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.

An integrative approach to inferring biologically meaningful gene modules.

PubMed

Cho, Ji-Hoon; Wang, Kai; Galas, David J

2011-07-26

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. 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. 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.

Applications of systems approaches in the study of rheumatic diseases.

PubMed

Kim, Ki-Jo; Lee, Saseong; Kim, Wan-Uk

2015-03-01

The complex interaction of molecules within a biological system constitutes a functional module. These modules are then acted upon by both internal and external factors, such as genetic and environmental stresses, which under certain conditions can manifest as complex disease phenotypes. Recent advances in high-throughput biological analyses, in combination with improved computational methods for data enrichment, functional annotation, and network visualization, have enabled a much deeper understanding of the mechanisms underlying important biological processes by identifying functional modules that are temporally and spatially perturbed in the context of disease development. Systems biology approaches such as these have produced compelling observations that would be impossible to replicate using classical methodologies, with greater insights expected as both the technology and methods improve in the coming years. Here, we examine the use of systems biology and network analysis in the study of a wide range of rheumatic diseases to better understand the underlying molecular and clinical features.

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

Modelling of pathologies of the nervous system by the example of computational and electronic models of elementary nervous systems

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

Shumilov, V. N., E-mail: vnshumilov@rambler.ru; Syryamkin, V. I., E-mail: maximus70sir@gmail.com; Syryamkin, M. V., E-mail: maximus70sir@gmail.com

The paper puts forward principles of action of devices operating similarly to the nervous system and the brain of biological systems. We propose an alternative method of studying diseases of the nervous system, which may significantly influence prevention, medical treatment, or at least retardation of development of these diseases. This alternative is to use computational and electronic models of the nervous system. Within this approach, we represent the brain in the form of a huge electrical circuit composed of active units, namely, neuron-like units and connections between them. As a result, we created computational and electronic models of elementary nervousmore » systems, which are based on the principles of functioning of biological nervous systems that we have put forward. Our models demonstrate reactions to external stimuli and their change similarly to the behavior of simplest biological organisms. The models possess the ability of self-training and retraining in real time without human intervention and switching operation/training modes. In our models, training and memorization take place constantly under the influence of stimuli on the organism. Training is without any interruption and switching operation modes. Training and formation of new reflexes occur by means of formation of new connections between excited neurons, between which formation of connections is physically possible. Connections are formed without external influence. They are formed under the influence of local causes. Connections are formed between outputs and inputs of two neurons, when the difference between output and input potentials of excited neurons exceeds a value sufficient to form a new connection. On these grounds, we suggest that the proposed principles truly reflect mechanisms of functioning of biological nervous systems and the brain. In order to confirm the correspondence of the proposed principles to biological nature, we carry out experiments for the study of processes of formation of connections between neurons in simplest biological objects. Based on the correspondence of function of the created models to function of biological nervous systems we suggest the use of computational and electronic models of the brain for the study of its function under normal and pathological conditions, because operating principles of the models are built on principles imitating the function of biological nervous systems and the brain.« less

Modelling of pathologies of the nervous system by the example of computational and electronic models of elementary nervous systems

NASA Astrophysics Data System (ADS)

Shumilov, V. N.; Syryamkin, V. I.; Syryamkin, M. V.

2015-11-01

The paper puts forward principles of action of devices operating similarly to the nervous system and the brain of biological systems. We propose an alternative method of studying diseases of the nervous system, which may significantly influence prevention, medical treatment, or at least retardation of development of these diseases. This alternative is to use computational and electronic models of the nervous system. Within this approach, we represent the brain in the form of a huge electrical circuit composed of active units, namely, neuron-like units and connections between them. As a result, we created computational and electronic models of elementary nervous systems, which are based on the principles of functioning of biological nervous systems that we have put forward. Our models demonstrate reactions to external stimuli and their change similarly to the behavior of simplest biological organisms. The models possess the ability of self-training and retraining in real time without human intervention and switching operation/training modes. In our models, training and memorization take place constantly under the influence of stimuli on the organism. Training is without any interruption and switching operation modes. Training and formation of new reflexes occur by means of formation of new connections between excited neurons, between which formation of connections is physically possible. Connections are formed without external influence. They are formed under the influence of local causes. Connections are formed between outputs and inputs of two neurons, when the difference between output and input potentials of excited neurons exceeds a value sufficient to form a new connection. On these grounds, we suggest that the proposed principles truly reflect mechanisms of functioning of biological nervous systems and the brain. In order to confirm the correspondence of the proposed principles to biological nature, we carry out experiments for the study of processes of formation of connections between neurons in simplest biological objects. Based on the correspondence of function of the created models to function of biological nervous systems we suggest the use of computational and electronic models of the brain for the study of its function under normal and pathological conditions, because operating principles of the models are built on principles imitating the function of biological nervous systems and the brain.

Rewiring cells: synthetic biology as a tool to interrogate the organizational principles of living systems.

PubMed

Bashor, Caleb J; Horwitz, Andrew A; Peisajovich, Sergio G; Lim, Wendell A

2010-01-01

The living cell is an incredibly complex entity, and the goal of predictively and quantitatively understanding its function is one of the next great challenges in biology. Much of what we know about the cell concerns its constituent parts, but to a great extent we have yet to decode how these parts are organized to yield complex physiological function. Classically, we have learned about the organization of cellular networks by disrupting them through genetic or chemical means. The emerging discipline of synthetic biology offers an additional, powerful approach to study systems. By rearranging the parts that comprise existing networks, we can gain valuable insight into the hierarchical logic of the networks and identify the modular building blocks that evolution uses to generate innovative function. In addition, by building minimal toy networks, one can systematically explore the relationship between network structure and function. Here, we outline recent work that uses synthetic biology approaches to investigate the organization and function of cellular networks, and describe a vision for a synthetic biology toolkit that could be used to interrogate the design principles of diverse systems.

Relations among Functional Systems in Behavior Analysis

ERIC Educational Resources Information Center

Thompson, Travis

2007-01-01

This paper proposes that an organism's integrated repertoire of operant behavior has the status of a biological system, similar to other biological systems, like the nervous, cardiovascular, or immune systems. Evidence from a number of sources indicates that the distinctions between biological and behavioral events is often misleading, engendering…

Synthetic biology: insights into biological computation.

PubMed

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

2016-04-18

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

A functional approach to emotion in autonomous systems.

PubMed

Sanz, Ricardo; Hernández, Carlos; Gómez, Jaime; Hernando, Adolfo

2010-01-01

The construction of fully effective systems seems to pass through the proper exploitation of goal-centric self-evaluative capabilities that let the system teleologically self-manage. Emotions seem to provide this kind of functionality to biological systems and hence the interest in emotion for function sustainment in artificial systems performing in changing and uncertain environments; far beyond the media hullabaloo of displaying human-like emotion-laden faces in robots. This chapter provides a brief analysis of the scientific theories of emotion and presents an engineering approach for developing technology for robust autonomy by implementing functionality inspired in that of biological emotions.

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.

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

[Biotechnological functional systems].

PubMed

Bokser, O Ia

1999-01-01

Based on the theory of functional systems and a concept of the quantum system of behavior, studies of the quantumsystems were conducted. Their structure, the interaction of biological and technical sections were analyzed. Mathematical, biophysical, and experimental models were designed. The paper shows that biotechnical quantumsystems are involved in the formation of biological feedback. A system with imperative feedback from the programmed and introduced current results of efforts has been developed and put into practice for the self-regulation of muscle tension. Training by using this biological feedback system causes a stable increase in the perception rate of proprioceptive stimulus in examinees (operates, sportsmen, neurological patients).

Applications of systems biology towards microbial fuel production.

PubMed

Gowen, Christopher M; Fong, Stephen S

2011-10-01

Harnessing the immense natural diversity of biological functions for economical production of fuel has enormous potential benefits. Inevitably, however, the native capabilities for any given organism must be modified to increase the productivity or efficiency of a biofuel bioprocess. From a broad perspective, the challenge is to sufficiently understand the details of cellular functionality to be able to prospectively predict and modify the cellular function of a microorganism. Recent advances in experimental and computational systems biology approaches can be used to better understand cellular level function and guide future experiments. With pressure to quickly develop viable, renewable biofuel processes a balance must be maintained between obtaining depth of biological knowledge and applying that knowledge. Copyright © 2011 Elsevier Ltd. All rights reserved.

Neural system modeling and simulation using Hybrid Functional Petri Net.

PubMed

Tang, Yin; Wang, Fei

2012-02-01

The Petri net formalism has been proved to be powerful in biological modeling. It not only boasts of a most intuitive graphical presentation but also combines the methods of classical systems biology with the discrete modeling technique. Hybrid Functional Petri Net (HFPN) was proposed specially for biological system modeling. An array of well-constructed biological models using HFPN yielded very interesting results. In this paper, we propose a method to represent neural system behavior, where biochemistry and electrical chemistry are both included using the Petri net formalism. We built a model for the adrenergic system using HFPN and employed quantitative analysis. Our simulation results match the biological data well, showing that the model is very effective. Predictions made on our model further manifest the modeling power of HFPN and improve the understanding of the adrenergic system. The file of our model and more results with their analysis are available in our supplementary material.

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.

The role of low-grade inflammation and metabolic flexibility in aging and nutritional modulation thereof: a systems biology approach.

PubMed

Calçada, Dulce; Vianello, Dario; Giampieri, Enrico; Sala, Claudia; Castellani, Gastone; de Graaf, Albert; Kremer, Bas; van Ommen, Ben; Feskens, Edith; Santoro, Aurelia; Franceschi, Claudio; Bouwman, Jildau

2014-01-01

Aging is a biological process characterized by the progressive functional decline of many interrelated physiological systems. In particular, aging is associated with the development of a systemic state of low-grade chronic inflammation (inflammaging), and with progressive deterioration of metabolic function. Systems biology has helped in identifying the mediators and pathways involved in these phenomena, mainly through the application of high-throughput screening methods, valued for their molecular comprehensiveness. Nevertheless, inflammation and metabolic regulation are dynamical processes whose behavior must be understood at multiple levels of biological organization (molecular, cellular, organ, and system levels) and on multiple time scales. Mathematical modeling of such behavior, with incorporation of mechanistic knowledge on interactions between inflammatory and metabolic mediators, may help in devising nutritional interventions capable of preventing, or ameliorating, the age-associated functional decline of the corresponding systems. Copyright © 2014 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

A Converter from the Systems Biology Markup Language to the Synthetic Biology Open Language.

PubMed

Nguyen, Tramy; Roehner, Nicholas; Zundel, Zach; Myers, Chris J

2016-06-17

Standards are important to synthetic biology because they enable exchange and reproducibility of genetic designs. This paper describes a procedure for converting between two standards: the Systems Biology Markup Language (SBML) and the Synthetic Biology Open Language (SBOL). SBML is a standard for behavioral models of biological systems at the molecular level. SBOL describes structural and basic qualitative behavioral aspects of a biological design. Converting SBML to SBOL enables a consistent connection between behavioral and structural information for a biological design. The conversion process described in this paper leverages Systems Biology Ontology (SBO) annotations to enable inference of a designs qualitative function.

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.

Learning Systems Biology: Conceptual Considerations toward a Web-Based Learning Platform

ERIC Educational Resources Information Center

Emmert-Streib, Frank; Dehmer, Matthias; Lyardet, Fernando

2013-01-01

Within recent years, there is an increasing need to train students, from biology and beyond, in quantitative methods that are relevant to cope with data-driven biology. Systems Biology is such a field that places a particular focus on the functional aspect of biology and molecular interacting processes. This paper deals with the conceptual design…

Systems Biology Graphical Notation: Activity Flow language Level 1 Version 1.2.

PubMed

Mi, Huaiyu; Schreiber, Falk; Moodie, Stuart; Czauderna, Tobias; Demir, Emek; Haw, Robin; Luna, Augustin; Le Novère, Nicolas; Sorokin, Anatoly; Villéger, Alice

2015-09-04

The Systems Biological Graphical Notation (SBGN) is an international community effort for standardized graphical representations of biological pathways and networks. The goal of SBGN is to provide unambiguous pathway and network maps for readers with different scientific backgrounds as well as to support efficient and accurate exchange of biological knowledge between different research communities, industry, and other players in systems biology. Three SBGN languages, Process Description (PD), Entity Relationship (ER) and Activity Flow (AF), allow for the representation of different aspects of biological and biochemical systems at different levels of detail. The SBGN Activity Flow language represents the influences of activities among various entities within a network. Unlike SBGN PD and ER that focus on the entities and their relationships with others, SBGN AF puts the emphasis on the functions (or activities) performed by the entities, and their effects to the functions of the same or other entities. The nodes (elements) describe the biological activities of the entities, such as protein kinase activity, binding activity or receptor activity, which can be easily mapped to Gene Ontology molecular function terms. The edges (connections) provide descriptions of relationships (or influences) between the activities, e.g., positive influence and negative influence. Among all three languages of SBGN, AF is the closest to signaling pathways in biological literature and textbooks, but its well-defined semantics offer a superior precision in expressing biological knowledge.

Analysis of undergraduate students' conceptual models of a complex biological system across a diverse body of learners

NASA Astrophysics Data System (ADS)

Dirnbeck, Matthew R.

Biological systems pose a challenge both for learners and teachers because they are complex systems mediated by feedback loops; networks of cause-effect relationships; and non-linear, hierarchical, and emergent properties. Teachers and scientists routinely use models to communicate ideas about complex systems. Model-based pedagogies engage students in model construction as a means of practicing higher-order reasoning skills. One such modeling paradigm describes systems in terms of their structures, behaviors, and functions (SBF). The SBF framework is a simple modeling language that has been used to teach about complex biological systems. Here, we used student-generated SBF models to assess students' causal reasoning in the context of a novel biological problem on an exam. We compared students' performance on the modeling problem, their performance on a set of knowledge/comprehension questions, and their performance on a set of scientific reasoning questions. We found that students who performed well on knowledge and understanding questions also constructed more networked, higher quality models. Previous studies have shown that learners' mental maps increase in complexity with increased expertise. We wanted to investigate if biology students with varying levels of training in biology showed a similar pattern when constructing system models. In a pilot study, we administered the same modeling problem to two additional groups of students: 1) an animal physiology course for students pursuing a major in biology (n=37) and 2) an exercise physiology course for non-majors (n=27). We found that there was no significant difference in model organization across the three student populations, but there was a significant difference in the ability to represent function between the three populations. Between the three groups the non-majors had the lowest function scores, the introductory majors had the middle function scores, and the upper division majors had the highest function scores.

Biological systems for human life support: Review of the research in the USSR

NASA Technical Reports Server (NTRS)

Shepelev, Y. Y.

1979-01-01

Various models of biological human life support systems are surveyed. Biological structures, dimensions, and functional parameters of man-chlorella-microorganism models are described. Significant observations and the results obtained from these models are reported.

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

Hierarchical functional organization of formal biological systems: a dynamical approach. II. The concept of non-symmetry leads to a criterion of evolution deduced from an optimum principle of the (O-FBS) sub-system.

PubMed

Chauvet, G A

1993-03-29

In paper I a theory of functional organization in terms of functional interactions was proposed for a formal biological system (FBS). A functional interaction was defined as the product emitted by a structural unit, i.e. an assembly of molecules, cells, tissues or organs, which acts on another. We have shown that a self-association hypothesis could be an explanation for the source of these functional interactions because it is consistent with increased stability of the system after association. The construction of the set of interactions provides the topology of the biological system, called (O-FBS), in contrast to the (D-FBS) which describes the dynamics of the processes associated with the functional interactions. In this paper, an optimum principle is established, due to the non-symmetry of functional interactions, which could explain the stability of an FBS, and a criterion of evolution for the hierarchical topological organization of a FBS during development is deduced from that principle. The combinatorics of the (O-FBS) leads to the topological stability of the related graph. It is shown that this problem can be expressed as the re-distribution of sources and sinks, when one of them is suppressed, given the constraint of the invariance of the physiological function. Such an optimum principle could be called a 'principle of increase in functional order by hierarchy'. The first step is the formulation of a 'potential' for the functional organization, which describes the ability of the system to combine functional interactions, such that the principle of vital coherence (paper I) is satisfied. This function measures the number of potential functional interactions. The second step is to discover the maximum of this function. Biological systems in such a state of maximum organization are shown to satisfy particular dynamics, which can be experimentally verified: either the number of sinks decreases, or this number increases, in a monotonic way. The class of systems considered here is assumed to satisfy such an extremum hypothesis. The third step is a study of the variation of the degree of organization (paper I), i.e. the number of structural units when the biological system is growing. We establish an optimum principle for a new function called 'orgatropy'. By adding a criterion of specialization to the system we show the emergence of a level of organization with a re-organization of the system.(ABSTRACT TRUNCATED AT 400 WORDS)

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.

Applications of cell-free protein synthesis in synthetic biology: Interfacing bio-machinery with synthetic environments.

PubMed

Lee, Kyung-Ho; Kim, Dong-Myung

2013-11-01

Synthetic biology is built on the synthesis, engineering, and assembly of biological parts. Proteins are the first components considered for the construction of systems with designed biological functions because proteins carry out most of the biological functions and chemical reactions inside cells. Protein synthesis is considered to comprise the most basic levels of the hierarchical structure of synthetic biology. Cell-free protein synthesis has emerged as a powerful technology that can potentially transform the concept of bioprocesses. With the ability to harness the synthetic power of biology without many of the constraints of cell-based systems, cell-free protein synthesis enables the rapid creation of protein molecules from diverse sources of genetic information. Cell-free protein synthesis is virtually free from the intrinsic constraints of cell-based methods and offers greater flexibility in system design and manipulability of biological synthetic machinery. Among its potential applications, cell-free protein synthesis can be combined with various man-made devices for rapid functional analysis of genomic sequences. This review covers recent efforts to integrate cell-free protein synthesis with various reaction devices and analytical platforms. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

Revealing complex function, process and pathway interactions with high-throughput expression and biological annotation data.

PubMed

Singh, Nitesh Kumar; Ernst, Mathias; Liebscher, Volkmar; Fuellen, Georg; Taher, Leila

2016-10-20

The biological relationships both between and within the functions, processes and pathways that operate within complex biological systems are only poorly characterized, making the interpretation of large scale gene expression datasets extremely challenging. Here, we present an approach that integrates gene expression and biological annotation data to identify and describe the interactions between biological functions, processes and pathways that govern a phenotype of interest. The product is a global, interconnected network, not of genes but of functions, processes and pathways, that represents the biological relationships within the system. We validated our approach on two high-throughput expression datasets describing organismal and organ development. Our findings are well supported by the available literature, confirming that developmental processes and apoptosis play key roles in cell differentiation. Furthermore, our results suggest that processes related to pluripotency and lineage commitment, which are known to be critical for development, interact mainly indirectly, through genes implicated in more general biological processes. Moreover, we provide evidence that supports the relevance of cell spatial organization in the developing liver for proper liver function. Our strategy can be viewed as an abstraction that is useful to interpret high-throughput data and devise further experiments.

A biomimetic functionalization approach to integration of carbon nanoutbes into biological systems

NASA Astrophysics Data System (ADS)

Chen, Xing; Tam, Un Chong; Bertozzi, Carolyn; Zettl, Alex

2006-03-01

Due to their remarkable structural, electrical, and mechanical properties, carbon nanotubes (CNTs) have potential applications in biology ranging from imaging and tissue engineering. To realize these applications, however, new strategies for controlling the interaction between CNTs and biological systems such as proteins and cells are required. Here we describe a biomimetic approach to functionalize CNTs and therefore render them biocompatibility in order to facilitate their integration into biological systems. CNTs were coated with synthetic gycopolymers that mimic cell surface mucin gycoproteins. The functionalized CNTs were soluble in water, resisted non-specific protein binding and bound specifically to biomolecules. The coated CNTs could then be integrated onto mammalian cell surface by virtue of glycan-receptor interactions. Furthermore, the functionalized CNTs are non-toxic to cells. This strategy offers new opportunities for development of biosensor to probe biological processes. References: 1. X. Chen, G. S. Lee, A. Zettl, C. R. Bertozzi, Angewandte Chemie-International Edition 43, 6111 (2004). 2. X. Chen, U. C. Tam, J. L. Czlapanski, G. S. Lee, D. Rabuka, A. Zettl, C. R. Bertozzi, submitted.

Dynamics of biological systems: role of systems biology in medical research.

PubMed

Assmus, Heike E; Herwig, Ralf; Cho, Kwang-Hyun; Wolkenhauer, Olaf

2006-11-01

Cellular systems are networks of interacting components that change with time in response to external and internal events. Studying the dynamic behavior of these networks is the basis for an understanding of cellular functions and disease mechanisms. Quantitative time-series data leading to meaningful models can improve our knowledge of human physiology in health and disease, and aid the search for earlier diagnoses, better therapies and a healthier life. The advent of systems biology is about to take the leap into clinical research and medical applications. This review emphasizes the importance of a dynamic view and understanding of cell function. We discuss the potential for computer-aided mathematical modeling of biological systems in medical research with examples from some of the major therapeutic areas: cancer, cardiovascular, diabetic and neurodegenerative medicine.

Hierarchical structure of biological systems

PubMed Central

Alcocer-Cuarón, Carlos; Rivera, Ana L; Castaño, Victor M

2014-01-01

A general theory of biological systems, based on few fundamental propositions, allows a generalization of both Wierner and Berthalanffy approaches to theoretical biology. Here, a biological system is defined as a set of self-organized, differentiated elements that interact pair-wise through various networks and media, isolated from other sets by boundaries. Their relation to other systems can be described as a closed loop in a steady-state, which leads to a hierarchical structure and functioning of the biological system. Our thermodynamical approach of hierarchical character can be applied to biological systems of varying sizes through some general principles, based on the exchange of energy information and/or mass from and within the systems. PMID:24145961

Hierarchical structure of biological systems: a bioengineering approach.

PubMed

Alcocer-Cuarón, Carlos; Rivera, Ana L; Castaño, Victor M

2014-01-01

A general theory of biological systems, based on few fundamental propositions, allows a generalization of both Wierner and Berthalanffy approaches to theoretical biology. Here, a biological system is defined as a set of self-organized, differentiated elements that interact pair-wise through various networks and media, isolated from other sets by boundaries. Their relation to other systems can be described as a closed loop in a steady-state, which leads to a hierarchical structure and functioning of the biological system. Our thermodynamical approach of hierarchical character can be applied to biological systems of varying sizes through some general principles, based on the exchange of energy information and/or mass from and within the systems.

Biological Basis For Computer Vision: Some Perspectives

NASA Astrophysics Data System (ADS)

Gupta, Madan M.

1990-03-01

Using biology as a basis for the development of sensors, devices and computer vision systems is a challenge to systems and vision scientists. It is also a field of promising research for engineering applications. Biological sensory systems, such as vision, touch and hearing, sense different physical phenomena from our environment, yet they possess some common mathematical functions. These mathematical functions are cast into the neural layers which are distributed throughout our sensory regions, sensory information transmission channels and in the cortex, the centre of perception. In this paper, we are concerned with the study of the biological vision system and the emulation of some of its mathematical functions, both retinal and visual cortex, for the development of a robust computer vision system. This field of research is not only intriguing, but offers a great challenge to systems scientists in the development of functional algorithms. These functional algorithms can be generalized for further studies in such fields as signal processing, control systems and image processing. Our studies are heavily dependent on the the use of fuzzy - neural layers and generalized receptive fields. Building blocks of such neural layers and receptive fields may lead to the design of better sensors and better computer vision systems. It is hoped that these studies will lead to the development of better artificial vision systems with various applications to vision prosthesis for the blind, robotic vision, medical imaging, medical sensors, industrial automation, remote sensing, space stations and ocean exploration.

"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.

Bionic Nanosystems

NASA Astrophysics Data System (ADS)

Sebastian Mannoor, Manu

Direct multidimensional integration of functional electronics and mechanical elements with viable biological systems could allow for the creation of bionic systems and devices possessing unique and advanced capabilities. For example, the ability to three dimensionally integrate functional electronic and mechanical components with biological cells and tissue could enable the creation of bionic systems that can have tremendous impact in regenerative medicine, prosthetics, and human-machine interfaces. However, as a consequence of the inherent dichotomy in material properties and limitations of conventional fabrication methods, the attainment of truly seamless integration of electronic and/or mechanical components with biological systems has been challenging. Nanomaterials engineering offers a general route for overcoming these dichotomies, primarily due to the existence of a dimensional compatibility between fundamental biological functional units and abiotic nanomaterial building blocks. One area of compelling interest for bionic systems is in the field of biomedical sensing, where the direct interfacing of nanosensors onto biological tissue or the human body could stimulate exciting opportunities such as on-body health quality monitoring and adaptive threat detection. Further, interfacing of antimicrobial peptide based bioselective probes onto the bionic nanosensors could offer abilities to detect pathogenic bacteria with bio-inspired selectivity. Most compellingly, when paired with additive manufacturing techniques such as 3D printing, these characteristics enable three dimensional integration and merging of a variety of functional materials including electronic, structural and biomaterials with viable biological cells, in the precise anatomic geometries of human organs, to form three dimensionally integrated, multi-functional bionic hybrids and cyborg devices with unique capabilities. In this thesis, we illustrate these approaches using three representative bionic systems: 1) Bionic Nanosensors: featuring bio-integrated graphene nanosensors for ubiquitous sensing, 2) Bionic Organs: featuring 3D printed bionic ears with three dimensionally integrated electronics and 3) Bionic Leaves: describing ongoing work in the direction of the creation of a bionic leaf enabled by the integration of plant derived photosynthetic functional units with electronic materials and components into a leaf-shaped hierarchical structure for harvesting photosynthetic bioelectricity.

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.

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

Quantitative Genetic Interactions Reveal Layers of Biological Modularity

PubMed Central

Beltrao, Pedro; Cagney, Gerard; Krogan, Nevan J.

2010-01-01

In the past, biomedical research has embraced a reductionist approach, primarily focused on characterizing the individual components that comprise a system of interest. Recent technical developments have significantly increased the size and scope of data describing biological systems. At the same time, advances in the field of systems biology have evoked a broader view of how the underlying components are interconnected. In this essay, we discuss how quantitative genetic interaction mapping has enhanced our view of biological systems, allowing a deeper functional interrogation at different biological scales. PMID:20510918

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.

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.

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

Mechanisms for Robust Cognition

ERIC Educational Resources Information Center

Walsh, Matthew M.; Gluck, Kevin A.

2015-01-01

To function well in an unpredictable environment using unreliable components, a system must have a high degree of robustness. Robustness is fundamental to biological systems and is an objective in the design of engineered systems such as airplane engines and buildings. Cognitive systems, like biological and engineered systems, exist within…

Potentials of single-cell biology in identification and validation of disease biomarkers.

PubMed

Niu, Furong; Wang, Diane C; Lu, Jiapei; Wu, Wei; Wang, Xiangdong

2016-09-01

Single-cell biology is considered a new approach to identify and validate disease-specific biomarkers. However, the concern raised by clinicians is how to apply single-cell measurements for clinical practice, translate the message of single-cell systems biology into clinical phenotype or explain alterations of single-cell gene sequencing and function in patient response to therapies. This study is to address the importance and necessity of single-cell gene sequencing in the identification and development of disease-specific biomarkers, the definition and significance of single-cell biology and single-cell systems biology in the understanding of single-cell full picture, the development and establishment of whole-cell models in the validation of targeted biological function and the figure and meaning of single-molecule imaging in single cell to trace intra-single-cell molecule expression, signal, interaction and location. We headline the important role of single-cell biology in the discovery and development of disease-specific biomarkers with a special emphasis on understanding single-cell biological functions, e.g. mechanical phenotypes, single-cell biology, heterogeneity and organization of genome function. We have reason to believe that such multi-dimensional, multi-layer, multi-crossing and stereoscopic single-cell biology definitely benefits the discovery and development of disease-specific biomarkers. © 2016 The Authors. Journal of Cellular and Molecular Medicine published by John Wiley & Sons Ltd and Foundation for Cellular and Molecular Medicine.

Findings

MedlinePlus

... Issue All Issues Explore Findings by Topic Cell Biology Cellular Structures, Functions, Processes, Imaging, Stress Response Chemistry ... Glycobiology, Synthesis, Natural Products, Chemical Reactions Computers in Biology Bioinformatics, Modeling, Systems Biology, Data Visualization Diseases Cancer, ...

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.

From noise to synthetic nucleoli: can synthetic biology achieve new insights?

PubMed

Ciechonska, Marta; Grob, Alice; Isalan, Mark

2016-04-18

Synthetic biology aims to re-organise and control biological components to make functional devices. Along the way, the iterative process of designing and testing gene circuits has the potential to yield many insights into the functioning of the underlying chassis of cells. Thus, synthetic biology is converging with disciplines such as systems biology and even classical cell biology, to give a new level of predictability to gene expression, cell metabolism and cellular signalling networks. This review gives an overview of the contributions that synthetic biology has made in understanding gene expression, in terms of cell heterogeneity (noise), the coupling of growth and energy usage to expression, and spatiotemporal considerations. We mainly compare progress in bacterial and mammalian systems, which have some of the most-developed engineering frameworks. Overall, one view of synthetic biology can be neatly summarised as "creating in order to understand."

The physical characteristics of human proteins in different biological functions.

PubMed

Wang, Tengjiao; Tang, Hailin

2017-01-01

The physical properties of gene products are the foundation of their biological functions. In this study, we systematically explored relationships between physical properties and biological functions. The physical properties including origin time, evolution pressure, mRNA and protein stability, molecular weight, hydrophobicity, acidity/alkaline, amino acid compositions, and chromosome location. The biological functions are defined from 4 aspects: biological process, molecular function, cellular component and cell/tissue/organ expression. We found that the proteins associated with basic material and energy metabolism process originated earlier, while the proteins associated with immune, neurological system process etc. originated later. Tissues may have a strong influence on evolution pressure. The proteins associated with energy metabolism are double-stable. Immune and peripheral cell proteins tend to be mRNA stable/protein unstable. There are very few function items with double-unstable of mRNA and protein. The proteins involved in the cell adhesion tend to consist of large proteins with high proportion of small amino acids. The proteins of organic acid transport, neurological system process and amine transport have significantly high hydrophobicity. Interestingly, the proteins involved in olfactory receptor activity tend to have high frequency of aromatic, sulfuric and hydroxyl amino acids.

The physical characteristics of human proteins in different biological functions

PubMed Central

Tang, Hailin

2017-01-01

The physical properties of gene products are the foundation of their biological functions. In this study, we systematically explored relationships between physical properties and biological functions. The physical properties including origin time, evolution pressure, mRNA and protein stability, molecular weight, hydrophobicity, acidity/alkaline, amino acid compositions, and chromosome location. The biological functions are defined from 4 aspects: biological process, molecular function, cellular component and cell/tissue/organ expression. We found that the proteins associated with basic material and energy metabolism process originated earlier, while the proteins associated with immune, neurological system process etc. originated later. Tissues may have a strong influence on evolution pressure. The proteins associated with energy metabolism are double-stable. Immune and peripheral cell proteins tend to be mRNA stable/protein unstable. There are very few function items with double-unstable of mRNA and protein. The proteins involved in the cell adhesion tend to consist of large proteins with high proportion of small amino acids. The proteins of organic acid transport, neurological system process and amine transport have significantly high hydrophobicity. Interestingly, the proteins involved in olfactory receptor activity tend to have high frequency of aromatic, sulfuric and hydroxyl amino acids. PMID:28459865

Underlying Principles of Natural Selection in Network Evolution: Systems Biology Approach

PubMed Central

Chen, Bor-Sen; Wu, Wei-Sheng

2007-01-01

Systems biology is a rapidly expanding field that integrates diverse areas of science such as physics, engineering, computer science, mathematics, and biology toward the goal of elucidating the underlying principles of hierarchical metabolic and regulatory systems in the cell, and ultimately leading to predictive understanding of cellular response to perturbations. Because post-genomics research is taking place throughout the tree of life, comparative approaches offer a way for combining data from many organisms to shed light on the evolution and function of biological networks from the gene to the organismal level. Therefore, systems biology can build on decades of theoretical work in evolutionary biology, and at the same time evolutionary biology can use the systems biology approach to go in new uncharted directions. In this study, we present a review of how the post-genomics era is adopting comparative approaches and dynamic system methods to understand the underlying design principles of network evolution and to shape the nascent field of evolutionary systems biology. Finally, the application of evolutionary systems biology to robust biological network designs is also discussed from the synthetic biology perspective. PMID:19468310

A dedicated database system for handling multi-level data in systems biology.

PubMed

Pornputtapong, Natapol; Wanichthanarak, Kwanjeera; Nilsson, Avlant; Nookaew, Intawat; Nielsen, Jens

2014-01-01

Advances in high-throughput technologies have enabled extensive generation of multi-level omics data. These data are crucial for systems biology research, though they are complex, heterogeneous, highly dynamic, incomplete and distributed among public databases. This leads to difficulties in data accessibility and often results in errors when data are merged and integrated from varied resources. Therefore, integration and management of systems biological data remain very challenging. To overcome this, we designed and developed a dedicated database system that can serve and solve the vital issues in data management and hereby facilitate data integration, modeling and analysis in systems biology within a sole database. In addition, a yeast data repository was implemented as an integrated database environment which is operated by the database system. Two applications were implemented to demonstrate extensibility and utilization of the system. Both illustrate how the user can access the database via the web query function and implemented scripts. These scripts are specific for two sample cases: 1) Detecting the pheromone pathway in protein interaction networks; and 2) Finding metabolic reactions regulated by Snf1 kinase. In this study we present the design of database system which offers an extensible environment to efficiently capture the majority of biological entities and relations encountered in systems biology. Critical functions and control processes were designed and implemented to ensure consistent, efficient, secure and reliable transactions. The two sample cases on the yeast integrated data clearly demonstrate the value of a sole database environment for systems biology research.

[Obesity as pathology of adipocytes: number of cells, volume of arterial bloodstream,local pools of circulation in vivo, natriuretic peptides and arterial hypertension].

PubMed

Titov, V N; Dmitriev, V A

2015-03-01

The non-specific systemic biological reaction of arterial pressure from the level of organism. vasomotor center and proximal section of arterial bloodstream is appealed to compensate disorders of metabolism and microcirculation in distal section of arteries. This phenomenon occurs in several cases. The primarily local disorders of metabolism at autocrine level, physiological (aphysiological) death of cells, "littering" of intercellular medium become the cause of disorder of microcirculation in paracrin cenosises and deteriorate realization of biological functions of homeostasis, trophology, endoecology and adaptation. The local compensation of affected perfusion in paracrin cenosises at the expense of function of peripheral peristaltic pumps, redistribution of local bloodflow in biological reaction of endothelium-depended vaso-dilation has no possibility to eliminate disorders in realization of biological functions. The systemic increase of arterial pressure under absence of specific symptoms of symptomatic arterial hypertension is a test to detect disorder of biological functions of homeostasis, trophology, biological function of endoecology and adaptation. Allforms of arterial hypertension develop by common algorithm independently from causes of disorders of blood flow, microcirculation in distal section of arteries. The non-specific systemic compensation ofdisorders of metabolism from level of organism, in proximal section of arterial bloodstream always is the same one and results in aphysiological alterations in organs-targets. To comprehend etiological characteristics of common pathogenesis of arterial hypertension is possible in case of application of such technically complicated and still unclear in differential diagnostic of deranged functions modes of metabolomics.

Computational approaches to metabolic engineering utilizing systems biology and synthetic biology.

PubMed

Fong, Stephen S

2014-08-01

Metabolic engineering modifies cellular function to address various biochemical applications. Underlying metabolic engineering efforts are a host of tools and knowledge that are integrated to enable successful outcomes. Concurrent development of computational and experimental tools has enabled different approaches to metabolic engineering. One approach is to leverage knowledge and computational tools to prospectively predict designs to achieve the desired outcome. An alternative approach is to utilize combinatorial experimental tools to empirically explore the range of cellular function and to screen for desired traits. This mini-review focuses on computational systems biology and synthetic biology tools that can be used in combination for prospective in silico strain design.

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

Adaptive Neurotechnology for Making Neural Circuits Functional .

NASA Astrophysics Data System (ADS)

Jung, Ranu

2008-03-01

Two of the most important trends in recent technological developments are that technology is increasingly integrated with biological systems and that it is increasingly adaptive in its capabilities. Neuroprosthetic systems that provide lost sensorimotor function after a neural disability offer a platform to investigate this interplay between biological and engineered systems. Adaptive neurotechnology (hardware and software) could be designed to be biomimetic, guided by the physical and programmatic constraints observed in biological systems, and allow for real-time learning, stability, and error correction. An example will present biomimetic neural-network hardware that can be interfaced with the isolated spinal cord of a lower vertebrate to allow phase-locked real-time neural control. Another will present adaptive neural network control algorithms for functional electrical stimulation of the peripheral nervous system to provide desired movements of paralyzed limbs in rodents or people. Ultimately, the frontier lies in being able to utilize the adaptive neurotechnology to promote neuroplasticity in the living system on a long-time scale under co-adaptive conditions.

Computing biological functions using BioΨ, a formal description of biological processes based on elementary bricks of actions

PubMed Central

Pérès, Sabine; Felicori, Liza; Rialle, Stéphanie; Jobard, Elodie; Molina, Franck

2010-01-01

Motivation: In the available databases, biological processes are described from molecular and cellular points of view, but these descriptions are represented with text annotations that make it difficult to handle them for computation. Consequently, there is an obvious need for formal descriptions of biological processes. Results: We present a formalism that uses the BioΨ concepts to model biological processes from molecular details to networks. This computational approach, based on elementary bricks of actions, allows us to calculate on biological functions (e.g. process comparison, mapping structure–function relationships, etc.). We illustrate its application with two examples: the functional comparison of proteases and the functional description of the glycolysis network. This computational approach is compatible with detailed biological knowledge and can be applied to different kinds of systems of simulation. Availability: www.sysdiag.cnrs.fr/publications/supplementary-materials/BioPsi_Manager/ Contact: sabine.peres@sysdiag.cnrs.fr; franck.molina@sysdiag.cnrs.fr Supplementary information: Supplementary data are available at Bioinformatics online. PMID:20448138

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.

New Tools and New Biology: Recent Miniaturized Systems for Molecular and Cellular Biology

PubMed Central

Hamon, Morgan; Hong, Jong Wook

2013-01-01

Recent advances in applied physics and chemistry have led to the development of novel microfluidic systems. Microfluidic systems allow minute amounts of reagents to be processed using μm-scale channels and offer several advantages over conventional analytical devices for use in biological sciences: faster, more accurate and more reproducible analytical performance, reduced cell and reagent consumption, portability, and integration of functional components in a single chip. In this review, we introduce how microfluidics has been applied to biological sciences. We first present an overview of the fabrication of microfluidic systems and describe the distinct technologies available for biological research. We then present examples of microsystems used in biological sciences, focusing on applications in molecular and cellular biology. PMID:24305843

Human-aided admixture may fuel ecosystem transformation during biological invasions: theoretical and experimental evidence.

PubMed

Molofsky, Jane; Keller, Stephen R; Lavergne, Sébastien; Kaproth, Matthew A; Eppinga, Maarten B

2014-04-01

Biological invasions can transform our understanding of how the interplay of historical isolation and contemporary (human-aided) dispersal affects the structure of intraspecific diversity in functional traits, and in turn, how changes in functional traits affect other scales of biological organization such as communities and ecosystems. Because biological invasions frequently involve the admixture of previously isolated lineages as a result of human-aided dispersal, studies of invasive populations can reveal how admixture results in novel genotypes and shifts in functional trait variation within populations. Further, because invasive species can be ecosystem engineers within invaded ecosystems, admixture-induced shifts in the functional traits of invaders can affect the composition of native biodiversity and alter the flow of resources through the system. Thus, invasions represent promising yet under-investigated examples of how the effects of short-term evolutionary changes can cascade across biological scales of diversity. Here, we propose a conceptual framework that admixture between divergent source populations during biological invasions can reorganize the genetic variation underlying key functional traits, leading to shifts in the mean and variance of functional traits within invasive populations. Changes in the mean or variance of key traits can initiate new ecological feedback mechanisms that result in a critical transition from a native ecosystem to a novel invasive ecosystem. We illustrate the application of this framework with reference to a well-studied plant model system in invasion biology and show how a combination of quantitative genetic experiments, functional trait studies, whole ecosystem field studies and modeling can be used to explore the dynamics predicted to trigger these critical transitions.

Systems biology and mechanics of growth.

PubMed

Eskandari, Mona; Kuhl, Ellen

2015-01-01

In contrast to inert systems, living biological systems have the advantage to adapt to their environment through growth and evolution. This transfiguration is evident during embryonic development, when the predisposed need to grow allows form to follow function. Alterations in the equilibrium state of biological systems breed disease and mutation in response to environmental triggers. The need to characterize the growth of biological systems to better understand these phenomena has motivated the continuum theory of growth and stimulated the development of computational tools in systems biology. Biological growth in development and disease is increasingly studied using the framework of morphoelasticity. Here, we demonstrate the potential for morphoelastic simulations through examples of volume, area, and length growth, inspired by tumor expansion, chronic bronchitis, brain development, intestine formation, plant shape, and myopia. We review the systems biology of living systems in light of biochemical and optical stimuli and classify different types of growth to facilitate the design of growth models for various biological systems within this generic framework. Exploring the systems biology of growth introduces a new venue to control and manipulate embryonic development, disease progression, and clinical intervention. © 2015 Wiley Periodicals, Inc.

The planetary biology of cytochrome P450 aromatases.

PubMed

Gaucher, Eric A; Graddy, Logan G; Li, Tang; Simmen, Rosalia C M; Simmen, Frank A; Schreiber, David R; Liberles, David A; Janis, Christine M; Benner, Steven A

2004-08-17

Joining a model for the molecular evolution of a protein family to the paleontological and geological records (geobiology), and then to the chemical structures of substrates, products, and protein folds, is emerging as a broad strategy for generating hypotheses concerning function in a post-genomic world. This strategy expands systems biology to a planetary context, necessary for a notion of fitness to underlie (as it must) any discussion of function within a biomolecular system. Here, we report an example of such an expansion, where tools from planetary biology were used to analyze three genes from the pig Sus scrofa that encode cytochrome P450 aromatases-enzymes that convert androgens into estrogens. The evolutionary history of the vertebrate aromatase gene family was reconstructed. Transition redundant exchange silent substitution metrics were used to interpolate dates for the divergence of family members, the paleontological record was consulted to identify changes in physiology that correlated in time with the change in molecular behavior, and new aromatase sequences from peccary were obtained. Metrics that detect changing function in proteins were then applied, including KA/KS values and those that exploit structural biology. These identified specific amino acid replacements that were associated with changing substrate and product specificity during the time of presumed adaptive change. The combined analysis suggests that aromatase paralogs arose in pigs as a result of selection for Suoidea with larger litters than their ancestors, and permitted the Suoidea to survive the global climatic trauma that began in the Eocene. This combination of bioinformatics analysis, molecular evolution, paleontology, cladistics, global climatology, structural biology, and organic chemistry serves as a paradigm in planetary biology. As the geological, paleontological, and genomic records improve, this approach should become widely useful to make systems biology statements about high-level function for biomolecular systems.

The planetary biology of cytochrome P450 aromatases

PubMed Central

Gaucher, Eric A; Graddy, Logan G; Li, Tang; Simmen, Rosalia CM; Simmen, Frank A; Schreiber, David R; Liberles, David A; Janis, Christine M; Benner, Steven A

2004-01-01

Background Joining a model for the molecular evolution of a protein family to the paleontological and geological records (geobiology), and then to the chemical structures of substrates, products, and protein folds, is emerging as a broad strategy for generating hypotheses concerning function in a post-genomic world. This strategy expands systems biology to a planetary context, necessary for a notion of fitness to underlie (as it must) any discussion of function within a biomolecular system. Results Here, we report an example of such an expansion, where tools from planetary biology were used to analyze three genes from the pig Sus scrofa that encode cytochrome P450 aromatases–enzymes that convert androgens into estrogens. The evolutionary history of the vertebrate aromatase gene family was reconstructed. Transition redundant exchange silent substitution metrics were used to interpolate dates for the divergence of family members, the paleontological record was consulted to identify changes in physiology that correlated in time with the change in molecular behavior, and new aromatase sequences from peccary were obtained. Metrics that detect changing function in proteins were then applied, including KA/KS values and those that exploit structural biology. These identified specific amino acid replacements that were associated with changing substrate and product specificity during the time of presumed adaptive change. The combined analysis suggests that aromatase paralogs arose in pigs as a result of selection for Suoidea with larger litters than their ancestors, and permitted the Suoidea to survive the global climatic trauma that began in the Eocene. Conclusions This combination of bioinformatics analysis, molecular evolution, paleontology, cladistics, global climatology, structural biology, and organic chemistry serves as a paradigm in planetary biology. As the geological, paleontological, and genomic records improve, this approach should become widely useful to make systems biology statements about high-level function for biomolecular systems. PMID:15315709

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.

Autonomous biological system-an unique method of conducting long duration space flight experiments for pharmaceutical and gravitational biology research

NASA Astrophysics Data System (ADS)

Anderson, G. A.; MacCallum, T. K.; Poynter, J. E.; Klaus, D., Dr.

1998-01-01

Paragon Space Development Corporation (SDC) has developed an Autonomous Biological System (ABS) that can be flown in space to provide for long term growth and breeding of aquatic plants, animals, microbes and algae. The system functions autonomously and in isolation from the spacecraft life support systems and with no mandatory crew time required for function or observation. The ABS can also be used for long term plant and animal life support and breeding on a free flyer space craft. The ABS units are a research tool for both pharmaceutical and basic space biological sciences. Development flights in May of 1996 and September, 1996 through January, 1997 were largely successful, showing both that the hardware and life systems are performing with beneficial results, though some surprises were still found. The two space flights, plus the current flight now on Mir, are expected to result in both a scientific and commercially usable system for breeding and propagation of animals and plants in space.

Bio-inspired engineering of cell- and virus-like nanoparticles for drug delivery.

PubMed

Parodi, Alessandro; Molinaro, Roberto; Sushnitha, Manuela; Evangelopoulos, Michael; Martinez, Jonathan O; Arrighetti, Noemi; Corbo, Claudia; Tasciotti, Ennio

2017-12-01

The engineering of future generations of nanodelivery systems aims at the creation of multifunctional vectors endowed with improved circulation, enhanced targeting and responsiveness to the biological environment. Moving past purely bio-inert systems, researchers have begun to create nanoparticles capable of proactively interacting with the biology of the body. Nature offers a wide-range of sources of inspiration for the synthesis of more effective drug delivery platforms. Because the nano-bio-interface is the key driver of nanoparticle behavior and function, the modification of nanoparticles' surfaces allows the transfer of biological properties to synthetic carriers by imparting them with a biological identity. Modulation of these surface characteristics governs nanoparticle interactions with the biological barriers they encounter. Building off these observations, we provide here an overview of virus- and cell-derived biomimetic delivery systems that combine the intrinsic hallmarks of biological membranes with the delivery capabilities of synthetic carriers. We describe the features and properties of biomimetic delivery systems, recapitulating the distinctive traits and functions of viruses, exosomes, platelets, red and white blood cells. By mimicking these biological entities, we will learn how to more efficiently interact with the human body and refine our ability to negotiate with the biological barriers that impair the therapeutic efficacy of nanoparticles. Copyright © 2017. Published by Elsevier Ltd.

Plant MetGenMAP: an integrative analysis system for plant systems biology

USDA-ARS?s Scientific Manuscript database

We have developed a web-based system, Plant MetGenMAP, which can identify significantly altered biochemical pathways and highly affected biological processes, predict functional roles of pathway genes, and potential pathway-related regulatory motifs from transcript and metabolite profile datasets. P...

Towards Self-Assembled Hybrid Artificial Cells: Novel Bottom-Up Approaches to Functional Synthetic Membranes

PubMed Central

Brea, Roberto J.; Hardy, Michael D.; Devaraj, Neal K.

2015-01-01

There has been increasing interest in utilizing bottom-up approaches to develop synthetic cells. A popular methodology is the integration of functionalized synthetic membranes with biological systems, producing “hybrid” artificial cells. This Concept article covers recent advances and the current state-of-the-art of such hybrid systems. Specifically, we describe minimal supramolecular constructs that faithfully mimic the structure and/or function of living cells, often by controlling the assembly of highly ordered membrane architectures with defined functionality. These studies give us a deeper understanding of the nature of living systems, bring new insights into the origin of cellular life, and provide novel synthetic chassis for advancing synthetic biology. PMID:26149747

Systematic, spatial imaging of large multimolecular assemblies and the emerging principles of supramolecular order in biological systems

PubMed Central

Schubert, Walter

2013-01-01

Understanding biological systems at the level of their relational (emergent) molecular properties in functional protein networks relies on imaging methods, able to spatially resolve a tissue or a cell as a giant, non-random, topologically defined collection of interacting supermolecules executing myriads of subcellular mechanisms. Here, the development and findings of parameter-unlimited functional super-resolution microscopy are described—a technology based on the fluorescence imaging cycler (IC) principle capable of co-mapping thousands of distinct biomolecular assemblies at high spatial resolution and differentiation (<40 nm distances). It is shown that the subcellular and transcellular features of such supermolecules can be described at the compositional and constitutional levels; that the spatial connection, relational stoichiometry, and topology of supermolecules generate hitherto unrecognized functional self-segmentation of biological tissues; that hierarchical features, common to thousands of simultaneously imaged supermolecules, can be identified; and how the resulting supramolecular order relates to spatial coding of cellular functionalities in biological systems. A large body of observations with IC molecular systems microscopy collected over 20 years have disclosed principles governed by a law of supramolecular segregation of cellular functionalities. This pervades phenomena, such as exceptional orderliness, functional selectivity, combinatorial and spatial periodicity, and hierarchical organization of large molecular systems, across all species investigated so far. This insight is based on the high degree of specificity, selectivity, and sensitivity of molecular recognition processes for fluorescence imaging beyond the spectral resolution limit, using probe libraries controlled by ICs. © 2013 The Authors. Journal of Molecular Recognition published by John Wiley & Sons, Ltd. PMID:24375580

Thinking about Digestive System in Early Childhood: A Comparative Study about Biological Knowledge

ERIC Educational Resources Information Center

AHI, Berat

2017-01-01

The current study aims to explore how children explain the concepts of biology and how biological knowledge develops across ages by focusing on the structure and functions of the digestive system. The study was conducted with 60 children. The data were collected through the interviews conducted within a think-aloud protocol. The interview data…

[Chronobiology of immune system].

PubMed

Trufakin, V A; Shurlygina, A V; Dergacheva, T I; Litvinenko, G I; Verbitskaia, L V

1999-01-01

The biological rhythmological programme of the immune system is a constituent of the body's common biological rhythmological programme. Its pattern seems to be genetically determined and reflects the functional status of the system. The chronobiological mechanisms responsible for the regulation of immune functions lie in the presence of certain phasic interrelations between the biological rhythms of the synthesis and production of regulatory agents on the one hand, and those of the receptor system and metabolic potential of immunocompetent cells on the other. The facts given in the paper may be a basis for a chronobiological approach to better understanding the mechanisms of the physiology and pathology of the immune system. The medical significance of study of the structural and temporal pattern of the immune system consists in the development of new techniques for diagnosis, prognosis, therapy, and assessment of risk factors in immunopathological conditions.

A Theoretical Mechanism of Szilard Engine Function in Nucleic Acids and the Implications for Quantum Coherence in Biological Systems

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

Matthew Mihelic, F.

