Computational Biology Approaches to Plant Metabolism and Photosynthesis: Applications for Corals in Times of Climate Change and Environmental Stress

Knowledge of factors that are important in reef resilience helps us to understand how reef ecosystems react following major an-thropogenic and environmental disturbances. The symbiotic rela-tionship between the photosynthetic zooxanthellae algal cells and corals is that the zooxanthellae provide the coral with carbon, while the coral provides protection and access to enough light for the zooxanthellae to photosynthesise. This article reviews some recent advances in computational biology relevant to photosynthetic or-ganisms, including Beyesian approaches to kinetics, computational methods for flux balances in metabolic processes, and determina-tion of clades of zooxanthallae. Application of these systems will be important in the conservation of coral reefs in times of climate change and environmental stress.     

Systems biology strategy to study lipotoxicity and the metabolic syndrome

Systems biology views and studies the biological systems in the context of complex interactions between their building blocks and processes. Given its multi-level complexity, metabolic syndrome (MetS) makes a strong case for adopting the systems biology approach. Despite many MetS traits being highly heritable, it is becoming evident that the genetic contribution to these traits is mediated via gene–gene and gene–environment interactions across several spatial and temporal scales, and that some of these traits such as lipotoxicity may even be a product of long-term dynamic changes of the underlying genetic and molecular networks. This presents several conceptual as well as methodological challenges and may demand a paradigm shift in how we study the undeniably strong genetic component of complex diseases such as MetS. The argument is made here that for adopting systems biology approaches to MetS an integrative framework is needed which glues the biological processes of MetS with specific physiological mechanisms and principles and that lipotoxicity is one such framework. The metabolic phenotypes, molecular and genetic networks can be modeled within the context of such integrative framework and the underlying physiology.     

Prediction of microbial growth rate versus biomass yield by a metabolic network with kinetic parameters

Identifying the factors that determine microbial growth rate under various environmental and genetic conditions is a major challenge of systems biology. While current genome-scale metabolic modeling approaches enable us to successfully predict a variety of metabolic phenotypes, including maximal biomass yield, the prediction of actual growth rate is a long standing goal. This gap stems from strictly relying on data regarding reaction stoichiometry and directionality, without accounting for enzyme kinetic considerations. Here we present a novel metabolic network-based approach, MetabOlic Modeling with ENzyme kineTics (MOMENT), which predicts metabolic flux rate and growth rate by utilizing prior data on enzyme turnover rates and enzyme molecular weights, without requiring measurements of nutrient uptake rates. The method is based on an identified design principle of metabolism in which enzymes catalyzing high flux reactions across different media tend to be more efficient in terms of having higher turnover numbers. Extending upon previous attempts to utilize kinetic data in genome-scale metabolic modeling, our approach takes into account the requirement for specific enzyme concentrations for catalyzing predicted metabolic flux rates, considering isozymes, protein complexes, and multi-functional enzymes. MOMENT is shown to significantly improve the prediction accuracy of various metabolic phenotypes in E. coli, including intracellular flux rates and changes in gene expression levels under different growth rates. Most importantly, MOMENT is shown to predict growth rates of E. coli under a diverse set of media that are correlated with experimental measurements, markedly improving upon existing state-of-the art stoichiometric modeling approaches. These results support the view that a physiological bound on cellular enzyme concentrations is a key factor that determines microbial growth rate.     

