offer a perspective on directions moving forward.

Exploring biological interaction networks with tailored weighted quasi-bicliques

PubMed Central

2012-01-01

Background Biological networks provide fundamental insights into the functional characterization of genes and their products, the characterization of DNA-protein interactions, the identification of regulatory mechanisms, and other biological tasks. Due to the experimental and biological complexity, their computational exploitation faces many algorithmic challenges. Results We introduce novel weighted quasi-biclique problems to identify functional modules in biological networks when represented by bipartite graphs. In difference to previous quasi-biclique problems, we include biological interaction levels by using edge-weighted quasi-bicliques. While we prove that our problems are NP-hard, we also describe IP formulations to compute exact solutions for moderately sized networks. Conclusions We verify the effectiveness of our IP solutions using both simulation and empirical data. The simulation shows high quasi-biclique recall rates, and the empirical data corroborate the abilities of our weighted quasi-bicliques in extracting features and recovering missing interactions from biological networks. PMID:22759421

Modular analysis of biological networks.

PubMed

Kaltenbach, Hans-Michael; Stelling, Jörg

2012-01-01

The analysis of complex biological networks has traditionally relied on decomposition into smaller, semi-autonomous units such as individual signaling pathways. With the increased scope of systems biology (models), rational approaches to modularization have become an important topic. With increasing acceptance of de facto modularity in biology, widely different definitions of what constitutes a module have sparked controversies. Here, we therefore review prominent classes of modular approaches based on formal network representations. Despite some promising research directions, several important theoretical challenges remain open on the way to formal, function-centered modular decompositions for dynamic biological networks.

Structure-based characterization of multiprotein complexes.

PubMed

Wiederstein, Markus; Gruber, Markus; Frank, Karl; Melo, Francisco; Sippl, Manfred J

2014-07-08

Multiprotein complexes govern virtually all cellular processes. Their 3D structures provide important clues to their biological roles, especially through structural correlations among protein molecules and complexes. The detection of such correlations generally requires comprehensive searches in databases of known protein structures by means of appropriate structure-matching techniques. Here, we present a high-speed structure search engine capable of instantly matching large protein oligomers against the complete and up-to-date database of biologically functional assemblies of protein molecules. We use this tool to reveal unseen structural correlations on the level of protein quaternary structure and demonstrate its general usefulness for efficiently exploring complex structural relationships among known protein assemblies. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.

Biological invasions on oceanic islands: Implications for island ecosystems and avifauna

Treesearch

Dean E. Pearson

2009-01-01

Biological invasions present a global threat to biodiversity, but oceanic islands are the systems hardest hit by invasions. Islands are generally depauperate in species richness, trophic complexity, and functional diversity relative to comparable mainland ecosystems. This situation results in low biotic resistance to invasion and many empty niches for invaders to...

What's My Math Course Got to Do with Biology?

ERIC Educational Resources Information Center

Burks, Robert; Lindquist, Joseph; McMurran, Shawnee

2008-01-01

At United States Military Academy, a unit on biological modeling applications forms the culminating component of the first semester core mathematics course for freshmen. The course emphasizes the use of problem-solving strategies and modeling to solve complex and ill-defined problems. Topic areas include functions and their shapes, data fitting,…

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.

MIMO: an efficient tool for molecular interaction maps overlap

PubMed Central

2013-01-01

Background Molecular pathways represent an ensemble of interactions occurring among molecules within the cell and between cells. The identification of similarities between molecular pathways across organisms and functions has a critical role in understanding complex biological processes. For the inference of such novel information, the comparison of molecular pathways requires to account for imperfect matches (flexibility) and to efficiently handle complex network topologies. To date, these characteristics are only partially available in tools designed to compare molecular interaction maps. Results Our approach MIMO (Molecular Interaction Maps Overlap) addresses the first problem by allowing the introduction of gaps and mismatches between query and template pathways and permits -when necessary- supervised queries incorporating a priori biological information. It then addresses the second issue by relying directly on the rich graph topology described in the Systems Biology Markup Language (SBML) standard, and uses multidigraphs to efficiently handle multiple queries on biological graph databases. The algorithm has been here successfully used to highlight the contact point between various human pathways in the Reactome database. Conclusions MIMO offers a flexible and efficient graph-matching tool for comparing complex biological pathways. PMID:23672344

Decoding Mechanisms by which Silent Codon Changes Influence Protein Biogenesis and Function

PubMed Central

Bali, Vedrana; Bebok, Zsuzsanna

2015-01-01

Scope Synonymous codon usage has been a focus of investigation since the discovery of the genetic code and its redundancy. The occurrences of synonymous codons vary between species and within genes of the same genome, known as codon usage bias. Today, bioinformatics and experimental data allow us to compose a global view of the mechanisms by which the redundancy of the genetic code contributes to the complexity of biological systems from affecting survival in prokaryotes, to fine tuning the structure and function of proteins in higher eukaryotes. Studies analyzing the consequences of synonymous codon changes in different organisms have revealed that they impact nucleic acid stability, protein levels, structure and function without altering amino acid sequence. As such, synonymous mutations inevitably contribute to the pathogenesis of complex human diseases. Yet, fundamental questions remain unresolved regarding the impact of silent mutations in human disorders. In the present review we describe developments in this area concentrating on mechanisms by which synonymous mutations may affect protein function and human health. Purpose This synopsis illustrates the significance of synonymous mutations in disease pathogenesis. We review the different steps of gene expression affected by silent mutations, and assess the benefits and possible harmful effects of codon optimization applied in the development of therapeutic biologics. Physiological and medical relevance Understanding mechanisms by which synonymous mutations contribute to complex diseases such as cancer, neurodegeneration and genetic disorders, including the limitations of codon-optimized biologics, provides insight concerning interpretation of silent variants and future molecular therapies. PMID:25817479

The biological effect of asbestos exposure is dependent on changes in iron homeostasis

EPA Science Inventory

Abstract Functional groups on the surface of fibrous silicates can complex iron. We tested the postulate that 1) asbestos complexes and sequesters host cell iron resulting in a disruption of metal homeostasis and 2) this loss of essential metal results in an oxidative stress and...

The search for Pleiades in trait constellations: functional integration and phenotypic selection in the complex flowers of Morrenia brachystephana (Apocynaceae).

PubMed

Baranzelli, M C; Sérsic, A N; Cocucci, A A

2014-04-01

Pollinator-mediated natural selection on single traits, such as corolla tube or spur length, has been well documented. However, flower phenotypes are usually complex, and selection is expected to act on several traits that functionally interact rather than on a single isolated trait. Despite the fact that selection on complex phenotypes is expectedly widespread, multivariate selection modelling on such phenotypes still remains under-explored in plants. Species of the subfamily Asclepiadoideae (Apocynaceae) provide an opportunity to study such complex flower contrivances integrated by fine-scaled organs from disparate developmental origin. We studied the correlation structure among linear floral traits (i) by testing a priori morphological, functional or developmental hypotheses among traits and (ii) by exploring the organization of flower covariation, considering alternative expectations of modular organization or whole flower integration through conditional dependence analysis (CDA) and integration matrices. The phenotypic selection approach was applied to determine whether floral traits involved in the functioning of the pollination mechanism were affected by natural selection. Floral integration was low, suggesting that flowers are organized in more than just one correlation pleiad; our hypothetical functional correlation matrix was significantly correlated with the empirical matrix, and the CDA revealed three putative modules. Analyses of phenotypic selection showed significant linear and correlational gradients, lending support to expectations of functional interactions between floral traits. Significant correlational selection gradients found involved traits of different floral whorls, providing evidence for the existence of functional integration across developmental domains. © 2014 The Authors. Journal of Evolutionary Biology © 2014 European Society For Evolutionary Biology.

Accurate evaluation and analysis of functional genomics data and methods

PubMed Central

Greene, Casey S.; Troyanskaya, Olga G.

2016-01-01

The development of technology capable of inexpensively performing large-scale measurements of biological systems has generated a wealth of data. Integrative analysis of these data holds the promise of uncovering gene function, regulation, and, in the longer run, understanding complex disease. However, their analysis has proved very challenging, as it is difficult to quickly and effectively assess the relevance and accuracy of these data for individual biological questions. Here, we identify biases that present challenges for the assessment of functional genomics data and methods. We then discuss evaluation methods that, taken together, begin to address these issues. We also argue that the funding of systematic data-driven experiments and of high-quality curation efforts will further improve evaluation metrics so that they more-accurately assess functional genomics data and methods. Such metrics will allow researchers in the field of functional genomics to continue to answer important biological questions in a data-driven manner. PMID:22268703

Complex dielectric properties of anhydrous polycrystalline glucose in the terahertz region

NASA Astrophysics Data System (ADS)

Sun, P.; Liu, W.; Zou, Y.; Jia, Qiong Z.; Li, Jia Y.

2015-03-01

We utilized terahertz time-domain spectroscopy (THz-TDS) to investigate the complex dielectric properties of solid polycrystalline material of anhydrous glucose (D-(+)-glucose with purity >99.9%). THz transmission spectra of samples were measured from 0.2 to 2.2 THz. The samples were prepared into tablets with thicknesses of 0.362, 0.447, 0.504, 0.522 and 0.626 mm, respectively. The imaginary part of the complex dielectric function of polycrystalline glucose showed that there were multiple characteristic absorption peaks at 1.232, 1.445, 1.522, 1.608, 1.811 and 1.987 THz, respectively. Moreover, for a given characteristic absorption peak, the real part of the complex dielectric function showed anomalous dispersion within the full width half maximum (FWHM) of the absorption peak. Both finite difference time-domain (FDTD) numerical simulations and experimental results showed that the complex dielectric function of anhydrous polycrystalline glucose fits well with the Lorentz dielectric mode. The plasma oscillation frequency was below the frequency of the light waves suggesting that the light waves passed through the polycrystalline glucose tablets. Calculations based on density functional theory (DFT) showed that the characteristic absorption peaks of polycrystalline glucose originated mainly from collective intermolecular vibrations such as hydrogen bonds and crystal phonon modes. The THz radiation can excite the vibrational or rotational energy levels of the biological macromolecules. This leads to changes in their spatial configuration or interactions. This study showed that THz-TDS has potential applications in biological and pharmaceutical research and food industry.

Imparting the unique properties of DNA into complex material architectures and functions.

PubMed

Xu, Phyllis F; Noh, Hyunwoo; Lee, Ju Hun; Domaille, Dylan W; Nakatsuka, Matthew A; Goodwin, Andrew P; Cha, Jennifer N

2013-07-01

While the remarkable chemical and biological properties of DNA have been known for decades, these properties have only been imparted into materials with unprecedented function much more recently. The inimitable ability of DNA to form programmable, complex assemblies through stable, specific, and reversible molecular recognition has allowed the creation of new materials through DNA's ability to control a material's architecture and properties. In this review we discuss recent progress in how DNA has brought unmatched function to materials, focusing specifically on new advances in delivery agents, devices, and sensors.

Systematic computation with functional gene-sets among leukemic and hematopoietic stem cells reveals a favorable prognostic signature for acute myeloid leukemia.

PubMed

Yang, Xinan Holly; Li, Meiyi; Wang, Bin; Zhu, Wanqi; Desgardin, Aurelie; Onel, Kenan; de Jong, Jill; Chen, Jianjun; Chen, Luonan; Cunningham, John M

2015-03-24

Genes that regulate stem cell function are suspected to exert adverse effects on prognosis in malignancy. However, diverse cancer stem cell signatures are difficult for physicians to interpret and apply clinically. To connect the transcriptome and stem cell biology, with potential clinical applications, we propose a novel computational "gene-to-function, snapshot-to-dynamics, and biology-to-clinic" framework to uncover core functional gene-sets signatures. This framework incorporates three function-centric gene-set analysis strategies: a meta-analysis of both microarray and RNA-seq data, novel dynamic network mechanism (DNM) identification, and a personalized prognostic indicator analysis. This work uses complex disease acute myeloid leukemia (AML) as a research platform. We introduced an adjustable "soft threshold" to a functional gene-set algorithm and found that two different analysis methods identified distinct gene-set signatures from the same samples. We identified a 30-gene cluster that characterizes leukemic stem cell (LSC)-depleted cells and a 25-gene cluster that characterizes LSC-enriched cells in parallel; both mark favorable-prognosis in AML. Genes within each signature significantly share common biological processes and/or molecular functions (empirical p = 6e-5 and 0.03 respectively). The 25-gene signature reflects the abnormal development of stem cells in AML, such as AURKA over-expression. We subsequently determined that the clinical relevance of both signatures is independent of known clinical risk classifications in 214 patients with cytogenetically normal AML. We successfully validated the prognosis of both signatures in two independent cohorts of 91 and 242 patients respectively (log-rank p < 0.0015 and 0.05; empirical p < 0.015 and 0.08). The proposed algorithms and computational framework will harness systems biology research because they efficiently translate gene-sets (rather than single genes) into biological discoveries about AML and other complex diseases.

Revisiting the Quantum Brain Hypothesis: Toward Quantum (Neuro)biology?

PubMed Central

Jedlicka, Peter

2017-01-01

The nervous system is a non-linear dynamical complex system with many feedback loops. A conventional wisdom is that in the brain the quantum fluctuations are self-averaging and thus functionally negligible. However, this intuition might be misleading in the case of non-linear complex systems. Because of an extreme sensitivity to initial conditions, in complex systems the microscopic fluctuations may be amplified and thereby affect the system’s behavior. In this way quantum dynamics might influence neuronal computations. Accumulating evidence in non-neuronal systems indicates that biological evolution is able to exploit quantum stochasticity. The recent rise of quantum biology as an emerging field at the border between quantum physics and the life sciences suggests that quantum events could play a non-trivial role also in neuronal cells. Direct experimental evidence for this is still missing but future research should address the possibility that quantum events contribute to an extremely high complexity, variability and computational power of neuronal dynamics. PMID:29163041

Revisiting the Quantum Brain Hypothesis: Toward Quantum (Neuro)biology?

PubMed

Jedlicka, Peter

2017-01-01

The nervous system is a non-linear dynamical complex system with many feedback loops. A conventional wisdom is that in the brain the quantum fluctuations are self-averaging and thus functionally negligible. However, this intuition might be misleading in the case of non-linear complex systems. Because of an extreme sensitivity to initial conditions, in complex systems the microscopic fluctuations may be amplified and thereby affect the system's behavior. In this way quantum dynamics might influence neuronal computations. Accumulating evidence in non-neuronal systems indicates that biological evolution is able to exploit quantum stochasticity. The recent rise of quantum biology as an emerging field at the border between quantum physics and the life sciences suggests that quantum events could play a non-trivial role also in neuronal cells. Direct experimental evidence for this is still missing but future research should address the possibility that quantum events contribute to an extremely high complexity, variability and computational power of neuronal dynamics.

AlignNemo: a local network alignment method to integrate homology and topology.

PubMed

Ciriello, Giovanni; Mina, Marco; Guzzi, Pietro H; Cannataro, Mario; Guerra, Concettina

2012-01-01

Local network alignment is an important component of the analysis of protein-protein interaction networks that may lead to the identification of evolutionary related complexes. We present AlignNemo, a new algorithm that, given the networks of two organisms, uncovers subnetworks of proteins that relate in biological function and topology of interactions. The discovered conserved subnetworks have a general topology and need not to correspond to specific interaction patterns, so that they more closely fit the models of functional complexes proposed in the literature. The algorithm is able to handle sparse interaction data with an expansion process that at each step explores the local topology of the networks beyond the proteins directly interacting with the current solution. To assess the performance of AlignNemo, we ran a series of benchmarks using statistical measures as well as biological knowledge. Based on reference datasets of protein complexes, AlignNemo shows better performance than other methods in terms of both precision and recall. We show our solutions to be biologically sound using the concept of semantic similarity applied to Gene Ontology vocabularies. The binaries of AlignNemo and supplementary details about the algorithms and the experiments are available at: sourceforge.net/p/alignnemo.

Self-transcending meditation is good for mental health: why this should be the case.

PubMed

Hankey, Alex; Shetkar, Rashmi

2016-06-01

A simple theory of health has recently been proposed: while poor quality regulation corresponds to poor quality health so that improving regulation should improve health, optimal regulation optimizes function and optimizes health. Examining the term 'optimal regulation' in biological systems leads to a straightforward definition in terms of 'criticality' in complexity biology, a concept that seems to apply universally throughout biology. Criticality maximizes information processing and sensitivity of response to external stimuli, and for these reasons may be held to optimize regulation. In this way a definition of health has been given in terms of regulation, a scientific concept, which ties into detailed properties of complex systems, including brain cortices, and mental health. Models of experience and meditation built on complexity also point to criticality: it represents the condition making self-awareness possible, and is strengthened by meditation practices leading to the state of pure consciousness-the content-free state of mind in deep meditation. From this it follows that healthy function of the brain cortex, its sensitivity,y and consistency of response to external challenges should improve by practicing techniques leading to content-free awareness-transcending the original focus introduced during practice. Evidence for this is reviewed.

Isothiocyanate-Functionalized Bifunctional Chelates and fac-[M(I)(CO)3](+) (M = Re, (99m)Tc) Complexes for Targeting uPAR in Prostate Cancer.

PubMed

Kasten, Benjamin B; Ma, Xiaowei; Cheng, Kai; Bu, Lihong; Slocumb, Winston S; Hayes, Thomas R; Trabue, Steven; Cheng, Zhen; Benny, Paul D

2016-01-20

Developing new strategies to rapidly incorporate the fac-[M(I)(CO)3](+) (M = Re, (99m)Tc) core into biological targeting vectors in radiopharmaceuticals continues to expand as molecules become more complex and as efforts to minimize nonspecific binding increase. This work examines a novel isothiocyanate-functionalized bifunctional chelate based on 2,2'-dipicolylamine (DPA) specifically designed for complexing the fac-[M(I)(CO)3](+) core. Two strategies (postlabeling and prelabeling) were explored using the isothiocyanate-functionalized DPA to determine the effectiveness of assembly on the overall yield and purity of the complex with amine containing biomolecules. A model amino acid (lysine) examined (1) amine conjugation of isothiocyanate-functionalized DPA followed by complexation with fac-[M(I)(CO)3](+) (postlabeling) and (2) complexation of fac-[M(I)(CO)3](+) with isothiocyanate-functionalized DPA followed by amine conjugation (prelabeling). Conducted with stable Re and radioactive (99m)Tc analogs, both strategies formed the product in good to excellent yields under macroscopic and radiotracer concentrations. A synthetic peptide (AE105) which targets an emerging biomarker in CaP prognosis, urokinase-type plasminogen activator receptor (uPAR), was also explored using the isothiocyanate-functionalized DPA strategy. In vitro PC-3 (uPAR+) cell uptake assays with the (99m)Tc-labeled peptide (8a) showed 4.2 ± 0.5% uptake at 4 h. In a murine model bearing PC-3 tumor xenografts, in vivo biodistribution of 8a led to favorable tumor uptake (3.7 ± 0.7% ID/g) at 4 h p.i. with relatively low accumulation (<2% ID/g) in normal organs not associated with normal peptide excretion. These results illustrate the promise of the isothiocyanate-functionalized approach for labeling amine containing biological targeting vectors with fac-[M(I)(CO)3](+).

"Life-bearing molecules" versus "life-embodying systems": Two contrasting views on the what-is-life (WIL) problem persisting from the early days of molecular biology to the post-genomic cell- and organism-level biology.

PubMed

Sato, Naoki

2018-05-01

"What is life?" is an ultimate biological quest for the principle that makes organisms alive. This 'WIL problem' is not, however, a simple one that we have a straightforward strategy to attack. From the beginning, molecular biology tried to identify molecules that bear the essence of life: the double helical DNA represented replication, and enzymes were micro-actuators of biological activities. A dominating idea behind these mainstream biological studies relies on the identification of life-bearing molecules, which themselves are models of life. Another, prevalent idea emphasizes that life resides in the whole system of an organism, but not in some particular molecules. The behavior of a complex system may be considered to embody the essence of life. The thermodynamic view of life system in the early 20th century was remodeled as physics of complex systems and systems biology. The two views contrast with each other, but they are no longer heritage of the historical dualism in biology, such as mechanism/materialism versus vitalism, or reductionism versus holism. These two views are both materialistic and mechanistic, and act as driving forces of modern biology. In reality, molecules function in a context of systems, whereas systems presuppose functional molecules. A key notion to reconcile this conflict is that subjects of biological studies are given before we start to study them. Cell- or organism-level biology is destined to the dialectic of molecules and systems, but this antagonism can be resolved by dynamic thinking involving biological evolution. Copyright © 2018 Elsevier B.V. All rights reserved.

Hollow silica microspheres for buoyancy-assisted separation of infectious pathogens from stool.

PubMed

Weigum, Shannon E; Xiang, Lichen; Osta, Erica; Li, Linying; López, Gabriel P

2016-09-30

Separation of cells and microorganisms from complex biological mixtures is a critical first step in many analytical applications ranging from clinical diagnostics to environmental monitoring for food and waterborne contaminants. Yet, existing techniques for cell separation are plagued by high reagent and/or instrumentation costs that limit their use in many remote or resource-poor settings, such as field clinics or developing countries. We developed an innovative approach to isolate infectious pathogens from biological fluids using buoyant hollow silica microspheres that function as "molecular buoys" for affinity-based target capture and separation by floatation. In this process, antibody functionalized glass microspheres are mixed with a complex biological sample, such as stool. When mixing is stopped, the target-bound, low-density microspheres float to the air/liquid surface, which simultaneously isolates and concentrates the target analytes from the sample matrix. The microspheres are highly tunable in terms of size, density, and surface functionality for targeting diverse analytes with separation times of ≤2min in viscous solutions. We have applied the molecular buoy technique for isolation of a protozoan parasite that causes diarrheal illness, Cryptosporidium, directly from stool with separation efficiencies over 90% and low non-specific binding. This low-cost method for phenotypic cell/pathogen separation from complex mixtures is expected to have widespread use in clinical diagnostics as well as basic research. Copyright © 2016 Elsevier B.V. All rights reserved.

Search for organising principles: understanding in systems biology.

PubMed

Mesarovic, M D; Sreenath, S N; Keene, J D

2004-06-01

Due in large measure to the explosive progress in molecular biology, biology has become arguably the most exciting scientific field. The first half of the 21st century is sometimes referred to as the 'era of biology', analogous to the first half of the 20th century, which was considered to be the 'era of physics'. Yet, biology is facing a crisis--or is it an opportunity--reminiscent of the state of biology in pre-double-helix time. The principal challenge facing systems biology is complexity. According to Hood, 'Systems biology defines and analyses the interrelationships of all of the elements in a functioning system in order to understand how the system works.' With 30000+ genes in the human genome the study of all relationships simultaneously becomes a formidably complex problem. Hanahan and Weinberg raised the question as to whether progress will consist of 'adding further layers of complexity to a scientific literature that is already complex almost beyond measure' or whether the progress will lead to a 'science with a conceptual structure and logical coherence that rivals that of chemistry or physics.' At the core of the challenge is the need for a new approach, a shift from reductionism to a holistic perspective. However, more than just a pronouncement of a new approach is needed. We suggest that what is needed is to provide a conceptual framework for systems biology research. We propose that the concept of a complex system, i.e. a system of systems as defined in mathematical general systems theory (MGST), is central to provide such a framework. We further argue that for a deeper understanding in systems biology investigations should go beyond building numerical mathematical or computer models--important as they are. Biological phenomena cannot be predicted with the level of numerical precision as in classical physics. Explanations in terms of how the categories of systems are organised to function in ever changing conditions are more revealing. Non-numerical mathematical tools are appropriate for the task. Such a categorical perspective led us to propose that the core of understanding in systems biology depends on the search for organising principles rather than solely on construction of predictive descriptions (i.e. models) that exactly outline the evolution of systems in space and time. The search for organising principles requires an identification/discovery of new concepts and hypotheses. Some of them, such as coordination motifs for transcriptional regulatory networks and bounded autonomy of levccels in a hierarchy, are outlined in this article. Experimental designs are outlined to help verify the applicability of the interaction balance principle of coordination to transcriptional and posttranscriptional networks.

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.

X-ray absorption spectroscopy to watch catalysis by metalloenzymes: status and perspectives discussed for the water-splitting manganese complex of photosynthesis.

PubMed

Dau, Holger; Haumann, Michael

2003-01-01

Understanding structure-function relations is one of the main interests in the molecular biosciences. X-ray absorption spectroscopy of biological samples (BioXAS) has gained the status of a useful tool for characterization of the structure of protein-bound metal centers with respect to the electronic structure (oxidation states, orbital occupancies) and atomic structure (arrangement of ligand atoms). Owing to progress in the performance characteristics of synchrotron radiation sources and of experimental stations dedicated to the study of (ultra-dilute) biological samples, it is now possible to carry out new types of BioXAS experiments, which have been impracticable in the past. Of particular interest are approaches to follow biological catalysis at metal sites by characterization of functionally relevant structural changes. In this Article, the first steps towards the use of BioXAS to 'watch' biological catalysis are reviewed for the water-splitting reactions occurring at the manganese complex of photosynthesis. The following aspects are considered: the role of BioXAS in life sciences; methodological aspects of BioXAS; catalysis at the Mn complex of photosynthesis; combination of EXAFS and crystallographic information; the freeze-quench technique to capture semi-stable states; time-resolved BioXAS using a freeze-quench approach; room-temperature experiments and 'real-time' BioXAS; tasks and perspectives.

Structure Prediction of Protein Complexes

NASA Astrophysics Data System (ADS)

Pierce, Brian; Weng, Zhiping

Protein-protein interactions are critical for biological function. They directly and indirectly influence the biological systems of which they are a part. Antibodies bind with antigens to detect and stop viruses and other infectious agents. Cell signaling is performed in many cases through the interactions between proteins. Many diseases involve protein-protein interactions on some level, including cancer and prion diseases.

Tangible Models and Haptic Representations Aid Learning of Molecular Biology Concepts

ERIC Educational Resources Information Center

Johannes, Kristen; Powers, Jacklyn; Couper, Lisa; Silberglitt, Matt; Davenport, Jodi

2016-01-01

Can novel 3D models help students develop a deeper understanding of core concepts in molecular biology? We adapted 3D molecular models, developed by scientists, for use in high school science classrooms. The models accurately represent the structural and functional properties of complex DNA and Virus molecules, and provide visual and haptic…

Active Interaction Mapping as a tool to elucidate hierarchical functions of biological processes.

PubMed

Farré, Jean-Claude; Kramer, Michael; Ideker, Trey; Subramani, Suresh

2017-07-03

Increasingly, various 'omics data are contributing significantly to our understanding of novel biological processes, but it has not been possible to iteratively elucidate hierarchical functions in complex phenomena. We describe a general systems biology approach called Active Interaction Mapping (AI-MAP), which elucidates the hierarchy of functions for any biological process. Existing and new 'omics data sets can be iteratively added to create and improve hierarchical models which enhance our understanding of particular biological processes. The best datatypes to further improve an AI-MAP model are predicted computationally. We applied this approach to our understanding of general and selective autophagy, which are conserved in most eukaryotes, setting the stage for the broader application to other cellular processes of interest. In the particular application to autophagy-related processes, we uncovered and validated new autophagy and autophagy-related processes, expanded known autophagy processes with new components, integrated known non-autophagic processes with autophagy and predict other unexplored connections.

Robust Design of Biological Circuits: Evolutionary Systems Biology Approach

PubMed Central

Chen, Bor-Sen; Hsu, Chih-Yuan; Liou, Jing-Jia

2011-01-01

Artificial gene circuits have been proposed to be embedded into microbial cells that function as switches, timers, oscillators, and the Boolean logic gates. Building more complex systems from these basic gene circuit components is one key advance for biologic circuit design and synthetic biology. However, the behavior of bioengineered gene circuits remains unstable and uncertain. In this study, a nonlinear stochastic system is proposed to model the biological systems with intrinsic parameter fluctuations and environmental molecular noise from the cellular context in the host cell. Based on evolutionary systems biology algorithm, the design parameters of target gene circuits can evolve to specific values in order to robustly track a desired biologic function in spite of intrinsic and environmental noise. The fitness function is selected to be inversely proportional to the tracking error so that the evolutionary biological circuit can achieve the optimal tracking mimicking the evolutionary process of a gene circuit. Finally, several design examples are given in silico with the Monte Carlo simulation to illustrate the design procedure and to confirm the robust performance of the proposed design method. The result shows that the designed gene circuits can robustly track desired behaviors with minimal errors even with nontrivial intrinsic and external noise. PMID:22187523

Robust design of biological circuits: evolutionary systems biology approach.

PubMed

Chen, Bor-Sen; Hsu, Chih-Yuan; Liou, Jing-Jia

2011-01-01

Artificial gene circuits have been proposed to be embedded into microbial cells that function as switches, timers, oscillators, and the Boolean logic gates. Building more complex systems from these basic gene circuit components is one key advance for biologic circuit design and synthetic biology. However, the behavior of bioengineered gene circuits remains unstable and uncertain. In this study, a nonlinear stochastic system is proposed to model the biological systems with intrinsic parameter fluctuations and environmental molecular noise from the cellular context in the host cell. Based on evolutionary systems biology algorithm, the design parameters of target gene circuits can evolve to specific values in order to robustly track a desired biologic function in spite of intrinsic and environmental noise. The fitness function is selected to be inversely proportional to the tracking error so that the evolutionary biological circuit can achieve the optimal tracking mimicking the evolutionary process of a gene circuit. Finally, several design examples are given in silico with the Monte Carlo simulation to illustrate the design procedure and to confirm the robust performance of the proposed design method. The result shows that the designed gene circuits can robustly track desired behaviors with minimal errors even with nontrivial intrinsic and external noise.

Dancing Protein Clouds: The Strange Biology and Chaotic Physics of Intrinsically Disordered Proteins.

PubMed

Uversky, Vladimir N

2016-03-25

Biologically active but floppy proteins represent a new reality of modern protein science. These intrinsically disordered proteins (IDPs) and hybrid proteins containing ordered and intrinsically disordered protein regions (IDPRs) constitute a noticeable part of any given proteome. Functionally, they complement ordered proteins, and their conformational flexibility and structural plasticity allow them to perform impossible tricks and be engaged in biological activities that are inaccessible to well folded proteins with their unique structures. The major goals of this minireview are to show that, despite their simplified amino acid sequences, IDPs/IDPRs are complex entities often resembling chaotic systems, are structurally and functionally heterogeneous, and can be considered an important part of the structure-function continuum. Furthermore, IDPs/IDPRs are everywhere, and are ubiquitously engaged in various interactions characterized by a wide spectrum of binding scenarios and an even wider spectrum of structural and functional outputs. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.

Fiber Diffraction of the Prion-Forming Domain HET-s(218-289) Shows Dehydration-Induced Deformation of a Complex Amyloid Structure

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

Wan, William; Stubbs, Gerald

2014-05-01

Amyloids are filamentous protein aggregates that can be formed by many different proteins and are associated with both disease and biological functions. The pathogenicities or biological functions of amyloids are determined by their particular molecular structures, making accurate structural models a requirement for understanding their biological effects. One potential factor that can affect amyloid structures is hydration. Previous studies of simple stacked β-sheet amyloids have suggested that dehydration does not impact structure, but other studies indicated dehydration-related structural changes of a putative water-filled nanotube. Our results show that dehydration significantly affects the molecular structure of the fungal prion-forming domain HET-s(218–289),more » which forms a β-solenoid with no internal solvent-accessible regions. The dehydration-related structural deformation of HET-s(218–289) indicates that water can play a significant role in complex amyloid structures, even when no obvious water-accessible cavities are present.« less

Application of Nuclear Magnetic Resonance and Hybrid Methods to Structure Determination of Complex Systems.

PubMed

Prischi, Filippo; Pastore, Annalisa

2016-01-01

The current main challenge of Structural Biology is to undertake the structure determination of increasingly complex systems in the attempt to better understand their biological function. As systems become more challenging, however, there is an increasing demand for the parallel use of more than one independent technique to allow pushing the frontiers of structure determination and, at the same time, obtaining independent structural validation. The combination of different Structural Biology methods has been named hybrid approaches. The aim of this review is to critically discuss the most recent examples and new developments that have allowed structure determination or experimentally-based modelling of various molecular complexes selecting them among those that combine the use of nuclear magnetic resonance and small angle scattering techniques. We provide a selective but focused account of some of the most exciting recent approaches and discuss their possible further developments.

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

Governability Framework for the Evaluation and Implementation of Complex Public Health Functions

ERIC Educational Resources Information Center

Varghese, Joe; Kutty, V. Raman

2012-01-01

Background: The dominant theoretical basis of our public health practice originates from a positivist or reductionist paradigm. It fails to take into account the complexity emerging out of public health's multiple influences originating from biological and social worlds. A deeper understanding of the interaction of elements that characterize the…

Categorizing Biases in High-Confidence High-Throughput Protein-Protein Interaction Data Sets*

PubMed Central

Yu, Xueping; Ivanic, Joseph; Memišević, Vesna; Wallqvist, Anders; Reifman, Jaques

2011-01-01

We characterized and evaluated the functional attributes of three yeast high-confidence protein-protein interaction data sets derived from affinity purification/mass spectrometry, protein-fragment complementation assay, and yeast two-hybrid experiments. The interacting proteins retrieved from these data sets formed distinct, partially overlapping sets with different protein-protein interaction characteristics. These differences were primarily a function of the deployed experimental technologies used to recover these interactions. This affected the total coverage of interactions and was especially evident in the recovery of interactions among different functional classes of proteins. We found that the interaction data obtained by the yeast two-hybrid method was the least biased toward any particular functional characterization. In contrast, interacting proteins in the affinity purification/mass spectrometry and protein-fragment complementation assay data sets were over- and under-represented among distinct and different functional categories. We delineated how these differences affected protein complex organization in the network of interactions, in particular for strongly interacting complexes (e.g. RNA and protein synthesis) versus weak and transient interacting complexes (e.g. protein transport). We quantified methodological differences in detecting protein interactions from larger protein complexes, in the correlation of protein abundance among interacting proteins, and in their connectivity of essential proteins. In the latter case, we showed that minimizing inherent methodology biases removed many of the ambiguous conclusions about protein essentiality and protein connectivity. We used these findings to rationalize how biological insights obtained by analyzing data sets originating from different sources sometimes do not agree or may even contradict each other. An important corollary of this work was that discrepancies in biological insights did not necessarily imply that one detection methodology was better or worse, but rather that, to a large extent, the insights reflected the methodological biases themselves. Consequently, interpreting the protein interaction data within their experimental or cellular context provided the best avenue for overcoming biases and inferring biological knowledge. PMID:21876202

Genomewide effects of peroxisome proliferator-activated receptor gamma in macrophages and dendritic cells--revealing complexity through systems biology.

PubMed

Cuaranta-Monroy, Ixchelt; Kiss, Mate; Simandi, Zoltan; Nagy, Laszlo

2015-09-01

Systems biology approaches have become indispensable tools in biomedical and basic research. These data integrating bioinformatic methods gained prominence after high-throughput technologies became available to investigate complex cellular processes, such as transcriptional regulation and protein-protein interactions, on a scale that had not been studied before. Immunology is one of the medical fields that systems biology impacted profoundly due to the plasticity of cell types involved and the accessibility of a wide range of experimental models. In this review, we summarize the most important recent genomewide studies exploring the function of peroxisome proliferator-activated receptor γ in macrophages and dendritic cells. PPARγ ChIP-seq experiments were performed in adipocytes derived from embryonic stem cells to complement the existing data sets and to provide comparators to macrophage data. Finally, lists of regulated genes generated from such experiments were analysed with bioinformatics and system biology approaches. We show that genomewide studies utilizing high-throughput data acquisition methods made it possible to gain deeper insights into the role of PPARγ in these immune cell types. We also demonstrate that analysis and visualization of data using network-based approaches can be used to identify novel genes and functions regulated by the receptor. The example of PPARγ in macrophages and dendritic cells highlights the crucial importance of systems biology approaches in establishing novel cellular functions for long-known signaling pathways. © 2015 Stichting European Society for Clinical Investigation Journal Foundation.

The Information Content of Discrete Functions and Their Application in Genetic Data Analysis

DOE PAGES

Sakhanenko, Nikita A.; Kunert-Graf, James; Galas, David J.

2017-10-13

The complex of central problems in data analysis consists of three components: (1) detecting the dependence of variables using quantitative measures, (2) defining the significance of these dependence measures, and (3) inferring the functional relationships among dependent variables. We have argued previously that an information theory approach allows separation of the detection problem from the inference of functional form problem. We approach here the third component of inferring functional forms based on information encoded in the functions. Here, we present here a direct method for classifying the functional forms of discrete functions of three variables represented in data sets. Discretemore » variables are frequently encountered in data analysis, both as the result of inherently categorical variables and from the binning of continuous numerical variables into discrete alphabets of values. The fundamental question of how much information is contained in a given function is answered for these discrete functions, and their surprisingly complex relationships are illustrated. The all-important effect of noise on the inference of function classes is found to be highly heterogeneous and reveals some unexpected patterns. We apply this classification approach to an important area of biological data analysis—that of inference of genetic interactions. Genetic analysis provides a rich source of real and complex biological data analysis problems, and our general methods provide an analytical basis and tools for characterizing genetic problems and for analyzing genetic data. Finally, we illustrate the functional description and the classes of a number of common genetic interaction modes and also show how different modes vary widely in their sensitivity to noise.« less

The Information Content of Discrete Functions and Their Application in Genetic Data Analysis

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

Sakhanenko, Nikita A.; Kunert-Graf, James; Galas, David J.

The complex of central problems in data analysis consists of three components: (1) detecting the dependence of variables using quantitative measures, (2) defining the significance of these dependence measures, and (3) inferring the functional relationships among dependent variables. We have argued previously that an information theory approach allows separation of the detection problem from the inference of functional form problem. We approach here the third component of inferring functional forms based on information encoded in the functions. Here, we present here a direct method for classifying the functional forms of discrete functions of three variables represented in data sets. Discretemore » variables are frequently encountered in data analysis, both as the result of inherently categorical variables and from the binning of continuous numerical variables into discrete alphabets of values. The fundamental question of how much information is contained in a given function is answered for these discrete functions, and their surprisingly complex relationships are illustrated. The all-important effect of noise on the inference of function classes is found to be highly heterogeneous and reveals some unexpected patterns. We apply this classification approach to an important area of biological data analysis—that of inference of genetic interactions. Genetic analysis provides a rich source of real and complex biological data analysis problems, and our general methods provide an analytical basis and tools for characterizing genetic problems and for analyzing genetic data. Finally, we illustrate the functional description and the classes of a number of common genetic interaction modes and also show how different modes vary widely in their sensitivity to noise.« less

The Information Content of Discrete Functions and Their Application in Genetic Data Analysis.

PubMed

Sakhanenko, Nikita A; Kunert-Graf, James; Galas, David J

2017-12-01

The complex of central problems in data analysis consists of three components: (1) detecting the dependence of variables using quantitative measures, (2) defining the significance of these dependence measures, and (3) inferring the functional relationships among dependent variables. We have argued previously that an information theory approach allows separation of the detection problem from the inference of functional form problem. We approach here the third component of inferring functional forms based on information encoded in the functions. We present here a direct method for classifying the functional forms of discrete functions of three variables represented in data sets. Discrete variables are frequently encountered in data analysis, both as the result of inherently categorical variables and from the binning of continuous numerical variables into discrete alphabets of values. The fundamental question of how much information is contained in a given function is answered for these discrete functions, and their surprisingly complex relationships are illustrated. The all-important effect of noise on the inference of function classes is found to be highly heterogeneous and reveals some unexpected patterns. We apply this classification approach to an important area of biological data analysis-that of inference of genetic interactions. Genetic analysis provides a rich source of real and complex biological data analysis problems, and our general methods provide an analytical basis and tools for characterizing genetic problems and for analyzing genetic data. We illustrate the functional description and the classes of a number of common genetic interaction modes and also show how different modes vary widely in their sensitivity to noise.

Optimal network alignment with graphlet degree vectors.

PubMed

Milenković, Tijana; Ng, Weng Leong; Hayes, Wayne; Przulj, Natasa

2010-06-30

Important biological information is encoded in the topology of biological networks. Comparative analyses of biological networks are proving to be valuable, as they can lead to transfer of knowledge between species and give deeper insights into biological function, disease, and evolution. We introduce a new method that uses the Hungarian algorithm to produce optimal global alignment between two networks using any cost function. We design a cost function based solely on network topology and use it in our network alignment. Our method can be applied to any two networks, not just biological ones, since it is based only on network topology. We use our new method to align protein-protein interaction networks of two eukaryotic species and demonstrate that our alignment exposes large and topologically complex regions of network similarity. At the same time, our alignment is biologically valid, since many of the aligned protein pairs perform the same biological function. From the alignment, we predict function of yet unannotated proteins, many of which we validate in the literature. Also, we apply our method to find topological similarities between metabolic networks of different species and build phylogenetic trees based on our network alignment score. The phylogenetic trees obtained in this way bear a striking resemblance to the ones obtained by sequence alignments. Our method detects topologically similar regions in large networks that are statistically significant. It does this independent of protein sequence or any other information external to network topology.

Signalling networks and dynamics of allosteric transitions in bacterial chaperonin GroEL: implications for iterative annealing of misfolded proteins.

PubMed

Thirumalai, D; Hyeon, Changbong

2018-06-19

Signal transmission at the molecular level in many biological complexes occurs through allosteric transitions. Allostery describes the responses of a complex to binding of ligands at sites that are spatially well separated from the binding region. We describe the structural perturbation method, based on phonon propagation in solids, which can be used to determine the signal-transmitting allostery wiring diagram (AWD) in large but finite-sized biological complexes. Application to the bacterial chaperonin GroEL-GroES complex shows that the AWD determined from structures also drives the allosteric transitions dynamically. From both a structural and dynamical perspective these transitions are largely determined by formation and rupture of salt-bridges. The molecular description of allostery in GroEL provides insights into its function, which is quantitatively described by the iterative annealing mechanism. Remarkably, in this complex molecular machine, a deep connection is established between the structures, reaction cycle during which GroEL undergoes a sequence of allosteric transitions, and function, in a self-consistent manner.This article is part of a discussion meeting issue 'Allostery and molecular machines'. © 2018 The Author(s).

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

MultitaskProtDB: a database of multitasking proteins.

PubMed

Hernández, Sergio; Ferragut, Gabriela; Amela, Isaac; Perez-Pons, JosepAntoni; Piñol, Jaume; Mozo-Villarias, Angel; Cedano, Juan; Querol, Enrique

2014-01-01

We have compiled MultitaskProtDB, available online at http://wallace.uab.es/multitask, to provide a repository where the many multitasking proteins found in the literature can be stored. Multitasking or moonlighting is the capability of some proteins to execute two or more biological functions. Usually, multitasking proteins are experimentally revealed by serendipity. This ability of proteins to perform multitasking functions helps us to understand one of the ways used by cells to perform many complex functions with a limited number of genes. Even so, the study of this phenomenon is complex because, among other things, there is no database of moonlighting proteins. The existence of such a tool facilitates the collection and dissemination of these important data. This work reports the database, MultitaskProtDB, which is designed as a friendly user web page containing >288 multitasking proteins with their NCBI and UniProt accession numbers, canonical and additional biological functions, monomeric/oligomeric states, PDB codes when available and bibliographic references. This database also serves to gain insight into some characteristics of multitasking proteins such as frequencies of the different pairs of functions, phylogenetic conservation and so forth.

Exploration of the Energy Landscape of Acetylcholinesterase by Molecular Dynamics Simulation.

NASA Astrophysics Data System (ADS)

McCammon, J. Andrew

2002-03-01

Proteins have rough energy landscapes. Often more states than just the ground state are occupied and have biological functions. It is essential to study these conformational substates and the dynamical transitions among them. Acetylcholinesterase (AChE) is an important enzyme that has biological functions including the termination of synaptic transmission signals. X-ray structures show that it has an active site that is accessible only via a long and narrow channel from its surface. Therefore the fact that acetylcholine and larger ligands can reach the active site is believed to reflect the protein's structural fluctuation. We carried out long molecular dynamics simulations to investigate the dynamics of AChE and its relation to biological function, and compared our results with experiments. The results reveal several "doors" that open intermittantly between the active site and the surface. Instead of having simple exponential decay correlation functions, the time series of these channels reveal complex, fractal gating between conformations. We also compared the AChE dynamics data with those from an AchE-fasciculin complex. (Fasciculin is a small protein that is a natural inhibitor of AChE.) The results show remarkable effects of the protein-protein interaction, including allosteric and dynamical inhibition by fasciculin besides direct steric blocking. More information and images can be found at http://mccammon.ucsd.edu

A biomimetic colorimetric logic gate system based on multi-functional peptide-mediated gold nanoparticle assembly

NASA Astrophysics Data System (ADS)

Li, Yong; Li, Wang; He, Kai-Yu; Li, Pei; Huang, Yan; Nie, Zhou; Yao, Shou-Zhuo

2016-04-01

In natural biological systems, proteins exploit various functional peptide motifs to exert target response and activity switch, providing a functional and logic basis for complex cellular activities. Building biomimetic peptide-based bio-logic systems is highly intriguing but remains relatively unexplored due to limited logic recognition elements and complex signal outputs. In this proof-of-principle work, we attempted to address these problems by utilizing multi-functional peptide probes and the peptide-mediated nanoparticle assembly system. Here, the rationally designed peptide probes function as the dual-target responsive element specifically responsive to metal ions and enzymes as well as the mediator regulating the assembly of gold nanoparticles (AuNPs). Taking advantage of Zn2+ ions and chymotrypsin as the model inputs of metal ions and enzymes, respectively, we constructed the peptide logic system computed by the multi-functional peptide probes and outputted by the readable colour change of AuNPs. In this way, the representative binary basic logic gates (AND, OR, INHIBIT, NAND, IMPLICATION) have been achieved by delicately coding the peptide sequence, demonstrating the versatility of our logic system. Additionally, we demonstrated that the three-input combinational logic gate (INHIBIT-OR) could also be successfully integrated and applied as a multi-tasking biosensor for colorimetric detection of dual targets. This nanoparticle-based peptide logic system presents a valid strategy to illustrate peptide information processing and provides a practical platform for executing peptide computing or peptide-related multiplexing sensing, implying that the controllable nanomaterial assembly is a promising and potent methodology for the advancement of biomimetic bio-logic computation.In natural biological systems, proteins exploit various functional peptide motifs to exert target response and activity switch, providing a functional and logic basis for complex cellular activities. Building biomimetic peptide-based bio-logic systems is highly intriguing but remains relatively unexplored due to limited logic recognition elements and complex signal outputs. In this proof-of-principle work, we attempted to address these problems by utilizing multi-functional peptide probes and the peptide-mediated nanoparticle assembly system. Here, the rationally designed peptide probes function as the dual-target responsive element specifically responsive to metal ions and enzymes as well as the mediator regulating the assembly of gold nanoparticles (AuNPs). Taking advantage of Zn2+ ions and chymotrypsin as the model inputs of metal ions and enzymes, respectively, we constructed the peptide logic system computed by the multi-functional peptide probes and outputted by the readable colour change of AuNPs. In this way, the representative binary basic logic gates (AND, OR, INHIBIT, NAND, IMPLICATION) have been achieved by delicately coding the peptide sequence, demonstrating the versatility of our logic system. Additionally, we demonstrated that the three-input combinational logic gate (INHIBIT-OR) could also be successfully integrated and applied as a multi-tasking biosensor for colorimetric detection of dual targets. This nanoparticle-based peptide logic system presents a valid strategy to illustrate peptide information processing and provides a practical platform for executing peptide computing or peptide-related multiplexing sensing, implying that the controllable nanomaterial assembly is a promising and potent methodology for the advancement of biomimetic bio-logic computation. Electronic supplementary information (ESI) available: Additional figures (Tables S1-S3 and Fig. S1-S6). See DOI: 10.1039/c6nr01072e

Nature versus design: synthetic biology or how to build a biological non-machine.

PubMed

Porcar, M; Peretó, J

2016-04-18

The engineering ideal of synthetic biology presupposes that organisms are composed of standard, interchangeable parts with a predictive behaviour. In one word, organisms are literally recognized as machines. Yet living objects are the result of evolutionary processes without any purposiveness, not of a design by external agents. Biological components show massive overlapping and functional degeneracy, standard-free complexity, intrinsic variation and context dependent performances. However, although organisms are not full-fledged machines, synthetic biologists may still be eager for machine-like behaviours from artificially modified biosystems.

The genotype-phenotype map of an evolving digital organism.

PubMed

Fortuna, Miguel A; Zaman, Luis; Ofria, Charles; Wagner, Andreas

2017-02-01

To understand how evolving systems bring forth novel and useful phenotypes, it is essential to understand the relationship between genotypic and phenotypic change. Artificial evolving systems can help us understand whether the genotype-phenotype maps of natural evolving systems are highly unusual, and it may help create evolvable artificial systems. Here we characterize the genotype-phenotype map of digital organisms in Avida, a platform for digital evolution. We consider digital organisms from a vast space of 10141 genotypes (instruction sequences), which can form 512 different phenotypes. These phenotypes are distinguished by different Boolean logic functions they can compute, as well as by the complexity of these functions. We observe several properties with parallels in natural systems, such as connected genotype networks and asymmetric phenotypic transitions. The likely common cause is robustness to genotypic change. We describe an intriguing tension between phenotypic complexity and evolvability that may have implications for biological evolution. On the one hand, genotypic change is more likely to yield novel phenotypes in more complex organisms. On the other hand, the total number of novel phenotypes reachable through genotypic change is highest for organisms with simple phenotypes. Artificial evolving systems can help us study aspects of biological evolvability that are not accessible in vastly more complex natural systems. They can also help identify properties, such as robustness, that are required for both human-designed artificial systems and synthetic biological systems to be evolvable.

