Two approaches for metabolic pathway analysis?

Metabolic pathway analysis is becoming increasingly important for assessing inherent network properties in (reconstructed) biochemical reaction networks. Of the two most promising concepts for pathway analysis, one relies on elementary flux modes and the other on extreme pathways. These concepts are closely related because extreme pathways are a subset of elementary modes. Here, the common features, differences and applicability of these concepts are discussed. Assessing metabolic systems by the set of extreme pathways can, in general, give misleading results owing to the exclusion of possibly important routes. However, in certain network topologies, the sets of elementary modes and extreme pathways coincide. This is quite often the case in realistic applications. In our opinion, the unification of both approaches into one common framework for metabolic pathway analysis is necessary and achievable.     

Choke point analysis of metabolic pathways in E.histolytica: a computational approach for drug target identification

With the Entamoeba genome essentially complete, the organism can be studied from a whole genome standpoint. The understanding of cellular mechanisms and interactions between cellular components is instrumental to the development of new effective drugs and vaccines. Metabolic pathway analysis is becoming increasingly important for assessing inherent network properties in reconstructed biochemical reaction networks. Metabolic pathways illustrate how proteins work in concert to produce cellular compounds or to transmit information at different levels. Identification of drug targets in E. histolytica through metabolic pathway analysis promises to be a novel approach in this direction. This article focuses on the identification of drug targets by subjecting the Entamoeba genome to BLAST with the e-value inclusion threshold set to 0.005 and choke point analysis. A total of 86.9 percent of proposed drug targets with biological evidence are chokepoint reactions in Entamoeba genome database.     

Experimental and mathematical approaches to modeling plant metabolic networks

To support their sessile and autotrophic lifestyle higher plants have evolved elaborate networks of metabolic pathways. Dynamic changes in these metabolic networks are among the developmental forces underlying the functional differentiation of organs, tissues and specialized cell types. They are also important in the various interactions of a plant with its environment. Further complexity is added by the extensive compartmentation of the various interconnected metabolic pathways in plants. Thus, although being used widely for assessing the control of metabolic flux in microbes, mathematical modeling approaches that require steady-state approximations are of limited utility for understanding complex plant metabolic networks. However, considerable progress has been made when manageable metabolic subsystems were studied. In this article, we will explain in general terms and using simple examples the concepts underlying stoichiometric modeling (metabolic flux analysis and metabolic pathway analysis) and kinetic approaches to modeling (including metabolic control analysis as a special case). Selected studies demonstrating the prospects of these approaches, or combinations of them, for understanding the control of flux through particular plant pathways are discussed. We argue that iterative cycles of (dry) mathematical modeling and (wet) laboratory testing will become increasingly important for simulating the distribution of flux in plant metabolic networks and deriving rational experimental designs for metabolic engineering efforts.     

Control, regulation and thermodynamics of free-energy transduction

The quantitative formalism called Metabolic Control Theory makes it possible to be precise in discussions of metabolic control. To illustrate this, I will mention 2 experimental systems where free energy is converted from one form to another, i.e., bacteriorhodopsin liposomes and mitochondrial oxidative phosphorylation. More specifically I shall discuss how the distribution of the control of fluxes, concentrations and potentials, among the various enzymes (catalysts) in these systems has been measured and how this distribution can be understood in terms of the enzyme properties. From the outset, Metabolic Control Theory was valid for branched metabolic pathways with non-linear kinetics. Yet, it seemed to be limited to metabolic pathways without enzyme-enzyme interactions and to steady states. It is now clear that these limitations were apparent only and recent extensions to Metabolic Control Theory deal explicitly with enzyme-enzyme interaction and with transient-time analysis. Other limitations are inherent. For instance, Metabolic Control Theory pays for its clarity and exactness by being limited to small modulations. Mosaic Non Equilibrium Thermodynamics and Biochemical System Analysis are formalisms that deal with larger changes, at the cost of accuracy and exactness.     