2010-12-22

Nucleic acids theoretically possess a Szilard engine function that can convert the energy associated with the Shannon entropy of molecules for which they have coded recognition, into the useful work of geometric reconfiguration of the nucleic acid molecule. This function is logically reversible because its mechanism is literally and physically constructed out of the information necessary to reduce the Shannon entropy of such molecules, which means that this information exists on both sides of the theoretical engine, and because information is retained in the geometric degrees of freedom of the nucleic acid molecule, a quantum gate is formed through whichmore » multi-state nucleic acid qubits can interact. Entangled biophotons emitted as a consequence of symmetry breaking nucleic acid Szilard engine (NASE) function can be used to coordinate relative positioning of different nucleic acid locations, both within and between cells, thus providing the potential for quantum coherence of an entire biological system. Theoretical implications of understanding biological systems as such 'quantum adaptive systems' include the potential for multi-agent based quantum computing, and a better understanding of systemic pathologies such as cancer, as being related to a loss of systemic quantum coherence.« less

A Theoretical Mechanism of Szilard Engine Function in Nucleic Acids and the Implications for Quantum Coherence in Biological Systems

NASA Astrophysics Data System (ADS)

Matthew Mihelic, F.

2010-12-01

Nucleic acids theoretically possess a Szilard engine function that can convert the energy associated with the Shannon entropy of molecules for which they have coded recognition, into the useful work of geometric reconfiguration of the nucleic acid molecule. This function is logically reversible because its mechanism is literally and physically constructed out of the information necessary to reduce the Shannon entropy of such molecules, which means that this information exists on both sides of the theoretical engine, and because information is retained in the geometric degrees of freedom of the nucleic acid molecule, a quantum gate is formed through which multi-state nucleic acid qubits can interact. Entangled biophotons emitted as a consequence of symmetry breaking nucleic acid Szilard engine (NASE) function can be used to coordinate relative positioning of different nucleic acid locations, both within and between cells, thus providing the potential for quantum coherence of an entire biological system. Theoretical implications of understanding biological systems as such "quantum adaptive systems" include the potential for multi-agent based quantum computing, and a better understanding of systemic pathologies such as cancer, as being related to a loss of systemic quantum coherence.

Biological-based and physical-based optimization for biological evaluation of prostate patient's plans

NASA Astrophysics Data System (ADS)

Sukhikh, E.; Sheino, I.; Vertinsky, A.

2017-09-01

Modern modalities of radiation treatment therapy allow irradiation of the tumor to high dose values and irradiation of organs at risk (OARs) to low dose values at the same time. In this paper we study optimal radiation treatment plans made in Monaco system. The first aim of this study was to evaluate dosimetric features of Monaco treatment planning system using biological versus dose-based cost functions for the OARs and irradiation targets (namely tumors) when the full potential of built-in biological cost functions is utilized. The second aim was to develop criteria for the evaluation of radiation dosimetry plans for patients based on the macroscopic radiobiological criteria - TCP/NTCP. In the framework of the study four dosimetric plans were created utilizing the full extent of biological and physical cost functions using dose calculation-based treatment planning for IMRT Step-and-Shoot delivery of stereotactic body radiation therapy (SBRT) in prostate case (5 fractions per 7 Gy).

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

Biocompatible Nanomaterials and Nanodevices Promising for Biomedical Applications

NASA Astrophysics Data System (ADS)

Firkowska, Izabela; Giannona, Suna; Rojas-Chapana, José A.; Luecke, Klaus; Brüstle, Oliver; Giersig, Michael

Nanotechnology applied to biology requires a thorough understanding of how molecules, sub-cellular entities, cells, tissues, and organs function and how they are structured. The merging of nanomaterials and life science into hybrids of controlled organization and function is possible, assuming that biology is nanostructured, and therefore man-made nano-materials can structurally mimic nature and complement each other. By taking advantage of their special properties, nanomaterials can stimulate, respond to and interact with target cells and tissues in controlled ways to induce desired physiological responses with a minimum of undesirable effects. To fulfill this goal the fabrication of nano-engineered materials and devices has to consider the design of natural systems. Thus, engineered micro-nano-featured systems can be applied to biology and biomedicine to enable new functionalities and new devices. These include, among others, nanostructured implants providing many advantages over existing, conventional ones, nanodevices for cell manipulation, and nanosensors that would provide reliable information on biological processes and functions.

Genome Editing to Study Ca2+ Homeostasis in Zebrafish Cone Photoreceptors.

PubMed

Brockerhoff, Susan E

2017-01-01

Photoreceptors are specialized sensory neurons with unique biological features. Phototransduction is well understood due in part to the exclusive expression and function of the molecular components of this cascade. Many other processes are less well understood, but also extremely important for understanding photoreceptor function and for treating disease. One example is the role of Ca 2+ in the cell body and overall compartmentalization and regulation of Ca 2+ within the cell. The recent development of CRISPR/Cas9 genome editing techniques has made it possible to rapidly and cheaply alter specific genes. This will help to define the biological function of elusive processes that have been more challenging to study. CRISPR/Cas9 has been optimized in many systems including zebrafish, which already has some distinct advantages for studying photoreceptor biology and function. These new genome editing technologies and the continued use of the zebrafish model system will help advance our understanding of important understudied aspects of photoreceptor biology.

Fostering synergy between cell biology and systems biology.

PubMed

Eddy, James A; Funk, Cory C; Price, Nathan D

2015-08-01

In the shared pursuit of elucidating detailed mechanisms of cell function, systems biology presents a natural complement to ongoing efforts in cell biology. Systems biology aims to characterize biological systems through integrated and quantitative modeling of cellular information. The process of model building and analysis provides value through synthesizing and cataloging information about cells and molecules, predicting mechanisms and identifying generalizable themes, generating hypotheses and guiding experimental design, and highlighting knowledge gaps and refining understanding. In turn, incorporating domain expertise and experimental data is crucial for building towards whole cell models. An iterative cycle of interaction between cell and systems biologists advances the goals of both fields and establishes a framework for mechanistic understanding of the genome-to-phenome relationship. Crown Copyright © 2015. Published by Elsevier Ltd. All rights reserved.

Validation of Procedures for Monitoring Crewmember Immune Function - Short Duration Biological Investigation

NASA Technical Reports Server (NTRS)

Sams, Clarence; Crucian, Brian; Stowe, Raymond; Pierson, Duane; Mehta, Satish; Morukov, Boris; Uchakin, Peter; Nehlsen-Cannarella, Sandra

2008-01-01

Validation of Procedures for Monitoring Crew Member Immune Function - Short Duration Biological Investigation (Integrated Immune-SDBI) will assess the clinical risks resulting from the adverse effects of space flight on the human immune system and will validate a flightcompatible immune monitoring strategy. Immune system changes will be monitored by collecting and analyzing blood, urine and saliva samples from crewmembers before, during and after space flight.

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

Why Do I Crave that Cookie?

ERIC Educational Resources Information Center

Ashmann, Scott; Nelson, Amanda

2012-01-01

Many traditional science curricula explore human body systems separately, paying little attention to how the systems interact. For example, the textbooks "Biology" (Miller and Levine 2006) and "Biology: An Everyday Experience" (Kaskel, Hummer, and Daniel 2003) detail the structure and function of each system and individual organs but offer little…

Genetic Resources of Energy Crops: Biological Systems to Combat Climate Change

USDA-ARS?s Scientific Manuscript database

Biological systems are expected to contribute to renewable energy production, help stabilize rising levels of green house gases (GHG), and mitigate the risk of global climate change (GCC). Bioenergy crop plants that function as solar energy collectors and thermo-chemical energy storage systems are t...

Emergence of biological organization through thermodynamic inversion.

PubMed

Kompanichenko, Vladimir

2014-01-01

Biological organization arises under thermodynamic inversion in prebiotic systems that provide the prevalence of free energy and information contribution over the entropy contribution. The inversion might occur under specific far-from-equilibrium conditions in prebiotic systems oscillating around the bifurcation point. At the inversion moment, (physical) information characteristic of non-biological systems acquires the new features: functionality, purposefulness, and control over the life processes, which transform it into biological information. Random sequences of amino acids and nucleotides, spontaneously synthesized in the prebiotic microsystem, in the primary living unit (probiont) re-assemble into functional sequences, involved into bioinformation circulation through nucleoprotein interaction, resulted in the genetic code emergence. According to the proposed concept, oscillating three-dimensional prebiotic microsystems transformed into probionts in the changeable hydrothermal medium of the early Earth. The inversion concept states that spontaneous (accidental, random) transformations in prebiotic systems cannot produce life; it is only non-spontaneous (perspective, purposeful) transformations, which are the result of thermodynamic inversion, that lead to the negentropy conversion of prebiotic systems into initial living units.

Modelling the Impact of Soil Management on Soil Functions

NASA Astrophysics Data System (ADS)

Vogel, H. J.; Weller, U.; Rabot, E.; Stößel, B.; Lang, B.; Wiesmeier, M.; Urbanski, L.; Wollschläger, U.

2017-12-01

Due to an increasing soil loss and an increasing demand for food and energy there is an enormous pressure on soils as the central resource for agricultural production. Besides the importance of soils for biomass production there are other essential soil functions, i.e. filter and buffer for water, carbon sequestration, provision and recycling of nutrients, and habitat for biological activity. All these functions have a direct feed back to biogeochemical cycles and climate. To render agricultural production efficient and sustainable we need to develop model tools that are capable to predict quantitatively the impact of a multitude of management measures on these soil functions. These functions are considered as emergent properties produced by soils as complex systems. The major challenge is to handle the multitude of physical, chemical and biological processes interacting in a non-linear manner. A large number of validated models for specific soil processes are available. However, it is not possible to simulate soil functions by coupling all the relevant processes at the detailed (i.e. molecular) level where they are well understood. A new systems perspective is required to evaluate the ensemble of soil functions and their sensitivity to external forcing. Another challenge is that soils are spatially heterogeneous systems by nature. Soil processes are highly dependent on the local soil properties and, hence, any model to predict soil functions needs to account for the site-specific conditions. For upscaling towards regional scales the spatial distribution of functional soil types need to be taken into account. We propose a new systemic model approach based on a thorough analysis of the interactions between physical, chemical and biological processes considering their site-specific characteristics. It is demonstrated for the example of soil compaction and the recovery of soil structure, water capacity and carbon stocks as a result of plant growth and biological activity. Coupling of the observed nonlinear interactions allows for modeling the stability and resilience of soil systems in terms of their essential functions.

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

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

Petunia, Your Next Supermodel?

PubMed Central

Vandenbussche, Michiel; Chambrier, Pierre; Rodrigues Bento, Suzanne; Morel, Patrice

2016-01-01

Plant biology in general, and plant evo–devo in particular would strongly benefit from a broader range of available model systems. In recent years, technological advances have facilitated the analysis and comparison of individual gene functions in multiple species, representing now a fairly wide taxonomic range of the plant kingdom. Because genes are embedded in gene networks, studying evolution of gene function ultimately should be put in the context of studying the evolution of entire gene networks, since changes in the function of a single gene will normally go together with further changes in its network environment. For this reason, plant comparative biology/evo–devo will require the availability of a defined set of ‘super’ models occupying key taxonomic positions, in which performing gene functional analysis and testing genetic interactions ideally is as straightforward as, e.g., in Arabidopsis. Here we review why petunia has the potential to become one of these future supermodels, as a representative of the Asterid clade. We will first detail its intrinsic qualities as a model system. Next, we highlight how the revolution in sequencing technologies will now finally allows exploitation of the petunia system to its full potential, despite that petunia has already a long history as a model in plant molecular biology and genetics. We conclude with a series of arguments in favor of a more diversified multi-model approach in plant biology, and we point out where the petunia model system may further play a role, based on its biological features and molecular toolkit. PMID:26870078

Biological organization of the extraocular muscles.

PubMed

Spencer, Robert F; Porter, John D

2006-01-01

Extraocular muscle is fundamentally distinct from other skeletal muscles. Here, we review the biological organization of the extraocular muscles with the intent of understanding this novel muscle group in the context of oculomotor system function. The specific objectives of this review are threefold. The first objective is to understand the anatomic arrangement of the extraocular muscles and their compartmental or layered organization in the context of a new concept of orbital mechanics, the active pulley hypothesis. The second objective is to present an integrated view of the morphologic, cellular, and molecular differences between extraocular and the more traditional skeletal muscles. The third objective is to relate recent data from functional and molecular biology studies to the established extraocular muscle fiber types. Developmental mechanisms that may be responsible for the divergence of the eye muscles from a skeletal muscle prototype also are considered. Taken together, a multidisciplinary understanding of extraocular muscle biology in health and disease provides insights into oculomotor system function and malfunction. Moreover, because the eye muscles are selectively involved or spared in a variety of neuromuscular diseases, knowledge of their biology may improve current pathogenic models of and treatments for devastating systemic diseases.

Darwin's legacy: the forms, function and sexual diversity of flowers

PubMed Central

Barrett, Spencer C. H.

2010-01-01

Charles Darwin studied floral biology for over 40 years and wrote three major books on plant reproduction. These works have provided the conceptual foundation for understanding floral adaptations that promote cross-fertilization and the mechanisms responsible for evolutionary transitions in reproductive systems. Many of Darwin's insights, gained from careful observations and experiments on diverse angiosperm species, remain remarkably durable today and have stimulated much current research on floral function and the evolution of mating systems. Here I review Darwin's seminal contributions to reproductive biology and provide an overview of the current status of research on several of the main topics to which he devoted considerable effort, including the consequences to fitness of cross- versus self-fertilization, the evolution and function of stylar polymorphisms, the adaptive significance of heteranthery, the origins of dioecy and related gender polymorphisms, and the transition from animal pollination to wind pollination. Post-Darwinian perspectives on floral function now recognize the importance of pollen dispersal and male outcrossed siring success in shaping floral adaptation. This has helped to link work on pollination biology and mating systems, two subfields of reproductive biology that remained largely isolated during much of the twentieth century despite Darwin's efforts towards integration. PMID:20047864

Applications of large-scale density functional theory in biology

NASA Astrophysics Data System (ADS)

Cole, Daniel J.; Hine, Nicholas D. M.

2016-10-01

Density functional theory (DFT) has become a routine tool for the computation of electronic structure in the physics, materials and chemistry fields. Yet the application of traditional DFT to problems in the biological sciences is hindered, to a large extent, by the unfavourable scaling of the computational effort with system size. Here, we review some of the major software and functionality advances that enable insightful electronic structure calculations to be performed on systems comprising many thousands of atoms. We describe some of the early applications of large-scale DFT to the computation of the electronic properties and structure of biomolecules, as well as to paradigmatic problems in enzymology, metalloproteins, photosynthesis and computer-aided drug design. With this review, we hope to demonstrate that first principles modelling of biological structure-function relationships are approaching a reality.

A Novel Characterization of Amalgamated Networks in Natural Systems

PubMed Central

Barranca, Victor J.; Zhou, Douglas; Cai, David

2015-01-01

Densely-connected networks are prominent among natural systems, exhibiting structural characteristics often optimized for biological function. To reveal such features in highly-connected networks, we introduce a new network characterization determined by a decomposition of network-connectivity into low-rank and sparse components. Based on these components, we discover a new class of networks we define as amalgamated networks, which exhibit large functional groups and dense connectivity. Analyzing recent experimental findings on cerebral cortex, food-web, and gene regulatory networks, we establish the unique importance of amalgamated networks in fostering biologically advantageous properties, including rapid communication among nodes, structural stability under attacks, and separation of network activity into distinct functional modules. We further observe that our network characterization is scalable with network size and connectivity, thereby identifying robust features significant to diverse physical systems, which are typically undetectable by conventional characterizations of connectivity. We expect that studying the amalgamation properties of biological networks may offer new insights into understanding their structure-function relationships. PMID:26035066

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

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

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.

The aims of systems biology: between molecules and organisms.

PubMed

Noble, D

2011-05-01

The systems approach to biology has a long history. Its recent rapid resurgence at the turn of the century reflects the problems encountered in interpreting the sequencing of the genome and the failure of that immense achievement to provide rapid and direct solutions to major multi-factorial diseases. This paper argues that systems biology is necessarily multilevel and that there is no privileged level of causality in biological systems. It is an approach rather than a separate discipline. Functionality arises from biological networks that interact with the genome, the environment and the phenotype. This view of biology is very different from the gene-centred views of neo-Darwinism and molecular biology. In neuroscience, the systems approach leads naturally to 2 important conclusions: first, that the idea of 'programs' in the brain is confusing, and second, that the self is better interpreted as a process than as an object. © Georg Thieme Verlag KG Stuttgart · New York.

Pushing the lipid envelope: using bio-inspired nanocomposites to understand and exploit lipid membrane limitations

NASA Astrophysics Data System (ADS)

Montano, Gabriel

Lipids serve as the organizing matrix material for biological membranes, the site of interaction of cells with the external environment. . As such, lipids play a critical role in structure/function relationships of an extraordinary number of critical biological processes. In this talk, we will look at bio-inspired membrane assemblies to better understand the roles of lipids in biological systems as well as attempt to generate materials that can mimic and potentially advance upon biological membrane processes. First, we will investigate the response of lipids to adverse conditions. In particular, I will present data that demonstrates the response of lipids to harsh conditions and how such responses can be exploited to generate nanocomposite rearrangements. I will also show the effect of adding the endotoxin lipopolysaccharide (LPS) to lipid bilayer assemblies and describe implications on our understanding of LPS organization in biological systems as well as describe induced lipid modifications that can be exploited to organize membrane composites with precise, two-dimensional geometric control. Lastly, I will describe the use of amphiphilic block copolymers to create membrane nanocomposites capable of mimicking biological systems. In particular, I will describe the use of our polymer-based membranes in creating artificial photosynthetic assemblies that rival biological systems in function in a more flexible, dynamic matrix.

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.

Biological Stress Systems, Adverse Life Events, and the Improvement of Chronic Multisite Musculoskeletal Pain Across a 6-Year Follow-Up.

PubMed

Generaal, Ellen; Vogelzangs, Nicole; Macfarlane, Gary J; Geenen, Rinie; Smit, Johannes H; de Geus, Eco J C N; Dekker, Joost; Penninx, Brenda W J H

2017-02-01

Dysfunction of biological stress systems and adverse life events, independently and in interaction, have been hypothesized to predict chronic pain persistence. Conversely, these factors may hamper the improvement of chronic pain. Longitudinal evidence is currently lacking. We examined whether: 1) function of biological stress systems, 2) adverse life events, and 3) their combination predict the improvement of chronic multisite musculoskeletal pain. Subjects of the Netherlands Study of Depression and Anxiety (NESDA) with chronic multisite musculoskeletal pain at baseline (N = 665) were followed-up 2, 4, and 6 years later. The Chronic Pain Grade Questionnaire was used to determine improvement (not meeting the criteria) of chronic multisite musculoskeletal pain at follow-up. Baseline assessment of biological stress systems included function of hypothalamic-pituitary-adrenal axis (1-hour cortisol awakening response, evening level, and post dexamethasone level), the immune system (basal and lipopolysaccharide-stimulated inflammatory markers), the autonomic nervous system (heart rate, pre-ejection period, SD of the normal-to-normal interval, and respiratory sinus arrhythmia). The number of adverse life events were assessed at baseline and 2-year follow-up using the List of Threatening Events Questionnaire. We showed that hypothalamic-pituitary-adrenal axis, immune system, and autonomic nervous system functioning and adverse life events were not associated with the improvement of chronic multisite musculoskeletal pain, either as a main effect or in interaction. This longitudinal study could not confirm that biological stress system dysfunction and adverse life events affect the course of chronic multisite musculoskeletal pain. Biological stress systems and adverse life events are not associated with the improvement of chronic multisite musculoskeletal pain over 6 years of follow-up. Other determinants should thus be considered in future research to identify in which persons pain symptoms will improve. Copyright © 2016 American Pain Society. Published by Elsevier Inc. All rights reserved.

Towards a behavioral-matching based compilation of synthetic biology functions.

PubMed

Basso-Blandin, Adrien; Delaplace, Franck

2015-09-01

The field of synthetic biology is looking forward engineering framework for safely designing reliable de-novo biological functions. In this undertaking, Computer-Aided-Design (CAD) environments should play a central role for facilitating the design. Although, CAD environment is widely used to engineer artificial systems the application in synthetic biology is still in its infancy. In this article we address the problem of the design of a high level language which at the core of CAD environment. More specifically the Gubs (Genomic Unified Behavioural Specification) language is a specification language used to describe the observations of the expected behaviour. The compiler appropriately selects components such that the observation of the synthetic biological function resulting to their assembly complies to the programmed behaviour.

Modeling Protein Evolution

NASA Astrophysics Data System (ADS)

Goldstein, Richard; Pollock, David

The study of biology is fundamentally different from many other scientific pursuits, such as geology or astrophysics. This difference stems from the ubiquitous questions that arise about function and purpose. These are questions concerning why biological objects operate the way they do: what is the function of a polymerase? What is the role of the immune system? No one, aside from the most dedicated anthropist or interventionist theist, would attempt to determine the purpose of the earth's mantle or the function of a binary star. Among the sciences, it is only biology in which the details of what an object does can be said to be part of the reason for its existence. This is because the process of evolution is capable of improving an object to better carry out a function; that is, it adapts an object within the constraints of mechanics and history (i.e., what has come before). Thus, the ultimate basis of these biological questions is the process of evolution; generally, the function of an enzyme, cell type, organ, system, or trait is the thing that it does that contributes to the fitness (i.e., reproductive success) of the organism of which it is a part or characteristic. Our investigations cannot escape the simple fact that all things in biology (including ourselves) are, ultimately, the result of an evolutionary process.

An online model composition tool for system biology models

PubMed Central

2013-01-01

Background There are multiple representation formats for Systems Biology computational models, and the Systems Biology Markup Language (SBML) is one of the most widely used. SBML is used to capture, store, and distribute computational models by Systems Biology data sources (e.g., the BioModels Database) and researchers. Therefore, there is a need for all-in-one web-based solutions that support advance SBML functionalities such as uploading, editing, composing, visualizing, simulating, querying, and browsing computational models. Results We present the design and implementation of the Model Composition Tool (Interface) within the PathCase-SB (PathCase Systems Biology) web portal. The tool helps users compose systems biology models to facilitate the complex process of merging systems biology models. We also present three tools that support the model composition tool, namely, (1) Model Simulation Interface that generates a visual plot of the simulation according to user’s input, (2) iModel Tool as a platform for users to upload their own models to compose, and (3) SimCom Tool that provides a side by side comparison of models being composed in the same pathway. Finally, we provide a web site that hosts BioModels Database models and a separate web site that hosts SBML Test Suite models. Conclusions Model composition tool (and the other three tools) can be used with little or no knowledge of the SBML document structure. For this reason, students or anyone who wants to learn about systems biology will benefit from the described functionalities. SBML Test Suite models will be a nice starting point for beginners. And, for more advanced purposes, users will able to access and employ models of the BioModels Database as well. PMID:24006914

Teleology and its constitutive role for biology as the science of organized systems in nature.

PubMed

Toepfer, Georg

2012-03-01

'Nothing in biology makes sense, except in the light of teleology'. This could be the first sentence in a textbook about the methodology of biology. The fundamental concepts in biology, e.g. 'organism' and 'ecosystem', are only intelligible given a teleological framework. Since early modern times, teleology has often been considered methodologically unscientific. With the acceptance of evolutionary theory, one popular strategy for accommodating teleological reasoning was to explain it by reference to selection in the past: functions were reconstructed as 'selected effects'. But the theory of evolution obviously presupposes the existence of organisms as organized and regulated, i.e. functional systems. Therefore, evolutionary theory cannot provide the foundation for teleology. The underlying reason for the central methodological role of teleology in biology is not its potential to offer particular forms of (evolutionary) explanations for the presence of parts, but rather an ontological one: organisms and other basic biological entities do not exist as physical bodies do, as amounts of matter with a definite form. Rather, they are dynamic systems in stable equilibrium; despite changes of their matter and form (in metabolism and metamorphosis) they maintain their identity. What remains constant in these kinds of systems is their 'organization', i.e. the causal pattern of interdependence of parts with certain effects of each part being relevant for the working of the system. Teleological analysis consists in the identification of these system-relevant effects and at the same time of the system as a whole. Therefore, the identity of biological systems cannot be specified without teleological reasoning. Copyright © 2011 Elsevier Ltd. All rights reserved.

From protein-protein interactions to protein co-expression networks: a new perspective to evaluate large-scale proteomic data.

PubMed

Vella, Danila; Zoppis, Italo; Mauri, Giancarlo; Mauri, Pierluigi; Di Silvestre, Dario

2017-12-01

The reductionist approach of dissecting biological systems into their constituents has been successful in the first stage of the molecular biology to elucidate the chemical basis of several biological processes. This knowledge helped biologists to understand the complexity of the biological systems evidencing that most biological functions do not arise from individual molecules; thus, realizing that the emergent properties of the biological systems cannot be explained or be predicted by investigating individual molecules without taking into consideration their relations. Thanks to the improvement of the current -omics technologies and the increasing understanding of the molecular relationships, even more studies are evaluating the biological systems through approaches based on graph theory. Genomic and proteomic data are often combined with protein-protein interaction (PPI) networks whose structure is routinely analyzed by algorithms and tools to characterize hubs/bottlenecks and topological, functional, and disease modules. On the other hand, co-expression networks represent a complementary procedure that give the opportunity to evaluate at system level including organisms that lack information on PPIs. Based on these premises, we introduce the reader to the PPI and to the co-expression networks, including aspects of reconstruction and analysis. In particular, the new idea to evaluate large-scale proteomic data by means of co-expression networks will be discussed presenting some examples of application. Their use to infer biological knowledge will be shown, and a special attention will be devoted to the topological and module analysis.

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

Yeast mitochondria: an overview of mitochondrial biology and the potential of mitochondrial systems biology.

PubMed

Malina, Carl; Larsson, Christer; Nielsen, Jens

2018-08-01

Mitochondria are dynamic organelles of endosymbiotic origin that are essential components of eukaryal cells. They contain their own genetic machinery, have multicopy genomes and like their bacterial ancestors they consist of two membranes. However, the majority of the ancestral genome has been lost or transferred to the nuclear genome of the host, preserving only a core set of genes involved in oxidative phosphorylation. Mitochondria perform numerous biological tasks ranging from bioenergetics to production of protein co-factors, including heme and iron-sulfur clusters. Due to the importance of mitochondria in many cellular processes, mitochondrial dysfunction is implicated in a wide variety of human disorders. Much of our current knowledge on mitochondrial function and dysfunction comes from studies using Saccharomyces cerevisiae. This yeast has good fermenting capacity, rendering tolerance to mutations that inactivate oxidative phosphorylation and complete loss of mitochondrial DNA. Here, we review yeast mitochondrial metabolism and function with focus on S. cerevisiae and its contribution in understanding mitochondrial biology. We further review how systems biology studies, including mathematical modeling, has allowed gaining new insight into mitochondrial function, and argue that this approach may enable us to gain a holistic view on how mitochondrial function interacts with different cellular processes.

Philosophical Basis and Some Historical Aspects of Systems Biology: From Hegel to Noble - Applications for Bioenergetic Research

PubMed Central

Saks, Valdur; Monge, Claire; Guzun, Rita

2009-01-01

We live in times of paradigmatic changes for the biological sciences. Reductionism, that for the last six decades has been the philosophical basis of biochemistry and molecular biology, is being displaced by Systems Biology, which favors the study of integrated systems. Historically, Systems Biology - defined as the higher level analysis of complex biological systems - was pioneered by Claude Bernard in physiology, Norbert Wiener with the development of cybernetics, and Erwin Schrödinger in his thermodynamic approach to the living. Systems Biology applies methods inspired by cybernetics, network analysis, and non-equilibrium dynamics of open systems. These developments follow very precisely the dialectical principles of development from thesis to antithesis to synthesis discovered by Hegel. Systems Biology opens new perspectives for studies of the integrated processes of energy metabolism in different cells. These integrated systems acquire new, system-level properties due to interaction of cellular components, such as metabolic compartmentation, channeling and functional coupling mechanisms, which are central for regulation of the energy fluxes. State of the art of these studies in the new area of Molecular System Bioenergetics is analyzed. PMID:19399243

Biological stress systems, adverse life events and the onset of chronic multisite musculoskeletal pain: a 6-year cohort study.

PubMed

Generaal, Ellen; Vogelzangs, Nicole; Macfarlane, Gary J; Geenen, Rinie; Smit, Johannes H; de Geus, Eco J C N; Penninx, Brenda W J H; Dekker, Joost

2016-05-01

Dysregulated biological stress systems and adverse life events, independently and in interaction, have been hypothesised to initiate chronic pain. We examine whether (1) function of biological stress systems, (2) adverse life events, and (3) their combination predict the onset of chronic multisite musculoskeletal pain. Subjects (n=2039) of the Netherlands Study of Depression and Anxiety, free from chronic multisite musculoskeletal pain at baseline, were identified using the Chronic Pain Grade Questionnaire and followed up for the onset of chronic multisite musculoskeletal pain over 6 years. Baseline assessment of biological stress systems comprised function of the hypothalamic-pituitary-adrenal axis (1-h cortisol awakening response, evening levels, postdexamethasone levels), the immune system (basal and lipopolysaccharide-stimulated inflammation) and the autonomic nervous system (heart rate, pre-ejection period, SD of the normal-to-normal interval, respiratory sinus arrhythmia). The number of recent adverse life events was assessed at baseline using the List of Threatening Events Questionnaire. Hypothalamic-pituitary-adrenal axis, immune system and autonomic nervous system functioning was not associated with onset of chronic multisite musculoskeletal pain, either by itself or in interaction with adverse life events. Adverse life events did predict onset of chronic multisite musculoskeletal pain (HR per event=1.14, 95% CI 1.04 to 1.24, p=0.005). This longitudinal study could not confirm that dysregulated biological stress systems increase the risk of developing chronic multisite musculoskeletal pain. Adverse life events were a risk factor for the onset of chronic multisite musculoskeletal pain, suggesting that psychosocial factors play a role in triggering the development of this condition. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

Understanding Biological Regulation Through Synthetic Biology.

PubMed

Bashor, Caleb J; Collins, James J

2018-05-20

Engineering synthetic gene regulatory circuits proceeds through iterative cycles of design, building, and testing. Initial circuit designs must rely on often-incomplete models of regulation established by fields of reductive inquiry-biochemistry and molecular and systems biology. As differences in designed and experimentally observed circuit behavior are inevitably encountered, investigated, and resolved, each turn of the engineering cycle can force a resynthesis in understanding of natural network function. Here, we outline research that uses the process of gene circuit engineering to advance biological discovery. Synthetic gene circuit engineering research has not only refined our understanding of cellular regulation but furnished biologists with a toolkit that can be directed at natural systems to exact precision manipulation of network structure. As we discuss, using circuit engineering to predictively reorganize, rewire, and reconstruct cellular regulation serves as the ultimate means of testing and understanding how cellular phenotype emerges from systems-level network function.

Bioinspired spring origami

NASA Astrophysics Data System (ADS)

Faber, Jakob A.; Arrieta, Andres F.; Studart, André R.

2018-03-01

Origami enables folding of objects into a variety of shapes in arts, engineering, and biological systems. In contrast to well-known paper-folded objects, the wing of the earwig has an exquisite natural folding system that cannot be sufficiently described by current origami models. Such an unusual biological system displays incompatible folding patterns, remains open by a bistable locking mechanism during flight, and self-folds rapidly without muscular actuation. We show that these notable functionalities arise from the protein-rich joints of the earwig wing, which work as extensional and rotational springs between facets. Inspired by this biological wing, we establish a spring origami model that broadens the folding design space of traditional origami and allows for the fabrication of precisely tunable, four-dimensional–printed objects with programmable bioinspired morphing functionalities.

Molecular biomimetics: utilizing nature's molecular ways in practical engineering.

PubMed

Tamerler, Candan; Sarikaya, Mehmet

2007-05-01

In nature, proteins are the machinery that accomplish many functions through their specific recognition and interactions in biological systems from single-celled to multicellular organisms. Biomolecule-material interaction is accomplished via molecular specificity, leading to the formation of controlled structures and functions at all scales of dimensional hierarchy. Through evolution, molecular recognition and, consequently, functions developed through successive cycles of mutation and selection. Using biology as a guide, we can now understand, engineer and control peptide-material interactions and exploit these to tailor novel materials and systems for practical applications. We adapted combinatorial biology protocols to display peptide libraries, either on the cell surface or on phages, to select short peptides specific to a variety of practical materials systems. Following the selection step, we determined the kinetics and stability of peptide binding experimentally to understand the bound peptide structure via modeling and its assembly via atomic force microscopy. The peptides were further engineered to have multiple repeats or their amino acid sequences varied to tailor their function. Both nanoparticles and flat inorganic substrates containing multimaterials patterned at the nano- and microscales were used for self-directed immobilization of molecular constructs. The molecular biomimetic approach opens up new avenues for the design and utilization of multifunctional molecular systems with wide ranging applications, from tissue engineering, drug delivery and biosensors, to nanotechnology and bioremediation. Here we give examples of protein-mediated functional materials in biology, peptide selection and engineering with affinity to inorganics, demonstrate potential utilizations in materials science, engineering and medicine, and describe future prospects.

Bioinspired Functional Surfaces for Technological Applications

NASA Astrophysics Data System (ADS)

Sharma, Vipul; Kumar, Suneel; Reddy, Kumbam Lingeshwar; Bahuguna, Ashish; Krishnan, Venkata

2016-08-01

Biological matters have been in continuous encounter with extreme environmental conditions leading to their evolution over millions of years. The fittest have survived through continuous evolution, an ongoing process. Biological surfaces are the important active interfaces between biological matters and the environment, and have been evolving over time to a higher state of intelligent functionality. Bioinspired surfaces with special functionalities have grabbed attention in materials research in the recent times. The microstructures and mechanisms behind these functional biological surfaces with interesting properties have inspired scientists to create artificial materials and surfaces which possess the properties equivalent to their counterparts. In this review, we have described the interplay between unique multiscale (micro- and nano-scale) structures of biological surfaces with intrinsic material properties which have inspired researchers to achieve the desired wettability and functionalities. Inspired by naturally occurring surfaces, researchers have designed and fabricated novel interfacial materials with versatile functionalities and wettability, such as superantiwetting surfaces (superhydrophobic and superoleophobic), omniphobic, switching wettability and water collecting surfaces. These strategies collectively enable functional surfaces to be utilized in different applications such as fog harvesting, surface-enhanced Raman spectroscopy (SERS), catalysis, sensing and biological applications. This paper delivers a critical review of such inspiring biological surfaces and artificial bioinspired surfaces utilized in different applications, where material science and engineering have merged by taking inspiration from the natural systems.

Holistic systems biology approaches to molecular mechanisms of human helper T cell differentiation to functionally distinct subsets.

PubMed

Chen, Z; Lönnberg, T; Lahesmaa, R

2013-08-01

Current knowledge of helper T cell differentiation largely relies on data generated from mouse studies. To develop therapeutical strategies combating human diseases, understanding the molecular mechanisms how human naïve T cells differentiate to functionally distinct T helper (Th) subsets as well as studies on human differentiated Th cell subsets is particularly valuable. Systems biology approaches provide a holistic view of the processes of T helper differentiation, enable discovery of new factors and pathways involved and generation of new hypotheses to be tested to improve our understanding of human Th cell differentiation and immune-mediated diseases. Here, we summarize studies where high-throughput systems biology approaches have been exploited to human primary T cells. These studies reveal new factors and signalling pathways influencing T cell differentiation towards distinct subsets, important for immune regulation. Such information provides new insights into T cell biology and into targeting immune system for therapeutic interventions. © 2013 John Wiley & Sons Ltd.

Reverse engineering and identification in systems biology: strategies, perspectives and challenges.

PubMed

Villaverde, Alejandro F; Banga, Julio R

2014-02-06

The interplay of mathematical modelling with experiments is one of the central elements in systems biology. The aim of reverse engineering is to infer, analyse and understand, through this interplay, the functional and regulatory mechanisms of biological systems. Reverse engineering is not exclusive of systems biology and has been studied in different areas, such as inverse problem theory, machine learning, nonlinear physics, (bio)chemical kinetics, control theory and optimization, among others. However, it seems that many of these areas have been relatively closed to outsiders. In this contribution, we aim to compare and highlight the different perspectives and contributions from these fields, with emphasis on two key questions: (i) why are reverse engineering problems so hard to solve, and (ii) what methods are available for the particular problems arising from systems biology?

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.

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.

Self-restoration as fundamental property of CES providing their sustainability

NASA Astrophysics Data System (ADS)

Gitelson, I. I.; Degermendzhy, A. G.; Rodicheva, E. K.

Sustainability is one of the most important criteria in the creation and evaluation of human life support systems intended for use during long space flights. The common feature of biological and physicochemical life support systems is that basically they are both catalytic. But there are two fundamental properties distinguishing biological systems: 1) they are auto-catalytic: their catalysts — enzymes of protein nature — are continuously reproduced when the system functions; 2) the program of every process performed by enzymes and the program of their reproduction are inherent in the biological system itself — in the totality of genomes of the species involved in the functioning of the ecosystem. Actually, one cell with the genome capable of the phenotypic realization is enough for the self-restoration of the function performed by the cells of this species in the ecosystem. The continuous microalgal culture of Chlorella vulgaris was taken to investigate quantitatively the process of self-restoration in unicellular algae population. Based on the data obtained, we proposed a mathematical model of the restoration process in a cell population that has suffered an acute radiation damage.

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.

Organism and artifact: Proper functions in Paley organisms.

PubMed

Holm, Sune

2013-12-01

In this paper I assess the explanatory powers of theories of function in the context of products that may result from synthetic biology. The aim is not to develop a new theory of functions, but to assess existing theories of function in relation to a new kind of biological and artifactual entity that might be produced in the not-too-distant future by means of synthetic biology. The paper thus investigates how to conceive of the functional nature of living systems that are not the result of evolution by natural selection, or instantly generated by cosmic coincidence, but which are products of intelligent design. The paper argues that the aetiological theory of proper functions in organisms and artifacts is inadequate as an account of proper functions in such 'Paley organisms' and defends an alternative organisational approach. The paper ends by considering the implications of the discussion of biological function for questions about the interests and moral status of non-sentient organisms. Copyright © 2013 Elsevier Ltd. All rights reserved.

Structure, Biology, and Therapeutic Application of Toxin-Antitoxin Systems in Pathogenic Bacteria.

PubMed

Lee, Ki-Young; Lee, Bong-Jin

2016-10-22

Bacterial toxin-antitoxin (TA) systems have received increasing attention for their diverse identities, structures, and functional implications in cell cycle arrest and survival against environmental stresses such as nutrient deficiency, antibiotic treatments, and immune system attacks. In this review, we describe the biological functions and the auto-regulatory mechanisms of six different types of TA systems, among which the type II TA system has been most extensively studied. The functions of type II toxins include mRNA/tRNA cleavage, gyrase/ribosome poison, and protein phosphorylation, which can be neutralized by their cognate antitoxins. We mainly explore the similar but divergent structures of type II TA proteins from 12 important pathogenic bacteria, including various aspects of protein-protein interactions. Accumulating knowledge about the structure-function correlation of TA systems from pathogenic bacteria has facilitated a novel strategy to develop antibiotic drugs that target specific pathogens. These molecules could increase the intrinsic activity of the toxin by artificially interfering with the intermolecular network of the TA systems.

Structure, Biology, and Therapeutic Application of Toxin–Antitoxin Systems in Pathogenic Bacteria

PubMed Central

Lee, Ki-Young; Lee, Bong-Jin

2016-01-01

Bacterial toxin–antitoxin (TA) systems have received increasing attention for their diverse identities, structures, and functional implications in cell cycle arrest and survival against environmental stresses such as nutrient deficiency, antibiotic treatments, and immune system attacks. In this review, we describe the biological functions and the auto-regulatory mechanisms of six different types of TA systems, among which the type II TA system has been most extensively studied. The functions of type II toxins include mRNA/tRNA cleavage, gyrase/ribosome poison, and protein phosphorylation, which can be neutralized by their cognate antitoxins. We mainly explore the similar but divergent structures of type II TA proteins from 12 important pathogenic bacteria, including various aspects of protein–protein interactions. Accumulating knowledge about the structure–function correlation of TA systems from pathogenic bacteria has facilitated a novel strategy to develop antibiotic drugs that target specific pathogens. These molecules could increase the intrinsic activity of the toxin by artificially interfering with the intermolecular network of the TA systems. PMID:27782085

Scaffolded biology.

PubMed

Minelli, Alessandro

2016-09-01

Descriptions and interpretations of the natural world are dominated by dichotomies such as organism vs. environment, nature vs. nurture, genetic vs. epigenetic, but in the last couple of decades strong dissatisfaction with those partitions has been repeatedly voiced and a number of alternative perspectives have been suggested, from perspectives such as Dawkins' extended phenotype, Turner's extended organism, Oyama's Developmental Systems Theory and Odling-Smee's niche construction theory. Last in time is the description of biological phenomena in terms of hybrids between an organism (scaffolded system) and a living or non-living scaffold, forming unit systems to study processes such as reproduction and development. As scaffold, eventually, we can define any resource used by the biological system, especially in development and reproduction, without incorporating it as happens in the case of resources fueling metabolism. Addressing biological systems as functionally scaffolded systems may help pointing to functional relationships that can impart temporal marking to the developmental process and thus explain its irreversibility; revisiting the boundary between development and metabolism and also regeneration phenomena, by suggesting a conceptual framework within which to investigate phenomena of regular hypermorphic regeneration such as characteristic of deer antlers; fixing a periodization of development in terms of the times at which a scaffolding relationship begins or is terminated; and promoting plant galls to legitimate study objects of developmental biology.

Metabolomics: Definitions and Significance in Systems Biology.

PubMed

Klassen, Aline; Faccio, Andréa Tedesco; Canuto, Gisele André Baptista; da Cruz, Pedro Luis Rocha; Ribeiro, Henrique Caracho; Tavares, Marina Franco Maggi; Sussulini, Alessandra

2017-01-01

Nowadays, there is a growing interest in deeply understanding biological mechanisms not only at the molecular level (biological components) but also the effects of an ongoing biological process in the organism as a whole (biological functionality), as established by the concept of systems biology. Within this context, metabolomics is one of the most powerful bioanalytical strategies that allow obtaining a picture of the metabolites of an organism in the course of a biological process, being considered as a phenotyping tool. Briefly, metabolomics approach consists in identifying and determining the set of metabolites (or specific metabolites) in biological samples (tissues, cells, fluids, or organisms) under normal conditions in comparison with altered states promoted by disease, drug treatment, dietary intervention, or environmental modulation. The aim of this chapter is to review the fundamentals and definitions used in the metabolomics field, as well as to emphasize its importance in systems biology and clinical studies.

Humidity-controlled preparation of frozen-hydrated biological samples for cryogenic coherent x-ray diffraction microscopy

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

Takayama, Yuki; Nakasako, Masayoshi; RIKEN Harima Institute/SPring-8, 1-1-1 Kouto, Mikaduki, Sayo, Hyogo 679-5148

2012-05-15

Coherent x-ray diffraction microscopy (CXDM) has the potential to visualize the structures of micro- to sub-micrometer-sized biological particles, such as cells and organelles, at high resolution. Toward advancing structural studies on the functional states of such particles, here, we developed a system for the preparation of frozen-hydrated biological samples for cryogenic CXDM experiments. The system, which comprised a moist air generator, microscope, micro-injector mounted on a micromanipulator, custom-made sample preparation chamber, and flash-cooling device, allowed for the manipulation of sample particles in the relative humidity range of 20%-94%rh at 293 K to maintain their hydrated and functional states. Here, wemore » report the details of the system and the operation procedure, including its application to the preparation of a frozen-hydrated chloroplast sample. Sample quality was evaluated through a cryogenic CXDM experiment conducted at BL29XUL of SPring-8. Taking the performance of the system and the quality of the sample, the system was suitable to prepare frozen-hydrated biological samples for cryogenic CXDM experiments.« less

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.

New tools for the analysis of glial cell biology in Drosophila.

PubMed

Awasaki, Takeshi; Lee, Tzumin

2011-09-01

Because of its genetic, molecular, and behavioral tractability, Drosophila has emerged as a powerful model system for studying molecular and cellular mechanisms underlying the development and function of nervous systems. The Drosophila nervous system has fewer neurons and exhibits a lower glia:neuron ratio than is seen in vertebrate nervous systems. Despite the simplicity of the Drosophila nervous system, glial organization in flies is as sophisticated as it is in vertebrates. Furthermore, fly glial cells play vital roles in neural development and behavior. In addition, powerful genetic tools are continuously being created to explore cell function in vivo. In taking advantage of these features, the fly nervous system serves as an excellent model system to study general aspects of glial cell development and function in vivo. In this article, we review and discuss advanced genetic tools that are potentially useful for understanding glial cell biology in Drosophila. Copyright © 2011 Wiley-Liss, Inc.

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.

Chemical genomics in plant biology.

PubMed

Sadhukhan, Ayan; Sahoo, Lingaraj; Panda, Sanjib Kumar

2012-06-01

Chemical genomics is a newly emerged and rapidly progressing field in biology, where small chemical molecules bind specifically and reversibly to protein(s) to modulate their function(s), leading to the delineation and subsequent unravelling of biological processes. This approach overcomes problems like lethality and redundancy of classical genetics. Armed with the powerful techniques of combinatorial synthesis, high-throughput screening and target discovery chemical genomics expands its scope to diverse areas in biology. The well-established genetic system of Arabidopsis model allows chemical genomics to enter into the realm of plant biology exploring signaling pathways of growth regulators, endomembrane signaling cascades, plant defense mechanisms and many more events.

Biological standards for the Knowledge-Based BioEconomy: What is at stake.

PubMed

de Lorenzo, Víctor; Schmidt, Markus

2018-01-25

The contribution of life sciences to the Knowledge-Based Bioeconomy (KBBE) asks for the transition of contemporary, gene-based biotechnology from being a trial-and-error endeavour to becoming an authentic branch of engineering. One requisite to this end is the need for standards to measure and represent accurately biological functions, along with languages for data description and exchange. However, the inherent complexity of biological systems and the lack of quantitative tradition in the field have largely curbed this enterprise. Fortunately, the onset of systems and synthetic biology has emphasized the need for standards not only to manage omics data, but also to increase reproducibility and provide the means of engineering living systems in earnest. Some domains of biotechnology can be easily standardized (e.g. physical composition of DNA sequences, tools for genome editing, languages to encode workflows), while others might be standardized with some dedicated research (e.g. biological metrology, operative systems for bio-programming cells) and finally others will require a considerable effort, e.g. defining the rules that allow functional composition of biological activities. Despite difficulties, these are worthy attempts, as the history of technology shows that those who set/adopt standards gain a competitive advantage over those who do not. Copyright © 2017 Elsevier B.V. All rights reserved.

Tracing organizing principles: learning from the history of systems biology.

PubMed

Green, Sara; Wolkenhauer, Olaf

2013-01-01

With the emergence of systems biology, the identification of organizing principles is being highlighted as a key research aim. Researchers attempt to "reverse engineer" the functional organization of biological systems using methodologies from mathematics, engineering and computer science while taking advantage of data produced by new experimental techniques. While systems biology is a relatively new approach, the quest for general principles of biological organization dates back to systems theoretic approaches in early and mid-twentieth century. The aim of this paper is to draw on this historical background in order to increase the understanding of the motivation behind the search for general principles and to clarify different epistemic aims within systems biology. We pinpoint key aspects of earlier approaches that also underlie the current practice. These are i) the focus on relational and system-level properties, ii) the inherent critique of reductionism and fragmentation of knowledge resulting from overspecialization, and iii) the insight that the ideal of formulating abstract organizing principles is complementary to, rather than conflicting with, the aim of formulating detailed explanations of biological mechanisms. We argue that looking back not only helps us understand the current practice but also points to possible future directions for systems biology.

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.

[Topical issues of biological safety under current conditions. Part 3. Scientific provision for the national regulation of the biological safety framework in its broad interpretation].

PubMed

Onishchenko, G G; Smolensky, V Yu; Ezhlova, E B; Demina, Yu V; Toporkov, V P; Toporkov, A V; Lyapin, M N; Kutyrev, V V

2014-01-01

Consequent of investigation concerned with biological safety (BS) framework development in its broad interpretation, reflected in the Russian Federation State Acts, identified have been conceptual entity parameters of the up-to-date broad interpretation of BS, which have formed a part of the developed by the authors system for surveillance (prophylaxis, localization, indication, identification, and diagnostics) and control (prophylaxis, localization, and response/elimination) over the emergency situations of biological (sanitary-epidemiological) character. The System functionality is activated through supplying the content with information data which are concerned with monitoring and control of specific internal and external threats in the sphere of BS provision fixed in the Supplement 2 of the International Health Regulations (IHR, 2005), and with the previously characterized nomenclature of hazardous biological factors. The system is designed as a network-based research-and-practice tool for evaluation of the situation in the sphere of BS provision, as well as assessment of efficacy of management decision making as regards BS control and proper State policy implementation. Most of the system elements either directly or indirectly relate to the scope of activities conducted by Federal Service for Surveillance in the Sphere of Consumers Rights Protection and Human Welfare, being substantial argument for allocating coordination functions in the sphere of BS provision to this government agency and consistent with its function as the State Coordinator on IHR (2005). The data collected serve as materials to Draft Federal Law "Concerning biological safety provision of the population".

Biological properties of extracellular vesicles and their physiological functions

PubMed Central

Yáñez-Mó, María; Siljander, Pia R.-M.; Andreu, Zoraida; Zavec, Apolonija Bedina; Borràs, Francesc E.; Buzas, Edit I.; Buzas, Krisztina; Casal, Enriqueta; Cappello, Francesco; Carvalho, Joana; Colás, Eva; Silva, Anabela Cordeiro-da; Fais, Stefano; Falcon-Perez, Juan M.; Ghobrial, Irene M.; Giebel, Bernd; Gimona, Mario; Graner, Michael; Gursel, Ihsan; Gursel, Mayda; Heegaard, Niels H. H.; Hendrix, An; Kierulf, Peter; Kokubun, Katsutoshi; Kosanovic, Maja; Kralj-Iglic, Veronika; Krämer-Albers, Eva-Maria; Laitinen, Saara; Lässer, Cecilia; Lener, Thomas; Ligeti, Erzsébet; Linē, Aija; Lipps, Georg; Llorente, Alicia; Lötvall, Jan; Manček-Keber, Mateja; Marcilla, Antonio; Mittelbrunn, Maria; Nazarenko, Irina; Hoen, Esther N.M. Nolte-‘t; Nyman, Tuula A.; O'Driscoll, Lorraine; Olivan, Mireia; Oliveira, Carla; Pállinger, Éva; del Portillo, Hernando A.; Reventós, Jaume; Rigau, Marina; Rohde, Eva; Sammar, Marei; Sánchez-Madrid, Francisco; Santarém, N.; Schallmoser, Katharina; Ostenfeld, Marie Stampe; Stoorvogel, Willem; Stukelj, Roman; Van der Grein, Susanne G.; Vasconcelos, M. Helena; Wauben, Marca H. M.; De Wever, Olivier

2015-01-01

In the past decade, extracellular vesicles (EVs) have been recognized as potent vehicles of intercellular communication, both in prokaryotes and eukaryotes. This is due to their capacity to transfer proteins, lipids and nucleic acids, thereby influencing various physiological and pathological functions of both recipient and parent cells. While intensive investigation has targeted the role of EVs in different pathological processes, for example, in cancer and autoimmune diseases, the EV-mediated maintenance of homeostasis and the regulation of physiological functions have remained less explored. Here, we provide a comprehensive overview of the current understanding of the physiological roles of EVs, which has been written by crowd-sourcing, drawing on the unique EV expertise of academia-based scientists, clinicians and industry based in 27 European countries, the United States and Australia. This review is intended to be of relevance to both researchers already working on EV biology and to newcomers who will encounter this universal cell biological system. Therefore, here we address the molecular contents and functions of EVs in various tissues and body fluids from cell systems to organs. We also review the physiological mechanisms of EVs in bacteria, lower eukaryotes and plants to highlight the functional uniformity of this emerging communication system. PMID:25979354

Biological properties of extracellular vesicles and their physiological functions.