The genotype-phenotype map of an evolving digital organism

PubMed Central

Zaman, Luis; Wagner, Andreas

2017-01-01

To understand how evolving systems bring forth novel and useful phenotypes, it is essential to understand the relationship between genotypic and phenotypic change. Artificial evolving systems can help us understand whether the genotype-phenotype maps of natural evolving systems are highly unusual, and it may help create evolvable artificial systems. Here we characterize the genotype-phenotype map of digital organisms in Avida, a platform for digital evolution. We consider digital organisms from a vast space of 10141 genotypes (instruction sequences), which can form 512 different phenotypes. These phenotypes are distinguished by different Boolean logic functions they can compute, as well as by the complexity of these functions. We observe several properties with parallels in natural systems, such as connected genotype networks and asymmetric phenotypic transitions. The likely common cause is robustness to genotypic change. We describe an intriguing tension between phenotypic complexity and evolvability that may have implications for biological evolution. On the one hand, genotypic change is more likely to yield novel phenotypes in more complex organisms. On the other hand, the total number of novel phenotypes reachable through genotypic change is highest for organisms with simple phenotypes. Artificial evolving systems can help us study aspects of biological evolvability that are not accessible in vastly more complex natural systems. They can also help identify properties, such as robustness, that are required for both human-designed artificial systems and synthetic biological systems to be evolvable. PMID:28241039

Lanthanide tris(β-diketonates) as useful probes for chirality determination of biological amino alcohols in vibrational circular dichroism: ligand to ligand chirality transfer in lanthanide coordination sphere.

PubMed

Miyake, Hiroyuki; Terada, Keiko; Tsukube, Hiroshi

2014-06-01

A series of lanthanide tris(β-diketonates) functioned as useful chirality probes in the vibrational circular dichroism (VCD) characterization of biological amino alcohols. Various chiral amino alcohols induced intense VCD signals upon ternary complexation with racemic lanthanide tris(β-diketonates). The VCD signals observed around 1500 cm(-1) (β-diketonate IR absorption region) correlated well with the stereochemistry and enantiomeric purity of the targeted amino alcohol, while the corresponding monoalcohol, monoamine, and diol substrates induced very weak VCD signals. The high-coordination number and dynamic property of the lanthanide complex offer an effective chirality VCD probing of biological substrates. © 2014 Wiley Periodicals, Inc.

Biological and Clinical Aspects of Lanthanide Coordination Compounds

PubMed Central

Misra, Sudhindra N.; M., Indira Devi; Shukla, Ram S.

2004-01-01

The coordinating chemistry of lanthanides, relevant to the biological, biochemical and medical aspects, makes a significant contribution to understanding the basis of application of lanthanides, particularly in biological and medical systems. The importance of the applications of lanthanides, as an excellent diagnostic and prognostic probe in clinical diagnostics, and an anticancer material, is remarkably increasing. Lanthanide complexes based X-ray contrast imaging and lanthanide chelates based contrast enhancing agents for magnetic resonance imaging (MRI) are being excessively used in radiological analysis in our body systems. The most important property of the chelating agents, in lanthanide chelate complex, is its ability to alter the behaviour of lanthanide ion with which it binds in biological systems, and the chelation markedly modifies the biodistribution and excretion profile of the lanthanide ions. The chelating agents, especially aminopoly carboxylic acids, being hydrophilic, increase the proportion of their complex excreted from complexed lanthanide ion form biological systems. Lanthanide polyamino carboxylate-chelate complexes are used as contrast enhancing agents for Magnetic Resonance Imaging. Conjugation of antibodies and other tissue specific molecules to lanthanide chelates has led to a new type of specific MRI contrast agents and their conjugated MRI contrast agents with improved relaxivity, functioning in the body similar to drugs. Many specific features of contrast agent assisted MRI make it particularly effective for musculoskeletal and cerebrospinal imaging. Lanthanide-chelate contrast agents are effectively used in clinical diagnostic investigations involving cerebrospinal diseases and in evaluation of central nervous system. Chelated lanthanide complexes shift reagent aided 23Na NMR spectroscopic analysis is used in cellular, tissue and whole organ systems. PMID:18365075

Molecular architecture and function of the SEA complex, a modulator of the TORC1 pathway.

PubMed

Algret, Romain; Fernandez-Martinez, Javier; Shi, Yi; Kim, Seung Joong; Pellarin, Riccardo; Cimermancic, Peter; Cochet, Emilie; Sali, Andrej; Chait, Brian T; Rout, Michael P; Dokudovskaya, Svetlana

2014-11-01

The TORC1 signaling pathway plays a major role in the control of cell growth and response to stress. Here we demonstrate that the SEA complex physically interacts with TORC1 and is an important regulator of its activity. During nitrogen starvation, deletions of SEA complex components lead to Tor1 kinase delocalization, defects in autophagy, and vacuolar fragmentation. TORC1 inactivation, via nitrogen deprivation or rapamycin treatment, changes cellular levels of SEA complex members. We used affinity purification and chemical cross-linking to generate the data for an integrative structure modeling approach, which produced a well-defined molecular architecture of the SEA complex and showed that the SEA complex comprises two regions that are structurally and functionally distinct. The SEA complex emerges as a platform that can coordinate both structural and enzymatic activities necessary for the effective functioning of the TORC1 pathway. © 2014 by The American Society for Biochemistry and Molecular Biology, Inc.

DNAproDB: an interactive tool for structural analysis of DNA–protein complexes

PubMed Central

Sagendorf, Jared M.

2017-01-01

Abstract Many biological processes are mediated by complex interactions between DNA and proteins. Transcription factors, various polymerases, nucleases and histones recognize and bind DNA with different levels of binding specificity. To understand the physical mechanisms that allow proteins to recognize DNA and achieve their biological functions, it is important to analyze structures of DNA–protein complexes in detail. DNAproDB is a web-based interactive tool designed to help researchers study these complexes. DNAproDB provides an automated structure-processing pipeline that extracts structural features from DNA–protein complexes. The extracted features are organized in structured data files, which are easily parsed with any programming language or viewed in a browser. We processed a large number of DNA–protein complexes retrieved from the Protein Data Bank and created the DNAproDB database to store this data. Users can search the database by combining features of the DNA, protein or DNA–protein interactions at the interface. Additionally, users can upload their own structures for processing privately and securely. DNAproDB provides several interactive and customizable tools for creating visualizations of the DNA–protein interface at different levels of abstraction that can be exported as high quality figures. All functionality is documented and freely accessible at http://dnaprodb.usc.edu. PMID:28431131

Dancing Protein Clouds: The Strange Biology and Chaotic Physics of Intrinsically Disordered Proteins*

PubMed Central

2016-01-01

Biologically active but floppy proteins represent a new reality of modern protein science. These intrinsically disordered proteins (IDPs) and hybrid proteins containing ordered and intrinsically disordered protein regions (IDPRs) constitute a noticeable part of any given proteome. Functionally, they complement ordered proteins, and their conformational flexibility and structural plasticity allow them to perform impossible tricks and be engaged in biological activities that are inaccessible to well folded proteins with their unique structures. The major goals of this minireview are to show that, despite their simplified amino acid sequences, IDPs/IDPRs are complex entities often resembling chaotic systems, are structurally and functionally heterogeneous, and can be considered an important part of the structure-function continuum. Furthermore, IDPs/IDPRs are everywhere, and are ubiquitously engaged in various interactions characterized by a wide spectrum of binding scenarios and an even wider spectrum of structural and functional outputs. PMID:26851286

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.

Nanodiamonds as Carriers for Address Delivery of Biologically Active Substances

NASA Astrophysics Data System (ADS)

Purtov, K. V.; Petunin, A. I.; Burov, A. E.; Puzyr, A. P.; Bondar, V. S.

2010-03-01

Surface of detonation nanodiamonds was functionalized for the covalent attachment of immunoglobulin, and simultaneously bovine serum albumin and Rabbit Anti-Mouse Antibody. The nanodiamond-IgGI125 and RAM-nanodiamond-BSAI125 complexes are stable in blood serum and the immobilized proteins retain their biological activity. It was shown that the RAM-nanodiamond-BSAI125 complex is able to bind to the target antigen immobilized on the Sepharose 6B matrix through antibody-antigen interaction. The idea can be extended to use nanodiamonds as carriers for delivery of bioactive substances (i.e., drugs) to various targets in vivo.

BioCreative V track 4: a shared task for the extraction of causal network information using the Biological Expression Language.

PubMed

Rinaldi, Fabio; Ellendorff, Tilia Renate; Madan, Sumit; Clematide, Simon; van der Lek, Adrian; Mevissen, Theo; Fluck, Juliane

2016-01-01

Automatic extraction of biological network information is one of the most desired and most complex tasks in biological and medical text mining. Track 4 at BioCreative V attempts to approach this complexity using fragments of large-scale manually curated biological networks, represented in Biological Expression Language (BEL), as training and test data. BEL is an advanced knowledge representation format which has been designed to be both human readable and machine processable. The specific goal of track 4 was to evaluate text mining systems capable of automatically constructing BEL statements from given evidence text, and of retrieving evidence text for given BEL statements. Given the complexity of the task, we designed an evaluation methodology which gives credit to partially correct statements. We identified various levels of information expressed by BEL statements, such as entities, functions, relations, and introduced an evaluation framework which rewards systems capable of delivering useful BEL fragments at each of these levels. The aim of this evaluation method is to help identify the characteristics of the systems which, if combined, would be most useful for achieving the overall goal of automatically constructing causal biological networks from text. © The Author(s) 2016. Published by Oxford University Press.

Evolving Concepts and Translational Relevance of Enteroendocrine Cell Biology.

PubMed

Drucker, Daniel J

2016-03-01

Classical enteroenteroendocrine cell (EEC) biology evolved historically from identification of scattered hormone-producing endocrine cells within the epithelial mucosa of the stomach, small and large intestine. Purification of functional EEC hormones from intestinal extracts, coupled with molecular cloning of cDNAs and genes expressed within EECs has greatly expanded the complexity of EEC endocrinology, with implications for understanding the contribution of EECs to disease pathophysiology. Pubmed searches identified manuscripts highlighting new concepts illuminating the molecular biology, classification and functional role(s) of EECs and their hormonal products. Molecular interrogation of EECs has been transformed over the past decade, raising multiple new questions that challenge historical concepts of EEC biology. Evidence for evolution of the EEC from a unihormonal cell type with classical endocrine actions, to a complex plurihormonal dynamic cell with pleiotropic interactive functional networks within the gastrointestinal mucosa is critically assessed. We discuss gaps in understanding how EECs sense and respond to nutrients, cytokines, toxins, pathogens, the microbiota, and the microbial metabolome, and highlight the expanding translational relevance of EECs in the pathophysiology and therapy of metabolic and inflammatory disorders. The EEC system represents the largest specialized endocrine network in human physiology, integrating environmental and nutrient cues, enabling neural and hormonal control of metabolic homeostasis. Updating EEC classification systems will enable more accurate comparative analyses of EEC subpopulations and endocrine networks in multiple regions of the gastrointestinal tract.

Integrated Micro/nanoengineered Functional Biomaterials for Cell Mechanics and Mechanobiology: A Materials Perspective

PubMed Central

Shao, Yue

2014-01-01

The rapid development of micro/nanoengineered functional biomaterials in the last two decades has empowered materials scientists and bioengineers to precisely control different aspects of the in vitro cell microenvironment. Following a philosophy of reductionism, many studies using synthetic functional biomaterials have revealed instructive roles of individual extracellular biophysical and biochemical cues in regulating cellular behaviors. Development of integrated micro/nanoengineered functional biomaterials to study complex and emergent biological phenomena has also thrived rapidly in recent years, revealing adaptive and integrated cellular behaviors closely relevant to human physiological and pathological conditions. Working at the interface between materials science and engineering, biology, and medicine, we are now at the beginning of a great exploration using micro/nanoengineered functional biomaterials for both fundamental biology study and clinical and biomedical applications such as regenerative medicine and drug screening. In this review, we present an overview of state of the art micro/nanoengineered functional biomaterials that can control precisely individual aspects of cell-microenvironment interactions and highlight them as well-controlled platforms for mechanistic studies of mechano-sensitive and -responsive cellular behaviors and integrative biology research. We also discuss the recent exciting trend where micro/nanoengineered biomaterials are integrated into miniaturized biological and biomimetic systems for dynamic multiparametric microenvironmental control of emergent and integrated cellular behaviors. The impact of integrated micro/nanoengineered functional biomaterials for future in vitro studies of regenerative medicine, cell biology, as well as human development and disease models are discussed. PMID:24339188

BioLayout(Java): versatile network visualisation of structural and functional relationships.

PubMed

Goldovsky, Leon; Cases, Ildefonso; Enright, Anton J; Ouzounis, Christos A

2005-01-01

Visualisation of biological networks is becoming a common task for the analysis of high-throughput data. These networks correspond to a wide variety of biological relationships, such as sequence similarity, metabolic pathways, gene regulatory cascades and protein interactions. We present a general approach for the representation and analysis of networks of variable type, size and complexity. The application is based on the original BioLayout program (C-language implementation of the Fruchterman-Rheingold layout algorithm), entirely re-written in Java to guarantee portability across platforms. BioLayout(Java) provides broader functionality, various analysis techniques, extensions for better visualisation and a new user interface. Examples of analysis of biological networks using BioLayout(Java) are presented.

Venom Proteins from Parasitoid Wasps and Their Biological Functions

PubMed Central

Moreau, Sébastien J. M.; Asgari, Sassan

2015-01-01

Parasitoid wasps are valuable biological control agents that suppress their host populations. Factors introduced by the female wasp at parasitization play significant roles in facilitating successful development of the parasitoid larva either inside (endoparasitoid) or outside (ectoparasitoid) the host. Wasp venoms consist of a complex cocktail of proteinacious and non-proteinacious components that may offer agrichemicals as well as pharmaceutical components to improve pest management or health related disorders. Undesirably, the constituents of only a small number of wasp venoms are known. In this article, we review the latest research on venom from parasitoid wasps with an emphasis on their biological function, applications and new approaches used in venom studies. PMID:26131769

Altered cell function in microgravity

NASA Technical Reports Server (NTRS)

Hughes-Fulford, Millie

1991-01-01

The paper overviews published results from investigations of changes in basic biological parameters taking place as a result of spaceflight exposure. These include changes in the rates of the DNA, mRNA, and protein biosyntheses; changes in the growth rate of an organism; and alterations in the cytoskeleton structure, differentiation, hormone accumulation, and collagen matrix secretion. These results, obtained both in complex biological organisms and on cultured cells, suggest that a basic cellular function is influenced and changed by microgravity. Many of the above mentioned changes are also found to take place in aging cells.

Endobiogeny: a global approach to systems biology (part 2 of 2).

PubMed

Lapraz, Jean-Claude; Hedayat, Kamyar M; Pauly, Patrice

2013-03-01

ENDOBIOGENY AND THE BIOLOGY OF FUNCTIONS ARE BASED ON FOUR SCIENTIFIC CONCEPTS THAT ARE KNOWN AND GENERALLY ACCEPTED: (1) human physiology is complex and multifactorial and exhibits the properties of a system; (2) the endocrine system manages metabolism, which is the basis of the continuity of life; (3) the metabolic activity managed by the endocrine system results in the output of biomarkers that reflect the functional achievement of specific aspects of metabolism; and (4) when biomarkers are related to each other in ratios, it contextualizes one type of function relative to another to which is it linked anatomically, sequentially, chronologically, biochemically, etc.

[Architecture of receptor-operated ionic channels of biological membranes].

PubMed

Bregestovski, P D

2011-01-01

Ion channels of biological membranes are the key proteins, which provide bioelectric functioning of living systems. These proteins are homo- or heterooligomers assembled from several identical or different subunits. Understanding the architectural organization and functioning of ion channels has been significantly extended due to resolving the crystal structure of several types of voltage-gated and receptor-operated channels. This review summarizes the information obtained from crystal structures of potassium, nicotinic acetylcholine receptor, P2X, and other ligand-gated ion channels. Despite the differences in the function, topology, ionic selectivity, and the subunit stoichiometry, a high similarity in the principles of organization of these macromolecular complexes has been revealed.

Emerging themes in the ecology and management of North American forests

Treesearch

Terry L. Sharik; William Adair; Fred A. Baker; Michael Battaglia; Emily J. Comfort; Anthony W. D' Amato; Craig Delong; R. Justin DeRose; Mark J. Ducey; Mark Harmon; Louise Levy; Jesse A. Logan; Joseph O' Brien; Brian J. Palik; Scott D. Roberts; Paul C. Rogers; Douglas J. Shinneman; Thomas Spies; Sarah L. Taylor; Christopher Woodall; Andrew Youngblood

2010-01-01

Forests are extremely complex systems that respond to an overwhelming number of biological and environmental factors, which can act singularly and in concert with each other, as exemplified by Puettmann et al. [1]. The complexity of forest systems presents an enormous challenge for forest researchers who try to deepen their understanding of the structure and function...

Synergizing Engineering and Biology to Treat and Model Skeletal Muscle Injury and Disease

PubMed Central

Bursac, Nenad; Juhas, Mark; Rando, Thomas A.

2016-01-01

Although skeletal muscle is one of the most regenerative organs in our body, various genetic defects, alterations in extrinsic signaling, or substantial tissue damage can impair muscle function and the capacity for self-repair. The diversity and complexity of muscle disorders have attracted much interest from both cell biologists and, more recently, bioengineers, leading to concentrated efforts to better understand muscle pathology and develop more efficient therapies. This review describes the biological underpinnings of muscle development, repair, and disease, and discusses recent bioengineering efforts to design and control myomimetic environments, both to study muscle biology and function and to aid in the development of new drug, cell, and gene therapies for muscle disorders. The synergy between engineering-aided biological discovery and biology-inspired engineering solutions will be the path forward for translating laboratory results into clinical practice. PMID:26643021

A Biomimetic Approach to Discrimination Between Sequential and Concerted Models for the Oxidation of Ubiquinol at the Qo­ site of the Cyt bc1 Complex

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

Cape, Jonathan L.; Forquer, Isaac P.; Bowman, Michael K.

2005-09-26

The cytochrome bc complexes function as quinol:cytochrome c oxidoreductases in the energy conserving membranes of nearly all organisms, where they couple the oxidation of a quinol substrate (QH2) to the pumping of protons across the bioenergetic membrane, resulting in the establishment of a proton motive force, which is used to drive the (C)F0/(C)F1 ATP synthase (Trumpower and Gennis 1994). Among the variety of biological quinols characterized, ubiquinol is the substrate used by most bc-type complexes, and its reactions are of great interest concerning diseases related to oxidative stress and the fundamentals of biological energy transduction.

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.

Quantitative biology of single neurons

PubMed Central

Eberwine, James; Lovatt, Ditte; Buckley, Peter; Dueck, Hannah; Francis, Chantal; Kim, Tae Kyung; Lee, Jaehee; Lee, Miler; Miyashiro, Kevin; Morris, Jacqueline; Peritz, Tiina; Schochet, Terri; Spaethling, Jennifer; Sul, Jai-Yoon; Kim, Junhyong

2012-01-01

The building blocks of complex biological systems are single cells. Fundamental insights gained from single-cell analysis promise to provide the framework for understanding normal biological systems development as well as the limits on systems/cellular ability to respond to disease. The interplay of cells to create functional systems is not well understood. Until recently, the study of single cells has concentrated primarily on morphological and physiological characterization. With the application of new highly sensitive molecular and genomic technologies, the quantitative biochemistry of single cells is now accessible. PMID:22915636

Plant peptide hormone signalling.

PubMed

Motomitsu, Ayane; Sawa, Shinichiro; Ishida, Takashi

2015-01-01

The ligand-receptor-based cell-to-cell communication system is one of the most important molecular bases for the establishment of complex multicellular organisms. Plants have evolved highly complex intercellular communication systems. Historical studies have identified several molecules, designated phytohormones, that function in these processes. Recent advances in molecular biological analyses have identified phytohormone receptors and signalling mediators, and have led to the discovery of numerous peptide-based signalling molecules. Subsequent analyses have revealed the involvement in and contribution of these peptides to multiple aspects of the plant life cycle, including development and environmental responses, similar to the functions of canonical phytohormones. On the basis of this knowledge, the view that these peptide hormones are pivotal regulators in plants is becoming increasingly accepted. Peptide hormones are transcribed from the genome and translated into peptides. However, these peptides generally undergo further post-translational modifications to enable them to exert their function. Peptide hormones are expressed in and secreted from specific cells or tissues. Apoplastic peptides are perceived by specialized receptors that are located at the surface of target cells. Peptide hormone-receptor complexes activate intracellular signalling through downstream molecules, including kinases and transcription factors, which then trigger cellular events. In this chapter we provide a comprehensive summary of the biological functions of peptide hormones, focusing on how they mature and the ways in which they modulate plant functions. © 2015 Authors; published by Portland Press Limited.

Processes that Drove the Transition from Chemistry to Biology: Concepts and Evidence

NASA Technical Reports Server (NTRS)

Pohorille, Andrew

2012-01-01

Two properties are particularly germane to the transition from chemistry to biology. One is the emergence of complex molecules (polymers) capable of performing non-trivial functions, such as catalysis, energy transduction or transport across cell walls. The other is the ability of several functions to work in concert to provide reproductive advantage to systems hosting these functions. Biological systems exhibit these properties at remarkable levels of efficiency and accuracy in a way that appears effortless. However, dissection of these properties reveals great complexities that are involved. This opens a question: how a simple, ancestral system could have acquired the required properties? Other questions follow. What are the chances that a functional polymer emerges at random? What is the minimum structural complexity of a polymer to carry out a function at a reasonable level of efficiency? Can we identify concrete, protobiologically plausible mechanisms that yield advantageous coupling between different functions? These and similar questions are at the core of the main topic of this session: how soulless chemistry became life? Clearly, we do not have complete answers to any of these questions. However, in recent years a number of new and sometimes unexpected clues have been brought to light. Of particular interest are proteins because they are the main functional polymers in contemporary cells. The emergence of protein functions is a puzzle. It is widely accepted that a well ]defined, compact structure (fold) is a prerequisite for function. It is equally widely accepted that compact folds are rare among random amino acid polymers. Then, how did protein functionality start? According to one hypothesis well folded were preceded by their poorly folded, yet still functional ancestors. Only recently, however, experimental evidence supporting this hypothesis has been presented. In particular, a small enzyme capable of ligating two RNA fragments with the rate of 106 above background was evolved in vitro. This enzyme does not look like any contemporary protein. It is very flexible and its structure is kept together just by a single salt bridge between a charged residue and a coordinating zinc. A similar picture emerges from studies of simple transmembrane channels that mimic those in ancestral cells. Again, they are extremely flexible and do not form a conventional pore. Yet, they efficiently mediate ion transport. Studies on simple proteins that are on-going in several laboratories hold promise of revealing crucial links between chemical and biological catalysis and other ubiquitous cell functions. Interaction between composition, growth and division of protobiologically relevant vesicles and metabolic reactions that they encapsulate is an example of coupling between simple functions that promotes reproduction and evolution. Recent studies have demonstrated possible mechanisms by which vesicles might have evolved their composition from fatty acids to phospholipids, thus facilitating a number of new cellular functions. Conversely, it has been also demonstrated that an encapsulated metabolism might drive vesicle division. These are, again, examples of processes that might have driven the transition from chemistry to biology.

Supported inhibitor for fishing lipases in complex biological media and mass spectrometry identification.

PubMed

Delorme, Vincent; Raux, Brigitt; Puppo, Rémy; Leclaire, Julien; Cavalier, Jean-François; Marc, Sylvain; Kamarajugadda, Pavan-Kumar; Buono, Gérard; Fotiadu, Frédéric; Canaan, Stéphane; Carrière, Frédéric

2014-12-01

A synthetic phosphonate inhibitor designed for lipase inhibition but displaying a broader range of activity was covalently immobilized on a solid support to generate a function-directed tool targeting serine hydrolases. To achieve this goal, straightforward and reliable analytical techniques were developed, allowing the monitoring of the solid support's chemical functionalization, enzyme capture processes and physisorption artifacts. This grafted inhibitor was tested on pure lipases and serine proteases from various origins, and assayed for the selective capture of lipases from several complex biological extracts. The direct identification of captured enzymes by mass spectrometry brought the proof of concept on the efficiency of this supported covalent inhibitor. The features and limitations of this "enzyme-fishing" proteomic tool provide new insight on solid-liquid inhibition process. Copyright © 2014. Published by Elsevier B.V.

Inferring hidden causal relations between pathway members using reduced Google matrix of directed biological networks

PubMed Central

2018-01-01

Signaling pathways represent parts of the global biological molecular network which connects them into a seamless whole through complex direct and indirect (hidden) crosstalk whose structure can change during development or in pathological conditions. We suggest a novel methodology, called Googlomics, for the structural analysis of directed biological networks using spectral analysis of their Google matrices, using parallels with quantum scattering theory, developed for nuclear and mesoscopic physics and quantum chaos. We introduce analytical “reduced Google matrix” method for the analysis of biological network structure. The method allows inferring hidden causal relations between the members of a signaling pathway or a functionally related group of genes. We investigate how the structure of hidden causal relations can be reprogrammed as a result of changes in the transcriptional network layer during cancerogenesis. The suggested Googlomics approach rigorously characterizes complex systemic changes in the wiring of large causal biological networks in a computationally efficient way. PMID:29370181

A method to identify and analyze biological programs through automated reasoning

PubMed Central

Yordanov, Boyan; Dunn, Sara-Jane; Kugler, Hillel; Smith, Austin; Martello, Graziano; Emmott, Stephen

2016-01-01

Predictive biology is elusive because rigorous, data-constrained, mechanistic models of complex biological systems are difficult to derive and validate. Current approaches tend to construct and examine static interaction network models, which are descriptively rich, but often lack explanatory and predictive power, or dynamic models that can be simulated to reproduce known behavior. However, in such approaches implicit assumptions are introduced as typically only one mechanism is considered, and exhaustively investigating all scenarios is impractical using simulation. To address these limitations, we present a methodology based on automated formal reasoning, which permits the synthesis and analysis of the complete set of logical models consistent with experimental observations. We test hypotheses against all candidate models, and remove the need for simulation by characterizing and simultaneously analyzing all mechanistic explanations of observed behavior. Our methodology transforms knowledge of complex biological processes from sets of possible interactions and experimental observations to precise, predictive biological programs governing cell function. PMID:27668090

Predicting Physical Interactions between Protein Complexes*

PubMed Central

Clancy, Trevor; Rødland, Einar Andreas; Nygard, Ståle; Hovig, Eivind

2013-01-01

Protein complexes enact most biochemical functions in the cell. Dynamic interactions between protein complexes are frequent in many cellular processes. As they are often of a transient nature, they may be difficult to detect using current genome-wide screens. Here, we describe a method to computationally predict physical interactions between protein complexes, applied to both humans and yeast. We integrated manually curated protein complexes and physical protein interaction networks, and we designed a statistical method to identify pairs of protein complexes where the number of protein interactions between a complex pair is due to an actual physical interaction between the complexes. An evaluation against manually curated physical complex-complex interactions in yeast revealed that 50% of these interactions could be predicted in this manner. A community network analysis of the highest scoring pairs revealed a biologically sensible organization of physical complex-complex interactions in the cell. Such analyses of proteomes may serve as a guide to the discovery of novel functional cellular relationships. PMID:23438732

Evolution of egg coats: linking molecular biology and ecology.

PubMed

Shu, Longfei; Suter, Marc J-F; Räsänen, Katja

2015-08-01

One central goal of evolutionary biology is to explain how biological diversity emerges and is maintained in nature. Given the complexity of the phenotype and the multifaceted nature of inheritance, modern evolutionary ecological studies rely heavily on the use of molecular tools. Here, we show how molecular tools help to gain insight into the role of egg coats (i.e. the extracellular structures surrounding eggs and embryos) in evolutionary diversification. Egg coats are maternally derived structures that have many biological functions from mediating fertilization to protecting the embryo from environmental hazards. They show great molecular, structural and functional diversity across species, but intraspecific variability and the role of ecology in egg coat evolution have largely been overlooked. Given that much of the variation that influences egg coat function is ultimately determined by their molecular phenotype, cutting-edge molecular tools (e.g. proteomics, glycomics and transcriptomics), combined with functional assays, are needed for rigorous inferences on their evolutionary ecology. Here, we identify key research areas and highlight emerging molecular techniques that can increase our understanding of the role of egg coats in the evolution of biological diversity, from adaptation to speciation. © 2015 John Wiley & Sons Ltd.

Linear ubiquitin chains: enzymes, mechanisms and biology

PubMed Central

2017-01-01

Ubiquitination is a versatile post-translational modification that regulates a multitude of cellular processes. Its versatility is based on the ability of ubiquitin to form multiple types of polyubiquitin chains, which are recognized by specific ubiquitin receptors to induce the required cellular response. Linear ubiquitin chains are linked through Met 1 and have been established as important players of inflammatory signalling and apoptotic cell death. These chains are generated by a ubiquitin E3 ligase complex called the linear ubiquitin chain assembly complex (LUBAC) that is thus far the only E3 ligase capable of forming linear ubiquitin chains. The complex consists of three subunits, HOIP, HOIL-1L and SHARPIN, each of which have specific roles in the observed biological functions of LUBAC. Furthermore, LUBAC has been found to be associated with OTULIN and CYLD, deubiquitinases that disassemble linear chains and counterbalance the E3 ligase activity of LUBAC. Gene mutations in HOIP, HOIL-1L and OTULIN are found in human patients who suffer from autoimmune diseases, and HOIL-1L mutations are also found in myopathy patients. In this paper, we discuss the mechanisms of linear ubiquitin chain generation and disassembly by their respective enzymes and review our current understanding of their biological functions and association with human diseases. PMID:28446710

Linear ubiquitin chains: enzymes, mechanisms and biology.

PubMed

Rittinger, Katrin; Ikeda, Fumiyo

2017-04-01

Ubiquitination is a versatile post-translational modification that regulates a multitude of cellular processes. Its versatility is based on the ability of ubiquitin to form multiple types of polyubiquitin chains, which are recognized by specific ubiquitin receptors to induce the required cellular response. Linear ubiquitin chains are linked through Met 1 and have been established as important players of inflammatory signalling and apoptotic cell death. These chains are generated by a ubiquitin E3 ligase complex called the linear ubiquitin chain assembly complex (LUBAC) that is thus far the only E3 ligase capable of forming linear ubiquitin chains. The complex consists of three subunits, HOIP, HOIL-1L and SHARPIN, each of which have specific roles in the observed biological functions of LUBAC. Furthermore, LUBAC has been found to be associated with OTULIN and CYLD, deubiquitinases that disassemble linear chains and counterbalance the E3 ligase activity of LUBAC. Gene mutations in HOIP, HOIL-1L and OTULIN are found in human patients who suffer from autoimmune diseases, and HOIL-1L mutations are also found in myopathy patients. In this paper, we discuss the mechanisms of linear ubiquitin chain generation and disassembly by their respective enzymes and review our current understanding of their biological functions and association with human diseases. © 2017 The Authors.

Discovering Link Communities in Complex Networks by an Integer Programming Model and a Genetic Algorithm

PubMed Central

Li, Zhenping; Zhang, Xiang-Sun; Wang, Rui-Sheng; Liu, Hongwei; Zhang, Shihua

2013-01-01

Identification of communities in complex networks is an important topic and issue in many fields such as sociology, biology, and computer science. Communities are often defined as groups of related nodes or links that correspond to functional subunits in the corresponding complex systems. While most conventional approaches have focused on discovering communities of nodes, some recent studies start partitioning links to find overlapping communities straightforwardly. In this paper, we propose a new quantity function for link community identification in complex networks. Based on this quantity function we formulate the link community partition problem into an integer programming model which allows us to partition a complex network into overlapping communities. We further propose a genetic algorithm for link community detection which can partition a network into overlapping communities without knowing the number of communities. We test our model and algorithm on both artificial networks and real-world networks. The results demonstrate that the model and algorithm are efficient in detecting overlapping community structure in complex networks. PMID:24386268

An integrated native mass spectrometry and top-down proteomics method that connects sequence to structure and function of macromolecular complexes

NASA Astrophysics Data System (ADS)

Li, Huilin; Nguyen, Hong Hanh; Ogorzalek Loo, Rachel R.; Campuzano, Iain D. G.; Loo, Joseph A.

2018-02-01

Mass spectrometry (MS) has become a crucial technique for the analysis of protein complexes. Native MS has traditionally examined protein subunit arrangements, while proteomics MS has focused on sequence identification. These two techniques are usually performed separately without taking advantage of the synergies between them. Here we describe the development of an integrated native MS and top-down proteomics method using Fourier-transform ion cyclotron resonance (FTICR) to analyse macromolecular protein complexes in a single experiment. We address previous concerns of employing FTICR MS to measure large macromolecular complexes by demonstrating the detection of complexes up to 1.8 MDa, and we demonstrate the efficacy of this technique for direct acquirement of sequence to higher-order structural information with several large complexes. We then summarize the unique functionalities of different activation/dissociation techniques. The platform expands the ability of MS to integrate proteomics and structural biology to provide insights into protein structure, function and regulation.

Zinc complexes developed as metallopharmaceutics for treating diabetes mellitus based on the bio-medicinal inorganic chemistry.

PubMed

Yoshikawa, Yutaka; Yasui, Hiroyuki

2012-01-01

Biological trace metals such as iron, zinc, copper, and manganese are essential to life and health of humans, and the success of platinum drugs in the cancer chemotherapy has rapidly grown interest in developing inorganic pharmaceutical agents in medicinal chemistry, that is, medicinal inorganic chemistry, using essential elements and other biological trace metals. Transition metal complexes with unique chemical structures may be useful alternatives to the drugs available to address some of the incurable diseases. In this review, we emphasize that metal complexes are an expanding of interest in the research field of treatment of diabetes mellitus. Especially, orally active anti-diabetic and anti-metabolic syndrome zinc complexes have been developed and progressed since the discovery in 2001, where several highly potent anti-diabetic zinc complexes with different coordination structures have quite recently been disclosed, using experimental diabetic animals. In all of the complexes discussed, zinc is found to be biologically active and function by interacting with some target proteins related with diabetes mellitus. The design and screening of zinc complexes with higher activity is not efficient without consideration of the translational research. For the development of a clinically useful metallopharmaceutics, the research of zinc complexes on the long-term toxicity including side effects, clear-cut evidence of target molecule for the in vivo pharmacological action, and good pharmacokinetic property are essential in the current and future studies.

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

Biological materials by design.

PubMed

Qin, Zhao; Dimas, Leon; Adler, David; Bratzel, Graham; Buehler, Markus J

2014-02-19

In this topical review we discuss recent advances in the use of physical insight into the way biological materials function, to design novel engineered materials 'from scratch', or from the level of fundamental building blocks upwards and by using computational multiscale methods that link chemistry to material function. We present studies that connect advances in multiscale hierarchical material structuring with material synthesis and testing, review case studies of wood and other biological materials, and illustrate how engineered fiber composites and bulk materials are designed, modeled, and then synthesized and tested experimentally. The integration of experiment and simulation in multiscale design opens new avenues to explore the physics of materials from a fundamental perspective, and using complementary strengths from models and empirical techniques. Recent developments in this field illustrate a new paradigm by which complex material functionality is achieved through hierarchical structuring in spite of simple material constituents.

Functional classification of schizophrenia using feed forward neural networks.

PubMed

Jafri, Madiha J; Calhoun, Vince D

2006-01-01

In medicine, the nature of an illness is often determined through behavioral or biological markers. The process of diagnosis becomes difficult when dealing with mental disorders since they rely primarily on behavioral markers. Schizophrenia is an example of a complex mental disorder that relies on aberrant behavior such as auditory hallucinations, dampening of emotions, paranoia, etc. This research is an attempt to determine a biological marker for schizophrenia through the use of functional magnetic resonance imaging (fMRI). In this paper, we propose a method of classification of schizophrenia and healthy controls, using a neural network approach and functional brain 'modes'estimated from resting state data using independent component analysis. A reliable technique for discriminating schizophrenia based upon fMRI would be a significant advance and may also provide additional information about the biological implications of mental illness.

Sequence co-evolution gives 3D contacts and structures of protein complexes

PubMed Central

Hopf, Thomas A; Schärfe, Charlotta P I; Rodrigues, João P G L M; Green, Anna G; Kohlbacher, Oliver; Sander, Chris; Bonvin, Alexandre M J J; Marks, Debora S

2014-01-01

Protein–protein interactions are fundamental to many biological processes. Experimental screens have identified tens of thousands of interactions, and structural biology has provided detailed functional insight for select 3D protein complexes. An alternative rich source of information about protein interactions is the evolutionary sequence record. Building on earlier work, we show that analysis of correlated evolutionary sequence changes across proteins identifies residues that are close in space with sufficient accuracy to determine the three-dimensional structure of the protein complexes. We evaluate prediction performance in blinded tests on 76 complexes of known 3D structure, predict protein–protein contacts in 32 complexes of unknown structure, and demonstrate how evolutionary couplings can be used to distinguish between interacting and non-interacting protein pairs in a large complex. With the current growth of sequences, we expect that the method can be generalized to genome-wide elucidation of protein–protein interaction networks and used for interaction predictions at residue resolution. DOI: http://dx.doi.org/10.7554/eLife.03430.001 PMID:25255213

Hydrolytic microbial communities in terrestrial ecosystems

NASA Astrophysics Data System (ADS)

Manucharova, Natalia; Chernov, Timofey; Kolcova, Ekaterina; Zelezova, Alena; Lukacheva, Euhenia; Zenova, Galina

2014-05-01

Hydrolytic microbial communities in terrestrial ecosystems Manucharova N.A., Chernov T.I., Kolcova E.M., Zelezova A.D., Lukacheva E.G. Lomonosov Moscow State University, Russia Vertical differentiation of terrestrial biogeocenoses is conditioned by the formation of vertical tiers that differ considerably in the composition and structure of microbial communities. All the three tiers, phylloplane, litter and soil, are united by a single flow of organic matter, and are spatially separated successional stages of decomposition of organic substances. Decomposition of organic matter is mainly due to the activity of microorganisms producing enzymes - hydrolase and lyase - which destroy complex organic compounds. Application of molecular biological techniques (FISH) in environmental studies provides a more complete information concerning the taxonomic diversity and potential hydrolytic activity of microbial complexes of terrestrial ecosystems that exist in a wide range of environmental factors (moisture, temperature, redox potential, organic matter). The combination of two molecular biological techniques (FISH and DGGE-analysis of fragments of gene 16S rRNA total amplificate) enables an informative assessment of the differences in the structure of dominant and minor components of hydrolytic complexes formed in different tiers of terrestrial ecosystems. The functional activity of hydrolytic microbial complexes of terrestrial ecosystems is determined by the activity of dominant and minor components, which also have a high gross enzymatic activity. Degradation of biopolymers in the phylloplane is mainly due to the representatives of the Proteobacteria phylogenetic group (classes alpha and beta). In mineral soil horizons, the role of hydrolytic representatives of Firmicutes and Actinobacteria increases. Among the key environmental parameters that determine the functional activity of the hydrolytic (chitinolytic) complex of soil layer (moisture, nutrient supply, successional time), the most significant one is moisture. Moisture levels providing maximum activity of a hydrolytic microbial complex depend on the soil type. Development of a hydrolytic microbial complex occurs in a very wide moisture range - from values close to field capacity to those close to the wilting moisture point. The functional role of mycelial actinobacteria in the metabolism of chitin consists, on the one hand, in active decomposition of this biopolymer, and on the other hand, in the regulation of microbial hydrolytic complex activity through the production of biologically active regulatory metabolites, which occurs in a wide range of environmental parameters (moisture, temperature, organic matter, successional time). Experimental design is applicable to identify in situ optimal values of environmental factors that considerably affect the functional parameters of hydrolytic microbial complexes.

Condensins: universal organizers of chromosomes with diverse functions

PubMed Central

Hirano, Tatsuya

2012-01-01

Condensins are multisubunit protein complexes that play a fundamental role in the structural and functional organization of chromosomes in the three domains of life. Most eukaryotic species have two different types of condensin complexes, known as condensins I and II, that fulfill nonoverlapping functions and are subjected to differential regulation during mitosis and meiosis. Recent studies revealed that the two complexes contribute to a wide variety of interphase chromosome functions, such as gene regulation, recombination, and repair. Also emerging are their cell type- and tissue-specific functions and relevance to human disease. Biochemical and structural analyses of eukaryotic and bacterial condensins steadily uncover the mechanisms of action of this class of highly sophisticated molecular machines. Future studies on condensins will not only enhance our understanding of chromosome architecture and dynamics, but also help address a previously underappreciated yet profound set of questions in chromosome biology. PMID:22855829

Integrated omics for the identification of key functionalities in biological wastewater treatment microbial communities.

PubMed

Narayanasamy, Shaman; Muller, Emilie E L; Sheik, Abdul R; Wilmes, Paul

2015-05-01

Biological wastewater treatment plants harbour diverse and complex microbial communities which prominently serve as models for microbial ecology and mixed culture biotechnological processes. Integrated omic analyses (combined metagenomics, metatranscriptomics, metaproteomics and metabolomics) are currently gaining momentum towards providing enhanced understanding of community structure, function and dynamics in situ as well as offering the potential to discover novel biological functionalities within the framework of Eco-Systems Biology. The integration of information from genome to metabolome allows the establishment of associations between genetic potential and final phenotype, a feature not realizable by only considering single 'omes'. Therefore, in our opinion, integrated omics will become the future standard for large-scale characterization of microbial consortia including those underpinning biological wastewater treatment processes. Systematically obtained time and space-resolved omic datasets will allow deconvolution of structure-function relationships by identifying key members and functions. Such knowledge will form the foundation for discovering novel genes on a much larger scale compared with previous efforts. In general, these insights will allow us to optimize microbial biotechnological processes either through better control of mixed culture processes or by use of more efficient enzymes in bioengineering applications. © 2015 The Authors. Microbial Biotechnology published by John Wiley & Sons Ltd and Society for Applied Microbiology.

An α-catenin déjà vu.

PubMed

Han, Siew-Ping; Yap, Alpha S

2013-03-01

α-Catenin exists as part of the cadherin-catenin adhesion complex as well as in a cytoplasmic pool. However, which of these pools is responsible for its biological impact remains controversial. A structure-function analysis in Drosophila melanogaster illuminates how the molecular properties of α-catenin translate into functional outcomes in an intact organism.

Enzymes in human milk

PubMed Central

Dallas, David C.; German, J. Bruce

2017-01-01

Milk proteins are a complex and diverse source of biological activities. Beyond their function intact, milk proteins also act as carriers of encrypted functional sequences that when released as peptides exert biological functions, including antimicrobial and immunomodulatory, which could contribute to the infant’s competitive success. Research has now revealed that the release of these functional peptides begins within the mammary gland itself. A complex array of proteases produced in mother’s milk have been shown to be active in the milk, releasing these peptides. Moreover, our recent research demonstrates that these milk proteases continue to digest milk proteins within the infant’s stomach, possibly even to a larger extent than the infant’s own proteases. As the neonate has relatively low digestive capacity, the activity of milk proteases in the infant may provide important assistance to digesting milk proteins. The coordinated release of these encrypted sequences is accomplished by selective proteolytic action provided by an array of native milk proteases and infant-produced enzymes. The task for scientists is now to discover the selective advantages of this protein-protease based peptide release system. PMID:28346930

Enzymes in Human Milk.

PubMed

Dallas, David C; German, J Bruce

2017-01-01

Milk proteins are a complex and diverse source of biological activities. Beyond their function, intact milk proteins also act as carriers of encrypted functional sequences that, when released as peptides, exert biological functions, including antimicrobial and immunomodulatory activity, which could contribute to the infant's competitive success. Research has now revealed that the release of these functional peptides begins within the mammary gland itself. A complex array of proteases produced in mother's milk has been shown to be active in the milk, releasing these peptides. Moreover, our recent research demonstrates that these milk proteases continue to digest milk proteins within the infant's stomach, possibly even to a larger extent than the infant's own proteases. As the neonate has relatively low digestive capacity, the activity of milk proteases in the infant may provide important assistance to digesting milk proteins. The coordinated release of these encrypted sequences is accomplished by selective proteolytic action provided by an array of native milk proteases and infant-produced enzymes. The task for scientists is now to discover the selective advantages of this protein-protease-based peptide release system. © 2017 Nestec Ltd., Vevey/S. Karger AG, Basel.

Biological effects of simple changes in functionality on rhodium metalloinsertors

PubMed Central

Weidmann, Alyson G.; Komor, Alexis C.; Barton, Jacqueline K.

2013-01-01

DNA mismatch repair (MMR) is crucial to ensuring the fidelity of the genome. The inability to correct single base mismatches leads to elevated mutation rates and carcinogenesis. Using metalloinsertors–bulky metal complexes that bind with high specificity to mismatched sites in the DNA duplex–our laboratory has adopted a new chemotherapeutic strategy through the selective targeting of MMR-deficient cells, that is, those that have a propensity for cancerous transformation. Rhodium metalloinsertors display inhibitory effects selectively in cells that are deficient in the MMR machinery, consistent with this strategy. However, a highly sensitive structure–function relationship is emerging with the development of new complexes that highlights the importance of subcellular localization. We have found that small structural modifications, for example a hydroxyl versus a methyl functional group, can yield profound differences in biological function. Despite similar binding affinities and selectivities for DNA mismatches, only one metalloinsertor shows selective inhibition of cellular proliferation in MMR-deficient versus -proficient cells. Studies of whole-cell, nuclear and mitochondrial uptake reveal that this selectivity depends upon targeting DNA mismatches in the cell nucleus. PMID:23776288

Drosophila melanogaster--the model organism of choice for the complex biology of multi-cellular organisms

NASA Technical Reports Server (NTRS)

Beckingham, Kathleen M.; Armstrong, J. Douglas; Texada, Michael J.; Munjaal, Ravi; Baker, Dean A.

2005-01-01

Drosophila melanogaster has been intensely studied for almost 100 years. The sophisticated array of genetic and molecular tools that have evolved for analysis of gene function in this organism are unique. Further, Drosophila is a complex multi-cellular organism in which many aspects of development and behavior parallel those in human beings. These combined advantages have permitted research in Drosophila to make seminal contributions to the understanding of fundamental biological processes and ensure that Drosophila will continue to provide unique insights in the genomic era. An overview of the genetic methodologies available in Drosophila is given here, together with examples of outstanding recent contributions of Drosophila to our understanding of cell and organismal biology. The growing contribution of Drosophila to our knowledge of gravity-related responses is addressed.

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.

The relative vertex clustering value - a new criterion for the fast discovery of functional modules in protein interaction networks

PubMed Central

2015-01-01

Background Cellular processes are known to be modular and are realized by groups of proteins implicated in common biological functions. Such groups of proteins are called functional modules, and many community detection methods have been devised for their discovery from protein interaction networks (PINs) data. In current agglomerative clustering approaches, vertices with just a very few neighbors are often classified as separate clusters, which does not make sense biologically. Also, a major limitation of agglomerative techniques is that their computational efficiency do not scale well to large PINs. Finally, PIN data obtained from large scale experiments generally contain many false positives, and this makes it hard for agglomerative clustering methods to find the correct clusters, since they are known to be sensitive to noisy data. Results We propose a local similarity premetric, the relative vertex clustering value, as a new criterion allowing to decide when a node can be added to a given node's cluster and which addresses the above three issues. Based on this criterion, we introduce a novel and very fast agglomerative clustering technique, FAC-PIN, for discovering functional modules and protein complexes from a PIN data. Conclusions Our proposed FAC-PIN algorithm is applied to nine PIN data from eight different species including the yeast PIN, and the identified functional modules are validated using Gene Ontology (GO) annotations from DAVID Bioinformatics Resources. Identified protein complexes are also validated using experimentally verified complexes. Computational results show that FAC-PIN can discover functional modules or protein complexes from PINs more accurately and more efficiently than HC-PIN and CNM, the current state-of-the-art approaches for clustering PINs in an agglomerative manner. PMID:25734691

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.

Telomere biology in aging and cancer: early history and perspectives.

PubMed

Hayashi, Makoto T

2018-01-20

The ends of eukaryotic linear chromosomes are protected from undesired enzymatic activities by a nucleoprotein complex called the telomere. Expanding evidence indicates that telomeres have central functions in human aging and tumorigenesis. While it is undoubtedly important to follow current advances in telomere biology, it is also fruitful to be well informed in seminal historical studies for a comprehensive understanding of telomere biology, and for the anticipation of future directions. With this in mind, I here summarize the early history of telomere biology and current advances in the field, mostly focusing on mammalian studies relevant to aging and cancer.

Bringing the physical sciences into your cell biology research

PubMed Central

Robinson, Douglas N.; Iglesias, Pablo A.

2012-01-01

Historically, much of biology was studied by physicists and mathematicians. With the advent of modern molecular biology, a wave of researchers became trained in a new scientific discipline filled with the language of genes, mutants, and the central dogma. These new molecular approaches have provided volumes of information on biomolecules and molecular pathways from the cellular to the organismal level. The challenge now is to determine how this seemingly endless list of components works together to promote the healthy function of complex living systems. This effort requires an interdisciplinary approach by investigators from both the biological and the physical sciences. PMID:23112230

Bringing the physical sciences into your cell biology research.

PubMed

Robinson, Douglas N; Iglesias, Pablo A

2012-11-01

Historically, much of biology was studied by physicists and mathematicians. With the advent of modern molecular biology, a wave of researchers became trained in a new scientific discipline filled with the language of genes, mutants, and the central dogma. These new molecular approaches have provided volumes of information on biomolecules and molecular pathways from the cellular to the organismal level. The challenge now is to determine how this seemingly endless list of components works together to promote the healthy function of complex living systems. This effort requires an interdisciplinary approach by investigators from both the biological and the physical sciences.

Unzippers, Resolvers and Sensors: A Structural and Functional Biochemistry Tale of RNA Helicases

PubMed Central

Leitão, Ana Lúcia; Costa, Marina C.; Enguita, Francisco J.

2015-01-01

The centrality of RNA within the biological world is an irrefutable fact that currently attracts increasing attention from the scientific community. The panoply of functional RNAs requires the existence of specific biological caretakers, RNA helicases, devoted to maintain the proper folding of those molecules, resolving unstable structures. However, evolution has taken advantage of the specific position and characteristics of RNA helicases to develop new functions for these proteins, which are at the interface of the basic processes for transference of information from DNA to proteins. RNA helicases are involved in many biologically relevant processes, not only as RNA chaperones, but also as signal transducers, scaffolds of molecular complexes, and regulatory elements. Structural biology studies during the last decade, founded in X-ray crystallography, have characterized in detail several RNA-helicases. This comprehensive review summarizes the structural knowledge accumulated in the last two decades within this family of proteins, with special emphasis on the structure-function relationships of the most widely-studied families of RNA helicases: the DEAD-box, RIG-I-like and viral NS3 classes. PMID:25622248

Gene-Disease Network Analysis Reveals Functional Modules in Mendelian, Complex and Environmental Diseases

PubMed Central

Bauer-Mehren, Anna; Bundschus, Markus; Rautschka, Michael; Mayer, Miguel A.; Sanz, Ferran; Furlong, Laura I.