基于信息度量的基因网络建模

基因网络作为生物系统三大网络中最基础的组成部分,是目前系统生物学研究的一大热点。本文分析了目前基因网络。建模的各种方法。井着重分析了布尔网络的建模特点。提出了利用信息理论中的信息熵和互信息方法来分析基因网络的各元素之间的布尔逻辑关系。通过实例分析说明了该方法在布尔网络建模中的有效性。     

Errors in bone remodeling: toward a unified theory of metabolic bone disease

Recent evidence suggests that skeletal adaptation is organized by a functional unit that includes cells of diverse origin working in coordination. Genetic and metabolic factors control and regulate the processes of modeling and remodeling, only rarely acting on the isolated individual functions of specific cell lines. Errors in the genetic or metabolic regulation of the functional unit affect the entire process of skeletal adaptation rather than specific elements of it. Viewed in this way, some metabolic bone diseases can be understood as relatively simple errors in factors that control the coordinated activities of the entire functional unit. This paper reviews the modeling and remodeling processes and demonstrates how abnormal morphological characteristics of bone tissue can be viewed as products of specific errors in the adaptive process.     

The challenges for molecular nutrition research 3: comparative nutrigenomics research as a basis for entering the systems level

Human nutrition and metabolism may serve as the paradigm for the complex interplay of the genome with its environment. The concept of nutrigenomics now enables science with new tools and comprehensive analytical techniques to investigate this interaction at all levels of the complexity of the organism. Moreover, nutrigenomics seeks to better define the homeostatic control mechanisms, identify the de-regulation in the early phases of diet-related diseases, and attempts to assess to what extent an individual's sensitizing genotype contributes to the overall health or disease state. In a comparative approach nutrigenomics uses biological systems of increasing complexity from yeast to mammalian models to define the general rules of metabolic and genetic mechanisms in adaptations to the nutritional environment. Powerful information technology, bioinformatics and knowledge management tools as well as new mathematical and computational approaches now make it possible to study these molecular mechanisms at the cellular, organ and whole organism level and take it on to modeling the processes in a "systems biology" approach. This review summarizes some of the concepts of a comparative approach to nutrigenomics research, identifies current lacks and proposes a concerted scientific effort to create the basis for nutritional systems biology.     

Microbiology is the basis of sustainable agriculture: an opinion

Agricultural microbiology is presented as a synthetic research field responsible for knowledge transfer from general microbiology and microbial ecology to the agricultural biotechnologies. The major goal of agricultural microbiology is a comprehensive analysis of symbiotic micro‐organisms (bacteria, fungi) interacting with agriculturally important plants and animals: here we have focussed on plants. In plants, interactions with micro‐organisms are diverse, ranging from two‐partite symbioses (e.g. legume–rhizobia N₂‐fixing nodular symbioses or arbuscular mycorrhiza) to multipartite endophytic and epiphytic (root‐associated, phyllosphere) communities. Two‐partite symbioses provide the clearest models for addressing genetic cooperation between partners, resulting in the formation of super‐organism genetic systems, which are responsible for host productivity. Analysis of these systems has now been extended considerably by using the approaches of metagenomics, which allow the dissection of taxonomic/population structures and the metabolic/ecological functions of microbial communities, which have resulted from the adaptation of free‐living, soil microflora in the endosymbiotic niches. Both beneficial (nutritional, defensive, regulatory) and antagonistic (biocontrol) functions expressed by symbiotic microbes towards their hosts are the potential subjects of effective agronomic use. A fundamental knowledge of the genetics, molecular biology, ecology and evolution of symbiotic interactions could enable the development of microbe‐based sustainable agriculture. This could achieve: (a) an improvement of major adaptive functions and productivity in crop plants by manipulating their microbial cohabitants; (b) partial or even full substitution of ecologically hazardous agrochemicals (mineral fertilizers, pesticides) by microbial preparations; (c) a decrease in the cost and an improvement of the quality of agricultural products.     

Metabolic and evolutionary engineering research in Turkey and beyond

This review discusses metabolic engineering research with an emphasis on evolutionary (whole cell and protein) engineering, which is an inverse metabolic engineering approach. For each section on metabolic, inverse metabolic and evolutionary engineering research, a general review of the major global studies in the literature is made and research examples from Turkey are given and discussed. It is expected that with the rapid development in systems biology and the novel powerful analytical technologies to identify the genetic basis of cellular phenotypes, metabolic and evolutionary engineering research will become widespread and increasingly important in Turkey, following global scientific trends.     