Healthy and unhealthy plants: The effect of stress on the metabolism of Brassicaceae

Brassicaceae plants are one of the most popular vegetables consumed all over the world and considered to be a good source of bioactive phytochemicals. Additionally, Brassica species and varieties are increasingly becoming a research model in plant science, as a consequence of the importance of their primary and secondary metabolites. Plant interaction with environmental stress factors including animals and insects herbivory, pathogens, metal ions, light, among others, is known to lead to the activation of various defense mechanisms resulting in a qualitative and/or quantitative change in plant metabolite production. Pre-harvest and/or post-harvest conditions are also known to affect this, since plants produce signaling molecules (e.g. salicylic acid, jasmonic acid, etc.) that cause a direct or indirect activation of metabolic pathways. That ultimately affects the production of phytochemicals, such as carbohydrates (sucrose and glucose), amino acids, phenolics (phenylpropanoids and flavonoids) and glucosinolates. These phytochemicals have diverse applications due to their antimicrobial, antioxidant and anti-carcinogenic properties, but on the other hand these compounds or their breakdown products can act as anti-nutritional factors in diet. In this review we report a wide range of the stress-induced metabolic responses in the Brassica plants commonly used for human consumption.     

Proteomics: a link between genomics,genetics and physiology

Thanks to spectacular advances in the techniques for identifying proteins separated by two-dimensional electrophoresis and in methods for large-scale analysis of proteome variations, proteomics is becoming an essential methodology in various fields of plant biology. In the study of pleiotropic effects of mutants and in the analysis of responses to hormones and to environmental changes, the identification of involved metabolic pathways can be deduced from the function of affected proteins. In molecular quantitative genetics, proteomics can be used to map translated genes and loci controlling their expression, which can be used to identify proteins accounting for the variation of complex phenotypic traits. Linking gene expression to cell metabolism on the one hand and to genetic maps on the other, proteomics is a central tool for functional genomics.     

Genetic engineering of polyamine and carbohydrate metabolism for osmotic stress tolerance in higher plants

Plant growth and productivity are greatly affected by various stress factors. The molecular mechanisms of stress tolerance in plant species have been well established. Metabolic pathways involving the synthesis of metabolites such as polyamines, carbohydrates, proline and glycine betaine have been shown to be associated with stress tolerance. Introduction of the stress-induced genes involved in these pathways from tolerant species to sensitive plants seems to be a promising approach to confer stress tolerance in plants. In cases where single gene is not enough to confer tolerance, metabolic engineering necessitates the introduction of multiple transgenes in plants.     

Design principles and operating principles: the yin and yang of optimal functioning

Metabolic engineering has as a goal the improvement of yield of desired products from microorganisms and cell lines. This goal has traditionally been approached with experimental biotechnological methods, but it is becoming increasingly popular to precede the experimental phase by a mathematical modeling step that allows objective pre-screening of possible improvement strategies. The models are either linear and represent the stoichiometry and flux distribution in pathways or they are non-linear and account for the full kinetic behavior of the pathway, which is often significantly effected by regulatory signals. Linear flux analysis is simpler and requires less input information than a full kinetic analysis, and the question arises whether the consideration of non-linearities is really necessary for devising optimal strategies for yield improvements. The article analyzes this question with a generic, representative pathway. It shows that flux split ratios, which are the key criterion for linear flux analysis, are essentially sufficient for unregulated, but not for regulated branch points. The interrelationships between regulatory design on one hand and optimal patterns of operation on the other suggest the investigation of operating principles that complement design principles, like a user's manual complements the hardwiring of electronic equipment.     

Metabolic engineering of plants for alkaloid production.

Alkaloids purified from plants provide many pharmacologically active compounds, including leading chemotherapy drugs. As is generally true of secondary metabolites, overall productivity is low, making commercial production expensive. Alternative production methods remain impractical, leaving the plant as the best source for these valuable chemicals. Recently, significant progress in characterizing the biosynthetic pathways leading to various alkaloids has been made, and a number of relevant genes have been cloned. Metabolic engineering employing such genes provides a promising technology for improved productivity in plant cell cultures, plant tissue cultures, or intact plants. In exploring solutions though, metabolic engineers must be careful to recognize the limitations inherent in designing plant systems.     