2011-01-01

Background Scientists have been trying to understand the molecular mechanisms of diseases to design preventive and therapeutic strategies for a long time. For some diseases, it has become evident that it is not enough to obtain a catalogue of the disease-related genes but to uncover how disruptions of molecular networks in the cell give rise to disease phenotypes. Moreover, with the unprecedented wealth of information available, even obtaining such catalogue is extremely difficult. Principal Findings We developed a comprehensive gene-disease association database by integrating associations from several sources that cover different biomedical aspects of diseases. In particular, we focus on the current knowledge of human genetic diseases including mendelian, complex and environmental diseases. To assess the concept of modularity of human diseases, we performed a systematic study of the emergent properties of human gene-disease networks by means of network topology and functional annotation analysis. The results indicate a highly shared genetic origin of human diseases and show that for most diseases, including mendelian, complex and environmental diseases, functional modules exist. Moreover, a core set of biological pathways is found to be associated with most human diseases. We obtained similar results when studying clusters of diseases, suggesting that related diseases might arise due to dysfunction of common biological processes in the cell. Conclusions For the first time, we include mendelian, complex and environmental diseases in an integrated gene-disease association database and show that the concept of modularity applies for all of them. We furthermore provide a functional analysis of disease-related modules providing important new biological insights, which might not be discovered when considering each of the gene-disease association repositories independently. Hence, we present a suitable framework for the study of how genetic and environmental factors, such as drugs, contribute to diseases. Availability The gene-disease networks used in this study and part of the analysis are available at http://ibi.imim.es/DisGeNET/DisGeNETweb.html#Download. PMID:21695124

Gene-disease network analysis reveals functional modules in mendelian, complex and environmental diseases.

PubMed

Bauer-Mehren, Anna; Bundschus, Markus; Rautschka, Michael; Mayer, Miguel A; Sanz, Ferran; Furlong, Laura I

2011-01-01

Scientists have been trying to understand the molecular mechanisms of diseases to design preventive and therapeutic strategies for a long time. For some diseases, it has become evident that it is not enough to obtain a catalogue of the disease-related genes but to uncover how disruptions of molecular networks in the cell give rise to disease phenotypes. Moreover, with the unprecedented wealth of information available, even obtaining such catalogue is extremely difficult. We developed a comprehensive gene-disease association database by integrating associations from several sources that cover different biomedical aspects of diseases. In particular, we focus on the current knowledge of human genetic diseases including mendelian, complex and environmental diseases. To assess the concept of modularity of human diseases, we performed a systematic study of the emergent properties of human gene-disease networks by means of network topology and functional annotation analysis. The results indicate a highly shared genetic origin of human diseases and show that for most diseases, including mendelian, complex and environmental diseases, functional modules exist. Moreover, a core set of biological pathways is found to be associated with most human diseases. We obtained similar results when studying clusters of diseases, suggesting that related diseases might arise due to dysfunction of common biological processes in the cell. For the first time, we include mendelian, complex and environmental diseases in an integrated gene-disease association database and show that the concept of modularity applies for all of them. We furthermore provide a functional analysis of disease-related modules providing important new biological insights, which might not be discovered when considering each of the gene-disease association repositories independently. Hence, we present a suitable framework for the study of how genetic and environmental factors, such as drugs, contribute to diseases. The gene-disease networks used in this study and part of the analysis are available at http://ibi.imim.es/DisGeNET/DisGeNETweb.html#Download.

Understanding RNA modifications: the promises and technological bottlenecks of the ‘epitranscriptome’

PubMed Central

Kapoor, Utkarsh

2017-01-01

The discovery of mechanisms that alter genetic information via RNA editing or introducing covalent RNA modifications points towards a complexity in gene expression that challenges long-standing concepts. Understanding the biology of RNA modifications represents one of the next frontiers in molecular biology. To this date, over 130 different RNA modifications have been identified, and improved mass spectrometry approaches are still adding to this list. However, only recently has it been possible to map selected RNA modifications at single-nucleotide resolution, which has created a number of exciting hypotheses about the biological function of RNA modifications, culminating in the proposition of the ‘epitranscriptome’. Here, we review some of the technological advances in this rapidly developing field, identify the conceptual challenges and discuss approaches that are needed to rigorously test the biological function of specific RNA modifications. PMID:28566301

Functional annotation of the vlinc class of non-coding RNAs using systems biology approach

PubMed Central

Laurent, Georges St.; Vyatkin, Yuri; Antonets, Denis; Ri, Maxim; Qi, Yao; Saik, Olga; Shtokalo, Dmitry; de Hoon, Michiel J.L.; Kawaji, Hideya; Itoh, Masayoshi; Lassmann, Timo; Arner, Erik; Forrest, Alistair R.R.; Nicolas, Estelle; McCaffrey, Timothy A.; Carninci, Piero; Hayashizaki, Yoshihide; Wahlestedt, Claes; Kapranov, Philipp

2016-01-01

Functionality of the non-coding transcripts encoded by the human genome is the coveted goal of the modern genomics research. While commonly relied on the classical methods of forward genetics, integration of different genomics datasets in a global Systems Biology fashion presents a more productive avenue of achieving this very complex aim. Here we report application of a Systems Biology-based approach to dissect functionality of a newly identified vast class of very long intergenic non-coding (vlinc) RNAs. Using highly quantitative FANTOM5 CAGE dataset, we show that these RNAs could be grouped into 1542 novel human genes based on analysis of insulators that we show here indeed function as genomic barrier elements. We show that vlincRNAs genes likely function in cis to activate nearby genes. This effect while most pronounced in closely spaced vlincRNA–gene pairs can be detected over relatively large genomic distances. Furthermore, we identified 101 vlincRNA genes likely involved in early embryogenesis based on patterns of their expression and regulation. We also found another 109 such genes potentially involved in cellular functions also happening at early stages of development such as proliferation, migration and apoptosis. Overall, we show that Systems Biology-based methods have great promise for functional annotation of non-coding RNAs. PMID:27001520

Biological Perspectives of Delayed Fracture Healing

PubMed Central

Hankenson, KD; Zmmerman, G; Marcucio, R

2015-01-01

Fracture healing is a complex biological process that requires interaction among a series of different cell types. Maintaining the appropriate temporal progression and spatial pattern is essential to achieve robust healing. We can temporally assess the biological phases via gene expression, protein analysis, histologically, or non-invasively using biomarkers as well as imaging techniques. However, determining what leads to normal verses abnormal healing is more challenging. Since the ultimate outcome of the process of fracture healing is to restore the original functions of bone, assessment of fracture healing should include not only monitoring the restoration of structure and mechanical function, but also an evaluation of the restoration of normal bone biology. Currently very few non-invasive measures of the biology of healing exist; however, recent studies that have correlated non-invasive measures with fracture healing outcome in humans have shown that serum TGFbeta1 levels appear to be an indicator of healing vs non-healing. In the future, developing additional serum measures to assess biological healing will improve the reliability and permit us to assess stages of fracture healing. Additionally, new functional imaging technologies could prove useful for better understanding both normal fracture healing and predicting dysfunctional healing in human patients. PMID:24857030

Chromatin Computation

PubMed Central

Bryant, Barbara

2012-01-01

In living cells, DNA is packaged along with protein and RNA into chromatin. Chemical modifications to nucleotides and histone proteins are added, removed and recognized by multi-functional molecular complexes. Here I define a new computational model, in which chromatin modifications are information units that can be written onto a one-dimensional string of nucleosomes, analogous to the symbols written onto cells of a Turing machine tape, and chromatin-modifying complexes are modeled as read-write rules that operate on a finite set of adjacent nucleosomes. I illustrate the use of this “chromatin computer” to solve an instance of the Hamiltonian path problem. I prove that chromatin computers are computationally universal – and therefore more powerful than the logic circuits often used to model transcription factor control of gene expression. Features of biological chromatin provide a rich instruction set for efficient computation of nontrivial algorithms in biological time scales. Modeling chromatin as a computer shifts how we think about chromatin function, suggests new approaches to medical intervention, and lays the groundwork for the engineering of a new class of biological computing machines. PMID:22567109

Predicting overlapping protein complexes from weighted protein interaction graphs by gradually expanding dense neighborhoods.

PubMed

Dimitrakopoulos, Christos; Theofilatos, Konstantinos; Pegkas, Andreas; Likothanassis, Spiros; Mavroudi, Seferina

2016-07-01

Proteins are vital biological molecules driving many fundamental cellular processes. They rarely act alone, but form interacting groups called protein complexes. The study of protein complexes is a key goal in systems biology. Recently, large protein-protein interaction (PPI) datasets have been published and a plethora of computational methods that provide new ideas for the prediction of protein complexes have been implemented. However, most of the methods suffer from two major limitations: First, they do not account for proteins participating in multiple functions and second, they are unable to handle weighted PPI graphs. Moreover, the problem remains open as existing algorithms and tools are insufficient in terms of predictive metrics. In the present paper, we propose gradually expanding neighborhoods with adjustment (GENA), a new algorithm that gradually expands neighborhoods in a graph starting from highly informative "seed" nodes. GENA considers proteins as multifunctional molecules allowing them to participate in more than one protein complex. In addition, GENA accepts weighted PPI graphs by using a weighted evaluation function for each cluster. In experiments with datasets from Saccharomyces cerevisiae and human, GENA outperformed Markov clustering, restricted neighborhood search and clustering with overlapping neighborhood expansion, three state-of-the-art methods for computationally predicting protein complexes. Seven PPI networks and seven evaluation datasets were used in total. GENA outperformed existing methods in 16 out of 18 experiments achieving an average improvement of 5.5% when the maximum matching ratio metric was used. Our method was able to discover functionally homogeneous protein clusters and uncover important network modules in a Parkinson expression dataset. When used on the human networks, around 47% of the detected clusters were enriched in gene ontology (GO) terms with depth higher than five in the GO hierarchy. In the present manuscript, we introduce a new method for the computational prediction of protein complexes by making the realistic assumption that proteins participate in multiple protein complexes and cellular functions. Our method can detect accurate and functionally homogeneous clusters. Copyright © 2016 Elsevier B.V. All rights reserved.

Embodying Markov blankets. Comment on "Answering Schrödinger's question: A free-energy formulation" by Maxwell James Désormeau Ramstead et al.

NASA Astrophysics Data System (ADS)

Pezzulo, Giovanni; Levin, Michael

2018-03-01

The free-energy principle (FEP) has been initially proposed as a theory of brain structure and function [1], but its scope is rapidly extending to explain biological phenomena at multiple levels of complexity, from simple life forms and their morphology [2] to complex societal and cultural dynamics [3].

DNA in a Tunnel: A Comfy Spot for Recognition - or -The Structure of BsoBI Complexed with DNA. What can we Learn about Function via Structure Determination and how can this be Applied to Bone or Muscle Biology?

NASA Technical Reports Server (NTRS)

vanderWoerd, Mark

2004-01-01

The structure and function of a biologically active molecule are related. To understand its function, it is necessary (but not always sufficient) to know the structure of the molecule. There are many ways of relating the molecular function with the structure. Mutation analysis can identify pertinent amino acids of an enzyme, or alternatively structure comparison of the of two similar molecules with different function may lead to understanding which parts are responsible for a functional aspect, or a series of "structural cartoons" - enzyme structure, enzyme plus substrate, enzyme with transition state analog, and enzyme with product - may give insight in the function of a molecule. As an example we will discuss the structure and function of the restriction enzyme BsoBI from Bacillus stearothemzophilus in complex with its cognate DNA. The enzyme forms a unique complex with DNA in that it completely encircles the DNA. The structure reveals the enzyme-DNA contacts, how the DNA is distorted compared with the canonical forms, and elegantly shows how two distinct DNA sequences can be recognized with the same efficiency. Based on the structure we may also propose a hypothesis how the enzymatic mechanism works. The knowledge gained thru studies such as this one can be used to alter the function by changing the molecular structure. Usually this is done by design of inhibitors specifically active against and fitting into an active site of the enzyme of choice. In the case of BsoBI one of the objectives of the study was to alter the enzyme specificity. In bone biology there are many candidates available for molecular study in order to explain, alter, or (temporarily) suspend activity. For example, the understanding of a pathway that negatively regulates bone formation may be a good target for drug design to stimulate bone formation and have good potential as the basis for new countermeasures against bone loss. In principle the same approach may aid muscle atrophy, radiation damage, immune response changes and other risks identified for long-duration Space travel.

Structural studies of P-type ATPase–ligand complexes using an X-ray free-electron laser

DOE PAGES

Bublitz, Maike; Nass, Karol; Drachmann, Nikolaj D.; ...

2015-06-11

Membrane proteins are key players in biological systems, mediating signalling events and the specific transport ofe.g.ions and metabolites. Consequently, membrane proteins are targeted by a large number of currently approved drugs. Understanding their functions and molecular mechanisms is greatly dependent on structural information, not least on complexes with functionally or medically important ligands. Structure determination, however, is hampered by the difficulty of obtaining well diffracting, macroscopic crystals. Here, the feasibility of X-ray free-electron-laser-based serial femtosecond crystallography (SFX) for the structure determination of membrane protein–ligand complexes using microcrystals of various native-source and recombinant P-type ATPase complexes is demonstrated. The data revealmore » the binding sites of a variety of ligands, including lipids and inhibitors such as the hallmark P-type ATPase inhibitor orthovanadate. By analyzing the resolution dependence of ligand densities and overall model qualities, SFX data quality metrics as well as suitable refinement procedures are discussed. Even at relatively low resolution and multiplicity, the identification of ligands can be demonstrated. This makes SFX a useful tool for ligand screening and thus for unravelling the molecular mechanisms of biologically active proteins.« less

Bioinformatics of cardiovascular miRNA biology.

PubMed

Kunz, Meik; Xiao, Ke; Liang, Chunguang; Viereck, Janika; Pachel, Christina; Frantz, Stefan; Thum, Thomas; Dandekar, Thomas

2015-12-01

MicroRNAs (miRNAs) are small ~22 nucleotide non-coding RNAs and are highly conserved among species. Moreover, miRNAs regulate gene expression of a large number of genes associated with important biological functions and signaling pathways. Recently, several miRNAs have been found to be associated with cardiovascular diseases. Thus, investigating the complex regulatory effect of miRNAs may lead to a better understanding of their functional role in the heart. To achieve this, bioinformatics approaches have to be coupled with validation and screening experiments to understand the complex interactions of miRNAs with the genome. This will boost the subsequent development of diagnostic markers and our understanding of the physiological and therapeutic role of miRNAs in cardiac remodeling. In this review, we focus on and explain different bioinformatics strategies and algorithms for the identification and analysis of miRNAs and their regulatory elements to better understand cardiac miRNA biology. Starting with the biogenesis of miRNAs, we present approaches such as LocARNA and miRBase for combining sequence and structure analysis including phylogenetic comparisons as well as detailed analysis of RNA folding patterns, functional target prediction, signaling pathway as well as functional analysis. We also show how far bioinformatics helps to tackle the unprecedented level of complexity and systemic effects by miRNA, underlining the strong therapeutic potential of miRNA and miRNA target structures in cardiovascular disease. In addition, we discuss drawbacks and limitations of bioinformatics algorithms and the necessity of experimental approaches for miRNA target identification. This article is part of a Special Issue entitled 'Non-coding RNAs'. Copyright © 2014 Elsevier Ltd. All rights reserved.

Conferring biological activity to native spider silk: A biofunctionalized protein-based microfiber.

PubMed

Wu, Hsuan-Chen; Quan, David N; Tsao, Chen-Yu; Liu, Yi; Terrell, Jessica L; Luo, Xiaolong; Yang, Jen-Chang; Payne, Gregory F; Bentley, William E

2017-01-01

Spider silk is an extraordinary material with physical properties comparable to the best scaffolding/structural materials, and as a fiber it can be manipulated with ease into a variety of configurations. Our work here demonstrates that natural spider silk fibers can also be used to organize biological components on and in devices through rapid and simple means. Micron scale spider silk fibers (5-10 μm in diameter) were surface modified with a variety of biological entities engineered with pentaglutamine tags via microbial transglutaminase (mTG). Enzymes, enzyme pathways, antibodies, and fluorescent proteins were all assembled onto spider silk fibers using this biomolecular engineering/biofabrication process. Additionally, arrangement of biofunctionalized fiber should in of itself generate a secondary level of biomolecular organization. Toward this end, as proofs of principle, spatially defined arrangement of biofunctionalized spider silk fiber was shown to generate effects specific to silk position in two cases. In one instance, arrangement perpendicular to a flow produced selective head and neck carcinoma cell capture on silk with antibodies complexed to conjugated protein G. In a second scenario, asymmetric bacterial chemotaxis arose from asymmetric conjugation of enzymes to arranged silk. Overall, the biofabrication processes used here were rapid, required no complex chemistries, were biologically benign, and also the resulting engineered silk microfibers were flexible, readily manipulated and functionally active. Deployed here in microfluidic environments, biofunctional spider silk fiber provides a means to convey complex biological functions over a range of scales, further extending its potential as a biomaterial in biotechnological settings. Biotechnol. Bioeng. 2017;114: 83-95. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Multidimensional approaches for studying plant defence against insects: from ecology to omics and synthetic biology.

PubMed

Barah, Pankaj; Bones, Atle M

2015-02-01

The biggest challenge for modern biology is to integrate multidisciplinary approaches towards understanding the organizational and functional complexity of biological systems at different hierarchies, starting from the subcellular molecular mechanisms (microscopic) to the functional interactions of ecological communities (macroscopic). The plant-insect interaction is a good model for this purpose with the availability of an enormous amount of information at the molecular and the ecosystem levels. Changing global climatic conditions are abruptly resetting plant-insect interactions. Integration of discretely located heterogeneous information from the ecosystem to genes and pathways will be an advantage to understand the complexity of plant-insect interactions. This review will present the recent developments in omics-based high-throughput experimental approaches, with particular emphasis on studying plant defence responses against insect attack. The review highlights the importance of using integrative systems approaches to study plant-insect interactions from the macroscopic to the microscopic level. We analyse the current efforts in generating, integrating and modelling multiomics data to understand plant-insect interaction at a systems level. As a future prospect, we highlight the growing interest in utilizing the synthetic biology platform for engineering insect-resistant plants. © The Author 2014. Published by Oxford University Press on behalf of the Society for Experimental Biology. All rights reserved. For permissions, please email: journals.permissions@oup.com.

A pathway-based network analysis of hypertension-related genes

NASA Astrophysics Data System (ADS)

Wang, Huan; Hu, Jing-Bo; Xu, Chuan-Yun; Zhang, De-Hai; Yan, Qian; Xu, Ming; Cao, Ke-Fei; Zhang, Xu-Sheng

2016-02-01

Complex network approach has become an effective way to describe interrelationships among large amounts of biological data, which is especially useful in finding core functions and global behavior of biological systems. Hypertension is a complex disease caused by many reasons including genetic, physiological, psychological and even social factors. In this paper, based on the information of biological pathways, we construct a network model of hypertension-related genes of the salt-sensitive rat to explore the interrelationship between genes. Statistical and topological characteristics show that the network has the small-world but not scale-free property, and exhibits a modular structure, revealing compact and complex connections among these genes. By the threshold of integrated centrality larger than 0.71, seven key hub genes are found: Jun, Rps6kb1, Cycs, Creb312, Cdk4, Actg1 and RT1-Da. These genes should play an important role in hypertension, suggesting that the treatment of hypertension should focus on the combination of drugs on multiple genes.

Functional tissue engineering of tendon: Establishing biological success criteria for improving tendon repair.

PubMed

Breidenbach, Andrew P; Gilday, Steven D; Lalley, Andrea L; Dyment, Nathaniel A; Gooch, Cynthia; Shearn, Jason T; Butler, David L

2014-06-27

Improving tendon repair using Functional Tissue Engineering (FTE) principles has been the focus of our laboratory over the last decade. Although our primary goals were initially focused only on mechanical outcomes, we are now carefully assessing the biological properties of our tissue-engineered tendon repairs so as to link biological influences with mechanics. However, given the complexities of tendon development and healing, it remains challenging to determine which aspects of tendon biology are the most important to focus on in the context of tissue engineering. To address this problem, we have formalized a strategy to identify, prioritize, and evaluate potential biological success criteria for tendon repair. We have defined numerous biological properties of normal tendon relative to cellular phenotype, extracellular matrix and tissue ultra-structure that we would like to reproduce in our tissue-engineered repairs and prioritized these biological criteria by examining their relative importance during both normal development and natural tendon healing. Here, we propose three specific biological criteria which we believe are essential for normal tendon function: (1) scleraxis-expressing cells; (2) well-organized and axially-aligned collagen fibrils having bimodal diameter distribution; and (3) a specialized tendon-to-bone insertion site. Moving forward, these biological success criteria will be used in conjunction with our already established mechanical success criteria to evaluate the effectiveness of our tissue-engineered tendon repairs. © 2013 Published by Elsevier Ltd.

A global interaction network maps a wiring diagram of cellular function

PubMed Central

Costanzo, Michael; VanderSluis, Benjamin; Koch, Elizabeth N.; Baryshnikova, Anastasia; Pons, Carles; Tan, Guihong; Wang, Wen; Usaj, Matej; Hanchard, Julia; Lee, Susan D.; Pelechano, Vicent; Styles, Erin B.; Billmann, Maximilian; van Leeuwen, Jolanda; van Dyk, Nydia; Lin, Zhen-Yuan; Kuzmin, Elena; Nelson, Justin; Piotrowski, Jeff S.; Srikumar, Tharan; Bahr, Sondra; Chen, Yiqun; Deshpande, Raamesh; Kurat, Christoph F.; Li, Sheena C.; Li, Zhijian; Usaj, Mojca Mattiazzi; Okada, Hiroki; Pascoe, Natasha; Luis, Bryan-Joseph San; Sharifpoor, Sara; Shuteriqi, Emira; Simpkins, Scott W.; Snider, Jamie; Suresh, Harsha Garadi; Tan, Yizhao; Zhu, Hongwei; Malod-Dognin, Noel; Janjic, Vuk; Przulj, Natasa; Troyanskaya, Olga G.; Stagljar, Igor; Xia, Tian; Ohya, Yoshikazu; Gingras, Anne-Claude; Raught, Brian; Boutros, Michael; Steinmetz, Lars M.; Moore, Claire L.; Rosebrock, Adam P.; Caudy, Amy A.; Myers, Chad L.; Andrews, Brenda; Boone, Charles

2017-01-01

We generated a global genetic interaction network for Saccharomyces cerevisiae, constructing over 23 million double mutants, identifying ~550,000 negative and ~350,000 positive genetic interactions. This comprehensive network maps genetic interactions for essential gene pairs, highlighting essential genes as densely connected hubs. Genetic interaction profiles enabled assembly of a hierarchical model of cell function, including modules corresponding to protein complexes and pathways, biological processes, and cellular compartments. Negative interactions connected functionally related genes, mapped core bioprocesses, and identified pleiotropic genes, whereas positive interactions often mapped general regulatory connections among gene pairs, rather than shared functionality. The global network illustrates how coherent sets of genetic interactions connect protein complex and pathway modules to map a functional wiring diagram of the cell. PMID:27708008

The human mouth: oral functions in a social complexity perspective.

PubMed

Eriksen, Harald M; Dimitrov, Vladimir

2003-06-01

In the dental and medical literature, the mouth and oral functions are usually presented in a biomedical context. However, there may be a need for a broader perspective if we are to appreciate the importance of the human mouth as an organ with diverse functions. The paradigm of complexity appears to be of relevance in our understanding the social and psychological characteristics of the human mouth in addition to its biological functions. Examples such as the pleasures of taste, social aspects of eating, the importance of linguistics and communication are illustrations of some of the social and psychological aspects of oral functions. Professional knowledge related to such issues is important in our understanding the patient's priorities and in performing the relevant diagnosis and treatment planning.

MultitaskProtDB: a database of multitasking proteins

PubMed Central

Hernández, Sergio; Ferragut, Gabriela; Amela, Isaac; Perez-Pons, JosepAntoni; Piñol, Jaume; Mozo-Villarias, Angel; Cedano, Juan; Querol, Enrique

2014-01-01

We have compiled MultitaskProtDB, available online at http://wallace.uab.es/multitask, to provide a repository where the many multitasking proteins found in the literature can be stored. Multitasking or moonlighting is the capability of some proteins to execute two or more biological functions. Usually, multitasking proteins are experimentally revealed by serendipity. This ability of proteins to perform multitasking functions helps us to understand one of the ways used by cells to perform many complex functions with a limited number of genes. Even so, the study of this phenomenon is complex because, among other things, there is no database of moonlighting proteins. The existence of such a tool facilitates the collection and dissemination of these important data. This work reports the database, MultitaskProtDB, which is designed as a friendly user web page containing >288 multitasking proteins with their NCBI and UniProt accession numbers, canonical and additional biological functions, monomeric/oligomeric states, PDB codes when available and bibliographic references. This database also serves to gain insight into some characteristics of multitasking proteins such as frequencies of the different pairs of functions, phylogenetic conservation and so forth. PMID:24253302

Gene therapy restores auditory and vestibular function in a mouse model of Usher syndrome type 1c.

PubMed

Pan, Bifeng; Askew, Charles; Galvin, Alice; Heman-Ackah, Selena; Asai, Yukako; Indzhykulian, Artur A; Jodelka, Francine M; Hastings, Michelle L; Lentz, Jennifer J; Vandenberghe, Luk H; Holt, Jeffrey R; Géléoc, Gwenaëlle S

2017-03-01

Because there are currently no biological treatments for hearing loss, we sought to advance gene therapy approaches to treat genetic deafness. We focused on Usher syndrome, a devastating genetic disorder that causes blindness, balance disorders and profound deafness, and studied a knock-in mouse model, Ush1c c.216G>A, for Usher syndrome type IC (USH1C). As restoration of complex auditory and balance function is likely to require gene delivery systems that target auditory and vestibular sensory cells with high efficiency, we delivered wild-type Ush1c into the inner ear of Ush1c c.216G>A mice using a synthetic adeno-associated viral vector, Anc80L65, shown to transduce 80-90% of sensory hair cells. We demonstrate recovery of gene and protein expression, restoration of sensory cell function, rescue of complex auditory function and recovery of hearing and balance behavior to near wild-type levels. The data represent unprecedented recovery of inner ear function and suggest that biological therapies to treat deafness may be suitable for translation to humans with genetic inner ear disorders.

Integrated micro/nanoengineered functional biomaterials for cell mechanics and mechanobiology: a materials perspective.

PubMed

Shao, Yue; Fu, Jianping

2014-03-12

The rapid development of micro/nanoengineered functional biomaterials in the last two decades has empowered materials scientists and bioengineers to precisely control different aspects of the in vitro cell microenvironment. Following a philosophy of reductionism, many studies using synthetic functional biomaterials have revealed instructive roles of individual extracellular biophysical and biochemical cues in regulating cellular behaviors. Development of integrated micro/nanoengineered functional biomaterials to study complex and emergent biological phenomena has also thrived rapidly in recent years, revealing adaptive and integrated cellular behaviors closely relevant to human physiological and pathological conditions. Working at the interface between materials science and engineering, biology, and medicine, we are now at the beginning of a great exploration using micro/nanoengineered functional biomaterials for both fundamental biology study and clinical and biomedical applications such as regenerative medicine and drug screening. In this review, an overview of state of the art micro/nanoengineered functional biomaterials that can control precisely individual aspects of cell-microenvironment interactions is presented and they are highlighted them as well-controlled platforms for mechanistic studies of mechano-sensitive and -responsive cellular behaviors and integrative biology research. The recent exciting trend where micro/nanoengineered biomaterials are integrated into miniaturized biological and biomimetic systems for dynamic multiparametric microenvironmental control of emergent and integrated cellular behaviors is also discussed. The impact of integrated micro/nanoengineered functional biomaterials for future in vitro studies of regenerative medicine, cell biology, as well as human development and disease models are discussed. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Functional characterization of EZH2β reveals the increased complexity of EZH2 isoforms involved in the regulation of mammalian gene expression

PubMed Central

2013-01-01

Background Histone methyltransferase enhancer of zeste homologue 2 (EZH2) forms an obligate repressive complex with suppressor of zeste 12 and embryonic ectoderm development, which is thought, along with EZH1, to be primarily responsible for mediating Polycomb-dependent gene silencing. Polycomb-mediated repression influences gene expression across the entire gamut of biological processes, including development, differentiation and cellular proliferation. Deregulation of EZH2 expression is implicated in numerous complex human diseases. To date, most EZH2-mediated function has been primarily ascribed to a single protein product of the EZH2 locus. Results We report that the EZH2 locus undergoes alternative splicing to yield at least two structurally and functionally distinct EZH2 methyltransferases. The longest protein encoded by this locus is the conventional enzyme, which we refer to as EZH2α, whereas EZH2β, characterized here, represents a novel isoform. We find that EZH2β localizes to the cell nucleus, complexes with embryonic ectoderm development and suppressor of zeste 12, trimethylates histone 3 at lysine 27, and mediates silencing of target promoters. At the cell biological level, we find that increased EZH2β induces cell proliferation, demonstrating that this protein is functional in the regulation of processes previously attributed to EZH2α. Biochemically, through the use of genome-wide expression profiling, we demonstrate that EZH2β governs a pattern of gene repression that is often ontologically redundant from that of EZH2α, but also divergent for a wide variety of specific target genes. Conclusions Combined, these results demonstrate that an expanded repertoire of EZH2 writers can modulate histone code instruction during histone 3 lysine 27-mediated gene silencing. These data support the notion that the regulation of EZH2-mediated gene silencing is more complex than previously anticipated and should guide the design and interpretation of future studies aimed at understanding the biochemical and biological roles of this important family of epigenomic regulators. PMID:23448518

11th IUBMB Focused Meeting on the Aminoacyl-tRNA Synthetases: Sailing a New Sea of Complex Functions in Human Biology and Disease.

PubMed

Francklyn, Christopher; Roy, Herve; Alexander, Rebecca

2018-05-01

The 11th IUBMB Focused Meeting on Aminoacyl-tRNA Synthetases was held in Clearwater Beach, Florida from 29 October⁻2 November 2017, with the aim of presenting the latest research on these enzymes and promoting interchange among aminoacyl-tRNA synthetase (ARS) researchers. Topics covered in the meeting included many areas of investigation, including ARS evolution, mechanism, editing functions, biology in prokaryotic and eukaryotic cells and their organelles, their roles in human diseases, and their application to problems in emerging areas of synthetic biology. In this report, we provide a summary of the major themes of the meeting, citing contributions from the oral presentations in the meeting.

Scaffold Diversity Synthesis Delivers Complex, Structurally, and Functionally Distinct Tetracyclic Benzopyrones

PubMed Central

Sankar, Muthukumar G.; Roy, Sayantani; Tran, Tuyen Thi Ngoc; Wittstein, Kathrin; Bauer, Jonathan O.; Strohmann, Carsten; Ziegler, Slava

2018-01-01

Abstract Complexity‐generating chemical transformations that afford novel molecular scaffolds enriched in sp 3 character are highly desired. Here, we present a highly stereoselective scaffold diversity synthesis approach that utilizes cascade double‐annulation reactions of diverse pairs of zwitterionic and non‐zwitterionic partners with 3‐formylchromones to generate highly complex tetracyclic benzopyrones. Each pair of annulation partners adds to the common chroman‐4‐one scaffold to build two new rings, supporting up to four contiguous chiral centers that include an all‐carbon quaternary center. Differently ring‐fused benzopyrones display different biological activities, thus demonstrating their immense potential in medicinal chemistry and chemical biology research. PMID:29721402

A simple formula for the effective complex conductivity of periodic fibrous composites with interfacial impedance and applications to biological tissues

NASA Astrophysics Data System (ADS)

Bisegna, Paolo; Caselli, Federica

2008-06-01

This paper presents a simple analytical expression for the effective complex conductivity of a periodic hexagonal arrangement of conductive circular cylinders embedded in a conductive matrix, with interfaces exhibiting a capacitive impedance. This composite material may be regarded as an idealized model of a biological tissue comprising tubular cells, such as skeletal muscle. The asymptotic homogenization method is adopted, and the corresponding local problem is solved by resorting to Weierstrass elliptic functions. The effectiveness of the present analytical result is proved by convergence analysis and comparison with finite-element solutions and existing models.

Evolution of an ancient protein function involved in organized multicellularity in animals.

PubMed

Anderson, Douglas P; Whitney, Dustin S; Hanson-Smith, Victor; Woznica, Arielle; Campodonico-Burnett, William; Volkman, Brian F; King, Nicole; Thornton, Joseph W; Prehoda, Kenneth E

2016-01-07

To form and maintain organized tissues, multicellular organisms orient their mitotic spindles relative to neighboring cells. A molecular complex scaffolded by the GK protein-interaction domain (GKPID) mediates spindle orientation in diverse animal taxa by linking microtubule motor proteins to a marker protein on the cell cortex localized by external cues. Here we illuminate how this complex evolved and commandeered control of spindle orientation from a more ancient mechanism. The complex was assembled through a series of molecular exploitation events, one of which - the evolution of GKPID's capacity to bind the cortical marker protein - can be recapitulated by reintroducing a single historical substitution into the reconstructed ancestral GKPID. This change revealed and repurposed an ancient molecular surface that previously had a radically different function. We show how the physical simplicity of this binding interface enabled the evolution of a new protein function now essential to the biological complexity of many animals.

Intermolecular hydrogen bonds in hetero-complexes of biologically active aromatic molecules probed by the methods of vibrational spectroscopy

NASA Astrophysics Data System (ADS)

Semenov, M. A.; Blyzniuk, Iu. N.; Bolbukh, T. V.; Shestopalova, A. V.; Evstigneev, M. P.; Maleev, V. Ya.

2012-09-01

By the methods of vibrational spectroscopy (Infrared and Raman) the investigation of the hetero-association of biologically active aromatic compounds: flavin-mononucleotide (FMN), ethidium bromide (EB) and proflavine (PRF) was performed in aqueous solutions. It was shown that between the functional groups (Cdbnd O and NH2) the intermolecular hydrogen bonds are formed in the hetero-complexes FMN-EB and FMN-PRF, additionally stabilizing these structures. An estimation of the enthalpy of Н-bonding obtained from experimental shifts of carbonyl vibrational frequencies has shown that the H-bonds do not dominate in the magnitude of experimentally measured total enthalpy of the hetero-association reactions. The main stabilization is likely due to intermolecular interactions of the molecules in these complexes and their interaction with water environment.

Advanced techniques in placental biology -- workshop report.

PubMed

Nelson, D M; Sadovsky, Y; Robinson, J M; Croy, B A; Rice, G; Kniss, D A

2006-04-01

Major advances in placental biology have been realized as new technologies have been developed and existing methods have been refined in many areas of biological research. Classical anatomy and whole-organ physiology tools once used to analyze placental structure and function have been supplanted by more sophisticated techniques adapted from molecular biology, proteomics, and computational biology and bioinformatics. In addition, significant refinements in morphological study of the placenta and its constituent cell types have improved our ability to assess form and function in highly integrated manner. To offer an overview of modern technologies used by investigators to study the placenta, this workshop: Advanced techniques in placental biology, assembled experts who discussed fundamental principles and real time examples of four separate methodologies. Y. Sadovsky presented the principles of microRNA function as an endogenous mechanism of gene regulation. J. Robinson demonstrated the utility of correlative microscopy in which light-level and transmission electron microscopy are combined to provide cellular and subcellular views of placental cells. A. Croy provided a lecture on the use of microdissection techniques which are invaluable for isolating very small subsets of cell types for molecular analysis. Finally, G. Rice presented an overview methods on profiling of complex protein mixtures within tissue and/or fluid samples that, when refined, will offer databases that will underpin a systems approach to modern trophoblast biology.

Development of hydrogels for regenerative engineering.

PubMed

Guan, Xiaofei; Avci-Adali, Meltem; Alarçin, Emine; Cheng, Hao; Kashaf, Sara Saheb; Li, Yuxiao; Chawla, Aditya; Jang, Hae Lin; Khademhosseini, Ali

2017-05-01

The aim of regenerative engineering is to restore complex tissues and biological systems through convergence in the fields of advanced biomaterials, stem cell science, and developmental biology. Hydrogels are one of the most attractive biomaterials for regenerative engineering, since they can be engineered into tissue mimetic 3D scaffolds to support cell growth due to their similarity to native extracellular matrix. Advanced nano- and micro-technologies have dramatically increased the ability to control properties and functionalities of hydrogel materials by facilitating biomimetic fabrication of more sophisticated compositions and architectures, thus extending our understanding of cell-matrix interactions at the nanoscale. With this perspective, this review discusses the most commonly used hydrogel materials and their fabrication strategies for regenerative engineering. We highlight the physical, chemical, and functional modulation of hydrogels to design and engineer biomimetic tissues based on recent achievements in nano- and micro-technologies. In addition, current hydrogel-based regenerative engineering strategies for treating multiple tissues, such as musculoskeletal, nervous and cardiac tissue, are also covered in this review. The interaction of multiple disciplines including materials science, cell biology, and chemistry, will further play an important role in the design of functional hydrogels for the regeneration of complex tissues. Copyright © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

ADAM: analysis of discrete models of biological systems using computer algebra.

PubMed

Hinkelmann, Franziska; Brandon, Madison; Guang, Bonny; McNeill, Rustin; Blekherman, Grigoriy; Veliz-Cuba, Alan; Laubenbacher, Reinhard

2011-07-20

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. 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. 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.

A biomimetic colorimetric logic gate system based on multi-functional peptide-mediated gold nanoparticle assembly.

PubMed

Li, Yong; Li, Wang; He, Kai-Yu; Li, Pei; Huang, Yan; Nie, Zhou; Yao, Shou-Zhuo

2016-04-28

In natural biological systems, proteins exploit various functional peptide motifs to exert target response and activity switch, providing a functional and logic basis for complex cellular activities. Building biomimetic peptide-based bio-logic systems is highly intriguing but remains relatively unexplored due to limited logic recognition elements and complex signal outputs. In this proof-of-principle work, we attempted to address these problems by utilizing multi-functional peptide probes and the peptide-mediated nanoparticle assembly system. Here, the rationally designed peptide probes function as the dual-target responsive element specifically responsive to metal ions and enzymes as well as the mediator regulating the assembly of gold nanoparticles (AuNPs). Taking advantage of Zn2+ ions and chymotrypsin as the model inputs of metal ions and enzymes, respectively, we constructed the peptide logic system computed by the multi-functional peptide probes and outputted by the readable colour change of AuNPs. In this way, the representative binary basic logic gates (AND, OR, INHIBIT, NAND, IMPLICATION) have been achieved by delicately coding the peptide sequence, demonstrating the versatility of our logic system. Additionally, we demonstrated that the three-input combinational logic gate (INHIBIT-OR) could also be successfully integrated and applied as a multi-tasking biosensor for colorimetric detection of dual targets. This nanoparticle-based peptide logic system presents a valid strategy to illustrate peptide information processing and provides a practical platform for executing peptide computing or peptide-related multiplexing sensing, implying that the controllable nanomaterial assembly is a promising and potent methodology for the advancement of biomimetic bio-logic computation.

A second RNA-binding protein is essential for ethanol tolerance provided by the bacterial OLE ribonucleoprotein complex.

PubMed

Harris, Kimberly A; Zhou, Zhiyuan; Peters, Michelle L; Wilkins, Sarah G; Breaker, Ronald R

2018-06-18

OLE (ornate, large, extremophilic) RNAs comprise a class of structured noncoding RNAs (ncRNAs) found in many extremophilic bacteria species. OLE RNAs constitute one of the longest and most widespread bacterial ncRNA classes whose major biochemical function remains unknown. In the Gram-positive alkaliphile Bacillus halodurans , OLE RNA is abundant, and localizes to the cell membrane by association with the transmembrane OLE-associated protein called OapA (formerly OAP). These characteristics, along with the well-conserved sequence and structural features of OLE RNAs, suggest that the OLE ribonucleoprotein (RNP) complex performs important biological functions. B. halodurans strains lacking OLE RNA ( ∆ole ) or OapA ( ∆oapA ) are less tolerant of cold (20 °C) and short-chain alcohols (e.g., ethanol). Here, we describe the effects of a mutant OapA (called PM1) that more strongly inhibits growth under cold or ethanol stress compared with strains lacking the oapA gene, even when wild-type OapA is present. This dominant-negative effect of PM1 is reversed by mutations that render OLE RNA nonfunctional. This finding demonstrates that the deleterious PM1 phenotype requires an intact RNP complex, and suggests that the complex has one or more additional undiscovered components. A genetic screen uncovered PM1 phenotype suppressor mutations in the ybzG gene, which codes for a putative RNA-binding protein of unknown biological function. We observe that YbzG protein (also called OapB) selectively binds OLE RNA in vitro, whereas a mutant version of the protein is not observed to bind OLE RNA. Thus, YbzG/OapB is an important component of the functional OLE RNP complex in B. halodurans .

Conformational Transitions in Molecular Systems

NASA Astrophysics Data System (ADS)

Bachmann, M.; Janke, W.

2008-11-01

Proteins are the "work horses" in biological systems. In almost all functions specific proteins are involved. They control molecular transport processes, stabilize the cell structure, enzymatically catalyze chemical reactions; others act as molecular motors in the complex machinery of molecular synthetization processes. Due to their significance, misfolds and malfunctions of proteins typically entail disastrous diseases, such as Alzheimer's disease and bovine spongiform encephalopathy (BSE). Therefore, the understanding of the trinity of amino acid composition, geometric structure, and biological function is one of the most essential challenges for the natural sciences. Here, we glance at conformational transitions accompanying the structure formation in protein folding processes.

Reflecting on complexity of biological systems: Kant and beyond?

PubMed

Van de Vijver, Gertrudis; Van Speybroeck, Linda; Vandevyvere, Windy

2003-01-01

Living organisms are currently most often seen as complex dynamical systems that develop and evolve in relation to complex environments. Reflections on the meaning of the complex dynamical nature of living systems show an overwhelming multiplicity in approaches, descriptions, definitions and methodologies. Instead of sustaining an epistemic pluralism, which often functions as a philosophical armistice in which tolerance and so-called neutrality discharge proponents of the burden to clarify the sources and conditions of agreement and disagreement, this paper aims at analysing: (i) what has been Kant's original conceptualisation of living organisms as natural purposes; (ii) how the current perspectives are to be related to Kant's viewpoint; (iii) what are the main trends in current complexity thinking. One of the basic ideas is that the attention for structure and its epistemological consequences witness to a great extent of Kant's viewpoint, and that the idea of organisational stratification today constitutes a different breeding ground within which complexity issues are raised. The various approaches of complexity in biological systems are captured in terms of two different styles, universalism and (weak and strong) constructivism, between which hybrid forms exist.

The evolution of the natural killer complex; a comparison between mammals using new high-quality genome assemblies and targeted annotation

USDA-ARS?s Scientific Manuscript database

Natural killer (NK) cells are a diverse population of lymphocytes with a range of biological roles including essential immune functions. NK cell diversity is created by the differential expression of cell surface receptors which modulate activation and function, including multiple subfamilies of C-t...

Structure and Function of Wood

Treesearch

Alex C. Wiedenhoeft

2012-01-01

Wood is a complex biological structure, a composite of many cell types and chemistries acting together to serve the needs of living plant. Attempting to understand wood inthe context of wood technology, we have often overlooked the basic fact that wood evolved over the course of millions of years to serve three main functions in plants-conduction of water from the...

Video Views and Reviews: Neurulation and the Fashioning of the Vertebrate Central Nervous System

ERIC Educational Resources Information Center

Watters, Christopher

2006-01-01

The central nervous system (CNS) is the first adult organ system to appear during vertebrate development, and the process of its emergence is commonly called neurulation. Such biological "urgency" is perhaps not surprising given the structural and functional complexity of the CNS and the importance of neural function to adaptive behavior and…

Isothiocyanate-functionalized bifunctional chelates and fac-[MI(CO)3]+ (M = Re, 99mTc) complexes for targeting uPAR in prostate cancer

USDA-ARS?s Scientific Manuscript database

Developing strategies to rapidly incorporate the fac-[MI(CO)3]+ (M = Re, 99mTc) core into biological targeting vectors is a growing realm in radiopharmaceutical development. This work presents the preparation of a novel isothiocyanate-functionalized bifunctional chelate based on 2,2´-dipicolylamine ...

Molecular Mechanics and Dynamics Characterization of an "in silico" Mutated Protein: A Stand-Alone Lab Module or Support Activity for "in vivo" and "in vitro" Analyses of Targeted Proteins

ERIC Educational Resources Information Center

Chiang, Harry; Robinson, Lucy C.; Brame, Cynthia J.; Messina, Troy C.

2013-01-01

Over the past 20 years, the biological sciences have increasingly incorporated chemistry, physics, computer science, and mathematics to aid in the development and use of mathematical models. Such combined approaches have been used to address problems from protein structure-function relationships to the workings of complex biological systems.…

Modular biological function is most effectively captured by combining molecular interaction data types.

PubMed

Ames, Ryan M; Macpherson, Jamie I; Pinney, John W; Lovell, Simon C; Robertson, David L

2013-01-01

Large-scale molecular interaction data sets have the potential to provide a comprehensive, system-wide understanding of biological function. Although individual molecules can be promiscuous in terms of their contribution to function, molecular functions emerge from the specific interactions of molecules giving rise to modular organisation. As functions often derive from a range of mechanisms, we demonstrate that they are best studied using networks derived from different sources. Implementing a graph partitioning algorithm we identify subnetworks in yeast protein-protein interaction (PPI), genetic interaction and gene co-regulation networks. Among these subnetworks we identify cohesive subgraphs that we expect to represent functional modules in the different data types. We demonstrate significant overlap between the subgraphs generated from the different data types and show these overlaps can represent related functions as represented by the Gene Ontology (GO). Next, we investigate the correspondence between our subgraphs and the Gene Ontology. This revealed varying degrees of coverage of the biological process, molecular function and cellular component ontologies, dependent on the data type. For example, subgraphs from the PPI show enrichment for 84%, 58% and 93% of annotated GO terms, respectively. Integrating the interaction data into a combined network increases the coverage of GO. Furthermore, the different annotation types of GO are not predominantly associated with one of the interaction data types. Collectively our results demonstrate that successful capture of functional relationships by network data depends on both the specific biological function being characterised and the type of network data being used. We identify functions that require integrated information to be accurately represented, demonstrating the limitations of individual data types. Combining interaction subnetworks across data types is therefore essential for fully understanding the complex and emergent nature of biological function.

RNA structures as mediators of neurological diseases and as drug targets

PubMed Central

Bernat, Viachaslau; Disney, Matthew D.

2015-01-01

RNAs adopt diverse folded structures that are essential for function and thus play critical roles in cellular biology. A striking example of this is the ribosome, a complex, three-dimensionally folded macromolecular machine that orchestrates protein synthesis. Advances in RNA biochemistry, structural and molecular biology, and bioinformatics have revealed other non-coding RNAs whose functions are dictated by their structure. It is not surprising that aberrantly folded RNA structures contribute to disease. In this review, we provide a brief introduction into RNA structural biology and then describe how RNA structures function in cells and cause or contribute to neurological disease. Finally, we highlight successful applications of rational design principles to provide chemical probes and lead compounds targeting structured RNAs. Based on several examples of well-characterized RNA-driven neurological disorders, we demonstrate how designed small molecules can facilitate study of RNA dysfunction, elucidating previously unknown roles for RNA in disease, and provide lead therapeutics. PMID:26139368

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.

“Gestaltomics”: Systems Biology Schemes for the Study of Neuropsychiatric Diseases

PubMed Central

Gutierrez Najera, Nora A.; Resendis-Antonio, Osbaldo; Nicolini, Humberto

2017-01-01

The integration of different sources of biological information about what defines a behavioral phenotype is difficult to unify in an entity that reflects the arithmetic sum of its individual parts. In this sense, the challenge of Systems Biology for understanding the “psychiatric phenotype” is to provide an improved vision of the shape of the phenotype as it is visualized by “Gestalt” psychology, whose fundamental axiom is that the observed phenotype (behavior or mental disorder) will be the result of the integrative composition of every part. Therefore, we propose the term “Gestaltomics” as a term from Systems Biology to integrate data coming from different sources of information (such as the genome, transcriptome, proteome, epigenome, metabolome, phenome, and microbiome). In addition to this biological complexity, the mind is integrated through multiple brain functions that receive and process complex information through channels and perception networks (i.e., sight, ear, smell, memory, and attention) that in turn are programmed by genes and influenced by environmental processes (epigenetic). Today, the approach of medical research in human diseases is to isolate one disease for study; however, the presence of an additional disease (co-morbidity) or more than one disease (multimorbidity) adds complexity to the study of these conditions. This review will present the challenge of integrating psychiatric disorders at different levels of information (Gestaltomics). The implications of increasing the level of complexity, for example, studying the co-morbidity with another disease such as cancer, will also be discussed. PMID:28536537

Beyond the known functions of the CCR4-NOT complex in gene expression regulatory mechanisms: New structural insights to unravel CCR4-NOT mRNA processing machinery.

PubMed

Ukleja, Marta; Valpuesta, José María; Dziembowski, Andrzej; Cuellar, Jorge

2016-10-01

Large protein assemblies are usually the effectors of major cellular processes. The intricate cell homeostasis network is divided into numerous interconnected pathways, each controlled by a set of protein machines. One of these master regulators is the CCR4-NOT complex, which ultimately controls protein expression levels. This multisubunit complex assembles around a scaffold platform, which enables a wide variety of well-studied functions from mRNA synthesis to transcript decay, as well as other tasks still being identified. Solving the structure of the entire CCR4-NOT complex will help to define the distribution of its functions. The recently published three-dimensional reconstruction of the complex, in combination with the known crystal structures of some of the components, has begun to address this. Methodological improvements in structural biology, especially in cryoelectron microscopy, encourage further structural and protein-protein interaction studies, which will advance our comprehension of the gene expression machinery. © 2016 WILEY Periodicals, Inc.