Rhizobium plasmids in bacteria-legume interactions

The functional analysis of plasmids in Rhizobium strains has concentrated mainly on the symbiotic plasmid (pSym). However, genetic information relevant to both symbiotic and saprophytic Rhizobium life cycles, localized on other cryptic replicons, has also been reported. Information is reviewed which concerns functional features encoded in plasmids other than the pSym: biosynthesis of cell surface polysaccharides, metabolic processes, the utilization of plant exudates, aromatic compounds and diverse sugars, and features involved symbiotic performance. In addition, factors which affect plasmid evolution through their influence on structural features of the plasmids, such as conjugative transfer and genomic rearrangements, is discussed. Based on the overall data, we propose that together the plasmids and the chromosome constitute a fully integrated genomic complex, entailing structural features as well as saprophytic and cellular functions.The authors are with the Depto. de Genética Molecular. Centro de Investigación sobre Fijación de Nitrógeno. UNAM. A. Postal 565-A, Cuernavaca. Morelos, México;     

Metabolic ensemble modeling for strain engineers

Previous mathematical modeling efforts have made significant contributions to the development of systems biology for predicting biological behavior quantitatively. However, dynamic metabolic model construction remains challenging due to uncertainties in mechanistic structures and parameters. In addition, parameter estimation and model validation often require designated experiments conducted only for purpose of modeling. Such difficulties have hampered the progress of modeling in biology and biotechnology. To circumvent these problems, ensemble approaches have been used to account for uncertainties in model structure and parameters. Specifically, this review focuses on approaches that utilize readily available fermentation data for parameter screening and model validation. Time course data for metabolite measurements, if available, can further calibrate the model. The basis for this approach is explained in non-mathematical terms accessible to experimentalists. Information gained from such an approach has been shown to be useful in designing Escherichia coli strains for metabolic engineering and synthetic biology.     

Computational methods and applications for quantitative systems pharmacology

Background: Quantitative systems pharmacology (QSP) is an emerging discipline that integrates diverse data to quantitatively explore the interactions between drugs and multi-scale systems including small compounds, nucleic acids, proteins, pathways, cells, organs and disease processes. Results: Various computational methods such as ADME/T evaluation, molecular modeling, logical modeling, network modeling, pathway analysis, multi-scale systems pharmacology platforms and virtual patient for QSP have been developed. We reviewed the major progresses and broad applications in medical guidance, drug discovery and exploration of pharmacodynamic material basis and mechanism of traditional Chinese medicine. Conclusion: QSP has significant achievements in recent years and is a promising approach for quantitative evaluation of drug efficacy and systematic exploration of mechanisms of action of drugs.     

Genetic-evolutionary basis of symbiosis doctrine

The author presents the current notion of symbiosis as one of the main adaptation of an organism to changeable environment. Symbiosis is considered as a super organism genetic system within which there are different interactions (including mutualism and antagonism). Genetic integration of symbiotic partners can be realized as cross regulation of their genes, exchange of gene products (proteins, RNA), gene amplification and sometimes gene transfer between organisms. On the phenotypic level these processes result in signal interactions, integration of partner metabolic systems and development of symbiotic organs. Co-evolution is considered as an assemblage of micro- and macroevolution processes basing on pre-adaptations and proceeding under influence of different forms of natural selection (individual, frequency-depended and kin selection). Symbiosis can be compared with sexual process since both are the forms of organism integration characterized by different genetic mechanisms and evolutionary consequences. The genome evolution in symbiotic microorganisms can proceed by: 1) simplification of genome in obligate symbiosis (loss of genes that are necessary for independent existence, transfer of some genes to the host organism); 2) complication of genome in facultative symbiosis (increase in genome plasticity, structural and functional differentiation of genome into systems controlling free-living and symbiotic parts of life cycle). Most of symbiotic interactions are correlated to an increase in genetic plasticity of an organism that can lead to evolutionary saltations and origin of new forms of life.     