Plant cytochrome P450s: nomenclature and involvement in natural product biosynthesis

Cytochrome P450s constitute the largest family of enzymatic proteins in plants acting on various endogenous and xenobiotic molecules. They are monooxygenases that insert one oxygen atom into inert hydrophobic molecules to make them more reactive and hydro-soluble. Besides for physiological functions, the extremely versatile cytochrome P450 biocatalysts are highly demanded in the fields of biotechnology, medicine, and phytoremediation. The nature of reactions catalyzed by P450s is irreversible, which makes these enzymes attractions in the evolution of plant metabolic pathways. P450s are prime targets in metabolic engineering approaches for improving plant defense against insects and pathogens and for production of secondary metabolites such as the anti-neoplastic drugs taxol or indole alkaloids. The emerging examples of P450 involvement in natural product synthesis in traditional medicinal plant species are becoming increasingly interesting, as they provide new alternatives to modern medicines. In view of the divergent roles of P450s, we review their classification and nomenclature, functions and evolution, role in biosynthesis of secondary metabolites, and use as tools in pharmacology.     

Systems-level analysis of genome-scalein silico metabolic models using MetaFluxNet

The systems-level analysis of microbes with myriad of heterologous data generated by omics technologies has been applied to improve our understanding of cellular function and physiology and consequently to enhance production of various bioproducts. At the heart of this revolution residesin silico genome-scale metabolic model. In order to fully exploit the power of genome-scale model, a systematic approach employing user-friendly software is required. Metabolic flux analysis of genome-scale metabolic network is becoming widely employed to quantify the flux distribution and validate model-driven hypotheses. Here we describe the development of an upgraded MetaFluxNet which allows (1) construction of metabolic models connected to metabolic databases, (2) calculation of fluxes by metabolic flux analysis, (3) comparative flux analysis with flux-profile visualization, (4) the use of metabolic flux analysis markup language to enable models to be exchanged efficiently, and (5) the exporting of data from constraints-based flux analysis into various formats. MetaFluxNet also allows cellular physiology to be predicted and strategies for strain improvement to be developed from genome-based information on flux distributions. This integrated software environment promises to enhance our understanding on metabolic network at a whole organism level and to establish novel strategies for improving the properties of organisms for various biotechnological applications.     

Metabolic tinker: an online tool for guiding the design of synthetic metabolic pathways

One of the primary aims of synthetic biology is to (re)design metabolic pathways towards the production of desired chemicals. The fast pace of developments in molecular biology increasingly makes it possible to experimentally redesign existing pathways and implement de novo ones in microbes or using in vitro platforms. For such experimental studies, the bottleneck is shifting from implementation of pathways towards their initial design. Here, we present an online tool called ‘Metabolic Tinker’, which aims to guide the design of synthetic metabolic pathways between any two desired compounds. Given two user-defined ‘target’ and ‘source’ compounds, Metabolic Tinker searches for thermodynamically feasible paths in the entire known metabolic universe using a tailored heuristic search strategy. Compared with similar graph-based search tools, Metabolic Tinker returns a larger number of possible paths owing to its broad search base and fast heuristic, and provides for the first time thermodynamic feasibility information for the discovered paths. Metabolic Tinker is available as a web service at http://osslab.ex.ac.uk/tinker.aspx. The same website also provides the source code for Metabolic Tinker, allowing it to be developed further or run on personal machines for specific applications.     