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

A mass graph-based approach for the identification of modified proteoforms using top-down tandem mass spectra

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

Kou, Qiang; Wu, Si; Tolić, Nikola

Motivation: Although proteomics has rapidly developed in the past decade, researchers are still in the early stage of exploring the world of complex proteoforms, which are protein products with various primary structure alterations resulting from gene mutations, alternative splicing, post-translational modifications, and other biological processes. Proteoform identification is essential to mapping proteoforms to their biological functions as well as discovering novel proteoforms and new protein functions. Top-down mass spectrometry is the method of choice for identifying complex proteoforms because it provides a “bird’s eye view” of intact proteoforms. The combinatorial explosion of various alterations on a protein may result inmore » billions of possible proteoforms, making proteoform identification a challenging computational problem. Results: We propose a new data structure, called the mass graph, for efficient representation of proteoforms and design mass graph alignment algorithms. We developed TopMG, a mass graph-based software tool for proteoform identification by top-down mass spectrometry. Experiments on top-down mass spectrometry data sets showed that TopMG outperformed existing methods in identifying complex proteoforms.« less

Quantifying uncertainty in partially specified biological models: how can optimal control theory help us?

PubMed

Adamson, M W; Morozov, A Y; Kuzenkov, O A

2016-09-01

Mathematical models in biology are highly simplified representations of a complex underlying reality and there is always a high degree of uncertainty with regards to model function specification. This uncertainty becomes critical for models in which the use of different functions fitting the same dataset can yield substantially different predictions-a property known as structural sensitivity. Thus, even if the model is purely deterministic, then the uncertainty in the model functions carries through into uncertainty in model predictions, and new frameworks are required to tackle this fundamental problem. Here, we consider a framework that uses partially specified models in which some functions are not represented by a specific form. The main idea is to project infinite dimensional function space into a low-dimensional space taking into account biological constraints. The key question of how to carry out this projection has so far remained a serious mathematical challenge and hindered the use of partially specified models. Here, we propose and demonstrate a potentially powerful technique to perform such a projection by using optimal control theory to construct functions with the specified global properties. This approach opens up the prospect of a flexible and easy to use method to fulfil uncertainty analysis of biological models.

Genome-Wide Detection and Analysis of Multifunctional Genes

PubMed Central

Pritykin, Yuri; Ghersi, Dario; Singh, Mona

2015-01-01

Many genes can play a role in multiple biological processes or molecular functions. Identifying multifunctional genes at the genome-wide level and studying their properties can shed light upon the complexity of molecular events that underpin cellular functioning, thereby leading to a better understanding of the functional landscape of the cell. However, to date, genome-wide analysis of multifunctional genes (and the proteins they encode) has been limited. Here we introduce a computational approach that uses known functional annotations to extract genes playing a role in at least two distinct biological processes. We leverage functional genomics data sets for three organisms—H. sapiens, D. melanogaster, and S. cerevisiae—and show that, as compared to other annotated genes, genes involved in multiple biological processes possess distinct physicochemical properties, are more broadly expressed, tend to be more central in protein interaction networks, tend to be more evolutionarily conserved, and are more likely to be essential. We also find that multifunctional genes are significantly more likely to be involved in human disorders. These same features also hold when multifunctionality is defined with respect to molecular functions instead of biological processes. Our analysis uncovers key features about multifunctional genes, and is a step towards a better genome-wide understanding of gene multifunctionality. PMID:26436655

Quantitative genetic-interaction mapping in mammalian cells

PubMed Central

Roguev, Assen; Talbot, Dale; Negri, Gian Luca; Shales, Michael; Cagney, Gerard; Bandyopadhyay, Sourav; Panning, Barbara; Krogan, Nevan J

2013-01-01

Mapping genetic interactions (GIs) by simultaneously perturbing pairs of genes is a powerful tool for understanding complex biological phenomena. Here we describe an experimental platform for generating quantitative GI maps in mammalian cells using a combinatorial RNA interference strategy. We performed ~11,000 pairwise knockdowns in mouse fibroblasts, focusing on 130 factors involved in chromatin regulation to create a GI map. Comparison of the GI and protein-protein interaction (PPI) data revealed that pairs of genes exhibiting positive GIs and/or similar genetic profiles were predictive of the corresponding proteins being physically associated. The mammalian GI map identified pathways and complexes but also resolved functionally distinct submodules within larger protein complexes. By integrating GI and PPI data, we created a functional map of chromatin complexes in mouse fibroblasts, revealing that the PAF complex is a central player in the mammalian chromatin landscape. PMID:23407553

Plant Systems Biology at the Single-Cell Level.

PubMed

Libault, Marc; Pingault, Lise; Zogli, Prince; Schiefelbein, John

2017-11-01

Our understanding of plant biology is increasingly being built upon studies using 'omics and system biology approaches performed at the level of the entire plant, organ, or tissue. Although these approaches open new avenues to better understand plant biology, they suffer from the cellular complexity of the analyzed sample. Recent methodological advances now allow plant scientists to overcome this limitation and enable biological analyses of single-cells or single-cell-types. Coupled with the development of bioinformatics and functional genomics resources, these studies provide opportunities for high-resolution systems analyses of plant phenomena. In this review, we describe the recent advances, current challenges, and future directions in exploring the biology of single-cells and single-cell-types to enhance our understanding of plant biology as a system. Copyright © 2017 Elsevier Ltd. All rights reserved.

Engineering scalable biological systems

PubMed Central

2010-01-01

Synthetic biology is focused on engineering biological organisms to study natural systems and to provide new solutions for pressing medical, industrial and environmental problems. At the core of engineered organisms are synthetic biological circuits that execute the tasks of sensing inputs, processing logic and performing output functions. In the last decade, significant progress has been made in developing basic designs for a wide range of biological circuits in bacteria, yeast and mammalian systems. However, significant challenges in the construction, probing, modulation and debugging of synthetic biological systems must be addressed in order to achieve scalable higher-complexity biological circuits. Furthermore, concomitant efforts to evaluate the safety and biocontainment of engineered organisms and address public and regulatory concerns will be necessary to ensure that technological advances are translated into real-world solutions. PMID:21468204

Protein-protein interaction predictions using text mining methods.

PubMed

Papanikolaou, Nikolas; Pavlopoulos, Georgios A; Theodosiou, Theodosios; Iliopoulos, Ioannis

2015-03-01

It is beyond any doubt that proteins and their interactions play an essential role in most complex biological processes. The understanding of their function individually, but also in the form of protein complexes is of a great importance. Nowadays, despite the plethora of various high-throughput experimental approaches for detecting protein-protein interactions, many computational methods aiming to predict new interactions have appeared and gained interest. In this review, we focus on text-mining based computational methodologies, aiming to extract information for proteins and their interactions from public repositories such as literature and various biological databases. We discuss their strengths, their weaknesses and how they complement existing experimental techniques by simultaneously commenting on the biological databases which hold such information and the benchmark datasets that can be used for evaluating new tools. Copyright © 2014 Elsevier Inc. All rights reserved.

Ferrocene-containing non-interlocked molecular machines.

PubMed

Scottwell, Synøve Ø; Crowley, James D

2016-02-11

Ferrocene is the prototypical organometallic sandwich complex and despite over 60 years passing since the discovery and elucidation of ferrocene's structure, research into ferrocene-containing compounds continues to grow as potential new applications in catalysis, biology and the material sciences are found. Ferrocene is chemically robust and readily functionalized which enables its facile incorporation into more complex molecular systems. This coupled with ferrocene's reversible redox properties and ability function as a "molecular ball bearing" has led to the use of ferrocene as a component in wide range of interlocked and non-interlocked synthetic molecular machine systems. This review will focus on the exploitation of ferrocene (and related sandwich complexes) for the development of non-interlocked synthetic molecular machines.

Methods for protein complex prediction and their contributions towards understanding the organisation, function and dynamics of complexes.

PubMed

Srihari, Sriganesh; Yong, Chern Han; Patil, Ashwini; Wong, Limsoon

2015-09-14

Complexes of physically interacting proteins constitute fundamental functional units responsible for driving biological processes within cells. A faithful reconstruction of the entire set of complexes is therefore essential to understand the functional organisation of cells. In this review, we discuss the key contributions of computational methods developed till date (approximately between 2003 and 2015) for identifying complexes from the network of interacting proteins (PPI network). We evaluate in depth the performance of these methods on PPI datasets from yeast, and highlight their limitations and challenges, in particular at detecting sparse and small or sub-complexes and discerning overlapping complexes. We describe methods for integrating diverse information including expression profiles and 3D structures of proteins with PPI networks to understand the dynamics of complex formation, for instance, of time-based assembly of complex subunits and formation of fuzzy complexes from intrinsically disordered proteins. Finally, we discuss methods for identifying dysfunctional complexes in human diseases, an application that is proving invaluable to understand disease mechanisms and to discover novel therapeutic targets. We hope this review aptly commemorates a decade of research on computational prediction of complexes and constitutes a valuable reference for further advancements in this exciting area. Copyright © 2015 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.

Mining for Micropeptides.

PubMed

Makarewich, Catherine A; Olson, Eric N

2017-09-01

Advances in computational biology and large-scale transcriptome analyses have revealed that a much larger portion of the genome is transcribed than was previously recognized, resulting in the production of a diverse population of RNA molecules with both protein-coding and noncoding potential. Emerging evidence indicates that several RNA molecules have been mis-annotated as noncoding and in fact harbor short open reading frames (sORFs) that encode functional peptides and that have evaded detection until now due to their small size. sORF-encoded peptides (SEPs), or micropeptides, have been shown to have important roles in fundamental biological processes and in the maintenance of cellular homeostasis. These small proteins can act independently, for example as ligands or signaling molecules, or they can exert their biological functions by engaging with and modulating larger regulatory proteins. Given their small size, micropeptides may be uniquely suited to fine-tune complex biological systems. Copyright © 2017 Elsevier Ltd. All rights reserved.

From pull-down data to protein interaction networks and complexes with biological relevance.

PubMed

Zhang, Bing; Park, Byung-Hoon; Karpinets, Tatiana; Samatova, Nagiza F

2008-04-01

Recent improvements in high-throughput Mass Spectrometry (MS) technology have expedited genome-wide discovery of protein-protein interactions by providing a capability of detecting protein complexes in a physiological setting. Computational inference of protein interaction networks and protein complexes from MS data are challenging. Advances are required in developing robust and seamlessly integrated procedures for assessment of protein-protein interaction affinities, mathematical representation of protein interaction networks, discovery of protein complexes and evaluation of their biological relevance. A multi-step but easy-to-follow framework for identifying protein complexes from MS pull-down data is introduced. It assesses interaction affinity between two proteins based on similarity of their co-purification patterns derived from MS data. It constructs a protein interaction network by adopting a knowledge-guided threshold selection method. Based on the network, it identifies protein complexes and infers their core components using a graph-theoretical approach. It deploys a statistical evaluation procedure to assess biological relevance of each found complex. On Saccharomyces cerevisiae pull-down data, the framework outperformed other more complicated schemes by at least 10% in F(1)-measure and identified 610 protein complexes with high-functional homogeneity based on the enrichment in Gene Ontology (GO) annotation. Manual examination of the complexes brought forward the hypotheses on cause of false identifications. Namely, co-purification of different protein complexes as mediated by a common non-protein molecule, such as DNA, might be a source of false positives. Protein identification bias in pull-down technology, such as the hydrophilic bias could result in false negatives.

Synthesis, characterization and deepening in the comprehension of the biological action mechanisms of a new nickel complex with antiproliferative activity.

PubMed

Buschini, Annamaria; Pinelli, Silvana; Pellacani, Claudia; Giordani, Federica; Ferrari, Marisa Belicchi; Bisceglie, Franco; Giannetto, Marco; Pelosi, Giorgio; Tarasconi, Pieralberto

2009-05-01

Thiosemicarbazones are versatile organic compounds that present considerable pharmaceutical interest because of a wide range of properties. In our laboratory we synthesised some new metal-complexes with thiosemicarbazones derived from natural aldehydes which showed peculiar biological activities. In particular, a nickel complex [Ni(S-tcitr)(2)] (S-tcitr=S-citronellalthiosemicarbazonate) was observed to induce an antiproliferative effect on U937, a human histiocytic lymphoma cell line, at low concentrations (IC(50)=14.4microM). Therefore, we decided to study the interactions of this molecule with various cellular components and to characterise the induced apoptotic pathway. Results showed that [Ni(S-tcitr)(2)] causes programmed cell death via down-regulation of Bcl-2, alteration of mitochondrial membrane potential and caspase-3 activity, regardless of p53 function. The metal complex is not active on G(0) cells (i.e. fresh leukocytes) but is able to induce perturbation of the cell cycle on stimulated lymphocytes and U937 cells, in which a G(2)/M block was detected. It reaches the nucleus where it induces, at low concentrations (2.5-5.0microM), DNA damage, which could be partially ascribed to oxidative stress. [Ni(S-tcitr)(2)] is moreover able to strongly reduce the telomerase activity. Although the biological target of this metal complex is still unknown, the reported data suggest that [Ni(S-tcitr)(2)] could be a good model for the synthesis of new metal thiosemicarbazones with specific biological activity.

A CellML simulation compiler and code generator using ODE solving schemes

PubMed Central

2012-01-01

Models written in description languages such as CellML are becoming a popular solution to the handling of complex cellular physiological models in biological function simulations. However, in order to fully simulate a model, boundary conditions and ordinary differential equation (ODE) solving schemes have to be combined with it. Though boundary conditions can be described in CellML, it is difficult to explicitly specify ODE solving schemes using existing tools. In this study, we define an ODE solving scheme description language-based on XML and propose a code generation system for biological function simulations. In the proposed system, biological simulation programs using various ODE solving schemes can be easily generated. We designed a two-stage approach where the system generates the equation set associating the physiological model variable values at a certain time t with values at t + Δt in the first stage. The second stage generates the simulation code for the model. This approach enables the flexible construction of code generation modules that can support complex sets of formulas. We evaluate the relationship between models and their calculation accuracies by simulating complex biological models using various ODE solving schemes. Using the FHN model simulation, results showed good qualitative and quantitative correspondence with the theoretical predictions. Results for the Luo-Rudy 1991 model showed that only first order precision was achieved. In addition, running the generated code in parallel on a GPU made it possible to speed up the calculation time by a factor of 50. The CellML Compiler source code is available for download at http://sourceforge.net/projects/cellmlcompiler. PMID:23083065

Synthetic biology in mammalian cells: Next generation research tools and therapeutics

PubMed Central

Lienert, Florian; Lohmueller, Jason J; Garg, Abhishek; Silver, Pamela A

2014-01-01

Recent progress in DNA manipulation and gene circuit engineering has greatly improved our ability to programme and probe mammalian cell behaviour. These advances have led to a new generation of synthetic biology research tools and potential therapeutic applications. Programmable DNA-binding domains and RNA regulators are leading to unprecedented control of gene expression and elucidation of gene function. Rebuilding complex biological circuits such as T cell receptor signalling in isolation from their natural context has deepened our understanding of network motifs and signalling pathways. Synthetic biology is also leading to innovative therapeutic interventions based on cell-based therapies, protein drugs, vaccines and gene therapies. PMID:24434884

TRIENNIAL LACTATION SYMPOSIUM: Nutrigenomics in livestock: Systems biology meets nutrition.

PubMed

Loor, J J; Vailati-Riboni, M; McCann, J C; Zhou, Z; Bionaz, M

2015-12-01

The advent of high-throughput technologies to study an animal's genome, proteome, and metabolome (i.e., "omics" tools) constituted a setback to the use of reductionism in livestock research. More recent development of "next-generation sequencing" tools was instrumental in allowing in-depth studies of the microbiome in the rumen and other sections of the gastrointestinal tract. Omics, along with bioinformatics, constitutes the foundation of modern systems biology, a field of study widely used in model organisms (e.g., rodents, yeast, humans) to enhance understanding of the complex biological interactions occurring within cells and tissues at the gene, protein, and metabolite level. Application of systems biology concepts is ideal for the study of interactions between nutrition and physiological state with tissue and cell metabolism and function during key life stages of livestock species, including the transition from pregnancy to lactation, in utero development, or postnatal growth. Modern bioinformatic tools capable of discerning functional outcomes and biologically meaningful networks complement the ever-increasing ability to generate large molecular, microbial, and metabolite data sets. Simultaneous visualization of the complex intertissue adaptations to physiological state and nutrition can now be discerned. Studies to understand the linkages between the microbiome and the absorptive epithelium using the integrative approach are emerging. We present examples of new knowledge generated through the application of functional analyses of transcriptomic, proteomic, and metabolomic data sets encompassing nutritional management of dairy cows, pigs, and poultry. Published work to date underscores that the integrative approach across and within tissues may prove useful for fine-tuning nutritional management of livestock. An important goal during this process is to uncover key molecular players involved in the organismal adaptations to nutrition.

The Reconstruction and Analysis of Gene Regulatory Networks.

PubMed

Zheng, Guangyong; Huang, Tao

2018-01-01

In post-genomic era, an important task is to explore the function of individual biological molecules (i.e., gene, noncoding RNA, protein, metabolite) and their organization in living cells. For this end, gene regulatory networks (GRNs) are constructed to show relationship between biological molecules, in which the vertices of network denote biological molecules and the edges of network present connection between nodes (Strogatz, Nature 410:268-276, 2001; Bray, Science 301:1864-1865, 2003). Biologists can understand not only the function of biological molecules but also the organization of components of living cells through interpreting the GRNs, since a gene regulatory network is a comprehensively physiological map of living cells and reflects influence of genetic and epigenetic factors (Strogatz, Nature 410:268-276, 2001; Bray, Science 301:1864-1865, 2003). In this paper, we will review the inference methods of GRN reconstruction and analysis approaches of network structure. As a powerful tool for studying complex diseases and biological processes, the applications of the network method in pathway analysis and disease gene identification will be introduced.

Magnetic separation techniques in sample preparation for biological analysis: a review.

PubMed

He, Jincan; Huang, Meiying; Wang, Dongmei; Zhang, Zhuomin; Li, Gongke

2014-12-01

Sample preparation is a fundamental and essential step in almost all the analytical procedures, especially for the analysis of complex samples like biological and environmental samples. In past decades, with advantages of superparamagnetic property, good biocompatibility and high binding capacity, functionalized magnetic materials have been widely applied in various processes of sample preparation for biological analysis. In this paper, the recent advancements of magnetic separation techniques based on magnetic materials in the field of sample preparation for biological analysis were reviewed. The strategy of magnetic separation techniques was summarized. The synthesis, stabilization and bio-functionalization of magnetic nanoparticles were reviewed in detail. Characterization of magnetic materials was also summarized. Moreover, the applications of magnetic separation techniques for the enrichment of protein, nucleic acid, cell, bioactive compound and immobilization of enzyme were described. Finally, the existed problems and possible trends of magnetic separation techniques for biological analysis in the future were proposed. Copyright © 2014 Elsevier B.V. All rights reserved.

A machine learning approach to predicting protein-ligand binding affinity with applications to molecular docking.

PubMed

Ballester, Pedro J; Mitchell, John B O

2010-05-01

Accurately predicting the binding affinities of large sets of diverse protein-ligand complexes is an extremely challenging task. The scoring functions that attempt such computational prediction are essential for analysing the outputs of molecular docking, which in turn is an important technique for drug discovery, chemical biology and structural biology. Each scoring function assumes a predetermined theory-inspired functional form for the relationship between the variables that characterize the complex, which also include parameters fitted to experimental or simulation data and its predicted binding affinity. The inherent problem of this rigid approach is that it leads to poor predictivity for those complexes that do not conform to the modelling assumptions. Moreover, resampling strategies, such as cross-validation or bootstrapping, are still not systematically used to guard against the overfitting of calibration data in parameter estimation for scoring functions. We propose a novel scoring function (RF-Score) that circumvents the need for problematic modelling assumptions via non-parametric machine learning. In particular, Random Forest was used to implicitly capture binding effects that are hard to model explicitly. RF-Score is compared with the state of the art on the demanding PDBbind benchmark. Results show that RF-Score is a very competitive scoring function. Importantly, RF-Score's performance was shown to improve dramatically with training set size and hence the future availability of more high-quality structural and interaction data is expected to lead to improved versions of RF-Score. pedro.ballester@ebi.ac.uk; jbom@st-andrews.ac.uk Supplementary data are available at Bioinformatics online.

Translating Mendelian and complex inheritance of Alzheimer's disease genes for predicting unique personal genome variants

PubMed Central

Regan, Kelly; Wang, Kanix; Doughty, Emily; Li, Haiquan; Li, Jianrong; Lee, Younghee; Kann, Maricel G

2012-01-01

Objective Although trait-associated genes identified as complex versus single-gene inheritance differ substantially in odds ratio, the authors nonetheless posit that their mechanistic concordance can reveal fundamental properties of the genetic architecture, allowing the automated interpretation of unique polymorphisms within a personal genome. Materials and methods An analytical method, SPADE-gen, spanning three biological scales was developed to demonstrate the mechanistic concordance between Mendelian and complex inheritance of Alzheimer's disease (AD) genes: biological functions (BP), protein interaction modeling, and protein domain implicated in the disease-associated polymorphism. Results Among Gene Ontology (GO) biological processes (BP) enriched at a false detection rate <5% in 15 AD genes of Mendelian inheritance (Online Mendelian Inheritance in Man) and independently in those of complex inheritance (25 host genes of intragenic AD single-nucleotide polymorphisms confirmed in genome-wide association studies), 16 overlapped (empirical p=0.007) and 45 were similar (empirical p<0.009; information theory). SPAN network modeling extended the canonical pathway of AD (KEGG) with 26 new protein interactions (empirical p<0.0001). Discussion The study prioritized new AD-associated biological mechanisms and focused the analysis on previously unreported interactions associated with the biological processes of polymorphisms that affect specific protein domains within characterized AD genes and their direct interactors using (1) concordant GO-BP and (2) domain interactions within STRING protein–protein interactions corresponding to the genomic location of the AD polymorphism (eg, EPHA1, APOE, and CD2AP). Conclusion These results are in line with unique-event polymorphism theory, indicating how disease-associated polymorphisms of Mendelian or complex inheritance relate genetically to those observed as ‘unique personal variants’. They also provide insight for identifying novel targets, for repositioning drugs, and for personal therapeutics. PMID:22319180

A Multidisciplinary, Open Access Platform for Research on Biomolecules.

PubMed

Bähler, Jürg

2011-08-22

I am pleased to introduce Biomolecules, a new journal to report on all aspects of science that focuses on biologically derived substances, from small molecules to complex polymers. Some examples are lipids, carbohydrates, vitamins, hormones, amino acids, nucleotides, peptides, RNA and polysaccharides, but this list is far from exhaustive. Research on biomolecules encompasses multiple fascinating questions. How are biomolecules synthesized and modified? What are their structures and interactions with other biomolecules? How do biomolecules function in biological processes, at the level of organelles, cells, organs, organisms, or even ecosystems? How do biomolecules affect either the organism that produces them or other organisms of the same or different species? How are biomolecules shaped by evolution, and how in turn do they affect cellular phenotypes? What is the systems-level contribution of biomolecules to biological function? [...].

Functional annotation of the vlinc class of non-coding RNAs using systems biology approach.

PubMed

St Laurent, Georges; Vyatkin, Yuri; Antonets, Denis; Ri, Maxim; Qi, Yao; Saik, Olga; Shtokalo, Dmitry; de Hoon, Michiel J L; Kawaji, Hideya; Itoh, Masayoshi; Lassmann, Timo; Arner, Erik; Forrest, Alistair R R; Nicolas, Estelle; McCaffrey, Timothy A; Carninci, Piero; Hayashizaki, Yoshihide; Wahlestedt, Claes; Kapranov, Philipp

2016-04-20

Functionality of the non-coding transcripts encoded by the human genome is the coveted goal of the modern genomics research. While commonly relied on the classical methods of forward genetics, integration of different genomics datasets in a global Systems Biology fashion presents a more productive avenue of achieving this very complex aim. Here we report application of a Systems Biology-based approach to dissect functionality of a newly identified vast class of very long intergenic non-coding (vlinc) RNAs. Using highly quantitative FANTOM5 CAGE dataset, we show that these RNAs could be grouped into 1542 novel human genes based on analysis of insulators that we show here indeed function as genomic barrier elements. We show that vlinc RNAs genes likely function in cisto activate nearby genes. This effect while most pronounced in closely spaced vlinc RNA-gene pairs can be detected over relatively large genomic distances. Furthermore, we identified 101 vlinc RNA genes likely involved in early embryogenesis based on patterns of their expression and regulation. We also found another 109 such genes potentially involved in cellular functions also happening at early stages of development such as proliferation, migration and apoptosis. Overall, we show that Systems Biology-based methods have great promise for functional annotation of non-coding RNAs. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Global functional atlas of Escherichia coli encompassing previously uncharacterized proteins.

PubMed

Hu, Pingzhao; Janga, Sarath Chandra; Babu, Mohan; Díaz-Mejía, J Javier; Butland, Gareth; Yang, Wenhong; Pogoutse, Oxana; Guo, Xinghua; Phanse, Sadhna; Wong, Peter; Chandran, Shamanta; Christopoulos, Constantine; Nazarians-Armavil, Anaies; Nasseri, Negin Karimi; Musso, Gabriel; Ali, Mehrab; Nazemof, Nazila; Eroukova, Veronika; Golshani, Ashkan; Paccanaro, Alberto; Greenblatt, Jack F; Moreno-Hagelsieb, Gabriel; Emili, Andrew

2009-04-28

One-third of the 4,225 protein-coding genes of Escherichia coli K-12 remain functionally unannotated (orphans). Many map to distant clades such as Archaea, suggesting involvement in basic prokaryotic traits, whereas others appear restricted to E. coli, including pathogenic strains. To elucidate the orphans' biological roles, we performed an extensive proteomic survey using affinity-tagged E. coli strains and generated comprehensive genomic context inferences to derive a high-confidence compendium for virtually the entire proteome consisting of 5,993 putative physical interactions and 74,776 putative functional associations, most of which are novel. Clustering of the respective probabilistic networks revealed putative orphan membership in discrete multiprotein complexes and functional modules together with annotated gene products, whereas a machine-learning strategy based on network integration implicated the orphans in specific biological processes. We provide additional experimental evidence supporting orphan participation in protein synthesis, amino acid metabolism, biofilm formation, motility, and assembly of the bacterial cell envelope. This resource provides a "systems-wide" functional blueprint of a model microbe, with insights into the biological and evolutionary significance of previously uncharacterized proteins.

Functional modules of sigma factor regulons guarantee adaptability and evolvability

PubMed Central

Binder, Sebastian C.; Eckweiler, Denitsa; Schulz, Sebastian; Bielecka, Agata; Nicolai, Tanja; Franke, Raimo; Häussler, Susanne; Meyer-Hermann, Michael

2016-01-01

The focus of modern molecular biology turns from assigning functions to individual genes towards understanding the expression and regulation of complex sets of molecules. Here, we provide evidence that alternative sigma factor regulons in the pathogen Pseudomonas aeruginosa largely represent insulated functional modules which provide a critical level of biological organization involved in general adaptation and survival processes. Analysis of the operational state of the sigma factor network revealed that transcription factors functionally couple the sigma factor regulons and significantly modulate the transcription levels in the face of challenging environments. The threshold quality of newly evolved transcription factors was reached faster and more robustly in in silico testing when the structural organization of sigma factor networks was taken into account. These results indicate that the modular structures of alternative sigma factor regulons provide P. aeruginosa with a robust framework to function adequately in its environment and at the same time facilitate evolutionary change. Our data support the view that widespread modularity guarantees robustness of biological networks and is a key driver of evolvability. PMID:26915971

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.

Back to the biology in systems biology: what can we learn from biomolecular networks?

PubMed

Huang, Sui

2004-02-01

Genome-scale molecular networks, including protein interaction and gene regulatory networks, have taken centre stage in the investigation of the burgeoning disciplines of systems biology and biocomplexity. What do networks tell us? Some see in networks simply the comprehensive, detailed description of all cellular pathways, others seek in networks simple, higher-order qualities that emerge from the collective action of the individual pathways. This paper discusses networks from an encompassing category of thinking that will hopefully help readers to bridge the gap between these polarised viewpoints. Systems biology so far has emphasised the characterisation of large pathway maps. Now one has to ask: where is the actual biology in 'systems biology'? As structures midway between genome and phenome, and by serving as an 'extended genotype' or an 'elementary phenotype', molecular networks open a new window to the study of evolution and gene function in complex living systems. For the study of evolution, features in network topology offer a novel starting point for addressing the old debate on the relative contributions of natural selection versus intrinsic constraints to a particular trait. To study the function of genes, it is necessary not only to see them in the context of gene networks, but also to reach beyond describing network topology and to embrace the global dynamics of networks that will reveal higher-order, collective behaviour of the interacting genes. This will pave the way to understanding how the complexity of genome-wide molecular networks collapses to produce a robust whole-cell behaviour that manifests as tightly-regulated switching between distinct cell fates - the basis for multicellular life.

(PS)2: protein structure prediction server version 3.0.

PubMed

Huang, Tsun-Tsao; Hwang, Jenn-Kang; Chen, Chu-Huang; Chu, Chih-Sheng; Lee, Chi-Wen; Chen, Chih-Chieh

2015-07-01

Protein complexes are involved in many biological processes. Examining coupling between subunits of a complex would be useful to understand the molecular basis of protein function. Here, our updated (PS)(2) web server predicts the three-dimensional structures of protein complexes based on comparative modeling; furthermore, this server examines the coupling between subunits of the predicted complex by combining structural and evolutionary considerations. The predicted complex structure could be indicated and visualized by Java-based 3D graphics viewers and the structural and evolutionary profiles are shown and compared chain-by-chain. For each subunit, considerations with or without the packing contribution of other subunits cause the differences in similarities between structural and evolutionary profiles, and these differences imply which form, complex or monomeric, is preferred in the biological condition for the subunit. We believe that the (PS)(2) server would be a useful tool for biologists who are interested not only in the structures of protein complexes but also in the coupling between subunits of the complexes. The (PS)(2) is freely available at http://ps2v3.life.nctu.edu.tw/. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

Will Systems Biology Deliver Its Promise and Contribute to the Development of New or Improved Vaccines? What Really Constitutes the Study of "Systems Biology" and How Might Such an Approach Facilitate Vaccine Design.

PubMed

Germain, Ronald N

2017-10-16

A dichotomy exists in the field of vaccinology about the promise versus the hype associated with application of "systems biology" approaches to rational vaccine design. Some feel it is the only way to efficiently uncover currently unknown parameters controlling desired immune responses or discover what elements actually mediate these responses. Others feel that traditional experimental, often reductionist, methods for incrementally unraveling complex biology provide a more solid way forward, and that "systems" approaches are costly ways to collect data without gaining true insight. Here I argue that both views are inaccurate. This is largely because of confusion about what can be gained from classical experimentation versus statistical analysis of large data sets (bioinformatics) versus methods that quantitatively explain emergent properties of complex assemblies of biological components, with the latter reflecting what was previously called "physiology." Reductionist studies will remain essential for generating detailed insight into the functional attributes of specific elements of biological systems, but such analyses lack the power to provide a quantitative and predictive understanding of global system behavior. But by employing (1) large-scale screening methods for discovery of unknown components and connections in the immune system ( omics ), (2) statistical analysis of large data sets ( bioinformatics ), and (3) the capacity of quantitative computational methods to translate these individual components and connections into models of emergent behavior ( systems biology ), we will be able to better understand how the overall immune system functions and to determine with greater precision how to manipulate it to produce desired protective responses. Copyright © 2017 Cold Spring Harbor Laboratory Press; all rights reserved.

Interfacing cellular networks of S. cerevisiae and E. coli: Connecting dynamic and genetic information

PubMed Central

2013-01-01

Background In recent years, various types of cellular networks have penetrated biology and are nowadays used omnipresently for studying eukaryote and prokaryote organisms. Still, the relation and the biological overlap among phenomenological and inferential gene networks, e.g., between the protein interaction network and the gene regulatory network inferred from large-scale transcriptomic data, is largely unexplored. Results We provide in this study an in-depth analysis of the structural, functional and chromosomal relationship between a protein-protein network, a transcriptional regulatory network and an inferred gene regulatory network, for S. cerevisiae and E. coli. Further, we study global and local aspects of these networks and their biological information overlap by comparing, e.g., the functional co-occurrence of Gene Ontology terms by exploiting the available interaction structure among the genes. Conclusions Although the individual networks represent different levels of cellular interactions with global structural and functional dissimilarities, we observe crucial functions of their network interfaces for the assembly of protein complexes, proteolysis, transcription, translation, metabolic and regulatory interactions. Overall, our results shed light on the integrability of these networks and their interfacing biological processes. PMID:23663484

Air pollution particles and iron homeostasis | Science ...

EPA Pesticide Factsheets

Background: The mechanism underlying biological effects of particles deposited in the lung has not been defined. Major Conclusions: A disruption in iron homeostasis follows exposure of cells to all particulate matter including air pollution particles. Following endocytosis, functional groups at the surface of retained particle complex iron available in the cell. In response to a reduction in concentrations of requisite iron, a functional deficiency can result intracellularly. Superoxide production by the cell exposed to a particle increases ferrireduction which facilitates import of iron with the objective being the reversal of the metal deficiency. Failure to resolve the functional iron deficiency following cell exposure to particles activates kinases and transcription factors resulting in a release of inflammatory mediators and inflammation. Tissue injury is the end product of this disruption in iron homeostasis initiated by the particle exposure. Elevation of available iron to the cell precludes deficiency of the metal and either diminishes or eliminates biological effects.General Significance: Recognition of the pathway for biological effects after particle exposure to involve a functional deficiency of iron suggests novel therapies such as metal supplementation (e.g. inhaled and oral). In addition, the demonstration of a shared mechanism of biological effects allows understanding the common clinical, physiological, and pathological presentation fol

Structure and function of wood

Treesearch

Alex Wiedenhoeft

2010-01-01

Wood is a complex biological structure, a composite of many chemistries and cell types acting together to serve the needs of a living plant. Attempting to understand wood in the context of wood technology, we have often overlooked the key and basic fact that wood evolved over the course of millions of years to serve three main functions in plants― conduction of water...

Intermolecular hydrogen bonds in hetero-complexes of biologically active aromatic molecules probed by the methods of vibrational spectroscopy.

PubMed

Semenov, M A; Blyzniuk, Iu N; Bolbukh, T V; Shestopalova, A V; Evstigneev, M P; Maleev, V Ya

2012-09-01

By the methods of vibrational spectroscopy (Infrared and Raman) the investigation of the hetero-association of biologically active aromatic compounds: flavin-mononucleotide (FMN), ethidium bromide (EB) and proflavine (PRF) was performed in aqueous solutions. It was shown that between the functional groups (CO and NH(2)) the intermolecular hydrogen bonds are formed in the hetero-complexes FMN-EB and FMN-PRF, additionally stabilizing these structures. An estimation of the enthalpy of Н-bonding obtained from experimental shifts of carbonyl vibrational frequencies has shown that the H-bonds do not dominate in the magnitude of experimentally measured total enthalpy of the hetero-association reactions. The main stabilization is likely due to intermolecular interactions of the molecules in these complexes and their interaction with water environment. Copyright © 2012 Elsevier B.V. All rights reserved.

Biological conservation law as an emerging functionality in dynamical neuronal networks.

PubMed

Podobnik, Boris; Jusup, Marko; Tiganj, Zoran; Wang, Wen-Xu; Buldú, Javier M; Stanley, H Eugene

2017-11-07

Scientists strive to understand how functionalities, such as conservation laws, emerge in complex systems. Living complex systems in particular create high-ordered functionalities by pairing up low-ordered complementary processes, e.g., one process to build and the other to correct. We propose a network mechanism that demonstrates how collective statistical laws can emerge at a macro (i.e., whole-network) level even when they do not exist at a unit (i.e., network-node) level. Drawing inspiration from neuroscience, we model a highly stylized dynamical neuronal network in which neurons fire either randomly or in response to the firing of neighboring neurons. A synapse connecting two neighboring neurons strengthens when both of these neurons are excited and weakens otherwise. We demonstrate that during this interplay between the synaptic and neuronal dynamics, when the network is near a critical point, both recurrent spontaneous and stimulated phase transitions enable the phase-dependent processes to replace each other and spontaneously generate a statistical conservation law-the conservation of synaptic strength. This conservation law is an emerging functionality selected by evolution and is thus a form of biological self-organized criticality in which the key dynamical modes are collective.

Computational multiscale modeling in protein--ligand docking.

PubMed

Taufer, Michela; Armen, Roger; Chen, Jianhan; Teller, Patricia; Brooks, Charles

2009-01-01

In biological systems, the binding of small molecule ligands to proteins is a crucial process for almost every aspect of biochemistry and molecular biology. Enzymes are proteins that function by catalyzing specific biochemical reactions that convert reactants into products. Complex organisms are typically composed of cells in which thousands of enzymes participate in complex and interconnected biochemical pathways. Some enzymes serve as sequential steps in specific pathways (such as energy metabolism), while others function to regulate entire pathways and cellular functions [1]. Small molecule ligands can be designed to bind to a specific enzyme and inhibit the biochemical reaction. Inhibiting the activity of key enzymes may result in the entire biochemical pathways being turned on or off [2], [3]. Many small molecule drugs marketed today function in this generic way as enzyme inhibitors. If research identifies a specific enzyme as being crucial to the progress of disease, then this enzyme may be targeted with an inhibitor, which may slow down or reverse the progress of disease. In this way, enzymes are targeted from specific pathogens (e.g., virus, bacteria, fungi) for infectious diseases [4], [5], and human enzymes are targeted for noninfectious diseases such as cardiovascular disease, cancer, diabetes, and neurodegenerative diseases [6].

Biological conservation law as an emerging functionality in dynamical neuronal networks

PubMed Central

Podobnik, Boris; Tiganj, Zoran; Wang, Wen-Xu; Buldú, Javier M.

2017-01-01

Scientists strive to understand how functionalities, such as conservation laws, emerge in complex systems. Living complex systems in particular create high-ordered functionalities by pairing up low-ordered complementary processes, e.g., one process to build and the other to correct. We propose a network mechanism that demonstrates how collective statistical laws can emerge at a macro (i.e., whole-network) level even when they do not exist at a unit (i.e., network-node) level. Drawing inspiration from neuroscience, we model a highly stylized dynamical neuronal network in which neurons fire either randomly or in response to the firing of neighboring neurons. A synapse connecting two neighboring neurons strengthens when both of these neurons are excited and weakens otherwise. We demonstrate that during this interplay between the synaptic and neuronal dynamics, when the network is near a critical point, both recurrent spontaneous and stimulated phase transitions enable the phase-dependent processes to replace each other and spontaneously generate a statistical conservation law—the conservation of synaptic strength. This conservation law is an emerging functionality selected by evolution and is thus a form of biological self-organized criticality in which the key dynamical modes are collective. PMID:29078286

Genomic survey, expression profile and co-expression network analysis of OsWD40 family in rice

PubMed Central

2012-01-01

Background WD40 proteins represent a large family in eukaryotes, which have been involved in a broad spectrum of crucial functions. Systematic characterization and co-expression analysis of OsWD40 genes enable us to understand the networks of the WD40 proteins and their biological processes and gene functions in rice. Results In this study, we identify and analyze 200 potential OsWD40 genes in rice, describing their gene structures, genome localizations, and evolutionary relationship of each member. Expression profiles covering the whole life cycle in rice has revealed that transcripts of OsWD40 were accumulated differentially during vegetative and reproductive development and preferentially up or down-regulated in different tissues. Under phytohormone treatments, 25 OsWD40 genes were differentially expressed with treatments of one or more of the phytohormone NAA, KT, or GA3 in rice seedlings. We also used a combined analysis of expression correlation and Gene Ontology annotation to infer the biological role of the OsWD40 genes in rice. The results suggested that OsWD40 genes may perform their diverse functions by complex network, thus were predictive for understanding their biological pathways. The analysis also revealed that OsWD40 genes might interact with each other to take part in metabolic pathways, suggesting a more complex feedback network. Conclusions All of these analyses suggest that the functions of OsWD40 genes are diversified, which provide useful references for selecting candidate genes for further functional studies. PMID:22429805

Spectroscopic exploration of interaction between PEG-functionalized Ag2S nanoparticles with bovine serum albumin

NASA Astrophysics Data System (ADS)

Prasanth, S.; RitheshRaj, D.; Vineeshkumar, T. V.; Sudarsanakumar, C.

2018-05-01

The introduction of nanoparticles into biological fluids often leads to the formation of biocorona over the surface of nanoparticles. For the effective use of nanoparticles in biological applications it is very essential to understand their interactions with proteins. Herein, we investigated the interactions of Poly ethylene glycol capped Ag2S nanoparticles with Bovine Serum Albumin by spectroscopic techniques. By the addition of Ag2S nanoparticles, a ground state complex is formed. The CD spectroscopy reveals that the secondary structure of BSA is altered by complexation with PEG-Ag2S nanoparticles, while the overall tertiary structure remains closer to that of native BSA.

Protein complexes, big data, machine learning and integrative proteomics: lessons learned over a decade of systematic analysis of protein interaction networks.

PubMed

Havugimana, Pierre C; Hu, Pingzhao; Emili, Andrew

2017-10-01

Elucidation of the networks of physical (functional) interactions present in cells and tissues is fundamental for understanding the molecular organization of biological systems, the mechanistic basis of essential and disease-related processes, and for functional annotation of previously uncharacterized proteins (via guilt-by-association or -correlation). After a decade in the field, we felt it timely to document our own experiences in the systematic analysis of protein interaction networks. Areas covered: Researchers worldwide have contributed innovative experimental and computational approaches that have driven the rapidly evolving field of 'functional proteomics'. These include mass spectrometry-based methods to characterize macromolecular complexes on a global-scale and sophisticated data analysis tools - most notably machine learning - that allow for the generation of high-quality protein association maps. Expert commentary: Here, we recount some key lessons learned, with an emphasis on successful workflows, and challenges, arising from our own and other groups' ongoing efforts to generate, interpret and report proteome-scale interaction networks in increasingly diverse biological contexts.

Presenilin-1 affects trafficking and processing of βAPP and is targeted in a complex with nicastrin to the plasma membrane

PubMed Central

Kaether, Christoph; Lammich, Sven; Edbauer, Dieter; Ertl, Michaela; Rietdorf, Jens; Capell, Anja; Steiner, Harald; Haass, Christian

2002-01-01

Amyloid β-peptide (Aβ) is generated by the consecutive cleavages of β- and γ-secretase. The intramembraneous γ-secretase cleavage critically depends on the activity of presenilins (PS1 and PS2). Although there is evidence that PSs are aspartyl proteases with γ-secretase activity, it remains controversial whether their subcellular localization overlaps with the cellular sites of Aβ production. We now demonstrate that biologically active GFP-tagged PS1 as well as endogenous PS1 are targeted to the plasma membrane (PM) of living cells. On the way to the PM, PS1 binds to nicastrin (Nct), an essential component of the γ-secretase complex. This complex is targeted through the secretory pathway where PS1-bound Nct becomes endoglycosidase H resistant. Moreover, surface-biotinylated Nct can be coimmunoprecipitated with PS1 antibodies, demonstrating that this complex is located to cellular sites with γ-secretase activity. Inactivating PS1 or PS2 function by mutagenesis of one of the critical aspartate residues or by γ-secretase inhibitors results in delayed reinternalization of the β-amyloid precursor protein and its accumulation at the cell surface. Our data suggest that PS is targeted as a biologically active complex with Nct through the secretory pathway to the cell surface and suggest a dual function of PS in γ-secretase processing and in trafficking. PMID:12147673

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.

Toward a multiscale modeling framework for understanding serotonergic function

PubMed Central

Wong-Lin, KongFatt; Wang, Da-Hui; Moustafa, Ahmed A; Cohen, Jeremiah Y; Nakamura, Kae

2017-01-01

Despite its importance in regulating emotion and mental wellbeing, the complex structure and function of the serotonergic system present formidable challenges toward understanding its mechanisms. In this paper, we review studies investigating the interactions between serotonergic and related brain systems and their behavior at multiple scales, with a focus on biologically-based computational modeling. We first discuss serotonergic intracellular signaling and neuronal excitability, followed by neuronal circuit and systems levels. At each level of organization, we will discuss the experimental work accompanied by related computational modeling work. We then suggest that a multiscale modeling approach that integrates the various levels of neurobiological organization could potentially transform the way we understand the complex functions associated with serotonin. PMID:28417684

Diagnostic nanoparticle targeting of the EGF-receptor in complex biological conditions using single-domain antibodies.

PubMed

Zarschler, K; Prapainop, K; Mahon, E; Rocks, L; Bramini, M; Kelly, P M; Stephan, H; Dawson, K A

2014-06-07

For effective localization of functionalized nanoparticles at diseased tissues such as solid tumours or metastases through biorecognition, appropriate targeting vectors directed against selected tumour biomarkers are a key prerequisite. The diversity of such vector molecules ranges from proteins, including antibodies and fragments thereof, through aptamers and glycans to short peptides and small molecules. Here, we analyse the specific nanoparticle targeting capabilities of two previously suggested peptides (D4 and GE11) and a small camelid single-domain antibody (sdAb), representing potential recognition agents for the epidermal growth factor receptor (EGFR). We investigate specificity by way of receptor RNA silencing techniques and look at increasing complexity in vitro by introducing increasing concentrations of human or bovine serum. Peptides D4 and GE11 proved problematic to employ and conjugation resulted in non-receptor specific uptake into cells. Our results show that sdAb-functionalized particles can effectively target the EGFR, even in more complex bovine and human serum conditions where targeting specificity is largely conserved for increasing serum concentration. In human serum however, an inhibition of overall nanoparticle uptake is observed with increasing protein concentration. For highly affine targeting ligands such as sdAbs, targeting a receptor such as EGFR with low serum competitor abundance, receptor recognition function can still be partially realised in complex conditions. Here, we stress the value of evaluating the targeting efficiency of nanoparticle constructs in realistic biological milieu, prior to more extensive in vivo studies.

Spatial Navigation in Complex and Radial Mazes in APP23 Animals and Neurotrophin Signaling as a Biological Marker of Early Impairment

ERIC Educational Resources Information Center

Hellweg, Rainer; Huber, Roman; Kuhl, Alexander; Riepe, Matthias W.; Lohmann, Peter

2006-01-01

Impairment of hippocampal function precedes frontal and parietal cortex impairment in human Alzheimer's disease(AD). Neurotrophins are critical for behavioral performance and neuronal survival in AD. We used complex and radial mazes to assess spatial orientation and learning in wild-type and B6-Tg(ThylAPP)23Sdz (APP23) animals, a transgenic mouse…

Step-by-Step Simulation of Radiation of Radiation Chemistry Using Green Functions for Diffusion-Influenced Reactions

NASA Technical Reports Server (NTRS)

Plante, Ianik; Cucinotta, Francis A.

2011-01-01

The irradiation of biological systems leads to the formation of radiolytic species such as H(raised dot), (raised dot)OH, H2, H2O2, e(sup -)(sub aq), etc.[1]. These species react with neighboring molecules, which result in damage in biological molecules such as DNA. Radiation chemistry is there for every important to understand the radiobiological consequences of radiation[2]. In this work, we discuss an approach based on the exact Green Functions for diffusion-influenced reactions which may be used to simulate radiation chemistry and eventually extended to study more complex systems, including DNA.

Concise Review: Organ Engineering: Design, Technology, and Integration.

PubMed

Kaushik, Gaurav; Leijten, Jeroen; Khademhosseini, Ali

2017-01-01

Engineering complex tissues and whole organs has the potential to dramatically impact translational medicine in several avenues. Organ engineering is a discipline that integrates biological knowledge of embryological development, anatomy, physiology, and cellular interactions with enabling technologies including biocompatible biomaterials and biofabrication platforms such as three-dimensional bioprinting. When engineering complex tissues and organs, core design principles must be taken into account, such as the structure-function relationship, biochemical signaling, mechanics, gradients, and spatial constraints. Technological advances in biomaterials, biofabrication, and biomedical imaging allow for in vitro control of these factors to recreate in vivo phenomena. Finally, organ engineering emerges as an integration of biological design and technical rigor. An overall workflow for organ engineering and guiding technology to advance biology as well as a perspective on necessary future iterations in the field is discussed. Stem Cells 2017;35:51-60. © 2016 AlphaMed Press.

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.

The interactions of peripheral membrane proteins with biological membranes

DOE PAGES

Johs, Alexander; Whited, A. M.

2015-07-29

The interactions of peripheral proteins with membrane surfaces are critical to many biological processes, including signaling, recognition, membrane trafficking, cell division and cell structure. On a molecular level, peripheral membrane proteins can modulate lipid composition, membrane dynamics and protein-protein interactions. Biochemical and biophysical studies have shown that these interactions are in fact highly complex, dominated by several different types of interactions, and have an interdependent effect on both the protein and membrane. Here we examine three major mechanisms underlying the interactions between peripheral membrane proteins and membranes: electrostatic interactions, hydrophobic interactions, and fatty acid modification of proteins. While experimental approachesmore » continue to provide critical insights into specific interaction mechanisms, emerging bioinformatics resources and tools contribute to a systems-level picture of protein-lipid interactions. Through these recent advances, we begin to understand the pivotal role of protein-lipid interactions underlying complex biological functions at membrane interfaces.« less

Reverse Ecology: from systems to environments and back.

PubMed

Levy, Roie; Borenstein, Elhanan

2012-01-01

The structure of complex biological systems reflects not only their function but also the environments in which they evolved and are adapted to. Reverse Ecology-an emerging new frontier in Evolutionary Systems Biology-aims to extract this information and to obtain novel insights into an organism's ecology. The Reverse Ecology framework facilitates the translation of high-throughput genomic data into large-scale ecological data, and has the potential to transform ecology into a high-throughput field. In this chapter, we describe some of the pioneering work in Reverse Ecology, demonstrating how system-level analysis of complex biological networks can be used to predict the natural habitats of poorly characterized microbial species, their interactions with other species, and universal patterns governing the adaptation of organisms to their environments. We further present several studies that applied Reverse Ecology to elucidate various aspects of microbial ecology, and lay out exciting future directions and potential future applications in biotechnology, biomedicine, and ecological engineering.

Unraveling the Pathogenesis of Hoyeraal-Hreidarsson Syndrome, a Complex Telomere Biology Disorder

PubMed Central

Glousker, Galina; Touzot, Fabien; Revy, Patrick; Tzfati, Yehuda; Savage, Sharon A.