PubMed

Yáñez-Mó, María; Siljander, Pia R-M; Andreu, Zoraida; Zavec, Apolonija Bedina; Borràs, Francesc E; Buzas, Edit I; Buzas, Krisztina; Casal, Enriqueta; Cappello, Francesco; Carvalho, Joana; Colás, Eva; Cordeiro-da Silva, Anabela; Fais, Stefano; Falcon-Perez, Juan M; Ghobrial, Irene M; Giebel, Bernd; Gimona, Mario; Graner, Michael; Gursel, Ihsan; Gursel, Mayda; Heegaard, Niels H H; Hendrix, An; Kierulf, Peter; Kokubun, Katsutoshi; Kosanovic, Maja; Kralj-Iglic, Veronika; Krämer-Albers, Eva-Maria; Laitinen, Saara; Lässer, Cecilia; Lener, Thomas; Ligeti, Erzsébet; Linē, Aija; Lipps, Georg; Llorente, Alicia; Lötvall, Jan; Manček-Keber, Mateja; Marcilla, Antonio; Mittelbrunn, Maria; Nazarenko, Irina; Nolte-'t Hoen, Esther N M; Nyman, Tuula A; O'Driscoll, Lorraine; Olivan, Mireia; Oliveira, Carla; Pállinger, Éva; Del Portillo, Hernando A; Reventós, Jaume; Rigau, Marina; Rohde, Eva; Sammar, Marei; Sánchez-Madrid, Francisco; Santarém, N; Schallmoser, Katharina; Ostenfeld, Marie Stampe; Stoorvogel, Willem; Stukelj, Roman; Van der Grein, Susanne G; Vasconcelos, M Helena; Wauben, Marca H M; De Wever, Olivier

2015-01-01

In the past decade, extracellular vesicles (EVs) have been recognized as potent vehicles of intercellular communication, both in prokaryotes and eukaryotes. This is due to their capacity to transfer proteins, lipids and nucleic acids, thereby influencing various physiological and pathological functions of both recipient and parent cells. While intensive investigation has targeted the role of EVs in different pathological processes, for example, in cancer and autoimmune diseases, the EV-mediated maintenance of homeostasis and the regulation of physiological functions have remained less explored. Here, we provide a comprehensive overview of the current understanding of the physiological roles of EVs, which has been written by crowd-sourcing, drawing on the unique EV expertise of academia-based scientists, clinicians and industry based in 27 European countries, the United States and Australia. This review is intended to be of relevance to both researchers already working on EV biology and to newcomers who will encounter this universal cell biological system. Therefore, here we address the molecular contents and functions of EVs in various tissues and body fluids from cell systems to organs. We also review the physiological mechanisms of EVs in bacteria, lower eukaryotes and plants to highlight the functional uniformity of this emerging communication system.

The Biology of Behaviour.

ERIC Educational Resources Information Center

Broom, D. M.

1981-01-01

Discusses topics to aid in understanding animal behavior, including the value of the biological approach to psychology, functional systems, optimality and fitness, universality of environmental effects on behavior, and evolution of social behavior. (DS)

The biological correction is the new way of preservation of the Face of the Earth

NASA Astrophysics Data System (ADS)

Popov, Alexander

2014-05-01

The major links of terrestrial ecosystems functioning are: composted organic material with mull humus type, nitrogen-fixing microorganisms and litholytic organisms, which capable of active biological weathering of minerals and/or rock in the soil. Now the main ways of influence on plant-soil system functioning are physical and chemical correction. Physical correction is the system of different soil cultivation and land reclamation. It directed on creation and maintenance of favorable water, thermal and air regimes and also the biological activity of soils for crops. Although the general tendency of agriculture is minimized of tillage (strip-till, mini-till and no-till), nevertheless the intensive cultivation is widely used in modern agriculture. Chemical correction is the agriculture chemicalixation. It directed on regulation of plant producing by replenishment of plant, mineral nutrition elements in soils, by foliar nutrition using water solutions of macro- and microelements, and by regulation of acidic and salt soil regimes. In this case the plant protection against the pests and infections is carried out by various pesticides. This way of correction is completely realized in agriculture, but it doesn't consider the natural laws due to plants together with the soil from the interconnected and interdependent system. The continuing increase of agriculture chemicalixation simultaneously with a repeated tillage is led to loss of the major links of plant-soil systems functioning and to the degradation of a soil cover. Such way of plant productivity is a deadlock. New evolutionary way of preservation of the Face of the Earth is biological correction of plant-soil system functioning. A gist of this correction is the replenishment of the lost plant-soil system links. Biological correction leans on scientific achievements of modern biotechnologies, such as: vermicomposting, microbiologic specimens, physiologically active substances, biological agents of plant protection, etc. Methods of biological correction are exact biological analogs of natural links and so they can't cause the negative phenomena of plant growth and development. The principle of biological interrelationship is the base of these methods. At the heart of these methods the principle of biological compliance lies. Herewith, physiological features of plants are considered necessary. There are following main biological correction methods of plant productivity: (i) biological amelioration of soils (using of vermicomposts, earthworms, microbiologic specimens, organic and green manure, etc.); (ii) infection of plants by cultures of living microorganisms (for plant nutrition and protection); (iii) inputting of biological insecticides into plants (allows to fight even against larvae of mining insects successfully); (iv) influence on a plant metabolism by physiologically active substances (such as solutions of humic substances in particular); (v) creation of multilayered mats for gardening of deserts. The field experiments in working conditions, which were carried out in different climatic zones, bear evidence of efficiency of biological correction methods. In our opinion biological correction methods are capable to support and/or restore land-cover, to stop a degradation, and by that to prevent a disfigurement of the Face of the Earth.

Reverse engineering and identification in systems biology: strategies, perspectives and challenges

PubMed Central

Villaverde, Alejandro F.; Banga, Julio R.

2014-01-01

The interplay of mathematical modelling with experiments is one of the central elements in systems biology. The aim of reverse engineering is to infer, analyse and understand, through this interplay, the functional and regulatory mechanisms of biological systems. Reverse engineering is not exclusive of systems biology and has been studied in different areas, such as inverse problem theory, machine learning, nonlinear physics, (bio)chemical kinetics, control theory and optimization, among others. However, it seems that many of these areas have been relatively closed to outsiders. In this contribution, we aim to compare and highlight the different perspectives and contributions from these fields, with emphasis on two key questions: (i) why are reverse engineering problems so hard to solve, and (ii) what methods are available for the particular problems arising from systems biology? PMID:24307566

Biomimicry, Biofabrication, and Biohybrid Systems: The Emergence and Evolution of Biological Design.

PubMed

Raman, Ritu; Bashir, Rashid

2017-10-01

The discipline of biological design has a relatively short history, but has undergone very rapid expansion and development over that time. This Progress Report outlines the evolution of this field from biomimicry to biofabrication to biohybrid systems' design, showcasing how each subfield incorporates bioinspired dynamic adaptation into engineered systems. Ethical implications of biological design are discussed, with an emphasis on establishing responsible practices for engineering non-natural or hypernatural functional behaviors in biohybrid systems. This report concludes with recommendations for implementing biological design into educational curricula, ensuring effective and responsible practices for the next generation of engineers and scientists. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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.

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.

Pharmacological Properties of Melanin and its Function in Health.

PubMed

ElObeid, Adila Salih; Kamal-Eldin, Afaf; Abdelhalim, Mohamed Anwar K; Haseeb, Adil M

2017-06-01

The biological pigment melanin is present in most of the biological systems. It manifests a host of biological and pharmacological properties. Its role as a molecule with special properties and functions affecting general health, including photoprotective and immunological action, are well recognized. Its antioxidant, anti-inflammatory, immunomodulatory, radioprotective, hepatic, gastrointestinal and hypoglycaemic benefits have only recently been recognized and studied. It is also associated with certain disorders of the nervous system. In this MiniReview, we consider the steadily increasing literature on the bioavailability and functional activity of melanin. Published literature shows that melanin may play a number of possible pharmacological effects such as protective, stimulatory, diagnostic and curative roles in human health. In this MiniReview, possible health roles and pharmacological effects are considered. © 2016 Nordic Association for the Publication of BCPT (former Nordic Pharmacological Society).

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

Emerging biomedical applications of synthetic biology.

PubMed

Weber, Wilfried; Fussenegger, Martin

2011-11-29

Synthetic biology aims to create functional devices, systems and organisms with novel and useful functions on the basis of catalogued and standardized biological building blocks. Although they were initially constructed to elucidate the dynamics of simple processes, designed devices now contribute to the understanding of disease mechanisms, provide novel diagnostic tools, enable economic production of therapeutics and allow the design of novel strategies for the treatment of cancer, immune diseases and metabolic disorders, such as diabetes and gout, as well as a range of infectious diseases. In this Review, we cover the impact and potential of synthetic biology for biomedical applications.

Oligodendroglia: metabolic supporters of axons.

PubMed

Morrison, Brett M; Lee, Youngjin; Rothstein, Jeffrey D

2013-12-01

Axons are specialized extensions of neurons that are critical for the organization of the nervous system. To maintain function in axons that often extend some distance from the cell body, specialized mechanisms of energy delivery are likely to be necessary. Over the past decade, greater understanding of human demyelinating diseases and the development of animal models have suggested that oligodendroglia are critical for maintaining the function of axons. In this review, we discuss evidence for the vulnerability of neurons to energy deprivation, the importance of oligodendrocytes for axon function and survival, and recent data suggesting that transfer of energy metabolites from oligodendroglia to axons through monocarboxylate transporter 1 (MCT1) may be critical for the survival of axons. This pathway has important implications both for the basic biology of the nervous system and for human neurological disease. New insights into the role of oligodendroglial biology provide an exciting opportunity for revisions in nervous system biology, understanding myelin-based disorders, and therapeutics development. Copyright © 2013 Elsevier Ltd. All rights reserved.

The evolvability of programmable hardware.

PubMed

Raman, Karthik; Wagner, Andreas

2011-02-06

In biological systems, individual phenotypes are typically adopted by multiple genotypes. Examples include protein structure phenotypes, where each structure can be adopted by a myriad individual amino acid sequence genotypes. These genotypes form vast connected 'neutral networks' in genotype space. The size of such neutral networks endows biological systems not only with robustness to genetic change, but also with the ability to evolve a vast number of novel phenotypes that occur near any one neutral network. Whether technological systems can be designed to have similar properties is poorly understood. Here we ask this question for a class of programmable electronic circuits that compute digital logic functions. The functional flexibility of such circuits is important in many applications, including applications of evolutionary principles to circuit design. The functions they compute are at the heart of all digital computation. We explore a vast space of 10(45) logic circuits ('genotypes') and 10(19) logic functions ('phenotypes'). We demonstrate that circuits that compute the same logic function are connected in large neutral networks that span circuit space. Their robustness or fault-tolerance varies very widely. The vicinity of each neutral network contains circuits with a broad range of novel functions. Two circuits computing different functions can usually be converted into one another via few changes in their architecture. These observations show that properties important for the evolvability of biological systems exist in a commercially important class of electronic circuitry. They also point to generic ways to generate fault-tolerant, adaptable and evolvable electronic circuitry.

The evolvability of programmable hardware

PubMed Central

Raman, Karthik; Wagner, Andreas

2011-01-01

In biological systems, individual phenotypes are typically adopted by multiple genotypes. Examples include protein structure phenotypes, where each structure can be adopted by a myriad individual amino acid sequence genotypes. These genotypes form vast connected ‘neutral networks’ in genotype space. The size of such neutral networks endows biological systems not only with robustness to genetic change, but also with the ability to evolve a vast number of novel phenotypes that occur near any one neutral network. Whether technological systems can be designed to have similar properties is poorly understood. Here we ask this question for a class of programmable electronic circuits that compute digital logic functions. The functional flexibility of such circuits is important in many applications, including applications of evolutionary principles to circuit design. The functions they compute are at the heart of all digital computation. We explore a vast space of 1045 logic circuits (‘genotypes’) and 1019 logic functions (‘phenotypes’). We demonstrate that circuits that compute the same logic function are connected in large neutral networks that span circuit space. Their robustness or fault-tolerance varies very widely. The vicinity of each neutral network contains circuits with a broad range of novel functions. Two circuits computing different functions can usually be converted into one another via few changes in their architecture. These observations show that properties important for the evolvability of biological systems exist in a commercially important class of electronic circuitry. They also point to generic ways to generate fault-tolerant, adaptable and evolvable electronic circuitry. PMID:20534598

Can Simple Biophysical Principles Yield Complicated Biological Functions?

NASA Astrophysics Data System (ADS)

Liphardt, Jan

2011-03-01

About once a year, a new regulatory paradigm is discovered in cell biology. As of last count, eukaryotic cells have more than 40 distinct ways of regulating protein concentration and function. Regulatory possibilities include site-specific phosphorylation, epigenetics, alternative splicing, mRNA (re)localization, and modulation of nucleo-cytoplasmic transport. This raises a simple question. Do all the remarkable things cells do, require an intricately choreographed supporting cast of hundreds of molecular machines and associated signaling networks? Alternatively, are there a few simple biophysical principles that can generate apparently very complicated cellular behaviors and functions? I'll discuss two problems, spatial organization of the bacterial chemotaxis system and nucleo-cytoplasmic transport, where the latter might be true. In both cases, the ability to precisely quantify biological organization and function, at the single-molecule level, helped to find signatures of basic biological organizing principles.

Future Science Teachers' Understandings of Diffusion and Osmosis Concepts

ERIC Educational Resources Information Center

Tomazic, Iztok; Vidic, Tatjana

2012-01-01

The concepts of diffusion and osmosis cross the disciplinary boundaries of physics, chemistry and biology. They are important for understanding how biological systems function. Since future (pre-service) science teachers in Slovenia encounter both concepts at physics, chemistry and biology courses during their studies, we assessed the first-,…

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.

Tiling solutions for optimal biological sensing

NASA Astrophysics Data System (ADS)

Walczak, Aleksandra M.

2015-10-01

Biological systems, from cells to organisms, must respond to the ever-changing environment in order to survive and function. This is not a simple task given the often random nature of the signals they receive, as well as the intrinsically stochastic, many-body and often self-organized nature of the processes that control their sensing and response and limited resources. Despite a wide range of scales and functions that can be observed in the living world, some common principles that govern the behavior of biological systems emerge. Here I review two examples of very different biological problems: information transmission in gene regulatory networks and diversity of adaptive immune receptor repertoires that protect us from pathogens. I discuss the trade-offs that physical laws impose on these systems and show that the optimal designs of both immune repertoires and gene regulatory networks display similar discrete tiling structures. These solutions rely on locally non-overlapping placements of the responding elements (genes and receptors) that, overall, cover space nearly uniformly.

Positive affect and psychobiological processes

PubMed Central

Dockray, Samantha; Steptoe, Andrew

2010-01-01

Positive affect has been associated with favourable health outcomes, and it is likely that several biological processes mediate the effects of positive mood on physical health. There is converging evidence that positive affect activates the neuroendocrine, autonomic and immune systems in distinct and functionally meaningful ways. Cortisol, both total output and the awakening response, has consistently been shown to be lower among individuals with higher levels of positive affect. The beneficial effects of positive mood on cardiovascular function, including heart rate and blood pressure, and the immune system have also been described. The influence of positive affect on these psychobiological processes are independent of negative affect, suggesting that positive affect may have characteristic biological correlates. The duration and conceptualisation of positive affect may be important considerations in understanding how different biological systems are activated in association with positive affect. The association of positive affect and psychobiological processes has been established, and these biological correlates may be partly responsible for the protective effects of positive affect on health outcomes. PMID:20097225

Physiological Aging and Exercise.

ERIC Educational Resources Information Center

Osness, Wayne

This paper explores the nature of the aging process by providing an overview of the available evidence relating to the body systems that are most critical to biological function. Each system is treated separately to more clearly describe various aspects of the aging process and then integrated in a discussion of the theories of biological aging.…

A Graphical Systems Model and Tissue-specific Functional Gene Sets to Aid Transcriptomic Analysis of Chemical Impacts on the Female Teleost Reproductive Axis

EPA Science Inventory

Oligonucleotide microarrays and other ‘omics’ approaches are powerful tools for unsupervised analysis of chemical impacts on biological systems. However, the lack of well annotated biological pathways for many aquatic organisms, including fish, and the poor power of microarray-b...

Synthetic biology: tools to design microbes for the production of chemicals and fuels.

PubMed

Seo, Sang Woo; Yang, Jina; Min, Byung Eun; Jang, Sungho; Lim, Jae Hyung; Lim, Hyun Gyu; Kim, Seong Cheol; Kim, Se Yeon; Jeong, Jun Hong; Jung, Gyoo Yeol

2013-11-01

The engineering of biological systems to achieve specific purposes requires design tools that function in a predictable and quantitative manner. Recent advances in the field of synthetic biology, particularly in the programmable control of gene expression at multiple levels of regulation, have increased our ability to efficiently design and optimize biological systems to perform designed tasks. Furthermore, implementation of these designs in biological systems highlights the potential of using these tools to build microbial cell factories for the production of chemicals and fuels. In this paper, we review current developments in the design of tools for controlling gene expression at transcriptional, post-transcriptional and post-translational levels, and consider potential applications of these tools. Copyright © 2013 Elsevier Inc. All rights reserved.

A Unifying Theory of Biological Function.

PubMed

van Hateren, J H

2017-01-01

A new theory that naturalizes biological function is explained and compared with earlier etiological and causal role theories. Etiological (or selected effects) theories explain functions from how they are caused over their evolutionary history. Causal role theories analyze how functional mechanisms serve the current capacities of their containing system. The new proposal unifies the key notions of both kinds of theories, but goes beyond them by explaining how functions in an organism can exist as factors with autonomous causal efficacy. The goal-directedness and normativity of functions exist in this strict sense as well. The theory depends on an internal physiological or neural process that mimics an organism's fitness, and modulates the organism's variability accordingly. The structure of the internal process can be subdivided into subprocesses that monitor specific functions in an organism. The theory matches well with each intuition on a previously published list of intuited ideas about biological functions, including intuitions that have posed difficulties for other theories.

In silico experiment system for testing hypothesis on gene functions using three condition specific biological networks.

PubMed

Lee, Chai-Jin; Kang, Dongwon; Lee, Sangseon; Lee, Sunwon; Kang, Jaewoo; Kim, Sun

2018-05-25

Determining functions of a gene requires time consuming, expensive biological experiments. Scientists can speed up this experimental process if the literature information and biological networks can be adequately provided. In this paper, we present a web-based information system that can perform in silico experiments of computationally testing hypothesis on the function of a gene. A hypothesis that is specified in English by the user is converted to genes using a literature and knowledge mining system called BEST. Condition-specific TF, miRNA and PPI (protein-protein interaction) networks are automatically generated by projecting gene and miRNA expression data to template networks. Then, an in silico experiment is to test how well the target genes are connected from the knockout gene through the condition-specific networks. The test result visualizes path from the knockout gene to the target genes in the three networks. Statistical and information-theoretic scores are provided on the resulting web page to help scientists either accept or reject the hypothesis being tested. Our web-based system was extensively tested using three data sets, such as E2f1, Lrrk2, and Dicer1 knockout data sets. We were able to re-produce gene functions reported in the original research papers. In addition, we comprehensively tested with all disease names in MalaCards as hypothesis to show the effectiveness of our system. Our in silico experiment system can be very useful in suggesting biological mechanisms which can be further tested in vivo or in vitro. http://biohealth.snu.ac.kr/software/insilico/. Copyright © 2018 Elsevier Inc. All rights reserved.

Endocrine Disruptors (Chapter 14) in Mammalian Toxicology Book

EPA Science Inventory

Endocrine disrupting chemicals (EDCs) are exogenous substances that alter endocrine system function(s) and consequently cause adverse health effects in intact organisms or its progeny. The endocrine system is important for a wide range of biological processes, from normal cell si...

Characteristics of microbial community functional structure of a biological coking wastewater treatment system.

PubMed

Joshi, Dev Raj; Zhang, Yu; Zhang, Hong; Gao, Yingxin; Yang, Min

2018-01-01

Nitrogenous heterocyclic compounds are key pollutants in coking wastewater; however, the functional potential of microbial communities for biodegradation of such contaminants during biological treatment is still elusive. Herein, a high throughput functional gene array (GeoChip 5.0) in combination with Illumina HiSeq2500 sequencing was used to compare and characterize the microbial community functional structure in a long run (500days) bench scale bioreactor treating coking wastewater, with a control system treating synthetic wastewater. Despite the inhibitory toxic pollutants, GeoChip 5.0 detected almost all key functional gene (average 61,940 genes) categories in the coking wastewater sludge. With higher abundance, aromatic ring cleavage dioxygenase genes including multi ring1,2diox; one ring2,3diox; catechol represented significant functional potential for degradation of aromatic pollutants which was further confirmed by Illumina HiSeq2500 analysis results. Response ratio analysis revealed that three nitrogenous compound degrading genes- nbzA (nitro-aromatics), tdnB (aniline), and scnABC (thiocyanate) were unique for coking wastewater treatment, which might be strong cause to increase ammonia level during the aerobic process. Additionally, HiSeq2500 elucidated carbozole and isoquinoline degradation genes in the system. These findings expanded our understanding on functional potential of microbial communities to remove organic nitrogenous pollutants; hence it will be useful in optimization strategies for biological treatment of coking wastewater. Copyright © 2017. Published by Elsevier B.V.

Systems Biology in Immunology – A Computational Modeling Perspective

PubMed Central

Germain, Ronald N.; Meier-Schellersheim, Martin; Nita-Lazar, Aleksandra; Fraser, Iain D. C.

2011-01-01

Systems biology is an emerging discipline that combines high-content, multiplexed measurements with informatic and computational modeling methods to better understand biological function at various scales. Here we present a detailed review of the methods used to create computational models and conduct simulations of immune function, We provide descriptions of the key data gathering techniques employed to generate the quantitative and qualitative data required for such modeling and simulation and summarize the progress to date in applying these tools and techniques to questions of immunological interest, including infectious disease. We include comments on what insights modeling can provide that complement information obtained from the more familiar experimental discovery methods used by most investigators and why quantitative methods are needed to eventually produce a better understanding of immune system operation in health and disease. PMID:21219182

[Biological characteristics of an enteroinvasive Escherichia coli strain with tatABC deletion].

PubMed

Gong, Zhaolong; Ye, Changyun; Liu, Xiaobing; Zhang, Min; Zhuo, Qin

2013-05-04

To study the relationship between twin-arginine translocation system (Tat) system with the biological characteristics of enteroinvasive Escherichia coli (EIEC). Through homologous recombination, we constructed EIEC's tatABC gene deletion strain and complementary strain, and explored their impact on bacterial form, substrate transport function as well as on HeLa cells and guinea pig's corneal invasion force. The tatABC gene deletion strain had apparent changes in bacterial form, loss of substrate transporter function, and significant weakened bacterial invasion force (the number of the deletion strain invading into HeLa cells was decreased significantly, and the ability of its corneal lesion capacity of the guinea pig was significantly weakened), while the complementary strain was similar to the wild strain in the above respects. EIEC's Tat protein transport system is closely related with the biological characteristics of EIEC.

Biological Mechanisms Underlying the Relationship between Stress and Smoking: State of the Science and Directions for Future Work

PubMed Central

Richards, Jessica; Stipelman, Brooke A.; Bornovalova, Marina A.; Daughters, Stacey; Sinha, Rajita; Lejuez, C.W.

2011-01-01

Theories of addiction implicate stress as a crucial mechanism underlying initiation, maintenance, and relapse to cigarette smoking. Examinations of the biological stress systems, including functioning of the hypothalamic-pituitary-adrenal (HPA) axis and the autonomic nervous system (ANS), have provided additional insights into the relationship between stress and smoking. To date, convergent data suggests that chronic cigarette smoking is associated with alterations in HPA and ANS functioning; however, less is known about the role of HPA and ANS functioning in smoking initiation and relapse following cessation. In order to organize existing findings and stimulate future research, the current paper summarizes the available literature on the roles of HPA axis and ANS functioning in the relationship between stress and cigarette smoking, highlights limitations within the existing literature, and suggests directions for future research to address unanswered questions in the extant literature on the biological mechanisms underlying the relationship between stress and smoking. PMID:21741435

Cell-based composite materials with programmed structures and functions

DOEpatents

None

2016-03-01

The present invention is directed to the use of silicic acid to transform biological materials, including cellular architecture into inorganic materials to provide biocomposites (nanomaterials) with stabilized structure and function. In the present invention, there has been discovered a means to stabilize the structure and function of biological materials, including cells, biomolecules, peptides, proteins (especially including enzymes), lipids, lipid vesicles, polysaccharides, cytoskeletal filaments, tissue and organs with silicic acid such that these materials may be used as biocomposites. In many instances, these materials retain their original biological activity and may be used in harsh conditions which would otherwise destroy the integrity of the biological material. In certain instances, these biomaterials may be storage stable for long periods of time and reconstituted after storage to return the biological material back to its original form. In addition, by exposing an entire cell to form CSCs, the CSCs may function to provide a unique system to study enzymes or a cascade of enzymes which are otherwise unavailable.

Cell-based composite materials with programmed structures and functions

DOEpatents

Kaehr, Bryan J.; Brinker, C. Jeffrey; Townson, Jason L.

2018-05-15

The present invention is directed to the use of silicic acid to transform biological materials, including cellular architecture into inorganic materials to provide biocomposites (nanomaterials) with stabilized structure and function. In the present invention, there has been discovered a means to stabilize the structure and function of biological materials, including cells, biomolecules, peptides, proteins (especially including enzymes), lipids, lipid vesicles, polysaccharides, cytoskeletal filaments, tissue and organs with silicic acid such that these materials may be used as biocomposites. In many instances, these materials retain their original biological activity and may be used in harsh conditions which would otherwise destroy the integrity of the biological material. In certain instances, these biomaterials may be storage stable for long periods of time and reconstituted after storage to return the biological material back to its original form. In addition, by exposing an entire cell to form CSCs, the CSCs may function to provide a unique system to study enzymes or a cascade of enzymes which are otherwise unavailable.

Materials learning from life: concepts for active, adaptive and autonomous molecular systems.

PubMed

Merindol, Rémi; Walther, Andreas

2017-09-18

Bioinspired out-of-equilibrium systems will set the scene for the next generation of molecular materials with active, adaptive, autonomous, emergent and intelligent behavior. Indeed life provides the best demonstrations of complex and functional out-of-equilibrium systems: cells keep track of time, communicate, move, adapt, evolve and replicate continuously. Stirred by the understanding of biological principles, artificial out-of-equilibrium systems are emerging in many fields of soft matter science. Here we put in perspective the molecular mechanisms driving biological functions with the ones driving synthetic molecular systems. Focusing on principles that enable new levels of functionalities (temporal control, autonomous structures, motion and work generation, information processing) rather than on specific material classes, we outline key cross-disciplinary concepts that emerge in this challenging field. Ultimately, the goal is to inspire and support new generations of autonomous and adaptive molecular devices fueled by self-regulating chemistry.

[The characteristics of the geroprotective action of magnetotherapy in elderly patients with combined cardiovascular pathology].

PubMed

Abramovich, S G; Fedotchenko, A A; Koriakina, A V; Pogodin, K V; Smirnov, S N

1999-01-01

Central hemodynamics, diastolic and pumping functions of the heart, myocardial reactivity, microcirculation and biological age of cardiovascular system were studied in 66 elderly patients suffering from hypertension and ischemic heart disease. The patients received systemic magnetotherapy which produced a geroprotective effect as shown by improved microcirculation, myocardial reactivity, central hemodynamics reducing biological age of cardiovascular system and inhibiting its ageing.

Biology Notes.

ERIC Educational Resources Information Center

School Science Review, 1980

1980-01-01

Describes equipment, activities, and experiments useful in biology and environmental education instruction, including, among others, sampling in ecology using an overhead projector, the slide finder as an aid to microscopy, teaching kidney function, and teaching wildlife conservation-sand dune systems. (SK)

Genomes, Proteomes and the Central Dogma

PubMed Central

Franklin, Sarah; Vondriska, Thomas M.

2011-01-01

Systems biology, with its associated technologies of proteomics, genomics and metabolomics, is driving the evolution of our understanding of cardiovascular physiology. Rather than studying individual molecules or even single reactions, a systems approach allows integration of orthogonal datasets from distinct tiers of biological data, including gene, RNA, protein, metabolite and other component networks. Together these networks give rise to emergent properties of cellular function and it is their reprogramming that causes disease. We present five observations regarding how systems biology is guiding a revisiting of the central dogma: (i) de-emphasizing the unidirectional flow of information from genes to proteins; (ii) revealing the role of modules of molecules as opposed to individual proteins acting in isolation; (iii) enabling discovery of novel emergent properties; (iv) demonstrating the importance of networks in biology; and (v) adding new dimensionality to the study of biological systems. PMID:22010165

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.

Bioelectronic Sensors and Devices

NASA Astrophysics Data System (ADS)

Reed, Mark

Nanoscale electronic devices have recently enabled the ability to controllably probe biological systems, from the molecular to the cellular level, opening up new applications and understanding of biological function and response. This talk reviews some of the advances in the field, ranging from diagnostic and therapeutic applications, to cellular manipulation and response, to the emulation of biological response. In diagnostics, integrated nanodevice biosensors compatible with CMOS technology have achieved unprecedented sensitivity, enabling a wide range of label-free biochemical and macromolecule sensing applications down to femtomolar concentrations. These systems have demonstrated integrated assays of biomarkers at clinically important concentrations for both diagnostics and as a quantitative tool for drug design and discovery. Cellular level response can also be observed, including immune response function and dynamics. Finally, the field is beginning to create devices that emulate function, and the demonstration of a solid state artificial ion channel will be discussed.

Receptive fields and the theory of discriminant operators

NASA Astrophysics Data System (ADS)

Gupta, Madan M.; Hungenahally, Suresh K.

1991-02-01

Biological basis for machine vision is a notion which is being used extensively for the development of machine vision systems for various applications. In this paper we have made an attempt to emulate the receptive fields that exist in the biological visual channels. In particular we have exploited the notion of receptive fields for developing the mathematical functions named as discriminantfunctions for the extraction of transition information from signals and multi-dimensional signals and images. These functions are found to be useful for the development of artificial receptive fields for neuro-vision systems. 1.

Systems biology of cellular membranes: a convergence with biophysics.

PubMed

Chabanon, Morgan; Stachowiak, Jeanne C; Rangamani, Padmini

2017-09-01

Systems biology and systems medicine have played an important role in the last two decades in shaping our understanding of biological processes. While systems biology is synonymous with network maps and '-omics' approaches, it is not often associated with mechanical processes. Here, we make the case for considering the mechanical and geometrical aspects of biological membranes as a key step in pushing the frontiers of systems biology of cellular membranes forward. We begin by introducing the basic components of cellular membranes, and highlight their dynamical aspects. We then survey the functions of the plasma membrane and the endomembrane system in signaling, and discuss the role and origin of membrane curvature in these diverse cellular processes. We further give an overview of the experimental and modeling approaches to study membrane phenomena. We close with a perspective on the converging futures of systems biology and membrane biophysics, invoking the need to include physical variables such as location and geometry in the study of cellular membranes. WIREs Syst Biol Med 2017, 9:e1386. doi: 10.1002/wsbm.1386 For further resources related to this article, please visit the WIREs website. © 2017 Wiley Periodicals, Inc.

Sixth International Conference on Systems Biology (ICSB 2005)

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

Professor Andrew Murray

2005-10-22

This grant supported the Sixth International Conference on Systems Biology (ICSB 2005), held in Boston, Massachusetts from October 19th to 22nd, 2005. The ICSB is the only major, annual, international conference focused exclusively on the important emerging field of systems biology. It draws together scientists with expertise in theoretical, computational and experimental approaches to understanding biological systems at many levels. Previous ICSB meetings have been held in Tokyo (2000), at Caltech (2001), at the Karolinska Institute (2002), at Washington University in St. Louis (2003), and in Heidelberg (2004). These conferences have been increasingly successful at bringing together the growing communitymore » of established and junior researchers with interests in this area. Boston is home to several groups that have shown leadership in the field and was therefore an ideal place to hold this conference . The executive committee for the conference comprised Jim Collins (Biomedical Engineering, Boston University), Marc Kirschner (chair of the new Department of Systems Biology at Harvard Medical School), Eric Lander (director of the Broad Institute of MIT and Harvard), Andrew Murray (director of Harvard’s Bauer Center for Genomics Research) and Peter Sorger (director of MIT’s Computational and Systems Biology Initiative). There are almost as many definitions of systems biology as there are systems biologists. We take a broad view of the field, and we succeeded in one of our major aims in organizing a conference that bridges two types of divide. The first is that between traditional academic disciplines: each of our sessions includes speakers from biology and from one or more physical or quantitative sciences. The second type includes those that separate experimental biologists from their colleagues who work on theory or computation. Here again, each session included representatives from at least two of these three categories; indeed, many of the speakers combined at least two of the categories in their own research activities. We define systems biology as a widening of focus in biology from individual genes or proteins to the complex networks of these molecules that allow cells and organisms to function. In the same way that conscious thought cannot be said to reside in any single neuron in the brain, simpler biological functions such as cell division arise from the interactions among many components in a network or ‘functional module’. For us, systems biology is characterized by the recognition that a higher-order description of biological function, accompanied by quantitative methods of analysis — often borrowed from disciplines such as physics, engineering, computer science or mathematics — can lead to the identification of general principles that underlie the structure, behavior, and evolution of cells and organisms. The heart of the conference were sessions on six topics: intracellular dynamics (featuring measurements on single cells, and their interpretation); biology by design (synthetic biology); intracellular networks (signal transduction and transcriptional regulation); multicellular networks (development and pattern formation); mechanics and scale in cellular behavior (featuring work on cytoskeletal mechanics, and on scaling relationships in biology); and evolution in action (including experimental evolution, of both real and artificial life-forms). Each session had four invited speakers; 23 of the 24 invited speakers attended (see below). We have selected these speakers not only for the interest of their research, but for their skills as communicators, thereby giving us the best chance of bridging the divides mentioned above. We also made a point of including women, younger investigators and people from outside the United States among the speakers. In addition to the invited speakers, we allotted time in the program for at least five contributed talks, which were selected from the poster submissions. Our aim in selecting these contributors showcased work that is “hot off the bench” (or computer) at the time of the conference, and also created additional opportunities for younger investigators to present their work. The main conference was preceded by a day of tutorials, and followed by two days of workshops, on a range of topics in quantitative, computational and systems biology.« less

Engineering the robustness of industrial microbes through synthetic biology.

PubMed

Zhu, Linjiang; Zhu, Yan; Zhang, Yanping; Li, Yin

2012-02-01

Microbial fermentations and bioconversions play a central role in the production of pharmaceuticals, enzymes and chemicals. To meet the demands of industrial production, it is desirable that microbes maintain a maximized carbon flux towards target metabolites regardless of fluctuations in intracellular or extracellular environments. This requires cellular systems that maintain functional stability and dynamic homeostasis in a given physiological state, or manipulate transitions between different physiological states. Stable maintenance or smooth transition can be achieved through engineering of dynamic controllability, modular and hierarchical organization, or functional redundancy, three key features of biological robustness in a cellular system. This review summarizes how synthetic biology can be used to improve the robustness of industrial microbes. Copyright © 2011 Elsevier Ltd. All rights reserved.

A Systems Biology Analysis Unfolds the Molecular Pathways and Networks of Two Proteobacteria in Spaceflight and Simulated Microgravity Conditions.

PubMed

Roy, Raktim; Shilpa, P Phani; Bagh, Sangram

2016-09-01

Bacteria are important organisms for space missions due to their increased pathogenesis in microgravity that poses risks to the health of astronauts and for projected synthetic biology applications at the space station. We understand little about the effect, at the molecular systems level, of microgravity on bacteria, despite their significant incidence. In this study, we proposed a systems biology pipeline and performed an analysis on published gene expression data sets from multiple seminal studies on Pseudomonas aeruginosa and Salmonella enterica serovar Typhimurium under spaceflight and simulated microgravity conditions. By applying gene set enrichment analysis on the global gene expression data, we directly identified a large number of new, statistically significant cellular and metabolic pathways involved in response to microgravity. Alteration of metabolic pathways in microgravity has rarely been reported before, whereas in this analysis metabolic pathways are prevalent. Several of those pathways were found to be common across studies and species, indicating a common cellular response in microgravity. We clustered genes based on their expression patterns using consensus non-negative matrix factorization. The genes from different mathematically stable clusters showed protein-protein association networks with distinct biological functions, suggesting the plausible functional or regulatory network motifs in response to microgravity. The newly identified pathways and networks showed connection with increased survival of pathogens within macrophages, virulence, and antibiotic resistance in microgravity. Our work establishes a systems biology pipeline and provides an integrated insight into the effect of microgravity at the molecular systems level. Systems biology-Microgravity-Pathways and networks-Bacteria. Astrobiology 16, 677-689.

Conciliation biology: the eco-evolutionary management of permanently invaded biotic systems

PubMed Central

Carroll, Scott P

2011-01-01

Biotic invaders and similar anthropogenic novelties such as domesticates, transgenics, and cancers can alter ecology and evolution in environmental, agricultural, natural resource, public health, and medical systems. The resulting biological changes may either hinder or serve management objectives. For example, biological control and eradication programs are often defeated by unanticipated resistance evolution and by irreversibility of invader impacts. Moreover, eradication may be ill-advised when nonnatives introduce beneficial functions. Thus, contexts that appear to call for eradication may instead demand managed coexistence of natives with nonnatives, and yet applied biologists have not generally considered the need to manage the eco-evolutionary dynamics that commonly result from interactions of natives with nonnatives. Here, I advocate a conciliatory approach to managing systems where novel organisms cannot or should not be eradicated. Conciliatory strategies incorporate benefits of nonnatives to address many practical needs including slowing rates of resistance evolution, promoting evolution of indigenous biological control, cultivating replacement services and novel functions, and managing native–nonnative coevolution. Evolutionary links across disciplines foster cohesion essential for managing the broad impacts of novel biotic systems. Rather than signaling defeat, conciliation biology thus utilizes the predictive power of evolutionary theory to offer diverse and flexible pathways to more sustainable outcomes. PMID:25567967

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.

Activated Biological Filters (ABF Towers). Student Manual. Biological Treatment Process Control.

ERIC Educational Resources Information Center

Wooley, John F.

This student manual contains textual material for a two-lesson unit on activated bio-filters (ABF). The first lesson (the sewage treatment plant) examines those process units that are unique to the ABF system. The lesson includes a review of the structural components of the ABF system and their functions and a discussion of several operational…

Analyzing Defects in the "Caenorhabditis Elegans" Nervous System Using Organismal and Cell Biological Approaches

ERIC Educational Resources Information Center

Guziewicz, Megan; Vitullo, Toni; Simmons, Bethany; Kohn, Rebecca Eustance

2002-01-01

The goal of this laboratory exercise is to increase student understanding of the impact of nervous system function at both the organismal and cellular levels. This inquiry-based exercise is designed for an undergraduate course examining principles of cell biology. After observing the movement of "Caenorhabditis elegans" with defects in their…

Functional Amyloids in Reproduction.

PubMed

Hewetson, Aveline; Do, Hoa Quynh; Myers, Caitlyn; Muthusubramanian, Archana; Sutton, Roger Bryan; Wylie, Benjamin J; Cornwall, Gail A

2017-06-29

Amyloids are traditionally considered pathological protein aggregates that play causative roles in neurodegenerative disease, diabetes and prionopathies. However, increasing evidence indicates that in many biological systems nonpathological amyloids are formed for functional purposes. In this review, we will specifically describe amyloids that carry out biological roles in sexual reproduction including the processes of gametogenesis, germline specification, sperm maturation and fertilization. Several of these functional amyloids are evolutionarily conserved across several taxa, including human, emphasizing the critical role amyloids perform in reproduction. Evidence will also be presented suggesting that, if altered, some functional amyloids may become pathological.

Building New Bridges between In Vitro and In Vivo in Early Drug Discovery: Where Molecular Modeling Meets Systems Biology.

PubMed

Pearlstein, Robert A; McKay, Daniel J J; Hornak, Viktor; Dickson, Callum; Golosov, Andrei; Harrison, Tyler; Velez-Vega, Camilo; Duca, José

2017-01-01

Cellular drug targets exist within networked function-generating systems whose constituent molecular species undergo dynamic interdependent non-equilibrium state transitions in response to specific perturbations (i.e.. inputs). Cellular phenotypic behaviors are manifested through the integrated behaviors of such networks. However, in vitro data are frequently measured and/or interpreted with empirical equilibrium or steady state models (e.g. Hill, Michaelis-Menten, Briggs-Haldane) relevant to isolated target populations. We propose that cells act as analog computers, "solving" sets of coupled "molecular differential equations" (i.e. represented by populations of interacting species)via "integration" of the dynamic state probability distributions among those populations. Disconnects between biochemical and functional/phenotypic assays (cellular/in vivo) may arise with targetcontaining systems that operate far from equilibrium, and/or when coupled contributions (including target-cognate partner binding and drug pharmacokinetics) are neglected in the analysis of biochemical results. The transformation of drug discovery from a trial-and-error endeavor to one based on reliable design criteria depends on improved understanding of the dynamic mechanisms powering cellular function/dysfunction at the systems level. Here, we address the general mechanisms of molecular and cellular function and pharmacological modulation thereof. We outline a first principles theory on the mechanisms by which free energy is stored and transduced into biological function, and by which biological function is modulated by drug-target binding. We propose that cellular function depends on dynamic counter-balanced molecular systems necessitated by the exponential behavior of molecular state transitions under non-equilibrium conditions, including positive versus negative mass action kinetics and solute-induced perturbations to the hydrogen bonds of solvating water versus kT. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Assessment and management of soil microbial community structure for disease suppression.

PubMed

Mazzola, Mark

2004-01-01

Identification of the biological properties contributing to the function of suppressive soils is a necessary first step to the management of such systems for use in the control of soilborne diseases. The development and application of molecular methods for the characterization and monitoring of soil microbial properties will enable a more rapid and detailed assessment of the biological nature of soil suppressiveness. Although suppressive soils have provided a wealth of microbial resources that have subsequently been applied for the biological control of soilborne plant pathogens, the full functional capabilities of the phenomena have not been realized in production agricultural ecosystems. Cultural practices, such as the application of soil amendments, have the capacity to enhance disease suppression, though the biological modes of action may vary from that initially resident to the soil. Plants have a distinct impact on characteristics and activity of resident soil microbial communities, and therefore play an important role in determining the development of the disease-suppressive state. Likewise, plant genotype will modulate these same biological communities, and should be considered when developing strategies to exploit the potential of such a natural disease control system. Implementation of consistently effective practices to manage this resource in an economically and environmentally feasible manner will require more detailed investigation of these biologically complex systems and refinement of currently available methodologies.

Prokaryotic regulatory systems biology: Common principles governing the functional architectures of Bacillus subtilis and Escherichia coli unveiled by the natural decomposition approach.

PubMed

Freyre-González, Julio A; Treviño-Quintanilla, Luis G; Valtierra-Gutiérrez, Ilse A; Gutiérrez-Ríos, Rosa María; Alonso-Pavón, José A

2012-10-31

Escherichia coli and Bacillus subtilis are two of the best-studied prokaryotic model organisms. Previous analyses of their transcriptional regulatory networks have shown that they exhibit high plasticity during evolution and suggested that both converge to scale-free-like structures. Nevertheless, beyond this suggestion, no analyses have been carried out to identify the common systems-level components and principles governing these organisms. Here we show that these two phylogenetically distant organisms follow a set of common novel biologically consistent systems principles revealed by the mathematically and biologically founded natural decomposition approach. The discovered common functional architecture is a diamond-shaped, matryoshka-like, three-layer (coordination, processing, and integration) hierarchy exhibiting feedback, which is shaped by four systems-level components: global transcription factors (global TFs), locally autonomous modules, basal machinery and intermodular genes. The first mathematical criterion to identify global TFs, the κ-value, was reassessed on B. subtilis and confirmed its high predictive power by identifying all the previously reported, plus three potential, master regulators and eight sigma factors. The functionally conserved cores of modules, basal cell machinery, and a set of non-orthologous common physiological global responses were identified via both orthologous genes and non-orthologous conserved functions. This study reveals novel common systems principles maintained between two phylogenetically distant organisms and provides a comparison of their lifestyle adaptations. Our results shed new light on the systems-level principles and the fundamental functions required by bacteria to sustain life. Copyright © 2012 Elsevier B.V. All rights reserved.

Social networks to biological networks: systems biology of Mycobacterium tuberculosis.

PubMed

Vashisht, Rohit; Bhardwaj, Anshu; Osdd Consortium; Brahmachari, Samir K

2013-07-01

Contextualizing relevant information to construct a network that represents a given biological process presents a fundamental challenge in the network science of biology. The quality of network for the organism of interest is critically dependent on the extent of functional annotation of its genome. Mostly the automated annotation pipelines do not account for unstructured information present in volumes of literature and hence large fraction of genome remains poorly annotated. However, if used, this information could substantially enhance the functional annotation of a genome, aiding the development of a more comprehensive network. Mining unstructured information buried in volumes of literature often requires manual intervention to a great extent and thus becomes a bottleneck for most of the automated pipelines. In this review, we discuss the potential of scientific social networking as a solution for systematic manual mining of data. Focusing on Mycobacterium tuberculosis, as a case study, we discuss our open innovative approach for the functional annotation of its genome. Furthermore, we highlight the strength of such collated structured data in the context of drug target prediction based on systems level analysis of pathogen.

Biology doesn't waste energy: that's really smart

NASA Astrophysics Data System (ADS)

Vincent, Julian F. V.; Bogatyreva, Olga; Bogatyrev, Nikolaj

2006-03-01

Biology presents us with answers to design problems that we suspect would be very useful if only we could implement them successfully. We use the Russian theory of problem solving - TRIZ - in a novel way to provide a system for analysis and technology transfer. The analysis shows that whereas technology uses energy as the main means of solving technical problems, biology uses information and structure. Biology is also strongly hierarchical. The suggestion is that smart technology in hierarchical structures can help us to design much more efficient technology. TRIZ also suggests that biological design is autonomous and can be defined by the prefix "self-" with any function. This autonomy extends to the control system, so that the sensor is commonly also the actuator, resulting in simpler systems and greater reliability.

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

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.

Grammar as a Feature of Text Construction: Time and Rhetorical Function in French Journal Articles in Biology

ERIC Educational Resources Information Center

Liddicoat, Anthony J.

2004-01-01

This article investigates one aspect of scientific style in French: the use of tenses. It investigates the claims made in the literature that the verb system of scientific French is a temporal. The frequency of tensed finite forms in 10 French language journal articles on biological sciences is examined. The rhetorical function of past and future…

Hypothermic temperature effects on organ survival and restoration

PubMed Central

Ishikawa, Jun; Oshima, Masamitsu; Iwasaki, Fumitaka; Suzuki, Ryoji; Park, Joonhong; Nakao, Kazuhisa; Matsuzawa-Adachi, Yuki; Mizutsuki, Taro; Kobayashi, Ayaka; Abe, Yuta; Kobayashi, Eiji; Tezuka, Katsunari; Tsuji, Takashi

2015-01-01

A three-dimensional multicellular organism maintains the biological functions of life support by using the blood circulation to transport oxygen and nutrients and to regulate body temperature for intracellular enzymatic reactions. Donor organ transplantation using low-temperature storage is used as the fundamental treatment for dysfunctional organs. However, this approach has a serious problem in that donor organs maintain healthy conditions only during short-term storage. In this study, we developed a novel liver perfusion culture system based on biological metabolism that can maintain physiological functions, including albumin synthesis, bile secretion and urea production. This system also allows for the resurrection of a severely ischaemic liver. This study represents a significant advance for the development of an ex vivo organ perfusion system based on biological metabolism. It can be used not only to address donor organ shortages but also as the basis of future regenerative organ replacement therapy. PMID:25900715

Bioinspired spring origami.

PubMed

Faber, Jakob A; Arrieta, Andres F; Studart, André R

2018-03-23

Origami enables folding of objects into a variety of shapes in arts, engineering, and biological systems. In contrast to well-known paper-folded objects, the wing of the earwig has an exquisite natural folding system that cannot be sufficiently described by current origami models. Such an unusual biological system displays incompatible folding patterns, remains open by a bistable locking mechanism during flight, and self-folds rapidly without muscular actuation. We show that these notable functionalities arise from the protein-rich joints of the earwig wing, which work as extensional and rotational springs between facets. Inspired by this biological wing, we establish a spring origami model that broadens the folding design space of traditional origami and allows for the fabrication of precisely tunable, four-dimensional-printed objects with programmable bioinspired morphing functionalities. Copyright © 2018 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.

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.

Event-based text mining for biology and functional genomics

PubMed Central

Thompson, Paul; Nawaz, Raheel; McNaught, John; Kell, Douglas B.

2015-01-01

The assessment of genome function requires a mapping between genome-derived entities and biochemical reactions, and the biomedical literature represents a rich source of information about reactions between biological components. However, the increasingly rapid growth in the volume of literature provides both a challenge and an opportunity for researchers to isolate information about reactions of interest in a timely and efficient manner. In response, recent text mining research in the biology domain has been largely focused on the identification and extraction of ‘events’, i.e. categorised, structured representations of relationships between biochemical entities, from the literature. Functional genomics analyses necessarily encompass events as so defined. Automatic event extraction systems facilitate the development of sophisticated semantic search applications, allowing researchers to formulate structured queries over extracted events, so as to specify the exact types of reactions to be retrieved. This article provides an overview of recent research into event extraction. We cover annotated corpora on which systems are trained, systems that achieve state-of-the-art performance and details of the community shared tasks that have been instrumental in increasing the quality, coverage and scalability of recent systems. Finally, several concrete applications of event extraction are covered, together with emerging directions of research. PMID:24907365

Thematic review series: systems biology approaches to metabolic and cardiovascular disorders. Lipidomics: a global approach to lipid analysis in biological systems.

PubMed

Watson, Andrew D

2006-10-01

Lipids are water-insoluble molecules that have a wide variety of functions within cells, including: 1) maintenance of electrochemical gradients; 2) subcellular partitioning; 3) first- and second-messenger cell signaling; 4) energy storage; and 5) protein trafficking and membrane anchoring. The physiological importance of lipids is illustrated by the numerous diseases to which lipid abnormalities contribute, including atherosclerosis, diabetes, obesity, and Alzheimer's disease. Lipidomics, a branch of metabolomics, is a systems-based study of all lipids, the molecules with which they interact, and their function within the cell. Recent advances in soft-ionization mass spectrometry, combined with established separation techniques, have allowed the rapid and sensitive detection of a variety of lipid species with minimal sample preparation. A "lipid profile" from a crude lipid extract is a mass spectrum of the composition and abundance of the lipids it contains, which can be used to monitor changes over time and in response to particular stimuli. Lipidomics, integrated with genomics, proteomics, and metabolomics, will contribute toward understanding how lipids function in a biological system and will provide a powerful tool for elucidating the mechanism of lipid-based disease, for biomarker screening, and for monitoring pharmacologic therapy.

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

Frontiers of optofluidics in synthetic biology.

PubMed

Tan, Cheemeng; Lo, Shih-Jie; LeDuc, Philip R; Cheng, Chao-Min

2012-10-07

The development of optofluidic-based technology has ushered in a new era of lab-on-a-chip functionality, including miniaturization of biomedical devices, enhanced sensitivity for molecular detection, and multiplexing of optical measurements. While having great potential, optofluidic devices have only begun to be exploited in many biotechnological applications. Here, we highlight the potential of integrating optofluidic devices with synthetic biological systems, which is a field focusing on creating novel cellular systems by engineering synthetic gene and protein networks. First, we review the development of synthetic biology at different length scales, ranging from single-molecule, single-cell, to cellular population. We emphasize light-sensitive synthetic biological systems that would be relevant for the integration with optofluidic devices. Next, we propose several areas for potential applications of optofluidics in synthetic biology. The integration of optofluidics and synthetic biology would have a broad impact on point-of-care diagnostics and biotechnology.