Green pathways: Metabolic network analysis of plant systems

Metabolic engineering of plants with enhanced crop yield and value-added compositional traits is particularly challenging as they probably exhibit the highest metabolic network complexity of all living organisms. Therefore, approaches of plant metabolic network analysis, which can provide systems-level understanding of plant physiology, appear valuable as guidance for plant metabolic engineers. Strongly supported by the sequencing of plant genomes, a number of different experimental and computational methods have emerged in recent years to study plant systems at various levels: from heterotrophic cell cultures to autotrophic entire plants. The present review presents a state-of-the-art toolbox for plant metabolic network analysis. Among the described approaches are different in silico modeling techniques, including flux balance analysis, elementary flux mode analysis and kinetic flux profiling, as well as different variants of experiments with plant systems which use radioactive and stable isotopes to determine in vivo plant metabolic fluxes. The fundamental principles of these techniques, the required data input and the obtained flux information are enriched by technical advices, specific to plants. In addition, pioneering and high-impacting findings of plant metabolic network analysis highlight the potential of the field.     

Metabolic effects of CO2 anaesthesia in Drosophila melanogaster

Immobilization of insects is necessary for various experimental purposes, and CO₂ exposure remains the most popular anaesthetic method in entomological research. A number of negative side effects of CO₂ anaesthesia have been reported, but CO₂ probably brings about metabolic modifications that are poorly known. In this work, we used GC/MS-based metabolic fingerprinting to assess the effect of CO₂ anaesthesia in Drosophila melanogaster adults. We analysed metabolic variation of flies submitted to acute CO₂ exposure and assessed the temporal metabolic changes during short- and long-term recovery. We found that D. melanogaster metabotypes were significantly affected by the anaesthetic treatment. Metabolic changes caused by acute CO₂ exposure were still manifested after 14 h of recovery. However, we found no evidence of metabolic alterations when a long recovery period was allowed (more than 24 h). This study points to some metabolic pathways altered during CO₂ anaesthesia (e.g. energetic metabolism). Evidence of short-term metabolic changes indicates that CO₂ anaesthesia should be used with utmost caution in physiological studies when a short recovery is allowed. In spite of this, CO₂ treatment seems to be an acceptable anaesthetic method provided that a long recovery period is allowed (more than 24 h).     

Metabolic control analysis: biological applications and insights

Metabolic control analysis provides a robust mathematical and theoretical framework for describing metabolic and signaling pathways and networks, and for quantifying the controls over these processes. Its application has already shed light on some of the principles underlying the regulation of metabolic pathways, and it is well suited to the analysis of the types of data emerging from genomic studies.     

Plant biotechnology and breeding: allied for years to come

Plant metabolic engineering is lagging behind other kinds of genetic manipulation of plants. Creating metabolic pathways or improving their yields requires a better understanding of plant metabolism and of its regulation. Metabolic Control Analysis provides an interpretation of experimental failures and a guide for manipulators. It suggests also that there might be intrinsic limits to raising yields in already abundant products. At present, these limits can be dealt with more effectively by plant breeding.     

肥胖诱导的骨骼肌萎缩机制研究进展

骨骼肌是人体氨基酸和蛋白质的主要贮存、代谢库,其正常功能和代谢过程受到多种病理因素的影响。骨骼肌萎缩发生于骨骼肌稳态严重失衡状态下,对患者生活和社会医疗造成了沉重负担。近年来,由于世界肥胖人群数量激增,肥胖诱导的骨骼肌萎缩正日益成为公共卫生的严峻挑战之一。肥胖诱导的骨骼肌萎缩过程涉及多种信号分子或通路的改变,如泛素蛋白酶系统、自噬溶酶体系统、胰岛素/IGF1-PI3K-Akt、肌肉生长抑制素、白细胞介素-6、肿瘤坏死因子等;这些信号分子或通路在肥胖状态下被激活或抑制后,可共同影响蛋白质合成/分解平衡进而造成骨骼肌萎缩。基于上述信号分子或通路,系统总结并讨论了肥胖诱导的骨骼肌萎缩机制,以期为寻找缓解/治疗肥胖诱导的肌萎缩靶点和进一步开发利用天然植物化学物提供理论依据。