2015-01-01

SUMMARY Hoyeraal-Hreidarsson (HH) syndrome is a multisystem genetic disorder characterized by very short telomeres and considered a clinically severe variant of dyskeratosis congenita (DC). The main cause of mortality, usually in early childhood, is bone marrow failure. Mutations in several telomere biology genes have been reported to cause HH in about 60% of the HH patients, but the genetic defects in the rest of the patients are still unknown. Understanding the aetiology of HH and its diverse manifestations is challenging because of the complexity of telomere biology and the multiple telomeric and non-telomeric functions played by telomere-associated proteins in processes such as telomere replication, telomere protection, DNA damage response and ribosome and spliceosome assembly. Here we review the known clinical complications, molecular defects and germline mutations associated with HH, and elucidate possible mechanistic explanations and remaining questions in our understanding of the disease. PMID:25940403

Diversity-oriented synthetic strategy for developing a chemical modulator of protein-protein interaction

NASA Astrophysics Data System (ADS)

Kim, Jonghoon; Jung, Jinjoo; Koo, Jaeyoung; Cho, Wansang; Lee, Won Seok; Kim, Chanwoo; Park, Wonwoo; Park, Seung Bum

2016-10-01

Diversity-oriented synthesis (DOS) can provide a collection of diverse and complex drug-like small molecules, which is critical in the development of new chemical probes for biological research of undruggable targets. However, the design and synthesis of small-molecule libraries with improved biological relevance as well as maximized molecular diversity represent a key challenge. Herein, we employ functional group-pairing strategy for the DOS of a chemical library containing privileged substructures, pyrimidodiazepine or pyrimidine moieties, as chemical navigators towards unexplored bioactive chemical space. To validate the utility of this DOS library, we identify a new small-molecule inhibitor of leucyl-tRNA synthetase-RagD protein-protein interaction, which regulates the amino acid-dependent activation of mechanistic target of rapamycin complex 1 signalling pathway. This work highlights that privileged substructure-based DOS strategy can be a powerful research tool for the construction of drug-like compounds to address challenging biological targets.

A network-based multi-target computational estimation scheme for anticoagulant activities of compounds.

PubMed

Li, Qian; Li, Xudong; Li, Canghai; Chen, Lirong; Song, Jun; Tang, Yalin; Xu, Xiaojie

2011-03-22

Traditional virtual screening method pays more attention on predicted binding affinity between drug molecule and target related to a certain disease instead of phenotypic data of drug molecule against disease system, as is often less effective on discovery of the drug which is used to treat many types of complex diseases. Virtual screening against a complex disease by general network estimation has become feasible with the development of network biology and system biology. More effective methods of computational estimation for the whole efficacy of a compound in a complex disease system are needed, given the distinct weightiness of the different target in a biological process and the standpoint that partial inhibition of several targets can be more efficient than the complete inhibition of a single target. We developed a novel approach by integrating the affinity predictions from multi-target docking studies with biological network efficiency analysis to estimate the anticoagulant activities of compounds. From results of network efficiency calculation for human clotting cascade, factor Xa and thrombin were identified as the two most fragile enzymes, while the catalytic reaction mediated by complex IXa:VIIIa and the formation of the complex VIIIa:IXa were recognized as the two most fragile biological matter in the human clotting cascade system. Furthermore, the method which combined network efficiency with molecular docking scores was applied to estimate the anticoagulant activities of a serial of argatroban intermediates and eight natural products respectively. The better correlation (r = 0.671) between the experimental data and the decrease of the network deficiency suggests that the approach could be a promising computational systems biology tool to aid identification of anticoagulant activities of compounds in drug discovery. This article proposes a network-based multi-target computational estimation method for anticoagulant activities of compounds by combining network efficiency analysis with scoring function from molecular docking.

A Network-Based Multi-Target Computational Estimation Scheme for Anticoagulant Activities of Compounds

PubMed Central

Li, Canghai; Chen, Lirong; Song, Jun; Tang, Yalin; Xu, Xiaojie

2011-01-01

Background Traditional virtual screening method pays more attention on predicted binding affinity between drug molecule and target related to a certain disease instead of phenotypic data of drug molecule against disease system, as is often less effective on discovery of the drug which is used to treat many types of complex diseases. Virtual screening against a complex disease by general network estimation has become feasible with the development of network biology and system biology. More effective methods of computational estimation for the whole efficacy of a compound in a complex disease system are needed, given the distinct weightiness of the different target in a biological process and the standpoint that partial inhibition of several targets can be more efficient than the complete inhibition of a single target. Methodology We developed a novel approach by integrating the affinity predictions from multi-target docking studies with biological network efficiency analysis to estimate the anticoagulant activities of compounds. From results of network efficiency calculation for human clotting cascade, factor Xa and thrombin were identified as the two most fragile enzymes, while the catalytic reaction mediated by complex IXa:VIIIa and the formation of the complex VIIIa:IXa were recognized as the two most fragile biological matter in the human clotting cascade system. Furthermore, the method which combined network efficiency with molecular docking scores was applied to estimate the anticoagulant activities of a serial of argatroban intermediates and eight natural products respectively. The better correlation (r = 0.671) between the experimental data and the decrease of the network deficiency suggests that the approach could be a promising computational systems biology tool to aid identification of anticoagulant activities of compounds in drug discovery. Conclusions This article proposes a network-based multi-target computational estimation method for anticoagulant activities of compounds by combining network efficiency analysis with scoring function from molecular docking. PMID:21445339

Contaminant Organic Complexes: Their Structure and Energetics in Surface Decontamination Processes

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

Satish C. B. Myneni

2005-12-13

Siderophores are biological macromolecules (400-2000 Da) released by bacteria in iron limiting situations to sequester Fe from iron oxyhydroxides and silicates in the natural environment. These molecules contain hydroxamate and phenolate functional groups, and exhibit very high affinity for Fe{sup 3+}. While several studies were conducted to understand the behavior of siderophores and their application to the metal sequestration and mineral dissolution, only a few of them have examined the molecular structure of siderophores and their interactions with metals and mineral surfaces in aqueous solutions. Improved understanding of the chemical state of different functional moieties in siderophores can assist inmore » the application of these biological molecules in actinide separation, sequestration and decontamination processes. The focus of our research group is to evaluate the (a) functional group chemistry of selected siderophores and their metal complexes in aqueous solutions, and (b) the nature of siderophore interactions at the mineral-water interfaces. We selected desferrioxamine B (desB), a hydroxamate siderophore, and its small structural analogue, acetohydroxamic acid (aHa), for this investigation. We examined the functional group chemistry of these molecules as a function of pH, and their complexation with aqueous and solid phase Fe(III). For solid phase Fe, we synthesized all naturally occurring Fe(III)-oxyhydroxides (goethite, lepidocrocite, akaganeite, feroxyhite) and hematite. We also synthesized Fe-oxides (goethite and hematite) of different sizes to evaluate the influence of particle size on mineral dissolution kinetics. We used a series of molecular techniques to explore the functional group chemistry of these molecules and their complexes. Infrared spectroscopy is used to specifically identify the variations in oxime group as a function of pH and Fe(III) complexation. Resonance Raman spectroscopy was used to evaluate the nature of hydroxamate binding in the case of Fe(III)-siderophore complexes and model ligands. Soft and hard X-ray spectroscopy techniques were used to examine the electronic structure of binding groups, and their local structural environment. The synchrotron X-ray studies were conducted at the Stanford Synchrotron Radiation Laboratory and at the Advanced Light Source (Lawrence Berkeley National Laboratory). These experimental vibrational and X-ray spectroscopy studies were complemented with density functional theory calculations. The highlight of this study is the evaluation of the fundamental electronic state information of the hydroxamate moiety in siderophores during deprotonation and Fe(III) complexation. The applications of soft X-ray studies are also new, and were applied, for the first time, to examine the chemistry of organic macromolecules in aqueous solutions.« less

X-ray emission spectroscopy of biomimetic Mn coordination complexes

DOE PAGES

Jensen, Scott C.; Davis, Katherine M.; Sullivan,

2017-05-19

Understanding the function of Mn ions in biological and chemical redox catalysis requires precise knowledge of their electronic structure. X-ray emission spectroscopy (XES) is an emerging technique with a growing application to biological and biomimetic systems. Here, we report an improved, cost-effective spectrometer used to analyze two biomimetic coordination compounds, [Mn IV(OH) 2(Me 2EBC)] 2+ and [Mn IV(O)(OH)(Me 2EBC)] +, the second of which contains a key Mn IV=O structural fragment. Despite having the same formal oxidation state (Mn IV) and tetradentate ligands, XES spectra from these two compounds demonstrate different electronic structures. Experimental measurements and DFT calculations yield differentmore » localized spin densities for the two complexes resulting from Mn IV–OH conversion to Mn IV=O. The relevance of the observed spectroscopic changes is discussed for applications in analyzing complex biological systems such as photosystem II. In conclusion, a model of the S 3 intermediate state of photosystem II containing a Mn IV=O fragment is compared to recent time-resolved X-ray diffraction data of the same state.« less

X-ray Emission Spectroscopy of Biomimetic Mn Coordination Complexes.

PubMed

Jensen, Scott C; Davis, Katherine M; Sullivan, Brendan; Hartzler, Daniel A; Seidler, Gerald T; Casa, Diego M; Kasman, Elina; Colmer, Hannah E; Massie, Allyssa A; Jackson, Timothy A; Pushkar, Yulia

2017-06-15

Understanding the function of Mn ions in biological and chemical redox catalysis requires precise knowledge of their electronic structure. X-ray emission spectroscopy (XES) is an emerging technique with a growing application to biological and biomimetic systems. Here, we report an improved, cost-effective spectrometer used to analyze two biomimetic coordination compounds, [Mn IV (OH) 2 (Me 2 EBC)] 2+ and [Mn IV (O)(OH)(Me 2 EBC)] + , the second of which contains a key Mn IV ═O structural fragment. Despite having the same formal oxidation state (Mn IV ) and tetradentate ligands, XES spectra from these two compounds demonstrate different electronic structures. Experimental measurements and DFT calculations yield different localized spin densities for the two complexes resulting from Mn IV -OH conversion to Mn IV ═O. The relevance of the observed spectroscopic changes is discussed for applications in analyzing complex biological systems such as photosystem II. A model of the S 3 intermediate state of photosystem II containing a Mn IV ═O fragment is compared to recent time-resolved X-ray diffraction data of the same state.

Cellular automata with object-oriented features for parallel molecular network modeling.

PubMed

Zhu, Hao; Wu, Yinghui; Huang, Sui; Sun, Yan; Dhar, Pawan

2005-06-01

Cellular automata are an important modeling paradigm for studying the dynamics of large, parallel systems composed of multiple, interacting components. However, to model biological systems, cellular automata need to be extended beyond the large-scale parallelism and intensive communication in order to capture two fundamental properties characteristic of complex biological systems: hierarchy and heterogeneity. This paper proposes extensions to a cellular automata language, Cellang, to meet this purpose. The extended language, with object-oriented features, can be used to describe the structure and activity of parallel molecular networks within cells. Capabilities of this new programming language include object structure to define molecular programs within a cell, floating-point data type and mathematical functions to perform quantitative computation, message passing capability to describe molecular interactions, as well as new operators, statements, and built-in functions. We discuss relevant programming issues of these features, including the object-oriented description of molecular interactions with molecule encapsulation, message passing, and the description of heterogeneity and anisotropy at the cell and molecule levels. By enabling the integration of modeling at the molecular level with system behavior at cell, tissue, organ, or even organism levels, the program will help improve our understanding of how complex and dynamic biological activities are generated and controlled by parallel functioning of molecular networks. Index Terms-Cellular automata, modeling, molecular network, object-oriented.

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.

microRNA regulation of T lymphocyte immunity: modulation of molecular networks responsible for T cell activation, differentiation and development

PubMed Central

Podshivalova, Katie; Salomon, Daniel R.

2014-01-01

MicroRNAs (miRNA) are a class of small non-coding RNAs that constitute an essential and evolutionarily conserved mechanism for post-transcriptional gene regulation. Multiple miRNAs have been described to play key roles in T lymphocyte development, differentiation and function. In this review we highlight the current literature regarding the differential expression of miRNAs in various models of mouse and human T cell biology and emphasize mechanistic understandings of miRNA regulation of thymocyte development, T cell activation, and differentiation into effector and memory subsets. We describe the participation of miRNAs in complex regulatory circuits shaping T cell proteomes in a context-dependent manner. It is striking that some miRNAs regulate multiple processes, while others only appear in limited functional contexts. It is also evident that the expression and function of specific miRNAs can differ between mouse and human systems. Ultimately, it is not always correct to simplify the complex events of T cell biology into a model driven by only one or two master regulator miRNAs. In reality, T cell activation and differentiation involves the expression of multiple miRNAs with many mRNA targets and thus, the true extent of miRNA regulation of T cell biology is likely far more vast than currently appreciated. PMID:24099302

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.

Chinese Herbal Medicine Meets Biological Networks of Complex Diseases: A Computational Perspective

PubMed Central

Gu, Shuo

2017-01-01

With the rapid development of cheminformatics, computational biology, and systems biology, great progress has been made recently in the computational research of Chinese herbal medicine with in-depth understanding towards pharmacognosy. This paper summarized these studies in the aspects of computational methods, traditional Chinese medicine (TCM) compound databases, and TCM network pharmacology. Furthermore, we chose arachidonic acid metabolic network as a case study to demonstrate the regulatory function of herbal medicine in the treatment of inflammation at network level. Finally, a computational workflow for the network-based TCM study, derived from our previous successful applications, was proposed. PMID:28690664

Chinese Herbal Medicine Meets Biological Networks of Complex Diseases: A Computational Perspective.

PubMed

Gu, Shuo; Pei, Jianfeng

2017-01-01

With the rapid development of cheminformatics, computational biology, and systems biology, great progress has been made recently in the computational research of Chinese herbal medicine with in-depth understanding towards pharmacognosy. This paper summarized these studies in the aspects of computational methods, traditional Chinese medicine (TCM) compound databases, and TCM network pharmacology. Furthermore, we chose arachidonic acid metabolic network as a case study to demonstrate the regulatory function of herbal medicine in the treatment of inflammation at network level. Finally, a computational workflow for the network-based TCM study, derived from our previous successful applications, was proposed.

UNDERSTANDING THE ROLE OF OZONE STRESS IN ALTERING BELOWGROUND PROCESSES

EPA Science Inventory

Forested ecosystems are comprised of tremendous biological diversity and functional complexity both above and belowground. Soil ecosystems are known to contain thousands of species, with many more that have not yet been identified. Soil heterotrophic organisms depend on green p...

The Importance of Normalization on Large and Heterogeneous Microarray Datasets

EPA Science Inventory

DNA microarray technology is a powerful functional genomics tool increasingly used for investigating global gene expression in environmental studies. Microarrays can also be used in identifying biological networks, as they give insight on the complex gene-to-gene interactions, ne...

MECHANISMS OF MALE REPRODUCTIVE TOXICITY: BED, BATH AND BEYOND

EPA Science Inventory

Male reproductive function depends upon the integration of a great number of highly complex biological processes and their endocrine support. Therefore it is not surprising that male reproductive health can be impaired by exposures to drugs and environmental toxicants that impact...

Carbohydrase Systems of Saccharophagus degradans Degrading Marine Complex Polysaccharides

PubMed Central

Hutcheson, Steven W.; Zhang, Haitao; Suvorov, Maxim

2011-01-01

Saccharophagus degradans 2–40 is a γ-subgroup proteobacterium capable of using many of the complex polysaccharides found in the marine environment for growth. To utilize these complex polysaccharides, this bacterium produces a plethora of carbohydrases dedicated to the processing of a carbohydrate class. Aiding in the identification of the contributing genes and enzymes is the known genome sequence for this bacterium. This review catalogs the genes and enzymes of the S. degradans genome that are likely to function in the systems for the utilization of agar, alginate, α- and β-glucans, chitin, mannans, pectins, and xylans and discusses the cell biology and genetics of each system as it functions to transfer carbon back to the bacterium. PMID:21731555

BIOLOGICAL NETWORK EXPLORATION WITH CYTOSCAPE 3

PubMed Central

Su, Gang; Morris, John H.; Demchak, Barry; Bader, Gary D.

2014-01-01

Cytoscape is one of the most popular open-source software tools for the visual exploration of biomedical networks composed of protein, gene and other types of interactions. It offers researchers a versatile and interactive visualization interface for exploring complex biological interconnections supported by diverse annotation and experimental data, thereby facilitating research tasks such as predicting gene function and pathway construction. Cytoscape provides core functionality to load, visualize, search, filter and save networks, and hundreds of Apps extend this functionality to address specific research needs. The latest generation of Cytoscape (version 3.0 and later) has substantial improvements in function, user interface and performance relative to previous versions. This protocol aims to jump-start new users with specific protocols for basic Cytoscape functions, such as installing Cytoscape and Cytoscape Apps, loading data, visualizing and navigating the network, visualizing network associated data (attributes) and identifying clusters. It also highlights new features that benefit experienced users. PMID:25199793

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.

Advanced Engineering Strategies for Periodontal Complex Regeneration.

PubMed

Park, Chan Ho; Kim, Kyoung-Hwa; Lee, Yong-Moo; Seol, Yang-Jo

2016-01-18

The regeneration and integration of multiple tissue types is critical for efforts to restore the function of musculoskeletal complex. In particular, the neogenesis of periodontal constructs for systematic tooth-supporting functions is a current challenge due to micron-scaled tissue compartmentalization, oblique/perpendicular orientations of fibrous connective tissues to the tooth root surface and the orchestration of multiple regenerated tissues. Although there have been various biological and biochemical achievements, periodontal tissue regeneration remains limited and unpredictable. The purpose of this paper is to discuss current advanced engineering approaches for periodontal complex formations; computer-designed, customized scaffolding architectures; cell sheet technology-based multi-phasic approaches; and patient-specific constructs using bioresorbable polymeric material and 3-D printing technology for clinical application. The review covers various advanced technologies for periodontal complex regeneration and state-of-the-art therapeutic avenues in periodontal tissue engineering.

Rapamycin-induced oligomer formation system of FRB-FKBP fusion proteins.

PubMed

Inobe, Tomonao; Nukina, Nobuyuki

2016-07-01

Most proteins form larger protein complexes and perform multiple functions in the cell. Thus, artificial regulation of protein complex formation controls the cellular functions that involve protein complexes. Although several artificial dimerization systems have already been used for numerous applications in biomedical research, cellular protein complexes form not only simple dimers but also larger oligomers. In this study, we showed that fusion proteins comprising the induced heterodimer formation proteins FRB and FKBP formed various oligomers upon addition of rapamycin. By adjusting the configuration of fusion proteins, we succeeded in generating an inducible tetramer formation system. Proteins of interest also formed tetramers by fusing to the inducible tetramer formation system, which exhibits its utility in a broad range of biological applications. Copyright © 2015 The Society for Biotechnology, Japan. Published by Elsevier B.V. All rights reserved.

A bio-inspired design of live cell biosensors

NASA Astrophysics Data System (ADS)

Marcek Chorvatova, A.; Teplicky, T.; Pavlinska, Z.; Kronekova, Z.; Trelova, D.; Razga, F.; Nemethova, V.; Uhelska, L.; Lacik, I.; Chorvat, D.

2018-02-01

The last decade has witnessed a rapid growth of nanoscale-oriented biosensors that becomes one of the most promising and rapidly growing areas of modern research. Despite significant advancements in conception of such biosensors, most are based at evaluation of molecular, or protein interactions. It is however becoming increasingly evident that functionality of a living system does not reside in genome or in individual proteins, as no real biological functionality is expressed at these levels. Instead, to comprehend the true functioning of a biological system, it is essential to understand the integrative physiological behavior of the complex molecular interactions in their natural environment and precise spatio-temporal topology. In this contribution we therefore present a new concept for creation of biosensors, bio-inspired from true functioning of living cells, while monitoring their endogenous fluorescence, or autofluorescence.

Cheering for Team Science | Office of Cancer Genomics

Cancer.gov

As a graduate student, my PhD thesis focused on the function of a single human gene, within a genome of some 20,000 genes. Although this sometimes made my work seem insignificant, I was reminded of how important one small piece of a large puzzle can be when I discovered all the ways the gene knockout cells were disadvantaged. Studying the basic biology of our cells made me appreciate the beautiful complexity of human biology.

Noninvasive imaging of protein-protein interactions in living organisms.

PubMed

Haberkorn, Uwe; Altmann, Annette

2003-06-01

Genomic research is expected to generate new types of complex observational data, changing the types of experiments as well as our understanding of biological processes. The investigation and definition of relationships among proteins is essential for understanding the function of each gene and the mechanisms of biological processes that specific genes are involved in. Recently, a study by Paulmurugan et al. demonstrated a tool for in vivo noninvasive imaging of protein-protein interactions and intracellular networks.

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.

Detecting UV-lesions in the genome: The modular CRL4 ubiquitin ligase does it best!

PubMed

Scrima, Andrea; Fischer, Eric S; Lingaraju, Gondichatnahalli M; Böhm, Kerstin; Cavadini, Simone; Thomä, Nicolas H

2011-09-16

The DDB1-DDB2-CUL4-RBX1 complex serves as the primary detection device for UV-induced lesions in the genome. It simultaneously functions as a CUL4 type E3 ubiquitin ligase. We review the current understanding of this dual function ubiquitin ligase and damage detection complex. The DDB2 damage binding module is merely one of a large family of possible DDB1-CUL4 associated factors (DCAF), most of which are substrate receptors for other DDB1-CUL4 complexes. DDB2 and the Cockayne-syndrome A protein (CSA) function in nucleotide excision repair, whereas the remaining receptors operate in a wide range of other biological pathways. We will examine the modular architecture of DDB1-CUL4 in complex with DDB2, CSA and CDT2 focusing on shared architectural, targeting and regulatory principles. Copyright © 2011 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.

Evolution of an intricate J-protein network driving protein disaggregation in eukaryotes.

PubMed

Nillegoda, Nadinath B; Stank, Antonia; Malinverni, Duccio; Alberts, Niels; Szlachcic, Anna; Barducci, Alessandro; De Los Rios, Paolo; Wade, Rebecca C; Bukau, Bernd

2017-05-15

Hsp70 participates in a broad spectrum of protein folding processes extending from nascent chain folding to protein disaggregation. This versatility in function is achieved through a diverse family of J-protein cochaperones that select substrates for Hsp70. Substrate selection is further tuned by transient complexation between different classes of J-proteins, which expands the range of protein aggregates targeted by metazoan Hsp70 for disaggregation. We assessed the prevalence and evolutionary conservation of J-protein complexation and cooperation in disaggregation. We find the emergence of a eukaryote-specific signature for interclass complexation of canonical J-proteins. Consistently, complexes exist in yeast and human cells, but not in bacteria, and correlate with cooperative action in disaggregation in vitro. Signature alterations exclude some J-proteins from networking, which ensures correct J-protein pairing, functional network integrity and J-protein specialization. This fundamental change in J-protein biology during the prokaryote-to-eukaryote transition allows for increased fine-tuning and broadening of Hsp70 function in eukaryotes.

Evolution of an ancient protein function involved in organized multicellularity in animals

PubMed Central

Anderson, Douglas P; Whitney, Dustin S; Hanson-Smith, Victor; Woznica, Arielle; Campodonico-Burnett, William; Volkman, Brian F; King, Nicole; Thornton, Joseph W; Prehoda, Kenneth E

2016-01-01

To form and maintain organized tissues, multicellular organisms orient their mitotic spindles relative to neighboring cells. A molecular complex scaffolded by the GK protein-interaction domain (GKPID) mediates spindle orientation in diverse animal taxa by linking microtubule motor proteins to a marker protein on the cell cortex localized by external cues. Here we illuminate how this complex evolved and commandeered control of spindle orientation from a more ancient mechanism. The complex was assembled through a series of molecular exploitation events, one of which – the evolution of GKPID’s capacity to bind the cortical marker protein – can be recapitulated by reintroducing a single historical substitution into the reconstructed ancestral GKPID. This change revealed and repurposed an ancient molecular surface that previously had a radically different function. We show how the physical simplicity of this binding interface enabled the evolution of a new protein function now essential to the biological complexity of many animals. DOI: http://dx.doi.org/10.7554/eLife.10147.001 PMID:26740169

microRNAs Databases: Developmental Methodologies, Structural and Functional Annotations.

PubMed

Singh, Nagendra Kumar

2017-09-01

microRNA (miRNA) is an endogenous and evolutionary conserved non-coding RNA, involved in post-transcriptional process as gene repressor and mRNA cleavage through RNA-induced silencing complex (RISC) formation. In RISC, miRNA binds in complementary base pair with targeted mRNA along with Argonaut proteins complex, causes gene repression or endonucleolytic cleavage of mRNAs and results in many diseases and syndromes. After the discovery of miRNA lin-4 and let-7, subsequently large numbers of miRNAs were discovered by low-throughput and high-throughput experimental techniques along with computational process in various biological and metabolic processes. The miRNAs are important non-coding RNA for understanding the complex biological phenomena of organism because it controls the gene regulation. This paper reviews miRNA databases with structural and functional annotations developed by various researchers. These databases contain structural and functional information of animal, plant and virus miRNAs including miRNAs-associated diseases, stress resistance in plant, miRNAs take part in various biological processes, effect of miRNAs interaction on drugs and environment, effect of variance on miRNAs, miRNAs gene expression analysis, sequence of miRNAs, structure of miRNAs. This review focuses on the developmental methodology of miRNA databases such as computational tools and methods used for extraction of miRNAs annotation from different resources or through experiment. This study also discusses the efficiency of user interface design of every database along with current entry and annotations of miRNA (pathways, gene ontology, disease ontology, etc.). Here, an integrated schematic diagram of construction process for databases is also drawn along with tabular and graphical comparison of various types of entries in different databases. Aim of this paper is to present the importance of miRNAs-related resources at a single place.

Critical elements in the development of cell therapy potency assays for ischemic conditions.

PubMed

Porat, Yael; Abraham, Eytan; Karnieli, Ohad; Nahum, Sagi; Woda, Juliana; Zylberberg, Claudia

2015-07-01

A successful potency assay for a cell therapy product (CTP) used in the treatment of ischemic conditions should quantitatively measure relevant biological properties that predict therapeutic activity. This is especially challenging because of numerous degrees of complexity stemming from factors that include a multifactorial complex mechanism of action, cell source, inherent cell characteristics, culture method, administration mode and the in vivo conditions to which the cells are exposed. The expected biological function of a CTP encompasses complex interactions that range from a biochemical, metabolic or immunological activity to structural replacement of damaged tissue or organ. Therefore, the requirements for full characterization of the active substance with respect to biological function could be taxing. Moreover, the specific mechanism of action is often difficult to pinpoint to a specific molecular entity; rather, it is more dependent on the functionality of the cellular components acting in a in a multifactorial fashion. In the case of ischemic conditions, the cell therapy mechanism of action can vary from angiogenesis, vasculogenesis and arteriogenesis that may activate different pathways and clinical outcomes. The CTP cellular attributes with relation to the suggested mechanism of action can be used for the development of quantitative and reproducible analytical potency assays. CTPs selected and released on the basis of such potency assays should have the highest probability of providing meaningful clinical benefit for patients. This White Paper will discuss and give examples for key elements in the development of a potency assay for treatment of ischemic disorders treated by the use of CTPs. Copyright © 2015 International Society for Cellular Therapy. Published by Elsevier Inc. All rights reserved.

Category Theoretic Analysis of Hierarchical Protein Materials and Social Networks

PubMed Central

Spivak, David I.; Giesa, Tristan; Wood, Elizabeth; Buehler, Markus J.

2011-01-01

Materials in biology span all the scales from Angstroms to meters and typically consist of complex hierarchical assemblies of simple building blocks. Here we describe an application of category theory to describe structural and resulting functional properties of biological protein materials by developing so-called ologs. An olog is like a “concept web” or “semantic network” except that it follows a rigorous mathematical formulation based on category theory. This key difference ensures that an olog is unambiguous, highly adaptable to evolution and change, and suitable for sharing concepts with other olog. We consider simple cases of beta-helical and amyloid-like protein filaments subjected to axial extension and develop an olog representation of their structural and resulting mechanical properties. We also construct a representation of a social network in which people send text-messages to their nearest neighbors and act as a team to perform a task. We show that the olog for the protein and the olog for the social network feature identical category-theoretic representations, and we proceed to precisely explicate the analogy or isomorphism between them. The examples presented here demonstrate that the intrinsic nature of a complex system, which in particular includes a precise relationship between structure and function at different hierarchical levels, can be effectively represented by an olog. This, in turn, allows for comparative studies between disparate materials or fields of application, and results in novel approaches to derive functionality in the design of de novo hierarchical systems. We discuss opportunities and challenges associated with the description of complex biological materials by using ologs as a powerful tool for analysis and design in the context of materiomics, and we present the potential impact of this approach for engineering, life sciences, and medicine. PMID:21931622

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.

Different design of enzyme-triggered CO-releasing molecules (ET-CORMs) reveals quantitative differences in biological activities in terms of toxicity and inflammation.

PubMed

Stamellou, E; Storz, D; Botov, S; Ntasis, E; Wedel, J; Sollazzo, S; Krämer, B K; van Son, W; Seelen, M; Schmalz, H G; Schmidt, A; Hafner, M; Yard, B A

2014-01-01

Acyloxydiene-Fe(CO)3 complexes can act as enzyme-triggered CO-releasing molecules (ET-CORMs). Their biological activity strongly depends on the mother compound from which they are derived, i.e. cyclohexenone or cyclohexanedione, and on the position of the ester functionality they harbour. The present study addresses if the latter characteristic affects CO release, if cytotoxicity of ET-CORMs is mediated through iron release or inhibition of cell respiration and to what extent cyclohexenone and cyclohexanedione derived ET-CORMs differ in their ability to counteract TNF-α mediated inflammation. Irrespective of the formulation (DMSO or cyclodextrin), toxicity in HUVEC was significantly higher for ET-CORMs bearing the ester functionality at the outer (rac-4), as compared to the inner (rac-1) position of the cyclohexenone moiety. This was paralleled by an increased CO release from the former ET-CORM. Toxicity was not mediated via iron as EC50 values for rac-4 were significantly lower than for FeCl2 or FeCl3 and were not influenced by iron chelation. ATP depletion preceded toxicity suggesting impaired cell respiration as putative cause for cell death. In long-term HUVEC cultures inhibition of VCAM-1 expression by rac-1 waned in time, while for the cyclohexanedione derived rac-8 inhibition seems to increase. NFκB was inhibited by both rac-1 and rac-8 independent of IκBα degradation. Both ET-CORMs activated Nrf-2 and consequently induced the expression of HO-1. This study further provides a rational framework for designing acyloxydiene-Fe(CO)3 complexes as ET-CORMs with differential CO release and biological activities. We also provide a better understanding of how these complexes affect cell-biology in mechanistic terms.

Integrative, Dynamic Structural Biology at Atomic Resolution—It’s About Time

PubMed Central

van den Bedem, Henry; Fraser, James S.

2015-01-01

Biomolecules adopt a dynamic ensemble of conformations, each with the potential to interact with binding partners or perform the chemical reactions required for a multitude of cellular functions. Recent advances in X-ray crystallography, Nuclear Magnetic Resonance (NMR) spectroscopy, and other techniques are helping us realize the dream of seeing—in atomic detail—how different parts of biomolecules exchange between functional sub-states using concerted motions. Integrative structural biology has advanced our understanding of the formation of large macromolecular complexes and how their components interact in assemblies by leveraging data from many low-resolution methods. Here, we review the growing opportunities for integrative, dynamic structural biology at the atomic scale, contending there is increasing synergistic potential between X-ray crystallography, NMR, and computer simulations to reveal a structural basis for protein conformational dynamics at high resolution. PMID:25825836

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

A new approach to interpretation of heterogeneity of fluorescence decay in complex biological systems

NASA Astrophysics Data System (ADS)

Wlodarczyk, Jakub; Kierdaszuk, Borys

2005-08-01

Decays of tyrosine fluorescence in protein-ligand complexes are described by a model of continuous distribution of fluorescence lifetimes. Resulted analytical power-like decay function provides good fits to highly complex fluorescence kinetics. Moreover, this is a manifestation of so-called Tsallis q-exponential function, which is suitable for description of the systems with long-range interactions, memory effect, as well as with fluctuations of the characteristic lifetime of fluorescence. The proposed decay functions were applied to analysis of fluorescence decays of tyrosine in a protein, i.e. the enzyme purine nucleoside phosphorylase from E. coli (the product of the deoD gene), free in aqueous solution and in a complex with formycin A (an inhibitor) and orthophosphate (a co-substrate). The power-like function provides new information about enzyme-ligand complex formation based on the physically justified heterogeneity parameter directly related to the lifetime distribution. A measure of the heterogeneity parameter in the enzyme systems is provided by a variance of fluorescence lifetime distribution. The possible number of deactivation channels and excited state mean lifetime can be easily derived without a priori knowledge of the complexity of studied system. Moreover, proposed model is simpler then traditional multi-exponential one, and better describes heterogeneous nature of studied systems.

FUSE: a profit maximization approach for functional summarization of biological networks.

PubMed

Seah, Boon-Siew; Bhowmick, Sourav S; Dewey, C Forbes; Yu, Hanry

2012-03-21

The availability of large-scale curated protein interaction datasets has given rise to the opportunity to investigate higher level organization and modularity within the protein interaction network (PPI) using graph theoretic analysis. Despite the recent progress, systems level analysis of PPIS remains a daunting task as it is challenging to make sense out of the deluge of high-dimensional interaction data. Specifically, techniques that automatically abstract and summarize PPIS at multiple resolutions to provide high level views of its functional landscape are still lacking. We present a novel data-driven and generic algorithm called FUSE (Functional Summary Generator) that generates functional maps of a PPI at different levels of organization, from broad process-process level interactions to in-depth complex-complex level interactions, through a pro t maximization approach that exploits Minimum Description Length (MDL) principle to maximize information gain of the summary graph while satisfying the level of detail constraint. We evaluate the performance of FUSE on several real-world PPIS. We also compare FUSE to state-of-the-art graph clustering methods with GO term enrichment by constructing the biological process landscape of the PPIS. Using AD network as our case study, we further demonstrate the ability of FUSE to quickly summarize the network and identify many different processes and complexes that regulate it. Finally, we study the higher-order connectivity of the human PPI. By simultaneously evaluating interaction and annotation data, FUSE abstracts higher-order interaction maps by reducing the details of the underlying PPI to form a functional summary graph of interconnected functional clusters. Our results demonstrate its effectiveness and superiority over state-of-the-art graph clustering methods with GO term enrichment.

Getting a Grip on Complexes

PubMed Central

Nie, Yan; Viola, Cristina; Bieniossek, Christoph; Trowitzsch, Simon; Vijay-achandran, Lakshmi Sumitra; Chaillet, Maxime; Garzoni, Frederic; Berger, Imre

2009-01-01

We are witnessing tremendous advances in our understanding of the organization of life. Complete genomes are being deciphered with ever increasing speed and accuracy, thereby setting the stage for addressing the entire gene product repertoire of cells, towards understanding whole biological systems. Advances in bioinformatics and mass spectrometric techniques have revealed the multitude of interactions present in the proteome. Multiprotein complexes are emerging as a paramount cornerstone of biological activity, as many proteins appear to participate, stably or transiently, in large multisubunit assemblies. Analysis of the architecture of these assemblies and their manifold interactions is imperative for understanding their function at the molecular level. Structural genomics efforts have fostered the development of many technologies towards achieving the throughput required for studying system-wide single proteins and small interaction motifs at high resolution. The present shift in focus towards large multiprotein complexes, in particular in eukaryotes, now calls for a likewise concerted effort to develop and provide new technologies that are urgently required to produce in quality and quantity the plethora of multiprotein assemblies that form the complexome, and to routinely study their structure and function at the molecular level. Current efforts towards this objective are summarized and reviewed in this contribution. PMID:20514218

Site-specific identification of heparan and chondroitin sulfate glycosaminoglycans in hybrid proteoglycans.

PubMed

Noborn, Fredrik; Gomez Toledo, Alejandro; Green, Anders; Nasir, Waqas; Sihlbom, Carina; Nilsson, Jonas; Larson, Göran

2016-10-03

Heparan sulfate (HS) and chondroitin sulfate (CS) are complex polysaccharides that regulate important biological pathways in virtually all metazoan organisms. The polysaccharides often display opposite effects on cell functions with HS and CS structural motifs presenting unique binding sites for specific ligands. Still, the mechanisms by which glycan biosynthesis generates complex HS and CS polysaccharides required for the regulation of mammalian physiology remain elusive. Here we present a glycoproteomic approach that identifies and differentiates between HS and CS attachment sites and provides identity to the core proteins. Glycopeptides were prepared from perlecan, a complex proteoglycan known to be substituted with both HS and CS chains, further digested with heparinase or chondroitinase ABC to reduce the HS and CS chain lengths respectively, and thereafter analyzed by nLC-MS/MS. This protocol enabled the identification of three consensus HS sites and one hybrid site, carrying either a HS or a CS chain. Inspection of the amino acid sequence at the hybrid attachment locus indicates that certain peptide motifs may encode for the chain type selection process. This analytical approach will become useful when addressing fundamental questions in basic biology specifically in elucidating the functional roles of site-specific glycosylations of proteoglycans.

Modulation of electronic structures of bases through DNA recognition of protein.

PubMed

Hagiwara, Yohsuke; Kino, Hiori; Tateno, Masaru

2010-04-21

The effects of environmental structures on the electronic states of functional regions in a fully solvated DNA·protein complex were investigated using combined ab initio quantum mechanics/molecular mechanics calculations. A complex of a transcriptional factor, PU.1, and the target DNA was used for the calculations. The effects of solvent on the energies of molecular orbitals (MOs) of some DNA bases strongly correlate with the magnitude of masking of the DNA bases from the solvent by the protein. In the complex, PU.1 causes a variation in the magnitude among DNA bases by means of directly recognizing the DNA bases through hydrogen bonds and inducing structural changes of the DNA structure from the canonical one. Thus, the strong correlation found in this study is the first evidence showing the close quantitative relationship between recognition modes of DNA bases and the energy levels of the corresponding MOs. Thus, it has been revealed that the electronic state of each base is highly regulated and organized by the DNA recognition of the protein. Other biological macromolecular systems can be expected to also possess similar modulation mechanisms, suggesting that this finding provides a novel basis for the understanding for the regulation functions of biological macromolecular systems.

Quantitative interaction analysis permits molecular insights into functional NOX4 NADPH oxidase heterodimer assembly.

PubMed

O'Neill, Sharon; Mathis, Magalie; Kovačič, Lidija; Zhang, Suisheng; Reinhardt, Jürgen; Scholz, Dimitri; Schopfer, Ulrich; Bouhelal, Rochdi; Knaus, Ulla G

2018-06-08

Protein-protein interactions critically regulate many biological systems, but quantifying functional assembly of multipass membrane complexes in their native context is still challenging. Here, we combined modeling-assisted protein modification and information from human disease variants with a minimal-size fusion tag, split-luciferase-based approach to probe assembly of the NADPH oxidase 4 (NOX4)-p22 phox enzyme, an integral membrane complex with unresolved structure, which is required for electron transfer and generation of reactive oxygen species (ROS). Integrated analyses of heterodimerization, trafficking, and catalytic activity identified determinants for the NOX4-p22 phox interaction, such as heme incorporation into NOX4 and hot spot residues in transmembrane domains 1 and 4 in p22 phox Moreover, their effect on NOX4 maturation and ROS generation was analyzed. We propose that this reversible and quantitative protein-protein interaction technique with its small split-fragment approach will provide a protein engineering and discovery tool not only for NOX research, but also for other intricate membrane protein complexes, and may thereby facilitate new drug discovery strategies for managing NOX-associated diseases. © 2018 by The American Society for Biochemistry and Molecular Biology, Inc.

Mediator-dependent Nuclear Receptor Functions

PubMed Central

Chen, Wei; Roeder, Robert

2011-01-01

As gene-specific transcription factors, nuclear hormone receptors are broadly involved in many important biological processes. Their function on target genes requires the stepwise assembly of different coactivator complexes that facilitate chromatin remodeling and subsequent preinitiation complex (PIC) formation and function. Mediator has proved to be a crucial, and general, nuclear receptor-interacting coactivator, with demonstrated functions in transcription steps ranging from chromatin remodeling to subsequent PIC formation and function. Here we discuss (i) our current understanding of pathways that nuclear receptors and other interacting cofactors employ to recruit Mediator to target gene enhancers and promoters, including conditional requirements for the strong NR-Mediator interactions mediated by the NR AF2 domain and the MED1 LXXLLL motifs and (ii) mechanisms by which Mediator acts to transmit signals from enhancer-bound nuclear receptors to the general transcription machinery at core promoters to effect PIC formation and function. PMID:21854863

Bioengineering strategies to generate artificial protein complexes.

PubMed

Kim, Heejae; Siu, Ka-Hei; Raeeszadeh-Sarmazdeh, Maryam; Sun, Qing; Chen, Qi; Chen, Wilfred

2015-08-01

For many applications, increasing synergy between distinct proteins through organization is important for the specificity, regulation, and overall reaction efficiency. Although there are many examples of protein complexes in nature, a generalized method to create these complexes remains elusive. Many conventional techniques such as random chemical conjugation, physical adsorption onto surfaces, and encapsulation within matrices are imprecise approaches and can lead to deactivation of protein native functionalities. More "bio-friendly" approaches such as genetically fused proteins and biological scaffolds often can result in low yields and low complex stability. Alternatively, site-specific protein conjugation or ligation can generate artificial protein complexes that preserve the native functionalities of protein domains and maintain stability through covalent bonds. In this review, we describe three distinct methods to synthesize artificial protein complexes (genetic incorPoration of unnatural amino acids to introduce bio-orthogonal azide and alkyne groups to proteins, split-intein based expressed protein ligation, and sortase mediated ligation) and highlight interesting applications for each technique. © 2015 Wiley Periodicals, Inc.

Complexes of the ATP-dependent Lon protease and DNA aptamers with G-quadruplexes as a model for developing a nanosensor biomagnetic immunoassay system

NASA Astrophysics Data System (ADS)

Spiridonova, V. A.; Sizov, V. A.; Kuzmenko, E. O.; Melnichuk, A. V.; Oleinichenko, E. A.; Kudzhaev, A. M.; Rotanova, T. V.; Snigirev, O. V.

2017-07-01

The binding to Lon protease through biotinylated aptamers whose structures contain G-quadruplex fragments with magnetic nanoparticles (MNPs) functionalized by streptavidin was investigated. The conditions of binding of target aptamers to MNPs are met. The resulting complexes are proposed for detection of Lon protease in different biological sources and for constructing a novel biomagnetic nanosensor immunoassay system.

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.

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.

STRIPAK complexes: structure, biological function, and involvement in human diseases.

PubMed

Hwang, Juyeon; Pallas, David C

2014-02-01

The mammalian striatin family consists of three proteins, striatin, S/G2 nuclear autoantigen, and zinedin. Striatin family members have no intrinsic catalytic activity, but rather function as scaffolding proteins. Remarkably, they organize multiple diverse, large signaling complexes that participate in a variety of cellular processes. Moreover, they appear to be regulatory/targeting subunits for the major eukaryotic serine/threonine protein phosphatase 2A. In addition, striatin family members associate with germinal center kinase III kinases as well as other novel components, earning these assemblies the name striatin-interacting phosphatase and kinase (STRIPAK) complexes. Recently, there has been a great increase in functional and mechanistic studies aimed at identifying and understanding the roles of STRIPAK and STRIPAK-like complexes in cellular processes of multiple organisms. These studies have identified novel STRIPAK and STRIPAK-like complexes and have explored their roles in specific signaling pathways. Together, the results of these studies have sparked increased interest in striatin family complexes because they have revealed roles in signaling, cell cycle control, apoptosis, vesicular trafficking, Golgi assembly, cell polarity, cell migration, neural and vascular development, and cardiac function. Moreover, STRIPAK complexes have been connected to clinical conditions, including cardiac disease, diabetes, autism, and cerebral cavernous malformation. In this review, we discuss the expression, localization, and protein domain structure of striatin family members. Then we consider the diverse complexes these proteins and their homologs form in various organisms, emphasizing what is known regarding function and regulation. Finally, we explore possible roles of striatin family complexes in disease, especially cerebral cavernous malformation. Copyright © 2013 Elsevier Ltd. All rights reserved.

Using biotechnology and genomics to improve biotic and abiotic stress in apple

USDA-ARS?s Scientific Manuscript database

Genomic sequencing, molecular biology, and transformation technologies are providing valuable tools to better understand the complexity of how plants develop, function, and respond to biotic and abiotic stress. These approaches should complement but not replace a solid understanding of whole plant ...

Structural and functional diversity in Listeria cell wall teichoic acids.

PubMed

Shen, Yang; Boulos, Samy; Sumrall, Eric; Gerber, Benjamin; Julian-Rodero, Alicia; Eugster, Marcel R; Fieseler, Lars; Nyström, Laura; Ebert, Marc-Olivier; Loessner, Martin J

2017-10-27

Wall teichoic acids (WTAs) are the most abundant glycopolymers found on the cell wall of many Gram-positive bacteria, whose diverse surface structures play key roles in multiple biological processes. Despite recent technological advances in glycan analysis, structural elucidation of WTAs remains challenging due to their complex nature. Here, we employed a combination of ultra-performance liquid chromatography-coupled electrospray ionization tandem-MS/MS and NMR to determine the structural complexity of WTAs from Listeria species. We unveiled more than 10 different types of WTA polymers that vary in their linkage and repeating units. Disparity in GlcNAc to ribitol connectivity, as well as variable O -acetylation and glycosylation of GlcNAc contribute to the structural diversity of WTAs. Notably, SPR analysis indicated that constitution of WTA determines the recognition by bacteriophage endolysins. Collectively, these findings provide detailed insight into Listeria cell wall-associated carbohydrates, and will guide further studies on the structure-function relationship of WTAs. © 2017 by The American Society for Biochemistry and Molecular Biology, Inc.

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

Structural and molecular interrogation of intact biological systems

PubMed Central

Chung, Kwanghun; Wallace, Jenelle; Kim, Sung-Yon; Kalyanasundaram, Sandhiya; Andalman, Aaron S.; Davidson, Thomas J.; Mirzabekov, Julie J.; Zalocusky, Kelly A.; Mattis, Joanna; Denisin, Aleksandra K.; Pak, Sally; Bernstein, Hannah; Ramakrishnan, Charu; Grosenick, Logan; Gradinaru, Viviana; Deisseroth, Karl

2014-01-01

Obtaining high-resolution information from a complex system, while maintaining the global perspective needed to understand system function, represents a key challenge in biology. Here we address this challenge with a method (termed CLARITY) for the transformation of intact tissue into a nanoporous hydrogel-hybridized form (crosslinked to a three-dimensional network of hydrophilic polymers) that is fully assembled but optically transparent and macromolecule-permeable. Using mouse brains, we show intact-tissue imaging of long-range projections, local circuit wiring, cellular relationships, subcellular structures, protein complexes, nucleic acids and neurotransmitters. CLARITY also enables intact-tissue in situ hybridization, immunohistochemistry with multiple rounds of staining and de-staining in non-sectioned tissue, and antibody labelling throughout the intact adult mouse brain. Finally, we show that CLARITY enables fine structural analysis of clinical samples, including non-sectioned human tissue from a neuropsychiatric-disease setting, establishing a path for the transmutation of human tissue into a stable, intact and accessible form suitable for probing structural and molecular underpinnings of physiological function and disease. PMID:23575631

Semiconductor nanowires: A platform for nanoscience and nanotechnology

PubMed Central

Lieber, Charles M.

2012-01-01

Advances in nanoscience and nanotechnology critically depend on the development of nanostructures whose properties are controlled during synthesis. We focus on this critical concept using semiconductor nanowires, which provide the capability through design and rational synthesis to realize unprecedented structural and functional complexity in building blocks as a platform material. First, a brief review of the synthesis of complex modulated nanowires in which rational design and synthesis can be used to precisely control composition, structure, and, most recently, structural topology is discussed. Second, the unique functional characteristics emerging from our exquisite control of nanowire materials are illustrated using several selected examples from nanoelectronics and nano-enabled energy. Finally, the remarkable power of nanowire building blocks is further highlighted through their capability to create unprecedented, active electronic interfaces with biological systems. Recent work pushing the limits of both multiplexed extracellular recording at the single-cell level and the first examples of intracellular recording is described, as well as the prospects for truly blurring the distinction between nonliving nanoelectronic and living biological systems. PMID:22707850

Deterministic Integration of Biological and Soft Materials onto 3D Microscale Cellular Frameworks

PubMed Central

McCracken, Joselle M.; Xu, Sheng; Badea, Adina; Jang, Kyung-In; Yan, Zheng; Wetzel, David J.; Nan, Kewang; Lin, Qing; Han, Mengdi; Anderson, Mikayla A.; Lee, Jung Woo; Wei, Zijun; Pharr, Matt; Wang, Renhan; Su, Jessica; Rubakhin, Stanislav S.; Sweedler, Jonathan V.

2018-01-01

Complex 3D organizations of materials represent ubiquitous structural motifs found in the most sophisticated forms of matter, the most notable of which are in life-sustaining hierarchical structures found in biology, but where simpler examples also exist as dense multilayered constructs in high-performance electronics. Each class of system evinces specific enabling forms of assembly to establish their functional organization at length scales not dissimilar to tissue-level constructs. This study describes materials and means of assembly that extend and join these disparate systems—schemes for the functional integration of soft and biological materials with synthetic 3D microscale, open frameworks that can leverage the most advanced forms of multilayer electronic technologies, including device-grade semiconductors such as monocrystalline silicon. Cellular migration behaviors, temporal dependencies of their growth, and contact guidance cues provided by the nonplanarity of these frameworks illustrate design criteria useful for their functional integration with living matter (e.g., NIH 3T3 fibroblast and primary rat dorsal root ganglion cell cultures). PMID:29552634

RNA Structures as Mediators of Neurological Diseases and as Drug Targets.

PubMed

Bernat, Viachaslau; Disney, Matthew D

2015-07-01

RNAs adopt diverse folded structures that are essential for function and thus play critical roles in cellular biology. A striking example of this is the ribosome, a complex, three-dimensionally folded macromolecular machine that orchestrates protein synthesis. Advances in RNA biochemistry, structural and molecular biology, and bioinformatics have revealed other non-coding RNAs whose functions are dictated by their structure. It is not surprising that aberrantly folded RNA structures contribute to disease. In this Review, we provide a brief introduction into RNA structural biology and then describe how RNA structures function in cells and cause or contribute to neurological disease. Finally, we highlight successful applications of rational design principles to provide chemical probes and lead compounds targeting structured RNAs. Based on several examples of well-characterized RNA-driven neurological disorders, we demonstrate how designed small molecules can facilitate the study of RNA dysfunction, elucidating previously unknown roles for RNA in disease, and provide lead therapeutics. Copyright © 2015 Elsevier Inc. All rights reserved.