Modeling for Visual Feature Extraction Using Spiking Neural Networks

NASA Astrophysics Data System (ADS)

Kimura, Ichiro; Kuroe, Yasuaki; Kotera, Hiromichi; Murata, Tomoya

This paper develops models for “visual feature extraction” in biological systems by using “spiking neural network (SNN)”. The SNN is promising for developing the models because the information is encoded and processed by spike trains similar to biological neural networks. Two architectures of SNN are proposed for modeling the directionally selective and the motion parallax cell in neuro-sensory systems and they are trained so as to possess actual biological responses of each cell. To validate the developed models, their representation ability is investigated and their visual feature extraction mechanisms are discussed from the neurophysiological viewpoint. It is expected that this study can be the first step to developing a sensor system similar to the biological systems and also a complementary approach to investigating the function of the brain.

BioCore Guide: A Tool for Interpreting the Core Concepts of Vision and Change for Biology Majors

ERIC Educational Resources Information Center

Brownell, Sara E.; Freeman, Scott; Wenderoth, Mary Pat; Crowe, Alison J.

2014-01-01

"Vision and Change in Undergraduate Biology Education" outlined five core concepts intended to guide undergraduate biology education: 1) evolution; 2) structure and function; 3) information flow, exchange, and storage; 4) pathways and transformations of energy and matter; and 5) systems. We have taken these general recommendations and…

Invited review article: Advanced light microscopy for biological space research.

PubMed

De Vos, Winnok H; Beghuin, Didier; Schwarz, Christian J; Jones, David B; van Loon, Jack J W A; Bereiter-Hahn, Juergen; Stelzer, Ernst H K

2014-10-01

As commercial space flights have become feasible and long-term extraterrestrial missions are planned, it is imperative that the impact of space travel and the space environment on human physiology be thoroughly characterized. Scrutinizing the effects of potentially detrimental factors such as ionizing radiation and microgravity at the cellular and tissue level demands adequate visualization technology. Advanced light microscopy (ALM) is the leading tool for non-destructive structural and functional investigation of static as well as dynamic biological systems. In recent years, technological developments and advances in photochemistry and genetic engineering have boosted all aspects of resolution, readout and throughput, rendering ALM ideally suited for biological space research. While various microscopy-based studies have addressed cellular response to space-related environmental stressors, biological endpoints have typically been determined only after the mission, leaving an experimental gap that is prone to bias results. An on-board, real-time microscopical monitoring device can bridge this gap. Breadboards and even fully operational microscope setups have been conceived, but they need to be rendered more compact and versatile. Most importantly, they must allow addressing the impact of gravity, or the lack thereof, on physiologically relevant biological systems in space and in ground-based simulations. In order to delineate the essential functionalities for such a system, we have reviewed the pending questions in space science, the relevant biological model systems, and the state-of-the art in ALM. Based on a rigorous trade-off, in which we recognize the relevance of multi-cellular systems and the cellular microenvironment, we propose a compact, but flexible concept for space-related cell biological research that is based on light sheet microscopy.

Invited Review Article: Advanced light microscopy for biological space research

NASA Astrophysics Data System (ADS)

De Vos, Winnok H.; Beghuin, Didier; Schwarz, Christian J.; Jones, David B.; van Loon, Jack J. W. A.; Bereiter-Hahn, Juergen; Stelzer, Ernst H. K.

2014-10-01

As commercial space flights have become feasible and long-term extraterrestrial missions are planned, it is imperative that the impact of space travel and the space environment on human physiology be thoroughly characterized. Scrutinizing the effects of potentially detrimental factors such as ionizing radiation and microgravity at the cellular and tissue level demands adequate visualization technology. Advanced light microscopy (ALM) is the leading tool for non-destructive structural and functional investigation of static as well as dynamic biological systems. In recent years, technological developments and advances in photochemistry and genetic engineering have boosted all aspects of resolution, readout and throughput, rendering ALM ideally suited for biological space research. While various microscopy-based studies have addressed cellular response to space-related environmental stressors, biological endpoints have typically been determined only after the mission, leaving an experimental gap that is prone to bias results. An on-board, real-time microscopical monitoring device can bridge this gap. Breadboards and even fully operational microscope setups have been conceived, but they need to be rendered more compact and versatile. Most importantly, they must allow addressing the impact of gravity, or the lack thereof, on physiologically relevant biological systems in space and in ground-based simulations. In order to delineate the essential functionalities for such a system, we have reviewed the pending questions in space science, the relevant biological model systems, and the state-of-the art in ALM. Based on a rigorous trade-off, in which we recognize the relevance of multi-cellular systems and the cellular microenvironment, we propose a compact, but flexible concept for space-related cell biological research that is based on light sheet microscopy.

The necessity of a theory of biology for tissue engineering: metabolism-repair systems.

PubMed

Ganguli, Suman; Hunt, C Anthony

2004-01-01

Since there is no widely accepted global theory of biology, tissue engineering and bioengineering lack a theoretical understanding of the systems being engineered. By default, tissue engineering operates with a "reductionist" theoretical approach, inherited from traditional engineering of non-living materials. Long term, that approach is inadequate, since it ignores essential aspects of biology. Metabolism-repair systems are a theoretical framework which explicitly represents two "functional" aspects of living organisms: self-repair and self-replication. Since repair and replication are central to tissue engineering, we advance metabolism-repair systems as a potential theoretical framework for tissue engineering. We present an overview of the framework, and indicate directions to pursue for extending it to the context of tissue engineering. We focus on biological networks, both metabolic and cellular, as one such direction. The construction of these networks, in turn, depends on biological protocols. Together these concepts may help point the way to a global theory of biology appropriate for tissue engineering.

How do biological systems discriminate among physically similar ions?

PubMed

Diamond, J M

1975-10-01

This paper reviews the history of understanding how biological systems can discriminate so strikingly among physically similar ions, especially alkali cations. Appreciation of qualitative regularities ("permitted sequences") and quantitative regularities ("selectivity isotherms") in ion selectivity grew first from studies of ion exchangers and glass electrodes, then of biological systems such as enzymes and cell membranes, and most recently of lipid bilayers doped with model pores and carriers. Discrimination of ions depends on both electrostatic and steric forces. "Black-box" studies on intact biological membranes have in some cases yielded molecular clues to the structure of the actual biological pores and carriers. Major current problems involve the extraction of these molecules; how to do it, what to do when it is achieved, and how (and if) it is relevant to the central problems of membrane function. Further advances are expected soon from studies of rate barriers within membranes, of voltage-dependent ("excitable") conducting channels, and of increasingly complex model systems and biological membranes.

The Use of Functional Genomics in Conjunction with Metabolomics for Mycobacterium tuberculosis Research

PubMed Central

Swanepoel, Conrad C.

2014-01-01

Tuberculosis (TB), caused by Mycobacterium tuberculosis, is a fatal infectious disease, resulting in 1.4 million deaths globally per annum. Over the past three decades, genomic studies have been conducted in an attempt to elucidate the functionality of the genome of the pathogen. However, many aspects of this complex genome remain largely unexplored, as approaches like genomics, proteomics, and transcriptomics have failed to characterize them successfully. In turn, metabolomics, which is relatively new to the “omics” revolution, has shown great potential for investigating biological systems or their modifications. Furthermore, when these data are interpreted in combination with previously acquired genomics, proteomics and transcriptomics data, using what is termed a systems biology approach, a more holistic understanding of these systems can be achieved. In this review we discuss how metabolomics has contributed so far to characterizing TB, with emphasis on the resulting improved elucidation of M. tuberculosis in terms of (1) metabolism, (2) growth and replication, (3) pathogenicity, and (4) drug resistance, from the perspective of systems biology. PMID:24771957

Fabrication, Characterization, and Biological Activity of Avermectin Nano-delivery Systems with Different Particle Sizes

NASA Astrophysics Data System (ADS)

Wang, Anqi; Wang, Yan; Sun, Changjiao; Wang, Chunxin; Cui, Bo; Zhao, Xiang; Zeng, Zhanghua; Yao, Junwei; Yang, Dongsheng; Liu, Guoqiang; Cui, Haixin

2018-01-01

Nano-delivery systems for the active ingredients of pesticides can improve the utilization rates of pesticides and prolong their control effects. This is due to the nanocarrier envelope and controlled release function. However, particles containing active ingredients in controlled release pesticide formulations are generally large and have wide size distributions. There have been limited studies about the effect of particle size on the controlled release properties and biological activities of pesticide delivery systems. In the current study, avermectin (Av) nano-delivery systems were constructed with different particle sizes and their performances were evaluated. The Av release rate in the nano-delivery system could be effectively controlled by changing the particle size. The biological activity increased with decreasing particle size. These results suggest that Av nano-delivery systems can significantly improve the controllable release, photostability, and biological activity, which will improve efficiency and reduce pesticide residues.

The Comet Cometh: Evolving Developmental Systems.

PubMed

Jaeger, Johannes; Laubichler, Manfred; Callebaut, Werner

In a recent opinion piece, Denis Duboule has claimed that the increasing shift towards systems biology is driving evolutionary and developmental biology apart, and that a true reunification of these two disciplines within the framework of evolutionary developmental biology (EvoDevo) may easily take another 100 years. He identifies methodological, epistemological, and social differences as causes for this supposed separation. Our article provides a contrasting view. We argue that Duboule's prediction is based on a one-sided understanding of systems biology as a science that is only interested in functional, not evolutionary, aspects of biological processes. Instead, we propose a research program for an evolutionary systems biology, which is based on local exploration of the configuration space in evolving developmental systems. We call this approach-which is based on reverse engineering, simulation, and mathematical analysis-the natural history of configuration space. We discuss a number of illustrative examples that demonstrate the past success of local exploration, as opposed to global mapping, in different biological contexts. We argue that this pragmatic mode of inquiry can be extended and applied to the mathematical analysis of the developmental repertoire and evolutionary potential of evolving developmental mechanisms and that evolutionary systems biology so conceived provides a pragmatic epistemological framework for the EvoDevo synthesis.

Secure Encapsulation and Publication of Biological Services in the Cloud Computing Environment

PubMed Central

Zhang, Weizhe; Wang, Xuehui; Lu, Bo; Kim, Tai-hoon

2013-01-01

Secure encapsulation and publication for bioinformatics software products based on web service are presented, and the basic function of biological information is realized in the cloud computing environment. In the encapsulation phase, the workflow and function of bioinformatics software are conducted, the encapsulation interfaces are designed, and the runtime interaction between users and computers is simulated. In the publication phase, the execution and management mechanisms and principles of the GRAM components are analyzed. The functions such as remote user job submission and job status query are implemented by using the GRAM components. The services of bioinformatics software are published to remote users. Finally the basic prototype system of the biological cloud is achieved. PMID:24078906

Bioinspired Functional Materials

DOE PAGES

Zheng, Yongmei; Wang, Jingxia; Hou, Yongping; ...

2014-11-25

This special issue is focused on the nanoscale or micro-/nanoscale structures similar to the biological features in multilevels or hierarchy and so on. Research by mimicking biological systems has shown more impact on many applications due to the well-designed micro-/nanostructures inspired from the biological surfaces or interfaces; therefore, the materials may achieve the fascinating functionality. In conclusion, the bioinspired functional materials may be fabricated by developing novel technology or methods such as synthesis, self-assembly, and soft lithography at micro- or nanolevel or multilevels and, in addition, the multidisciplinary procedures of physical or chemical methods and nanotechnology to mimic the biologicalmore » multiscale micro-/nanostructures onto one-/two-dimensional surface materials.« less

Secure encapsulation and publication of biological services in the cloud computing environment.

PubMed

Zhang, Weizhe; Wang, Xuehui; Lu, Bo; Kim, Tai-hoon

2013-01-01

Secure encapsulation and publication for bioinformatics software products based on web service are presented, and the basic function of biological information is realized in the cloud computing environment. In the encapsulation phase, the workflow and function of bioinformatics software are conducted, the encapsulation interfaces are designed, and the runtime interaction between users and computers is simulated. In the publication phase, the execution and management mechanisms and principles of the GRAM components are analyzed. The functions such as remote user job submission and job status query are implemented by using the GRAM components. The services of bioinformatics software are published to remote users. Finally the basic prototype system of the biological cloud is achieved.

Structure-Function Relations in Physiology Education: Where's the Mechanism?

ERIC Educational Resources Information Center

Lira, Matthew E.; Gardner, Stephanie M.

2017-01-01

Physiology demands systems thinking: reasoning within and between levels of biological organization and across different organ systems. Many physiological mechanisms explain how structures and their properties interact at one level of organization to produce emergent functions at a higher level of organization. Current physiology principles, such…

Function, therapeutic potential and cell biology of BACE proteases: current status and future prospects.

PubMed

Vassar, Robert; Kuhn, Peer-Hendrik; Haass, Christian; Kennedy, Matthew E; Rajendran, Lawrence; Wong, Philip C; Lichtenthaler, Stefan F

2014-07-01

The β-site APP cleaving enzymes 1 and 2 (BACE1 and BACE2) were initially identified as transmembrane aspartyl proteases cleaving the amyloid precursor protein (APP). BACE1 is a major drug target for Alzheimer's disease because BACE1-mediated cleavage of APP is the first step in the generation of the pathogenic amyloid-β peptides. BACE1, which is highly expressed in the nervous system, is also required for myelination by cleaving neuregulin 1. Several recent proteomic and in vivo studies using BACE1- and BACE2-deficient mice demonstrate a much wider range of physiological substrates and functions for both proteases within and outside of the nervous system. For BACE1 this includes axon guidance, neurogenesis, muscle spindle formation, and neuronal network functions, whereas BACE2 was shown to be involved in pigmentation and pancreatic β-cell function. This review highlights the recent progress in understanding cell biology, substrates, and functions of BACE proteases and discusses the therapeutic options and potential mechanism-based liabilities, in particular for BACE inhibitors in Alzheimer's disease. The protease BACE1 is a major drug target in Alzheimer disease. Together with its homolog BACE2, both proteases have an increasing number of functions within and outside of the nervous system. This review highlights recent progress in understanding cell biology, substrates, and functions of BACE proteases and discusses the therapeutic options and potential mechanism-based liabilities, in particular for BACE inhibitors in Alzheimer disease. © 2014 International Society for Neurochemistry.

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…

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

De Vos, Winnok H., E-mail: winnok.devos@uantwerpen.be; Cell Systems and Imaging Research Group, Department of Molecular Biotechnology, Ghent University, Ghent; Beghuin, Didier

As commercial space flights have become feasible and long-term extraterrestrial missions are planned, it is imperative that the impact of space travel and the space environment on human physiology be thoroughly characterized. Scrutinizing the effects of potentially detrimental factors such as ionizing radiation and microgravity at the cellular and tissue level demands adequate visualization technology. Advanced light microscopy (ALM) is the leading tool for non-destructive structural and functional investigation of static as well as dynamic biological systems. In recent years, technological developments and advances in photochemistry and genetic engineering have boosted all aspects of resolution, readout and throughput, rendering ALMmore » ideally suited for biological space research. While various microscopy-based studies have addressed cellular response to space-related environmental stressors, biological endpoints have typically been determined only after the mission, leaving an experimental gap that is prone to bias results. An on-board, real-time microscopical monitoring device can bridge this gap. Breadboards and even fully operational microscope setups have been conceived, but they need to be rendered more compact and versatile. Most importantly, they must allow addressing the impact of gravity, or the lack thereof, on physiologically relevant biological systems in space and in ground-based simulations. In order to delineate the essential functionalities for such a system, we have reviewed the pending questions in space science, the relevant biological model systems, and the state-of-the art in ALM. Based on a rigorous trade-off, in which we recognize the relevance of multi-cellular systems and the cellular microenvironment, we propose a compact, but flexible concept for space-related cell biological research that is based on light sheet microscopy.« less

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.

Systemic Darwinism

PubMed Central

Winther, Rasmus Grønfeldt

2008-01-01

Darwin's 19th century evolutionary theory of descent with modification through natural selection opened up a multidimensional and integrative conceptual space for biology. We explore three dimensions of this space: explanatory pattern, levels of selection, and degree of difference among units of the same type. Each dimension is defined by a respective pair of poles: law and narrative explanation, organismic and hierarchical selection, and variational and essentialist thinking. As a consequence of conceptual debates in the 20th century biological sciences, the poles of each pair came to be seen as mutually exclusive opposites. A significant amount of 21st century research focuses on systems (e.g., genomic, cellular, organismic, and ecological/global). Systemic Darwinism is emerging in this context. It follows a “compositional paradigm” according to which complex systems and their hierarchical networks of parts are the focus of biological investigation. Through the investigation of systems, Systemic Darwinism promises to reintegrate each dimension of Darwin's original logical space. Moreover, this ideally and potentially unified theory of biological ontology coordinates and integrates a plurality of mathematical biological theories (e.g., self-organization/structure, cladistics/history, and evolutionary genetics/function). Integrative Systemic Darwinism requires communal articulation from a plurality of perspectives. Although it is more general than these, it draws on previous advances in Systems Theory, Systems Biology, and Hierarchy Theory. Systemic Darwinism would greatly further bioengineering research and would provide a significantly deeper and more critical understanding of biological reality. PMID:18697926

Systemic darwinism.

PubMed

Winther, Rasmus Grønfeldt

2008-08-19

Darwin's 19th century evolutionary theory of descent with modification through natural selection opened up a multidimensional and integrative conceptual space for biology. We explore three dimensions of this space: explanatory pattern, levels of selection, and degree of difference among units of the same type. Each dimension is defined by a respective pair of poles: law and narrative explanation, organismic and hierarchical selection, and variational and essentialist thinking. As a consequence of conceptual debates in the 20th century biological sciences, the poles of each pair came to be seen as mutually exclusive opposites. A significant amount of 21st century research focuses on systems (e.g., genomic, cellular, organismic, and ecological/global). Systemic Darwinism is emerging in this context. It follows a "compositional paradigm" according to which complex systems and their hierarchical networks of parts are the focus of biological investigation. Through the investigation of systems, Systemic Darwinism promises to reintegrate each dimension of Darwin's original logical space. Moreover, this ideally and potentially unified theory of biological ontology coordinates and integrates a plurality of mathematical biological theories (e.g., self-organization/structure, cladistics/history, and evolutionary genetics/function). Integrative Systemic Darwinism requires communal articulation from a plurality of perspectives. Although it is more general than these, it draws on previous advances in Systems Theory, Systems Biology, and Hierarchy Theory. Systemic Darwinism would greatly further bioengineering research and would provide a significantly deeper and more critical understanding of biological reality.

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.

Synthetic Biology for Therapeutic Applications

PubMed Central

2015-01-01

Synthetic biology is a relatively new field with the key aim of designing and constructing biological systems with novel functionalities. Today, synthetic biology devices are making their first steps in contributing new solutions to a number of biomedical challenges, such as emerging bacterial antibiotic resistance and cancer therapy. This review discusses some synthetic biology approaches and applications that were recently used in disease mechanism investigation and disease modeling, drug discovery and production, as well as vaccine development and treatment of infectious diseases, cancer, and metabolic disorders. PMID:25098838

Synthetic Biology for Therapeutic Applications

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

Abil, Zhanar; Xiong, Xiong; Zhao, Huimin

Synthetic biology is a relatively new field with the key aim of designing and constructing biological systems with novel functionalities. Today, synthetic biology devices are making their first steps in contributing new solutions to a number of biomedical challenges, such as emerging bacterial antibiotic resistance and cancer therapy. This review discusses some synthetic biology approaches and applications that were recently used in disease mechanism investigation and disease modeling, drug discovery and production, as well as vaccine development and treatment of infectious diseases, cancer, and metabolic disorders.

Synthetic Biology for Therapeutic Applications

DOE PAGES

Abil, Zhanar; Xiong, Xiong; Zhao, Huimin

2014-08-06

Synthetic biology is a relatively new field with the key aim of designing and constructing biological systems with novel functionalities. Today, synthetic biology devices are making their first steps in contributing new solutions to a number of biomedical challenges, such as emerging bacterial antibiotic resistance and cancer therapy. This review discusses some synthetic biology approaches and applications that were recently used in disease mechanism investigation and disease modeling, drug discovery and production, as well as vaccine development and treatment of infectious diseases, cancer, and metabolic disorders.

A methodology for global-sensitivity analysis of time-dependent outputs in systems biology modelling.

PubMed

Sumner, T; Shephard, E; Bogle, I D L

2012-09-07

One of the main challenges in the development of mathematical and computational models of biological systems is the precise estimation of parameter values. Understanding the effects of uncertainties in parameter values on model behaviour is crucial to the successful use of these models. Global sensitivity analysis (SA) can be used to quantify the variability in model predictions resulting from the uncertainty in multiple parameters and to shed light on the biological mechanisms driving system behaviour. We present a new methodology for global SA in systems biology which is computationally efficient and can be used to identify the key parameters and their interactions which drive the dynamic behaviour of a complex biological model. The approach combines functional principal component analysis with established global SA techniques. The methodology is applied to a model of the insulin signalling pathway, defects of which are a major cause of type 2 diabetes and a number of key features of the system are identified.

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.

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.

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).

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.

On the optimal design of molecular sensing interfaces with lipid bilayer assemblies - A knowledge based approach

NASA Astrophysics Data System (ADS)

Siontorou, Christina G.

2012-12-01

Biosensors are analytic devices that incorporate a biochemical recognition system (biological, biologicalderived or biomimic: enzyme, antibody, DNA, receptor, etc.) in close contact with a physicochemical transducer (electrochemical, optical, piezoelectric, conductimetric, etc.) that converts the biochemical information, produced by the specific biological recognition reaction (analyte-biomolecule binding), into a chemical or physical output signal, related to the concentration of the analyte in the measuring sample. The biosensing concept is based on natural chemoreception mechanisms, which are feasible over/within/by means of a biological membrane, i.e., a structured lipid bilayer, incorporating or attached to proteinaceous moieties that regulate molecular recognition events which trigger ion flux changes (facilitated or passive) through the bilayer. The creation of functional structures that are similar to natural signal transduction systems, correlating and interrelating compatibly and successfully the physicochemical transducer with the lipid film that is self-assembled on its surface while embedding the reconstituted biological recognition system, and at the same time manage to satisfy the basic conditions for measuring device development (simplicity, easy handling, ease of fabrication) is far from trivial. The aim of the present work is to present a methodological framework for designing such molecular sensing interfaces, functioning within a knowledge-based system built on an ontological platform for supplying sub-systems options, compatibilities, and optimization parameters.

Conceptual Model-Based Systems Biology: Mapping Knowledge and Discovering Gaps in the mRNA Transcription Cycle

PubMed Central

Somekh, Judith; Choder, Mordechai; Dori, Dov

2012-01-01

We propose a Conceptual Model-based Systems Biology framework for qualitative modeling, executing, and eliciting knowledge gaps in molecular biology systems. The framework is an adaptation of Object-Process Methodology (OPM), a graphical and textual executable modeling language. OPM enables concurrent representation of the system's structure—the objects that comprise the system, and behavior—how processes transform objects over time. Applying a top-down approach of recursively zooming into processes, we model a case in point—the mRNA transcription cycle. Starting with this high level cell function, we model increasingly detailed processes along with participating objects. Our modeling approach is capable of modeling molecular processes such as complex formation, localization and trafficking, molecular binding, enzymatic stimulation, and environmental intervention. At the lowest level, similar to the Gene Ontology, all biological processes boil down to three basic molecular functions: catalysis, binding/dissociation, and transporting. During modeling and execution of the mRNA transcription model, we discovered knowledge gaps, which we present and classify into various types. We also show how model execution enhances a coherent model construction. Identification and pinpointing knowledge gaps is an important feature of the framework, as it suggests where research should focus and whether conjectures about uncertain mechanisms fit into the already verified model. PMID:23308089

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

Development and implementation of an expert system to improve the control of nitrification and denitrification in the Vic wastewater treatment plant.

PubMed

Ribas, F; Rodríguez-Roda, I; Serrat, J; Clara, P; Comas, J

2008-05-01

Wastewater treatment plants employ various physical, chemical and biological processes to reduce pollutants from raw wastewater. One of the most important is the biological nitrogen removal process through nitrification and denitrification steps taking place in various sections of the biological reactor. One of the most extensively used configurations to achieve the biological nitrogen removal is an activated sludge system using oxidation ditch or extended aeration. To improve nitrogen removal in the wastewater treatment plant (WWTP) of Vic (Catalonia, NE Spain), the automatic aeration control system was complemented with an Expert System to always provide the most appropriate aeration or anoxia sequence based on the values of ammonium and nitrates given by an automatic analyzer. This article illustrates the development and implementation of this knowledge-based system within the framework of a Decision Support System, which performs SCADA functions. The paper also shows that the application of the decision support system in the Vic WWTP resulted in significant improvements to the biological nitrogen removal.

Bayesian parameter estimation for nonlinear modelling of biological pathways.

PubMed

Ghasemi, Omid; Lindsey, Merry L; Yang, Tianyi; Nguyen, Nguyen; Huang, Yufei; Jin, Yu-Fang

2011-01-01

The availability of temporal measurements on biological experiments has significantly promoted research areas in systems biology. To gain insight into the interaction and regulation of biological systems, mathematical frameworks such as ordinary differential equations have been widely applied to model biological pathways and interpret the temporal data. Hill equations are the preferred formats to represent the reaction rate in differential equation frameworks, due to their simple structures and their capabilities for easy fitting to saturated experimental measurements. However, Hill equations are highly nonlinearly parameterized functions, and parameters in these functions cannot be measured easily. Additionally, because of its high nonlinearity, adaptive parameter estimation algorithms developed for linear parameterized differential equations cannot be applied. Therefore, parameter estimation in nonlinearly parameterized differential equation models for biological pathways is both challenging and rewarding. In this study, we propose a Bayesian parameter estimation algorithm to estimate parameters in nonlinear mathematical models for biological pathways using time series data. We used the Runge-Kutta method to transform differential equations to difference equations assuming a known structure of the differential equations. This transformation allowed us to generate predictions dependent on previous states and to apply a Bayesian approach, namely, the Markov chain Monte Carlo (MCMC) method. We applied this approach to the biological pathways involved in the left ventricle (LV) response to myocardial infarction (MI) and verified our algorithm by estimating two parameters in a Hill equation embedded in the nonlinear model. We further evaluated our estimation performance with different parameter settings and signal to noise ratios. Our results demonstrated the effectiveness of the algorithm for both linearly and nonlinearly parameterized dynamic systems. Our proposed Bayesian algorithm successfully estimated parameters in nonlinear mathematical models for biological pathways. This method can be further extended to high order systems and thus provides a useful tool to analyze biological dynamics and extract information using temporal data.

Error-based analysis of optimal tuning functions explains phenomena observed in sensory neurons.

PubMed

Yaeli, Steve; Meir, Ron

2010-01-01

Biological systems display impressive capabilities in effectively responding to environmental signals in real time. There is increasing evidence that organisms may indeed be employing near optimal Bayesian calculations in their decision-making. An intriguing question relates to the properties of optimal encoding methods, namely determining the properties of neural populations in sensory layers that optimize performance, subject to physiological constraints. Within an ecological theory of neural encoding/decoding, we show that optimal Bayesian performance requires neural adaptation which reflects environmental changes. Specifically, we predict that neuronal tuning functions possess an optimal width, which increases with prior uncertainty and environmental noise, and decreases with the decoding time window. Furthermore, even for static stimuli, we demonstrate that dynamic sensory tuning functions, acting at relatively short time scales, lead to improved performance. Interestingly, the narrowing of tuning functions as a function of time was recently observed in several biological systems. Such results set the stage for a functional theory which may explain the high reliability of sensory systems, and the utility of neuronal adaptation occurring at multiple time scales.

The Role of Noise in Brain Function

NASA Astrophysics Data System (ADS)

Roy, S.; Llinás, R.

2012-12-01

Noise plays a fundamental role in all living organisms from the earliest prokaryotes to advanced mammalian forms, such as ourselves. In the context of living organisms, the term 'noise' usually refers to the variance amongst measurements obtained from repeated identical experimental conditions, or from output signals from these systems. It is noteworthy that both these conditions are universally characterized by the presence of background fluctuations. In non-biological systems, such as electronics or in communications sciences, where the aim is to send error-free messages, noise was generally regarded as a problem. The discovery of Stochastic Resonances (SR) in non-linear dynamics brought a shift of perception where noise, rather than representing a problem, became fundamental to system function, especially so in biology. The question now is: to what extent is biological function dependent on random noise. Indeed, it seems feasible that noise also plays an important role in neuronal communication and oscillatory synchronization. Given this approach, it follows that determining Fisher information content could be relevant in neuronal communication. It also seems possible that the principle of least time, and that of the sum over histories, could be important basic principles in understanding the coherence dynamics responsible for action and perception. Ultimately, external noise cancellation combined with intrinsic noise signal embedding and, the use of the principle of least time may be considered an essential step in the organization of central nervous system (CNS) function.

A Personal Journey of Discovery: Developing Technology and Changing Biology

NASA Astrophysics Data System (ADS)

Hood, Lee

2008-07-01

This autobiographical article describes my experiences in developing chemically based, biological technologies for deciphering biological information: DNA, RNA, proteins, interactions, and networks. The instruments developed include protein and DNA sequencers and synthesizers, as well as ink-jet technology for synthesizing DNA chips. Diverse new strategies for doing biology also arose from novel applications of these instruments. The functioning of these instruments can be integrated to generate powerful new approaches to cloning and characterizing genes from a small amount of protein sequence or to using gene sequences to synthesize peptide fragments so as to characterize various properties of the proteins. I also discuss the five paradigm changes in which I have participated: the development and integration of biological instrumentation; the human genome project; cross-disciplinary biology; systems biology; and predictive, personalized, preventive, and participatory (P4) medicine. Finally, I discuss the origins, the philosophy, some accomplishments, and the future trajectories of the Institute for Systems Biology.

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.

Tomato functional genomics database (TFGD): a comprehensive collection and analysis package for tomato functional genomics

USDA-ARS?s Scientific Manuscript database

Tomato Functional Genomics Database (TFGD; http://ted.bti.cornell.edu) provides a comprehensive systems biology resource to store, mine, analyze, visualize and integrate large-scale tomato functional genomics datasets. The database is expanded from the previously described Tomato Expression Database...

Functionalized carbon nanotubes: biomedical applications

PubMed Central

Vardharajula, Sandhya; Ali, Sk Z; Tiwari, Pooja M; Eroğlu, Erdal; Vig, Komal; Dennis, Vida A; Singh, Shree R

2012-01-01

Carbon nanotubes (CNTs) are emerging as novel nanomaterials for various biomedical applications. CNTs can be used to deliver a variety of therapeutic agents, including biomolecules, to the target disease sites. In addition, their unparalleled optical and electrical properties make them excellent candidates for bioimaging and other biomedical applications. However, the high cytotoxicity of CNTs limits their use in humans and many biological systems. The biocompatibility and low cytotoxicity of CNTs are attributed to size, dose, duration, testing systems, and surface functionalization. The functionalization of CNTs improves their solubility and biocompatibility and alters their cellular interaction pathways, resulting in much-reduced cytotoxic effects. Functionalized CNTs are promising novel materials for a variety of biomedical applications. These potential applications are particularly enhanced by their ability to penetrate biological membranes with relatively low cytotoxicity. This review is directed towards the overview of CNTs and their functionalization for biomedical applications with minimal cytotoxicity. PMID:23091380

Functionalized carbon nanotubes: biomedical applications.

PubMed

Vardharajula, Sandhya; Ali, Sk Z; Tiwari, Pooja M; Eroğlu, Erdal; Vig, Komal; Dennis, Vida A; Singh, Shree R

2012-01-01

Carbon nanotubes (CNTs) are emerging as novel nanomaterials for various biomedical applications. CNTs can be used to deliver a variety of therapeutic agents, including biomolecules, to the target disease sites. In addition, their unparalleled optical and electrical properties make them excellent candidates for bioimaging and other biomedical applications. However, the high cytotoxicity of CNTs limits their use in humans and many biological systems. The biocompatibility and low cytotoxicity of CNTs are attributed to size, dose, duration, testing systems, and surface functionalization. The functionalization of CNTs improves their solubility and biocompatibility and alters their cellular interaction pathways, resulting in much-reduced cytotoxic effects. Functionalized CNTs are promising novel materials for a variety of biomedical applications. These potential applications are particularly enhanced by their ability to penetrate biological membranes with relatively low cytotoxicity. This review is directed towards the overview of CNTs and their functionalization for biomedical applications with minimal cytotoxicity.

Massive-scale gene co-expression network construction and robustness testing using random matrix theory.

PubMed

Gibson, Scott M; Ficklin, Stephen P; Isaacson, Sven; Luo, Feng; Feltus, Frank A; Smith, Melissa C

2013-01-01

The study of gene relationships and their effect on biological function and phenotype is a focal point in systems biology. Gene co-expression networks built using microarray expression profiles are one technique for discovering and interpreting gene relationships. A knowledge-independent thresholding technique, such as Random Matrix Theory (RMT), is useful for identifying meaningful relationships. Highly connected genes in the thresholded network are then grouped into modules that provide insight into their collective functionality. While it has been shown that co-expression networks are biologically relevant, it has not been determined to what extent any given network is functionally robust given perturbations in the input sample set. For such a test, hundreds of networks are needed and hence a tool to rapidly construct these networks. To examine functional robustness of networks with varying input, we enhanced an existing RMT implementation for improved scalability and tested functional robustness of human (Homo sapiens), rice (Oryza sativa) and budding yeast (Saccharomyces cerevisiae). We demonstrate dramatic decrease in network construction time and computational requirements and show that despite some variation in global properties between networks, functional similarity remains high. Moreover, the biological function captured by co-expression networks thresholded by RMT is highly robust.

JPRS Report, Science & Technology. Europe: Economic Competitiveness

DTIC Science & Technology

1992-02-24

Health Systems This area covers the harmonisation of methodologies and protocols in epidemiological, biological , clinical and technological...substances and biological agents on human health; and the application and enhancement of biomedical tech- nology to medical health care. Major Health...Work will cover the completion and integration of the genetic and physical maps; the genetic basis for biolog - ical functions; and the setting up a

Cooperativity to increase Turing pattern space for synthetic biology.

PubMed

Diambra, Luis; Senthivel, Vivek Raj; Menendez, Diego Barcena; Isalan, Mark

2015-02-20

It is hard to bridge the gap between mathematical formulations and biological implementations of Turing patterns, yet this is necessary for both understanding and engineering these networks with synthetic biology approaches. Here, we model a reaction-diffusion system with two morphogens in a monostable regime, inspired by components that we recently described in a synthetic biology study in mammalian cells.1 The model employs a single promoter to express both the activator and inhibitor genes and produces Turing patterns over large regions of parameter space, using biologically interpretable Hill function reactions. We applied a stability analysis and identified rules for choosing biologically tunable parameter relationships to increase the likelihood of successful patterning. We show how to control Turing pattern sizes and time evolution by manipulating the values for production and degradation relationships. More importantly, our analysis predicts that steep dose-response functions arising from cooperativity are mandatory for Turing patterns. Greater steepness increases parameter space and even reduces the requirement for differential diffusion between activator and inhibitor. These results demonstrate some of the limitations of linear scenarios for reaction-diffusion systems and will help to guide projects to engineer synthetic Turing patterns.

On the Interplay between the Evolvability and Network Robustness in an Evolutionary Biological Network: A Systems Biology Approach

PubMed Central

Chen, Bor-Sen; Lin, Ying-Po

2011-01-01

In the evolutionary process, the random transmission and mutation of genes provide biological diversities for natural selection. In order to preserve functional phenotypes between generations, gene networks need to evolve robustly under the influence of random perturbations. Therefore, the robustness of the phenotype, in the evolutionary process, exerts a selection force on gene networks to keep network functions. However, gene networks need to adjust, by variations in genetic content, to generate phenotypes for new challenges in the network’s evolution, ie, the evolvability. Hence, there should be some interplay between the evolvability and network robustness in evolutionary gene networks. In this study, the interplay between the evolvability and network robustness of a gene network and a biochemical network is discussed from a nonlinear stochastic system point of view. It was found that if the genetic robustness plus environmental robustness is less than the network robustness, the phenotype of the biological network is robust in evolution. The tradeoff between the genetic robustness and environmental robustness in evolution is discussed from the stochastic stability robustness and sensitivity of the nonlinear stochastic biological network, which may be relevant to the statistical tradeoff between bias and variance, the so-called bias/variance dilemma. Further, the tradeoff could be considered as an antagonistic pleiotropic action of a gene network and discussed from the systems biology perspective. PMID:22084563

Molecular phenology in plants: in natura systems biology for the comprehensive understanding of seasonal responses under natural environments.

PubMed

Kudoh, Hiroshi

2016-04-01

Phenology refers to the study of seasonal schedules of organisms. Molecular phenology is defined here as the study of the seasonal patterns of organisms captured by molecular biology techniques. The history of molecular phenology is reviewed briefly in relation to advances in the quantification technology of gene expression. High-resolution molecular phenology (HMP) data have enabled us to study phenology with an approach of in natura systems biology. I review recent analyses of FLOWERING LOCUS C (FLC), a temperature-responsive repressor of flowering, along the six steps in the typical flow of in natura systems biology. The extensive studies of the regulation of FLC have made this example a successful case in which a comprehensive understanding of gene functions has been progressing. The FLC-mediated long-term memory of past temperatures creates time lags with other seasonal signals, such as photoperiod and short-term temperature. Major signals that control flowering time have a phase lag between them under natural conditions, and hypothetical phase lag calendars are proposed as mechanisms of season detection in plants. Transcriptomic HMP brings a novel strategy to the study of molecular phenology, because it provides a comprehensive representation of plant functions. I discuss future perspectives of molecular phenology from the standpoints of molecular biology, evolutionary biology and ecology. © 2015 The Author. New Phytologist © 2015 New Phytologist Trust.

A Systems Biology Analysis Unfolds the Molecular Pathways and Networks of Two Proteobacteria in Spaceflight and Simulated Microgravity Conditions

NASA Astrophysics Data System (ADS)

Roy, Raktim; Phani Shilpa, P.; Bagh, Sangram

2016-09-01

Bacteria are important organisms for space missions due to their increased pathogenesis in microgravity that poses risks to the health of astronauts and for projected synthetic biology applications at the space station. We understand little about the effect, at the molecular systems level, of microgravity on bacteria, despite their significant incidence. In this study, we proposed a systems biology pipeline and performed an analysis on published gene expression data sets from multiple seminal studies on Pseudomonas aeruginosa and Salmonella enterica serovar Typhimurium under spaceflight and simulated microgravity conditions. By applying gene set enrichment analysis on the global gene expression data, we directly identified a large number of new, statistically significant cellular and metabolic pathways involved in response to microgravity. Alteration of metabolic pathways in microgravity has rarely been reported before, whereas in this analysis metabolic pathways are prevalent. Several of those pathways were found to be common across studies and species, indicating a common cellular response in microgravity. We clustered genes based on their expression patterns using consensus non-negative matrix factorization. The genes from different mathematically stable clusters showed protein-protein association networks with distinct biological functions, suggesting the plausible functional or regulatory network motifs in response to microgravity. The newly identified pathways and networks showed connection with increased survival of pathogens within macrophages, virulence, and antibiotic resistance in microgravity. Our work establishes a systems biology pipeline and provides an integrated insight into the effect of microgravity at the molecular systems level.

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].

Functionalized carbon nanotubes for potential medicinal applications.

PubMed

Zhang, Yi; Bai, Yuhong; Yan, Bing

2010-06-01

Functionalized carbon nanotubes display unique properties that enable a variety of medicinal applications, including the diagnosis and treatment of cancer, infectious diseases and central nervous system disorders, and applications in tissue engineering. These potential applications are particularly encouraged by their ability to penetrate biological membranes and relatively low toxicity. High aspect ratio, unique optical property and the likeness as small molecule make carbon nanotubes an unusual allotrope of element carbon. After functionalization, carbon nanotubes display potentials for a variety of medicinal applications, including the diagnosis and treatment of cancer, infectious diseases and central nervous system disorders, and applications in tissue engineering. These potential applications are particularly encouraged by their ability to penetrate biological membranes and relatively low toxicity. (c) 2010 Elsevier Ltd. All rights reserved.

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

Partial regularity of weak solutions to a PDE system with cubic nonlinearity

NASA Astrophysics Data System (ADS)

Liu, Jian-Guo; Xu, Xiangsheng

2018-04-01

In this paper we investigate regularity properties of weak solutions to a PDE system that arises in the study of biological transport networks. The system consists of a possibly singular elliptic equation for the scalar pressure of the underlying biological network coupled to a diffusion equation for the conductance vector of the network. There are several different types of nonlinearities in the system. Of particular mathematical interest is a term that is a polynomial function of solutions and their partial derivatives and this polynomial function has degree three. That is, the system contains a cubic nonlinearity. Only weak solutions to the system have been shown to exist. The regularity theory for the system remains fundamentally incomplete. In particular, it is not known whether or not weak solutions develop singularities. In this paper we obtain a partial regularity theorem, which gives an estimate for the parabolic Hausdorff dimension of the set of possible singular points.

Order or chaos in Boolean gene networks depends on the mean fraction of canalizing functions

NASA Astrophysics Data System (ADS)

Karlsson, Fredrik; Hörnquist, Michael

2007-10-01

We explore the connection between order/chaos in Boolean networks and the naturally occurring fraction of canalizing functions in such systems. This fraction turns out to give a very clear indication of whether the system possesses ordered or chaotic dynamics, as measured by Derrida plots, and also the degree of order when we compare different networks with the same number of vertices and edges. By studying also a wide distribution of indegrees in a network, we show that the mean probability of canalizing functions is a more reliable indicator of the type of dynamics for a finite network than the classical result on stability relating the bias to the mean indegree. Finally, we compare by direct simulations two biologically derived networks with networks of similar sizes but with power-law and Poisson distributions of indegrees, respectively. The biologically motivated networks are not more ordered than the latter, and in one case the biological network is even chaotic while the others are not.

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.

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.

Emergent properties of interacting populations of spiking neurons.

PubMed

Cardanobile, Stefano; Rotter, Stefan

2011-01-01

Dynamic neuronal networks are a key paradigm of increasing importance in brain research, concerned with the functional analysis of biological neuronal networks and, at the same time, with the synthesis of artificial brain-like systems. In this context, neuronal network models serve as mathematical tools to understand the function of brains, but they might as well develop into future tools for enhancing certain functions of our nervous system. Here, we present and discuss our recent achievements in developing multiplicative point processes into a viable mathematical framework for spiking network modeling. The perspective is that the dynamic behavior of these neuronal networks is faithfully reflected by a set of non-linear rate equations, describing all interactions on the population level. These equations are similar in structure to Lotka-Volterra equations, well known by their use in modeling predator-prey relations in population biology, but abundant applications to economic theory have also been described. We present a number of biologically relevant examples for spiking network function, which can be studied with the help of the aforementioned correspondence between spike trains and specific systems of non-linear coupled ordinary differential equations. We claim that, enabled by the use of multiplicative point processes, we can make essential contributions to a more thorough understanding of the dynamical properties of interacting neuronal populations.

Emergent Properties of Interacting Populations of Spiking Neurons

PubMed Central

Cardanobile, Stefano; Rotter, Stefan

2011-01-01

Dynamic neuronal networks are a key paradigm of increasing importance in brain research, concerned with the functional analysis of biological neuronal networks and, at the same time, with the synthesis of artificial brain-like systems. In this context, neuronal network models serve as mathematical tools to understand the function of brains, but they might as well develop into future tools for enhancing certain functions of our nervous system. Here, we present and discuss our recent achievements in developing multiplicative point processes into a viable mathematical framework for spiking network modeling. The perspective is that the dynamic behavior of these neuronal networks is faithfully reflected by a set of non-linear rate equations, describing all interactions on the population level. These equations are similar in structure to Lotka-Volterra equations, well known by their use in modeling predator-prey relations in population biology, but abundant applications to economic theory have also been described. We present a number of biologically relevant examples for spiking network function, which can be studied with the help of the aforementioned correspondence between spike trains and specific systems of non-linear coupled ordinary differential equations. We claim that, enabled by the use of multiplicative point processes, we can make essential contributions to a more thorough understanding of the dynamical properties of interacting neuronal populations. PMID:22207844

Network news: innovations in 21st century systems biology.

PubMed

Arkin, Adam P; Schaffer, David V

2011-03-18

A decade ago, seminal perspectives and papers set a strong vision for the field of systems biology, and a number of these themes have flourished. Here, we describe key technologies and insights that have elucidated the evolution, architecture, and function of cellular networks, ultimately leading to the first predictive genome-scale regulatory and metabolic models of organisms. Can systems approaches bridge the gap between correlative analysis and mechanistic insights? Copyright © 2011 Elsevier Inc. 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.

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.

Fundamental and functional aspects of mesoscopic architectures with examples in physics, cell biology, and chemistry.

PubMed

Kalay, Ziya

2011-08-01

How small can a macroscopic object be made without losing its intended function? Obviously, the smallest possible size is determined by the size of an atom, but it is not so obvious how many atoms are required to assemble an object so small, and yet that performs the same function as its macroscopic counterpart. In this review, we are concerned with objects of intermediate nature, lying between the microscopic and the macroscopic world. In physics and chemistry literature, this regime in-between is often called mesoscopic, and is known to bear interesting and counterintuitive features. After a brief introduction to the concept of mesoscopic systems from the perspective of physics, we discuss the functional aspects of mesoscopic architectures in cell biology, and supramolecular chemistry through many examples from the literature. We argue that the biochemistry of the cell is largely regulated by mesoscopic functional architectures; however, the significance of mesoscopic phenomena seems to be quite underappreciated in biological sciences. With this motivation, one of our main purposes here is to emphasize the critical role that mesoscopic structures play in cell biology and biochemistry.

Space Shuttle food galley design concept

NASA Technical Reports Server (NTRS)

Heidelbaugh, N. D.; Smith, M. C.; Fischer, R.; Cooper, B.

1974-01-01

A food galley has been designed for the crew compartment of the NASA Space Shuttle Orbiter. The rationale for the definition of this design was based upon assignment of priorities to each functional element of the total food system. Principle priority categories were assigned in the following order: food quality, nutrition, food packaging, menu acceptance, meal preparation efficiency, total system weight, total system volume, and total power requirements. Hence, the galley was designed using an 'inside-out' approach which first considered the food and related biological functions and subsequently proceeded 'outward' from the food to encompass supporting hardware. The resulting galley is an optimal design incorporating appropriate priorities for trade-offs between biological and engineering constraints. This design approach is offered as a model for the design of life support systems.

Mobilizing the rhizosphere microbiome to enhance orchard system resilience

USDA-ARS?s Scientific Manuscript database

Soils possess a wealth of biological resources that can be harnessed for use in the optimization of plant performance in agroecosystems. Functional biological control outcomes, beyond those realized based upon introduction of synthetic microbiomes, have been documented in a variety of instances, an...

Opportunities and questions for the fundamental biological sciences in space

NASA Technical Reports Server (NTRS)

Sharp, Joseph C.; Vernikos, Joan

1992-01-01

The nature of biological issues which can be addressed during long-term space missions is briefly discussed. These issues include structure, from cell to organ to organism; function, the regulation of systems such as immunology, neural sciences, and behavior; and reproduction and development.

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.

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

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.

Thiosulfoxide (Sulfane) Sulfur: New Chemistry and New Regulatory Roles in Biology

PubMed Central

Toohey, John I.; Cooper, Arthur J. L.

2014-01-01

The understanding of sulfur bonding is undergoing change. Old theories on hypervalency of sulfur and the nature of the chalcogen-chalcogen bond are now questioned. At the same time, there is a rapidly expanding literature on the effects of sulfur in regulating biological systems. The two fields are inter-related because the new understanding of the thiosulfoxide bond helps to explain the newfound roles of sulfur in biology. This review examines the nature of thiosulfoxide (sulfane, S0) sulfur, the history of its regulatory role, its generation in biological systems, and its functions in cells. The functions include synthesis of cofactors (molybdenum cofactor, iron-sulfur clusters), sulfuration of tRNA, modulation of enzyme activities, and regulating the redox environment by several mechanisms (including the enhancement of the reductive capacity of glutathione). A brief review of the analogous form of selenium suggests that the toxicity of selenium may be due to over-reduction caused by the powerful reductive activity of glutathione perselenide. PMID:25153879

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.

A machine-learned analysis of human gene polymorphisms modulating persisting pain points at major roles of neuroimmune processes.

PubMed

Kringel, Dario; Lippmann, Catharina; Parnham, Michael J; Kalso, Eija; Ultsch, Alfred; Lötsch, Jörn

2018-06-19

Human genetic research has implicated functional variants of more than one hundred genes in the modulation of persisting pain. Artificial intelligence and machine learning techniques may combine this knowledge with results of genetic research gathered in any context, which permits the identification of the key biological processes involved in chronic sensitization to pain. Based on published evidence, a set of 110 genes carrying variants reported to be associated with modulation of the clinical phenotype of persisting pain in eight different clinical settings was submitted to unsupervised machine-learning aimed at functional clustering. Subsequently, a mathematically supported subset of genes, comprising those most consistently involved in persisting pain, was analyzed by means of computational functional genomics in the Gene Ontology knowledgebase. Clustering of genes with evidence for a modulation of persisting pain elucidated a functionally heterogeneous set. The situation cleared when the focus was narrowed to a genetic modulation consistently observed throughout several clinical settings. On this basis, two groups of biological processes, the immune system and nitric oxide signaling, emerged as major players in sensitization to persisting pain, which is biologically highly plausible and in agreement with other lines of pain research. The present computational functional genomics-based approach provided a computational systems-biology perspective on chronic sensitization to pain. Human genetic control of persisting pain points to the immune system as a source of potential future targets for drugs directed against persisting pain. Contemporary machine-learned methods provide innovative approaches to knowledge discovery from previous evidence. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Multiview hyperspectral topography of tissue structural and functional characteristics

NASA Astrophysics Data System (ADS)

Zhang, Shiwu; Liu, Peng; Huang, Jiwei; Xu, Ronald

2012-12-01

Accurate and in vivo characterization of structural, functional, and molecular characteristics of biological tissue will facilitate quantitative diagnosis, therapeutic guidance, and outcome assessment in many clinical applications, such as wound healing, cancer surgery, and organ transplantation. However, many clinical imaging systems have limitations and fail to provide noninvasive, real time, and quantitative assessment of biological tissue in an operation room. To overcome these limitations, we developed and tested a multiview hyperspectral imaging system. The multiview hyperspectral imaging system integrated the multiview and the hyperspectral imaging techniques in a single portable unit. Four plane mirrors are cohered together as a multiview reflective mirror set with a rectangular cross section. The multiview reflective mirror set was placed between a hyperspectral camera and the measured biological tissue. For a single image acquisition task, a hyperspectral data cube with five views was obtained. The five-view hyperspectral image consisted of a main objective image and four reflective images. Three-dimensional topography of the scene was achieved by correlating the matching pixels between the objective image and the reflective images. Three-dimensional mapping of tissue oxygenation was achieved using a hyperspectral oxygenation algorithm. The multiview hyperspectral imaging technique is currently under quantitative validation in a wound model, a tissue-simulating blood phantom, and an in vivo biological tissue model. The preliminary results have demonstrated the technical feasibility of using multiview hyperspectral imaging for three-dimensional topography of tissue functional properties.

Artificial Synaptic Devices Based on Natural Chicken Albumen Coupled Electric-Double-Layer Transistors

NASA Astrophysics Data System (ADS)

Wu, Guodong; Feng, Ping; Wan, Xiang; Zhu, Liqiang; Shi, Yi; Wan, Qing

2016-03-01

Recent progress in using biomaterials to fabricate functional electronics has got growing attention for the new generation of environmentally friendly and biocompatible electronic devices. As a kind of biological material with rich source, proteins are essential natural component of all organisms. At the same time, artificial synaptic devices are of great significance for neuromorphic systems because they can emulate the signal process and memory behaviors of biological synapses. In this report, natural chicken albumen with high proton conductivity was used as the coupling electrolyte film for organic/inorganic hybrid synaptic devices fabrication. Some important synaptic functions including paired-pulse facilitation, dynamic filtering, short-term to long-term memory transition and spatial summation and shunting inhibition were successfully mimicked. Our results are very interesting for biological friendly artificial neuron networks and neuromorphic systems.