Proteomics revisits the cancer metabolome

Many cancer cells utilize aerobic glycolysis (also known as the 'Warburg effect'), instead of mitochondrial oxidative phosphorylation, to generate the energy necessary for diverse cellular processes. In tumor cells, mitochondria play more important roles in anabolism, for instance, de novo lipid biosynthesis and glutamine-dependent anaplerosis to fuel robust cell growth and proliferation. Proteomic analysis of tumor-related alterations of metabolism-associated proteins clearly indicates that such metabolic reprogramming contributes to cancer cell survival and cancer progression. Moreover, proteomics-based systems biology provides a powerful tool to re-evaluate the metabolic phenotype and regulatory mechanism associated with malignant cancer cells, and underscores their implications for cancer diagnosis and therapy. This article will address recent exciting advances in the understanding of cancer cell metabolism using proteomics-based systems biology approaches.     

Dynamic Processes in Regulation and Some Implications for Biofeedback and Biobehavioral Interventions

Systems theory has long been used in psychology, biology, and sociology. This paper applies newer methods of control systems modeling for assessing system stability in health and disease. Control systems can be characterized as open or closed systems with feedback loops. Feedback produces oscillatory activity, and the complexity of naturally occurring oscillatory patterns reflects the multiplicity of feedback mechanisms, such that many mechanisms operate simultaneously to control the system. Unstable systems, often associated with poor health, are characterized by absence of oscillation, random noise, or a very simple pattern of oscillation. This modeling approach can be applied to a diverse range of phenomena, including cardiovascular and brain activity, mood and thermal regulation, and social system stability. External system stressors such as disease, psychological stress, injury, or interpersonal conflict may perturb a system, yet simultaneously stimulate oscillatory processes and exercise control mechanisms. Resonance can occur in systems with negative feedback loops, causing high-amplitude oscillations at a single frequency. Resonance effects can be used to strengthen modulatory oscillations, but may obscure other information and control mechanisms, and weaken system stability. Positive as well as negative feedback loops are important for system function and stability. Examples are presented of oscillatory processes in heart rate variability, and regulation of autonomic, thermal, pancreatic and central nervous system processes, as well as in social/organizational systems such as marriages and business organizations. Resonance in negative feedback loops can help stimulate oscillations and exercise control reflexes, but also can deprive the system of important information. Empirical hypotheses derived from this approach are presented, including that moderate stress may enhance health and functioning.     

Insights into the genomic basis of niche specificity of Pseudomonas putida KT2440

A major challenge in microbiology is the elucidation of the genetic and ecophysiological basis of habitat specificity of microbes. Pseudomonas putida is a paradigm of a ubiquitous metabolically versatile soil bacterium. Strain KT2440, a safety strain that has become a laboratory workhorse worldwide, has been recently sequenced and its genome annotated. By drawing on both published information and on original in silico analysis of its genome, we address here the question of what genomic features of KT2440 could explain or are consistent with its ubiquity, metabolic versatility and adaptability. The genome of KT2440 exhibits combinations of features characteristic of terrestrial, rhizosphere and aquatic bacteria, which thrive in either copiotrophic or oligotrophic habitats, and suggests that P. putida has evolved and acquired functions that equip it to thrive in diverse, often inhospitable environments, either free-living, or in close association with plants. The high diversity of protein families encoded by its genome, the large number and variety of small aralogous families, insertion elements, repetitive extragenic palindromic sequences, as well as the mosaic structure of the genome (with many regions of 'atypical' composition) and the multiplicity of mobile elements, reflect a high functional diversity in P. putida and are indicative of its evolutionary trajectory and adaptation to the diverse habitats in which it thrives. The unusual wealth of determinants for high affinity nutrient acquisition systems, mono- and di-oxygenases, oxido-reductases, ferredoxins and cytochromes, dehydrogenases, sulfur metabolism proteins, for efflux pumps and glutathione-S-transfereases, and for the extensive array of extracytoplasmatic function sigma factors, regulators, and stress response systems, constitute the genomic basis for the exceptional nutritional versatility and opportunism of P. putida , its ubiquity in diverse soil, rhizosphere and aquatic systems, and its renowned tolerance of natural and anthropogenic stresses. This metabolic diversity is also the basis of the impressive evolutionary potential of KT2440, and its utility for the experimental design of novel pathways for the catabolism of organic, particularly aromatic, pollutants, and its potential for bioremediation of soils contaminated with such compounds as well as for its application in the production of high-added value compounds.     