Systems biology definition of the core proteome of metabolism and expression is consistent with high-throughput data.

PubMed

Yang, Laurence; Tan, Justin; O'Brien, Edward J; Monk, Jonathan M; Kim, Donghyuk; Li, Howard J; Charusanti, Pep; Ebrahim, Ali; Lloyd, Colton J; Yurkovich, James T; Du, Bin; Dräger, Andreas; Thomas, Alex; Sun, Yuekai; Saunders, Michael A; Palsson, Bernhard O

2015-08-25

Finding the minimal set of gene functions needed to sustain life is of both fundamental and practical importance. Minimal gene lists have been proposed by using comparative genomics-based core proteome definitions. A definition of a core proteome that is supported by empirical data, is understood at the systems-level, and provides a basis for computing essential cell functions is lacking. Here, we use a systems biology-based genome-scale model of metabolism and expression to define a functional core proteome consisting of 356 gene products, accounting for 44% of the Escherichia coli proteome by mass based on proteomics data. This systems biology core proteome includes 212 genes not found in previous comparative genomics-based core proteome definitions, accounts for 65% of known essential genes in E. coli, and has 78% gene function overlap with minimal genomes (Buchnera aphidicola and Mycoplasma genitalium). Based on transcriptomics data across environmental and genetic backgrounds, the systems biology core proteome is significantly enriched in nondifferentially expressed genes and depleted in differentially expressed genes. Compared with the noncore, core gene expression levels are also similar across genetic backgrounds (two times higher Spearman rank correlation) and exhibit significantly more complex transcriptional and posttranscriptional regulatory features (40% more transcription start sites per gene, 22% longer 5'UTR). Thus, genome-scale systems biology approaches rigorously identify a functional core proteome needed to support growth. This framework, validated by using high-throughput datasets, facilitates a mechanistic understanding of systems-level core proteome function through in silico models; it de facto defines a paleome.

The Evolving Contribution of Mass Spectrometry to Integrative Structural Biology

NASA Astrophysics Data System (ADS)

Faini, Marco; Stengel, Florian; Aebersold, Ruedi

2016-06-01

Protein complexes are key catalysts and regulators for the majority of cellular processes. Unveiling their assembly and structure is essential to understanding their function and mechanism of action. Although conventional structural techniques such as X-ray crystallography and NMR have solved the structure of important protein complexes, they cannot consistently deal with dynamic and heterogeneous assemblies, limiting their applications to small scale experiments. A novel methodological paradigm, integrative structural biology, aims at overcoming such limitations by combining complementary data sources into a comprehensive structural model. Recent applications have shown that a range of mass spectrometry (MS) techniques are able to generate interaction and spatial restraints (cross-linking MS) information on native complexes or to study the stoichiometry and connectivity of entire assemblies (native MS) rapidly, reliably, and from small amounts of substrate. Although these techniques by themselves do not solve structures, they do provide invaluable structural information and are thus ideally suited to contribute to integrative modeling efforts. The group of Brian Chait has made seminal contributions in the use of mass spectrometric techniques to study protein complexes. In this perspective, we honor the contributions of the Chait group and discuss concepts and milestones of integrative structural biology. We also review recent examples of integration of structural MS techniques with an emphasis on cross-linking MS. We then speculate on future MS applications that would unravel the dynamic nature of protein complexes upon diverse cellular states.

The biological effect of asbestos exposure is dependent on ...

EPA Pesticide Factsheets

Abstract Functional groups on the surface of fibrous silicates can complex iron. We tested the postulate that 1) asbestos complexes and sequesters host cell iron resulting in a disruption of metal homeostasis and 2) this loss of essential metal results in an oxidative stress and biological effect in respiratory epithelial cells. Exposure of BEAS-2B cells to 50 μg/mL chrysotile resulted in diminished concentrations of mitochondrial iron. Pre-incubation of these cells with 200 μM ferric ammonium citrate (FAC) prevented significant mitochondrial iron loss following the same exposure. The host response to chrysotile included increased expression of the importer divalent metal transporter-1 (DMT1) supporting a functional iron deficiency. Incubation of BEAS-2B cells with both 200 μM FAC and 50 μg/mL chrysotile was associated with a greater cell accumulation of iron relative to either iron or chrysotile alone reflecting increased import to correct metal deficiency immediately following fiber exposure. Cellular oxidant generation was elevated after chrysotile exposure and this signal was diminished by co-incubation with 200 μM FAC. Similarly, exposure of BEAS-2B cells to 50 µg/mL chrysotile was associated with release of the pro-inflammatory mediators interleukin (IL)-6 and IL-8 and these changes were diminished by co-incubation with 200 μM FAC. We conclude that 1) the biological response following exposure to chrysotile is associated with complexation an

From Molecules to Life: Quantifying the Complexity of Chemical and Biological Systems in the Universe.

PubMed

Böttcher, Thomas

2018-01-01

Life is a complex phenomenon and much research has been devoted to both understanding its origins from prebiotic chemistry and discovering life beyond Earth. Yet, it has remained elusive how to quantify this complexity and how to compare chemical and biological units on one common scale. Here, a mathematical description of molecular complexity was applied allowing to quantitatively assess complexity of chemical structures. This in combination with the orthogonal measure of information complexity resulted in a two-dimensional complexity space ranging over the entire spectrum from molecules to organisms. Entities with a certain level of information complexity directly require a functionally complex mechanism for their production or replication and are hence indicative for life-like systems. In order to describe entities combining molecular and information complexity, the term biogenic unit was introduced. Exemplified biogenic unit complexities were calculated for ribozymes, protein enzymes, multimeric protein complexes, and even an entire virus particle. Complexities of prokaryotic and eukaryotic cells, as well as multicellular organisms, were estimated. Thereby distinct evolutionary stages in complexity space were identified. The here developed approach to compare the complexity of biogenic units allows for the first time to address the gradual characteristics of prebiotic and life-like systems without the need for a definition of life. This operational concept may guide our search for life in the Universe, and it may direct the investigations of prebiotic trajectories that lead towards the evolution of complexity at the origins of life.

Mammalian synthetic biology for studying the cell

PubMed Central

Mathur, Melina; Xiang, Joy S.

2017-01-01

Synthetic biology is advancing the design of genetic devices that enable the study of cellular and molecular biology in mammalian cells. These genetic devices use diverse regulatory mechanisms to both examine cellular processes and achieve precise and dynamic control of cellular phenotype. Synthetic biology tools provide novel functionality to complement the examination of natural cell systems, including engineered molecules with specific activities and model systems that mimic complex regulatory processes. Continued development of quantitative standards and computational tools will expand capacities to probe cellular mechanisms with genetic devices to achieve a more comprehensive understanding of the cell. In this study, we review synthetic biology tools that are being applied to effectively investigate diverse cellular processes, regulatory networks, and multicellular interactions. We also discuss current challenges and future developments in the field that may transform the types of investigation possible in cell biology. PMID:27932576

Biological and medical applications of a brain-on-a-chip

PubMed Central

2016-01-01

The desire to develop and evaluate drugs as potential countermeasures for biological and chemical threats requires test systems that can also substitute for the clinical trials normally crucial for drug development. Current animal models have limited predictivity for drug efficacy in humans as the large majority of drugs fails in clinical trials. We have limited understanding of the function of the central nervous system and the complexity of the brain, especially during development and neuronal plasticity. Simple in vitro systems do not represent physiology and function of the brain. Moreover, the difficulty of studying interactions between human genetics and environmental factors leads to lack of knowledge about the events that induce neurological diseases. Microphysiological systems (MPS) promise to generate more complex in vitro human models that better simulate the organ’s biology and function. MPS combine different cell types in a specific three-dimensional (3D) configuration to simulate organs with a concrete function. The final aim of these MPS is to combine different “organoids” to generate a human-on-a-chip, an approach that would allow studies of complex physiological organ interactions. The recent discovery of induced pluripotent stem cells (iPSCs) gives a range of possibilities allowing cellular studies of individuals with different genetic backgrounds (e.g., human disease models). Application of iPSCs from different donors in MPS gives the opportunity to better understand mechanisms of the disease and can be a novel tool in drug development, toxicology, and medicine. In order to generate a brain-on-a-chip, we have established a 3D model from human iPSCs based on our experience with a 3D rat primary aggregating brain model. After four weeks of differentiation, human 3D aggregates stain positive for different neuronal markers and show higher gene expression of various neuronal differentiation markers compared to 2D cultures. Here we present the applications and challenges of this emerging technology. PMID:24912505

Microfluidic 3D cell culture: potential application for tissue-based bioassays

PubMed Central

Li, XiuJun (James); Valadez, Alejandra V.; Zuo, Peng; Nie, Zhihong

2014-01-01

Current fundamental investigations of human biology and the development of therapeutic drugs, commonly rely on two-dimensional (2D) monolayer cell culture systems. However, 2D cell culture systems do not accurately recapitulate the structure, function, physiology of living tissues, as well as highly complex and dynamic three-dimensional (3D) environments in vivo. The microfluidic technology can provide micro-scale complex structures and well-controlled parameters to mimic the in vivo environment of cells. The combination of microfluidic technology with 3D cell culture offers great potential for in vivo-like tissue-based applications, such as the emerging organ-on-a-chip system. This article will review recent advances in microfluidic technology for 3D cell culture and their biological applications. PMID:22793034

Synthesis of Polycyclic Natural Products

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

Nguyen, Tuan Hoang

With the continuous advancements in molecular biology and modern medicine, organic synthesis has become vital to the support and extension of those discoveries. The isolations of new natural products allow for the understanding of their biological activities and therapeutic value. Organic synthesis is employed to aid in the determination of the relationship between structure and function of these natural products. The development of synthetic methodologies in the course of total syntheses is imperative for the expansion of this highly interdisciplinary field of science. In addition to the practical applications of total syntheses, the structural complexity of natural products represents amore » worthwhile challenge in itself. The pursuit of concise and efficient syntheses of complex molecules is both gratifying and enjoyable.« less

Design Principles of Regulatory Networks: Searching for the Molecular Algorithms of the Cell

PubMed Central

Lim, Wendell A.; Lee, Connie M.; Tang, Chao

2013-01-01

A challenge in biology is to understand how complex molecular networks in the cell execute sophisticated regulatory functions. Here we explore the idea that there are common and general principles that link network structures to biological functions, principles that constrain the design solutions that evolution can converge upon for accomplishing a given cellular task. We describe approaches for classifying networks based on abstract architectures and functions, rather than on the specific molecular components of the networks. For any common regulatory task, can we define the space of all possible molecular solutions? Such inverse approaches might ultimately allow the assembly of a design table of core molecular algorithms that could serve as a guide for building synthetic networks and modulating disease networks. PMID:23352241

Self-assembly of Janus dendrimers into uniform dendrimersomes and other complex architectures.

PubMed

Percec, Virgil; Wilson, Daniela A; Leowanawat, Pawaret; Wilson, Christopher J; Hughes, Andrew D; Kaucher, Mark S; Hammer, Daniel A; Levine, Dalia H; Kim, Anthony J; Bates, Frank S; Davis, Kevin P; Lodge, Timothy P; Klein, Michael L; DeVane, Russell H; Aqad, Emad; Rosen, Brad M; Argintaru, Andreea O; Sienkowska, Monika J; Rissanen, Kari; Nummelin, Sami; Ropponen, Jarmo

2010-05-21

Self-assembled nanostructures obtained from natural and synthetic amphiphiles serve as mimics of biological membranes and enable the delivery of drugs, proteins, genes, and imaging agents. Yet the precise molecular arrangements demanded by these functions are difficult to achieve. Libraries of amphiphilic Janus dendrimers, prepared by facile coupling of tailored hydrophilic and hydrophobic branched segments, have been screened by cryogenic transmission electron microscopy, revealing a rich palette of morphologies in water, including vesicles, denoted dendrimersomes, cubosomes, disks, tubular vesicles, and helical ribbons. Dendrimersomes marry the stability and mechanical strength obtainable from polymersomes with the biological function of stabilized phospholipid liposomes, plus superior uniformity of size, ease of formation, and chemical functionalization. This modular synthesis strategy provides access to systematic tuning of molecular structure and of self-assembled architecture.

Preparation and Characterization of Biofunctionalized Inorganic Substrates.

PubMed

Dugger, Jason W; Webb, Lauren J

2015-09-29

Integrating the function of biological molecules into traditional inorganic materials and substrates couples biologically relevant function to synthetic devices and generates new materials and capabilities by combining biological and inorganic functions. At this so-called "bio/abio interface," basic biological functions such as ligand binding and catalysis can be co-opted to detect analytes with exceptional sensitivity or to generate useful molecules with chiral specificity under entirely benign reaction conditions. Proteins function in dynamic, complex, and crowded environments (the living cell) and are therefore appropriate for integrating into multistep, multiscale, multimaterial devices such as integrated circuits and heterogeneous catalysts. However, the goal of reproducing the highly specific activities of biomolecules in the perturbed chemical and electrostatic environment at an inorganic interface while maintaining their native conformations is challenging to achieve. Moreover, characterizing protein structure and function at a surface is often difficult, particularly if one wishes to compare the activity of the protein to that of the dilute, aqueous solution phase. Our laboratory has developed a general strategy to address this challenge by taking advantage of the structural and chemical properties of alkanethiol self-assembled monolayers (SAMs) on gold surfaces that are functionalized with covalently tethered peptides. These surface-bound peptides then act as the chemical recognition element for a target protein, generating a biomimetic surface in which protein orientation, structure, density, and function are controlled and variable. Herein we discuss current research and future directions related to generating a chemically tunable biofunctionalization strategy that has potential to successfully incorporate the highly specialized functions of proteins onto inorganic substrates.

Mammalian Synthetic Biology: Engineering Biological Systems.

PubMed

Black, Joshua B; Perez-Pinera, Pablo; Gersbach, Charles A

2017-06-21

The programming of new functions into mammalian cells has tremendous application in research and medicine. Continued improvements in the capacity to sequence and synthesize DNA have rapidly increased our understanding of mechanisms of gene function and regulation on a genome-wide scale and have expanded the set of genetic components available for programming cell biology. The invention of new research tools, including targetable DNA-binding systems such as CRISPR/Cas9 and sensor-actuator devices that can recognize and respond to diverse chemical, mechanical, and optical inputs, has enabled precise control of complex cellular behaviors at unprecedented spatial and temporal resolution. These tools have been critical for the expansion of synthetic biology techniques from prokaryotic and lower eukaryotic hosts to mammalian systems. Recent progress in the development of genome and epigenome editing tools and in the engineering of designer cells with programmable genetic circuits is expanding approaches to prevent, diagnose, and treat disease and to establish personalized theranostic strategies for next-generation medicines. This review summarizes the development of these enabling technologies and their application to transforming mammalian synthetic biology into a distinct field in research and medicine.

Systems biology in hepatology: approaches and applications.

PubMed

Mardinoglu, Adil; Boren, Jan; Smith, Ulf; Uhlen, Mathias; Nielsen, Jens

2018-06-01

Detailed insights into the biological functions of the liver and an understanding of its crosstalk with other human tissues and the gut microbiota can be used to develop novel strategies for the prevention and treatment of liver-associated diseases, including fatty liver disease, cirrhosis, hepatocellular carcinoma and type 2 diabetes mellitus. Biological network models, including metabolic, transcriptional regulatory, protein-protein interaction, signalling and co-expression networks, can provide a scaffold for studying the biological pathways operating in the liver in connection with disease development in a systematic manner. Here, we review studies in which biological network models were used to integrate multiomics data to advance our understanding of the pathophysiological responses of complex liver diseases. We also discuss how this mechanistic approach can contribute to the discovery of potential biomarkers and novel drug targets, which might lead to the design of targeted and improved treatment strategies. Finally, we present a roadmap for the successful integration of models of the liver and other human tissues with the gut microbiota to simulate whole-body metabolic functions in health and disease.

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.

Tissue matrix arrays for high throughput screening and systems analysis of cell function

PubMed Central

Beachley, Vince Z.; Wolf, Matthew T.; Sadtler, Kaitlyn; Manda, Srikanth S.; Jacobs, Heather; Blatchley, Michael; Bader, Joel S.; Pandey, Akhilesh; Pardoll, Drew; Elisseeff, Jennifer H.

2015-01-01

Cell and protein arrays have demonstrated remarkable utility in the high-throughput evaluation of biological responses; however, they lack the complexity of native tissue and organs. Here, we describe tissue extracellular matrix (ECM) arrays for screening biological outputs and systems analysis. We spotted processed tissue ECM particles as two-dimensional arrays or incorporated them with cells to generate three-dimensional cell-matrix microtissue arrays. We then investigated the response of human stem, cancer, and immune cells to tissue ECM arrays originating from 11 different tissues, and validated the 2D and 3D arrays as representative of the in vivo microenvironment through quantitative analysis of tissue-specific cellular responses, including matrix production, adhesion and proliferation, and morphological changes following culture. The biological outputs correlated with tissue proteomics, and network analysis identified several proteins linked to cell function. Our methodology enables broad screening of ECMs to connect tissue-specific composition with biological activity, providing a new resource for biomaterials research and translation. PMID:26480475

Probing the biology of cell boundary conditions through confinement of Xenopus cell-free cytoplasmic extracts.

PubMed

Bermudez, Jessica G; Chen, Hui; Einstein, Lily C; Good, Matthew C

2017-01-01

Cell-free cytoplasmic extracts prepared from Xenopus eggs and embryos have for decades provided a biochemical system with which to interrogate complex cell biological processes in vitro. Recently, the application of microfabrication and microfluidic strategies in biology has narrowed the gap between in vitro and in vivo studies by enabling formation of cell-size compartments containing functional cytoplasm. These approaches provide numerous advantages over traditional biochemical experiments performed in a test tube. Most notably, the cell-free cytoplasm is confined using a two- or three-dimensional boundary, which mimics the natural configuration of a cell. This strategy enables characterization of the spatial organization of a cell, and the role that boundaries play in regulating intracellular assembly and function. In this review, we describe the marriage of Xenopus cell-free cytoplasm and confinement technologies to generate synthetic cell-like systems, the recent biological insights they have enabled, and the promise they hold for future scientific discovery. © 2017 Wiley Periodicals, Inc.

Biological determination of mental disorders: a discussion based on recent hypotheses from neuroscience.

PubMed

Freitas-Silva, Luna Rodrigues; Ortega, Francisco

2016-08-29

Understanding the processes involved in the development of mental disorders has proven challenging ever since psychiatry was founded as a field. Neuroscience has provided new expectations that an explanation will be found for the development of mental disorders based on biological functioning alone. However, such a goal has not been that easy to achieve, and new hypotheses have begun to appear in neuroscience research. In this article we identify epigenetics, neurodevelopment, and plasticity as the principal avenues for a new understanding of the biology of mental phenomena. Genetic complexity, the environment's formative role, and variations in vulnerability involve important changes in the principal hypotheses on biological determination of mental disorders, suggesting a reconfiguration of the limits between the "social" and the "biological" in neuroscience research.

Teaching Electrostatics and Entropy in Introductory Physics

NASA Astrophysics Data System (ADS)

Reeves, Mark

Entropy changes underlie the physics that dominates biological interactions. Indeed, introductory biology courses often begin with an exploration of the qualities of water that are important to living systems. However, one idea that is not explicitly addressed in most introductory physics or biology courses is important contribution of the entropy in driving fundamental biological processes towards equilibrium. I will present material developed to teach electrostatic screening in solutions and the function of nerve cells where entropic effects act to counterbalance electrostatic attraction. These ideas are taught in an introductory, calculus-based physics course to biomedical engineers using SCALEUP pedagogy. Results of student mastering of complex problems that cross disciplinary boundaries between biology and physics, as well as the challenges that they face in learning this material will be presented.

The Pathway Coexpression Network: Revealing pathway relationships

PubMed Central

Tanzi, Rudolph E.

2018-01-01

A goal of genomics is to understand the relationships between biological processes. Pathways contribute to functional interplay within biological processes through complex but poorly understood interactions. However, limited functional references for global pathway relationships exist. Pathways from databases such as KEGG and Reactome provide discrete annotations of biological processes. Their relationships are currently either inferred from gene set enrichment within specific experiments, or by simple overlap, linking pathway annotations that have genes in common. Here, we provide a unifying interpretation of functional interaction between pathways by systematically quantifying coexpression between 1,330 canonical pathways from the Molecular Signatures Database (MSigDB) to establish the Pathway Coexpression Network (PCxN). We estimated the correlation between canonical pathways valid in a broad context using a curated collection of 3,207 microarrays from 72 normal human tissues. PCxN accounts for shared genes between annotations to estimate significant correlations between pathways with related functions rather than with similar annotations. We demonstrate that PCxN provides novel insight into mechanisms of complex diseases using an Alzheimer’s Disease (AD) case study. PCxN retrieved pathways significantly correlated with an expert curated AD gene list. These pathways have known associations with AD and were significantly enriched for genes independently associated with AD. As a further step, we show how PCxN complements the results of gene set enrichment methods by revealing relationships between enriched pathways, and by identifying additional highly correlated pathways. PCxN revealed that correlated pathways from an AD expression profiling study include functional clusters involved in cell adhesion and oxidative stress. PCxN provides expanded connections to pathways from the extracellular matrix. PCxN provides a powerful new framework for interrogation of global pathway relationships. Comprehensive exploration of PCxN can be performed at http://pcxn.org/. PMID:29554099

Integrative mental health care: from theory to practice, Part 2.

PubMed

Lake, James

2008-01-01

Integrative approaches will lead to more accurate and different understandings of mental illness. Beneficial responses to complementary and alternative therapies provide important clues about the phenomenal nature of the human body in space-time and disparate biological, informational, and energetic factors associated with normal and abnormal psychological functioning. The conceptual framework of contemporary Western psychiatry includes multiple theoretical viewpoints, and there is no single best explanatory model of mental illness. Future theories of mental illness causation will not depend exclusively on empirical verification of strictly biological processes but will take into account both classically described biological processes and non-classical models, including complexity theory, resulting in more complete explanations of the characteristics and causes of symptoms and mechanisms of action that result in beneficial responses to treatments. Part 1 of this article examined the limitations of the theory and contemporary clinical methods employed in Western psychiatry and discussed implications of emerging paradigms in physics and the biological sciences for the future of psychiatry. In part 2, a practical methodology, for planning integrative assessment and treatment strategies in mental health care is proposed. Using this methodology the integrative management of moderate and severe psychiatric symptoms is reviewed in detail. As the conceptual framework of Western medicine evolves toward an increasingly integrative perspective, novel understanding of complex relationships between biological, informational, and energetic processes associated with normal psychological functioning and mental illness will lead to more effective integrative assessment and treatment strategies addressing the causes or meanings of symptoms at multiple hierarchic levels of body-brain-mind.

Integrative mental health care: from theory to practice, part 1.

PubMed

Lake, James

2007-01-01

Integrative approaches will lead to more accurate and different understandings of mental illness. Beneficial responses to complementary and alternative therapies provide important clues about the phenomenal nature of the human body in space-time and disparate biological, informational, and energetic factors associated with normal and abnormal psychological functioning. The conceptual framework of contemporary Western psychiatry includes multiple theoretical viewpoints, and there is no single best explanatory model of mental illness. Future theories of mental illness causation will not depend exclusively on empirical verification of strictly biological processes but will take into account both classically described biological processes and non-classical models, including complexity theory, resulting in more complete explanations of the characteristics and causes of symptoms and mechanisms of action that result in beneficial responses to treatments. Part 1 of this article examines the limitations of the theory and contemporary clinical methods employed in Western psychiatry and discusses implications of emerging paradigms in physics and the biological sciences for the future of psychiatry. In part 2, a practical methodology for planning integrative assessment and treatment strategies in mental health care is proposed. Using this methodology the integrative management of moderate and severe psychiatric symptoms is reviewed in detail. As the conceptual framework of Western medicine evolves toward an increasingly integrative perspective, novel understandings of complex relationships between biological, informational, and energetic processes associated with normal psychological functioning and mental illness will lead to more effective integrative assessment and treatment strategies addressing the causes or meanings of symptoms at multiple hierarchic levels of body-brain-mind.

Beyond tRNA cleavage: novel essential function for yeast tRNA splicing endonuclease unrelated to tRNA processing

PubMed Central

Dhungel, Nripesh; Hopper, Anita K.

2012-01-01

Pre-tRNA splicing is an essential process in all eukaryotes. In yeast and vertebrates, the enzyme catalyzing intron removal from pre-tRNA is a heterotetrameric complex (splicing endonuclease [SEN] complex). Although the SEN complex is conserved, the subcellular location where pre-tRNA splicing occurs is not. In yeast, the SEN complex is located at the cytoplasmic surface of mitochondria, whereas in vertebrates, pre-tRNA splicing is nuclear. We engineered yeast to mimic the vertebrate cell biology and demonstrate that all three steps of pre-tRNA splicing, as well as tRNA nuclear export and aminoacylation, occur efficiently when the SEN complex is nuclear. However, nuclear pre-tRNA splicing fails to complement growth defects of cells with defective mitochondrial-located splicing, suggesting that the yeast SEN complex surprisingly serves a novel and essential function in the cytoplasm that is unrelated to tRNA splicing. The novel function requires all four SEN complex subunits and the catalytic core. A subset of pre-rRNAs accumulates when the SEN complex is restricted to the nucleus, indicating that the SEN complex moonlights in rRNA processing. Thus, findings suggest that selection for the subcellular distribution of the SEN complex may reside not in its canonical, but rather in a novel, activity. PMID:22391451

Small-angle neutron scattering reveals the assembly mode and oligomeric architecture of TET, a large, dodecameric aminopeptidase

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

Appolaire, Alexandre; Girard, Eric; Colombo, Matteo

2014-11-01

The present work illustrates that small-angle neutron scattering, deuteration and contrast variation, combined with in vitro particle reconstruction, constitutes a very efficient approach to determine subunit architectures in large, symmetric protein complexes. In the case of the 468 kDa heterododecameric TET peptidase machine, it was demonstrated that the assembly of the 12 subunits is a highly controlled process and represents a way to optimize the catalytic efficiency of the enzyme. The specific self-association of proteins into oligomeric complexes is a common phenomenon in biological systems to optimize and regulate their function. However, de novo structure determination of these important complexesmore » is often very challenging for atomic-resolution techniques. Furthermore, in the case of homo-oligomeric complexes, or complexes with very similar building blocks, the respective positions of subunits and their assembly pathways are difficult to determine using many structural biology techniques. Here, an elegant and powerful approach based on small-angle neutron scattering is applied, in combination with deuterium labelling and contrast variation, to elucidate the oligomeric organization of the quaternary structure and the assembly pathways of 468 kDa, hetero-oligomeric and symmetric Pyrococcus horikoshii TET2–TET3 aminopeptidase complexes. The results reveal that the topology of the PhTET2 and PhTET3 dimeric building blocks within the complexes is not casual but rather suggests that their quaternary arrangement optimizes the catalytic efficiency towards peptide substrates. This approach bears important potential for the determination of quaternary structures and assembly pathways of large oligomeric and symmetric complexes in biological systems.« less

Novel aspects of endometrial function: a biological sensor of embryo quality and driver of pregnancy success.

PubMed

Sandra, Olivier; Mansouri-Attia, Nadéra; Lea, Richard G

2011-01-01

Successful pregnancy depends on complex biological processes that are regulated temporally and spatially throughout gestation. The molecular basis of these processes have been examined in relation to gamete quality, early blastocyst development and placental function, and data have been generated showing perturbations of these developmental stages by environmental insults or embryo biotechnologies. The developmental period falling between the entry of the blastocyst into the uterine cavity to implantation has also been examined in terms of the biological function of the endometrium. Indeed several mechanisms underlying uterine receptivity, controlled by maternal factors, and the maternal recognition of pregnancy, requiring conceptus-produced signals, have been clarified. Nevertheless, recent data based on experimental perturbations have unveiled unexpected biological properties of the endometrium (sensor/driver) that make this tissue a dynamic and reactive entity. Persistent or transient modifications in organisation and functionality of the endometrium can dramatically affect pre-implantation embryo trajectory through epigenetic alterations with lasting consequences on later stages of pregnancy, including placentation, fetal development, pregnancy outcome and post-natal health. Developing diagnostic and prognostic tools based on endometrial factors may enable the assessment of maternal reproductive capacity and/or the developmental potential of the embryo, particularly when assisted reproductive technologies are applied.

04-ERD-052-Final Report

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

Loots, G G; Ovcharenko, I; Collette, N

2007-02-26

Generating the sequence of the human genome represents a colossal achievement for science and mankind. The technical use for the human genome project information holds great promise to cure disease, prevent bioterror threats, as well as to learn about human origins. Yet converting the sequence data into biological meaningful information has not been immediately obvious, and we are still in the preliminary stages of understanding how the genome is organized, what are the functional building blocks and how do these sequences mediate complex biological processes. The overarching goal of this program was to develop novel methods and high throughput strategiesmore » for determining the functions of ''anonymous'' human genes that are evolutionarily deeply conserved in other vertebrates. We coupled analytical tool development and computational predictions regarding gene function with novel high throughput experimental strategies and tested biological predictions in the laboratory. The tools required for comparative genomic data-mining are fundamentally the same whether they are applied to scientific studies of related microbes or the search for functions of novel human genes. For this reason the tools, conceptual framework and the coupled informatics-experimental biology paradigm we developed in this LDRD has many potential scientific applications relevant to LLNL multidisciplinary research in bio-defense, bioengineering, bionanosciences and microbial and environmental genomics.« less

Editorial overview: Omics

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

Barran, Perdita; Baker, Erin

The great complexity of biological systems and their environment poses similarly vast challenges for accurate analytical evaluations of their identity, structure and quantity. Post genomic science, has predicted much regarding the static populations of biological systems, but a further challenge for analysis is to test the accuracy of these predictions, as well as provide a better representation of the transient nature of the molecules of life. Accurate measurements of biological systems have wide applications for biological, forensic, biotechnological and healthcare fields. Therefore, the holy grail is to find a technique which can identify and quantify biological molecules with high throughput,more » sensitivity and robustness, as well evaluate molecular structure(s) in order to understand how the specific molecules interact and function. While wrapping all of these characteristics into one platform may sound difficult, ion mobility spectrometry (IMS) is addressing all of these challenges. Over the last decade, the number of analytical studies utilizing IMS for the evaluation of complex biological and environmental samples has greatly increased. In most cases IMS is coupled with mass spectrometry (IM-MS), but even alone IMS provides the unique capability of rapidly assessing a molecule’s structure, which can be extremely difficult with other techniques. The robustness of the IMS measurement is bourne out by its widespread use in security, environmental and military applications. The multidimensional IM-MS measurements however have been proven to be ever more powerful, as applied to complex mixtures as they enable the evaluation of both the structure and mass of every molecular component in a sample during a single measurement, without the need for continual reference calibration.« less

Discovering protein complexes in protein interaction networks via exploring the weak ties effect

PubMed Central

2012-01-01

Background Studying protein complexes is very important in biological processes since it helps reveal the structure-functionality relationships in biological networks and much attention has been paid to accurately predict protein complexes from the increasing amount of protein-protein interaction (PPI) data. Most of the available algorithms are based on the assumption that dense subgraphs correspond to complexes, failing to take into account the inherence organization within protein complex and the roles of edges. Thus, there is a critical need to investigate the possibility of discovering protein complexes using the topological information hidden in edges. Results To provide an investigation of the roles of edges in PPI networks, we show that the edges connecting less similar vertices in topology are more significant in maintaining the global connectivity, indicating the weak ties phenomenon in PPI networks. We further demonstrate that there is a negative relation between the weak tie strength and the topological similarity. By using the bridges, a reliable virtual network is constructed, in which each maximal clique corresponds to the core of a complex. By this notion, the detection of the protein complexes is transformed into a classic all-clique problem. A novel core-attachment based method is developed, which detects the cores and attachments, respectively. A comprehensive comparison among the existing algorithms and our algorithm has been made by comparing the predicted complexes against benchmark complexes. Conclusions We proved that the weak tie effect exists in the PPI network and demonstrated that the density is insufficient to characterize the topological structure of protein complexes. Furthermore, the experimental results on the yeast PPI network show that the proposed method outperforms the state-of-the-art algorithms. The analysis of detected modules by the present algorithm suggests that most of these modules have well biological significance in context of complexes, suggesting that the roles of edges are critical in discovering protein complexes. PMID:23046740

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.

Cell-selective metabolic labeling of biomolecules with bioorthogonal functionalities.

PubMed

Xie, Ran; Hong, Senlian; Chen, Xing

2013-10-01

Metabolic labeling of biomolecules with bioorthogonal functionalities enables visualization, enrichment, and analysis of the biomolecules of interest in their physiological environments. This versatile strategy has found utility in probing various classes of biomolecules in a broad range of biological processes. On the other hand, metabolic labeling is nonselective with respect to cell type, which imposes limitations for studies performed in complex biological systems. Herein, we review the recent methodological developments aiming to endow metabolic labeling strategies with cell-type selectivity. The cell-selective metabolic labeling strategies have emerged from protein and glycan labeling. We envision that these strategies can be readily extended to labeling of other classes of biomolecules. Copyright © 2013 Elsevier Ltd. All rights reserved.

A systems biology approach to studying Tai Chi, physiological complexity and healthy aging: design and rationale of a pragmatic randomized controlled trial.

PubMed

Wayne, Peter M; Manor, Brad; Novak, Vera; Costa, Madelena D; Hausdorff, Jeffrey M; Goldberger, Ary L; Ahn, Andrew C; Yeh, Gloria Y; Peng, C-K; Lough, Matthew; Davis, Roger B; Quilty, Mary T; Lipsitz, Lewis A

2013-01-01

Aging is typically associated with progressive multi-system impairment that leads to decreased physical and cognitive function and reduced adaptability to stress. Due to its capacity to characterize complex dynamics within and between physiological systems, the emerging field of complex systems biology and its array of quantitative tools show great promise for improving our understanding of aging, monitoring senescence, and providing biomarkers for evaluating novel interventions, including promising mind-body exercises, that treat age-related disease and promote healthy aging. An ongoing, two-arm randomized clinical trial is evaluating the potential of Tai Chi mind-body exercise to attenuate age-related loss of complexity. A total of 60 Tai Chi-naïve healthy older adults (aged 50-79) are being randomized to either six months of Tai Chi training (n=30), or to a waitlist control receiving unaltered usual medical care (n=30). Our primary outcomes are complexity-based measures of heart rate, standing postural sway and gait stride interval dynamics assessed at 3 and 6months. Multiscale entropy and detrended fluctuation analysis are used as entropy- and fractal-based measures of complexity, respectively. Secondary outcomes include measures of physical and psychological function and tests of physiological adaptability also assessed at 3 and 6months. Results of this study may lead to novel biomarkers that help us monitor and understand the physiological processes of aging and explore the potential benefits of Tai Chi and related mind-body exercises for healthy aging. Copyright © 2012 Elsevier Inc. All rights reserved.

From Genomes to Protein Models and Back

NASA Astrophysics Data System (ADS)

Tramontano, Anna; Giorgetti, Alejandro; Orsini, Massimiliano; Raimondo, Domenico

2007-12-01

The alternative splicing mechanism allows genes to generate more than one product. When the splicing events occur within protein coding regions they can modify the biological function of the protein. Alternative splicing has been suggested as one way for explaining the discrepancy between the number of human genes and functional complexity. We analysed the putative structure of the alternatively spliced gene products annotated in the ENCODE pilot project and discovered that many of the potential alternative gene products will be unlikely to produce stable functional proteins.

Toward structural elucidation of the gamma-secretase complex

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

Li, H.; Wolfe, M. S.; Selkoe, D. J.

2009-03-11

{gamma}-Secretase is an intramembrane protease complex that mediates the Notch signaling pathway and the production of amyloid {beta}-proteins. As such, this enzyme has emerged as an important target for development of novel therapeutics for Alzheimer disease and cancer. Great progress has been made in the identification and characterization of the membrane complex and its biological functions. One major challenge now is to illuminate the structure of this fascinating and important protease at atomic resolution. Here, we review recent progress on biochemical and biophysical probing of the structure of the four-component complex and discuss obstacles and potential pathways toward elucidating itsmore » detailed structure.« less

BATMAN-TCM: a Bioinformatics Analysis Tool for Molecular mechANism of Traditional Chinese Medicine.

PubMed

Liu, Zhongyang; Guo, Feifei; Wang, Yong; Li, Chun; Zhang, Xinlei; Li, Honglei; Diao, Lihong; Gu, Jiangyong; Wang, Wei; Li, Dong; He, Fuchu

2016-02-16

Traditional Chinese Medicine (TCM), with a history of thousands of years of clinical practice, is gaining more and more attention and application worldwide. And TCM-based new drug development, especially for the treatment of complex diseases is promising. However, owing to the TCM's diverse ingredients and their complex interaction with human body, it is still quite difficult to uncover its molecular mechanism, which greatly hinders the TCM modernization and internationalization. Here we developed the first online Bioinformatics Analysis Tool for Molecular mechANism of TCM (BATMAN-TCM). Its main functions include 1) TCM ingredients' target prediction; 2) functional analyses of targets including biological pathway, Gene Ontology functional term and disease enrichment analyses; 3) the visualization of ingredient-target-pathway/disease association network and KEGG biological pathway with highlighted targets; 4) comparison analysis of multiple TCMs. Finally, we applied BATMAN-TCM to Qishen Yiqi dripping Pill (QSYQ) and combined with subsequent experimental validation to reveal the functions of renin-angiotensin system responsible for QSYQ's cardioprotective effects for the first time. BATMAN-TCM will contribute to the understanding of the "multi-component, multi-target and multi-pathway" combinational therapeutic mechanism of TCM, and provide valuable clues for subsequent experimental validation, accelerating the elucidation of TCM's molecular mechanism. BATMAN-TCM is available at http://bionet.ncpsb.org/batman-tcm.

Bioinspired synthesis and self-assembly of hybrid organic–inorganic nanomaterials

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

Zhang, Honghu

Nature is replete with complex organic–inorganic hierarchical materials of diverse yet specific functions. These materials are intricately designed under physiological conditions through biomineralization and biological self-assembly processes. Tremendous efforts have been devoted to investigating mechanisms of such biomineralization and biological self-assembly processes as well as gaining inspiration to develop biomimetic methods for synthesis and self-assembly of functional nanomaterials. In this work, we focus on the bioinspired synthesis and self-assembly of functional inorganic nanomaterials templated by specialized macromolecules including proteins, DNA and polymers. The in vitro biomineralization process of the magnetite biomineralizing protein Mms6 has been investigated using small-angle X-ray scattering.more » Templated by Mms6, complex magnetic nanomaterials can be synthesized on surfaces and in the bulk. DNA and synthetic polymers have been exploited to construct macroscopic two- and three-dimensional (2D and 3D) superlattices of gold nanocrystals. Employing X-ray scattering and spectroscopy techniques, the self-assembled structures and the self-assembly mechanisms have been studied, and theoretical models have been developed. Our results show that specialized macromolecules including proteins, DNA and polymers act as effective templates for synthesis and self-assembly of nanomaterials. These bottom-up approaches provide promising routes to fabricate hybrid organic–inorganic nanomaterials with rationally designed hierarchical structures, targeting specific functions.« less

Diverse structures, functions and uses of FK506 binding proteins.

PubMed

Bonner, Julia Maeve; Boulianne, Gabrielle L

2017-10-01

FK506 (Tacrolimus), isolated from Streptomyces tsukubaenis is a powerful immunosuppressant shown to inhibit T cell activation. FK506 mediated immunosuppression requires the formation of a complex between FK506, a FK506 binding protein (FKBP) and calcineurin. Numerous FKBPs have been identified in a wide range of species, from single celled organisms to humans. FKBPs show peptidylprolyl cis/trans isomerase (PPIase) activity and have been shown to affect a wide range of cellular processes including protein folding, receptor signaling and apoptosis. FKBPs also affect numerous biological functions in addition to immunosuppression including regulation of cardiac function, neuronal function and development and have been implicated in several diseases including cardiac disease, cancer and neurodegenerative diseases such as Alzheimer's disease. More recently, FKBPs have proven useful as molecular tools for studying protein interactions, localization and functions. This review provides an overview of the current state of knowledge of FKBPs and their numerous biological functions and uses. Copyright © 2017 Elsevier Inc. All rights reserved.

Interdependency of formation and localisation of the Min complex controls symmetric plastid division.

PubMed

Maple, Jodi; Møller, Simon G

2007-10-01

Plastid division represents a fundamental biological process essential for plant development; however, the molecular basis of symmetric plastid division is unclear. AtMinE1 plays a pivotal role in selection of the plastid division site in concert with AtMinD1. AtMinE1 localises to discrete foci in chloroplasts and interacts with AtMinD1, which shows a similar localisation pattern. Here, we investigate the importance of Min protein complex formation during the chloroplast division process. Dissection of the assembly of the Min protein complex and determination of the interdependency of complex assembly and localisation in planta allow us to present a model of the molecular basis of selection of the division site in plastids. Moreover, functional analysis of AtMinE1 in bacteria demonstrates the level of functional conservation and divergence of the plastidic MinE proteins.

Linking Biological Responses of Terrestrial N Eutrophication to the Final Ecosystem Goods and Services Classification System

NASA Astrophysics Data System (ADS)

Bell, M. D.; Clark, C.; Blett, T.

2015-12-01

The response of a biological indicator to N deposition can indicate that an ecosystem has surpassed a critical load and is at risk of significant change. The importance of this exceedance is often difficult to digest by policy makers and public audiences if the change is not linked to a familiar ecosystem endpoint. A workshop was held to bring together scientists, resource managers, and policy makers with expertise in ecosystem functioning, critical loads, and economics in an effort to identify the ecosystem services impacted by air pollution. This was completed within the framework of the Final Ecosystem Goods and Services (FEGS) Classification System to produce a product that identified distinct interactions between society and the effects of nitrogen pollution. From each change in a biological indicator, we created multiple ecological production functions to identify the cascading effects of the change to a measureable ecosystem service that a user interacts with either by enjoying, consuming, or appreciating the good or service, or using it as an input in the human economy. This FEGS metric was then linked to a beneficiary group that interacts with the service. Chains detailing the links from the biological indicator to the beneficiary group were created for aquatic and terrestrial acidification and eutrophication at the workshop, and here we present a subset of the workshop results by highlighting for 9 different ecosystems affected by terrestrial eutrophication. A total of 213 chains that linked to 37 unique FEGS metrics and impacted 15 beneficiary groups were identified based on nitrogen deposition mediated changes to biological indicators. The chains within each ecosystem were combined in flow charts to show the complex, overlapping relationships among biological indicators, ecosystem services, and beneficiary groups. Strength of relationship values were calculated for each chain based on support for the link in the scientific literature. We produced the complex diagrams to provide details to scientists and experts, identify research gaps, and understand the complexity of critical load exceedances. We then simplified the flow charts into stories that could produce an emotional connection and resonate with a general audience. These stories are important steps to breach the gaps between science and policy.

Biomarkers of Aging: From Function to Molecular Biology

PubMed Central

Wagner, Karl-Heinz; Cameron-Smith, David; Wessner, Barbara; Franzke, Bernhard

2016-01-01

Aging is a major risk factor for most chronic diseases and functional impairments. Within a homogeneous age sample there is a considerable variation in the extent of disease and functional impairment risk, revealing a need for valid biomarkers to aid in characterizing the complex aging processes. The identification of biomarkers is further complicated by the diversity of biological living situations, lifestyle activities and medical treatments. Thus, there has been no identification of a single biomarker or gold standard tool that can monitor successful or healthy aging. Within this short review the current knowledge of putative biomarkers is presented, focusing on their application to the major physiological mechanisms affected by the aging process including physical capability, nutritional status, body composition, endocrine and immune function. This review emphasizes molecular and DNA-based biomarkers, as well as recent advances in other biomarkers such as microRNAs, bilirubin or advanced glycation end products. PMID:27271660

Zinc in Cellular Regulation: The Nature and Significance of "Zinc Signals".

PubMed

Maret, Wolfgang

2017-10-31

In the last decade, we witnessed discoveries that established Zn 2+ as a second major signalling metal ion in the transmission of information within cells and in communication between cells. Together with Ca 2+ and Mg 2+ , Zn 2+ covers biological regulation with redox-inert metal ions over many orders of magnitude in concentrations. The regulatory functions of zinc ions, together with their functions as a cofactor in about three thousand zinc metalloproteins, impact virtually all aspects of cell biology. This article attempts to define the regulatory functions of zinc ions, and focuses on the nature of zinc signals and zinc signalling in pathways where zinc ions are either extracellular stimuli or intracellular messengers. These pathways interact with Ca 2+ , redox, and phosphorylation signalling. The regulatory functions of zinc require a complex system of precise homeostatic control for transients, subcellular distribution and traffic, organellar homeostasis, and vesicular storage and exocytosis of zinc ions.

Sensitivity analysis of dynamic biological systems with time-delays.

PubMed

Wu, Wu Hsiung; Wang, Feng Sheng; Chang, Maw Shang

2010-10-15

Mathematical modeling has been applied to the study and analysis of complex biological systems for a long time. Some processes in biological systems, such as the gene expression and feedback control in signal transduction networks, involve a time delay. These systems are represented as delay differential equation (DDE) models. Numerical sensitivity analysis of a DDE model by the direct method requires the solutions of model and sensitivity equations with time-delays. The major effort is the computation of Jacobian matrix when computing the solution of sensitivity equations. The computation of partial derivatives of complex equations either by the analytic method or by symbolic manipulation is time consuming, inconvenient, and prone to introduce human errors. To address this problem, an automatic approach to obtain the derivatives of complex functions efficiently and accurately is necessary. We have proposed an efficient algorithm with an adaptive step size control to compute the solution and dynamic sensitivities of biological systems described by ordinal differential equations (ODEs). The adaptive direct-decoupled algorithm is extended to solve the solution and dynamic sensitivities of time-delay systems describing by DDEs. To save the human effort and avoid the human errors in the computation of partial derivatives, an automatic differentiation technique is embedded in the extended algorithm to evaluate the Jacobian matrix. The extended algorithm is implemented and applied to two realistic models with time-delays: the cardiovascular control system and the TNF-α signal transduction network. The results show that the extended algorithm is a good tool for dynamic sensitivity analysis on DDE models with less user intervention. By comparing with direct-coupled methods in theory, the extended algorithm is efficient, accurate, and easy to use for end users without programming background to do dynamic sensitivity analysis on complex biological systems with time-delays.

Systems biology-based approaches toward understanding drought tolerance in food crops.

PubMed

Jogaiah, Sudisha; Govind, Sharathchandra Ramsandra; Tran, Lam-Son Phan

2013-03-01

Economically important crops, such as maize, wheat, rice, barley, and other food crops are affected by even small changes in water potential at important growth stages. Developing a comprehensive understanding of host response to drought requires a global view of the complex mechanisms involved. Research on drought tolerance has generally been conducted using discipline-specific approaches. However, plant stress response is complex and interlinked to a point where discipline-specific approaches do not give a complete global analysis of all the interlinked mechanisms. Systems biology perspective is needed to understand genome-scale networks required for building long-lasting drought resistance. Network maps have been constructed by integrating multiple functional genomics data with both model plants, such as Arabidopsis thaliana, Lotus japonicus, and Medicago truncatula, and various food crops, such as rice and soybean. Useful functional genomics data have been obtained from genome-wide comparative transcriptome and proteome analyses of drought responses from different crops. This integrative approach used by many groups has led to identification of commonly regulated signaling pathways and genes following exposure to drought. Combination of functional genomics and systems biology is very useful for comparative analysis of other food crops and has the ability to develop stable food systems worldwide. In addition, studying desiccation tolerance in resurrection plants will unravel how combination of molecular genetic and metabolic processes interacts to produce a resurrection phenotype. Systems biology-based approaches have helped in understanding how these individual factors and mechanisms (biochemical, molecular, and metabolic) "interact" spatially and temporally. Signaling network maps of such interactions are needed that can be used to design better engineering strategies for improving drought tolerance of important crop species.

Diverse Supramolecular Nanofiber Networks Assembled by Functional Low-Complexity Domains.

PubMed

An, Bolin; Wang, Xinyu; Cui, Mengkui; Gui, Xinrui; Mao, Xiuhai; Liu, Yan; Li, Ke; Chu, Cenfeng; Pu, Jiahua; Ren, Susu; Wang, Yanyi; Zhong, Guisheng; Lu, Timothy K; Liu, Cong; Zhong, Chao

2017-07-25

Self-assembling supramolecular nanofibers, common in the natural world, are of fundamental interest and technical importance to both nanotechnology and materials science. Despite important advances, synthetic nanofibers still lack the structural and functional diversity of biological molecules, and the controlled assembly of one type of molecule into a variety of fibrous structures with wide-ranging functional attributes remains challenging. Here, we harness the low-complexity (LC) sequence domain of fused in sarcoma (FUS) protein, an essential cellular nuclear protein with slow kinetics of amyloid fiber assembly, to construct random copolymer-like, multiblock, and self-sorted supramolecular fibrous networks with distinct structural features and fluorescent functionalities. We demonstrate the utilities of these networks in the templated, spatially controlled assembly of ligand-decorated gold nanoparticles, quantum dots, nanorods, DNA origami, and hybrid structures. Owing to the distinguishable nanoarchitectures of these nanofibers, this assembly is structure-dependent. By coupling a modular genetic strategy with kinetically controlled complex supramolecular self-assembly, we demonstrate that a single type of protein molecule can be used to engineer diverse one-dimensional supramolecular nanostructures with distinct functionalities.

The emerging genomics and systems biology research lead to systems genomics studies.