Biological weighting function for the inhibition of phytoplankton photosynthesis by ultraviolet radiation

NASA Technical Reports Server (NTRS)

Cullen, John J.; Neale, Patrick J.; Lesser, Michael P.

1992-01-01

Severe reduction of stratospheric ozone over Antarctica has focused increasing concern on the biological effects of ultraviolet-B (UVB) radiation (280 to 320 nanometers). Measurements of photosynthesis from an experimental system, in which phytoplankton are exposed to a broad range of irradiance treatments, are fit to an analytical model to provide the spectral biological weighting function that can be used to predict the short-term effects of ozone depletion on aquatic photosynthesis. Results show that UVA (320 to 400 nanometers) significantly inhibits the photosynthesis of a marine diatom and a dinoflagellate, and that the effects of UVB are even more severe. Application of the model suggests that the Antarctic ozone hole might reduce near-surface photosynthesis by 12 to 15 percent, but less so at depth. The experimental system makes possible routine estimation of spectral weightings for natural phytoplankton.

WebBio, a web-based management and analysis system for patient data of biological products in hospital.

PubMed

Lu, Ying-Hao; Kuo, Chen-Chun; Huang, Yaw-Bin

2011-08-01

We selected HTML, PHP and JavaScript as the programming languages to build "WebBio", a web-based system for patient data of biological products and used MySQL as database. WebBio is based on the PHP-MySQL suite and is run by Apache server on Linux machine. WebBio provides the functions of data management, searching function and data analysis for 20 kinds of biological products (plasma expanders, human immunoglobulin and hematological products). There are two particular features in WebBio: (1) pharmacists can rapidly find out whose patients used contaminated products for medication safety, and (2) the statistics charts for a specific product can be automatically generated to reduce pharmacist's work loading. WebBio has successfully turned traditional paper work into web-based data management.

RAFT Nano-constructs: surfing to biological applications.

PubMed

Boturyn, Didier; Defrancq, Eric; Dolphin, Gunnar T; Garcia, Julian; Labbe, Pierre; Renaudet, Olivier; Dumy, Pascal

2008-02-01

Biologically programmed molecular recognition provides the basis of all natural systems and supplies evolution-optimized functional materials from self-assembly of a limited number of molecular building blocks. Biomolecules such as peptides, nucleic acids and carbohydrates represent a diverse supply of structural building blocks for the chemist to design and fabricate new functional nanostructured architectures. In this context, we review here the chemistry we have developed to conjugate peptides with nucleic acids, carbohydrates, and organic molecules, as well as combinations thereof using a template-assembled approach. With this methodology, we have prepared new integrated functional systems exhibiting designed properties in the field of nanovectors, biosensors as well as controlled peptide self-assembly. Thus this molecular engineering approach allows for the rational design of systems with integrated tailor-made properties and paves the way to more elaborate applications by bottom-up design in the domain of nanobiosciences.

Improving Microbial Genome Annotations in an Integrated Database Context

PubMed Central

Chen, I-Min A.; Markowitz, Victor M.; Chu, Ken; Anderson, Iain; Mavromatis, Konstantinos; Kyrpides, Nikos C.; Ivanova, Natalia N.

2013-01-01

Effective comparative analysis of microbial genomes requires a consistent and complete view of biological data. Consistency regards the biological coherence of annotations, while completeness regards the extent and coverage of functional characterization for genomes. We have developed tools that allow scientists to assess and improve the consistency and completeness of microbial genome annotations in the context of the Integrated Microbial Genomes (IMG) family of systems. All publicly available microbial genomes are characterized in IMG using different functional annotation and pathway resources, thus providing a comprehensive framework for identifying and resolving annotation discrepancies. A rule based system for predicting phenotypes in IMG provides a powerful mechanism for validating functional annotations, whereby the phenotypic traits of an organism are inferred based on the presence of certain metabolic reactions and pathways and compared to experimentally observed phenotypes. The IMG family of systems are available at http://img.jgi.doe.gov/. PMID:23424620

[THE INCONSISTENCIES OF REGULATION OF METABOLISM IN PHYLOGENESIS AT THREE LEVELS OF "RELATIVE BIOLOGICAL PERFECTION": ETIOLOGY OF METABOLIC PANDEMICS].

PubMed

Titov, V N

2015-11-01

The regulation of metabolism in vivo can be comprehended by considering stages of becoming inphylogenesis of humoral, hormonal, vegetative regulators separately: at the level of cells; in paracrin-regulated cenosises of cells; organs and systems under open blood circulation and closed system of blood flow. The levels of regulations formed at different stages of phylogenesis. Their completion occurred at achievement of "relative biological perfection". Only this way need of cells in functional, structural interaction and forming of multicellular developed. The development of organs and systems of organs also completed at the level of "relative biological perfection". From the same level the third stage of becoming of regulation of metabolism at the level of organism started. When three conditions of "relative biological perfection" achieved consequently at level in vivo are considered in species Homo sapiens using system approach it is detected that "relative biological perfection" in vivo is accompanied by different inconsistencies of regulation of metabolism. They are etiologic factors of "metabolic pandemics ". The inconsistencies (etiological factors) are consider as exemplified by local (at the level of paracrin-regulated cenosises of cells) and system (at the level of organism) regulation of biological reaction metabolism-microcirculation that results in dysfunction of target organs and development of pathogenesis of essential metabolic arterial hypertension. The article describes phylogenetic difference between visceral fatty cells and adpocytes, regulation of metabolism by phylogenetically late insulin, reaction of albumin at increasing of content of unesterified fatty acids in blood plasma, difference of function of resident macrophage and monocytes-macrophages in pathogenesis of atherosclerosis, metabolic syndrome, insulin resistance, obesity, under diabetes mellitus and essential metabolic arterial hypertension.

Systems biology of meridians, acupoints, and chinese herbs in disease.

PubMed

Lin, Li-Ling; Wang, Ya-Hui; Lai, Chi-Yu; Chau, Chan-Lao; Su, Guan-Chin; Yang, Chun-Yi; Lou, Shu-Ying; Chen, Szu-Kai; Hsu, Kuan-Hao; Lai, Yen-Ling; Wu, Wei-Ming; Huang, Jian-Long; Liao, Chih-Hsin; Juan, Hsueh-Fen

2012-01-01

Meridians, acupoints, and Chinese herbs are important components of traditional Chinese medicine (TCM). They have been used for disease treatment and prevention and as alternative and complementary therapies. Systems biology integrates omics data, such as transcriptional, proteomic, and metabolomics data, in order to obtain a more global and complete picture of biological activity. To further understand the existence and functions of the three components above, we reviewed relevant research in the systems biology literature and found many recent studies that indicate the value of acupuncture and Chinese herbs. Acupuncture is useful in pain moderation and relieves various symptoms arising from acute spinal cord injury and acute ischemic stroke. Moreover, Chinese herbal extracts have been linked to wound repair, the alleviation of postmenopausal osteoporosis severity, and anti-tumor effects, among others. Different acupoints, variations in treatment duration, and herbal extracts can be used to alleviate various symptoms and conditions and to regulate biological pathways by altering gene and protein expression. Our paper demonstrates how systems biology has helped to establish a platform for investigating the efficacy of TCM in treating different diseases and improving treatment strategies.

Unsupervised Learning and Pattern Recognition of Biological Data Structures with Density Functional Theory and Machine Learning.

PubMed

Chen, Chien-Chang; Juan, Hung-Hui; Tsai, Meng-Yuan; Lu, Henry Horng-Shing

2018-01-11

By introducing the methods of machine learning into the density functional theory, we made a detour for the construction of the most probable density function, which can be estimated by learning relevant features from the system of interest. Using the properties of universal functional, the vital core of density functional theory, the most probable cluster numbers and the corresponding cluster boundaries in a studying system can be simultaneously and automatically determined and the plausibility is erected on the Hohenberg-Kohn theorems. For the method validation and pragmatic applications, interdisciplinary problems from physical to biological systems were enumerated. The amalgamation of uncharged atomic clusters validated the unsupervised searching process of the cluster numbers and the corresponding cluster boundaries were exhibited likewise. High accurate clustering results of the Fisher's iris dataset showed the feasibility and the flexibility of the proposed scheme. Brain tumor detections from low-dimensional magnetic resonance imaging datasets and segmentations of high-dimensional neural network imageries in the Brainbow system were also used to inspect the method practicality. The experimental results exhibit the successful connection between the physical theory and the machine learning methods and will benefit the clinical diagnoses.

Using the underlying biological organization of the Mycobacterium tuberculosis functional network for protein function prediction.

PubMed

Mazandu, Gaston K; Mulder, Nicola J

2012-07-01

Despite ever-increasing amounts of sequence and functional genomics data, there is still a deficiency of functional annotation for many newly sequenced proteins. For Mycobacterium tuberculosis (MTB), more than half of its genome is still uncharacterized, which hampers the search for new drug targets within the bacterial pathogen and limits our understanding of its pathogenicity. As for many other genomes, the annotations of proteins in the MTB proteome were generally inferred from sequence homology, which is effective but its applicability has limitations. We have carried out large-scale biological data integration to produce an MTB protein functional interaction network. Protein functional relationships were extracted from the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database, and additional functional interactions from microarray, sequence and protein signature data. The confidence level of protein relationships in the additional functional interaction data was evaluated using a dynamic data-driven scoring system. This functional network has been used to predict functions of uncharacterized proteins using Gene Ontology (GO) terms, and the semantic similarity between these terms measured using a state-of-the-art GO similarity metric. To achieve better trade-off between improvement of quality, genomic coverage and scalability, this prediction is done by observing the key principles driving the biological organization of the functional network. This study yields a new functionally characterized MTB strain CDC1551 proteome, consisting of 3804 and 3698 proteins out of 4195 with annotations in terms of the biological process and molecular function ontologies, respectively. These data can contribute to research into the Development of effective anti-tubercular drugs with novel biological mechanisms of action. Copyright © 2011 Elsevier B.V. All rights reserved.

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.

Toward a systems-level analysis of infection biology: a new method for conducting genetic screens in human cells.

PubMed

Stanley, Sarah A; Hung, Deborah T

2009-12-16

Loss-of-function genetic screens have facilitated great strides in our understanding of the biology of model organisms but have not been possible in diploid human cells. A recent report by Brummelkamp's group in Science describes the use of insertional mutagenesis to generate loss-of-function alleles in a largely haploid human cell line and demonstrates the versatility of this method in screens designed to investigate the host/pathogen interaction. This approach has strengths that are complementary to existing strategies and will facilitate progress toward a systems-level understanding of infectious disease and ultimately the development of new therapeutics.

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.

Exploitation of peptide motif sequences and their use in nanobiotechnology.

PubMed

Shiba, Kiyotaka

2010-08-01

Short amino acid sequences extracted from natural proteins or created using in vitro evolution systems are sometimes associated with particular biological functions. These peptides, called peptide motifs, can serve as functional units for the creation of various tools for nanobiotechnology. In particular, peptide motifs that have the ability to specifically recognize the surfaces of solid materials and to mineralize certain inorganic materials have been linking biological science to material science. Here, I review how these peptide motifs have been isolated from natural proteins or created using in vitro evolution systems, and how they have been used in the nanobiotechnology field. Copyright © 2010 Elsevier Ltd. All rights reserved.

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.

Invited review: gravitational biology of the neuromotor systems: a perspective to the next era

NASA Technical Reports Server (NTRS)

Edgerton, V. R.; Roy, R. R.

2000-01-01

Earth's gravity has had a significant impact on the designs of the neuromotor systems that have evolved. Early indications are that gravity also plays a key role in the ontogenesis of some of these design features. The purpose of the present review is not to assess and interpret a body of knowledge in the usual sense of a review but to look ahead, given some of the general concepts that have evolved and observations made to date, which can guide our future approach to gravitational biology. We are now approaching an era in gravitational biology during which well-controlled experiments can be conducted for sustained periods in a microgravity environment. Thus it is now possible to study in greater detail the role of gravity in phylogenesis and ontogenesis. Experiments can range from those conducted on the simplest levels of organization of the components that comprise the neuromotor system to those conducted on the whole organism. Generally, the impact of Earth's gravitational environment on living systems becomes more complex as the level of integration of the biological phenomenon of interest increases. Studies of the effects of gravitational vectors on neuromotor systems have and should continue to provide unique insight into these mechanisms that control and maintain neural control systems designed to function in Earth's gravitational environment. A number of examples are given of how a gravitational biology perspective can lead to a clearer understanding of neuromotor disorders. Furthermore, the technologies developed for spaceflight studies have contributed and should continue to contribute to studies of motor dysfunctions, such as spinal cord injury and stroke. Disorders associated with energy support and delivery systems and how these functions are altered by sedentary life styles at 1 G and by space travel in a microgravity environment are also discussed.

Growing Spaceships?

NASA Technical Reports Server (NTRS)

Robertson, Glen A.

2013-01-01

NASA currently has a program called the Space Synthetic Biology Project. Synthetic Biology or SynBio is the design and construction of new biological functions and systems not found in nature. Four NASA field centers, along with experts from industry and academia, have been partnering on the Space Synthetic Biology Project and are working on new breakthroughs in this increasingly useful pursuit, which is part a science discipline and part engineering. Led by researchers at NASA s Ames Research Center, the team is studying how this powerful new tool can help NASA now and in the future. The project was created to harness biology in reliable, robust, engineered systems to support the agency s exploration and science missions, to improve life on Earth and to help shape NASA's future. The program also is intended to contribute foundational tools to the synthetic biology research community.

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

Adaptation, Growth, and Resilience in Biological Distribution Networks

NASA Astrophysics Data System (ADS)

Ronellenfitsch, Henrik; Katifori, Eleni

Highly optimized complex transport networks serve crucial functions in many man-made and natural systems such as power grids and plant or animal vasculature. Often, the relevant optimization functional is nonconvex and characterized by many local extrema. In general, finding the global, or nearly global optimum is difficult. In biological systems, it is believed that such an optimal state is slowly achieved through natural selection. However, general coarse grained models for flow networks with local positive feedback rules for the vessel conductivity typically get trapped in low efficiency, local minima. We show how the growth of the underlying tissue, coupled to the dynamical equations for network development, can drive the system to a dramatically improved optimal state. This general model provides a surprisingly simple explanation for the appearance of highly optimized transport networks in biology such as plant and animal vasculature. In addition, we show how the incorporation of spatially collective fluctuating sources yields a minimal model of realistic reticulation in distribution networks and thus resilience against damage.

Controlled ecological life support system higher plant flight experiments

NASA Technical Reports Server (NTRS)

Tibbitts, T. W.; Wheeler, R. M.

1984-01-01

Requirements for spaceflight experments which involve higher plants were determined. The plants are studied for use in controlled ecological life support systems (CELSS). Two categories of research requirements are discussed: (1) the physical needs which include nutrient, water and gas exchange requirements; (2) the biological and physiological functions which affect plants in zero gravity environments. Physical problems studies are given the priority since they affect all biological experiments.

Year 2 Report: Protein Function Prediction Platform

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

Zhou, C E

2012-04-27

Upon completion of our second year of development in a 3-year development cycle, we have completed a prototype protein structure-function annotation and function prediction system: Protein Function Prediction (PFP) platform (v.0.5). We have met our milestones for Years 1 and 2 and are positioned to continue development in completion of our original statement of work, or a reasonable modification thereof, in service to DTRA Programs involved in diagnostics and medical countermeasures research and development. The PFP platform is a multi-scale computational modeling system for protein structure-function annotation and function prediction. As of this writing, PFP is the only existing fullymore » automated, high-throughput, multi-scale modeling, whole-proteome annotation platform, and represents a significant advance in the field of genome annotation (Fig. 1). PFP modules perform protein functional annotations at the sequence, systems biology, protein structure, and atomistic levels of biological complexity (Fig. 2). Because these approaches provide orthogonal means of characterizing proteins and suggesting protein function, PFP processing maximizes the protein functional information that can currently be gained by computational means. Comprehensive annotation of pathogen genomes is essential for bio-defense applications in pathogen characterization, threat assessment, and medical countermeasure design and development in that it can short-cut the time and effort required to select and characterize protein biomarkers.« less

Lectins of beneficial microbes: system organisation, functioning and functional superfamily.

PubMed

Lakhtin, M; Lakhtin, V; Alyoshkin, V; Afanasyev, S

2011-06-01

In this review our last results and proposals with respect to general aspects of lectin studies are summarised and compared. System presence, organisation and functioning of lectins are proposed, and accents on beneficial symbiotic microbial lectins studies are presented. The proposed general principles of lectin functioning allows for a comparison of lectins with other carbohydrate-recognition systems. A new structure-functional superfamily of symbiotic microbial lectins is proposed and its main properties are described. The proposed superfamily allows for extended searches of the biological activities of any microbial member. Prospects of lectins of beneficial symbiotic microorganisms are discussed.

[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.

Mechanisms for Robust Cognition.

PubMed

Walsh, Matthew M; Gluck, Kevin A

2015-08-01

To function well in an unpredictable environment using unreliable components, a system must have a high degree of robustness. Robustness is fundamental to biological systems and is an objective in the design of engineered systems such as airplane engines and buildings. Cognitive systems, like biological and engineered systems, exist within variable environments. This raises the question, how do cognitive systems achieve similarly high degrees of robustness? The aim of this study was to identify a set of mechanisms that enhance robustness in cognitive systems. We identify three mechanisms that enhance robustness in biological and engineered systems: system control, redundancy, and adaptability. After surveying the psychological literature for evidence of these mechanisms, we provide simulations illustrating how each contributes to robust cognition in a different psychological domain: psychomotor vigilance, semantic memory, and strategy selection. These simulations highlight features of a mathematical approach for quantifying robustness, and they provide concrete examples of mechanisms for robust cognition. © 2014 Cognitive Science Society, Inc.

Photonics and bioinspiration

NASA Astrophysics Data System (ADS)

Lewis, Keith

2014-10-01

Biological systems exploiting light have benefitted from thousands of years of genetic evolution and can provide insight to support the development of new approaches for imaging, image processing and communication. For example, biological vision systems can provide significant diversity, yet are able to function with only a minimal degree of neural processing. Examples will be described underlying the processes used to support the development of new concepts for photonic systems, ranging from uncooled bolometers and tunable filters, to asymmetric free-space optical communication systems and new forms of camera capable of simultaneously providing spectral and polarimetric diversity.

SPED light sheet microscopy: fast mapping of biological system structure and function

PubMed Central

Tomer, Raju; Lovett-Barron, Matthew; Kauvar, Isaac; Andalman, Aaron; Burns, Vanessa M.; Sankaran, Sethuraman; Grosenick, Logan; Broxton, Michael; Yang, Samuel; Deisseroth, Karl

2016-01-01

The goal of understanding living nervous systems has driven interest in high-speed and large field-of-view volumetric imaging at cellular resolution. Light-sheet microscopy approaches have emerged for cellular-resolution functional brain imaging in small organisms such as larval zebrafish, but remain fundamentally limited in speed. Here we have developed SPED light sheet microscopy, which combines large volumetric field-of-view via an extended depth of field with the optical sectioning of light sheet microscopy, thereby eliminating the need to physically scan detection objectives for volumetric imaging. SPED enables scanning of thousands of volumes-per-second, limited only by camera acquisition rate, through the harnessing of optical mechanisms that normally result in unwanted spherical aberrations. We demonstrate capabilities of SPED microscopy by performing fast sub-cellular resolution imaging of CLARITY mouse brains and cellular-resolution volumetric Ca2+ imaging of entire zebrafish nervous systems. Together, SPED light sheet methods enable high-speed cellular-resolution volumetric mapping of biological system structure and function. PMID:26687363

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.

A systems biology approach to defining regulatory mechanisms for cartilage and tendon cell phenotypes.

PubMed

Mueller, A J; Tew, S R; Vasieva, O; Clegg, P D; Canty-Laird, E G

2016-09-27

Phenotypic plasticity of adult somatic cells has provided emerging avenues for the development of regenerative therapeutics. In musculoskeletal biology the mechanistic regulatory networks of genes governing the phenotypic plasticity of cartilage and tendon cells has not been considered systematically. Additionally, a lack of strategies to effectively reproduce in vitro functional models of cartilage and tendon is retarding progress in this field. De- and redifferentiation represent phenotypic transitions that may contribute to loss of function in ageing musculoskeletal tissues. Applying a systems biology network analysis approach to global gene expression profiles derived from common in vitro culture systems (monolayer and three-dimensional cultures) this study demonstrates common regulatory mechanisms governing de- and redifferentiation transitions in cartilage and tendon cells. Furthermore, evidence of convergence of gene expression profiles during monolayer expansion of cartilage and tendon cells, and the expression of key developmental markers, challenges the physiological relevance of this culture system. The study also suggests that oxidative stress and PI3K signalling pathways are key modulators of in vitro phenotypes for cells of musculoskeletal origin.

Biogenic Magnetite and EMF Effects

NASA Astrophysics Data System (ADS)

Kirschvink, Joseph L.

1996-03-01

Magnetite biomineralization is a genetically-controlled biochemical process through which organisms make perfect ferrimagnetic crystals, usually of single magnetic domain size. This process is an ancient one, having evolved about 2 billion years ago in the magnetotactic bacteria, and presumably was incorporated in the genome of higher organisms, including humans. During this time, DNA replication, protein synthesis, and many other biochemical processes have functioned in the presence of strong static fields of up to 400 mT adjacent to these magnetosomes without any obvious deleterious effects. Recent behavioral experiments using short but strong magnetic pulses in honeybees and birds demonstrates that ferromagnetic materials are involved in the sensory transduction of geomagnetic field information to the nervous system, and both behavioral and direct electrophysiological experiments indicate sensitivity thresholds to DC magnetic fields down to a few nT. However, far more biogenic magnetite is present in animal tissues than is needed for magnetoreception, and the biological function of this extra material is unknown. The presence of ferromagnetic materials in biological systems could provide physical transduction mechanisms for ELF magnetic fields, as well for microwave radiation in the .5 to 10 GHz band where magnetite has its peak ferromagnetic resonance. Elucidation of the cellular ultrastructure and biological function(s) of magnetite might help resolve the question of whether anthropogenic EMFs can cause deleterious biological effects. This work has been supported by grants from the NIH and EPRI.

Growing trend of CE at the omics level: the frontier of systems biology.

PubMed

Oh, Eulsik; Hasan, Md Nabiul; Jamshed, Muhammad; Park, Soo Hyun; Hong, Hye-Min; Song, Eun Joo; Yoo, Young Sook

2010-01-01

In a novel attempt to comprehend the complexity of life, systems biology has recently emerged as a state-of-the-art approach for biological research in contrast to the reductionist approaches that have been used in molecular cell biology since the 1950s. Because a massive amount of information is required in many systems biology studies of life processes, we have increasingly come to depend on techniques that provide high-throughput omics data. CE and CE coupled to MS have served as powerful analytical tools for providing qualitative and quantitative omics data. Recent systems biology studies have focused strongly on the diagnosis and treatment of diseases. The increasing number of clinical research papers on drug discovery and disease therapies reflects this growing interest among scientists. Since such clinical research reflects one of the ultimate purposes of bioscience, these trends will be sustained for a long time. Thus, this review mainly focuses on the application of CE and CE-MS in diagnosis as well as on the latest CE methods developed. Furthermore, we outline the new challenges that arose in 2008 and later in elucidating the system-level functions of the bioconstituents of living organisms.

Identification of Boolean Network Models From Time Series Data Incorporating Prior Knowledge.

PubMed

Leifeld, Thomas; Zhang, Zhihua; Zhang, Ping

2018-01-01

Motivation: Mathematical models take an important place in science and engineering. A model can help scientists to explain dynamic behavior of a system and to understand the functionality of system components. Since length of a time series and number of replicates is limited by the cost of experiments, Boolean networks as a structurally simple and parameter-free logical model for gene regulatory networks have attracted interests of many scientists. In order to fit into the biological contexts and to lower the data requirements, biological prior knowledge is taken into consideration during the inference procedure. In the literature, the existing identification approaches can only deal with a subset of possible types of prior knowledge. Results: We propose a new approach to identify Boolean networks from time series data incorporating prior knowledge, such as partial network structure, canalizing property, positive and negative unateness. Using vector form of Boolean variables and applying a generalized matrix multiplication called the semi-tensor product (STP), each Boolean function can be equivalently converted into a matrix expression. Based on this, the identification problem is reformulated as an integer linear programming problem to reveal the system matrix of Boolean model in a computationally efficient way, whose dynamics are consistent with the important dynamics captured in the data. By using prior knowledge the number of candidate functions can be reduced during the inference. Hence, identification incorporating prior knowledge is especially suitable for the case of small size time series data and data without sufficient stimuli. The proposed approach is illustrated with the help of a biological model of the network of oxidative stress response. Conclusions: The combination of efficient reformulation of the identification problem with the possibility to incorporate various types of prior knowledge enables the application of computational model inference to systems with limited amount of time series data. The general applicability of this methodological approach makes it suitable for a variety of biological systems and of general interest for biological and medical research.

Molecular communication and networking: opportunities and challenges.

PubMed

Nakano, Tadashi; Moore, Michael J; Wei, Fang; Vasilakos, Athanasios V; Shuai, Jianwei

2012-06-01

The ability of engineered biological nanomachines to communicate with biological systems at the molecular level is anticipated to enable future applications such as monitoring the condition of a human body, regenerating biological tissues and organs, and interfacing artificial devices with neural systems. From the viewpoint of communication theory and engineering, molecular communication is proposed as a new paradigm for engineered biological nanomachines to communicate with the natural biological nanomachines which form a biological system. Distinct from the current telecommunication paradigm, molecular communication uses molecules as the carriers of information; sender biological nanomachines encode information on molecules and release the molecules in the environment, the molecules then propagate in the environment to receiver biological nanomachines, and the receiver biological nanomachines biochemically react with the molecules to decode information. Current molecular communication research is limited to small-scale networks of several biological nanomachines. Key challenges to bridge the gap between current research and practical applications include developing robust and scalable techniques to create a functional network from a large number of biological nanomachines. Developing networking mechanisms and communication protocols is anticipated to introduce new avenues into integrating engineered and natural biological nanomachines into a single networked system. In this paper, we present the state-of-the-art in the area of molecular communication by discussing its architecture, features, applications, design, engineering, and physical modeling. We then discuss challenges and opportunities in developing networking mechanisms and communication protocols to create a network from a large number of bio-nanomachines for future applications.

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.

Functional genomics approaches in parasitic helminths.

PubMed

Hagen, J; Lee, E F; Fairlie, W D; Kalinna, B H

2012-01-01

As research on parasitic helminths is moving into the post-genomic era, an enormous effort is directed towards deciphering gene function and to achieve gene annotation. The sequences that are available in public databases undoubtedly hold information that can be utilized for new interventions and control but the exploitation of these resources has until recently remained difficult. Only now, with the emergence of methods to genetically manipulate and transform parasitic worms will it be possible to gain a comprehensive understanding of the molecular mechanisms involved in nutrition, metabolism, developmental switches/maturation and interaction with the host immune system. This review focuses on functional genomics approaches in parasitic helminths that are currently used, to highlight potential applications of these technologies in the areas of cell biology, systems biology and immunobiology of parasitic helminths. © 2011 Blackwell Publishing Ltd.

Sex Differences in Kappa Opioid Receptor Function and Their Potential Impact on Addiction

PubMed Central

Chartoff, Elena H.; Mavrikaki, Maria

2015-01-01

Behavioral, biological, and social sequelae that lead to drug addiction differ between men and women. Our efforts to understand addiction on a mechanistic level must include studies in both males and females. Stress, anxiety, and depression are tightly linked to addiction, and whether they precede or result from compulsive drug use depends on many factors, including biological sex. The neuropeptide dynorphin (DYN), an endogenous ligand at kappa opioid receptors (KORs), is necessary for stress-induced aversive states and is upregulated in the brain after chronic exposure to drugs of abuse. KOR agonists produce signs of anxiety, fear, and depression in laboratory animals and humans, findings that have led to the hypothesis that drug withdrawal-induced DYN release is instrumental in negative reinforcement processes that drive addiction. However, these studies were almost exclusively conducted in males. Only recently is evidence available that there are sex differences in the effects of KOR activation on affective state. This review focuses on sex differences in DYN and KOR systems and how these might contribute to sex differences in addictive behavior. Much of what is known about how biological sex influences KOR systems is from research on pain systems. The basic molecular and genetic mechanisms that have been discovered to underlie sex differences in KOR function in pain systems may apply to sex differences in KOR function in reward systems. Our goals are to discuss the current state of knowledge on how biological sex contributes to KOR function in the context of pain, mood, and addiction and to explore potential mechanisms for sex differences in KOR function. We will highlight evidence that the function of DYN-KOR systems is influenced in a sex-dependent manner by: polymorphisms in the prodynorphin (pDYN) gene, genetic linkage with the melanocortin-1 receptor (MC1R), heterodimerization of KORs and mu opioid receptors (MORs), and gonadal hormones. Finally, we identify several gaps in our understanding of “if” and “how” DYN and KORs modulate addictive behavior in a sex-dependent manner. Future work may address these gaps by building on the mechanistic studies outlined in this review. Ultimately this will enable the development of novel and effective addiction treatments tailored to either males or females. PMID:26733781

[THE OPTIMIZATION OF NUTRITION FUNCTION UNDER SYNDROME OF RESISTANCE TO INSULIN, DISORDER OF FATTY ACIDS' METABOLISM AND ABSORPTION OF GLUCOSE BY CELLS (A LECTURE)].

PubMed

Titov, V N

2016-01-01

The phylogenetic processes continue to proceed in Homo Sapiens. At the very early stages ofphylogenesis, the ancient Archaea that formed mitochondria under symbiotic interaction with later bacterial cells conjointly formed yet another system. In this system, there are no cells' absorption of glucose if it is possible to absorb fatty acids from intercellular medium in the form of unesterfied fatty acids or ketonic bodies--metabolites of fatty acids. This is caused by objectively existed conditions and subsequent availability of substrates at the stages ofphylogenesis: acetate, ketonic bodies, fatty acids and only later glucose. The phylogenetically late insulin used after billions years the same dependencies at formation of regulation ofmetabolism offatty acids and cells' absorption of glucose. In order that syndrome ofresistance ceased to exist as afoundation of metabolic pandemic Homo Sapiens has to understand the following. After successful function ofArchaea+bacterial cells and considered by biology action of insulin for the third time in phylogenesis and using biological function of intelligence the content ofphylogenetically earlier palmitic saturated fatty acid infood can't to exceed possibilities of phylogenetically late lipoproteins to transfer it in intercellular medium and blood and cells to absorb it. It is supposed that at early stages of phylogenesis biological function of intelligence is primarily formed to bring into line "unconformities" of regulation of metabolism against the background of seeming relative biological "perfection". These unconformities were subsequently and separately formed at the level of cells in paracrin regulated cenosises of cells and organs and at the level of organism. The prevention of resistance to insulin basically requires biological function of intelligence, principle of self-restraint, bringing into line multiple desires of Homo Sapiens with much less extensive biological possibilities. The "unconformities" of regulation of metabolism in vivo are etiological factors of all metabolic pandemics including atherosclerosis, metabolic arterial hypertension, obesity and metabolic syndrome Tertiannondatum.

Vitamin C: electron emission, free radicals and biological versatility.

PubMed

Getoff, Nikola

2013-01-01

The many-sided biological role of vitamin C (ascorbate) is briefly illustrated by specific examples. It is demonstrated that in aqueous solutions, vitamin C emits solvated electrons (e(aq)(-)), when excited in single state. Vitamin C can also react with e(aq)(-) as well as transfer them to other biological systems and thereby acts as efficient electron mediator. Based on its chemical and biological properties, it is clear that vitamin C plays a very important role in various functions in the organism alongside biochemical processes.

Biocellion: accelerating computer simulation of multicellular biological system models

PubMed Central

Kang, Seunghwa; Kahan, Simon; McDermott, Jason; Flann, Nicholas; Shmulevich, Ilya

2014-01-01

Motivation: Biological system behaviors are often the outcome of complex interactions among a large number of cells and their biotic and abiotic environment. Computational biologists attempt to understand, predict and manipulate biological system behavior through mathematical modeling and computer simulation. Discrete agent-based modeling (in combination with high-resolution grids to model the extracellular environment) is a popular approach for building biological system models. However, the computational complexity of this approach forces computational biologists to resort to coarser resolution approaches to simulate large biological systems. High-performance parallel computers have the potential to address the computing challenge, but writing efficient software for parallel computers is difficult and time-consuming. Results: We have developed Biocellion, a high-performance software framework, to solve this computing challenge using parallel computers. To support a wide range of multicellular biological system models, Biocellion asks users to provide their model specifics by filling the function body of pre-defined model routines. Using Biocellion, modelers without parallel computing expertise can efficiently exploit parallel computers with less effort than writing sequential programs from scratch. We simulate cell sorting, microbial patterning and a bacterial system in soil aggregate as case studies. Availability and implementation: Biocellion runs on x86 compatible systems with the 64 bit Linux operating system and is freely available for academic use. Visit http://biocellion.com for additional information. Contact: seunghwa.kang@pnnl.gov PMID:25064572

How the study of Listeria monocytogenes has led to new concepts in biology.

PubMed

Rolhion, Nathalie; Cossart, Pascale

2017-06-01

The opportunistic intracellular bacterial pathogen Listeria monocytogenes has in 30 years emerged as an exceptional bacterial model system in infection biology. Research on this bacterium has provided considerable insight into how pathogenic bacteria adapt to mammalian hosts, invade eukaryotic cells, move intracellularly, interfere with host cell functions and disseminate within tissues. It also contributed to unveil features of normal host cell pathways and unsuspected functions of previously known cellular proteins. This review provides an updated overview of our knowledge on this pathogen. In many examples, findings on L. monocytogenes provided the basis for new concepts in bacterial regulation, cell biology and infection processes.

SBEToolbox: A Matlab Toolbox for Biological Network Analysis

PubMed Central

Konganti, Kranti; Wang, Gang; Yang, Ence; Cai, James J.

2013-01-01

We present SBEToolbox (Systems Biology and Evolution Toolbox), an open-source Matlab toolbox for biological network analysis. It takes a network file as input, calculates a variety of centralities and topological metrics, clusters nodes into modules, and displays the network using different graph layout algorithms. Straightforward implementation and the inclusion of high-level functions allow the functionality to be easily extended or tailored through developing custom plugins. SBEGUI, a menu-driven graphical user interface (GUI) of SBEToolbox, enables easy access to various network and graph algorithms for programmers and non-programmers alike. All source code and sample data are freely available at https://github.com/biocoder/SBEToolbox/releases. PMID:24027418

SBEToolbox: A Matlab Toolbox for Biological Network Analysis.

PubMed

Konganti, Kranti; Wang, Gang; Yang, Ence; Cai, James J

2013-01-01

We present SBEToolbox (Systems Biology and Evolution Toolbox), an open-source Matlab toolbox for biological network analysis. It takes a network file as input, calculates a variety of centralities and topological metrics, clusters nodes into modules, and displays the network using different graph layout algorithms. Straightforward implementation and the inclusion of high-level functions allow the functionality to be easily extended or tailored through developing custom plugins. SBEGUI, a menu-driven graphical user interface (GUI) of SBEToolbox, enables easy access to various network and graph algorithms for programmers and non-programmers alike. All source code and sample data are freely available at https://github.com/biocoder/SBEToolbox/releases.

The path to next generation biofuels: successes and challenges in the era of synthetic biology

PubMed Central

2010-01-01

Volatility of oil prices along with major concerns about climate change, oil supply security and depleting reserves have sparked renewed interest in the production of fuels from renewable resources. Recent advances in synthetic biology provide new tools for metabolic engineers to direct their strategies and construct optimal biocatalysts for the sustainable production of biofuels. Metabolic engineering and synthetic biology efforts entailing the engineering of native and de novo pathways for conversion of biomass constituents to short-chain alcohols and advanced biofuels are herewith reviewed. In the foreseeable future, formal integration of functional genomics and systems biology with synthetic biology and metabolic engineering will undoubtedly support the discovery, characterization, and engineering of new metabolic routes and more efficient microbial systems for the production of biofuels. PMID:20089184

Molecular Force Spectroscopy on Cells

NASA Astrophysics Data System (ADS)

Liu, Baoyu; Chen, Wei; Zhu, Cheng

2015-04-01

Molecular force spectroscopy has become a powerful tool to study how mechanics regulates biology, especially the mechanical regulation of molecular interactions and its impact on cellular functions. This force-driven methodology has uncovered a wealth of new information of the physical chemistry of molecular bonds for various biological systems. The new concepts, qualitative and quantitative measures describing bond behavior under force, and structural bases underlying these phenomena have substantially advanced our fundamental understanding of the inner workings of biological systems from the nanoscale (molecule) to the microscale (cell), elucidated basic molecular mechanisms of a wide range of important biological processes, and provided opportunities for engineering applications. Here, we review major force spectroscopic assays, conceptual developments of mechanically regulated kinetics of molecular interactions, and their biological relevance. We also present current challenges and highlight future directions.

The Installation Restoration Program Toxicology Guide. Volume 5

DTIC Science & Technology

1990-11-01

biological systems may not differentiate metals on a basis other than oxidation state. In essence , this results in a specific function (e.g. intracellular...biological exposure Indices. 5th ed. Cincinnati, Ohio, pp. 422-426 (as cited in 6206). 6368. Jasmin , G. 1973. Experimental production of polycythcmia in

Students' Learning Activities While Studying Biological Process Diagrams

ERIC Educational Resources Information Center

Kragten, Marco; Admiraal, Wilfried; Rijlaarsdam, Gert

2015-01-01

Process diagrams describe how a system functions (e.g. photosynthesis) and are an important type of representation in Biology education. In the present study, we examined students' learning activities while studying process diagrams, related to their resulting comprehension of these diagrams. Each student completed three learning tasks. Verbal…

Derivation of Tissue-specific Functional Gene Sets to Aid Transcriptomic Analysis of Chemical Impacts on the Teleost Reproductive Axis.

EPA Science Inventory

Oligonucleotide microarrays are a powerful tool for unsupervised analysis of chemical impacts on biological systems. However, the lack of well annotated biological pathways for many aquatic organisms, including fish, and the poor power of microarray-based analyses to detect diffe...

Massive-Scale Gene Co-Expression Network Construction and Robustness Testing Using Random Matrix Theory

PubMed Central

Isaacson, Sven; Luo, Feng; Feltus, Frank A.; Smith, Melissa C.

2013-01-01

The study of gene relationships and their effect on biological function and phenotype is a focal point in systems biology. Gene co-expression networks built using microarray expression profiles are one technique for discovering and interpreting gene relationships. A knowledge-independent thresholding technique, such as Random Matrix Theory (RMT), is useful for identifying meaningful relationships. Highly connected genes in the thresholded network are then grouped into modules that provide insight into their collective functionality. While it has been shown that co-expression networks are biologically relevant, it has not been determined to what extent any given network is functionally robust given perturbations in the input sample set. For such a test, hundreds of networks are needed and hence a tool to rapidly construct these networks. To examine functional robustness of networks with varying input, we enhanced an existing RMT implementation for improved scalability and tested functional robustness of human (Homo sapiens), rice (Oryza sativa) and budding yeast (Saccharomyces cerevisiae). We demonstrate dramatic decrease in network construction time and computational requirements and show that despite some variation in global properties between networks, functional similarity remains high. Moreover, the biological function captured by co-expression networks thresholded by RMT is highly robust. PMID:23409071

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.

PREFACE: Nanobiology: from physics and engineering to biology

NASA Astrophysics Data System (ADS)

Nussinov, Ruth; Alemán, Carlos

2006-03-01

Biological systems are inherently nano in scale. Unlike nanotechnology, nanobiology is characterized by the interplay between physics, materials science, synthetic organic chemistry, engineering and biology. Nanobiology is a new discipline, with the potential of revolutionizing medicine: it combines the tools, ideas and materials of nanoscience and biology; it addresses biological problems that can be studied and solved by nanotechnology; it devises ways to construct molecular devices using biomacromolecules; and it attempts to build molecular machines utilizing concepts seen in nature. Its ultimate aim is to be able to predictably manipulate these, tailoring them to specified needs. Nanobiology targets biological systems and uses biomacromolecules. Hence, on the one hand, nanobiology is seemingly constrained in its scope as compared to general nanotechnology. Yet the amazing intricacy of biological systems, their complexity, and the richness of the shapes and properties provided by the biological polymers, enrich nanobiology. Targeting biological systems entails comprehension of how they work and the ability to use their components in design. From the physical standpoint, ultimately, if we are to understand biology we need to learn how to apply physical principles to figure out how these systems actually work. The goal of nanobiology is to assist in probing these systems at the appropriate length scale, heralding a new era in the biological, physical and chemical sciences. Biology is increasingly asking quantitative questions. Quantitation is essential if we are to understand how the cell works, and the details of its regulation. The physical sciences provide tools and strategies to obtain accurate measurements and simulate the information to allow comprehension of the processes. Nanobiology is at the interface of the physical and the biological sciences. Biology offers to the physical sciences fascinating problems, sophisticated systems and a rich repertoire of shapes and materials. Inspection of the protein structure databank illustrates the breadth of scaffolds, shapes and properties that protein molecules and their building blocks can provide. Via a shape-guided self-assembly strategy, these can be put together toward a specific function. Further, by inserting synthetic non-natural residues at judiciously selected positions, or synthetic peptide linkers, we may selectively rigidify the construct, or obtain a totally new world of shapes and scaffolds. Such broadening of the chemical space may lead to an almost unlimited range of nanosystems and architectures. Merging computation with experiment will accelerate nanodesign. Computational modeling will enhance the application of nanotechnology to key areas such as drug delivery and biomaterial design. Nanobiology is a field where interdisciplinary collaborations are essential and disciplines converge. Discipline convergence should enable the quantitation, leading to a better understanding of the regulatory networks within cells and between cells of an organism. These networks dictate how a cell responds to external stimuli, which in turn activate signaling cascades. It should allow the addressing of a broad range of questions on the structure and function of the cytoskeleton; the nuclear envelope; signal transduction by membrane embedded receptors; the nanomechanical properties of the extracellular matrix; nuclear transport; and voltage induced channel gating. For successful nanostructure design, we need to figure out and be able to control the intermolecular associations. For a stable functional construct, there are two key elements: first, the conformations of the building blocks in the designed structure should follow their natural tendencies; and second, the associations should be favorable. Molecules interact through their surfaces. Thus, favorable associations derive from shape complementarity and contributions of the various physical components. Nanobiology is in its infancy. Yet, biology provides an enormous range of engaging and stimulating problems with many in vivo examples of intricate, complex, fascinating biological systems. Understanding, mimicking and controlling the devices which target these processes and which are constructed from these molecules is a tremendous challenge to the converging disciplines in nanobiology.

Separating macroecological pattern and process: comparing ecological, economic, and geological systems.

PubMed

Blonder, Benjamin; Sloat, Lindsey; Enquist, Brian J; McGill, Brian

2014-01-01

Theories of biodiversity rest on several macroecological patterns describing the relationship between species abundance and diversity. A central problem is that all theories make similar predictions for these patterns despite disparate assumptions. A troubling implication is that these patterns may not reflect anything unique about organizational principles of biology or the functioning of ecological systems. To test this, we analyze five datasets from ecological, economic, and geological systems that describe the distribution of objects across categories in the United States. At the level of functional form ('first-order effects'), these patterns are not unique to ecological systems, indicating they may reveal little about biological process. However, we show that mechanism can be better revealed in the scale-dependency of first-order patterns ('second-order effects'). These results provide a roadmap for biodiversity theory to move beyond traditional patterns, and also suggest ways in which macroecological theory can constrain the dynamics of economic systems.

Sensors and actuators inherent in biological species

NASA Astrophysics Data System (ADS)

Taya, Minoru; Stahlberg, Rainer; Li, Fanghong; Zhao, Ying Joyce

2007-04-01

This paper addresses examples of sensing and active mechanisms inherent in some biological species where both plants and animals cases are discussed: mechanosensors and actuators in Venus Fly Trap and cucumber tendrils, chemosensors in insects, two cases of interactions between different kingdoms, (i) cotton plant smart defense system and (ii) bird-of-paradise flower and hamming bird interaction. All these cases lead us to recognize how energy-efficient and flexible the biological sensors and actuators are. This review reveals the importance of integration of sensing and actuation functions into an autonomous system if we make biomimetic design of a set of new autonomous systems which can sense and actuate under a number of different stimuli and threats.

Systems biology approach to bioremediation

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

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

2012-06-01

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

Biological fabrication of cellulose fibers with tailored properties

NASA Astrophysics Data System (ADS)

Natalio, Filipe; Fuchs, Regina; Cohen, Sidney R.; Leitus, Gregory; Fritz-Popovski, Gerhard; Paris, Oskar; Kappl, Michael; Butt, Hans-Jürgen

2017-09-01

Cotton is a promising basis for wearable smart textiles. Current approaches that rely on fiber coatings suffer from function loss during wear. We present an approach that allows biological incorporation of exogenous molecules into cotton fibers to tailor the material’s functionality. In vitro model cultures of upland cotton (Gossypium hirsutum) are incubated with 6-carboxyfluorescein-glucose and dysprosium-1,4,7,10-tetraazacyclododecane-1,4,7,10-tetraacetic acid-glucose, where the glucose moiety acts as a carrier capable of traveling from the vascular connection to the outermost cell layer of the ovule epidermis, becoming incorporated into the cellulose fibers. This yields fibers with unnatural properties such as fluorescence or magnetism. Combining biological systems with the appropriate molecular design offers numerous possibilities to grow functional composite materials and implements a material-farming concept.

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

Functional annotation of chemical libraries across diverse biological processes.

PubMed

Piotrowski, Jeff S; Li, Sheena C; Deshpande, Raamesh; Simpkins, Scott W; Nelson, Justin; Yashiroda, Yoko; Barber, Jacqueline M; Safizadeh, Hamid; Wilson, Erin; Okada, Hiroki; Gebre, Abraham A; Kubo, Karen; Torres, Nikko P; LeBlanc, Marissa A; Andrusiak, Kerry; Okamoto, Reika; Yoshimura, Mami; DeRango-Adem, Eva; van Leeuwen, Jolanda; Shirahige, Katsuhiko; Baryshnikova, Anastasia; Brown, Grant W; Hirano, Hiroyuki; Costanzo, Michael; Andrews, Brenda; Ohya, Yoshikazu; Osada, Hiroyuki; Yoshida, Minoru; Myers, Chad L; Boone, Charles

2017-09-01

Chemical-genetic approaches offer the potential for unbiased functional annotation of chemical libraries. Mutations can alter the response of cells in the presence of a compound, revealing chemical-genetic interactions that can elucidate a compound's mode of action. We developed a highly parallel, unbiased yeast chemical-genetic screening system involving three key components. First, in a drug-sensitive genetic background, we constructed an optimized diagnostic mutant collection that is predictive for all major yeast biological processes. Second, we implemented a multiplexed (768-plex) barcode-sequencing protocol, enabling the assembly of thousands of chemical-genetic profiles. Finally, based on comparison of the chemical-genetic profiles with a compendium of genome-wide genetic interaction profiles, we predicted compound functionality. Applying this high-throughput approach, we screened seven different compound libraries and annotated their functional diversity. We further validated biological process predictions, prioritized a diverse set of compounds, and identified compounds that appear to have dual modes of action.

BiologicalNetworks 2.0 - an integrative view of genome biology data

PubMed Central

2010-01-01

Background A significant problem in the study of mechanisms of an organism's development is the elucidation of interrelated factors which are making an impact on the different levels of the organism, such as genes, biological molecules, cells, and cell systems. Numerous sources of heterogeneous data which exist for these subsystems are still not integrated sufficiently enough to give researchers a straightforward opportunity to analyze them together in the same frame of study. Systematic application of data integration methods is also hampered by a multitude of such factors as the orthogonal nature of the integrated data and naming problems. Results Here we report on a new version of BiologicalNetworks, a research environment for the integral visualization and analysis of heterogeneous biological data. BiologicalNetworks can be queried for properties of thousands of different types of biological entities (genes/proteins, promoters, COGs, pathways, binding sites, and other) and their relations (interactions, co-expression, co-citations, and other). The system includes the build-pathways infrastructure for molecular interactions/relations and module discovery in high-throughput experiments. Also implemented in BiologicalNetworks are the Integrated Genome Viewer and Comparative Genomics Browser applications, which allow for the search and analysis of gene regulatory regions and their conservation in multiple species in conjunction with molecular pathways/networks, experimental data and functional annotations. Conclusions The new release of BiologicalNetworks together with its back-end database introduces extensive functionality for a more efficient integrated multi-level analysis of microarray, sequence, regulatory, and other data. BiologicalNetworks is freely available at http://www.biologicalnetworks.org. PMID:21190573

GOMA: functional enrichment analysis tool based on GO modules

PubMed Central

Huang, Qiang; Wu, Ling-Yun; Wang, Yong; Zhang, Xiang-Sun

2013-01-01

Analyzing the function of gene sets is a critical step in interpreting the results of high-throughput experiments in systems biology. A variety of enrichment analysis tools have been developed in recent years, but most output a long list of significantly enriched terms that are often redundant, making it difficult to extract the most meaningful functions. In this paper, we present GOMA, a novel enrichment analysis method based on the new concept of enriched functional Gene Ontology (GO) modules. With this method, we systematically revealed functional GO modules, i.e., groups of functionally similar GO terms, via an optimization model and then ranked them by enrichment scores. Our new method simplifies enrichment analysis results by reducing redundancy, thereby preventing inconsistent enrichment results among functionally similar terms and providing more biologically meaningful results. PMID:23237213

Robotics-inspired biology.

PubMed

Gravish, Nick; Lauder, George V

2018-03-29

For centuries, designers and engineers have looked to biology for inspiration. Biologically inspired robots are just one example of the application of knowledge of the natural world to engineering problems. However, recent work by biologists and interdisciplinary teams have flipped this approach, using robots and physical models to set the course for experiments on biological systems and to generate new hypotheses for biological research. We call this approach robotics-inspired biology; it involves performing experiments on robotic systems aimed at the discovery of new biological phenomena or generation of new hypotheses about how organisms function that can then be tested on living organisms. This new and exciting direction has emerged from the extensive use of physical models by biologists and is already making significant advances in the areas of biomechanics, locomotion, neuromechanics and sensorimotor control. Here, we provide an introduction and overview of robotics-inspired biology, describe two case studies and suggest several directions for the future of this exciting new research area. © 2018. Published by The Company of Biologists Ltd.

Systems Toxicology: From Basic Research to Risk Assessment

PubMed Central

2014-01-01

Systems Toxicology is the integration of classical toxicology with quantitative analysis of large networks of molecular and functional changes occurring across multiple levels of biological organization. Society demands increasingly close scrutiny of the potential health risks associated with exposure to chemicals present in our everyday life, leading to an increasing need for more predictive and accurate risk-assessment approaches. Developing such approaches requires a detailed mechanistic understanding of the ways in which xenobiotic substances perturb biological systems and lead to adverse outcomes. Thus, Systems Toxicology approaches offer modern strategies for gaining such mechanistic knowledge by combining advanced analytical and computational tools. Furthermore, Systems Toxicology is a means for the identification and application of biomarkers for improved safety assessments. In Systems Toxicology, quantitative systems-wide molecular changes in the context of an exposure are measured, and a causal chain of molecular events linking exposures with adverse outcomes (i.e., functional and apical end points) is deciphered. Mathematical models are then built to describe these processes in a quantitative manner. The integrated data analysis leads to the identification of how biological networks are perturbed by the exposure and enables the development of predictive mathematical models of toxicological processes. This perspective integrates current knowledge regarding bioanalytical approaches, computational analysis, and the potential for improved risk assessment. PMID:24446777

Systems toxicology: from basic research to risk assessment.