The secret to a successful relationship: lasting chemistry between ascidians and their symbiotic bacteria

Bioactive secondary metabolites are common components of marine animals. In many cases, symbiotic bacteria, and not the animals themselves, synthesize the compounds. Among marine animals, ascidians are good models for understanding these symbioses. Ascidians often contain potently bioactive secondary metabolites as their major extractable components. Strong evidence shows that ~8% of the known secondary metabolites from ascidians are made by symbiotic bacteria, and indirect evidence implicates bacteria in the synthesis of many more. Far from being “secondary” to the animals, secondary metabolites are essential components of the interaction between host animals and their symbiotic bacteria. These interactions have complex underlying biology, but the chemistry is clearly ascidian species‐specific. The chemical interactions are ancient in at least some cases, and they are widespread among ascidians. Ascidians maintain secondary metabolic symbioses with bacteria that are phylogenetically diverse, indicating convergent solutions to obtaining secondary metabolites and reinforcing the importance of secondary metabolism in animal survival.     

Macro- and microevolution of bacteria in symbiotic systems

Using the examples of diverse interactions among prokaryotes and eukaryotes, the relationships between molecular and population mechanisms of evolution of symbiotic bacteria are addressed. Their circulation in host-environment systems activates microevolutionary factors that direct combinative or reductive genome evolution in facultative, ecologically obligatory, and genetically obligatory symbioses. It is shown on the example of symbiosis of rhizobia with legumes, that due to intensive systemic intra-genome rearrangements and horizontal gene transfer, two types of gene systems evolve in these bacteria: (1) controlling the pathogenesis-like processes of host recognition and penetration and (2) responsible for mutualistic interactions that are related to nitrogen fixation and its transfer to the host. The evolution of gene systems of type 1 is directed by individual (Darwinian, frequency-dependent) selection, which is responsible for gene-for-gene interactions between the partners. In the evolution of the type 2 systems, group (interdeme, kin) selection plays the key role, being responsible for the development of bacterial traits beneficial for the host. It is shown that evolution of mutualism can be described in terms of biological altruism, whose regularities are common for intraspecific and interspecific relationships. Macroevolutionary rearrangements of bacterial genomes result from the structural changes in their populations, wherein various selection modes are combined with stochastic processes (genetic drift, population waves) induced in the symbiotic systems.     

Genomic studies on the nature of species: adaptation and speciation in Mimulus

Evolutionary biology is in an exciting era, in which powerful genomic tools make the answers accessible to long‐standing questions about variation, adaptation and speciation. The availability of a suite of genomic resources, a shared knowledge base and a long history of study have made the phenotypically diverse plant genus Mimulus an important system for understanding ecological and evolutionary processes. An international Mimulus Research Meeting was held at Duke University in June 2014 to discuss developments in ecological and evolutionary genetic studies in Mimulus. Here, we report major recent discoveries presented at the meeting that use genomic approaches to advance our understanding of three major themes: the parallel genetic basis of adaptation; the ecological genomics of speciation; and the evolutionary significance of structural genetic variation. We also suggest future research directions for studies of Mimulus and highlight challenges faced when developing new ecological and evolutionary model systems.