PubMed

Yang, Mary Qu; Yoshigoe, Kenji; Yang, William; Tong, Weida; Qin, Xiang; Dunker, A; Chen, Zhongxue; Arbania, Hamid R; Liu, Jun S; Niemierko, Andrzej; Yang, Jack Y

2014-01-01

Synergistically integrating multi-layer genomic data at systems level not only can lead to deeper insights into the molecular mechanisms related to disease initiation and progression, but also can guide pathway-based biomarker and drug target identification. With the advent of high-throughput next-generation sequencing technologies, sequencing both DNA and RNA has generated multi-layer genomic data that can provide DNA polymorphism, non-coding RNA, messenger RNA, gene expression, isoform and alternative splicing information. Systems biology on the other hand studies complex biological systems, particularly systematic study of complex molecular interactions within specific cells or organisms. Genomics and molecular systems biology can be merged into the study of genomic profiles and implicated biological functions at cellular or organism level. The prospectively emerging field can be referred to as systems genomics or genomic systems biology. The Mid-South Bioinformatics Centre (MBC) and Joint Bioinformatics Ph.D. Program of University of Arkansas at Little Rock and University of Arkansas for Medical Sciences are particularly interested in promoting education and research advancement in this prospectively emerging field. Based on past investigations and research outcomes, MBC is further utilizing differential gene and isoform/exon expression from RNA-seq and co-regulation from the ChiP-seq specific for different phenotypes in combination with protein-protein interactions, and protein-DNA interactions to construct high-level gene networks for an integrative genome-phoneme investigation at systems biology level.

SWI/SNF Chromatin-remodeling Factors: Multiscale Analyses and Diverse Functions*

PubMed Central

Euskirchen, Ghia; Auerbach, Raymond K.; Snyder, Michael

2012-01-01

Chromatin-remodeling enzymes play essential roles in many biological processes, including gene expression, DNA replication and repair, and cell division. Although one such complex, SWI/SNF, has been extensively studied, new discoveries are still being made. Here, we review SWI/SNF biochemistry; highlight recent genomic and proteomic advances; and address the role of SWI/SNF in human diseases, including cancer and viral infections. These studies have greatly increased our understanding of complex nuclear processes. PMID:22952240

Intracellular Transport and Kinesin Superfamily Proteins: Structure, Function and Dynamics

NASA Astrophysics Data System (ADS)

Hirokawa, N.; Takemura, R.

Using various molecular cell biological and molecular genetic approaches, we identified kinesin superfamily proteins (KIFs) and characterized their significant functions in intracellular transport, which is fundamental for cellular morphogenesis, functioning, and survival. We showed that KIFs not only transport various membranous organelles, proteins complexes and mRNAs fundamental for cellular functions but also play significant roles in higher brain functions such as memory and learning, determination of important developmental processes such as left-right asymmetry formation and brain wiring. We also elucidated that KIFs recognize and bind to their specific cargoes using scaffolding or adaptor protein complexes. Concerning the mechanism of motility, we discovered the simplest unique monomeric motor KIF1A and determined by molecular biophysics, cryoelectron microscopy and X-ray crystallography that KIF1A can move on a microtubule processively as a monomer by biased Brownian motion and by hydolyzing ATP.

Biomimetic carriers mimicking leukocyte plasma membrane to increase tumor vasculature permeability

NASA Astrophysics Data System (ADS)

Palomba, R.; Parodi, A.; Evangelopoulos, M.; Acciardo, S.; Corbo, C.; De Rosa, E.; Yazdi, I. K.; Scaria, S.; Molinaro, R.; Furman, N. E. Toledano; You, J.; Ferrari, M.; Salvatore, F.; Tasciotti, E.

2016-10-01

Recent advances in the field of nanomedicine have demonstrated that biomimicry can further improve targeting properties of current nanotechnologies while simultaneously enable carriers with a biological identity to better interact with the biological environment. Immune cells for example employ membrane proteins to target inflamed vasculature, locally increase vascular permeability, and extravasate across inflamed endothelium. Inspired by the physiology of immune cells, we recently developed a procedure to transfer leukocyte membranes onto nanoporous silicon particles (NPS), yielding Leukolike Vectors (LLV). LLV are composed of a surface coating containing multiple receptors that are critical in the cross-talk with the endothelium, mediating cellular accumulation in the tumor microenvironment while decreasing vascular barrier function. We previously demonstrated that lymphocyte function-associated antigen (LFA-1) transferred onto LLV was able to trigger the clustering of intercellular adhesion molecule 1 (ICAM-1) on endothelial cells. Herein, we provide a more comprehensive analysis of the working mechanism of LLV in vitro in activating this pathway and in vivo in enhancing vascular permeability. Our results suggest the biological activity of the leukocyte membrane can be retained upon transplant onto NPS and is critical in providing the particles with complex biological functions towards tumor vasculature.

[Biology and immunotherapy advance of interleukin 2 and interleukin 15-review].

PubMed

Chen, Guang-Hua; Wu, De-Pei

2009-08-01

IL-2 and IL-15 play an important roles in regulating the lymphocyte function and homeostasis. Advances in understanding of the cellular and molecular biology of IL-2 and IL-15 and their receptor complex have provided rationale to better utilize them to expand and activate immune effectors in patients with cancer. These two cytokines stimulate similar responses from lymphocytes in vitro, but play markedly distinct roles in lymphoid biology in vivo. Their distinct physiological functions can be ascribed to distinct signaling pathways initiated by distinct cytokine receptor subunits, differential expression patterns of their receptors. Recently, the discovery of a novel mechanism of IL-15 cytokine signaling, trans-presentation, has provided insights into the divergent ways of these cytokine function. Although their heterotrimeric receptors have two receptor subunits in common, these two cytokines have contrasting roles in adaptive immune responses. The unique role of interleukin 2 is in the elimination of self-reactive T cells to prevent autoimmunity. By contrast, interleukin 15 is dedicated to the prolonged maintenance of memory T-cell responses to pathogens. As discussed in this article, the biology of IL-2 and IL-15 two cytokines will affect the development of novel treatment for malignancies and autoimmune diseases.

Structural and Chemical Biology of Terpenoid Cyclases

PubMed Central

2017-01-01

The year 2017 marks the twentieth anniversary of terpenoid cyclase structural biology: a trio of terpenoid cyclase structures reported together in 1997 were the first to set the foundation for understanding the enzymes largely responsible for the exquisite chemodiversity of more than 80000 terpenoid natural products. Terpenoid cyclases catalyze the most complex chemical reactions in biology, in that more than half of the substrate carbon atoms undergo changes in bonding and hybridization during a single enzyme-catalyzed cyclization reaction. The past two decades have witnessed structural, functional, and computational studies illuminating the modes of substrate activation that initiate the cyclization cascade, the management and manipulation of high-energy carbocation intermediates that propagate the cyclization cascade, and the chemical strategies that terminate the cyclization cascade. The role of the terpenoid cyclase as a template for catalysis is paramount to its function, and protein engineering can be used to reprogram the cyclization cascade to generate alternative and commercially important products. Here, I review key advances in terpenoid cyclase structural and chemical biology, focusing mainly on terpenoid cyclases and related prenyltransferases for which X-ray crystal structures have informed and advanced our understanding of enzyme structure and function. PMID:28841019

Systematic methods for defining coarse-grained maps in large biomolecules.

PubMed

Zhang, Zhiyong

2015-01-01

Large biomolecules are involved in many important biological processes. It would be difficult to use large-scale atomistic molecular dynamics (MD) simulations to study the functional motions of these systems because of the computational expense. Therefore various coarse-grained (CG) approaches have attracted rapidly growing interest, which enable simulations of large biomolecules over longer effective timescales than all-atom MD simulations. The first issue in CG modeling is to construct CG maps from atomic structures. In this chapter, we review the recent development of a novel and systematic method for constructing CG representations of arbitrarily complex biomolecules, in order to preserve large-scale and functionally relevant essential dynamics (ED) at the CG level. In this ED-CG scheme, the essential dynamics can be characterized by principal component analysis (PCA) on a structural ensemble, or elastic network model (ENM) of a single atomic structure. Validation and applications of the method cover various biological systems, such as multi-domain proteins, protein complexes, and even biomolecular machines. The results demonstrate that the ED-CG method may serve as a very useful tool for identifying functional dynamics of large biomolecules at the CG level.

Nutritional Lipidomics: Molecular Metabolism, Analytics, and Diagnostics

PubMed Central

Smilowitz, Jennifer T.; Zivkovic, Angela M.; Wan, Yu-Jui Yvonne; Watkins, Steve M.; Nording, Malin L.; Hammock, Bruce D.; German, J. Bruce

2013-01-01

The field of lipidomics is providing nutritional science a more comprehensive view of lipid intermediates. Lipidomics research takes advantage of the increase in accuracy and sensitivity of mass detection of mass spectrometry with new bioinformatics toolsets to characterize the structures and abundances of complex lipids. Yet, translating lipidomics to practice via nutritional interventions is still in its infancy. No single instrumentation platform is able to solve the varying analytical challenges of the different molecular lipid species. Biochemical pathways of lipid metabolism remain incomplete and the tools to map lipid compositional data to pathways are still being assembled. Biology itself is dauntingly complex and simply separating biological structures remains a key challenge to lipidomics. Nonetheless, the strategy of combining tandem analytical methods to perform the sensitive, high-throughput, quantitative and comprehensive analysis of lipid metabolites of very large numbers of molecules is poised to drive the field forward rapidly. Among the next steps for nutrition to understand the changes in structures, compositions and function of lipid biomolecules in response to diet is to describe their distribution within discrete functional compartments-lipoproteins. Additionally, lipidomics must tackle the task of assigning the functions of lipids as signaling molecules, nutrient sensors, and intermediates of metabolic pathways. PMID:23818328

Ecological community integration increases with added trophic complexity

USGS Publications Warehouse

Wright, Christopher K.

2008-01-01

The existence of functional biological organization at the level of multi-species communities has long been contested in ecology and evolutionary biology. I found that adding a trophic level to simulated ecological communities enhanced their ability to compete at the community level, increasing the likelihood of one community forcing all or most species in a second community to extinction. Community-level identity emerged within systems of interacting ecological networks, while competitive ability at the community level was enhanced by intense within-community selection pressure. These results suggest a reassessment of the nature of biological organization above the level of species, indicating that the drive toward biological integration, so prominent throughout the history of life, might extend to multi-species communities.

Toward Engineering Synthetic Microbial Metabolism

PubMed Central

McArthur, George H.; Fong, Stephen S.

2010-01-01

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

Step-by-Step Simulation of Radiation Chemistry Using Green Functions for Diffusion-Influenced Reactions

NASA Technical Reports Server (NTRS)

Plante, Ianik; Cucinotta, Francis A.

2011-01-01

Radiolytic species are formed approximately 1 ps after the passage of ionizing radiation through matter. After their formation, they diffuse and chemically react with other radiolytic species and neighboring biological molecules, leading to various oxidative damage. Therefore, the simulation of radiation chemistry is of considerable importance to understand how radiolytic species damage biological molecules [1]. The step-by-step simulation of chemical reactions is difficult, because the radiolytic species are distributed non-homogeneously in the medium. Consequently, computational approaches based on Green functions for diffusion-influenced reactions should be used [2]. Recently, Green functions for more complex type of reactions have been published [3-4]. We have developed exact random variate generators of these Green functions [5], which will allow us to use them in radiation chemistry codes. Moreover, simulating chemistry using the Green functions is which is computationally very demanding, because the probabilities of reactions between each pair of particles should be evaluated at each timestep [2]. This kind of problem is well adapted for General Purpose Graphic Processing Units (GPGPU), which can handle a large number of similar calculations simultaneously. These new developments will allow us to include more complex reactions in chemistry codes, and to improve the calculation time. This code should be of importance to link radiation track structure simulations and DNA damage models.

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

Quantitative determination of the conformational properties of partially folded and intrinsically disordered proteins using NMR dipolar couplings.

PubMed

Jensen, Malene Ringkjøbing; Markwick, Phineus R L; Meier, Sebastian; Griesinger, Christian; Zweckstetter, Markus; Grzesiek, Stephan; Bernadó, Pau; Blackledge, Martin

2009-09-09

Intrinsically disordered proteins (IDPs) inhabit a conformational landscape that is too complex to be described by classical structural biology, posing an entirely new set of questions concerning the molecular understanding of functional biology. The characterization of the conformational properties of IDPs, and the elucidation of the role they play in molecular function, is therefore one of the major challenges remaining for modern structural biology. NMR is the technique of choice for studying this class of proteins, providing information about structure, flexibility, and interactions at atomic resolution even in completely disordered states. In particular, residual dipolar couplings (RDCs) have been shown to be uniquely sensitive and powerful tools for characterizing local and long-range structural behavior in disordered proteins. In this review we describe recent applications of RDCs to quantitatively describe the level of local structure and transient long-range order in IDPs involved in viral replication, neurodegenerative disease, and cancer.

Genomic Heterogeneity of Osteosarcoma - Shift from Single Candidates to Functional Modules

PubMed Central

Maugg, Doris; Eckstein, Gertrud; Baumhoer, Daniel; Nathrath, Michaela; Korsching, Eberhard

2015-01-01

Osteosarcoma (OS), a bone tumor, exhibit a complex karyotype. On the genomic level a highly variable degree of alterations in nearly all chromosomal regions and between individual tumors is observable. This hampers the identification of common drivers in OS biology. To identify the common molecular mechanisms involved in the maintenance of OS, we follow the hypothesis that all the copy number-associated differences between the patients are intercepted on the level of the functional modules. The implementation is based on a network approach utilizing copy number associated genes in OS, paired expression data and protein interaction data. The resulting functional modules of tightly connected genes were interpreted regarding their biological functions in OS and their potential prognostic significance. We identified an osteosarcoma network assembling well-known and lesser-known candidates. The derived network shows a significant connectivity and modularity suggesting that the genes affected by the heterogeneous genetic alterations share the same biological context. The network modules participate in several critical aspects of cancer biology like DNA damage response, cell growth, and cell motility which is in line with the hypothesis of specifically deregulated but functional modules in cancer. Further, we could deduce genes with possible prognostic significance in OS for further investigation (e.g. EZR, CDKN2A, MAP3K5). Several of those module genes were located on chromosome 6q. The given systems biological approach provides evidence that heterogeneity on the genomic and expression level is ordered by the biological system on the level of the functional modules. Different genomic aberrations are pointing to the same cellular network vicinity to form vital, but already neoplastically altered, functional modules maintaining OS. This observation, exemplarily now shown for OS, has been under discussion already for a longer time, but often in a hypothetical manner, and can here be exemplified for OS. PMID:25848766

Ecosystem health in mineralized terrane; data from podiform chromite (Chinese Camp mining district, California), quartz alunite (Castle Peak and Masonic mining districts, Nevada/California), and Mo/Cu porphyry (Battle Mountain mining district, Nevada) deposits

USGS Publications Warehouse

Blecker, Steve W.; Stillings, Lisa L.; Amacher, Michael C.; Ippolito, James A.; DeCrappeo, Nicole M.

2010-01-01

The myriad definitions of soil/ecosystem quality or health are often driven by ecosystem and management concerns, and they typically focus on the ability of the soil to provide functions relating to biological productivity and/or environmental quality. A variety of attempts have been made to create indices that quantify the complexities of soil quality and provide a means of evaluating the impact of various natural and anthropogenic disturbances. Though not without their limitations, indices can improve our understanding of the controls behind ecosystem processes and allow for the distillation of information to help link scientific and management communities. In terrestrial systems, indices were initially developed and modified for agroecosystems; however, the number of studies implementing such indices in nonagricultural systems is growing. Soil quality indices (SQIs) are typically composed of biological (and sometimes physical and chemical) parameters that attempt to reduce the complexity of a system into a metric of a soil’s ability to carry out one or more functions.The indicators utilized in SQIs can be as varied as the studies themselves, reflecting the complexity of the soil and ecosystems in which they function. Regardless, effective soil quality indicators should correlate well with soil or ecosystem processes, integrate those properties and processes, and be relevant to management practices. Commonly applied biological indicators include measures associated with soil microbial activity or function (for example, carbon and nitrogen mineralization, respiration, microbial biomass, enzyme activity. Cost, accessibility, ease of interpretation, and presence of existing data often dictate indicator selection given the number of available measures. We employed a large number of soil biological, chemical, and physical measures, along with measures of vegetation cover, density, and productivity, in order to test the utility and sensitivity of these measures within various mineralized terranes. We were also interested in examining these relations in the context of determining appropriate reference conditions with which to compare reclamation efforts.The purpose of this report is to present the data used to develop indices of soil and ecosystem quality associated with mineralized terranes (areas enriched in metal-bearing minerals), specifically podiform chromite, quartz alunite, and Mo/Cu porphyry systems. Within each of these mineralized terranes, a nearby unmineralized counterpart was chosen for comparison. The data consist of soil biological, chemical, and physical parameters, along with vegetation measurements for each of the sites described below. Synthesis of these data and index development will be the subject of future publications.

A Review of Podocyte Biology.

PubMed

Garg, Puneet

2018-05-31

Podocyte biology is a developing science that promises to help improve understanding of the mechanistic nature of multiple diseases associated with proteinuria. Proteinuria in nephrotic syndrome has been linked to mechanistic dysfunctions in the renal glomerulus involving the function of podocyte epithelial cells, including podocyte foot process effacement. Developments in imaging technology are improving knowledge of the detailed structure of the human renal glomerulus and cortex. Podocyte foot processes attach themselves to the glomerular capillaries at the glomerular basement membrane (GBM) forming intercellular junctions that form slit diaphragm filtration barriers that help maintain normal renal function. Damage in this area has been implicated in glomerular disease. Injured podocytes undergo effacement whereby they lose their structure and spread out, leading to a reduction in filtration barrier function. Effacement is typically associated with the presence of proteinuria in focal segmental glomerulosclerosis, minimal change disease, and diabetes. It is thought to be due to a breakdown in the actin cytoskeleton of the foot processes, complex contractile apparatuses that allow podocytes to dynamically reorganize according to changes in filtration requirements. The process of podocyte depletion correlates with the development of glomerular sclerosis and chronic kidney disease. Focal adhesion complexes that interact with the underlying GBM bind the podocytes within the glomerular structure and prevent their detachment. Key Messages: Knowledge of glomerular podocyte biology is helping to advance our understanding of the science and mechanics of the glomerular filtering process, opening the way to a variety of new potential applications for clinical targeting. © 2018 S. Karger AG, Basel.

Mode localization in the cooperative dynamics of protein recognition

NASA Astrophysics Data System (ADS)

Copperman, J.; Guenza, M. G.

2016-07-01

The biological function of proteins is encoded in their structure and expressed through the mediation of their dynamics. This paper presents a study on the correlation between local fluctuations, binding, and biological function for two sample proteins, starting from the Langevin Equation for Protein Dynamics (LE4PD). The LE4PD is a microscopic and residue-specific coarse-grained approach to protein dynamics, which starts from the static structural ensemble of a protein and predicts the dynamics analytically. It has been shown to be accurate in its prediction of NMR relaxation experiments and Debye-Waller factors. The LE4PD is solved in a set of diffusive modes which span a vast range of time scales of the protein dynamics, and provides a detailed picture of the mode-dependent localization of the fluctuation as a function of the primary structure of the protein. To investigate the dynamics of protein complexes, the theory is implemented here to treat the coarse-grained dynamics of interacting macromolecules. As an example, calculations of the dynamics of monomeric and dimerized HIV protease and the free Insulin Growth Factor II Receptor (IGF2R) domain 11 and its IGF2R:IGF2 complex are presented. Either simulation-derived or experimentally measured NMR conformers are used as input structural ensembles to the theory. The picture that emerges suggests a dynamical heterogeneous protein where biologically active regions provide energetically comparable conformational states that are trapped by a reacting partner in agreement with the conformation-selection mechanism of binding.

The fractal geometry of life.

PubMed

Losa, Gabriele A

2009-01-01

The extension of the concepts of Fractal Geometry (Mandelbrot [1983]) toward the life sciences has led to significant progress in understanding complex functional properties and architectural / morphological / structural features characterising cells and tissues during ontogenesis and both normal and pathological development processes. It has even been argued that fractal geometry could provide a coherent description of the design principles underlying living organisms (Weibel [1991]). Fractals fulfil a certain number of theoretical and methodological criteria including a high level of organization, shape irregularity, functional and morphological self-similarity, scale invariance, iterative pathways and a peculiar non-integer fractal dimension [FD]. Whereas mathematical objects are deterministic invariant or self-similar over an unlimited range of scales, biological components are statistically self-similar only within a fractal domain defined by upper and lower limits, called scaling window, in which the relationship between the scale of observation and the measured size or length of the object can be established (Losa and Nonnenmacher [1996]). Selected examples will contribute to depict complex biological shapes and structures as fractal entities, and also to show why the application of the fractal principle is valuable for measuring dimensional, geometrical and functional parameters of cells, tissues and organs occurring within the vegetal and animal realms. If the criteria for a strict description of natural fractals are met, then it follows that a Fractal Geometry of Life may be envisaged and all natural objects and biological systems exhibiting self-similar patterns and scaling properties may be considered as belonging to the new subdiscipline of "fractalomics".

Visualizing estrogen receptor-a-expressing neurons using a new ERa-ZsGreen reporter mouse line

USDA-ARS?s Scientific Manuscript database

A variety of biological functions of estrogens, including regulation of energy metabolism, are mediated by neurons expressingestrogen receptor-a (ERa) in the brain. However, complex intracellular processes in these ERa-expressing neurons are difficult to unravel, due to the lack of strategy to visua...

An efficient polymeric micromotor doped with Pt nanoparticle@carbon nanotubes for complex bio-media.

PubMed

Li, Yana; Wu, Jie; Xie, Yuzhe; Ju, Huangxian

2015-04-14

A highly efficient polymeric tubular micromotor doped with Pt nanoparticle@carbon nanotubes is fabricated by template-assisted electrochemical growth. The micromotors preserve good navigation in multi-media and surface modification, along with simple synthesis, easy functionalization and good biocompatibility, displaying great promise in biological applications.

A shortcut to wide-ranging biological actions of dietary polyphenols: modulation of the nitrate-nitrite-nitric oxide pathway in the gut.

PubMed

Rocha, Bárbara S; Nunes, Carla; Pereira, Cassilda; Barbosa, Rui M; Laranjinha, João

2014-08-01

Dietary polyphenols are complex, natural compounds with recognized health benefits. Initially attractive to the biomedical area due to their in vitro antioxidant properties, the biological implications of polyphenols are now known to be far from their acute ability to scavenge free radicals but rather to modulate redox signaling pathways. Actually, it is now recognized that dietary polyphenols are extensively metabolized in vivo and that the chemical, biophysical and biological properties of their metabolites are, in most cases, quite different from the ones of the parent molecules. Hence, the study of the metabolic, absorptive and signaling pathways of both phenolics and derivatives has become a major issue. In this paper we propose a short-cut for the systemic effects of polyphenols in connection with nitric oxide (˙NO) biology. This free radical is a ubiquitous signaling molecule with pivotal functions in vivo. It is produced through an enzymatic pathway and also through the reduction of dietary nitrate and nitrite in the human stomach. At acidic gastric pH, dietary polyphenols, in the form they are conveyed in foods and at high concentration, not only promote nitrite reduction to ˙NO but also embark in a complex network of chemical reactions to produce higher nitrogen oxides with signaling functions, namely by inducing post-translational modifications. Modified endogenous molecules, such as nitrated proteins and lipids, acquire important physiological functions. Thus, local and systemic effects of ˙NO such as modulation of vascular tone, mucus production in the gut and protection against ischemia-reperfusion injury are, in this sense, triggered by dietary polyphenols. Evidence to support the signaling and biological effects of polyphenols by modulation of the nitrate-nitrite-NO pathway will be herein provided and discussed. General actions of polyphenols encompassing absorption and metabolism in the intestine/liver are short-cut via the production of diffusible species in the stomach that have not only a local but also a general impact.

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.

Atomic switch networks—nanoarchitectonic design of a complex system for natural computing

NASA Astrophysics Data System (ADS)

Demis, E. C.; Aguilera, R.; Sillin, H. O.; Scharnhorst, K.; Sandouk, E. J.; Aono, M.; Stieg, A. Z.; Gimzewski, J. K.

2015-05-01

Self-organized complex systems are ubiquitous in nature, and the structural complexity of these natural systems can be used as a model to design new classes of functional nanotechnology based on highly interconnected networks of interacting units. Conventional fabrication methods for electronic computing devices are subject to known scaling limits, confining the diversity of possible architectures. This work explores methods of fabricating a self-organized complex device known as an atomic switch network and discusses its potential utility in computing. Through a merger of top-down and bottom-up techniques guided by mathematical and nanoarchitectonic design principles, we have produced functional devices comprising nanoscale elements whose intrinsic nonlinear dynamics and memorization capabilities produce robust patterns of distributed activity and a capacity for nonlinear transformation of input signals when configured in the appropriate network architecture. Their operational characteristics represent a unique potential for hardware implementation of natural computation, specifically in the area of reservoir computing—a burgeoning field that investigates the computational aptitude of complex biologically inspired systems.

Atomic switch networks-nanoarchitectonic design of a complex system for natural computing.

PubMed

Demis, E C; Aguilera, R; Sillin, H O; Scharnhorst, K; Sandouk, E J; Aono, M; Stieg, A Z; Gimzewski, J K

2015-05-22

Self-organized complex systems are ubiquitous in nature, and the structural complexity of these natural systems can be used as a model to design new classes of functional nanotechnology based on highly interconnected networks of interacting units. Conventional fabrication methods for electronic computing devices are subject to known scaling limits, confining the diversity of possible architectures. This work explores methods of fabricating a self-organized complex device known as an atomic switch network and discusses its potential utility in computing. Through a merger of top-down and bottom-up techniques guided by mathematical and nanoarchitectonic design principles, we have produced functional devices comprising nanoscale elements whose intrinsic nonlinear dynamics and memorization capabilities produce robust patterns of distributed activity and a capacity for nonlinear transformation of input signals when configured in the appropriate network architecture. Their operational characteristics represent a unique potential for hardware implementation of natural computation, specifically in the area of reservoir computing-a burgeoning field that investigates the computational aptitude of complex biologically inspired systems.

Silk-polypyrrole biocompatible actuator performance under biologically relevant conditions

NASA Astrophysics Data System (ADS)

Hagler, Jo'elen; Peterson, Ben; Murphy, Amanda; Leger, Janelle

Biocompatible actuators that are capable of controlled movement and can function under biologically relevant conditions are of significant interest in biomedical fields. Previously, we have demonstrated that a composite material of silk biopolymer and the conducting polymer polypyrrole (PPy) can be formed into a bilayer device that can bend under applied voltage. Further, these silk-PPy composites can generate forces comparable to human muscle (>0.1 MPa) making them ideal candidates for interfacing with biological tissues. Here silk-PPy composite films are tested for performance under biologically relevant conditions including exposure to a complex protein serum and biologically relevant temperatures. Free-end bending actuation performance, current response, force generation and, mass degradation were investigated . Preliminary results show that when exposed to proteins and biologically relevant temperatures, these silk-PPy composites show minimal degradation and are able to generate forces and conduct currents comparable to devices tested under standard conditions. NSF.

Mammalian synthetic biology for studying the cell.

PubMed

Mathur, Melina; Xiang, Joy S; Smolke, Christina D

2017-01-02

Synthetic biology is advancing the design of genetic devices that enable the study of cellular and molecular biology in mammalian cells. These genetic devices use diverse regulatory mechanisms to both examine cellular processes and achieve precise and dynamic control of cellular phenotype. Synthetic biology tools provide novel functionality to complement the examination of natural cell systems, including engineered molecules with specific activities and model systems that mimic complex regulatory processes. Continued development of quantitative standards and computational tools will expand capacities to probe cellular mechanisms with genetic devices to achieve a more comprehensive understanding of the cell. In this study, we review synthetic biology tools that are being applied to effectively investigate diverse cellular processes, regulatory networks, and multicellular interactions. We also discuss current challenges and future developments in the field that may transform the types of investigation possible in cell biology. © 2017 Mathur et al.

BioInt: an integrative biological object-oriented application framework and interpreter.

PubMed

Desai, Sanket; Burra, Prasad

2015-01-01

BioInt, a biological programming application framework and interpreter, is an attempt to equip the researchers with seamless integration, efficient extraction and effortless analysis of the data from various biological databases and algorithms. Based on the type of biological data, algorithms and related functionalities, a biology-specific framework was developed which has nine modules. The modules are a compilation of numerous reusable BioADTs. This software ecosystem containing more than 450 biological objects underneath the interpreter makes it flexible, integrative and comprehensive. Similar to Python, BioInt eliminates the compilation and linking steps cutting the time significantly. The researcher can write the scripts using available BioADTs (following C++ syntax) and execute them interactively or use as a command line application. It has features that enable automation, extension of the framework with new/external BioADTs/libraries and deployment of complex work flows.

Cooperation of Deterministic Dynamics and Random Noise in Production of Complex Syntactical Avian Song Sequences: A Neural Network Model

PubMed Central

Yamashita, Yuichi; Okumura, Tetsu; Okanoya, Kazuo; Tani, Jun

2011-01-01

How the brain learns and generates temporal sequences is a fundamental issue in neuroscience. The production of birdsongs, a process which involves complex learned sequences, provides researchers with an excellent biological model for this topic. The Bengalese finch in particular learns a highly complex song with syntactical structure. The nucleus HVC (HVC), a premotor nucleus within the avian song system, plays a key role in generating the temporal structures of their songs. From lesion studies, the nucleus interfacialis (NIf) projecting to the HVC is considered one of the essential regions that contribute to the complexity of their songs. However, the types of interaction between the HVC and the NIf that can produce complex syntactical songs remain unclear. In order to investigate the function of interactions between the HVC and NIf, we have proposed a neural network model based on previous biological evidence. The HVC is modeled by a recurrent neural network (RNN) that learns to generate temporal patterns of songs. The NIf is modeled as a mechanism that provides auditory feedback to the HVC and generates random noise that feeds into the HVC. The model showed that complex syntactical songs can be replicated by simple interactions between deterministic dynamics of the RNN and random noise. In the current study, the plausibility of the model is tested by the comparison between the changes in the songs of actual birds induced by pharmacological inhibition of the NIf and the changes in the songs produced by the model resulting from modification of parameters representing NIf functions. The efficacy of the model demonstrates that the changes of songs induced by pharmacological inhibition of the NIf can be interpreted as a trade-off between the effects of noise and the effects of feedback on the dynamics of the RNN of the HVC. These facts suggest that the current model provides a convincing hypothesis for the functional role of NIf–HVC interaction. PMID:21559065

EvoluCode: Evolutionary Barcodes as a Unifying Framework for Multilevel Evolutionary Data.

PubMed

Linard, Benjamin; Nguyen, Ngoc Hoan; Prosdocimi, Francisco; Poch, Olivier; Thompson, Julie D

2012-01-01

Evolutionary systems biology aims to uncover the general trends and principles governing the evolution of biological networks. An essential part of this process is the reconstruction and analysis of the evolutionary histories of these complex, dynamic networks. Unfortunately, the methodologies for representing and exploiting such complex evolutionary histories in large scale studies are currently limited. Here, we propose a new formalism, called EvoluCode (Evolutionary barCode), which allows the integration of different evolutionary parameters (eg, sequence conservation, orthology, synteny …) in a unifying format and facilitates the multilevel analysis and visualization of complex evolutionary histories at the genome scale. The advantages of the approach are demonstrated by constructing barcodes representing the evolution of the complete human proteome. Two large-scale studies are then described: (i) the mapping and visualization of the barcodes on the human chromosomes and (ii) automatic clustering of the barcodes to highlight protein subsets sharing similar evolutionary histories and their functional analysis. The methodologies developed here open the way to the efficient application of other data mining and knowledge extraction techniques in evolutionary systems biology studies. A database containing all EvoluCode data is available at: http://lbgi.igbmc.fr/barcodes.

Integrated Information Increases with Fitness in the Evolution of Animats

PubMed Central

Edlund, Jeffrey A.; Chaumont, Nicolas; Hintze, Arend; Koch, Christof; Tononi, Giulio; Adami, Christoph

2011-01-01

One of the hallmarks of biological organisms is their ability to integrate disparate information sources to optimize their behavior in complex environments. How this capability can be quantified and related to the functional complexity of an organism remains a challenging problem, in particular since organismal functional complexity is not well-defined. We present here several candidate measures that quantify information and integration, and study their dependence on fitness as an artificial agent (“animat”) evolves over thousands of generations to solve a navigation task in a simple, simulated environment. We compare the ability of these measures to predict high fitness with more conventional information-theoretic processing measures. As the animat adapts by increasing its “fit” to the world, information integration and processing increase commensurately along the evolutionary line of descent. We suggest that the correlation of fitness with information integration and with processing measures implies that high fitness requires both information processing as well as integration, but that information integration may be a better measure when the task requires memory. A correlation of measures of information integration (but also information processing) and fitness strongly suggests that these measures reflect the functional complexity of the animat, and that such measures can be used to quantify functional complexity even in the absence of fitness data. PMID:22028639

Grafting of [(64)Cu]-TPPF20 porphyrin complex on Functionalized nano-porous MCM-41 silica as a potential cancer imaging agent.

PubMed

Fazaeli, Yousef; Feizi, Shahzad; Jalilian, Amir R; Hejrani, Ali

2016-06-01

Mesoporous silica, MCM-41, functionalized with 3-aminopropyltriethoxysilane (APTES) was investigated as a potential drug delivery system, using [(64)Cu]-5, 10, 15, 20-tetrakis penta fluorophenyl porphyrin complex. [(64)Cu]-TPPF20 complex was grafted on functionalized MCM-41. The product was characterized by paper chromatography, FTIR spectroscopy, low angle X-ray diffraction, CHN and TGA/DTA analyses and atomic force microscopy. The biological evaluations of the grafted complex, [(64)Cu]-TPPF20@NH2-MCM-41, were done in Fibrosarcoma tumor-bearing Sprague-Dawley rats using scarification studies and Sopha DST-XL Dual-Head SPECT system. The actual loading amount of aminopropyl groups was found about 1.6mmol per gram of final silica. The specific activity of the final compound was found to be 3Ci/g. Amine functionalized MCM-41 was found to be a good platform for theranostic radiopharmaceuticals such as copper-64 complexes. Considering the accumulation of the tracer in tumor cells, fast wash-out from normal tissues, the short half-life copper-64 and less imposed radiation doses to patients, [(64)Cu]-TPPF20@NH2-MCM-41 can potentially be a suitable candidate for tumor imaging applications and future PET studies. Copyright © 2016 Elsevier Ltd. All rights reserved.

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.

Genome-wide protein-protein interactions and protein function exploration in cyanobacteria

PubMed Central

Lv, Qi; Ma, Weimin; Liu, Hui; Li, Jiang; Wang, Huan; Lu, Fang; Zhao, Chen; Shi, Tieliu

2015-01-01

Genome-wide network analysis is well implemented to study proteins of unknown function. Here, we effectively explored protein functions and the biological mechanism based on inferred high confident protein-protein interaction (PPI) network in cyanobacteria. We integrated data from seven different sources and predicted 1,997 PPIs, which were evaluated by experiments in molecular mechanism, text mining of literatures in proved direct/indirect evidences, and “interologs” in conservation. Combined the predicted PPIs with known PPIs, we obtained 4,715 no-redundant PPIs (involving 3,231 proteins covering over 90% of genome) to generate the PPI network. Based on the PPI network, terms in Gene ontology (GO) were assigned to function-unknown proteins. Functional modules were identified by dissecting the PPI network into sub-networks and analyzing pathway enrichment, with which we investigated novel function of underlying proteins in protein complexes and pathways. Examples of photosynthesis and DNA repair indicate that the network approach is a powerful tool in protein function analysis. Overall, this systems biology approach provides a new insight into posterior functional analysis of PPIs in cyanobacteria. PMID:26490033

Bipartite graphs in systems biology and medicine: a survey of methods and applications.

PubMed

Pavlopoulos, Georgios A; Kontou, Panagiota I; Pavlopoulou, Athanasia; Bouyioukos, Costas; Markou, Evripides; Bagos, Pantelis G

2018-04-01

The latest advances in high-throughput techniques during the past decade allowed the systems biology field to expand significantly. Today, the focus of biologists has shifted from the study of individual biological components to the study of complex biological systems and their dynamics at a larger scale. Through the discovery of novel bioentity relationships, researchers reveal new information about biological functions and processes. Graphs are widely used to represent bioentities such as proteins, genes, small molecules, ligands, and others such as nodes and their connections as edges within a network. In this review, special focus is given to the usability of bipartite graphs and their impact on the field of network biology and medicine. Furthermore, their topological properties and how these can be applied to certain biological case studies are discussed. Finally, available methodologies and software are presented, and useful insights on how bipartite graphs can shape the path toward the solution of challenging biological problems are provided.

Protein Complex Production from the Drug Discovery Standpoint.

PubMed

Moarefi, Ismail

2016-01-01

Small molecule drug discovery critically depends on the availability of meaningful in vitro assays to guide medicinal chemistry programs that are aimed at optimizing drug potency and selectivity. As it becomes increasingly evident, most disease relevant drug targets do not act as a single protein. In the body, they are instead generally found in complex with protein cofactors that are highly relevant for their correct function and regulation. This review highlights selected examples of the increasing trend to use biologically relevant protein complexes for rational drug discovery to reduce costly late phase attritions due to lack of efficacy or toxicity.

The KUPNetViz: a biological network viewer for multiple -omics datasets in kidney diseases.

PubMed

Moulos, Panagiotis; Klein, Julie; Jupp, Simon; Stevens, Robert; Bascands, Jean-Loup; Schanstra, Joost P

2013-07-24

Constant technological advances have allowed scientists in biology to migrate from conventional single-omics to multi-omics experimental approaches, challenging bioinformatics to bridge this multi-tiered information. Ongoing research in renal biology is no exception. The results of large-scale and/or high throughput experiments, presenting a wealth of information on kidney disease are scattered across the web. To tackle this problem, we recently presented the KUPKB, a multi-omics data repository for renal diseases. In this article, we describe KUPNetViz, a biological graph exploration tool allowing the exploration of KUPKB data through the visualization of biomolecule interactions. KUPNetViz enables the integration of multi-layered experimental data over different species, renal locations and renal diseases to protein-protein interaction networks and allows association with biological functions, biochemical pathways and other functional elements such as miRNAs. KUPNetViz focuses on the simplicity of its usage and the clarity of resulting networks by reducing and/or automating advanced functionalities present in other biological network visualization packages. In addition, it allows the extrapolation of biomolecule interactions across different species, leading to the formulations of new plausible hypotheses, adequate experiment design and to the suggestion of novel biological mechanisms. We demonstrate the value of KUPNetViz by two usage examples: the integration of calreticulin as a key player in a larger interaction network in renal graft rejection and the novel observation of the strong association of interleukin-6 with polycystic kidney disease. The KUPNetViz is an interactive and flexible biological network visualization and exploration tool. It provides renal biologists with biological network snapshots of the complex integrated data of the KUPKB allowing the formulation of new hypotheses in a user friendly manner.

The KUPNetViz: a biological network viewer for multiple -omics datasets in kidney diseases

PubMed Central

2013-01-01

Background Constant technological advances have allowed scientists in biology to migrate from conventional single-omics to multi-omics experimental approaches, challenging bioinformatics to bridge this multi-tiered information. Ongoing research in renal biology is no exception. The results of large-scale and/or high throughput experiments, presenting a wealth of information on kidney disease are scattered across the web. To tackle this problem, we recently presented the KUPKB, a multi-omics data repository for renal diseases. Results In this article, we describe KUPNetViz, a biological graph exploration tool allowing the exploration of KUPKB data through the visualization of biomolecule interactions. KUPNetViz enables the integration of multi-layered experimental data over different species, renal locations and renal diseases to protein-protein interaction networks and allows association with biological functions, biochemical pathways and other functional elements such as miRNAs. KUPNetViz focuses on the simplicity of its usage and the clarity of resulting networks by reducing and/or automating advanced functionalities present in other biological network visualization packages. In addition, it allows the extrapolation of biomolecule interactions across different species, leading to the formulations of new plausible hypotheses, adequate experiment design and to the suggestion of novel biological mechanisms. We demonstrate the value of KUPNetViz by two usage examples: the integration of calreticulin as a key player in a larger interaction network in renal graft rejection and the novel observation of the strong association of interleukin-6 with polycystic kidney disease. Conclusions The KUPNetViz is an interactive and flexible biological network visualization and exploration tool. It provides renal biologists with biological network snapshots of the complex integrated data of the KUPKB allowing the formulation of new hypotheses in a user friendly manner. PMID:23883183

The fusion of biology, computer science, and engineering: towards efficient and successful synthetic biology.

PubMed

Linshiz, Gregory; Goldberg, Alex; Konry, Tania; Hillson, Nathan J

2012-01-01

Synthetic biology is a nascent field that emerged in earnest only around the turn of the millennium. It aims to engineer new biological systems and impart new biological functionality, often through genetic modifications. The design and construction of new biological systems is a complex, multistep process, requiring multidisciplinary collaborative efforts from "fusion" scientists who have formal training in computer science or engineering, as well as hands-on biological expertise. The public has high expectations for synthetic biology and eagerly anticipates the development of solutions to the major challenges facing humanity. This article discusses laboratory practices and the conduct of research in synthetic biology. It argues that the fusion science approach, which integrates biology with computer science and engineering best practices, including standardization, process optimization, computer-aided design and laboratory automation, miniaturization, and systematic management, will increase the predictability and reproducibility of experiments and lead to breakthroughs in the construction of new biological systems. The article also discusses several successful fusion projects, including the development of software tools for DNA construction design automation, recursive DNA construction, and the development of integrated microfluidics systems.

URI Regulates KAP1 Phosphorylation and Transcriptional Repression via PP2A Phosphatase in Prostate Cancer Cells.

PubMed

Mita, Paolo; Savas, Jeffrey N; Briggs, Erica M; Ha, Susan; Gnanakkan, Veena; Yates, John R; Robins, Diane M; David, Gregory; Boeke, Jef D; Garabedian, Michael J; Logan, Susan K

2016-12-02

URI (unconventional prefoldin RPB5 interactor protein) is an unconventional prefoldin, RNA polymerase II interactor that functions as a transcriptional repressor and is part of a larger nuclear protein complex. The components of this complex and the mechanism of transcriptional repression have not been characterized. Here we show that KAP1 (KRAB-associated protein 1) and the protein phosphatase PP2A interact with URI. Mechanistically, we show that KAP1 phosphorylation is decreased following recruitment of PP2A by URI. We functionally characterize the novel URI-KAP1-PP2A complex, demonstrating a role of URI in retrotransposon repression, a key function previously demonstrated for the KAP1-SETDB1 complex. Microarray analysis of annotated transposons revealed a selective increase in the transcription of LINE-1 and L1PA2 retroelements upon knockdown of URI. These data unveil a new nuclear function of URI and identify a novel post-transcriptional regulation of KAP1 protein that may have important implications in reactivation of transposable elements in prostate cancer cells. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.

Functions of MicroRNAs in Cardiovascular Biology and Disease

PubMed Central

Hata, Akiko

2015-01-01

In 1993, lin-4 was discovered as a critical modulator of temporal development in Caenorhabditis elegans and, most notably, as the first in the class of small, single-stranded noncoding RNAs now defined as microRNAs (miRNAs). Another eight years elapsed before miRNA expression was detected in mammalian cells. Since then, explosive advancements in the field of miRNA biology have elucidated the basic mechanism of miRNA biogenesis, regulation, and gene-regulatory function. The discovery of this new class of small RNAs has augmented the complexity of gene-regulatory programs as well as the understanding of developmental and pathological processes in the cardiovascular system. Indeed, the contributions of miRNAs in cardiovascular development and function have been widely explored, revealing the extensive role of these small regulatory RNAs in cardiovascular physiology. PMID:23157557

Chemical roots of biological evolution: the origins of life as a process of development of autonomous functional systems

PubMed Central

Ruiz-Mirazo, Kepa; Briones, Carlos

2017-01-01

In recent years, an extension of the Darwinian framework is being considered for the study of prebiotic chemical evolution, shifting the attention from homogeneous populations of naked molecular species to populations of heterogeneous, compartmentalized and functionally integrated assemblies of molecules. Several implications of this shift of perspective are analysed in this critical review, both in terms of the individual units, which require an adequate characterization as self-maintaining systems with an internal organization, and also in relation to their collective and long-term evolutionary dynamics, based on competition, collaboration and selection processes among those complex individuals. On these lines, a concrete proposal for the set of molecular control mechanisms that must be coupled to bring about autonomous functional systems, at the interface between chemistry and biology, is provided. PMID:28446711

Chemical roots of biological evolution: the origins of life as a process of development of autonomous functional systems.

PubMed

Ruiz-Mirazo, Kepa; Briones, Carlos; de la Escosura, Andrés

2017-04-01

In recent years, an extension of the Darwinian framework is being considered for the study of prebiotic chemical evolution, shifting the attention from homogeneous populations of naked molecular species to populations of heterogeneous, compartmentalized and functionally integrated assemblies of molecules. Several implications of this shift of perspective are analysed in this critical review, both in terms of the individual units, which require an adequate characterization as self-maintaining systems with an internal organization, and also in relation to their collective and long-term evolutionary dynamics, based on competition, collaboration and selection processes among those complex individuals. On these lines, a concrete proposal for the set of molecular control mechanisms that must be coupled to bring about autonomous functional systems, at the interface between chemistry and biology, is provided. © 2017 The Authors.

Cellulosome-based, Clostridium-derived multi-functional enzyme complexes for advanced biotechnology tool development: advances and applications.

PubMed

Hyeon, Jeong Eun; Jeon, Sang Duck; Han, Sung Ok

2013-11-01

The cellulosome is one of nature's most elegant and elaborate nanomachines and a key biological and biotechnological macromolecule that can be used as a multi-functional protein complex tool. Each protein module in the cellulosome system is potentially useful in an advanced biotechnology application. The high-affinity interactions between the cohesin and dockerin domains can be used in protein-based biosensors to improve both sensitivity and selectivity. The scaffolding protein includes a carbohydrate-binding module (CBM) that attaches strongly to cellulose substrates and facilitates the purification of proteins fused with the dockerin module through a one-step CBM purification method. Although the surface layer homology (SLH) domain of CbpA is not present in other strains, replacement of the cell surface anchoring domain allows a foreign protein to be displayed on the surface of other strains. The development of a hydrolysis enzyme complex is a useful strategy for consolidated bioprocessing (CBP), enabling microorganisms with biomass hydrolysis activity. Thus, the development of various configurations of multi-functional protein complexes for use as tools in whole-cell biocatalyst systems has drawn considerable attention as an attractive strategy for bioprocess applications. This review provides a detailed summary of the current achievements in Clostridium-derived multi-functional complex development and the impact of these complexes in various areas of biotechnology. Copyright © 2013 Elsevier Inc. All rights reserved.

The semiotics of control and modeling relations in complex systems.

PubMed

Joslyn, C

2001-01-01

We provide a conceptual analysis of ideas and principles from the systems theory discourse which underlie Pattee's semantic or semiotic closure, which is itself foundational for a school of theoretical biology derived from systems theory and cybernetics, and is now being related to biological semiotics and explicated in the relational biological school of Rashevsky and Rosen. Atomic control systems and models are described as the canonical forms of semiotic organization, sharing measurement relations, but differing topologically in that control systems are circularly and models linearly related to their environments. Computation in control systems is introduced, motivating hierarchical decomposition, hybrid modeling and control systems, and anticipatory or model-based control. The semiotic relations in complex control systems are described in terms of relational constraints, and rules and laws are distinguished as contingent and necessary functional entailments, respectively. Finally, selection as a meta-level of constraint is introduced as the necessary condition for semantic relations in control systems and models.

Recombinant protein expression for structural biology in HEK 293F suspension cells: a novel and accessible approach.

PubMed

Portolano, Nicola; Watson, Peter J; Fairall, Louise; Millard, Christopher J; Milano, Charles P; Song, Yun; Cowley, Shaun M; Schwabe, John W R

2014-10-16

The expression and purification of large amounts of recombinant protein complexes is an essential requirement for structural biology studies. For over two decades, prokaryotic expression systems such as E. coli have dominated the scientific literature over costly and less efficient eukaryotic cell lines. Despite the clear advantage in terms of yields and costs of expressing recombinant proteins in bacteria, the absence of specific co-factors, chaperones and post-translational modifications may cause loss of function, mis-folding and can disrupt protein-protein interactions of certain eukaryotic multi-subunit complexes, surface receptors and secreted proteins. The use of mammalian cell expression systems can address these drawbacks since they provide a eukaryotic expression environment. However, low protein yields and high costs of such methods have until recently limited their use for structural biology. Here we describe a simple and accessible method for expressing and purifying milligram quantities of protein by performing transient transfections of suspension grown HEK (Human Embryonic Kidney) 293 F cells.

Macromolecular structures probed by combining single-shot free-electron laser diffraction with synchrotron coherent X-ray imaging.

PubMed

Gallagher-Jones, Marcus; Bessho, Yoshitaka; Kim, Sunam; Park, Jaehyun; Kim, Sangsoo; Nam, Daewoong; Kim, Chan; Kim, Yoonhee; Noh, Do Young; Miyashita, Osamu; Tama, Florence; Joti, Yasumasa; Kameshima, Takashi; Hatsui, Takaki; Tono, Kensuke; Kohmura, Yoshiki; Yabashi, Makina; Hasnain, S Samar; Ishikawa, Tetsuya; Song, Changyong

2014-05-02

Nanostructures formed from biological macromolecular complexes utilizing the self-assembly properties of smaller building blocks such as DNA and RNA hold promise for many applications, including sensing and drug delivery. New tools are required for their structural characterization. Intense, femtosecond X-ray pulses from X-ray free-electron lasers enable single-shot imaging allowing for instantaneous views of nanostructures at ambient temperatures. When combined judiciously with synchrotron X-rays of a complimentary nature, suitable for observing steady-state features, it is possible to perform ab initio structural investigation. Here we demonstrate a successful combination of femtosecond X-ray single-shot diffraction with an X-ray free-electron laser and coherent diffraction imaging with synchrotron X-rays to provide an insight into the nanostructure formation of a biological macromolecular complex: RNA interference microsponges. This newly introduced multimodal analysis with coherent X-rays can be applied to unveil nano-scale structural motifs from functional nanomaterials or biological nanocomplexes, without requiring a priori knowledge.