PubMed

Sturla, Shana J; Boobis, Alan R; FitzGerald, Rex E; Hoeng, Julia; Kavlock, Robert J; Schirmer, Kristin; Whelan, Maurice; Wilks, Martin F; Peitsch, Manuel C

2014-03-17

Systems Toxicology is the integration of classical toxicology with quantitative analysis of large networks of molecular and functional changes occurring across multiple levels of biological organization. Society demands increasingly close scrutiny of the potential health risks associated with exposure to chemicals present in our everyday life, leading to an increasing need for more predictive and accurate risk-assessment approaches. Developing such approaches requires a detailed mechanistic understanding of the ways in which xenobiotic substances perturb biological systems and lead to adverse outcomes. Thus, Systems Toxicology approaches offer modern strategies for gaining such mechanistic knowledge by combining advanced analytical and computational tools. Furthermore, Systems Toxicology is a means for the identification and application of biomarkers for improved safety assessments. In Systems Toxicology, quantitative systems-wide molecular changes in the context of an exposure are measured, and a causal chain of molecular events linking exposures with adverse outcomes (i.e., functional and apical end points) is deciphered. Mathematical models are then built to describe these processes in a quantitative manner. The integrated data analysis leads to the identification of how biological networks are perturbed by the exposure and enables the development of predictive mathematical models of toxicological processes. This perspective integrates current knowledge regarding bioanalytical approaches, computational analysis, and the potential for improved risk assessment.

Systematic analysis of signaling pathways using an integrative environment.

PubMed

Visvanathan, Mahesh; Breit, Marc; Pfeifer, Bernhard; Baumgartner, Christian; Modre-Osprian, Robert; Tilg, Bernhard

2007-01-01

Understanding the biological processes of signaling pathways as a whole system requires an integrative software environment that has comprehensive capabilities. The environment should include tools for pathway design, visualization, simulation and a knowledge base concerning signaling pathways as one. In this paper we introduce a new integrative environment for the systematic analysis of signaling pathways. This system includes environments for pathway design, visualization, simulation and a knowledge base that combines biological and modeling information concerning signaling pathways that provides the basic understanding of the biological system, its structure and functioning. The system is designed with a client-server architecture. It contains a pathway designing environment and a simulation environment as upper layers with a relational knowledge base as the underlying layer. The TNFa-mediated NF-kB signal trans-duction pathway model was designed and tested using our integrative framework. It was also useful to define the structure of the knowledge base. Sensitivity analysis of this specific pathway was performed providing simulation data. Then the model was extended showing promising initial results. The proposed system offers a holistic view of pathways containing biological and modeling data. It will help us to perform biological interpretation of the simulation results and thus contribute to a better understanding of the biological system for drug identification.

Sex differences in the development of brain mechanisms for processing biological motion.

PubMed

Anderson, L C; Bolling, D Z; Schelinski, S; Coffman, M C; Pelphrey, K A; Kaiser, M D

2013-12-01

Disorders related to social functioning including autism and schizophrenia differ drastically in incidence and severity between males and females. Little is known about the neural systems underlying these sex-linked differences in risk and resiliency. Using functional magnetic resonance imaging and a task involving the visual perception of point-light displays of coherent and scrambled biological motion, we discovered sex differences in the development of neural systems for basic social perception. In adults, we identified enhanced activity during coherent biological motion perception in females relative to males in a network of brain regions previously implicated in social perception including amygdala, medial temporal gyrus, and temporal pole. These sex differences were less pronounced in our sample of school-age youth. We hypothesize that the robust neural circuitry supporting social perception in females, which diverges from males beginning in childhood, may underlie sex differences in disorders related to social processing. © 2013 Elsevier Inc. All rights reserved.

Lone pair-π interactions in biological systems: occurrence, function, and physical origin.

PubMed

Kozelka, Jiří

2017-12-01

Lone pair-π interactions are now recognized as a supramolecular bond whose existence in biological systems is documented by a growing number of examples. They are commonly attributed to electrostatic forces. This review attempts to highlight some recent discoveries evidencing the important role which lone pair-π interactions, and anion-π interactions in particular, play in stabilizing the structure and affecting the function of biomolecules. Special attention is paid to studies exploring the physical origin of these at first glance counterintuitive interactions between a lone pair of electrons of one residue and the π-cloud of another. Recent theoretical work went beyond the popular electrostatic model and inquired the extent to which orbital interactions have to be taken into account. In at least one biologically relevant case-that of anion-flavin interactions-a substantial charge-transfer component has been shown to operate.

Magnetic skyrmion-based artificial neuron device

NASA Astrophysics Data System (ADS)

Li, Sai; Kang, Wang; Huang, Yangqi; Zhang, Xichao; Zhou, Yan; Zhao, Weisheng

2017-08-01

Neuromorphic computing, inspired by the biological nervous system, has attracted considerable attention. Intensive research has been conducted in this field for developing artificial synapses and neurons, attempting to mimic the behaviors of biological synapses and neurons, which are two basic elements of a human brain. Recently, magnetic skyrmions have been investigated as promising candidates in neuromorphic computing design owing to their topologically protected particle-like behaviors, nanoscale size and low driving current density. In one of our previous studies, a skyrmion-based artificial synapse was proposed, with which both short-term plasticity and long-term potentiation functions have been demonstrated. In this work, we further report on a skyrmion-based artificial neuron by exploiting the tunable current-driven skyrmion motion dynamics, mimicking the leaky-integrate-fire function of a biological neuron. With a simple single-device implementation, this proposed artificial neuron may enable us to build a dense and energy-efficient spiking neuromorphic computing system.

Sex Differences in the Development of Brain Mechanisms for Processing Biological Motion

PubMed Central

Anderson, L.C.; Bolling, D.Z.; Schelinski, S.; Coffman, M.C.; Pelphrey, K.A.; Kaiser, M.D.

2013-01-01

Disorders related to social functioning including autism and schizophrenia differ drastically in incidence and severity between males and females. Little is known about the neural systems underlying these sex-linked differences in risk and resiliency. Using functional magnetic resonance imaging and a task involving the visual perception of point-light displays of coherent and scrambled biological motion, we discovered sex differences in the development of neural systems for basic social perception. In adults, we identified enhanced activity during coherent biological motion perception in females relative to males in a network of brain regions previously implicated in social perception including amygdala, medial temporal gyrus, and temporal pole. These sex differences were less pronounced in our sample of school-age youth. We hypothesize that the robust neural circuitry supporting social perception in females, which diverges from males beginning in childhood, may underlie sex differences in disorders related to social processing. PMID:23876243

Molecularly Engineered Polymer-Based Systems in Drug Delivery and Regenerative Medicine.

PubMed

Piluso, Susanna; Soultan, Al Halifa; Patterson, Jennifer

2017-01-01

Polymer-based systems are attractive in drug delivery and regenerative medicine due to the possibility of tailoring their properties and functions to a specific application. The present review provides several examples of molecularly engineered polymer systems, including stimuli responsive polymers and supramolecular polymers. The advent of controlled polymerization techniques has enabled the preparation of polymers with controlled molecular weight and well-defined architecture. By using these techniques coupled to orthogonal chemical modification reactions, polymers can be molecularly engineered to incorporate functional groups able to respond to small changes in the local environment or to a specific biological signal. This review highlights the properties and applications of stimuli-responsive systems and polymer therapeutics, such as polymer-drug conjugates, polymer-protein conjugates, polymersomes, and hyperbranched systems. The applications of polymeric membranes in regenerative medicine are also discussed. The examples presented in this review suggest that the combination of membranes with polymers that are molecularly engineered to respond to specific biological functions could be relevant in the field of regenerative medicine. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Review of the fundamental theories behind small angle X-ray scattering, molecular dynamics simulations, and relevant integrated application.

PubMed

Boldon, Lauren; Laliberte, Fallon; Liu, Li

2015-01-01

In this paper, the fundamental concepts and equations necessary for performing small angle X-ray scattering (SAXS) experiments, molecular dynamics (MD) simulations, and MD-SAXS analyses were reviewed. Furthermore, several key biological and non-biological applications for SAXS, MD, and MD-SAXS are presented in this review; however, this article does not cover all possible applications. SAXS is an experimental technique used for the analysis of a wide variety of biological and non-biological structures. SAXS utilizes spherical averaging to produce one- or two-dimensional intensity profiles, from which structural data may be extracted. MD simulation is a computer simulation technique that is used to model complex biological and non-biological systems at the atomic level. MD simulations apply classical Newtonian mechanics' equations of motion to perform force calculations and to predict the theoretical physical properties of the system. This review presents several applications that highlight the ability of both SAXS and MD to study protein folding and function in addition to non-biological applications, such as the study of mechanical, electrical, and structural properties of non-biological nanoparticles. Lastly, the potential benefits of combining SAXS and MD simulations for the study of both biological and non-biological systems are demonstrated through the presentation of several examples that combine the two techniques.

[Topical issues of biological safety under current conditions. Part 2. Conceptual, terminological, and definitive framework of biological safety].

PubMed

Onishchenko, G G; Smolenskiĭ, V Iu; Ezhlova, E B; Demina, Iu V; Toporkov, V P; Toporkov, A V; Liapin, M N; Kutyrev, V V

2013-01-01

In accordance with the established conceptual base for the up-to-date broad interpretation of biological safety, and IHR (2005), developed is the notional, terminological, and definitive framework, comprising 33 elements. Key item of the nomenclature is the biological safety that is identified as population safety (individual, social, national) from direct and (or) human environment mediated (occupational, socio-economic, geopolitical infrastructures, ecological system) exposures to hazardous biological factors. Ultimate objective of the biological safety provision is to prevent and liquidate aftermaths of emergency situations of biological character either of natural or human origin (anthropogenic) arising from direct and indirect impact of the biological threats to the public health compatible with national and international security hazard. Elaborated terminological framework allows for the construction of self-sufficient semantic content for biological safety provision, subject to formalization in legislative, normative and methodological respects and indicative of improvement as regards organizational and structural-functional groundwork of the Russian Federation National chemical and biological safety system, which is to become topical issue of Part 3.

Quantum chemical methods for the investigation of photoinitiated processes in biological systems: theory and applications.

PubMed

Dreuw, Andreas

2006-11-13

With the advent of modern computers and advances in the development of efficient quantum chemical computer codes, the meaningful computation of large molecular systems at a quantum mechanical level became feasible. Recent experimental effort to understand photoinitiated processes in biological systems, for instance photosynthesis or vision, at a molecular level also triggered theoretical investigations in this field. In this Minireview, standard quantum chemical methods are presented that are applicable and recently used for the calculation of excited states of photoinitiated processes in biological molecular systems. These methods comprise configuration interaction singles, the complete active space self-consistent field method, and time-dependent density functional theory and its variants. Semiempirical approaches are also covered. Their basic theoretical concepts and mathematical equations are briefly outlined, and their properties and limitations are discussed. Recent successful applications of the methods to photoinitiated processes in biological systems are described and theoretical tools for the analysis of excited states are presented.

Bioprocess systems engineering: transferring traditional process engineering principles to industrial biotechnology.

PubMed

Koutinas, Michalis; Kiparissides, Alexandros; Pistikopoulos, Efstratios N; Mantalaris, Athanasios

2012-01-01

The complexity of the regulatory network and the interactions that occur in the intracellular environment of microorganisms highlight the importance in developing tractable mechanistic models of cellular functions and systematic approaches for modelling biological systems. To this end, the existing process systems engineering approaches can serve as a vehicle for understanding, integrating and designing biological systems and processes. Here, we review the application of a holistic approach for the development of mathematical models of biological systems, from the initial conception of the model to its final application in model-based control and optimisation. We also discuss the use of mechanistic models that account for gene regulation, in an attempt to advance the empirical expressions traditionally used to describe micro-organism growth kinetics, and we highlight current and future challenges in mathematical biology. The modelling research framework discussed herein could prove beneficial for the design of optimal bioprocesses, employing rational and feasible approaches towards the efficient production of chemicals and pharmaceuticals.

Bioprocess systems engineering: transferring traditional process engineering principles to industrial biotechnology

PubMed Central

Koutinas, Michalis; Kiparissides, Alexandros; Pistikopoulos, Efstratios N.; Mantalaris, Athanasios

2013-01-01

The complexity of the regulatory network and the interactions that occur in the intracellular environment of microorganisms highlight the importance in developing tractable mechanistic models of cellular functions and systematic approaches for modelling biological systems. To this end, the existing process systems engineering approaches can serve as a vehicle for understanding, integrating and designing biological systems and processes. Here, we review the application of a holistic approach for the development of mathematical models of biological systems, from the initial conception of the model to its final application in model-based control and optimisation. We also discuss the use of mechanistic models that account for gene regulation, in an attempt to advance the empirical expressions traditionally used to describe micro-organism growth kinetics, and we highlight current and future challenges in mathematical biology. The modelling research framework discussed herein could prove beneficial for the design of optimal bioprocesses, employing rational and feasible approaches towards the efficient production of chemicals and pharmaceuticals. PMID:24688682

Recent Developments in the Application of Biologically Inspired Computation to Chemical Sensing

NASA Astrophysics Data System (ADS)

Marco, S.; Gutierrez-Gálvez, A.

2009-05-01

Biological olfaction outperforms chemical instrumentation in specificity, response time, detection limit, coding capacity, time stability, robustness, size, power consumption, and portability. This biological function provides outstanding performance due, to a large extent, to the unique architecture of the olfactory pathway, which combines a high degree of redundancy, an efficient combinatorial coding along with unmatched chemical information processing mechanisms. The last decade has witnessed important advances in the understanding of the computational primitives underlying the functioning of the olfactory system. In this work, the state of the art concerning biologically inspired computation for chemical sensing will be reviewed. Instead of reviewing the whole body of computational neuroscience of olfaction, we restrict this review to the application of models to the processing of real chemical sensor data.

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.

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.

Membrane Protein Incorporation into Nano-Bioelectronics: An insight into Rhodopsin Controlled SiNW-FET Devices

NASA Astrophysics Data System (ADS)

Tunuguntla, Ramya

Biological systems use different energy sources to interact with their environments by creating ion gradients, membrane electric potentials, or a proton motive force to accomplish strikingly complex tasks on the nanometer length scale, such as energy harvesting, and whole organism replication. Most of this activity involves a vast arsenal of active and passive ion channels, membrane receptors and ion pumps that mediate complex and precise transport across biological membranes. Despite the remarkable rate of progress exhibited by modern microelectronic devices, they still cannot compete with the efficiency and precision of biological systems on the component level. At the same time, the sophistication of these molecular machines provides an excellent opportunity to use them in hybrid bioelectronic devices where such a combination could deliver enhanced electronic functionality and enable seamless bi-directional interfaces between man-made and biological assemblies. Artificial membrane systems allow researchers to study the structure and function of membrane proteins in a matrix that approximates their natural environment and to integrate these proteins in ex-vivo devices such as electronic biosensors, thin-film protein arrays, or bio-fuel cells. Since most membrane proteins have vectorial functions, both functional studies and applications require effective control over protein orientation within a lipid bilayer. In our work, we have explored the role of the bilayer surface charge in determining transmembrane protein orientation and functionality during formation of proteoliposomes. We reconstituted a model vectorial ion pump, proteorhodopsin, in liposomes of opposite charges and varying charge densities and determined the resultant protein orientation. Antibody-binding assay and proteolysis of proteoliposomes showed physical evidence of preferential orientation, and functional assays verified vectorial nature of ion transport in this system. Our results indicate that the manipulation of lipid composition can indeed control orientation of an asymmetrically charged membrane protein, proteorhodopsin, in liposomes. One-dimensional inorganic nanostructures, which have critical dimensions comparable to the sizes of biological molecules, form an excellent materials platform for building such integrated structures. Researchers already use silicon nanowire-based field effect transistors functionalized with molecular recognition sites in a diverse array of biosensors. In our group, we have been developing a platform for integration of membrane protein functionality and electronic devices using a 1-D phospholipid bilayer device architecture. In these devices, the membrane proteins reside within the lipid bilayer that covers a nanowire channel of a field-effect transistor. This lipid bilayer performs several functions: it shields the nanowire from the solution species; it serves as a native-like environment for membrane proteins and preserves their functionality, integrity, and even vectorality. In this work, we show that a 1-D bilayer device incorporating a rhodopsin proton pump allows us to couple light-driven proton transport to a bioelectronic circuit. We also report that we were able to adapt another distinctive feature of biological signal processing---their widespread use of modifiers, co-factors, and mediator molecules---to regulate and fine-tune the operational characteristics of the bioelectronic device. In our example, we use co-assembly of protein channels and ionophores in the 1-D bilayer to modify the device output levels and response time.

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.

Chronobiology of the neuroimmunoendocrine system and aging.

PubMed

Mate, Ianire; Madrid, Juan Antonio; De la Fuente, Mónica

2014-01-01

The health maintenance depends on the preservation of the homeostatic systems, such as nervous, endocrine and immune system, and a proper communication between them. In this regard, the circadian system, which promotes a better physiological system functions and thus well being, could be considered part of that homeostatic complex, since the neuroimmunoendocrine system possesses circadian patterns in most variables, as well as circannual or seasonal variations. With aging, an impairment of the homeostatic systems occurs and an alteration of circadian system regulation has been demonstrated. In the immune system, several function parameters, which are good markers of health and of the rate of aging, change not only with age (immunosenescence) but also throughout the day and year. Indeed, with advancing age there is a modification of immune cell circadian function especially in lymphocytes. Moreover, immune functions at early afternoon correspond to more aged values than at morning, especially in mature subjects (60-79 years of age). In addition, these mature men and women showed a significant impaired immune cell function, which is especially remarkable in the winter. It is noteworthy the role of immunomodulatory hormones, such as melatonin, in the regulation of biological rhythms and their involvement in the aging process. Furthermore, the evidence of a neuroimmune regulation of the circadian system and its disturbance with aging, highlights the importance of proinflammatory cytokines in this complex cross-talk. The biological rhythms disruption with age and some diseases (jet lag, cancer and seasonal affective disorder), could contribute increasing the immune system impairment and consequently the loss of health.

Advances in Omics and Bioinformatics Tools for Systems Analyses of Plant Functions

PubMed Central

Mochida, Keiichi; Shinozaki, Kazuo

2011-01-01

Omics and bioinformatics are essential to understanding the molecular systems that underlie various plant functions. Recent game-changing sequencing technologies have revitalized sequencing approaches in genomics and have produced opportunities for various emerging analytical applications. Driven by technological advances, several new omics layers such as the interactome, epigenome and hormonome have emerged. Furthermore, in several plant species, the development of omics resources has progressed to address particular biological properties of individual species. Integration of knowledge from omics-based research is an emerging issue as researchers seek to identify significance, gain biological insights and promote translational research. From these perspectives, we provide this review of the emerging aspects of plant systems research based on omics and bioinformatics analyses together with their associated resources and technological advances. PMID:22156726

Cysteine Cathepsins in the Secretory Vesicle Produce Active Peptides: Cathepsin L Generates Peptide Neurotransmitters and Cathepsin B Produces Beta-Amyloid of Alzheimer’s Disease

PubMed Central

Hook, Vivian; Funkelstein, Lydiane; Wegrzyn, Jill; Bark, Steven; Kindy, Mark; Hook, Gregory

2011-01-01

Recent new findings indicate significant biological roles of cysteine cathepsin proteases in secretory vesicles for production of biologically active peptides. Notably, cathepsin L in secretory vesicles has been demonstrated as a key protease for proteolytic processing of proneuropeptides (and prohormones) into active neuropeptides that are released to mediate cell-cell communication in the nervous system for neurotransmission. Moreover, cathepsin B in secretory vesicles has been recently identified as a β-secretase for production of neurotoxic β-amyloid (Aβ) peptides that accumulate in Alzheimer’s disease (AD), participating as a notable factor in the severe memory loss in AD. These secretory vesicle functions of cathepsins L and B for production of biologically active peptides contrasts with the well-known role of cathepsin proteases in lysosomes for the degradation of proteins to result in their inactivation. The unique secretory vesicle proteome indicates proteins of distinct functional categories that provide the intravesicular environment for support of cysteine cathepsin function. Features of the secretory vesicle protein systems insure optimized intravesicular conditions that support the proteolytic activity of cathepsins. These new findings of recently discovered biological roles of cathepsins L and B indicate their significance in human health and disease. PMID:21925292

Bio-hybrid cell-based actuators for microsystems.

PubMed

Carlsen, Rika Wright; Sitti, Metin

2014-10-15

As we move towards the miniaturization of devices to perform tasks at the nano and microscale, it has become increasingly important to develop new methods for actuation, sensing, and control. Over the past decade, bio-hybrid methods have been investigated as a promising new approach to overcome the challenges of scaling down robotic and other functional devices. These methods integrate biological cells with artificial components and therefore, can take advantage of the intrinsic actuation and sensing functionalities of biological cells. Here, the recent advancements in bio-hybrid actuation are reviewed, and the challenges associated with the design, fabrication, and control of bio-hybrid microsystems are discussed. As a case study, focus is put on the development of bacteria-driven microswimmers, which has been investigated as a targeted drug delivery carrier. Finally, a future outlook for the development of these systems is provided. The continued integration of biological and artificial components is envisioned to enable the performance of tasks at a smaller and smaller scale in the future, leading to the parallel and distributed operation of functional systems at the microscale. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Engineering responsive supramolecular biomaterials: Toward smart therapeutics.

PubMed

Webber, Matthew J

2016-09-01

Engineering materials using supramolecular principles enables generalizable and modular platforms that have tunable chemical, mechanical, and biological properties. Applying this bottom-up, molecular engineering-based approach to therapeutic design affords unmatched control of emergent properties and functionalities. In preparing responsive materials for biomedical applications, the dynamic character of typical supramolecular interactions facilitates systems that can more rapidly sense and respond to specific stimuli through a fundamental change in material properties or characteristics, as compared to cases where covalent bonds must be overcome. Several supramolecular motifs have been evaluated toward the preparation of "smart" materials capable of sensing and responding to stimuli. Triggers of interest in designing materials for therapeutic use include applied external fields, environmental changes, biological actuators, applied mechanical loading, and modulation of relative binding affinities. In addition, multistimuli-responsive routes can be realized that capture combinations of triggers for increased functionality. In sum, supramolecular engineering offers a highly functional strategy to prepare responsive materials. Future development and refinement of these approaches will improve precision in material formation and responsiveness, seek dynamic reciprocity in interactions with living biological systems, and improve spatiotemporal sensing of disease for better therapeutic deployment.

MicroRNAs from the Planarian Schmidtea mediterranea: a model system for stem cell biology.

PubMed

Palakodeti, Dasaradhi; Smielewska, Magda; Graveley, Brenton R

2006-09-01

MicroRNAs (miRNAs) are approximately 22-nt RNA molecules that typically bind to the 3' untranslated regions of target mRNAs and function to either induce mRNA degradation or repress translation. miRNAs have been shown to play important roles in the function of stem cells and cell lineage decisions in a variety of organisms, including humans. Planarians are bilaterally symmetric metazoans that have the unique ability to completely regenerate lost tissues or organs. This regenerative capacity is facilitated by a population of stem cells known as neoblasts. Planarians are therefore an excellent model system for studying many aspects of stem cell biology. Here we report the cloning and initial characterization of 71 miRNAs from the planarian Schmidtea mediterranea. While several of the S. mediterranea miRNAs are members of miRNA families identified in other species, we also identified a number of planarian-specific miRNAs. This work lays the foundation for functional studies aimed at addressing the role of these miRNAs in regeneration, cell lineage decisions, and basic stem cell biology.

Synergy among Microbiota and Their Hosts: Leveraging the Hawaiian Archipelago and Local Collaborative Networks To Address Pressing Questions in Microbiome Research

PubMed Central

Frank, Kiana L.; Alegado, Rosanna A.; Amend, Anthony S.; Arif, Mohammad; Bennett, Gordon M.; Jani, Andrea J.; Medeiros, Matthew C. I.; Mileyko, Yuriy; Nguyen, Nhu H.; Nigro, Olivia D.; Prisic, Sladjana; Shin, Sangwoo; Takagi, Daisuke; Wilson, Samuel T.; Yew, Joanne Y.

2018-01-01

ABSTRACT Despite increasing acknowledgment that microorganisms underpin the healthy functioning of basically all multicellular life, few cross-disciplinary teams address the diversity and function of microbiota across organisms and ecosystems. Our newly formed consortium of junior faculty spanning fields such as ecology and geoscience to mathematics and molecular biology from the University of Hawai‘i at Mānoa aims to fill this gap. We are united in our mutual interest in advancing a new paradigm for biology that incorporates our modern understanding of the importance of microorganisms. As our first concerted research effort, we will assess the diversity and function of microbes across an entire watershed on the island of Oahu, Hawai‘i. Due to its high ecological diversity across tractable areas of land and sea, Hawai‘i provides a model system for the study of complex microbial communities and the processes they mediate. Owing to our diverse expertise, we will leverage this study system to advance the field of biology. PMID:29556540

Strategies for structuring interdisciplinary education in Systems Biology: an European perspective

PubMed Central

Cvijovic, Marija; Höfer, Thomas; Aćimović, Jure; Alberghina, Lilia; Almaas, Eivind; Besozzi, Daniela; Blomberg, Anders; Bretschneider, Till; Cascante, Marta; Collin, Olivier; de Atauri, Pedro; Depner, Cornelia; Dickinson, Robert; Dobrzynski, Maciej; Fleck, Christian; Garcia-Ojalvo, Jordi; Gonze, Didier; Hahn, Jens; Hess, Heide Marie; Hollmann, Susanne; Krantz, Marcus; Kummer, Ursula; Lundh, Torbjörn; Martial, Gifta; dos Santos, Vítor Martins; Mauer-Oberthür, Angela; Regierer, Babette; Skene, Barbara; Stalidzans, Egils; Stelling, Jörg; Teusink, Bas; Workman, Christopher T; Hohmann, Stefan

2016-01-01

Systems Biology is an approach to biology and medicine that has the potential to lead to a better understanding of how biological properties emerge from the interaction of genes, proteins, molecules, cells and organisms. The approach aims at elucidating how these interactions govern biological function by employing experimental data, mathematical models and computational simulations. As Systems Biology is inherently multidisciplinary, education within this field meets numerous hurdles including departmental barriers, availability of all required expertise locally, appropriate teaching material and example curricula. As university education at the Bachelor’s level is traditionally built upon disciplinary degrees, we believe that the most effective way to implement education in Systems Biology would be at the Master’s level, as it offers a more flexible framework. Our team of experts and active performers of Systems Biology education suggest here (i) a definition of the skills that students should acquire within a Master’s programme in Systems Biology, (ii) a possible basic educational curriculum with flexibility to adjust to different application areas and local research strengths, (iii) a description of possible career paths for students who undergo such an education, (iv) conditions that should improve the recruitment of students to such programmes and (v) mechanisms for collaboration and excellence spreading among education professionals. With the growing interest of industry in applying Systems Biology approaches in their fields, a concerted action between academia and industry is needed to build this expertise. Here we present a reflection of the European situation and expertise, where most of the challenges we discuss are universal, anticipating that our suggestions will be useful internationally. We believe that one of the overriding goals of any Systems Biology education should be a student’s ability to phrase and communicate research questions in such a manner that they can be solved by the integration of experiments and modelling, as well as to communicate and collaborate productively across different experimental and theoretical disciplines in research and development. PMID:28725471

Next-Gen Gene Synthesis Enables Large-Scale Engineering in Biological Systems: Recent advances in synthetic biology are making this field more promising than ever.

PubMed

Leake, Devin

2015-01-01

As scientists make strides toward the goal of developing a form of biological engineering that's as predictive and reliable as chemical engineering is for chemistry, one technology component has become absolutely critical: gene synthesis. Gene synthesis is the process of building stretches of deoxyribonucleic acid (DNA) to order--some stretches based on DNA that exists already in nature, some based on novel designs intended to accomplish new functions. This process is the foundation of synthetic biology, which is rapidly becoming the engineering counterpart to biology.

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.

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.

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

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...

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.

Photo-Responsive Graphene and Carbon Nanotubes to Control and Tackle Biological Systems.

PubMed

Cardano, Francesca; Frasconi, Marco; Giordani, Silvia

2018-01-01

Photo-responsive multifunctional nanomaterials are receiving considerable attention for biological applications because of their unique properties. The functionalization of the surface of carbon nanotubes (CNTs) and graphene, among other carbon based nanomaterials, with molecular switches that exhibit reversible transformations between two or more isomers in response to different kind of external stimuli, such as electromagnetic radiation, temperature and pH, has allowed the control of the optical and electrical properties of the nanomaterial. Light-controlled molecular switches, such as azobenzene and spiropyran, have attracted a lot of attention for nanomaterial's functionalization because of the remote modulation of their physicochemical properties using light stimulus. The enhanced properties of the hybrid materials obtained from the coupling of carbon based nanomaterials with light-responsive switches has enabled the fabrication of smart devices for various biological applications, including drug delivery, bioimaging and nanobiosensors. In this review, we highlight the properties of photo-responsive carbon nanomaterials obtained by the conjugation of CNTs and graphene with azobenzenes and spiropyrans molecules to investigate biological systems, devising possible future directions in the field.

Photo-Responsive Graphene and Carbon Nanotubes to Control and Tackle Biological Systems

PubMed Central

Cardano, Francesca; Frasconi, Marco; Giordani, Silvia

2018-01-01

Photo-responsive multifunctional nanomaterials are receiving considerable attention for biological applications because of their unique properties. The functionalization of the surface of carbon nanotubes (CNTs) and graphene, among other carbon based nanomaterials, with molecular switches that exhibit reversible transformations between two or more isomers in response to different kind of external stimuli, such as electromagnetic radiation, temperature and pH, has allowed the control of the optical and electrical properties of the nanomaterial. Light-controlled molecular switches, such as azobenzene and spiropyran, have attracted a lot of attention for nanomaterial's functionalization because of the remote modulation of their physicochemical properties using light stimulus. The enhanced properties of the hybrid materials obtained from the coupling of carbon based nanomaterials with light-responsive switches has enabled the fabrication of smart devices for various biological applications, including drug delivery, bioimaging and nanobiosensors. In this review, we highlight the properties of photo-responsive carbon nanomaterials obtained by the conjugation of CNTs and graphene with azobenzenes and spiropyrans molecules to investigate biological systems, devising possible future directions in the field. PMID:29707534

Photo-Responsive Graphene and Carbon Nanotubes to Control and Tackle Biological Systems

NASA Astrophysics Data System (ADS)

Cardano, Francesca; Frasconi, Marco; Giordani, Silvia

2018-04-01

Photo-responsive multifunctional nanomaterials are receiving considerable attention for biological applications because of their unique properties. The functionalization of the surface of carbon nanotubes (CNTs) and graphene, among other carbon based nanomaterials, with molecular switches that exhibit reversible transformations between two or more isomers in response to different kind of external stimuli, such as electromagnetic radiation, temperature and pH, has allowed the control of the optical and electrical properties of the nanomaterial. Light-controlled molecular switches, such as azobenzene and spiropyran, have attracted a lot of attention for nanomaterial’s functionalization because of the remote modulation of their physicochemical properties using light stimulus. The enhanced properties of the hybrid materials obtained from the coupling of carbon based nanomaterials with light-responsive switches has enabled the fabrication of smart devices for various biological applications, including drug delivery, bioimaging and nanobiosensors. In this review, we highlight the properties of photo-responsive carbon nanomaterials obtained by the conjugation of CNTs and graphene with azobenzenes and spiropyrans molecules to investigate biological systems, devising possible future directions in the field.

Metabolomics: the apogee of the omic triology

PubMed Central

Patti, Gary J; Yanes, Oscar; Siuzdak, Gary

2013-01-01

Metabolites, the chemical entities that are transformed during metabolism, provide a functional readout of cellular biochemistry. With emerging technologies in mass spectrometry, thousands of metabolites can now be quantitatively measured from minimal amounts of biological material, which has thereby enabled systems-level analyses. By performing global metabolite profiling, also known as untargeted metabolomics, new discoveries linking cellular pathways to biological mechanism are being revealed and shaping our understanding of cell biology, physiology, and medicine. PMID:22436749

Classification and Analysis of Regulatory Pathways Using Graph Property, Biochemical and Physicochemical Property, and Functional Property

PubMed Central

Cai, Yu-Dong; Chou, Kuo-Chen

2011-01-01

Given a regulatory pathway system consisting of a set of proteins, can we predict which pathway class it belongs to? Such a problem is closely related to the biological function of the pathway in cells and hence is quite fundamental and essential in systems biology and proteomics. This is also an extremely difficult and challenging problem due to its complexity. To address this problem, a novel approach was developed that can be used to predict query pathways among the following six functional categories: (i) “Metabolism”, (ii) “Genetic Information Processing”, (iii) “Environmental Information Processing”, (iv) “Cellular Processes”, (v) “Organismal Systems”, and (vi) “Human Diseases”. The prediction method was established trough the following procedures: (i) according to the general form of pseudo amino acid composition (PseAAC), each of the pathways concerned is formulated as a 5570-D (dimensional) vector; (ii) each of components in the 5570-D vector was derived by a series of feature extractions from the pathway system according to its graphic property, biochemical and physicochemical property, as well as functional property; (iii) the minimum redundancy maximum relevance (mRMR) method was adopted to operate the prediction. A cross-validation by the jackknife test on a benchmark dataset consisting of 146 regulatory pathways indicated that an overall success rate of 78.8% was achieved by our method in identifying query pathways among the above six classes, indicating the outcome is quite promising and encouraging. To the best of our knowledge, the current study represents the first effort in attempting to identity the type of a pathway system or its biological function. It is anticipated that our report may stimulate a series of follow-up investigations in this new and challenging area. PMID:21980418

Integration of functional myotubes with a Bio-MEMS device for non-invasive interrogation.

PubMed

Wilson, Kerry; Molnar, Peter; Hickman, James

2007-07-01

We have developed a biological micro-electromechanical system (Bio-MEMS) device consisting of surface-modified microfabricated silicon cantilevers and an AFM detection apparatus for the study of cultured myotubes. With this system we are able to selectively stimulate the myotubes as well as report on a variety of physiological properties of the myotubes in real time and in a high-throughput manner. This system will serve as the foundation for future work integrating multiple tissue types for the creation of Bio-MEMS analogues of complex tissues and biological circuits.

What Happens to the Food We Eat? Children's Conceptions of the Structure and Function of the Digestive System.

ERIC Educational Resources Information Center

Teixeira, Francimar Martins

2000-01-01

Describes children's conceptions of the structure and function of the human digestive system based on an investigation carried out with children aged 4-10 (n=45). Finds that children possess biological knowledge as an independent knowledge domain from the age of four. Discusses acquisition of and barriers to scientific concepts related to human…

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

Diagnostic of students' misconceptions using the Biological Concepts Instrument (BCI): A method for conducting an educational needs assessment

PubMed Central

Champagne Queloz, Annie; Klymkowsky, Michael W.; Stern, Elsbeth; Hafen, Ernst; Köhler, Katja

2017-01-01

Concept inventories, constructed based on an analysis of students’ thinking and their explanations of scientific situations, serve as diagnostics for identifying misconceptions and logical inconsistencies and provide data that can help direct curricular reforms. In the current project, we distributed the Biological Concepts Instrument (BCI) to 17-18-year-old students attending the highest track of the Swiss school system (Gymnasium). Students’ performances on many questions related to evolution, genetics, molecular properties and functions were diverse. Important common misunderstandings were identified in the areas of evolutionary processes, molecular properties and an appreciation of stochastic processes in biological systems. Our observations provide further evidence that the BCI is efficient in identifying specific areas where targeted instruction is required. Based on these observations we have initiated changes at several levels to reconsider how biological systems are presented to university biology studies with the goal of improving student’s foundational understanding. PMID:28493960

Improved Dye Stability in Single-Molecule Fluorescence Experiments

NASA Astrophysics Data System (ADS)

EcheverrÍa Aitken, Colin; Marshall, R. Andrew; Pugi, Joseph D.

Complex biological systems challenge existing single-molecule methods. In particular, dye stability limits observation time in singlemolecule fluorescence applications. Current approaches to improving dye performance involve the addition of enzymatic oxygen scavenging systems and small molecule additives. We present an enzymatic oxygen scavenging system that improves dye stability in single-molecule experiments. Compared to the currently-employed glucose-oxidase/catalase system, the protocatechuate-3,4-dioxygenase system achieves lower dissolved oxygen concentration and stabilizes single Cy3, Cy5, and Alexa488 fluorophores. Moreover, this system possesses none of the limitations associated with the glucose oxidase/catalase system. We also tested the effects of small molecule additives in this system. Biological reducing agents significantly destabilize the Cy5 fluorophore as a function of reducing potential. In contrast, anti-oxidants stabilize the Cy3 and Alexa488 fluorophores. We recommend use of the protocatechuate-3,4,-dioxygenase system with antioxidant additives, and in the absence of biological reducing agents. This system should have wide application to single-molecule fluorescence experiments.

Biocellion: accelerating computer simulation of multicellular biological system models.

PubMed

Kang, Seunghwa; Kahan, Simon; McDermott, Jason; Flann, Nicholas; Shmulevich, Ilya

2014-11-01

Biological system behaviors are often the outcome of complex interactions among a large number of cells and their biotic and abiotic environment. Computational biologists attempt to understand, predict and manipulate biological system behavior through mathematical modeling and computer simulation. Discrete agent-based modeling (in combination with high-resolution grids to model the extracellular environment) is a popular approach for building biological system models. However, the computational complexity of this approach forces computational biologists to resort to coarser resolution approaches to simulate large biological systems. High-performance parallel computers have the potential to address the computing challenge, but writing efficient software for parallel computers is difficult and time-consuming. We have developed Biocellion, a high-performance software framework, to solve this computing challenge using parallel computers. To support a wide range of multicellular biological system models, Biocellion asks users to provide their model specifics by filling the function body of pre-defined model routines. Using Biocellion, modelers without parallel computing expertise can efficiently exploit parallel computers with less effort than writing sequential programs from scratch. We simulate cell sorting, microbial patterning and a bacterial system in soil aggregate as case studies. Biocellion runs on x86 compatible systems with the 64 bit Linux operating system and is freely available for academic use. Visit http://biocellion.com for additional information. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

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

The Chemo-Biological Outreach of Nano-Biomaterials: Implications for Tissue Engineering and Regenerative Medicine.

PubMed

Kumar, Pradeep; Choonara, Yahya E; Khan, Riaz A; Pillay, Viness

2017-01-01

Nanobiomaterials can be defined as materials interacting with and influencing the biological microenvironment at a nanointerface. Recently the basic as well as applied research related to nanobiomaterials - a conjugation of nano-, material- and life-sciences - has immensely evolved for therapeutics and related biotechnology areas. The current overview focused on the potential of nanobiomaterial-based substrates towards the generation of biocompatible surfaces, tissue engineering architectures, and regenerative medicine. Emphasis was given to chemomolecular functionalization of nanobiomaterials, nanobiomaterial composites, and morphomechanically modified nanoarchetypes and their inherent chemo-biological interaction with the biological microenvironment. Additionally, recent developments in nanobiomaterial substrate design and structure, chemo-biological interface related bio-systems uses and further evolving applications in health care, therapeutics and nanomedicine were discussed herein. Furthermore, a special emphasis was placed on the nano-chemo-biological interactions inherent to various nanobiomaterial substrates in close vicinity with biological systems. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Biological Implications of Dynamical Phases in Non-equilibrium Networks

NASA Astrophysics Data System (ADS)

Murugan, Arvind; Vaikuntanathan, Suriyanarayanan

2016-03-01

Biology achieves novel functions like error correction, ultra-sensitivity and accurate concentration measurement at the expense of free energy through Maxwell Demon-like mechanisms. The design principles and free energy trade-offs have been studied for a variety of such mechanisms. In this review, we emphasize a perspective based on dynamical phases that can explain commonalities shared by these mechanisms. Dynamical phases are defined by typical trajectories executed by non-equilibrium systems in the space of internal states. We find that coexistence of dynamical phases can have dramatic consequences for function vs free energy cost trade-offs. Dynamical phases can also provide an intuitive picture of the design principles behind such biological Maxwell Demons.

CADLIVE toolbox for MATLAB: automatic dynamic modeling of biochemical networks with comprehensive system analysis.

PubMed

Inoue, Kentaro; Maeda, Kazuhiro; Miyabe, Takaaki; Matsuoka, Yu; Kurata, Hiroyuki

2014-09-01

Mathematical modeling has become a standard technique to understand the dynamics of complex biochemical systems. To promote the modeling, we had developed the CADLIVE dynamic simulator that automatically converted a biochemical map into its associated mathematical model, simulated its dynamic behaviors and analyzed its robustness. To enhance the feasibility by CADLIVE and extend its functions, we propose the CADLIVE toolbox available for MATLAB, which implements not only the existing functions of the CADLIVE dynamic simulator, but also the latest tools including global parameter search methods with robustness analysis. The seamless, bottom-up processes consisting of biochemical network construction, automatic construction of its dynamic model, simulation, optimization, and S-system analysis greatly facilitate dynamic modeling, contributing to the research of systems biology and synthetic biology. This application can be freely downloaded from http://www.cadlive.jp/CADLIVE_MATLAB/ together with an instruction.

Endocannabinoids: Effectors of glucocorticoid signaling.

PubMed

Balsevich, Georgia; Petrie, Gavin N; Hill, Matthew N

2017-10-01

For decades, there has been speculation regarding the interaction of cannabinoids with glucocorticoid systems. Given the functional redundancy between many of the physiological effects of glucocorticoids and cannabinoids, it was originally speculated that the biological mechanisms of cannabinoids were mediated by direct interactions with glucocorticoid systems. With the discovery of the endocannabinoid system, additional research demonstrated that it was actually the opposite; glucocorticoids recruit endocannabinoid signaling, and that the engagement of endocannabinoid signaling mediated many of the neurobiological and physiological effects of glucocorticoids. With the development of advances in pharmacology and genetics, significant advances in this area have been made, and it is now clear that functional interactions between these systems are critical for a wide array of physiological processes. The current review acts a comprehensive summary of the contemporary state of knowledge regarding the biological interactions between glucocorticoids and endocannabinoids, and their potential role in health and disease. Copyright © 2017 Elsevier Inc. All rights reserved.

Developing and applying the adverse outcome pathway ...

EPA Pesticide Factsheets

To support a paradigm shift in regulatory toxicology testing and risk assessment, the Adverse Outcome Pathway (AOP) concept has recently been proposed. This concept is similar to that for Mode of Action (MOA), describing a sequence of measurable key events triggered by a molecular initiating event in which a stressor interacts with a biological target. The resulting cascade of key events includes molecular, cellular, structural and functional changes in biological systems, resulting in a measurable adverse outcome. Thereby, an AOP ideally provides information relevant to chemical structure-activity relationships as a basis to predict effects for structurally similar compounds. AOPs could potentially also form the basis for qualitative and quantitative predictive modeling of the human adverse outcome resulting from molecular initiating or other key events for which higher-throughput testing methods are available or can be developed.A variety of cellular and molecular processes are known to be critical to normal function of the central (CNS) and peripheral nervous systems (PNS). Because of the biological and functional complexity of the CNS and PNS, it has been challenging to establish causative links and quantitative relationships between key events that comprise the pathways leading from chemical exposure to an adverse outcome in the nervous system. Following introduction of principles of the description and assessment of MOA and AOPs, examples of adverse out

From proteomics to systems biology: MAPA, MASS WESTERN, PROMEX, and COVAIN as a user-oriented platform.

PubMed

Weckwerth, Wolfram; Wienkoop, Stefanie; Hoehenwarter, Wolfgang; Egelhofer, Volker; Sun, Xiaoliang

2014-01-01

Genome sequencing and systems biology are revolutionizing life sciences. Proteomics emerged as a fundamental technique of this novel research area as it is the basis for gene function analysis and modeling of dynamic protein networks. Here a complete proteomics platform suited for functional genomics and systems biology is presented. The strategy includes MAPA (mass accuracy precursor alignment; http://www.univie.ac.at/mosys/software.html ) as a rapid exploratory analysis step; MASS WESTERN for targeted proteomics; COVAIN ( http://www.univie.ac.at/mosys/software.html ) for multivariate statistical analysis, data integration, and data mining; and PROMEX ( http://www.univie.ac.at/mosys/databases.html ) as a database module for proteogenomics and proteotypic peptides for targeted analysis. Moreover, the presented platform can also be utilized to integrate metabolomics and transcriptomics data for the analysis of metabolite-protein-transcript correlations and time course analysis using COVAIN. Examples for the integration of MAPA and MASS WESTERN data, proteogenomic and metabolic modeling approaches for functional genomics, phosphoproteomics by integration of MOAC (metal-oxide affinity chromatography) with MAPA, and the integration of metabolomics, transcriptomics, proteomics, and physiological data using this platform are presented. All software and step-by-step tutorials for data processing and data mining can be downloaded from http://www.univie.ac.at/mosys/software.html.

Microbial Community Profiles in Wastewaters from Onsite Wastewater Treatment Systems Technology

PubMed Central

Jałowiecki, Łukasz; Chojniak, Joanna Małgorzata; Dorgeloh, Elmar; Hegedusova, Berta; Ejhed, Helene; Magnér, Jörgen; Płaza, Grażyna Anna

2016-01-01

The aim of the study was to determine the potential of community-level physiological profiles (CLPPs) methodology as an assay for characterization of the metabolic diversity of wastewater samples and to link the metabolic diversity patterns to efficiency of select onsite biological wastewater facilities. Metabolic fingerprints obtained from the selected samples were used to understand functional diversity implied by the carbon substrate shifts. Three different biological facilities of onsite wastewater treatment were evaluated: fixed bed reactor (technology A), trickling filter/biofilter system (technology B), and aerated filter system (the fluidized bed reactor, technology C). High similarities of the microbial community functional structures were found among the samples from the three onsite wastewater treatment plants (WWTPs), as shown by the diversity indices. Principal components analysis (PCA) showed that the diversity and CLPPs of microbial communities depended on the working efficiency of the wastewater treatment technologies. This study provided an overall picture of microbial community functional structures of investigated samples in WWTPs and discerned the linkages between microbial communities and technologies of onsite WWTPs used. The results obtained confirmed that metabolic profiles could be used to monitor treatment processes as valuable biological indicators of onsite wastewater treatment technologies efficiency. This is the first step toward understanding relations of technology types with microbial community patterns in raw and treated wastewaters. PMID:26807728

Ultrathin Ceramic Membranes as Scaffolds for Functional Cell Coculture Models on a Biomimetic Scale

PubMed Central

Jud, Corinne; Ahmed, Sher; Müller, Loretta; Kinnear, Calum; Vanhecke, Dimitri; Umehara, Yuki; Frey, Sabine; Liley, Martha; Angeloni, Silvia; Petri-Fink, Alke; Rothen-Rutishauser, Barbara

2015-01-01

Abstract Epithelial tissue serves as an interface between biological compartments. Many in vitro epithelial cell models have been developed as an alternative to animal experiments to answer a range of research questions. These in vitro models are grown on permeable two-chamber systems; however, commercially available, polymer-based cell culture inserts are around 10 μm thick. Since the basement membrane found in biological systems is usually less than 1 μm thick, the 10-fold thickness of cell culture inserts is a major limitation in the establishment of realistic models. In this work, an alternative insert, accommodating an ultrathin ceramic membrane with a thickness of only 500 nm (i.e., the Silicon nitride Microporous Permeable Insert [SIMPLI]-well), was produced and used to refine an established human alveolar barrier coculture model by both replacing the conventional inserts with the SIMPLI-well and completing it with endothelial cells. The structural–functional relationship of the model was evaluated, including the translocation of gold nanoparticles across the barrier, revealing a higher translocation if compared to corresponding polyethylene terephthalate (PET) membranes. This study demonstrates the power of the SIMPLI-well system as a scaffold for epithelial tissue cell models on a truly biomimetic scale, allowing construction of more functionally accurate models of human biological barriers. PMID:26713225

Biological roles and functional mechanisms of arenavirus Z protein in viral replication.

PubMed

Wang, Jialong; Danzy, Shamika; Kumar, Naveen; Ly, Hinh; Liang, Yuying

2012-09-01

Arenaviruses can cause severe hemorrhagic fever diseases in humans, with limited prophylactic or therapeutic measures. A small RING-domain viral protein Z has been shown to mediate the formation of virus-like particles and to inhibit viral RNA synthesis, although its biological roles in an infectious viral life cycle have not been directly addressed. By taking advantage of the available reverse genetics system for a model arenavirus, Pichinde virus (PICV), we provide the direct evidence for the essential biological roles of the Z protein's conserved residues, including the G2 myristylation site, the conserved C and H residues of RING domain, and the poorly characterized C-terminal L79 and P80 residues. Dicodon substitutions within the late (L) domain (PSAPPYEP) of the PICV Z protein, although producing viable mutant viruses, have significantly reduced virus growth, a finding suggestive of an important role for the intact L domain in viral replication. Further structure-function analyses of both PICV and Lassa fever virus Z proteins suggest that arenavirus Z proteins have similar molecular mechanisms in mediating their multiple functions, with some interesting variations, such as the role of the G2 residue in blocking viral RNA synthesis. In summary, our studies have characterized the biological roles of the Z protein in an infectious arenavirus system and have shed important light on the distinct functions of its domains in virus budding and viral RNA regulation, the knowledge of which may lead to the development of novel antiviral drugs.

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

Molecular biomimetics: GEPI-based biological routes to technology.

PubMed

Tamerler, Candan; Khatayevich, Dmitriy; Gungormus, Mustafa; Kacar, Turgay; Oren, E Emre; Hnilova, Marketa; Sarikaya, Mehmet

2010-01-01

In nature, the viability of biological systems is sustained via specific interactions among the tens of thousands of proteins, the major building blocks of organisms from the simplest single-celled to the most complex multicellular species. Biomolecule-material interaction is accomplished with molecular specificity and efficiency leading to the formation of controlled structures and functions at all scales of dimensional hierarchy. Through evolution, Mother Nature developed molecular recognition by successive cycles of mutation and selection. Molecular specificity of probe-target interactions, e.g., ligand-receptor, antigen-antibody, is always based on specific peptide molecular recognition. Using biology as a guide, we can now understand, engineer, and control peptide-material interactions and exploit them as a new design tool for novel materials and systems. We adapted the protocols of combinatorially designed peptide libraries, via both cell surface or phage display methods; using these we select short peptides with specificity to a variety of practical materials. These genetically engineered peptides for inorganics (GEPI) are then studied experimentally to establish their binding kinetics and surface stability. The bound peptide structure and conformations are interrogated both experimentally and via modeling, and self-assembly characteristics are tested via atomic force microscopy. We further engineer the peptide binding and assembly characteristics using a computational biomimetics approach where bioinformatics based peptide-sequence similarity analysis is developed to design higher generation function-specific peptides. The molecular biomimetic approach opens up new avenues for the design and utilization of multifunctional molecular systems in a wide-range of applications from tissue engineering, disease diagnostics, and therapeutics to various areas of nanotechnology where integration is required among inorganic, organic and biological materials. Here, we describe lessons from biology with examples of protein-mediated functional biological materials, explain how novel peptides can be designed with specific affinity to inorganic solids using evolutionary engineering approaches, give examples of their potential utilizations in technology and medicine, and, finally, provide a summary of challenges and future prospects. (c) 2010 Wiley Periodicals, Inc.

Recent Progress in the Development of Metabolome Databases for Plant Systems Biology

PubMed Central

Fukushima, Atsushi; Kusano, Miyako

2013-01-01

Metabolomics has grown greatly as a functional genomics tool, and has become an invaluable diagnostic tool for biochemical phenotyping of biological systems. Over the past decades, a number of databases involving information related to mass spectra, compound names and structures, statistical/mathematical models and metabolic pathways, and metabolite profile data have been developed. Such databases complement each other and support efficient growth in this area, although the data resources remain scattered across the World Wide Web. Here, we review available metabolome databases and summarize the present status of development of related tools, particularly focusing on the plant metabolome. Data sharing discussed here will pave way for the robust interpretation of metabolomic data and advances in plant systems biology. PMID:23577015

A CRISPR-based MLST Scheme for Understanding the Population Biology and Epidemiology of Salmonella Enterica

DTIC Science & Technology

2015-05-26

in other systems , or whether it has alternative functions. Here, we report that CRISPR can be used to subtype Salmonella enterica serovariants...protects the bacteria against foreign DNA as described in other systems , or whether it has alternative functions. Here, we report that CRISPR can be...N. Shariat, R. E. Timme, J. B. Pettengill, R. Barrangou, E. G. Dudley. Characterization and evolution of Salmonella CRISPR-Cas systems

Optimality principles in the regulation of metabolic networks.

PubMed

Berkhout, Jan; Bruggeman, Frank J; Teusink, Bas

2012-08-29

One of the challenging tasks in systems biology is to understand how molecular networks give rise to emergent functionality and whether universal design principles apply to molecular networks. To achieve this, the biophysical, evolutionary and physiological constraints that act on those networks need to be identified in addition to the characterisation of the molecular components and interactions. Then, the cellular "task" of the network-its function-should be identified. A network contributes to organismal fitness through its function. The premise is that the same functions are often implemented in different organisms by the same type of network; hence, the concept of design principles. In biology, due to the strong forces of selective pressure and natural selection, network functions can often be understood as the outcome of fitness optimisation. The hypothesis of fitness optimisation to understand the design of a network has proven to be a powerful strategy. Here, we outline the use of several optimisation principles applied to biological networks, with an emphasis on metabolic regulatory networks. We discuss the different objective functions and constraints that are considered and the kind of understanding that they provide.

Entrainment to periodic initiation and transition rates in a computational model for gene translation.

PubMed

Margaliot, Michael; Sontag, Eduardo D; Tuller, Tamir

2014-01-01

Periodic oscillations play an important role in many biomedical systems. Proper functioning of biological systems that respond to periodic signals requires the ability to synchronize with the periodic excitation. For example, the sleep/wake cycle is a manifestation of an internal timing system that synchronizes to the solar day. In the terminology of systems theory, the biological system must entrain or phase-lock to the periodic excitation. Entrainment is also important in synthetic biology. For example, connecting several artificial biological systems that entrain to a common clock may lead to a well-functioning modular system. The cell-cycle is a periodic program that regulates DNA synthesis and cell division. Recent biological studies suggest that cell-cycle related genes entrain to this periodic program at the gene translation level, leading to periodically-varying protein levels of these genes. The ribosome flow model (RFM) is a deterministic model obtained via a mean-field approximation of a stochastic model from statistical physics that has been used to model numerous processes including ribosome flow along the mRNA. Here we analyze the RFM under the assumption that the initiation and/or transition rates vary periodically with a common period T. We show that the ribosome distribution profile in the RFM entrains to this periodic excitation. In particular, the protein synthesis pattern converges to a unique periodic solution with period T. To the best of our knowledge, this is the first proof of entrainment in a mathematical model for translation that encapsulates aspects such as initiation and termination rates, ribosomal movement and interactions, and non-homogeneous elongation speeds along the mRNA. Our results support the conjecture that periodic oscillations in tRNA levels and other factors related to the translation process can induce periodic oscillations in protein levels, and may suggest a new approach for re-engineering genetic systems to obtain a desired, periodic, protein synthesis rate.

Novel approaches to determine contractile function of the isolated adult zebrafish ventricular cardiac myocyte.

PubMed

Dvornikov, Alexey V; Dewan, Sukriti; Alekhina, Olga V; Pickett, F Bryan; de Tombe, Pieter P

2014-05-01

The zebrafish (Danio rerio) has been used extensively in cardiovascular biology, but mainly in the study of heart development. The relative ease of its genetic manipulation may indicate the suitability of this species as a cost-effective model system for the study of cardiac contractile biology. However, whether the zebrafish heart is an appropriate model system for investigations pertaining to mammalian cardiac contractile structure-function relationships remains to be resolved. Myocytes were isolated from adult zebrafish hearts by enzymatic digestion, attached to carbon rods, and twitch force and intracellular Ca(2+) were measured. We observed the modulation of twitch force, but not of intracellular Ca(2+), by both extracellular [Ca(2+)] and sarcomere length. In permeabilized cells/myofibrils, we found robust myofilament length-dependent activation. Moreover, modulation of myofilament activation-relaxation and force redevelopment kinetics by varied Ca(2+) activation levels resembled that found previously in mammalian myofilaments. We conclude that the zebrafish is a valid model system for the study of cardiac contractile structure-function relationships.

Real-time electrical detection of nitric oxide in biological systems with sub-nanomolar sensitivity

NASA Astrophysics Data System (ADS)

Jiang, Shan; Cheng, Rui; Wang, Xiang; Xue, Teng; Liu, Yuan; Nel, Andre; Huang, Yu; Duan, Xiangfeng

2013-07-01

Real-time monitoring of nitric oxide concentrations is of central importance for probing the diverse roles of nitric oxide in neurotransmission, cardiovascular systems and immune responses. Here we report a new design of nitric oxide sensors based on hemin-functionalized graphene field-effect transistors. With its single atom thickness and the highest carrier mobility among all materials, graphene holds the promise for unprecedented sensitivity for molecular sensing. The non-covalent functionalization through π-π stacking interaction allows reliable immobilization of hemin molecules on graphene without damaging the graphene lattice to ensure the highly sensitive and specific detection of nitric oxide. Our studies demonstrate that the graphene-hemin sensors can respond rapidly to nitric oxide in physiological environments with a sub-nanomolar sensitivity. Furthermore, in vitro studies show that the graphene-hemin sensors can be used for the detection of nitric oxide released from macrophage cells and endothelial cells, demonstrating their practical functionality in complex biological systems.

GENESIS 1.1: A hybrid-parallel molecular dynamics simulator with enhanced sampling algorithms on multiple computational platforms.

PubMed

Kobayashi, Chigusa; Jung, Jaewoon; Matsunaga, Yasuhiro; Mori, Takaharu; Ando, Tadashi; Tamura, Koichi; Kamiya, Motoshi; Sugita, Yuji

2017-09-30

GENeralized-Ensemble SImulation System (GENESIS) is a software package for molecular dynamics (MD) simulation of biological systems. It is designed to extend limitations in system size and accessible time scale by adopting highly parallelized schemes and enhanced conformational sampling algorithms. In this new version, GENESIS 1.1, new functions and advanced algorithms have been added. The all-atom and coarse-grained potential energy functions used in AMBER and GROMACS packages now become available in addition to CHARMM energy functions. The performance of MD simulations has been greatly improved by further optimization, multiple time-step integration, and hybrid (CPU + GPU) computing. The string method and replica-exchange umbrella sampling with flexible collective variable choice are used for finding the minimum free-energy pathway and obtaining free-energy profiles for conformational changes of a macromolecule. These new features increase the usefulness and power of GENESIS for modeling and simulation in biological research. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Clarity of objectives and working principles enhances the success of biomimetic programs.

PubMed

Wolff, Jonas O; Wells, David; Reid, Chris R; Blamires, Sean J

2017-09-26

Biomimetics, the transfer of functional principles from living systems into product designs, is increasingly being utilized by engineers. Nevertheless, recurring problems must be overcome if it is to avoid becoming a short-lived fad. Here we assess the efficiency and suitability of methods typically employed by examining three flagship examples of biomimetic design approaches from different disciplines: (1) the creation of gecko-inspired adhesives; (2) the synthesis of spider silk, and (3) the derivation of computer algorithms from natural self-organizing systems. We find that identification of the elemental working principles is the most crucial step in the biomimetic design process. It bears the highest risk of failure (e.g. losing the target function) due to false assumptions about the working principle. Common problems that hamper successful implementation are: (i) a discrepancy between biological functions and the desired properties of the product, (ii) uncertainty about objectives and applications, (iii) inherent limits in methodologies, and (iv) false assumptions about the biology of the models. Projects that aim for multi-functional products are particularly challenging to accomplish. We suggest a simplification, modularisation and specification of objectives, and a critical assessment of the suitability of the model. Comparative analyses, experimental manipulation, and numerical simulations followed by tests of artificial models have led to the successful extraction of working principles. A searchable database of biological systems would optimize the choice of a model system in top-down approaches that start at an engineering problem. Only when biomimetic projects become more predictable will there be wider acceptance of biomimetics as an innovative problem-solving tool among engineers and industry.

Membrane Lipid Oscillation: An Emerging System of Molecular Dynamics in the Plant Membrane.

PubMed

Nakamura, Yuki

2018-03-01

Biological rhythm represents a major biological process of living organisms. However, rhythmic oscillation of membrane lipid content is poorly described in plants. The development of lipidomic technology has led to the illustration of precise molecular profiles of membrane lipids under various growth conditions. Compared with conventional lipid signaling, which produces unpredictable lipid changes in response to ever-changing environmental conditions, lipid oscillation generates a fairly predictable lipid profile, adding a new layer of biological function to the membrane system and possible cross-talk with the other chronobiological processes. This mini review covers recent studies elucidating membrane lipid oscillation in plants.

Integrative structure modeling with the Integrative Modeling Platform.

PubMed

Webb, Benjamin; Viswanath, Shruthi; Bonomi, Massimiliano; Pellarin, Riccardo; Greenberg, Charles H; Saltzberg, Daniel; Sali, Andrej

2018-01-01

Building models of a biological system that are consistent with the myriad data available is one of the key challenges in biology. Modeling the structure and dynamics of macromolecular assemblies, for example, can give insights into how biological systems work, evolved, might be controlled, and even designed. Integrative structure modeling casts the building of structural models as a computational optimization problem, for which information about the assembly is encoded into a scoring function that evaluates candidate models. Here, we describe our open source software suite for integrative structure modeling, Integrative Modeling Platform (https://integrativemodeling.org), and demonstrate its use. © 2017 The Protein Society.

Prediction of EST functional relationships via literature mining with user-specified parameters.

PubMed

Wang, Hei-Chia; Huang, Tian-Hsiang

2009-04-01

The massive amount of expressed sequence tags (ESTs) gathered over recent years has triggered great interest in efficient applications for genomic research. In particular, EST functional relationships can be used to determine a possible gene network for biological processes of interest. In recent years, many researchers have tried to determine EST functional relationships by analyzing the biological literature. However, it has been challenging to find efficient prediction methods. Moreover, an annotated EST is usually associated with many functions, so successful methods must be able to distinguish between relevant and irrelevant functions based on user specifications. This paper proposes a method to discover functional relationships between ESTs of interest by analyzing literature from the Medical Literature Analysis and Retrieval System Online, with user-specified parameters for selecting keywords. This method performs better than the multiple kernel documents method in setting up a specific threshold for gathering materials. The method is also able to uncover known functional relationships, as shown by a comparison with the Kyoto Encyclopedia of Genes and Genomes database. The reliable EST relationships predicted by the proposed method can help to construct gene networks for specific biological functions of interest.

The Temperature Optima and Temperature Sensitivity of Soil Respiration Explained By Macromolecular Rate Theory (MMRT).

NASA Astrophysics Data System (ADS)

Schipper, L. A.; O'Neill, T.; Arcus, V. L.

2014-12-01

One of the most fundamental factors controlling all biological and chemical processes is changing temperature. Temperature dependence was originally described by the Arrhenius function in the 19th century. This function provides an excellent description of chemical reaction rates. However, the Arrhenius function does not predict the temperature optimum of biological rates that is clearly evident in laboratory and field measurements. Previously, the temperature optimum of biological processes has been ascribed to denaturation of enzymes but the observed temperature optima in soil are often rather modest, occurring at about 40-50°C and generally less than recognised temperatures for protein unfolding. We have modified the Arrhenius function incorporating a temperature-dependent activation energy derived directly from first principles from thermodynamics of macromolecules. MacroMolecular Rate Theory (MMRT) accounts for large changes in the flexibility of enzymes during catalysis that result in changes in heat capacity (ΔC‡p) of the enzyme during the reaction. MMRT predicts an initially Arrhenius-like response followed by a temperature optimum without the need for enzyme denaturation (Hobbs et al., 2013. ACS Chemical Biology. 8: 2388-2393). Denaturation, of course, occurs at much higher temperatures. We have shown that MMRT fits biogeochemical data collected from laboratory and field studies with important implications for changes in absolute temperature sensitivity as temperature rises (Schipper et al., 2014. Global Change Biology). As the temperature optimum is approached the absolute temperature sensitivity of biological processes decreases to zero. Consequently, the absolute temperature-sensitivity of soil biological processes depends on both the change in ecosystem temperature and the temperature optimum of the biological process. MMRT also very clearly explains why Q10 values decline with increasing temperature more quickly than would be predicted from the Arrhenius function. Temperature optima of many soil biological processes including respiration are very poorly documented but would lead to a better understanding of how soil systems will respond to increasing global temperatures.

Steroid receptors and their ligands: Effects on male gamete functions

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

Aquila, Saveria; De Amicis, Francesca, E-mail: francesca.deamicis@unical.it

In recent years a new picture of human sperm biology is emerging. It is now widely recognized that sperm contain nuclear encoded mRNA, mitochondrial encoded RNA and different transcription factors including steroid receptors, while in the past sperm were considered incapable of transcription and translation. One of the main targets of steroid hormones and their receptors is reproductive function. Expression studies on Progesterone Receptor, estrogen receptor, androgen receptor and their specific ligands, demonstrate the presence of these systems in mature spermatozoa as surface but also as nuclear conventional receptors, suggesting that both systemic and local steroid hormones, through sperm receptors,more » may influence male reproduction. However, the relationship between the signaling events modulated by steroid hormones and sperm fertilization potential as well as the possible involvement of the specific receptors are still controversial issues. The main line of this review highlights the current research in human sperm biology examining new molecular systems of response to the hormones as well as specific regulatory pathways controlling sperm cell fate and biological functions. Most significant studies regarding the identification of steroid receptors are reported and the mechanistic insights relative to signaling pathways, together with the change in sperm metabolism energy influenced by steroid hormones are discussed.The reviewed evidences suggest important effects of Progesterone, Estrogen and Testosterone and their receptors on spermatozoa and implicate the involvement of both systemic and local steroid action in the regulation of male fertility potential. - Highlights: • One of the main targets of steroid hormones and their receptors is reproductive function. • Pg/PR co-work to stimulate enzymatic activities to sustain a capacitation process. • E2/ERs regulate sperm motility, capacitation and acrosome reaction and act as survival factors. • Androgens/AR mediate sperm death which is a novel field of investigation in sperm biology.« less

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.

BioASF: a framework for automatically generating executable pathway models specified in BioPAX.

PubMed

Haydarlou, Reza; Jacobsen, Annika; Bonzanni, Nicola; Feenstra, K Anton; Abeln, Sanne; Heringa, Jaap

2016-06-15

Biological pathways play a key role in most cellular functions. To better understand these functions, diverse computational and cell biology researchers use biological pathway data for various analysis and modeling purposes. For specifying these biological pathways, a community of researchers has defined BioPAX and provided various tools for creating, validating and visualizing BioPAX models. However, a generic software framework for simulating BioPAX models is missing. Here, we attempt to fill this gap by introducing a generic simulation framework for BioPAX. The framework explicitly separates the execution model from the model structure as provided by BioPAX, with the advantage that the modelling process becomes more reproducible and intrinsically more modular; this ensures natural biological constraints are satisfied upon execution. The framework is based on the principles of discrete event systems and multi-agent systems, and is capable of automatically generating a hierarchical multi-agent system for a given BioPAX model. To demonstrate the applicability of the framework, we simulated two types of biological network models: a gene regulatory network modeling the haematopoietic stem cell regulators and a signal transduction network modeling the Wnt/β-catenin signaling pathway. We observed that the results of the simulations performed using our framework were entirely consistent with the simulation results reported by the researchers who developed the original models in a proprietary language. The framework, implemented in Java, is open source and its source code, documentation and tutorial are available at http://www.ibi.vu.nl/programs/BioASF CONTACT: j.heringa@vu.nl. © The Author 2016. Published by Oxford University Press.

Development and application of automated systems for plasmid-based functional proteomics to improve syntheitc biology of engineered industrial microbes for high level expression of proteases for biofertilizer production

USDA-ARS?s Scientific Manuscript database

In addition to microarray technology, which provides a robust method to study protein function in a rapid, economical, and proteome-wide fashion, plasmid-based functional proteomics is an important technology for rapidly obtaining large quantities of protein and determining protein function across a...

Considerations to improve functional annotations in biological databases.

PubMed

Benítez-Páez, Alfonso

2009-12-01

Despite the great effort to design efficient systems allowing the electronic indexation of information concerning genes, proteins, structures, and interactions published daily in scientific journals, some problems are still observed in specific tasks such as functional annotation. The annotation of function is a critical issue for bioinformatic routines, such as for instance, in functional genomics and the further prediction of unknown protein function, which are highly dependent of the quality of existing annotations. Some information management systems evolve to efficiently incorporate information from large-scale projects, but often, annotation of single records from the literature is difficult and slow. In this short report, functional characterizations of a representative sample of the entire set of uncharacterized proteins from Escherichia coli K12 was compiled from Swiss-Prot, PubMed, and EcoCyc and demonstrate a functional annotation deficit in biological databases. Some issues are postulated as causes of the lack of annotation, and different solutions are evaluated and proposed to avoid them. The hope is that as a consequence of these observations, there will be new impetus to improve the speed and quality of functional annotation and ultimately provide updated, reliable information to the scientific community.

Simulations in Medicine and Biology: Insights and perspectives

NASA Astrophysics Data System (ADS)

Spyrou, George M.

2015-01-01

Modern medicine and biology have been transformed into quantitative sciences of high complexity, with challenging objectives. The aims of medicine are related to early diagnosis, effective therapy, accurate intervention, real time monitoring, procedures/systems/instruments optimization, error reduction, and knowledge extraction. Concurrently, following the explosive production of biological data concerning DNA, RNA, and protein biomolecules, a plethora of questions has been raised in relation to their structure and function, the interactions between them, their relationships and dependencies, their regulation and expression, their location, and their thermodynamic characteristics. Furthermore, the interplay between medicine and biology gives rise to fields like molecular medicine and systems biology which are further interconnected with physics, mathematics, informatics, and engineering. Modelling and simulation is a powerful tool in the fields of Medicine and Biology. Simulating the phenomena hidden inside a diagnostic or therapeutic medical procedure, we are able to obtain control on the whole system and perform multilevel optimization. Furthermore, modelling and simulation gives insights in the various scales of biological representation, facilitating the understanding of the huge amounts of derived data and the related mechanisms behind them. Several examples, as well as the insights and the perspectives of simulations in biomedicine will be presented.

[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.

Tetrazine ligation for chemical proteomics.

PubMed

Kang, Kyungtae; Park, Jongmin; Kim, Eunha

2016-01-01

Determining small molecule-target protein interaction is essential for the chemical proteomics. One of the most important keys to explore biological system in chemical proteomics field is finding first-class molecular tools. Chemical probes can provide great spatiotemporal control to elucidate biological functions of proteins as well as for interrogating biological pathways. The invention of bioorthogonal chemistry has revolutionized the field of chemical biology by providing superior chemical tools and has been widely used for investigating the dynamics and function of biomolecules in live condition. Among 20 different bioorthogonal reactions, tetrazine ligation has been spotlighted as the most advanced bioorthogonal chemistry because of their extremely faster kinetics and higher specificity than others. Therefore, tetrazine ligation has a tremendous potential to enhance the proteomic research. This review highlights the current status of tetrazine ligation reaction as a molecular tool for the chemical proteomics.

Persistent Memory in Single Node Delay-Coupled Reservoir Computing.

PubMed

Kovac, André David; Koall, Maximilian; Pipa, Gordon; Toutounji, Hazem

2016-01-01

Delays are ubiquitous in biological systems, ranging from genetic regulatory networks and synaptic conductances, to predator/pray population interactions. The evidence is mounting, not only to the presence of delays as physical constraints in signal propagation speed, but also to their functional role in providing dynamical diversity to the systems that comprise them. The latter observation in biological systems inspired the recent development of a computational architecture that harnesses this dynamical diversity, by delay-coupling a single nonlinear element to itself. This architecture is a particular realization of Reservoir Computing, where stimuli are injected into the system in time rather than in space as is the case with classical recurrent neural network realizations. This architecture also exhibits an internal memory which fades in time, an important prerequisite to the functioning of any reservoir computing device. However, fading memory is also a limitation to any computation that requires persistent storage. In order to overcome this limitation, the current work introduces an extended version to the single node Delay-Coupled Reservoir, that is based on trained linear feedback. We show by numerical simulations that adding task-specific linear feedback to the single node Delay-Coupled Reservoir extends the class of solvable tasks to those that require nonfading memory. We demonstrate, through several case studies, the ability of the extended system to carry out complex nonlinear computations that depend on past information, whereas the computational power of the system with fading memory alone quickly deteriorates. Our findings provide the theoretical basis for future physical realizations of a biologically-inspired ultrafast computing device with extended functionality.

Persistent Memory in Single Node Delay-Coupled Reservoir Computing

PubMed Central

Pipa, Gordon; Toutounji, Hazem

2016-01-01

Delays are ubiquitous in biological systems, ranging from genetic regulatory networks and synaptic conductances, to predator/pray population interactions. The evidence is mounting, not only to the presence of delays as physical constraints in signal propagation speed, but also to their functional role in providing dynamical diversity to the systems that comprise them. The latter observation in biological systems inspired the recent development of a computational architecture that harnesses this dynamical diversity, by delay-coupling a single nonlinear element to itself. This architecture is a particular realization of Reservoir Computing, where stimuli are injected into the system in time rather than in space as is the case with classical recurrent neural network realizations. This architecture also exhibits an internal memory which fades in time, an important prerequisite to the functioning of any reservoir computing device. However, fading memory is also a limitation to any computation that requires persistent storage. In order to overcome this limitation, the current work introduces an extended version to the single node Delay-Coupled Reservoir, that is based on trained linear feedback. We show by numerical simulations that adding task-specific linear feedback to the single node Delay-Coupled Reservoir extends the class of solvable tasks to those that require nonfading memory. We demonstrate, through several case studies, the ability of the extended system to carry out complex nonlinear computations that depend on past information, whereas the computational power of the system with fading memory alone quickly deteriorates. Our findings provide the theoretical basis for future physical realizations of a biologically-inspired ultrafast computing device with extended functionality. PMID:27783690

The Adaptive Calibration Model of stress responsivity

PubMed Central

Ellis, Bruce J.; Shirtcliff, Elizabeth A.

2010-01-01

This paper presents the Adaptive Calibration Model (ACM), an evolutionary-developmental theory of individual differences in the functioning of the stress response system. The stress response system has three main biological functions: (1) to coordinate the organism’s allostatic response to physical and psychosocial challenges; (2) to encode and filter information about the organism’s social and physical environment, mediating the organism’s openness to environmental inputs; and (3) to regulate the organism’s physiology and behavior in a broad range of fitness-relevant areas including defensive behaviors, competitive risk-taking, learning, attachment, affiliation and reproductive functioning. The information encoded by the system during development feeds back on the long-term calibration of the system itself, resulting in adaptive patterns of responsivity and individual differences in behavior. Drawing on evolutionary life history theory, we build a model of the development of stress responsivity across life stages, describe four prototypical responsivity patterns, and discuss the emergence and meaning of sex differences. The ACM extends the theory of biological sensitivity to context (BSC) and provides an integrative framework for future research in the field. PMID:21145350

Deep hierarchies in the primate visual cortex: what can we learn for computer vision?

PubMed

Krüger, Norbert; Janssen, Peter; Kalkan, Sinan; Lappe, Markus; Leonardis, Ales; Piater, Justus; Rodríguez-Sánchez, Antonio J; Wiskott, Laurenz

2013-08-01

Computational modeling of the primate visual system yields insights of potential relevance to some of the challenges that computer vision is facing, such as object recognition and categorization, motion detection and activity recognition, or vision-based navigation and manipulation. This paper reviews some functional principles and structures that are generally thought to underlie the primate visual cortex, and attempts to extract biological principles that could further advance computer vision research. Organized for a computer vision audience, we present functional principles of the processing hierarchies present in the primate visual system considering recent discoveries in neurophysiology. The hierarchical processing in the primate visual system is characterized by a sequence of different levels of processing (on the order of 10) that constitute a deep hierarchy in contrast to the flat vision architectures predominantly used in today's mainstream computer vision. We hope that the functional description of the deep hierarchies realized in the primate visual system provides valuable insights for the design of computer vision algorithms, fostering increasingly productive interaction between biological and computer vision research.

Evolving Relevance of Neuroproteomics in Alzheimer's Disease.

PubMed

Lista, Simone; Zetterberg, Henrik; O'Bryant, Sid E; Blennow, Kaj; Hampel, Harald

2017-01-01

Substantial progress in the understanding of the biology of Alzheimer's disease (AD) has been achieved over the past decades. The early detection and diagnosis of AD and other age-related neurodegenerative diseases, however, remain a challenging scientific frontier. Therefore, the comprehensive discovery (relating to all individual, converging or diverging biochemical disease mechanisms), development, validation, and qualification of standardized biological markers with diagnostic and prognostic functions with a precise performance profile regarding specificity, sensitivity, and positive and negative predictive value are warranted.Methodological innovations in the area of exploratory high-throughput technologies, such as sequencing, microarrays, and mass spectrometry-based analyses of proteins/peptides, have led to the generation of large global molecular datasets from a multiplicity of biological systems, such as biological fluids, cells, tissues, and organs. Such methodological progress has shifted the attention to the execution of hypothesis-independent comprehensive exploratory analyses (opposed to the classical hypothesis-driven candidate approach), with the aim of fully understanding the biological systems in physiology and disease as a whole. The systems biology paradigm integrates experimental biology with accurate and rigorous computational modelling to describe and foresee the dynamic features of biological systems. The use of dynamically evolving technological platforms, including mass spectrometry, in the area of proteomics has enabled to rush the process of biomarker discovery and validation for refining significantly the diagnosis of AD. Currently, proteomics-which is part of the systems biology paradigm-is designated as one of the dominant matured sciences needed for the effective exploratory discovery of prospective biomarker candidates expected to play an effective role in aiding the early detection, diagnosis, prognosis, and therapy development in AD.

Network news: prime time for systems biology of the plant circadian clock.

PubMed

McClung, C Robertson; Gutiérrez, Rodrigo A

2010-12-01

Whole-transcriptome analyses have established that the plant circadian clock regulates virtually every plant biological process and most prominently hormonal and stress response pathways. Systems biology efforts have successfully modeled the plant central clock machinery and an iterative process of model refinement and experimental validation has contributed significantly to the current view of the central clock machinery. The challenge now is to connect this central clock to the output pathways for understanding how the plant circadian clock contributes to plant growth and fitness in a changing environment. Undoubtedly, systems approaches will be needed to integrate and model the vastly increased volume of experimental data in order to extract meaningful biological information. Thus, we have entered an era of systems modeling, experimental testing, and refinement. This approach, coupled with advances from the genetic and biochemical analyses of clock function, is accelerating our progress towards a comprehensive understanding of the plant circadian clock network. Copyright © 2010 Elsevier Ltd. All rights reserved.

2K09 and thereafter : the coming era of integrative bioinformatics, systems biology and intelligent computing for functional genomics and personalized medicine research.

PubMed

Yang, Jack Y; Niemierko, Andrzej; Bajcsy, Ruzena; Xu, Dong; Athey, Brian D; Zhang, Aidong; Ersoy, Okan K; Li, Guo-Zheng; Borodovsky, Mark; Zhang, Joe C; Arabnia, Hamid R; Deng, Youping; Dunker, A Keith; Liu, Yunlong; Ghafoor, Arif

2010-12-01

Significant interest exists in establishing synergistic research in bioinformatics, systems biology and intelligent computing. Supported by the United States National Science Foundation (NSF), International Society of Intelligent Biological Medicine (http://www.ISIBM.org), International Journal of Computational Biology and Drug Design (IJCBDD) and International Journal of Functional Informatics and Personalized Medicine, the ISIBM International Joint Conferences on Bioinformatics, Systems Biology and Intelligent Computing (ISIBM IJCBS 2009) attracted more than 300 papers and 400 researchers and medical doctors world-wide. It was the only inter/multidisciplinary conference aimed to promote synergistic research and education in bioinformatics, systems biology and intelligent computing. The conference committee was very grateful for the valuable advice and suggestions from honorary chairs, steering committee members and scientific leaders including Dr. Michael S. Waterman (USC, Member of United States National Academy of Sciences), Dr. Chih-Ming Ho (UCLA, Member of United States National Academy of Engineering and Academician of Academia Sinica), Dr. Wing H. Wong (Stanford, Member of United States National Academy of Sciences), Dr. Ruzena Bajcsy (UC Berkeley, Member of United States National Academy of Engineering and Member of United States Institute of Medicine of the National Academies), Dr. Mary Qu Yang (United States National Institutes of Health and Oak Ridge, DOE), Dr. Andrzej Niemierko (Harvard), Dr. A. Keith Dunker (Indiana), Dr. Brian D. Athey (Michigan), Dr. Weida Tong (FDA, United States Department of Health and Human Services), Dr. Cathy H. Wu (Georgetown), Dr. Dong Xu (Missouri), Drs. Arif Ghafoor and Okan K Ersoy (Purdue), Dr. Mark Borodovsky (Georgia Tech, President of ISIBM), Dr. Hamid R. Arabnia (UGA, Vice-President of ISIBM), and other scientific leaders. The committee presented the 2009 ISIBM Outstanding Achievement Awards to Dr. Joydeep Ghosh (UT Austin), Dr. Aidong Zhang (Buffalo) and Dr. Zhi-Hua Zhou (Nanjing) for their significant contributions to the field of intelligent biological medicine.

2K09 and thereafter : the coming era of integrative bioinformatics, systems biology and intelligent computing for functional genomics and personalized medicine research

PubMed Central

2010-01-01

Significant interest exists in establishing synergistic research in bioinformatics, systems biology and intelligent computing. Supported by the United States National Science Foundation (NSF), International Society of Intelligent Biological Medicine (http://www.ISIBM.org), International Journal of Computational Biology and Drug Design (IJCBDD) and International Journal of Functional Informatics and Personalized Medicine, the ISIBM International Joint Conferences on Bioinformatics, Systems Biology and Intelligent Computing (ISIBM IJCBS 2009) attracted more than 300 papers and 400 researchers and medical doctors world-wide. It was the only inter/multidisciplinary conference aimed to promote synergistic research and education in bioinformatics, systems biology and intelligent computing. The conference committee was very grateful for the valuable advice and suggestions from honorary chairs, steering committee members and scientific leaders including Dr. Michael S. Waterman (USC, Member of United States National Academy of Sciences), Dr. Chih-Ming Ho (UCLA, Member of United States National Academy of Engineering and Academician of Academia Sinica), Dr. Wing H. Wong (Stanford, Member of United States National Academy of Sciences), Dr. Ruzena Bajcsy (UC Berkeley, Member of United States National Academy of Engineering and Member of United States Institute of Medicine of the National Academies), Dr. Mary Qu Yang (United States National Institutes of Health and Oak Ridge, DOE), Dr. Andrzej Niemierko (Harvard), Dr. A. Keith Dunker (Indiana), Dr. Brian D. Athey (Michigan), Dr. Weida Tong (FDA, United States Department of Health and Human Services), Dr. Cathy H. Wu (Georgetown), Dr. Dong Xu (Missouri), Drs. Arif Ghafoor and Okan K Ersoy (Purdue), Dr. Mark Borodovsky (Georgia Tech, President of ISIBM), Dr. Hamid R. Arabnia (UGA, Vice-President of ISIBM), and other scientific leaders. The committee presented the 2009 ISIBM Outstanding Achievement Awards to Dr. Joydeep Ghosh (UT Austin), Dr. Aidong Zhang (Buffalo) and Dr. Zhi-Hua Zhou (Nanjing) for their significant contributions to the field of intelligent biological medicine. PMID:21143775

Genomics and functional genomics in Chlamydomonas reinhardtii

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

Blaby, Ian K.; Blaby-Haas, Crysten E.

The availability of the Chlamydomonas reinhardtii nuclear genome sequence continues to enable researchers to address biological questions relevant to algae, land plants and animals in unprecedented ways. As we continue to characterize and understand biological processes in C. reinhardtii and translate that knowledge to other systems, we are faced with the realization that many genes encode proteins without a defined function. The field of functional genomics aims to close this gap between genome sequence and protein function. Transcriptomes, proteomes and phenomes can each provide layers of gene-specific functional data while supplying a global snapshot of cellular behavior under different conditions.more » Herein we present a brief history of functional genomics, the present status of the C. reinhardtii genome, how genome-wide experiments can aid in supplying protein function inferences, and provide an outlook for functional genomics in C. reinhardtii.« less

Genomics and functional genomics in Chlamydomonas reinhardtii

DOE PAGES

Blaby, Ian K.; Blaby-Haas, Crysten E.

2017-03-21

The availability of the Chlamydomonas reinhardtii nuclear genome sequence continues to enable researchers to address biological questions relevant to algae, land plants and animals in unprecedented ways. As we continue to characterize and understand biological processes in C. reinhardtii and translate that knowledge to other systems, we are faced with the realization that many genes encode proteins without a defined function. The field of functional genomics aims to close this gap between genome sequence and protein function. Transcriptomes, proteomes and phenomes can each provide layers of gene-specific functional data while supplying a global snapshot of cellular behavior under different conditions.more » Herein we present a brief history of functional genomics, the present status of the C. reinhardtii genome, how genome-wide experiments can aid in supplying protein function inferences, and provide an outlook for functional genomics in C. reinhardtii.« less

Computational dynamic approaches for temporal omics data with applications to systems medicine.

PubMed

Liang, Yulan; Kelemen, Arpad

2017-01-01

Modeling and predicting biological dynamic systems and simultaneously estimating the kinetic structural and functional parameters are extremely important in systems and computational biology. This is key for understanding the complexity of the human health, drug response, disease susceptibility and pathogenesis for systems medicine. Temporal omics data used to measure the dynamic biological systems are essentials to discover complex biological interactions and clinical mechanism and causations. However, the delineation of the possible associations and causalities of genes, proteins, metabolites, cells and other biological entities from high throughput time course omics data is challenging for which conventional experimental techniques are not suited in the big omics era. In this paper, we present various recently developed dynamic trajectory and causal network approaches for temporal omics data, which are extremely useful for those researchers who want to start working in this challenging research area. Moreover, applications to various biological systems, health conditions and disease status, and examples that summarize the state-of-the art performances depending on different specific mining tasks are presented. We critically discuss the merits, drawbacks and limitations of the approaches, and the associated main challenges for the years ahead. The most recent computing tools and software to analyze specific problem type, associated platform resources, and other potentials for the dynamic trajectory and interaction methods are also presented and discussed in detail.

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.

Review of the fundamental theories behind small angle X-ray scattering, molecular dynamics simulations, and relevant integrated application

PubMed Central

Boldon, Lauren; Laliberte, Fallon; Liu, Li

2015-01-01

In this paper, the fundamental concepts and equations necessary for performing small angle X-ray scattering (SAXS) experiments, molecular dynamics (MD) simulations, and MD-SAXS analyses were reviewed. Furthermore, several key biological and non-biological applications for SAXS, MD, and MD-SAXS are presented in this review; however, this article does not cover all possible applications. SAXS is an experimental technique used for the analysis of a wide variety of biological and non-biological structures. SAXS utilizes spherical averaging to produce one- or two-dimensional intensity profiles, from which structural data may be extracted. MD simulation is a computer simulation technique that is used to model complex biological and non-biological systems at the atomic level. MD simulations apply classical Newtonian mechanics’ equations of motion to perform force calculations and to predict the theoretical physical properties of the system. This review presents several applications that highlight the ability of both SAXS and MD to study protein folding and function in addition to non-biological applications, such as the study of mechanical, electrical, and structural properties of non-biological nanoparticles. Lastly, the potential benefits of combining SAXS and MD simulations for the study of both biological and non-biological systems are demonstrated through the presentation of several examples that combine the two techniques. PMID:25721341

Universal scaling function in discrete time asymmetric exclusion processes

NASA Astrophysics Data System (ADS)

Chia, Nicholas; Bundschuh, Ralf

2005-03-01

In the universality class of the one dimensional Kardar-Parisi-Zhang surface growth, Derrida and Lebowitz conjectured the universality of not only the scaling exponents, but of an entire scaling function. Since Derrida and Lebowitz' original publication this universality has been verified for a variety of continuous time systems in the KPZ universality class. We study the Derrida-Lebowitz scaling function for multi-particle versions of the discrete time Asymmetric Exclusion Process. We find that in this discrete time system the Derrida-Lebowitz scaling function not only properly characterizes the large system size limit, but even accurately describes surprisingly small systems. These results have immediate applications in searching biological sequence databases.

Roles for text mining in protein function prediction.

PubMed

Verspoor, Karin M

2014-01-01

The Human Genome Project has provided science with a hugely valuable resource: the blueprints for life; the specification of all of the genes that make up a human. While the genes have all been identified and deciphered, it is proteins that are the workhorses of the human body: they are essential to virtually all cell functions and are the primary mechanism through which biological function is carried out. Hence in order to fully understand what happens at a molecular level in biological organisms, and eventually to enable development of treatments for diseases where some aspect of a biological system goes awry, we must understand the functions of proteins. However, experimental characterization of protein function cannot scale to the vast amount of DNA sequence data now available. Computational protein function prediction has therefore emerged as a problem at the forefront of modern biology (Radivojac et al., Nat Methods 10(13):221-227, 2013).Within the varied approaches to computational protein function prediction that have been explored, there are several that make use of biomedical literature mining. These methods take advantage of information in the published literature to associate specific proteins with specific protein functions. In this chapter, we introduce two main strategies for doing this: association of function terms, represented as Gene Ontology terms (Ashburner et al., Nat Genet 25(1):25-29, 2000), to proteins based on information in published articles, and a paradigm called LEAP-FS (Literature-Enhanced Automated Prediction of Functional Sites) in which literature mining is used to validate the predictions of an orthogonal computational protein function prediction method.

A preliminary approach to creating an overview of lactoferrin multi-functionality utilizing a text mining method.

PubMed

Shimazaki, Kei-ichi; Kushida, Tatsuya

2010-06-01

Lactoferrin is a multi-functional metal-binding glycoprotein that exhibits many biological functions of interest to many researchers from the fields of clinical medicine, dentistry, pharmacology, veterinary medicine, nutrition and milk science. To date, a number of academic reports concerning the biological activities of lactoferrin have been published and are easily accessible through public data repositories. However, as the literature is expanding daily, this presents challenges in understanding the larger picture of lactoferrin function and mechanisms. In order to overcome the "analysis paralysis" associated with lactoferrin information, we attempted to apply a text mining method to the accumulated lactoferrin literature. To this end, we used the information extraction system GENPAC (provided by Nalapro Technologies Inc., Tokyo). This information extraction system uses natural language processing and text mining technology. This system analyzes the sentences and titles from abstracts stored in the PubMed database, and can automatically extract binary relations that consist of interactions between genes/proteins, chemicals and diseases/functions. We expect that such information visualization analysis will be useful in determining novel relationships among a multitude of lactoferrin functions and mechanisms. We have demonstrated the utilization of this method to find pathways of lactoferrin participation in neovascularization, Helicobacter pylori attack on gastric mucosa, atopic dermatitis and lipid metabolism.

Health, Health Care, and Systems Science: Emerging Paradigm.

PubMed

Janecka, Ivo

2017-02-15

Health is a continuum of an optimized state of a biologic system, an outcome of positive relationships with the self and others. A healthy system follows the principles of systems science derived from observations of nature, highlighting the character of relationships as the key determinant. Relationships evolve from our decisions, which are consequential to the function of our own biologic system on all levels, including the genome, where epigenetics impact our morphology. In healthy systems, decisions emanate from the reciprocal collaboration of hippocampal memory and the executive prefrontal cortex. We can decide to change relationships through choices. What is selected, however, only represents the cognitive interpretation of our limited sensory perception; it strongly reflects inherent biases toward either optimizing state, making a biologic system healthy, or not. Health or its absence is then the outcome; there is no inconsequential choice. Public health effort should not focus on punitive steps (e.g. taxation of unhealthy products or behaviors) in order to achieve a higher level of public's health. It should teach people the process of making healthy decisions; otherwise, people will just migrate/shift from one unhealthy product/behavior to another, and well-intended punitive steps will not make much difference. Physical activity, accompanied by nutrition and stress management, have the greatest impact on fashioning health and simultaneously are the most cost-effective measures. Moderate-to-vigorous exercise not only improves aerobic fitness but also positively influences cognition, including memory and senses. Collective, rational societal decisions can then be anticipated. Health care is a business system principally governed by self-maximizing decisions of its components; uneven and contradictory outcomes are the consequences within such a non-optimized system. Health is not health care. We are biologic systems subject to the laws of biology in spite of our incongruous decisions that are detrimental to health. A biologic system/a human body originates from structural, deterministic genes as well as shared epigenetic memory of our ancestors affecting our bodily function and structure. The political governing systems' vertical hierarchy has control over money and laws, neither of which materially affect individual lifestyle/behavioral choices toward health. Improved health comes from focusing on enhancing the biologic age and not the chronologic one, which simply represents a linear time from a birth certificate to a death certificate and is applicable only in its extremes. "Age-related diseases" are simply reflections of a given culture. Biologic age, reflecting the actual state of health, could be used in all health-related assessments including health-life insurance premiums, licensing of job categories, etc., all with a broader and healthy societal impact.

The implications of non-linear biological oscillations on human electrophysiology for electrohypersensitivity (EHS) and multiple chemical sensitivity (MCS).

PubMed

Sage, Cindy

2015-01-01

The 'informational content' of Earth's electromagnetic signaling is like a set of operating instructions for human life. These environmental cues are dynamic and involve exquisitely low inputs (intensities) of critical frequencies with which all life on Earth evolved. Circadian and other temporal biological rhythms depend on these fluctuating electromagnetic inputs to direct gene expression, cell communication and metabolism, neural development, brainwave activity, neural synchrony, a diversity of immune functions, sleep and wake cycles, behavior and cognition. Oscillation is also a universal phenomenon, and biological systems of the heart, brain and gut are dependent on the cooperative actions of cells that function according to principles of non-linear, coupled biological oscillations for their synchrony. They are dependent on exquisitely timed cues from the environment at vanishingly small levels. Altered 'informational content' of environmental cues can swamp natural electromagnetic cues and result in dysregulation of normal biological rhythms that direct growth, development, metabolism and repair mechanisms. Pulsed electromagnetic fields (PEMF) and radiofrequency radiation (RFR) can have the devastating biological effects of disrupting homeostasis and desynchronizing normal biological rhythms that maintain health. Non-linear, weak field biological oscillations govern body electrophysiology, organize cell and tissue functions and maintain organ systems. Artificial bioelectrical interference can give false information (disruptive signaling) sufficient to affect critical pacemaker cells (of the heart, gut and brain) and desynchronize functions of these important cells that orchestrate function and maintain health. Chronic physiological stress undermines homeostasis whether it is chemically induced or electromagnetically induced (or both exposures are simultaneous contributors). This can eventually break down adaptive biological responses critical to health maintenance; and resilience can be compromised. Electrohypersensitivity can be caused by successive assaults on human bioelectrochemical dynamics from exogenous electromagnetic fields (EMF) and RFR or a single acute exposure. Once sensitized, further exposures are widely reported to cause reactivity to lower and lower intensities of EMF/RFR, at which point thousand-fold lower levels can cause adverse health impacts to the electrosensitive person. Electrohypersensitivity (EHS) can be a precursor to, or linked with, multiple chemical sensitivity (MCS) based on reports of individuals who first develop one condition, then rapidly develop the other. Similarity of chemical biomarkers is seen in both conditions [histamines, markers of oxidative stress, auto-antibodies, heat shock protein (HSP), melatonin markers and leakage of the blood-brain barrier]. Low intensity pulsed microwave activation of voltage-gated calcium channels (VGCCs) is postulated as a mechanism of action for non-thermal health effects.

Carcinogenesis: alterations in reciprocal interactions of normal functional structure of biologic systems.

PubMed

Davydyan, Garri

2015-12-01

The evolution of biologic systems (BS) includes functional mechanisms that in some conditions may lead to the development of cancer. Using mathematical group theory and matrix analysis, previously, it was shown that normally functioning BS are steady functional structures regulated by three basis regulatory components: reciprocal links (RL), negative feedback (NFB) and positive feedback (PFB). Together, they form an integrative unit maintaining system's autonomy and functional stability. It is proposed that phylogenetic development of different species is implemented by the splitting of "rudimentary" characters into two relatively independent functional parts that become encoded in chromosomes. The functional correlate of splitting mechanisms is RL. Inversion of phylogenetic mechanisms during ontogenetic development leads cell differentiation until cells reach mature states. Deterioration of reciprocal structure in the genome during ontogenesis gives rise of pathological conditions characterized by unsteadiness of the system. Uncontrollable cell proliferation and invasive cell growth are the leading features of the functional outcomes of malfunctioning systems. The regulatory element responsible for these changes is RL. In matrix language, pathological regulation is represented by matrices having positive values of diagonal elements ( TrA  > 0) and also positive values of matrix determinant ( detA  > 0). Regulatory structures of that kind can be obtained if the negative entry of the matrix corresponding to RL is replaced with the positive one. To describe not only normal but also pathological states of BS, a unit matrix should be added to the basis matrices representing RL, NFB and PFB. A mathematical structure corresponding to the set of these four basis functional patterns (matrices) is a split quaternion (coquaternion). The structure and specific role of basis elements comprising four-dimensional linear space of split quaternions help to understand what changes in mechanism of cell differentiation may lead to cancer development.

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.

Cell-free biology: exploiting the interface between synthetic biology and synthetic chemistry

PubMed Central

Harris, D. Calvin; Jewett, Michael C.

2014-01-01

Just as synthetic organic chemistry once revolutionized the ability of chemists to build molecules (including those that did not exist in nature) following a basic set of design rules, cell-free synthetic biology is beginning to provide an improved toolbox and faster process for not only harnessing but also expanding the chemistry of life. At the interface between chemistry and biology, research in cell-free synthetic systems is proceeding in two different directions: using synthetic biology for synthetic chemistry and using synthetic chemistry to reprogram or mimic biology. In the coming years, the impact of advances inspired by these approaches will make possible the synthesis of non-biological polymers having new backbone compositions, new chemical properties, new structures, and new functions. PMID:22483202

Microfluidic technologies for synthetic biology.

PubMed

Vinuselvi, Parisutham; Park, Seongyong; Kim, Minseok; Park, Jung Min; Kim, Taesung; Lee, Sung Kuk

2011-01-01

Microfluidic technologies have shown powerful abilities for reducing cost, time, and labor, and at the same time, for increasing accuracy, throughput, and performance in the analysis of biological and biochemical samples compared with the conventional, macroscale instruments. Synthetic biology is an emerging field of biology and has drawn much attraction due to its potential to create novel, functional biological parts and systems for special purposes. Since it is believed that the development of synthetic biology can be accelerated through the use of microfluidic technology, in this review work we focus our discussion on the latest microfluidic technologies that can provide unprecedented means in synthetic biology for dynamic profiling of gene expression/regulation with high resolution, highly sensitive on-chip and off-chip detection of metabolites, and whole-cell analysis.

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.

Simulation-based model checking approach to cell fate specification during Caenorhabditis elegans vulval development by hybrid functional Petri net with extension.

PubMed

Li, Chen; Nagasaki, Masao; Ueno, Kazuko; Miyano, Satoru

2009-04-27

Model checking approaches were applied to biological pathway validations around 2003. Recently, Fisher et al. have proved the importance of model checking approach by inferring new regulation of signaling crosstalk in C. elegans and confirming the regulation with biological experiments. They took a discrete and state-based approach to explore all possible states of the system underlying vulval precursor cell (VPC) fate specification for desired properties. However, since both discrete and continuous features appear to be an indispensable part of biological processes, it is more appropriate to use quantitative models to capture the dynamics of biological systems. Our key motivation of this paper is to establish a quantitative methodology to model and analyze in silico models incorporating the use of model checking approach. A novel method of modeling and simulating biological systems with the use of model checking approach is proposed based on hybrid functional Petri net with extension (HFPNe) as the framework dealing with both discrete and continuous events. Firstly, we construct a quantitative VPC fate model with 1761 components by using HFPNe. Secondly, we employ two major biological fate determination rules - Rule I and Rule II - to VPC fate model. We then conduct 10,000 simulations for each of 48 sets of different genotypes, investigate variations of cell fate patterns under each genotype, and validate the two rules by comparing three simulation targets consisting of fate patterns obtained from in silico and in vivo experiments. In particular, an evaluation was successfully done by using our VPC fate model to investigate one target derived from biological experiments involving hybrid lineage observations. However, the understandings of hybrid lineages are hard to make on a discrete model because the hybrid lineage occurs when the system comes close to certain thresholds as discussed by Sternberg and Horvitz in 1986. Our simulation results suggest that: Rule I that cannot be applied with qualitative based model checking, is more reasonable than Rule II owing to the high coverage of predicted fate patterns (except for the genotype of lin-15ko; lin-12ko double mutants). More insights are also suggested. The quantitative simulation-based model checking approach is a useful means to provide us valuable biological insights and better understandings of biological systems and observation data that may be hard to capture with the qualitative one.

MSD-MAP: A Network-Based Systems Biology Platform for Predicting Disease-Metabolite Links.

PubMed

Wathieu, Henri; Issa, Naiem T; Mohandoss, Manisha; Byers, Stephen W; Dakshanamurthy, Sivanesan

2017-01-01

Cancer-associated metabolites result from cell-wide mechanisms of dysregulation. The field of metabolomics has sought to identify these aberrant metabolites as disease biomarkers, clues to understanding disease mechanisms, or even as therapeutic agents. This study was undertaken to reliably predict metabolites associated with colorectal, esophageal, and prostate cancers. Metabolite and disease biological action networks were compared in a computational platform called MSD-MAP (Multi Scale Disease-Metabolite Association Platform). Using differential gene expression analysis with patient-based RNAseq data from The Cancer Genome Atlas, genes up- or down-regulated in cancer compared to normal tissue were identified. Relational databases were used to map biological entities including pathways, functions, and interacting proteins, to those differential disease genes. Similar relational maps were built for metabolites, stemming from known and in silico predicted metabolite-protein associations. The hypergeometric test was used to find statistically significant relationships between disease and metabolite biological signatures at each tier, and metabolites were assessed for multi-scale association with each cancer. Metabolite networks were also directly associated with various other diseases using a disease functional perturbation database. Our platform recapitulated metabolite-disease links that have been empirically verified in the scientific literature, with network-based mapping of jointly-associated biological activity also matching known disease mechanisms. This was true for colorectal, esophageal, and prostate cancers, using metabolite action networks stemming from both predicted and known functional protein associations. By employing systems biology concepts, MSD-MAP reliably predicted known cancermetabolite links, and may serve as a predictive tool to streamline conventional metabolomic profiling methodologies. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Synthetic Biology Open Language (SBOL) Version 2.0.0.