Systems Biology and Biomechanical Model of Heart Failure

PubMed Central

Louridas, George E; Lourida, Katerina G

2012-01-01

Heart failure is seen as a complex disease caused by a combination of a mechanical disorder, cardiac remodeling and neurohormonal activation. To define heart failure the systems biology approach integrates genes and molecules, interprets the relationship of the molecular networks with modular functional units, and explains the interaction between mechanical dysfunction and cardiac remodeling. The biomechanical model of heart failure explains satisfactorily the progression of myocardial dysfunction and the development of clinical phenotypes. The earliest mechanical changes and stresses applied in myocardial cells and/or myocardial loss or dysfunction activate left ventricular cavity remodeling and other neurohormonal regulatory mechanisms such as early release of natriuretic peptides followed by SAS and RAAS mobilization. Eventually the neurohormonal activation and the left ventricular remodeling process are leading to clinical deterioration of heart failure towards a multi-organic damage. It is hypothesized that approaching heart failure with the methodology of systems biology we promote the elucidation of its complex pathophysiology and most probably we can invent new therapeutic strategies. PMID:22935019

A comparative approach for the investigation of biological information processing: An examination of the structure and function of computer hard drives and DNA

PubMed Central

2010-01-01

Background The robust storage, updating and utilization of information are necessary for the maintenance and perpetuation of dynamic systems. These systems can exist as constructs of metal-oxide semiconductors and silicon, as in a digital computer, or in the "wetware" of organic compounds, proteins and nucleic acids that make up biological organisms. We propose that there are essential functional properties of centralized information-processing systems; for digital computers these properties reside in the computer's hard drive, and for eukaryotic cells they are manifest in the DNA and associated structures. Methods Presented herein is a descriptive framework that compares DNA and its associated proteins and sub-nuclear structure with the structure and function of the computer hard drive. We identify four essential properties of information for a centralized storage and processing system: (1) orthogonal uniqueness, (2) low level formatting, (3) high level formatting and (4) translation of stored to usable form. The corresponding aspects of the DNA complex and a computer hard drive are categorized using this classification. This is intended to demonstrate a functional equivalence between the components of the two systems, and thus the systems themselves. Results Both the DNA complex and the computer hard drive contain components that fulfill the essential properties of a centralized information storage and processing system. The functional equivalence of these components provides insight into both the design process of engineered systems and the evolved solutions addressing similar system requirements. However, there are points where the comparison breaks down, particularly when there are externally imposed information-organizing structures on the computer hard drive. A specific example of this is the imposition of the File Allocation Table (FAT) during high level formatting of the computer hard drive and the subsequent loading of an operating system (OS). Biological systems do not have an external source for a map of their stored information or for an operational instruction set; rather, they must contain an organizational template conserved within their intra-nuclear architecture that "manipulates" the laws of chemistry and physics into a highly robust instruction set. We propose that the epigenetic structure of the intra-nuclear environment and the non-coding RNA may play the roles of a Biological File Allocation Table (BFAT) and biological operating system (Bio-OS) in eukaryotic cells. Conclusions The comparison of functional and structural characteristics of the DNA complex and the computer hard drive leads to a new descriptive paradigm that identifies the DNA as a dynamic storage system of biological information. This system is embodied in an autonomous operating system that inductively follows organizational structures, data hierarchy and executable operations that are well understood in the computer science industry. Characterizing the "DNA hard drive" in this fashion can lead to insights arising from discrepancies in the descriptive framework, particularly with respect to positing the role of epigenetic processes in an information-processing context. Further expansions arising from this comparison include the view of cells as parallel computing machines and a new approach towards characterizing cellular control systems. PMID:20092652

A comparative approach for the investigation of biological information processing: an examination of the structure and function of computer hard drives and DNA.

PubMed

D'Onofrio, David J; An, Gary

2010-01-21

The robust storage, updating and utilization of information are necessary for the maintenance and perpetuation of dynamic systems. These systems can exist as constructs of metal-oxide semiconductors and silicon, as in a digital computer, or in the "wetware" of organic compounds, proteins and nucleic acids that make up biological organisms. We propose that there are essential functional properties of centralized information-processing systems; for digital computers these properties reside in the computer's hard drive, and for eukaryotic cells they are manifest in the DNA and associated structures. Presented herein is a descriptive framework that compares DNA and its associated proteins and sub-nuclear structure with the structure and function of the computer hard drive. We identify four essential properties of information for a centralized storage and processing system: (1) orthogonal uniqueness, (2) low level formatting, (3) high level formatting and (4) translation of stored to usable form. The corresponding aspects of the DNA complex and a computer hard drive are categorized using this classification. This is intended to demonstrate a functional equivalence between the components of the two systems, and thus the systems themselves. Both the DNA complex and the computer hard drive contain components that fulfill the essential properties of a centralized information storage and processing system. The functional equivalence of these components provides insight into both the design process of engineered systems and the evolved solutions addressing similar system requirements. However, there are points where the comparison breaks down, particularly when there are externally imposed information-organizing structures on the computer hard drive. A specific example of this is the imposition of the File Allocation Table (FAT) during high level formatting of the computer hard drive and the subsequent loading of an operating system (OS). Biological systems do not have an external source for a map of their stored information or for an operational instruction set; rather, they must contain an organizational template conserved within their intra-nuclear architecture that "manipulates" the laws of chemistry and physics into a highly robust instruction set. We propose that the epigenetic structure of the intra-nuclear environment and the non-coding RNA may play the roles of a Biological File Allocation Table (BFAT) and biological operating system (Bio-OS) in eukaryotic cells. The comparison of functional and structural characteristics of the DNA complex and the computer hard drive leads to a new descriptive paradigm that identifies the DNA as a dynamic storage system of biological information. This system is embodied in an autonomous operating system that inductively follows organizational structures, data hierarchy and executable operations that are well understood in the computer science industry. Characterizing the "DNA hard drive" in this fashion can lead to insights arising from discrepancies in the descriptive framework, particularly with respect to positing the role of epigenetic processes in an information-processing context. Further expansions arising from this comparison include the view of cells as parallel computing machines and a new approach towards characterizing cellular control systems.

Engineering of routes to heparin and related polysaccharides.

PubMed

Bhaskar, Ujjwal; Sterner, Eric; Hickey, Anne Marie; Onishi, Akihiro; Zhang, Fuming; Dordick, Jonathan S; Linhardt, Robert J

2012-01-01

Anticoagulant heparin has been shown to possess important biological functions that vary according to its fine structure. Variability within heparin's structure occurs owing to its biosynthesis and animal tissue-based recovery and adds another dimension to its complex polymeric structure. The structural variations in chain length and sulfation patterns mediate its interaction with many heparin-binding proteins, thereby eliciting complex biological responses. The advent of novel chemical and enzymatic approaches for polysaccharide synthesis coupled with high throughput combinatorial approaches for drug discovery have facilitated an increased effort to understand heparin's structure-activity relationships. An improved understanding would offer potential for new therapeutic development through the engineering of polysaccharides. Such a bioengineering approach requires the amalgamation of several different disciplines, including carbohydrate synthesis, applied enzymology, metabolic engineering, and process biochemistry.

Application of Nanoparticle Technology to Reduce the Anti-Microbial Resistance through β-Lactam Antibiotic-Polymer Inclusion Nano-Complex.

PubMed

Salamanca, Constain H; Yarce, Cristhian J; Roman, Yony; Davalos, Andrés F; Rivera, Gustavo R

2018-02-10

Biocompatible polymeric materials with potential to form functional structures in association with different therapeutic molecules have a high potential for biological, medical and pharmaceutical applications. Therefore, the capability of the inclusion of nano-Complex formed between the sodium salt of poly(maleic acid- alt -octadecene) and a β-lactam drug (ampicillin trihydrate) to avoid the chemical and enzymatic degradation and enhance the biological activity were evaluated. PAM-18Na was produced and characterized, as reported previously. The formation of polymeric hydrophobic aggregates in aqueous solution was determined, using pyrene as a fluorescent probe. Furthermore, the formation of polymer-drug nano-complexes was characterized by Differential Scanning Calorimetry-DSC, viscometric, ultrafiltration/centrifugation assays, zeta potential and size measurements were determined by dynamic light scattering-DLS. The PAM-18Na capacity to avoid the chemical degradation was studied through stress stability tests. The enzymatic degradation was evaluated from a pure β-lactamase, while the biological degradation was determined by different β-lactamase producing Staphylococcus aureus strains. When ampicillin was associated with PAM-18Na, the half-life time in acidic conditions increased, whereas both the enzymatic degradation and the minimum inhibitory concentration decreased to a 90 and 75%, respectively. These results suggest a promissory capability of this polymer to protect the β-lactam drugs against chemical, enzymatic and biological degradation.

Application of Nanoparticle Technology to Reduce the Anti-Microbial Resistance through β-Lactam Antibiotic-Polymer Inclusion Nano-Complex

PubMed Central

Yarce, Cristhian J.; Roman, Yony; Davalos, Andrés F.; Rivera, Gustavo R.

2018-01-01

Biocompatible polymeric materials with potential to form functional structures in association with different therapeutic molecules have a high potential for biological, medical and pharmaceutical applications. Therefore, the capability of the inclusion of nano-Complex formed between the sodium salt of poly(maleic acid-alt-octadecene) and a β-lactam drug (ampicillin trihydrate) to avoid the chemical and enzymatic degradation and enhance the biological activity were evaluated. PAM-18Na was produced and characterized, as reported previously. The formation of polymeric hydrophobic aggregates in aqueous solution was determined, using pyrene as a fluorescent probe. Furthermore, the formation of polymer-drug nano-complexes was characterized by Differential Scanning Calorimetry-DSC, viscometric, ultrafiltration/centrifugation assays, zeta potential and size measurements were determined by dynamic light scattering-DLS. The PAM-18Na capacity to avoid the chemical degradation was studied through stress stability tests. The enzymatic degradation was evaluated from a pure β-lactamase, while the biological degradation was determined by different β-lactamase producing Staphylococcus aureus strains. When ampicillin was associated with PAM-18Na, the half-life time in acidic conditions increased, whereas both the enzymatic degradation and the minimum inhibitory concentration decreased to a 90 and 75%, respectively. These results suggest a promissory capability of this polymer to protect the β-lactam drugs against chemical, enzymatic and biological degradation. PMID:29439391

Structural Analysis of N- and O-glycans Using ZIC-HILIC/Dialysis Coupled to NMR Detection

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

Qu, Yi; Feng, Ju; Deng, Shuang

2014-11-19

Protein glycosylation, an important and complex post-translational modification (PTM), is involved in various biological processes including the receptor-ligand and cell-cell interaction, and plays a crucial role in many biological functions. However, little is known about the glycan structures of important biological complex samples, and the conventional glycan enrichment strategy (i.e., size-exclusion column [SEC] separation,) prior to nuclear magnetic resonance (NMR) detection is time-consuming and tedious. In this study, we employed SEC, Zwitterionic hydrophilic interaction liquid chromatography (ZIC-HILIC), and ZIC-HILIC coupled with dialysis strategies to enrich the glycopeptides from the pronase E digests of RNase B, followed by NMR analysis ofmore » the glycoconjugate. Our results suggest that the ZIC-HILIC enrichment coupled with dialysis is the most efficient, which was thus applied to the analysis of biological complex sample, the pronase E digest of the secreted proteins from the fungi Aspergillus niger. The NMR spectra revealed that the secreted proteins from A. niger contain both N-linked glycans with a high-mannose core and O-linked glycans bearing mannose and glucose with 1->3 and 1->6 linkages. In all, our study provides compelling evidence that ZIC-HILIC separation coupled to dialysis is superior to the commonly used SEC separation to prepare glycopeptides for the downstream NMR analysis, which could greatly facilitate the future NMR-based glycoproteomics research.« less

Linking network topology to function. Comment on "Drivers of structural features in gene regulatory networks: From biophysical constraints to biological function" by O.C. Martin, A. Krzywicki and M. Zagorski

NASA Astrophysics Data System (ADS)

di Bernardo, Diego

2016-07-01

The review by Martin et al. deals with a long standing problem at the interface of complex systems and molecular biology, that is the relationship between the topology of a complex network and its function. In biological terms the problem translates to relating the topology of gene regulatory networks (GRNs) to specific cellular functions. GRNs control the spatial and temporal activity of the genes encoded in the cell's genome by means of specialised proteins called Transcription Factors (TFs). A TF is able to recognise and bind specifically to a sequence (TF biding site) of variable length (order of magnitude of 10) found upstream of the sequence encoding one or more genes (at least in prokaryotes) and thus activating or repressing their transcription. TFs can thus be distinguished in activator and repressor. The picture can become more complex since some classes of TFs can form hetero-dimers consisting of a protein complex whose subunits are the individual TFs. Heterodimers can have completely different binding sites and activity compared to their individual parts. In this review the authors limit their attention to prokaryotes where the complexity of GRNs is somewhat reduced. Moreover they exploit a unique feature of living systems, i.e. evolution, to understand whether function can shape network topology. Indeed, prokaryotes such as bacteria are among the oldest living systems that have become perfectly adapted to their environment over geological scales and thus have reached an evolutionary steady-state where the fitness of the population has reached a plateau. By integrating in silico analysis and comparative evolution, the authors show that indeed function does tend to shape the structure of a GRN, however this trend is not always present and depends on the properties of the network being examined. Interestingly, the trend is more apparent for sparse networks, i.e. where the density of edges is very low. Sparsity is indeed one of the most prominent features of natural occurring GRNs, and more specifically GRNs have been found to approximate a power-law ;scale-free; degree distribution by Barabasi and Albert [2]. Why sparsity arises is still under debate, but Price in 1976 proposed a model [1], later renamed ;preferential attachment; by Barabasi and Albert [2], able to give rise to sparse scale-free networks. In this model, a network grows over time (such as GRN during evolution) by sequential addition of new nodes (caused by genome duplications) that attach with higher probability to nodes with higher degree. In this review, Martin et al. propose that sparsity could also be caused phenotypic constrains even in the absence of genome duplications, in order for the network to be robust against random mutations in the genome sequence, which in turn affect the specificity of TF binding sites. The authors also found that network motifs, i.e. subnetworks consisting of 3 or 4 nodes with a specific topology that are over-represented in the network, are also shaped by phenotypic constrains. Theoretical and computational approaches to understand the forces that shape network topology are of extreme interest in biology, although at this stage their impact has been limited. Neverteless, these approaches may soon have important practical applications. The era of synthetic biology is upon us, novel organisms with ;minimal genomes; are being built with the dual aim of simplifying engineering of new functions useful to humans and to understand which is the minimal set of genes needed to support life [3]. The first minimal organism has just been created [3] by randomly deleting genes and genomic regions until a minimal set supporting cell growth and replication was found. The GRN of this minimal organism has not been investigated yet, but it will be of limited complexity. What is the GRN structure in this organism? Will the cell phenotypes be robust to mutations? Is it possible to re-engineer the GRN in order to find an optimal structure that confers phenotypic robustness to the cell? All of these questions can be tackled only by understanding the guiding principles linking network topology to network function.

Coherent nonlinear optical studies of elementary processes in biological complexes: diagrammatic techniques based on the wave function versus the density matrix

PubMed Central

Biggs, Jason D.; Voll, Judith A.; Mukamel, Shaul

2012-01-01

Two types of diagrammatic approaches for the design and simulation of nonlinear optical experiments (closed-time path loops based on the wave function and double-sided Feynman diagrams for the density matrix) are presented and compared. We give guidelines for the assignment of relevant pathways and provide rules for the interpretation of existing nonlinear experiments in carotenoids. PMID:22753822

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

Reverse Genetics and High Throughput Sequencing Methodologies for Plant Functional Genomics

PubMed Central

Ben-Amar, Anis; Daldoul, Samia; Reustle, Götz M.; Krczal, Gabriele; Mliki, Ahmed

2016-01-01

In the post-genomic era, increasingly sophisticated genetic tools are being developed with the long-term goal of understanding how the coordinated activity of genes gives rise to a complex organism. With the advent of the next generation sequencing associated with effective computational approaches, wide variety of plant species have been fully sequenced giving a wealth of data sequence information on structure and organization of plant genomes. Since thousands of gene sequences are already known, recently developed functional genomics approaches provide powerful tools to analyze plant gene functions through various gene manipulation technologies. Integration of different omics platforms along with gene annotation and computational analysis may elucidate a complete view in a system biology level. Extensive investigations on reverse genetics methodologies were deployed for assigning biological function to a specific gene or gene product. We provide here an updated overview of these high throughout strategies highlighting recent advances in the knowledge of functional genomics in plants. PMID:28217003

Fitness landscapes, heuristics and technological paradigms: A critique on random search models in evolutionary economics

NASA Astrophysics Data System (ADS)

Frenken, Koen

2001-06-01

The biological evolution of complex organisms, in which the functioning of genes is interdependent, has been analyzed as "hill-climbing" on NK fitness landscapes through random mutation and natural selection. In evolutionary economics, NK fitness landscapes have been used to simulate the evolution of complex technological systems containing elements that are interdependent in their functioning. In these models, economic agents randomly search for new technological design by trial-and-error and run the risk of ending up in sub-optimal solutions due to interdependencies between the elements in a complex system. These models of random search are legitimate for reasons of modeling simplicity, but remain limited as these models ignore the fact that agents can apply heuristics. A specific heuristic is one that sequentially optimises functions according to their ranking by users of the system. To model this heuristic, a generalized NK-model is developed. In this model, core elements that influence many functions can be distinguished from peripheral elements that affect few functions. The concept of paradigmatic search can then be analytically defined as search that leaves core elements in tact while concentrating on improving functions by mutation of peripheral elements.

Towards systemic theories in biological psychiatry.

PubMed

Bender, W; Albus, M; Möller, H-J; Tretter, F

2006-02-01

Although still rather controversial, empirical data on the neurobiology of schizophrenia have reached a degree of complexity that makes it hard to obtain a coherent picture of the malfunctions of the brain in schizophrenia. Theoretical neuropsychiatry should therefore use the tools of theoretical sciences like cybernetics, informatics, computational neuroscience or systems science. The methodology of systems science permits the modeling of complex dynamic nonlinear systems. Such procedures might help us to understand brain functions and the disorders and actions of psychiatric drugs better.

Complex-formation-enhanced fluorescence quenching effect for efficient detection of picric acid.

PubMed

Ding, Aixiang; Yang, Longmei; Zhang, Yuyang; Zhang, Gaobin; Kong, Lin; Zhang, Xuanjun; Tian, Yupeng; Tao, Xutang; Yang, Jiaxiang

2014-09-15

Amine-functionalized α-cyanostilbene derivatives (Z)-2-(4-aminophenyl)-3-(4-butoxyphenyl)acrylonitrile (ABA) and (Z)-3-(4-butoxyphenyl)-2-[4-(butylamino)phenyl]acrylonitrile (BBA) were designed for specific recognition of picric acid (PA), an environmental and biological pollutant. The 1:1 host-guest complexes formed between the chemosensors and PA enhanced fluorescence quenching, thus leading to sensitive and selective detection in aqueous media and the solid phase. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Designed Proteins Induce the Formation of Nanocage-containing Extracellular Vesicles

PubMed Central

Votteler, Jörg; Ogohara, Cassandra; Yi, Sue; Hsia, Yang; Nattermann, Una; Belnap, David M.; King, Neil P.; Sundquist, Wesley I.

2017-01-01

Complex biological processes are often performed by self-organizing nanostructures comprising multiple classes of macromolecules, such as ribosomes (proteins and RNA) or enveloped viruses (proteins, nucleic acids, and lipids). Approaches have been developed for designing self-assembling structures consisting of either nucleic acids1,2 or proteins3–5, but strategies for engineering hybrid biological materials are only beginning to emerge6,7. Here, we describe the design of self-assembling protein nanocages that direct their own release from human cells inside small vesicles in a manner that resembles some viruses. We refer to these hybrid biomaterials as Enveloped Protein Nanocages (EPNs). Robust EPN biogenesis required protein sequence elements that encode three distinct functions: membrane binding, self-assembly, and recruitment of the Endosomal Sorting Complexes Required for Transport (ESCRT) machinery8. A variety of synthetic proteins with these functional elements induced EPN biogenesis, highlighting the modularity and generality of the design strategy. Biochemical and electron cryomicroscopic (cryo-EM) analyses revealed that one design, EPN-01, comprised small (~100 nm) vesicles containing multiple protein nanocages that closely matched the structure of the designed 60-subunit self-assembling scaffold9. EPNs that incorporated the vesicular stomatitis viral glycoprotein (VSV-G) could fuse with target cells and deliver their contents, thereby transferring cargoes from one cell to another. These studies show how proteins can be programmed to direct the formation of hybrid biological materials that perform complex tasks, and establish EPNs as a novel class of designed, modular, genetically-encoded nanomaterials that can transfer molecules between cells. PMID:27919066

Experimental and Theoretical Approaches for the Surface Interaction between Copper and Activated Sludge Microorganisms at Molecular Scale

NASA Astrophysics Data System (ADS)

Luo, Hong-Wei; Chen, Jie-Jie; Sheng, Guo-Ping; Su, Ji-Hu; Wei, Shi-Qiang; Yu, Han-Qing

2014-11-01

Interactions between metals and activated sludge microorganisms substantially affect the speciation, immobilization, transport, and bioavailability of trace heavy metals in biological wastewater treatment plants. In this study, the interaction of Cu(II), a typical heavy metal, onto activated sludge microorganisms was studied in-depth using a multi-technique approach. The complexing structure of Cu(II) on microbial surface was revealed by X-ray absorption fine structure (XAFS) and electron paramagnetic resonance (EPR) analysis. EPR spectra indicated that Cu(II) was held in inner-sphere surface complexes of octahedral coordination with tetragonal distortion of axial elongation. XAFS analysis further suggested that the surface complexation between Cu(II) and microbial cells was the distorted inner-sphere coordinated octahedra containing four short equatorial bonds and two elongated axial bonds. To further validate the results obtained from the XAFS and EPR analysis, density functional theory calculations were carried out to explore the structural geometry of the Cu complexes. These results are useful to better understand the speciation, immobilization, transport, and bioavailability of metals in biological wastewater treatment plants.

Functional screening for anti-CMV biologics identifies a broadly neutralizing epitope of an essential envelope protein.

PubMed

Gardner, Thomas J; Stein, Kathryn R; Duty, J Andrew; Schwarz, Toni M; Noriega, Vanessa M; Kraus, Thomas; Moran, Thomas M; Tortorella, Domenico

2016-12-14

The prototypic β-herpesvirus human cytomegalovirus (CMV) establishes life-long persistence within its human host. The CMV envelope consists of various protein complexes that enable wide viral tropism. More specifically, the glycoprotein complex gH/gL/gO (gH-trimer) is required for infection of all cell types, while the gH/gL/UL128/130/131a (gH-pentamer) complex imparts specificity in infecting epithelial, endothelial and myeloid cells. Here we utilize state-of-the-art robotics and a high-throughput neutralization assay to screen and identify monoclonal antibodies (mAbs) targeting the gH glycoproteins that display broad-spectrum properties to inhibit virus infection and dissemination. Subsequent biochemical characterization reveals that the mAbs bind to gH-trimer and gH-pentamer complexes and identify the antibodies' epitope as an 'antigenic hot spot' critical for virus entry. The mAbs inhibit CMV infection at a post-attachment step by interacting with a highly conserved central alpha helix-rich domain. The platform described here provides the framework for development of effective CMV biologics and vaccine design strategies.

Computational structure analysis of biomacromolecule complexes by interface geometry.

PubMed

Mahdavi, Sedigheh; Salehzadeh-Yazdi, Ali; Mohades, Ali; Masoudi-Nejad, Ali

2013-12-01

The ability to analyze and compare protein-nucleic acid and protein-protein interaction interface has critical importance in understanding the biological function and essential processes occurring in the cells. Since high-resolution three-dimensional (3D) structures of biomacromolecule complexes are available, computational characterizing of the interface geometry become an important research topic in the field of molecular biology. In this study, the interfaces of a set of 180 protein-nucleic acid and protein-protein complexes are computed to understand the principles of their interactions. The weighted Voronoi diagram of the atoms and the Alpha complex has provided an accurate description of the interface atoms. Our method is implemented in the presence and absence of water molecules. A comparison among the three types of interaction interfaces show that RNA-protein complexes have the largest size of an interface. The results show a high correlation coefficient between our method and the PISA server in the presence and absence of water molecules in the Voronoi model and the traditional model based on solvent accessibility and the high validation parameters in comparison to the classical model. Copyright © 2013 Elsevier Ltd. All rights reserved.

A mass graph-based approach for the identification of modified proteoforms using top-down tandem mass spectra.

PubMed

Kou, Qiang; Wu, Si; Tolic, Nikola; Paša-Tolic, Ljiljana; Liu, Yunlong; Liu, Xiaowen

2017-05-01

Although proteomics has rapidly developed in the past decade, researchers are still in the early stage of exploring the world of complex proteoforms, which are protein products with various primary structure alterations resulting from gene mutations, alternative splicing, post-translational modifications, and other biological processes. Proteoform identification is essential to mapping proteoforms to their biological functions as well as discovering novel proteoforms and new protein functions. Top-down mass spectrometry is the method of choice for identifying complex proteoforms because it provides a 'bird's eye view' of intact proteoforms. The combinatorial explosion of various alterations on a protein may result in billions of possible proteoforms, making proteoform identification a challenging computational problem. We propose a new data structure, called the mass graph, for efficient representation of proteoforms and design mass graph alignment algorithms. We developed TopMG, a mass graph-based software tool for proteoform identification by top-down mass spectrometry. Experiments on top-down mass spectrometry datasets showed that TopMG outperformed existing methods in identifying complex proteoforms. http://proteomics.informatics.iupui.edu/software/topmg/. xwliu@iupui.edu. Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Multimeric complexes among ankyrin-repeat and SOCS-box protein 9 (ASB9), ElonginBC, and Cullin 5: insights into the structure and assembly of ECS-type Cullin-RING E3 ubiquitin ligases.

PubMed

Thomas, Jemima C; Matak-Vinkovic, Dijana; Van Molle, Inge; Ciulli, Alessio

2013-08-06

Proteins of the ankyrin-repeat and SOCS-box (ASB) family act as the substrate-recognition subunits of ECS-type (ElonginBC-Cullin-SOCS-box) Cullin RING E3 ubiquitin ligase (CRL) complexes that catalyze the specific polyubiquitination of cellular proteins to target them for degradation by the proteasome. Therefore, ASB multimeric complexes are involved in numerous cell processes and pathways; however, their interactions, assembly, and biological roles remain poorly understood. To enhance our understanding of ASB CRL systems, we investigated the structure, affinity, and assembly of the quaternary multisubunit complex formed by ASB9, Elongin B, Elongin C (EloBC), and Cullin 5. Here, we describe the application of several biophysical techniques including differential scanning fluorimetry, isothermal titration calorimetry (ITC), nanoelectrospray ionization, and ion-mobility mass spectrometry (IM-MS) to provide structural and thermodynamic information for a quaternary ASB CRL complex. We find that ASB9 is unstable alone but forms a stable ternary complex with EloBC that binds with high affinity to the Cullin 5 N-terminal domain (Cul5NTD) but not to Cul2NTD. The structure of the monomeric ASB9-EloBC-Cul5NTD quaternary complex is revealed by molecular modeling and is consistent with IM-MS and temperature-dependent ITC data. This is the first experimental study to validate structural information for the assembly of the quaternary N-terminal region of an ASB CRL complex. The results suggest that ASB E3 ligase complexes function and assemble in an analogous manner to that of other CRL systems and provide a platform for further molecular investigation of this important protein family. The data reported here will also be of use for the future development of chemical probes to examine the biological function and modulation of other ECS-type CRL systems.

Multimeric Complexes among Ankyrin-Repeat and SOCS-box Protein 9 (ASB9), ElonginBC, and Cullin 5: Insights into the Structure and Assembly of ECS-type Cullin-RING E3 Ubiquitin Ligases

PubMed Central

2013-01-01

Proteins of the ankyrin-repeat and SOCS-box (ASB) family act as the substrate-recognition subunits of ECS-type (ElonginBC–Cullin–SOCS-box) Cullin RING E3 ubiquitin ligase (CRL) complexes that catalyze the specific polyubiquitination of cellular proteins to target them for degradation by the proteasome. Therefore, ASB multimeric complexes are involved in numerous cell processes and pathways; however, their interactions, assembly, and biological roles remain poorly understood. To enhance our understanding of ASB CRL systems, we investigated the structure, affinity, and assembly of the quaternary multisubunit complex formed by ASB9, Elongin B, Elongin C (EloBC), and Cullin 5. Here, we describe the application of several biophysical techniques including differential scanning fluorimetry, isothermal titration calorimetry (ITC), nanoelectrospray ionization, and ion-mobility mass spectrometry (IM–MS) to provide structural and thermodynamic information for a quaternary ASB CRL complex. We find that ASB9 is unstable alone but forms a stable ternary complex with EloBC that binds with high affinity to the Cullin 5 N-terminal domain (Cul5NTD) but not to Cul2NTD. The structure of the monomeric ASB9–EloBC–Cul5NTD quaternary complex is revealed by molecular modeling and is consistent with IM–MS and temperature-dependent ITC data. This is the first experimental study to validate structural information for the assembly of the quaternary N-terminal region of an ASB CRL complex. The results suggest that ASB E3 ligase complexes function and assemble in an analogous manner to that of other CRL systems and provide a platform for further molecular investigation of this important protein family. The data reported here will also be of use for the future development of chemical probes to examine the biological function and modulation of other ECS-type CRL systems. PMID:23837592

The hydroxyl-functionalized magnetic particles for purification of glycan-binding proteins.

PubMed

Sun, Xiuxuan; Yang, Ganglong; Sun, Shisheng; Quan, Rui; Dai, Weiwei; Li, Bin; Chen, Chao; Li, Zheng

2009-12-01

Glycan-protein interactions play important biological roles in biological processes. Although there are some methods such as glycan arrays that may elucidate recognition events between carbohydrates and protein as well as screen the important glycan-binding proteins, there is a lack of simple effectively separate method to purify them from complex samples. In proteomics studies, fractionation of samples can help to reduce their complexity and to enrich specific classes of proteins for subsequent downstream analyses. Herein, a rapid simple method for purification of glycan-binding proteins from proteomic samples was developed using hydroxyl-coated magnetic particles coupled with underivatized carbohydrate. Firstly, the epoxy-coated magnetic particles were further hydroxyl functionalized with 4-hydroxybenzhydrazide, then the carbohydrates were efficiently immobilized on hydroxyl functionalized surface of magnetic particles by formation of glycosidic bond with the hemiacetal group at the reducing end of the suitable carbohydrates via condensation. All conditions of this method were optimized. The magnetic particle-carbohydrate conjugates were used to purify the glycan-binding proteins from human serum. The fractionated glycan-binding protein population was displayed by SDS-PAGE. The result showed that the amount of 1 mg magnetic particles coupled with mannose in acetate buffer (pH 5.4) was 10 micromol. The fractionated glycan-binding protein population in human serum could be eluted from the magnetic particle-mannose conjugates by 0.1% SDS. The methodology could work together with the glycan microarrays for screening and purification of the important GBPs from complex protein samples.

The Role of Histone Deacetylases in Neurodegenerative Diseases and Small-Molecule Inhibitors as a Potential Therapeutic Approach

NASA Astrophysics Data System (ADS)

Bürli, Roland W.; Thomas, Elizabeth; Beaumont, Vahri

Neurodegenerative disorders are devastating for patients and their social environment. Their etiology is poorly understood and complex. As a result, there is clearly an urgent need for therapeutic agents that slow down disease progress and alleviate symptoms. In this respect, interference with expression and function of multiple gene products at the epigenetic level has offered much promise, and histone deacetylases play a crucial role in these processes. This review presents an overview of the biological pathways in which these enzymes are involved and illustrates the complex network of proteins that governs their activity. An overview of small molecules that interfere with histone deacetylase function is provided.

What is microbial community ecology?

PubMed

Konopka, Allan

2009-11-01

The activities of complex communities of microbes affect biogeochemical transformations in natural, managed and engineered ecosystems. Meaningfully defining what constitutes a community of interacting microbial populations is not trivial, but is important for rigorous progress in the field. Important elements of research in microbial community ecology include the analysis of functional pathways for nutrient resource and energy flows, mechanistic understanding of interactions between microbial populations and their environment, and the emergent properties of the complex community. Some emergent properties mirror those analyzed by community ecologists who study plants and animals: biological diversity, functional redundancy and system stability. However, because microbes possess mechanisms for the horizontal transfer of genetic information, the metagenome may also be considered as a community property.

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

Konopka, Allan

The activities of complex communities of microbes affect biogeochemical transformations in natural, managed and engineered ecosystems. Meaningfully defining what constitutes a community of interacting microbial populations is not trivial, but is important for rigorous progress in the field. Important elements of research in microbial community ecology include the analysis of functional pathways for nutrient resource and energy flows, mechanistic understanding of interactions between microbial populations and their environment, and the emergent properties of the complex community. Some emergent properties mirror those analyzed by community ecologists who study plants and animals: biological diversity, functional redundancy and system stability. However, because microbesmore » possess mechanisms for the horizontal transfer of genetic information, the metagenome may also be considered a community property.« less

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

Simulating biological processes: stochastic physics from whole cells to colonies.

PubMed

Earnest, Tyler M; Cole, John A; Luthey-Schulten, Zaida

2018-05-01

The last few decades have revealed the living cell to be a crowded spatially heterogeneous space teeming with biomolecules whose concentrations and activities are governed by intrinsically random forces. It is from this randomness, however, that a vast array of precisely timed and intricately coordinated biological functions emerge that give rise to the complex forms and behaviors we see in the biosphere around us. This seemingly paradoxical nature of life has drawn the interest of an increasing number of physicists, and recent years have seen stochastic modeling grow into a major subdiscipline within biological physics. Here we review some of the major advances that have shaped our understanding of stochasticity in biology. We begin with some historical context, outlining a string of important experimental results that motivated the development of stochastic modeling. We then embark upon a fairly rigorous treatment of the simulation methods that are currently available for the treatment of stochastic biological models, with an eye toward comparing and contrasting their realms of applicability, and the care that must be taken when parameterizing them. Following that, we describe how stochasticity impacts several key biological functions, including transcription, translation, ribosome biogenesis, chromosome replication, and metabolism, before considering how the functions may be coupled into a comprehensive model of a 'minimal cell'. Finally, we close with our expectation for the future of the field, focusing on how mesoscopic stochastic methods may be augmented with atomic-scale molecular modeling approaches in order to understand life across a range of length and time scales.

Simulating biological processes: stochastic physics from whole cells to colonies

NASA Astrophysics Data System (ADS)

Earnest, Tyler M.; Cole, John A.; Luthey-Schulten, Zaida

2018-05-01

The last few decades have revealed the living cell to be a crowded spatially heterogeneous space teeming with biomolecules whose concentrations and activities are governed by intrinsically random forces. It is from this randomness, however, that a vast array of precisely timed and intricately coordinated biological functions emerge that give rise to the complex forms and behaviors we see in the biosphere around us. This seemingly paradoxical nature of life has drawn the interest of an increasing number of physicists, and recent years have seen stochastic modeling grow into a major subdiscipline within biological physics. Here we review some of the major advances that have shaped our understanding of stochasticity in biology. We begin with some historical context, outlining a string of important experimental results that motivated the development of stochastic modeling. We then embark upon a fairly rigorous treatment of the simulation methods that are currently available for the treatment of stochastic biological models, with an eye toward comparing and contrasting their realms of applicability, and the care that must be taken when parameterizing them. Following that, we describe how stochasticity impacts several key biological functions, including transcription, translation, ribosome biogenesis, chromosome replication, and metabolism, before considering how the functions may be coupled into a comprehensive model of a ‘minimal cell’. Finally, we close with our expectation for the future of the field, focusing on how mesoscopic stochastic methods may be augmented with atomic-scale molecular modeling approaches in order to understand life across a range of length and time scales.

In vitro studies of actin filament and network dynamics

PubMed Central

Mullins, R Dyche; Hansen, Scott D

2013-01-01

Now that many genomes have been sequenced, a central concern of cell biology is to understand how the proteins they encode work together to create living matter. In vitro studies form an essential part of this program because understanding cellular functions of biological molecules often requires isolating them and reconstituting their activities. In particular, many elements of the actin cytoskeleton were first discovered by biochemical methods and their cellular functions deduced from in vitro experiments. We highlight recent advances that have come from in vitro studies, beginning with studies of actin filaments, and ending with multi-component reconstitutions of complex actin-based processes, including force-generation and cell spreading. We describe both scientific results and the technical innovations that made them possible. PMID:23267766

Analyzing and Understanding Lipids of Yeast: A Challenging Endeavor.

PubMed

Kohlwein, Sepp D

2017-05-01

Lipids are essential biomolecules with diverse biological functions, ranging from building blocks for all biological membranes to energy substrates, signaling molecules, and protein modifiers. Despite advances in lipid analytics by mass spectrometry, the extraction and quantitative analysis of the diverse classes of lipids are still an experimental challenge. Yeast is a model organism that provides several advantages for studying lipid metabolism, because most biosynthetic pathways are well described and a great deal of information is available on the regulatory mechanisms that control lipid homeostasis. In addition, the composition of yeast lipids is much less complex than that of mammalian lipids, making yeast an excellent reference system for studying lipid-associated cell functions. © 2017 Cold Spring Harbor Laboratory Press.

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

Management of Hyposalivation and Xerostomia: Criteria for Treatment Strategies.

PubMed

Epstein, Joel B; Beier Jensen, Siri

2015-09-01

Saliva management in patients with hyposalivation is potentially complex. Future development of oral care products and treatment strategies requires attention to the biology of saliva and the best means of providing a continuum of relief for people with xerostomia--the sensation of dry mouth--and hyposalivation--documented reduction in saliva flow. Improvement in patient care requires that clinicians be aware of approaches to management, desirable qualities of methods and products, and that they seek the development of products that support the functions of saliva and promote comfort and health. In this brief review of the epidemiology of hyposalivation, the biology and functions of saliva are presented in order to guide clinical decision-making to address the needs of patients with dry mouth.

Virtual surgical planning for treatment of severe mandibular retrognathia with collapsed occlusion using contemporary surgical and prosthodontic protocols.

PubMed

Dhima, Matilda; Salinas, Thomas J; Rieck, Kevin L

2013-11-01

To meet functional and esthetic needs in an older adult for treatment of complex skeletal and dentoalveolar deformities using contemporary surgical and prosthodontic protocols. An older adult with dentoalveolar complex and skeletal deformity (mandibular retrognathia) was treated by a combination of virtual planning and current surgical and prosthodontic protocols. Treatment planning steps and sequencing are presented. Skeletal, soft tissue, and dental harmonies were attained without biological or mechanical complications. Definitive oral rehabilitation was completed with a maxillary complete denture and a mandibular metal ceramic fixed implant-retained prosthesis. A surgical and prosthodontic team approach in combination with technologic advances can predictably optimize esthetic and functional outcomes for patients with complex skeletal and dentoalveolar deformities. Copyright © 2013 American Association of Oral and Maxillofacial Surgeons. Published by Elsevier Inc. All rights reserved.

The emerging complexity of ubiquitin architecture.

PubMed

Ohtake, Fumiaki; Tsuchiya, Hikaru

2017-02-01

Ubiquitylation is an essential post-translational modification (PTM) of proteins with diverse cellular functions. Polyubiquitin chains with different topologies have different cellular roles, and are referred to as a 'ubiquitin code'. Recent studies have begun to reveal that more complex ubiquitin architectures function as important signals in several biological pathways. These include PTMs of ubiquitin itself, such as acetylated ubiquitin and phospho-ubiquitin. Moreover, important roles for heterogeneous polyubiquitin chains, such as mixed or branched chains, have been reported, which significantly increase the diversity of the ubiquitin code. In this review, we describe mass spectrometry-based methods to characterize the ubiquitin signal. We also describe recent advances in our understanding of complex ubiquitin architectures, including our own findings concerning ubiquitin acetylation and branching within polyubiquitin chains. © The Authors 2016. Published by Oxford University Press on behalf of the Japanese Biochemical Society. All rights reserved.

A promising future for integrative biodiversity research: an increased role of scale-dependency and functional biology.

PubMed

Price, S A; Schmitz, L

2016-04-05

Studies into the complex interaction between an organism and changes to its biotic and abiotic environment are fundamental to understanding what regulates biodiversity. These investigations occur at many phylogenetic, temporal and spatial scales and within a variety of biological and geological disciplines but often in relative isolation. This issue focuses on what can be achieved when ecological mechanisms are integrated into analyses of deep-time biodiversity patterns through the union of fossil and extant data and methods. We expand upon this perspective to argue that, given its direct relevance to the current biodiversity crisis, greater integration is needed across biodiversity research. We focus on the need to understand scaling effects, how lower-level ecological and evolutionary processes scale up and vice versa, and the importance of incorporating functional biology. Placing function at the core of biodiversity research is fundamental, as it establishes how an organism interacts with its abiotic and biotic environment and it is functional diversity that ultimately determines important ecosystem processes. To achieve full integration, concerted and ongoing efforts are needed to build a united and interactive community of biodiversity researchers, with education and interdisciplinary training at its heart. © 2016 The Author(s).

A promising future for integrative biodiversity research: an increased role of scale-dependency and functional biology

PubMed Central

Schmitz, L.

2016-01-01

Studies into the complex interaction between an organism and changes to its biotic and abiotic environment are fundamental to understanding what regulates biodiversity. These investigations occur at many phylogenetic, temporal and spatial scales and within a variety of biological and geological disciplines but often in relative isolation. This issue focuses on what can be achieved when ecological mechanisms are integrated into analyses of deep-time biodiversity patterns through the union of fossil and extant data and methods. We expand upon this perspective to argue that, given its direct relevance to the current biodiversity crisis, greater integration is needed across biodiversity research. We focus on the need to understand scaling effects, how lower-level ecological and evolutionary processes scale up and vice versa, and the importance of incorporating functional biology. Placing function at the core of biodiversity research is fundamental, as it establishes how an organism interacts with its abiotic and biotic environment and it is functional diversity that ultimately determines important ecosystem processes. To achieve full integration, concerted and ongoing efforts are needed to build a united and interactive community of biodiversity researchers, with education and interdisciplinary training at its heart. PMID:26977068

Impact of silica nanoparticle surface chemistry on protein corona formation and consequential interactions with biological cells.

PubMed

Kurtz-Chalot, Andréa; Villiers, Christian; Pourchez, Jérémie; Boudard, Delphine; Martini, Matteo; Marche, Patrice N; Cottier, Michèle; Forest, Valérie

2017-06-01

Nanoparticles (NP) physico-chemical features greatly influence NP/cell interactions. NP surface functionalization is often used to improve NP biocompatibility or to enhance cellular uptake. But in biological media, the formation of a protein corona adds a level of complexity. The aim of this study was to investigate in vitro the influence of NP surface functionalization on their cellular uptake and the biological response induced. 50nm fluorescent silica NP were functionalized either with amine or carboxylic groups, in presence or in absence of polyethylene glycol (PEG). NP were incubated with macrophages, cellular uptake and cellular response were assessed in terms of cytotoxicity, pro-inflammatory response and oxidative stress. The NP protein corona was also characterized by protein mass spectroscopy. Results showed that NP uptake was enhanced in absence of PEG, while NP adsorption at the cell membrane was fostered by an initial positively charged NP surface. NP toxicity was not correlated with NP uptake. NP surface functionalization also influenced the formation of the protein corona as the profile of protein binding differed among the NP types. Copyright © 2017 Elsevier B.V. All rights reserved.

iAB-RBC-283: A proteomically derived knowledge-base of erythrocyte metabolism that can be used to simulate its physiological and patho-physiological states.

PubMed

Bordbar, Aarash; Jamshidi, Neema; Palsson, Bernhard O

2011-07-12

The development of high-throughput technologies capable of whole cell measurements of genes, proteins, and metabolites has led to the emergence of systems biology. Integrated analysis of the resulting omic data sets has proved to be hard to achieve. Metabolic network reconstructions enable complex relationships amongst molecular components to be represented formally in a biologically relevant manner while respecting physical constraints. In silico models derived from such reconstructions can then be queried or interrogated through mathematical simulations. Proteomic profiling studies of the mature human erythrocyte have shown more proteins present related to metabolic function than previously thought; however the significance and the causal consequences of these findings have not been explored. Erythrocyte proteomic data was used to reconstruct the most expansive description of erythrocyte metabolism to date, following extensive manual curation, assessment of the literature, and functional testing. The reconstruction contains 281 enzymes representing functions from glycolysis to cofactor and amino acid metabolism. Such a comprehensive view of erythrocyte metabolism implicates the erythrocyte as a potential biomarker for different diseases as well as a 'cell-based' drug-screening tool. The analysis shows that 94 erythrocyte enzymes are implicated in morbid single nucleotide polymorphisms, representing 142 pathologies. In addition, over 230 FDA-approved and experimental pharmaceuticals have enzymatic targets in the erythrocyte. The advancement of proteomic technologies and increased generation of high-throughput proteomic data have created the need for a means to analyze these data in a coherent manner. Network reconstructions provide a systematic means to integrate and analyze proteomic data in a biologically meaning manner. Analysis of the red cell proteome has revealed an unexpected level of complexity in the functional capabilities of human erythrocyte metabolism.

Modularity and evolutionary constraints in a baculovirus gene regulatory network

PubMed Central

2013-01-01

Background The structure of regulatory networks remains an open question in our understanding of complex biological systems. Interactions during complete viral life cycles present unique opportunities to understand how host-parasite network take shape and behave. The Anticarsia gemmatalis multiple nucleopolyhedrovirus (AgMNPV) is a large double-stranded DNA virus, whose genome may encode for 152 open reading frames (ORFs). Here we present the analysis of the ordered cascade of the AgMNPV gene expression. Results We observed an earlier onset of the expression than previously reported for other baculoviruses, especially for genes involved in DNA replication. Most ORFs were expressed at higher levels in a more permissive host cell line. Genes with more than one copy in the genome had distinct expression profiles, which could indicate the acquisition of new functionalities. The transcription gene regulatory network (GRN) for 149 ORFs had a modular topology comprising five communities of highly interconnected nodes that separated key genes that are functionally related on different communities, possibly maximizing redundancy and GRN robustness by compartmentalization of important functions. Core conserved functions showed expression synchronicity, distinct GRN features and significantly less genetic diversity, consistent with evolutionary constraints imposed in key elements of biological systems. This reduced genetic diversity also had a positive correlation with the importance of the gene in our estimated GRN, supporting a relationship between phylogenetic data of baculovirus genes and network features inferred from expression data. We also observed that gene arrangement in overlapping transcripts was conserved among related baculoviruses, suggesting a principle of genome organization. Conclusions Albeit with a reduced number of nodes (149), the AgMNPV GRN had a topology and key characteristics similar to those observed in complex cellular organisms, which indicates that modularity may be a general feature of biological gene regulatory networks. PMID:24006890

Heparin functionalization increases retention of TGF-β2 and GDF5 on biphasic silk fibroin scaffolds for tendon/ligament-to-bone tissue engineering.

PubMed

Font Tellado, Sònia; Chiera, Silvia; Bonani, Walter; Poh, Patrina S P; Migliaresi, Claudio; Motta, Antonella; Balmayor, Elizabeth R; van Griensven, Martijn

2018-05-01

The tendon/ligament-to-bone transition (enthesis) is a highly specialized interphase tissue with structural gradients of extracellular matrix composition, collagen molecule alignment and mineralization. These structural features are essential for enthesis function, but are often not regenerated after injury. Tissue engineering is a promising strategy for enthesis repair. Engineering of complex tissue interphases such as the enthesis is likely to require a combination of biophysical, biological and chemical cues to achieve functional tissue regeneration. In this study, we cultured human primary adipose-derived mesenchymal stem cells (AdMCs) on biphasic silk fibroin scaffolds with integrated anisotropic (tendon/ligament-like) and isotropic (bone/cartilage like) pore alignment. We functionalized those scaffolds with heparin and explored their ability to deliver transforming growth factor β2 (TGF-β2) and growth/differentiation factor 5 (GDF5). Heparin functionalization increased the amount of TGF-β2 and GDF5 remaining attached to the scaffold matrix and resulted in biological effects at low growth factor doses. We analyzed the combined impact of pore alignment and growth factors on AdMSCs. TGF-β2 and pore anisotropy synergistically increased the expression of tendon/ligament markers and collagen I protein content. In addition, the combined delivery of TGF-β2 and GDF5 enhanced the expression of cartilage markers and collagen II protein content on substrates with isotropic porosity, whereas enthesis markers were enhanced in areas of mixed anisotropic/isotropic porosity. Altogether, the data obtained in this study improves current understanding on the combined effects of biological and structural cues on stem cell fate and presents a promising strategy for tendon/ligament-to-bone regeneration. Regeneration of the tendon/ligament-to-bone interphase (enthesis) is of significance in the repair of ruptured tendons/ligaments to bone to improve implant integration and clinical outcome. This study proposes a novel approach for enthesis regeneration based on a biomimetic and integrated tendon/ligament-to-bone construct, stem cells and heparin-based delivery of growth factors. We show that heparin can keep growth factors local and biologically active at low doses, which is critical to avoid supraphysiological doses and associated side effects. In addition, we identify synergistic effects of biological (growth factors) and structural (pore alignment) cues on stem cells. These results improve current understanding on the combined impact of biological and structural cues on the multi-lineage differentiation capacity of stem cells for regenerating complex tissue interphases. Copyright © 2018 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

Molecular locks and keys: the role of small molecules in phytohormone research

PubMed Central

Fonseca, Sandra; Rosado, Abel; Vaughan-Hirsch, John; Bishopp, Anthony; Chini, Andrea

2014-01-01

Plant adaptation, growth and development rely on the integration of many environmental and endogenous signals that collectively determine the overall plant phenotypic plasticity. Plant signaling molecules, also known as phytohormones, are fundamental to this process. These molecules act at low concentrations and regulate multiple aspects of plant fitness and development via complex signaling networks. By its nature, phytohormone research lies at the interface between chemistry and biology. Classically, the scientific community has always used synthetic phytohormones and analogs to study hormone functions and responses. However, recent advances in synthetic and combinational chemistry, have allowed a new field, plant chemical biology, to emerge and this has provided a powerful tool with which to study phytohormone function. Plant chemical biology is helping to address some of the most enduring questions in phytohormone research such as: Are there still undiscovered plant hormones? How can we identify novel signaling molecules? How can plants activate specific hormone responses in a tissue-specific manner? How can we modulate hormone responses in one developmental context without inducing detrimental effects on other processes? The chemical genomics approaches rely on the identification of small molecules modulating different biological processes and have recently identified active forms of plant hormones and molecules regulating many aspects of hormone synthesis, transport and response. We envision that the field of chemical genomics will continue to provide novel molecules able to elucidate specific aspects of hormone-mediated mechanisms. In addition, compounds blocking specific responses could uncover how complex biological responses are regulated. As we gain information about such compounds we can design small alterations to the chemical structure to further alter specificity, enhance affinity or modulate the activity of these compounds. PMID:25566283