PubMed

Bartley, Bryan; Beal, Jacob; Clancy, Kevin; Misirli, Goksel; Roehner, Nicholas; Oberortner, Ernst; Pocock, Matthew; Bissell, Michael; Madsen, Curtis; Nguyen, Tramy; Zhang, Zhen; Gennari, John H; Myers, Chris; Wipat, Anil; Sauro, Herbert

2015-09-04

Synthetic biology builds upon the techniques and successes of genetics, molecular biology, and metabolic engineering by applying engineering principles to the design of biological systems. The field still faces substantial challenges, including long development times, high rates of failure, and poor reproducibility. One method to ameliorate these problems would be to improve the exchange of information about designed systems between laboratories. The Synthetic Biology Open Language (SBOL) has been developed as a standard to support the specification and exchange of biological design information in synthetic biology, filling a need not satisfied by other pre-existing standards. This document details version 2.0 of SBOL, introducing a standardized format for the electronic exchange of information on the structural and functional aspects of biological designs. The standard has been designed to support the explicit and unambiguous description of biological designs by means of a well defined data model. The standard also includes rules and best practices on how to use this data model and populate it with relevant design details. The publication of this specification is intended to make these capabilities more widely accessible to potential developers and users in the synthetic biology community and beyond.

Activity-based protein profiling: from enzyme chemistry to proteomic chemistry.

PubMed

Cravatt, Benjamin F; Wright, Aaron T; Kozarich, John W

2008-01-01

Genome sequencing projects have provided researchers with a complete inventory of the predicted proteins produced by eukaryotic and prokaryotic organisms. Assignment of functions to these proteins represents one of the principal challenges for the field of proteomics. Activity-based protein profiling (ABPP) has emerged as a powerful chemical proteomic strategy to characterize enzyme function directly in native biological systems on a global scale. Here, we review the basic technology of ABPP, the enzyme classes addressable by this method, and the biological discoveries attributable to its application.

Synthesis and Characterization of Rhodamine B-ethylenediamine-hyaluronan Acid as Potential Biological Functional Materials

NASA Astrophysics Data System (ADS)

Li, Y. L.; Wang, W. X.; Wang, Y.; Zhang, W. B.; Gong, H. M.; Liu, M. X.

2018-05-01

The purpose of this study is to synthesize and characterize fluorescent polymers, rhodamine B-ethylenediamine-hyaluronan acid (RhB-EA-HA). RhB-EA-HA was successfully synthesized by ester ammonolysis reaction and amidation reaction. Moreover, the structural properties of RhB-EA-HA were characterized by 1H-NMR spectra, UV-vis spectrometry and Fourier transform infrared spectroscopy (FT-IR). RhB-EA-HA can be grafted on the surface of silica nanomaterials, which may be potential biological functional materials for drug delivery system.

Syntheses and Biological Studies of Marine Terpenoids Derived from Inorganic Cyanide

PubMed Central

Schnermann, Martin J.; Shenvi, Ryan A.

2015-01-01

Isocyanoterpenes (ICTs) are marine natural products biosynthesized through an unusual pathway that adorns terpene scaffolds with nitrogenous functionality derived from cyanide. The appendage of nitrogen functional groups–isonitriles in particular–onto stereochemically-rich carbocyclic ring systems provides enigmatic, bioactive molecules that have required innovative chemical syntheses. This review discusses the challenges inherent to the synthesis of this diverse family and details the development of the field. We also present recent progress in isolation and discuss key aspects of the remarkable biological activity of these compounds. PMID:25514696

Biotechnological synthesis of functional nanomaterials.

PubMed

Lloyd, Jonathan R; Byrne, James M; Coker, Victoria S

2011-08-01

Biological systems, especially those using microorganisms, have the potential to offer cheap, scalable and highly tunable green synthetic routes for the production of the latest generation of nanomaterials. Recent advances in the biotechnological synthesis of functional nano-scale materials are described. These nanomaterials range from catalysts to novel inorganic antimicrobials, nanomagnets, remediation agents and quantum dots for electronic and optical devices. Where possible, the roles of key biological macromolecules in controlling production of the nanomaterials are highlighted, and also technological limitations that must be addressed for widespread implementation are discussed. Copyright © 2011 Elsevier Ltd. All rights reserved.

Data processing, multi-omic pathway mapping, and metabolite activity analysis using XCMS Online

PubMed Central

Forsberg, Erica M; Huan, Tao; Rinehart, Duane; Benton, H Paul; Warth, Benedikt; Hilmers, Brian; Siuzdak, Gary

2018-01-01

Systems biology is the study of complex living organisms, and as such, analysis on a systems-wide scale involves the collection of information-dense data sets that are representative of an entire phenotype. To uncover dynamic biological mechanisms, bioinformatics tools have become essential to facilitating data interpretation in large-scale analyses. Global metabolomics is one such method for performing systems biology, as metabolites represent the downstream functional products of ongoing biological processes. We have developed XCMS Online, a platform that enables online metabolomics data processing and interpretation. A systems biology workflow recently implemented within XCMS Online enables rapid metabolic pathway mapping using raw metabolomics data for investigating dysregulated metabolic processes. In addition, this platform supports integration of multi-omic (such as genomic and proteomic) data to garner further systems-wide mechanistic insight. Here, we provide an in-depth procedure showing how to effectively navigate and use the systems biology workflow within XCMS Online without a priori knowledge of the platform, including uploading liquid chromatography (LCLC)–mass spectrometry (MS) data from metabolite-extracted biological samples, defining the job parameters to identify features, correcting for retention time deviations, conducting statistical analysis of features between sample classes and performing predictive metabolic pathway analysis. Additional multi-omics data can be uploaded and overlaid with previously identified pathways to enhance systems-wide analysis of the observed dysregulations. We also describe unique visualization tools to assist in elucidation of statistically significant dysregulated metabolic pathways. Parameter input takes 5–10 min, depending on user experience; data processing typically takes 1–3 h, and data analysis takes ~30 min. PMID:29494574

Bioengineering of plant (tri)terpenoids: from metabolic engineering of plants to synthetic biology in vivo and in vitro.

PubMed

Moses, Tessa; Pollier, Jacob; Thevelein, Johan M; Goossens, Alain

2013-10-01

Terpenoids constitute a large and diverse class of natural products that serve many functions in nature. Most of the tens of thousands of the discovered terpenoids are synthesized by plants, where they function as primary metabolites involved in growth and development, or as secondary metabolites that optimize the interaction between the plant and its environment. Several plant terpenoids are economically important molecules that serve many applications as pharmaceuticals, pesticides, etc. Major challenges for the commercialization of plant-derived terpenoids include their low production levels in planta and the continuous demand of industry for novel molecules with new or superior biological activities. Here, we highlight several synthetic biology methods to enhance and diversify the production of plant terpenoids, with a foresight towards triterpenoid engineering, the least engineered class of bioactive terpenoids. Increased or cheaper production of valuable triterpenoids may be obtained by 'classic' metabolic engineering of plants or by heterologous production of the compounds in other plants or microbes. Novel triterpenoid structures can be generated through combinatorial biosynthesis or directed enzyme evolution approaches. In its ultimate form, synthetic biology may lead to the production of large amounts of plant triterpenoids in in vitro systems or custom-designed artificial biological systems. © 2013 The Authors. New Phytologist © 2013 New Phytologist Trust.

Cell-free synthetic biology for environmental sensing and remediation.

PubMed

Karig, David K

2017-06-01

The fields of biosensing and bioremediation leverage the phenomenal array of sensing and metabolic capabilities offered by natural microbes. Synthetic biology provides tools for transforming these fields through complex integration of natural and novel biological components to achieve sophisticated sensing, regulation, and metabolic function. However, the majority of synthetic biology efforts are conducted in living cells, and concerns over releasing genetically modified organisms constitute a key barrier to environmental applications. Cell-free protein expression systems offer a path towards leveraging synthetic biology, while preventing the spread of engineered organisms in nature. Recent efforts in the areas of cell-free approaches for sensing, regulation, and metabolic pathway implementation, as well as for preserving and deploying cell-free expression components, embody key steps towards realizing the potential of cell-free systems for environmental sensing and remediation. Copyright © 2017 The Author. Published by Elsevier Ltd.. All rights reserved.

Modulation of Immune Function by Polyphenols: Possible Contribution of Epigenetic Factors

PubMed Central

Cuevas, Alejandro; Saavedra, Nicolás; Salazar, Luis A.; Abdalla, Dulcineia S. P.

2013-01-01

Several biological activities have been described for polyphenolic compounds, including a modulator effect on the immune system. The effects of these biologically active compounds on the immune system are associated to processes as differentiation and activation of immune cells. Among the mechanisms associated to immune regulation are epigenetic modifications as DNA methylation of regulatory sequences, histone modifications and posttranscriptional repression by microRNAs that influences the gene expression of key players involved in the immune response. Considering that polyphenols are able to regulate the immune function and has been also demonstrated an effect on epigenetic mechanisms, it is possible to hypothesize that there exists a mediator role of epigenetic mechanisms in the modulation of the immune response by polyphenols. PMID:23812304

Computational Study on Atomic Structures, Electronic Properties, and Chemical Reactions at Surfaces and Interfaces and in Biomaterials

NASA Astrophysics Data System (ADS)

Takano, Yu; Kobayashi, Nobuhiko; Morikawa, Yoshitada

2018-06-01

Through computer simulations using atomistic models, it is becoming possible to calculate the atomic structures of localized defects or dopants in semiconductors, chemically active sites in heterogeneous catalysts, nanoscale structures, and active sites in biological systems precisely. Furthermore, it is also possible to clarify physical and chemical properties possessed by these nanoscale structures such as electronic states, electronic and atomic transport properties, optical properties, and chemical reactivity. It is sometimes quite difficult to clarify these nanoscale structure-function relations experimentally and, therefore, accurate computational studies are indispensable in materials science. In this paper, we review recent studies on the relation between local structures and functions for inorganic, organic, and biological systems by using atomistic computer simulations.

Neuronal Organization of Deep Brain Opsin Photoreceptors in Adult Teleosts

PubMed Central

Hang, Chong Yee; Kitahashi, Takashi; Parhar, Ishwar S.

2016-01-01

Biological impacts of light beyond vision, i.e., non-visual functions of light, signify the need to better understand light detection (or photoreception) systems in vertebrates. Photopigments, which comprise light-absorbing chromophores bound to a variety of G-protein coupled receptor opsins, are responsible for visual and non-visual photoreception. Non-visual opsin photopigments in the retina of mammals and extra-retinal tissues of non-mammals play an important role in non-image-forming functions of light, e.g., biological rhythms and seasonal reproduction. This review highlights the role of opsin photoreceptors in the deep brain, which could involve conserved neurochemical systems that control different time- and light-dependent physiologies in in non-mammalian vertebrates including teleost fish. PMID:27199680

Use of ozone in a water reuse system for salmonids

USGS Publications Warehouse

Williams, R.C.; Hughes, S.G.; Rumsey, G.L.

1982-01-01

A water reuse system is described in which ozone is used in addition to biological filters to remove toxic metabolic wastes from the water. The system functions at a higher rate of efficiency than has been reported for other reuse systems and supports excellent growth of rainbow trout (Salmo gairdneri).

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…

Potential for biological nitrification inhibition to reduce nitrification and N2O emissions in pasture crop-livestock systems.

PubMed

Subbarao, G V; Rao, I M; Nakahara, K; Sahrawat, K L; Ando, Y; Kawashima, T

2013-06-01

Agriculture and livestock production systems are two major emitters of greenhouse gases. Methane with a GWP (global warming potential) of 21, and nitrous oxide (N2O) with a GWP of 300, are largely emitted from animal production agriculture, where livestock production is based on pasture and feed grains. The principal biological processes involved in N2O emissions are nitrification and denitrification. Biological nitrification inhibition (BNI) is the natural ability of certain plant species to release nitrification inhibitors from their roots that suppress nitrifier activity, thus reducing soil nitrification and N2O emission. Recent methodological developments (e.g. bioluminescence assay to detect BNIs in plant root systems) have led to significant advances in our ability to quantify and characterize the BNI function. Synthesis and release of BNIs from plants is a highly regulated process triggered by the presence of NH4 + in the rhizosphere, which results in the inhibitor being released precisely where the majority of the soil-nitrifier population resides. Among the tropical pasture grasses, the BNI function is strongest (i.e. BNI capacity) in Brachiaria sp. Some feed-grain crops such as sorghum also have significant BNI capacity present in their root systems. The chemical identity of some of these BNIs has now been established, and their mode of inhibitory action on Nitrosomonas has been characterized. The ability of the BNI function in Brachiaria pastures to suppress N2O emissions and soil nitrification potential has been demonstrated; however, its potential role in controlling N2O emissions in agro-pastoral systems is under investigation. Here we present the current status of our understanding on how the BNI functions in Brachiaria pastures and feed-grain crops such as sorghum can be exploited both genetically and, from a production system's perspective, to develop low-nitrifying and low N2O-emitting production systems that would be economically profitable and ecologically sustainable.

Microchip-Based Single-Cell Functional Proteomics for Biomedical Applications

PubMed Central

Lu, Yao; Yang, Liu; Wei, Wei; Shi, Qihui

2017-01-01

Cellular heterogeneity has been widely recognized but only recently have single cell tools become available that allow characterizing heterogeneity at the genomic and proteomic levels. We review the technological advances in microchip-based toolkits for single-cell functional proteomics. Each of these tools has distinct advantages and limitations, and a few have advanced toward being applied to address biological or clinical problems that fail to be addressed by traditional population-based methods. High-throughput single-cell proteomic assays generate high-dimensional data sets that contain new information and thus require developing new analytical framework to extract new biology. In this review article, we highlight a few biological and clinical applications in which the microchip-based single-cell proteomic tools provide unique advantages. The examples include resolving functional heterogeneity and dynamics of immune cells, dissecting cell-cell interaction by creating well-contolled on-chip microenvironment, capturing high-resolution snapshots of immune system functions in patients for better immunotherapy and elucidating phosphoprotein signaling networks in cancer cells for guiding effective molecularly targeted therapies. PMID:28280819

PROFESS: a PROtein Function, Evolution, Structure and Sequence database

PubMed Central

Triplet, Thomas; Shortridge, Matthew D.; Griep, Mark A.; Stark, Jaime L.; Powers, Robert; Revesz, Peter

2010-01-01

The proliferation of biological databases and the easy access enabled by the Internet is having a beneficial impact on biological sciences and transforming the way research is conducted. There are ∼1100 molecular biology databases dispersed throughout the Internet. To assist in the functional, structural and evolutionary analysis of the abundant number of novel proteins continually identified from whole-genome sequencing, we introduce the PROFESS (PROtein Function, Evolution, Structure and Sequence) database. Our database is designed to be versatile and expandable and will not confine analysis to a pre-existing set of data relationships. A fundamental component of this approach is the development of an intuitive query system that incorporates a variety of similarity functions capable of generating data relationships not conceived during the creation of the database. The utility of PROFESS is demonstrated by the analysis of the structural drift of homologous proteins and the identification of potential pancreatic cancer therapeutic targets based on the observation of protein–protein interaction networks. Database URL: http://cse.unl.edu/∼profess/ PMID:20624718

Eugene--a domain specific language for specifying and constraining synthetic biological parts, devices, and systems.

PubMed

Bilitchenko, Lesia; Liu, Adam; Cheung, Sherine; Weeding, Emma; Xia, Bing; Leguia, Mariana; Anderson, J Christopher; Densmore, Douglas

2011-04-29

Synthetic biological systems are currently created by an ad-hoc, iterative process of specification, design, and assembly. These systems would greatly benefit from a more formalized and rigorous specification of the desired system components as well as constraints on their composition. Therefore, the creation of robust and efficient design flows and tools is imperative. We present a human readable language (Eugene) that allows for the specification of synthetic biological designs based on biological parts, as well as provides a very expressive constraint system to drive the automatic creation of composite Parts (Devices) from a collection of individual Parts. We illustrate Eugene's capabilities in three different areas: Device specification, design space exploration, and assembly and simulation integration. These results highlight Eugene's ability to create combinatorial design spaces and prune these spaces for simulation or physical assembly. Eugene creates functional designs quickly and cost-effectively. Eugene is intended for forward engineering of DNA-based devices, and through its data types and execution semantics, reflects the desired abstraction hierarchy in synthetic biology. Eugene provides a powerful constraint system which can be used to drive the creation of new devices at runtime. It accomplishes all of this while being part of a larger tool chain which includes support for design, simulation, and physical device assembly.

Bacteria, Yeast, Worms, and Flies: Exploiting simple model organisms to investigate human mitochondrial diseases

PubMed Central

Rea, Shane L.; Graham, Brett H.; Nakamaru-Ogiso, Eiko; Kar, Adwitiya; Falk, Marni J.

2013-01-01

The extensive conservation of mitochondrial structure, composition, and function across evolution offers a unique opportunity to expand our understanding of human mitochondrial biology and disease. By investigating the biology of much simpler model organisms, it is often possible to answer questions that are unreachable at the clinical level. Here, we review the relative utility of four different model organisms, namely the bacteria Escherichia coli, the yeast Saccharomyces cerevisiae, the nematode Caenorhabditis elegans and the fruit fly Drosophila melanogaster, in studying the role of mitochondrial proteins relevant to human disease. E. coli are single cell, prokaryotic bacteria that have proven to be a useful model system in which to investigate mitochondrial respiratory chain protein structure and function. S. cerevisiae is a single-celled eukaryote that can grow equally well by mitochondrial-dependent respiration or by ethanol fermentation, a property that has proven to be a veritable boon for investigating mitochondrial functionality. C. elegans is a multi-cellular, microscopic worm that is organized into five major tissues and has proven to be a robust model animal for in vitro and in vivo studies of primary respiratory chain dysfunction and its potential therapies in humans. Studied for over a century, D. melanogaster is a classic metazoan model system offering an abundance of genetic tools and reagents that facilitates investigations of mitochondrial biology using both forward and reverse genetics. The respective strengths and limitations of each species relative to mitochondrial studies are explored. In addition, an overview is provided of major discoveries made in mitochondrial biology in each of these four model systems. PMID:20818735

A Simple and Low-Cost Monitoring System to Investigate Environmental Conditions in a Biological Research Laboratory.

PubMed

Gurdita, Akshay; Vovko, Heather; Ungrin, Mark

2016-01-01

Basic equipment such as incubation and refrigeration systems plays a critical role in nearly all aspects of the traditional biological research laboratory. Their proper functioning is therefore essential to ensure reliable and repeatable experimental results. Despite this fact, in many academic laboratories little attention is paid to validating and monitoring their function, primarily due to the cost and/or technical complexity of available commercial solutions. We have therefore developed a simple and low-cost monitoring system that combines a "Raspberry Pi" single-board computer with USB-connected sensor interfaces to track and log parameters such as temperature and pressure, and send email alert messages as appropriate. The system is controlled by open-source software, and we have also generated scripts to automate software setup so that no background in programming is required to install and use it. We have applied it to investigate the behaviour of our own equipment, and present here the results along with the details of the monitoring system used to obtain them.

Automated cross-modal mapping in robotic eye/hand systems using plastic radial basis function networks

NASA Astrophysics Data System (ADS)

Meng, Qinggang; Lee, M. H.

2007-03-01

Advanced autonomous artificial systems will need incremental learning and adaptive abilities similar to those seen in humans. Knowledge from biology, psychology and neuroscience is now inspiring new approaches for systems that have sensory-motor capabilities and operate in complex environments. Eye/hand coordination is an important cross-modal cognitive function, and is also typical of many of the other coordinations that must be involved in the control and operation of embodied intelligent systems. This paper examines a biologically inspired approach for incrementally constructing compact mapping networks for eye/hand coordination. We present a simplified node-decoupled extended Kalman filter for radial basis function networks, and compare this with other learning algorithms. An experimental system consisting of a robot arm and a pan-and-tilt head with a colour camera is used to produce results and test the algorithms in this paper. We also present three approaches for adapting to structural changes during eye/hand coordination tasks, and the robustness of the algorithms under noise are investigated. The learning and adaptation approaches in this paper have similarities with current ideas about neural growth in the brains of humans and animals during tool-use, and infants during early cognitive development.

The Protein Structure Initiative Structural Biology Knowledgebase Technology Portal: a structural biology web resource.

PubMed

Gifford, Lida K; Carter, Lester G; Gabanyi, Margaret J; Berman, Helen M; Adams, Paul D

2012-06-01

The Technology Portal of the Protein Structure Initiative Structural Biology Knowledgebase (PSI SBKB; http://technology.sbkb.org/portal/ ) is a web resource providing information about methods and tools that can be used to relieve bottlenecks in many areas of protein production and structural biology research. Several useful features are available on the web site, including multiple ways to search the database of over 250 technological advances, a link to videos of methods on YouTube, and access to a technology forum where scientists can connect, ask questions, get news, and develop collaborations. The Technology Portal is a component of the PSI SBKB ( http://sbkb.org ), which presents integrated genomic, structural, and functional information for all protein sequence targets selected by the Protein Structure Initiative. Created in collaboration with the Nature Publishing Group, the SBKB offers an array of resources for structural biologists, such as a research library, editorials about new research advances, a featured biological system each month, and a functional sleuth for searching protein structures of unknown function. An overview of the various features and examples of user searches highlight the information, tools, and avenues for scientific interaction available through the Technology Portal.

Thermodynamics and the evolution of a city: a tale of how Chicago came to be, from biophysical and socio-economic perspectives

EPA Science Inventory

Cities are complex organized systems, similar to biological and ecological systems in the way that they are structured and function. These systems are subject to the laws of thermodynamics and the principles of Energy Systems Theory (EST). Like other systems, cities experience l...

Health, Health Care, and Systems Science: Emerging Paradigm

PubMed Central

2017-01-01

Health is a continuum of an optimized state of a biologic system, an outcome of positive relationships with the self and others. A healthy system follows the principles of systems science derived from observations of nature, highlighting the character of relationships as the key determinant. Relationships evolve from our decisions, which are consequential to the function of our own biologic system on all levels, including the genome, where epigenetics impact our morphology. In healthy systems, decisions emanate from the reciprocal collaboration of hippocampal memory and the executive prefrontal cortex. We can decide to change relationships through choices. What is selected, however, only represents the cognitive interpretation of our limited sensory perception; it strongly reflects inherent biases toward either optimizing state, making a biologic system healthy, or not. Health or its absence is then the outcome; there is no inconsequential choice. Public health effort should not focus on punitive steps (e.g. taxation of unhealthy products or behaviors) in order to achieve a higher level of public’s health. It should teach people the process of making healthy decisions; otherwise, people will just migrate/shift from one unhealthy product/behavior to another, and well-intended punitive steps will not make much difference. Physical activity, accompanied by nutrition and stress management, have the greatest impact on fashioning health and simultaneously are the most cost-effective measures. Moderate-to-vigorous exercise not only improves aerobic fitness but also positively influences cognition, including memory and senses. Collective, rational societal decisions can then be anticipated. Health care is a business system principally governed by self-maximizing decisions of its components; uneven and contradictory outcomes are the consequences within such a non-optimized system. Health is not health care. We are biologic systems subject to the laws of biology in spite of our incongruous decisions that are detrimental to health. A biologic system/a human body originates from structural, deterministic genes as well as shared epigenetic memory of our ancestors affecting our bodily function and structure. The political governing systems’ vertical hierarchy has control over money and laws, neither of which materially affect individual lifestyle/behavioral choices toward health. Improved health comes from focusing on enhancing the biologic age and not the chronologic one, which simply represents a linear time from a birth certificate to a death certificate and is applicable only in its extremes. “Age-related diseases” are simply reflections of a given culture. Biologic age, reflecting the actual state of health, could be used in all health-related assessments including health-life insurance premiums, licensing of job categories, etc., all with a broader and healthy societal impact. PMID:28357162

The functional role of long non-coding RNA in digestive system carcinomas.

PubMed

Wang, Guang-Yu; Zhu, Yuan-Yuan; Zhang, Yan-Qiao

2014-09-01

In recent years, long non-coding RNAs (lncRNAs) are emerging as either oncogenes or tumor suppressor genes. Recent evidences suggest that lncRNAs play a very important role in digestive system carcinomas. However, the biological function of lncRNAs in the vast majority of digestive system carcinomas remains unclear. Recently, increasing studies has begun to explore their molecular mechanisms and regulatory networks that they are implicated in tumorigenesis. In this review, we highlight the emerging functional role of lncRNAs in digestive system carcinomas. It is becoming clear that lncRNAs will be exciting and potentially useful for diagnosis and treatment of digestive system carcinomas, some of these lncRNAs might function as both diagnostic markers and the treatment targets of digestive system carcinomas.

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.

What we can learn from a tadpole about ciliopathies and airway diseases: Using systems biology in Xenopus to study cilia and mucociliary epithelia.

PubMed

Walentek, Peter; Quigley, Ian K

2017-01-01

Over the past years, the Xenopus embryo has emerged as an incredibly useful model organism for studying the formation and function of cilia and ciliated epithelia in vivo. This has led to a variety of findings elucidating the molecular mechanisms of ciliated cell specification, basal body biogenesis, cilia assembly, and ciliary motility. These findings also revealed the deep functional conservation of signaling, transcriptional, post-transcriptional, and protein networks employed in the formation and function of vertebrate ciliated cells. Therefore, Xenopus research can contribute crucial insights not only into developmental and cell biology, but also into the molecular mechanisms underlying cilia related diseases (ciliopathies) as well as diseases affecting the ciliated epithelium of the respiratory tract in humans (e.g., chronic lung diseases). Additionally, systems biology approaches including transcriptomics, genomics, and proteomics have been rapidly adapted for use in Xenopus, and broaden the applications for current and future translational biomedical research. This review aims to present the advantages of using Xenopus for cilia research, highlight some of the evolutionarily conserved key concepts and mechanisms of ciliated cell biology that were elucidated using the Xenopus model, and describe the potential for Xenopus research to address unresolved questions regarding the molecular mechanisms of ciliopathies and airway diseases. © 2017 Wiley Periodicals, Inc.

Toward systems metabolic engineering of Aspergillus and Pichia species for the production of chemicals and biofuels.

PubMed

Caspeta, Luis; Nielsen, Jens

2013-05-01

Recently genome sequence data have become available for Aspergillus and Pichia species of industrial interest. This has stimulated the use of systems biology approaches for large-scale analysis of the molecular and metabolic responses of Aspergillus and Pichia under defined conditions, which has resulted in much new biological information. Case-specific contextualization of this information has been performed using comparative and functional genomic tools. Genomics data are also the basis for constructing genome-scale metabolic models, and these models have helped in the contextualization of knowledge on the fundamental biology of Aspergillus and Pichia species. Furthermore, with the availability of these models, the engineering of Aspergillus and Pichia is moving from traditional approaches, such as random mutagenesis, to a systems metabolic engineering approach. Here we review the recent trends in systems biology of Aspergillus and Pichia species, highlighting the relevance of these developments for systems metabolic engineering of these organisms for the production of hydrolytic enzymes, biofuels and chemicals from biomass. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

[The application of laser beam welding of biological tissues for the purpose of ossiculoplasty].

PubMed

Semenov, V F

2013-01-01

The objective of the present work was to estimate the functional outcome of ossiculoplasty in the patients presenting with chronic suppurative otitis media and treated by means of laser beam welding of biological tissues. In order to obtain a good functional result of tympanoplasty including ossiculoplasty, it is necessary to conserve the elements of the sound-conducting system in the positions to which they were set during surgery. We reached this goal by fixing individual elements of the chain of the auditory ossicles by means of the laser beam welding of biological tissues with the use of platelet-rich plasma as a solder alloy. The audiometric examination of the patients within 1, 3, and 12 months after surgery showed that this technique improves the functional outcome of the treatment of the patients with chronic suppurative otitis media using prostheses for the substitution of the auditory ossicles.

Rational Design of an Ultrasensitive Quorum-Sensing Switch.

PubMed

Zeng, Weiqian; Du, Pei; Lou, Qiuli; Wu, Lili; Zhang, Haoqian M; Lou, Chunbo; Wang, Hongli; Ouyang, Qi

2017-08-18

One of the purposes of synthetic biology is to develop rational methods that accelerate the design of genetic circuits, saving time and effort spent on experiments and providing reliably predictable circuit performance. We applied a reverse engineering approach to design an ultrasensitive transcriptional quorum-sensing switch. We want to explore how systems biology can guide synthetic biology in the choice of specific DNA sequences and their regulatory relations to achieve a targeted function. The workflow comprises network enumeration that achieves the target function robustly, experimental restriction of the obtained candidate networks, global parameter optimization via mathematical analysis, selection and engineering of parts based on these calculations, and finally, circuit construction based on the principles of standardization and modularization. The performance of realized quorum-sensing switches was in good qualitative agreement with the computational predictions. This study provides practical principles for the rational design of genetic circuits with targeted functions.

Biological fabrication of cellulose fibers with tailored properties.

PubMed

Natalio, Filipe; Fuchs, Regina; Cohen, Sidney R; Leitus, Gregory; Fritz-Popovski, Gerhard; Paris, Oskar; Kappl, Michael; Butt, Hans-Jürgen

2017-09-15

Cotton is a promising basis for wearable smart textiles. Current approaches that rely on fiber coatings suffer from function loss during wear. We present an approach that allows biological incorporation of exogenous molecules into cotton fibers to tailor the material's functionality. In vitro model cultures of upland cotton ( Gossypium hirsutum ) are incubated with 6-carboxyfluorescein-glucose and dysprosium-1,4,7,10-tetraazacyclododecane-1,4,7,10-tetraacetic acid-glucose, where the glucose moiety acts as a carrier capable of traveling from the vascular connection to the outermost cell layer of the ovule epidermis, becoming incorporated into the cellulose fibers. This yields fibers with unnatural properties such as fluorescence or magnetism. Combining biological systems with the appropriate molecular design offers numerous possibilities to grow functional composite materials and implements a material-farming concept. Copyright © 2017 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.

[The biological reaction of inflammation, methylglyoxal of blood plasma, functional and structural alterations in elastic type arteries at the early stage of hypertension disease].

PubMed

Titov, V N; Dmitriev, V A; Oshchepkov, E V; Balakhonova, T V; Tripoten', M I; Shiriaeva, Iu K

2012-08-01

The article deals with studying of the relationship between biologic reaction of inflammation with glycosylation reaction and content of methylglyoxal in blood serum. The positive correlation between pulse wave velocity and content of methylglyoxal, C-reactive protein in intercellular medium and malleolar brachial index value was established. This data matches the experimental results concerning involvement of biological reaction of inflammation into structural changes of elastic type arteries under hypertension disease, formation of arteries' rigidity and increase of pulse wave velocity. The arterial blood pressure is a biological reaction of hydrodynamic pressure which is used in vivo by several biological functions: biological function of homeostasis, function of endoecology, biological function of adaptation and function of locomotion. The biological reaction of hydrodynamic (hydraulic) pressure is a mode of compensation of derangement of several biological functions which results in the very high rate of hypertension disease in population. As a matter of fact, hypertension disease is a syndrome of lingering pathological compensation by higher arterial blood pressure of the biological functions derangements occurring in the distal section at the level of paracrine cenoses of cells. The arterial blood pressure is a kind of in vivo integral indicator of deranged metabolism. The essential hypertension disease pathogenically is a result of the derangement of three biological functions: biological function of homeostasis, biological function of trophology - nutrition (biological reaction of external feeding - exotrophia) and biological function of endoecology. In case of "littering" of intercellular medium in vivo with nonspecific endogenic flogogens a phylogenetically earlier activation of biological reactions of excretion, inflammation and hydrodynamic arterial blood pressure occur. In case of derangement of biological function of homeostasis, decreasing of perfusion even in single paracrine cenoses and derangement of biological function of endoecology ("purity" of intercellular medium) the only response always will be the increase of arterial blood pressure.

Biologically inspired dynamic material systems.

PubMed

Studart, André R

2015-03-09

Numerous examples of material systems that dynamically interact with and adapt to the surrounding environment are found in nature, from hair-based mechanoreceptors in animals to self-shaping seed dispersal units in plants to remodeling bone in vertebrates. Inspired by such fascinating biological structures, a wide range of synthetic material systems have been created to replicate the design concepts of dynamic natural architectures. Examples of biological structures and their man-made counterparts are herein revisited to illustrate how dynamic and adaptive responses emerge from the intimate microscale combination of building blocks with intrinsic nanoscale properties. By using top-down photolithographic methods and bottom-up assembly approaches, biologically inspired dynamic material systems have been created 1) to sense liquid flow with hair-inspired microelectromechanical systems, 2) to autonomously change shape by utilizing plantlike heterogeneous architectures, 3) to homeostatically influence the surrounding environment through self-regulating adaptive surfaces, and 4) to spatially concentrate chemical species by using synthetic microcompartments. The ever-increasing complexity and remarkable functionalities of such synthetic systems offer an encouraging perspective to the rich set of dynamic and adaptive properties that can potentially be implemented in future man-made material systems. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Redox Regulation of Endothelial Cell Fate

PubMed Central

Song, Ping; Zou, Ming-Hui

2014-01-01

Endothelial cells (ECs) are present throughout blood vessels and have variable roles in both physiological and pathological settings. EC fate is altered and regulated by several key factors in physiological or pathological conditions. Reactive nitrogen species and reactive oxygen species derived from NAD(P)H oxidases, mitochondria, or nitric oxide-producing enzymes are not only cytotoxic but also compose a signaling network in the redox system. The formation, actions, key molecular interactions, and physiological and pathological relevance of redox signals in ECs remain unclear. We review the identities, sources, and biological actions of oxidants and reductants produced during EC function or dysfunction. Further, we discuss how ECs shape key redox sensors and examine the biological functions, transcriptional responses, and post-translational modifications evoked by the redox system in ECs. We summarize recent findings regarding the mechanisms by which redox signals regulate the fate of ECs and address the outcome of altered EC fate in health and disease. Future studies will examine if the redox biology of ECs can be targeted in pathophysiological conditions. PMID:24633153

Bioinspired microrobots

NASA Astrophysics Data System (ADS)

Palagi, Stefano; Fischer, Peer

2018-06-01

Microorganisms can move in complex media, respond to the environment and self-organize. The field of microrobotics strives to achieve these functions in mobile robotic systems of sub-millimetre size. However, miniaturization of traditional robots and their control systems to the microscale is not a viable approach. A promising alternative strategy in developing microrobots is to implement sensing, actuation and control directly in the materials, thereby mimicking biological matter. In this Review, we discuss design principles and materials for the implementation of robotic functionalities in microrobots. We examine different biological locomotion strategies, and we discuss how they can be artificially recreated in magnetic microrobots and how soft materials improve control and performance. We show that smart, stimuli-responsive materials can act as on-board sensors and actuators and that `active matter' enables autonomous motion, navigation and collective behaviours. Finally, we provide a critical outlook for the field of microrobotics and highlight the challenges that need to be overcome to realize sophisticated microrobots, which one day might rival biological machines.

Yeast Genomics for Bread, Beer, Biology, Bucks and Breath

NASA Astrophysics Data System (ADS)

Sakharkar, Kishore R.; Sakharkar, Meena K.

The rapid advances and scale up of projects in DNA sequencing dur ing the past two decades have produced complete genome sequences of several eukaryotic species. The versatile genetic malleability of the yeast, and the high degree of conservation between its cellular processes and those of human cells have made it a model of choice for pioneering research in molecular and cell biology. The complete sequence of yeast genome has proven to be extremely useful as a reference towards the sequences of human and for providing systems to explore key gene functions. Yeast has been a ‘legendary model’ for new technologies and gaining new biological insights into basic biological sciences and biotechnology. This chapter describes the awesome power of yeast genetics, genomics and proteomics in understanding of biological function. The applications of yeast as a screening tool to the field of drug discovery and development are highlighted and the traditional importance of yeast for bakers and brewers is discussed.

Payao: a community platform for SBML pathway model curation

PubMed Central

Matsuoka, Yukiko; Ghosh, Samik; Kikuchi, Norihiro; Kitano, Hiroaki

2010-01-01

Summary: Payao is a community-based, collaborative web service platform for gene-regulatory and biochemical pathway model curation. The system combines Web 2.0 technologies and online model visualization functions to enable a collaborative community to annotate and curate biological models. Payao reads the models in Systems Biology Markup Language format, displays them with CellDesigner, a process diagram editor, which complies with the Systems Biology Graphical Notation, and provides an interface for model enrichment (adding tags and comments to the models) for the access-controlled community members. Availability and implementation: Freely available for model curation service at http://www.payaologue.org. Web site implemented in Seaser Framework 2.0 with S2Flex2, MySQL 5.0 and Tomcat 5.5, with all major browsers supported. Contact: kitano@sbi.jp PMID:20371497

Optimality Principles in the Regulation of Metabolic Networks

PubMed Central

Berkhout, Jan; Bruggeman, Frank J.; Teusink, Bas

2012-01-01

One of the challenging tasks in systems biology is to understand how molecular networks give rise to emergent functionality and whether universal design principles apply to molecular networks. To achieve this, the biophysical, evolutionary and physiological constraints that act on those networks need to be identified in addition to the characterisation of the molecular components and interactions. Then, the cellular “task” of the network—its function—should be identified. A network contributes to organismal fitness through its function. The premise is that the same functions are often implemented in different organisms by the same type of network; hence, the concept of design principles. In biology, due to the strong forces of selective pressure and natural selection, network functions can often be understood as the outcome of fitness optimisation. The hypothesis of fitness optimisation to understand the design of a network has proven to be a powerful strategy. Here, we outline the use of several optimisation principles applied to biological networks, with an emphasis on metabolic regulatory networks. We discuss the different objective functions and constraints that are considered and the kind of understanding that they provide. PMID:24957646

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.

Subcortical encoding of sound is enhanced in bilinguals and relates to executive function advantages

PubMed Central

Krizman, Jennifer; Marian, Viorica; Shook, Anthony; Skoe, Erika; Kraus, Nina

2012-01-01

Bilingualism profoundly affects the brain, yielding functional and structural changes in cortical regions dedicated to language processing and executive function [Crinion J, et al. (2006) Science 312:1537–1540; Kim KHS, et al. (1997) Nature 388:171–174]. Comparatively, musical training, another type of sensory enrichment, translates to expertise in cognitive processing and refined biological processing of sound in both cortical and subcortical structures. Therefore, we asked whether bilingualism can also promote experience-dependent plasticity in subcortical auditory processing. We found that adolescent bilinguals, listening to the speech syllable [da], encoded the stimulus more robustly than age-matched monolinguals. Specifically, bilinguals showed enhanced encoding of the fundamental frequency, a feature known to underlie pitch perception and grouping of auditory objects. This enhancement was associated with executive function advantages. Thus, through experience-related tuning of attention, the bilingual auditory system becomes highly efficient in automatically processing sound. This study provides biological evidence for system-wide neural plasticity in auditory experts that facilitates a tight coupling of sensory and cognitive functions. PMID:22547804

What makes closed ecological systems sustainable?

NASA Astrophysics Data System (ADS)

Gitelson, I.; Degermendzhy, A.; Rodicheva, E.

A closed ecosystem has some properties that an open systems lacks. Let us consider the ones that increase the sustainability of an ecosystem. The common feature of biological and physicochemical life support systems is that basically they are both catalytic. There are two fundamental properties distinguishing biological systems: 1) they are auto-catalytic: their catalysts - enzymes of protein nature - are continuously reproduced when the system functions; 2) the program of every process performed by enzymes and the program of their reproduction are inherent in the biological system itself - in the totality of genomes of the species involved in the functioning of the ecosystem. Actually, one cell with the genome capable of the phenotypic realization is enough for the self- restoration of the function performed by the cells of this species in the ecosystem. The multi-cellular organisms with stem cells are constantly ready to repair themselves by intensifying the continuous process of regeneration. We (Gitelson) have made a quantitative investigation of this process by studying the regeneration and reparation of erythrocytes in mammals. The continuous microalgal culture of Chlorella vulgaris was taken to investigate quantitatively the similar functional process of self-restoration in unicellular algae (Rodicheva). Based on the data obtained, we proposed a mathematical model of the restoration process in the cell population that has suffered an acute radiation damage. Besides these general biological mechanisms responsible for their sustainability, closed systems also possess specific features enhancing their stability. They are as follows: 1. Nutrients cannot leave the system. 2. The metabolic pathways of the material cycling are closed. 3. The rates of interlink metabolism are in conformity with each other due to their mutual limitation. We present the data obtained in the Bios-3 experiments that prove the efficiency of this mechanism as a factor of the sustainability. The factors that reduce the sustainability of a CES are as follows: the range of ambient physicochemical parameters compatible with life is rather narrow and it takes rather a long time for the system to restore itself if damage is done to its relatively long-lived species, such as higher plants. A specific property of a small CES is that humans inhabiting it must perform a deterministic control. Our experiments in Bios-3 proved that this control is quite feasible and that it effectively increases the stability of the system. Thus, we can predict that humanity may perform the function of control in the Earth's biosphere in the course of its transformation into the noosphere. * "This work was made possible in part by Award No. REC-002 of the U.S. Civilian Research &Development Foundation for the Independent States of the Former Union (CRDF) and RF Ministry of Education."

Synthetic biology projects in vitro.

PubMed

Forster, Anthony C; Church, George M

2007-01-01

Advances in the in vitro synthesis and evolution of DNA, RNA, and polypeptides are accelerating the construction of biopolymers, pathways, and organisms with novel functions. Known functions are being integrated and debugged with the aim of synthesizing life-like systems. The goals are knowledge, tools, smart materials, and therapies.

Embedded Literacy: Knowledge as Meaning

ERIC Educational Resources Information Center

Martin, J. R.

2013-01-01

This paper takes as point of departure the register variable field, and explores its application to the discourse of History and Biology in secondary school classrooms from the perspective of systemic functional linguistics. In particular it considers the functions of technicality and abstraction in these subject specific discourses, and their…

Impaired visual recognition of biological motion in schizophrenia.

PubMed

Kim, Jejoong; Doop, Mikisha L; Blake, Randolph; Park, Sohee

2005-09-15

Motion perception deficits have been suggested to be an important feature of schizophrenia but the behavioral consequences of such deficits are unknown. Biological motion refers to the movements generated by living beings. The human visual system rapidly and effortlessly detects and extracts socially relevant information from biological motion. A deficit in biological motion perception may have significant consequences for detecting and interpreting social information. Schizophrenia patients and matched healthy controls were tested on two visual tasks: recognition of human activity portrayed in point-light animations (biological motion task) and a perceptual control task involving detection of a grouped figure against the background noise (global-form task). Both tasks required detection of a global form against background noise but only the biological motion task required the extraction of motion-related information. Schizophrenia patients performed as well as the controls in the global-form task, but were significantly impaired on the biological motion task. In addition, deficits in biological motion perception correlated with impaired social functioning as measured by the Zigler social competence scale [Zigler, E., Levine, J. (1981). Premorbid competence in schizophrenia: what is being measured? Journal of Consulting and Clinical Psychology, 49, 96-105.]. The deficit in biological motion processing, which may be related to the previously documented deficit in global motion processing, could contribute to abnormal social functioning in schizophrenia.

BIOZON: a system for unification, management and analysis of heterogeneous biological data.

PubMed

Birkland, Aaron; Yona, Golan

2006-02-15

Integration of heterogeneous data types is a challenging problem, especially in biology, where the number of databases and data types increase rapidly. Amongst the problems that one has to face are integrity, consistency, redundancy, connectivity, expressiveness and updatability. Here we present a system (Biozon) that addresses these problems, and offers biologists a new knowledge resource to navigate through and explore. Biozon unifies multiple biological databases consisting of a variety of data types (such as DNA sequences, proteins, interactions and cellular pathways). It is fundamentally different from previous efforts as it uses a single extensive and tightly connected graph schema wrapped with hierarchical ontology of documents and relations. Beyond warehousing existing data, Biozon computes and stores novel derived data, such as similarity relationships and functional predictions. The integration of similarity data allows propagation of knowledge through inference and fuzzy searches. Sophisticated methods of query that span multiple data types were implemented and first-of-a-kind biological ranking systems were explored and integrated. The Biozon system is an extensive knowledge resource of heterogeneous biological data. Currently, it holds more than 100 million biological documents and 6.5 billion relations between them. The database is accessible through an advanced web interface that supports complex queries, "fuzzy" searches, data materialization and more, online at http://biozon.org.

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.

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.

Carbon Nanotubes in Biology and Medicine: In vitro and in vivo Detection, Imaging and Drug Delivery

PubMed Central

Liu, Zhuang; Tabakman, Scott; Welsher, Kevin; Dai, Hongjie

2010-01-01

Carbon nanotubes exhibit many unique intrinsic physical and chemical properties and have been intensively explored for biological and biomedical applications in the past few years. In this comprehensive review, we summarize the main results from our and other groups in this field and clarify that surface functionalization is critical to the behavior of carbon nanotubes in biological systems. Ultrasensitive detection of biological species with carbon nanotubes can be realized after surface passivation to inhibit the non-specific binding of biomolecules on the hydrophobic nanotube surface. Electrical nanosensors based on nanotubes provide a label-free approach to biological detection. Surface-enhanced Raman spectroscopy of carbon nanotubes opens up a method of protein microarray with detection sensitivity down to 1 fmol/L. In vitro and in vivo toxicity studies reveal that highly water soluble and serum stable nanotubes are biocompatible, nontoxic, and potentially useful for biomedical applications. In vivo biodistributions vary with the functionalization and possibly also size of nanotubes, with a tendency to accumulate in the reticuloendothelial system (RES), including the liver and spleen, after intravenous administration. If well functionalized, nanotubes may be excreted mainly through the biliary pathway in feces. Carbon nanotube-based drug delivery has shown promise in various In vitro and in vivo experiments including delivery of small interfering RNA (siRNA), paclitaxel and doxorubicin. Moreover, single-walled carbon nanotubes with various interesting intrinsic optical properties have been used as novel photoluminescence, Raman, and photoacoustic contrast agents for imaging of cells and animals. Further multidisciplinary explorations in this field may bring new opportunities in the realm of biomedicine. PMID:20174481

Network analysis reveals stage-specific changes in zebrafish embryo development using time course whole transcriptome profiling and prior biological knowledge.

PubMed

Zhang, Yuji

2015-01-01

Molecular networks act as the backbone of molecular activities within cells, offering a unique opportunity to better understand the mechanism of diseases. While network data usually constitute only static network maps, integrating them with time course gene expression information can provide clues to the dynamic features of these networks and unravel the mechanistic driver genes characterizing cellular responses. Time course gene expression data allow us to broadly "watch" the dynamics of the system. However, one challenge in the analysis of such data is to establish and characterize the interplay among genes that are altered at different time points in the context of a biological process or functional category. Integrative analysis of these data sources will lead us a more complete understanding of how biological entities (e.g., genes and proteins) coordinately perform their biological functions in biological systems. In this paper, we introduced a novel network-based approach to extract functional knowledge from time-dependent biological processes at a system level using time course mRNA sequencing data in zebrafish embryo development. The proposed method was applied to investigate 1α, 25(OH)2D3-altered mechanisms in zebrafish embryo development. We applied the proposed method to a public zebrafish time course mRNA-Seq dataset, containing two different treatments along four time points. We constructed networks between gene ontology biological process categories, which were enriched in differential expressed genes between consecutive time points and different conditions. The temporal propagation of 1α, 25-Dihydroxyvitamin D3-altered transcriptional changes started from a few genes that were altered initially at earlier stage, to large groups of biological coherent genes at later stages. The most notable biological processes included neuronal and retinal development and generalized stress response. In addition, we also investigated the relationship among biological processes enriched in co-expressed genes under different conditions. The enriched biological processes include translation elongation, nucleosome assembly, and retina development. These network dynamics provide new insights into the impact of 1α, 25-Dihydroxyvitamin D3 treatment in bone and cartilage development. We developed a network-based approach to analyzing the DEGs at different time points by integrating molecular interactions and gene ontology information. These results demonstrate that the proposed approach can provide insight on the molecular mechanisms taking place in vertebrate embryo development upon treatment with 1α, 25(OH)2D3. Our approach enables the monitoring of biological processes that can serve as a basis for generating new testable hypotheses. Such network-based integration approach can be easily extended to any temporal- or condition-dependent genomic data analyses.

A tunable algorithm for collective decision-making.

PubMed

Pratt, Stephen C; Sumpter, David J T

2006-10-24

Complex biological systems are increasingly understood in terms of the algorithms that guide the behavior of system components and the information pathways that link them. Much attention has been given to robust algorithms, or those that allow a system to maintain its functions in the face of internal or external perturbations. At the same time, environmental variation imposes a complementary need for algorithm versatility, or the ability to alter system function adaptively as external circumstances change. An important goal of systems biology is thus the identification of biological algorithms that can meet multiple challenges rather than being narrowly specified to particular problems. Here we show that emigrating colonies of the ant Temnothorax curvispinosus tune the parameters of a single decision algorithm to respond adaptively to two distinct problems: rapid abandonment of their old nest in a crisis and deliberative selection of the best available new home when their old nest is still intact. The algorithm uses a stepwise commitment scheme and a quorum rule to integrate information gathered by numerous individual ants visiting several candidate homes. By varying the rates at which they search for and accept these candidates, the ants yield a colony-level response that adaptively emphasizes either speed or accuracy. We propose such general but tunable algorithms as a design feature of complex systems, each algorithm providing elegant solutions to a wide range of problems.

Systematic reconstruction of TRANSPATH data into Cell System Markup Language

PubMed Central

Nagasaki, Masao; Saito, Ayumu; Li, Chen; Jeong, Euna; Miyano, Satoru

2008-01-01

Background Many biological repositories store information based on experimental study of the biological processes within a cell, such as protein-protein interactions, metabolic pathways, signal transduction pathways, or regulations of transcription factors and miRNA. Unfortunately, it is difficult to directly use such information when generating simulation-based models. Thus, modeling rules for encoding biological knowledge into system-dynamics-oriented standardized formats would be very useful for fully understanding cellular dynamics at the system level. Results We selected the TRANSPATH database, a manually curated high-quality pathway database, which provides a plentiful source of cellular events in humans, mice, and rats, collected from over 31,500 publications. In this work, we have developed 16 modeling rules based on hybrid functional Petri net with extension (HFPNe), which is suitable for graphical representing and simulating biological processes. In the modeling rules, each Petri net element is incorporated with Cell System Ontology to enable semantic interoperability of models. As a formal ontology for biological pathway modeling with dynamics, CSO also defines biological terminology and corresponding icons. By combining HFPNe with the CSO features, it is possible to make TRANSPATH data to simulation-based and semantically valid models. The results are encoded into a biological pathway format, Cell System Markup Language (CSML), which eases the exchange and integration of biological data and models. Conclusion By using the 16 modeling rules, 97% of the reactions in TRANSPATH are converted into simulation-based models represented in CSML. This reconstruction demonstrates that it is possible to use our rules to generate quantitative models from static pathway descriptions. PMID:18570683

Systematic reconstruction of TRANSPATH data into cell system markup language.

PubMed

Nagasaki, Masao; Saito, Ayumu; Li, Chen; Jeong, Euna; Miyano, Satoru

2008-06-23

Many biological repositories store information based on experimental study of the biological processes within a cell, such as protein-protein interactions, metabolic pathways, signal transduction pathways, or regulations of transcription factors and miRNA. Unfortunately, it is difficult to directly use such information when generating simulation-based models. Thus, modeling rules for encoding biological knowledge into system-dynamics-oriented standardized formats would be very useful for fully understanding cellular dynamics at the system level. We selected the TRANSPATH database, a manually curated high-quality pathway database, which provides a plentiful source of cellular events in humans, mice, and rats, collected from over 31,500 publications. In this work, we have developed 16 modeling rules based on hybrid functional Petri net with extension (HFPNe), which is suitable for graphical representing and simulating biological processes. In the modeling rules, each Petri net element is incorporated with Cell System Ontology to enable semantic interoperability of models. As a formal ontology for biological pathway modeling with dynamics, CSO also defines biological terminology and corresponding icons. By combining HFPNe with the CSO features, it is possible to make TRANSPATH data to simulation-based and semantically valid models. The results are encoded into a biological pathway format, Cell System Markup Language (CSML), which eases the exchange and integration of biological data and models. By using the 16 modeling rules, 97% of the reactions in TRANSPATH are converted into simulation-based models represented in CSML. This reconstruction demonstrates that it is possible to use our rules to generate quantitative models from static pathway descriptions.

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.