Enzyme-enzyme interactions and their metabolic role

There are continuing reports on the existence of complexes of sequential metabolic enzymes. New techniques for their detection have been described and include affinity electrophoresis and the use of anti-idiotypic antibodies. Channeling of substrates has been reported for several systems as well as direct substrate transfer through dynamic enzyme associations. Kinetic parameters of metabolic control of organized systems have been formulated and tested in several systems. These recent results are expanding our understanding of metabolic processes and their control.     

OptORF: Optimal metabolic and regulatory perturbations for metabolic engineering of microbial strains

Background  

Computational modeling and analysis of metabolic networks has been successful in metabolic engineering of microbial strains for valuable biochemical production. Limitations of currently available computational methods for metabolic engineering are that they are often based on reaction deletions rather than gene deletions and do not consider the regulatory networks that control metabolism. Due to the presence of multi-functional enzymes and isozymes, computational designs based on reaction deletions can sometimes result in strategies that are genetically complicated or infeasible. Additionally, strains might not be able to grow initially due to regulatory restrictions. To overcome these limitations, we have developed a new approach (OptORF) for identifying metabolic engineering strategies based on gene deletion and overexpression.     

Yeast metabolic innovations emerged via expanded metabolic network and gene positive selection

Yeasts are known to have versatile metabolic traits, while how these metabolic traits have evolved has not been elucidated systematically. We performed integrative evolution analysis to investigate how genomic evolution determines trait generation by reconstructing genome‐scale metabolic models (GEMs) for 332 yeasts. These GEMs could comprehensively characterize trait diversity and predict enzyme functionality, thereby signifying that sequence‐level evolution has shaped reaction networks towards new metabolic functions. Strikingly, using GEMs, we can mechanistically map different evolutionary events, e.g. horizontal gene transfer and gene duplication, onto relevant subpathways to explain metabolic plasticity. This demonstrates that gene family expansion and enzyme promiscuity are prominent mechanisms for metabolic trait gains, while GEM simulations reveal that additional factors, such as gene loss from distant pathways, contribute to trait losses. Furthermore, our analysis could pinpoint to specific genes and pathways that have been under positive selection and relevant for the formulation of complex metabolic traits, i.e. thermotolerance and the Crabtree effect. Our findings illustrate how multidimensional evolution in both metabolic network structure and individual enzymes drives phenotypic variations.     

Adaptive evolution of metabolic pathways in Drosophila

The adaptive significance of enzyme variation has been of central interest in population genetics. Yet, how natural selection operates on enzymes in the larger context of biochemical pathways has not been broadly explored. A basic expectation is that natural selection on metabolic phenotypes will target enzymes that control metabolic flux, but how adaptive variation is distributed among enzymes in metabolic networks is poorly understood. Here, we use population genetic methods to identify enzymes responding to adaptive selection in the pathways of central metabolism in Drosophila melanogaster and Drosophila simulans. We report polymorphism and divergence data for 17 genes that encode enzymes of 5 metabolic pathways that converge at glucose-6-phosphate (G6P). Deviations from neutral expectations were observed at five loci. Of the 10 genes that encode the enzymes of glycolysis, only aldolase (Ald) deviated from neutrality. The other 4 genes that were inconsistent with neutral evolution (glucose-6-phosphate dehydrogenase [G6pd]), phosphoglucomutase [Pgm], trehalose-6-phosphate synthetase [Tps1], and glucose-6phosphatase [G6pase] encode G6P branch point enzymes that catalyze reactions at the entry point to the pentose-phosphate, glycogenic, trehalose synthesis, and gluconeogenic pathways. We reconcile these results with population genetics theory and existing arguments on metabolic regulation and propose that the incidence of adaptive selection in this system is related to the distribution of flux control. The data suggest that adaptive evolution of G6P branch point enzymes may have special significance in metabolic adaptation.     

Design of large metabolic responses. Constraints and sensitivity analysis

Metabolic control analysis (Kacser & Burns (1973). Symp. Soc. Exp. Biol.27, 65-104; Heinrich & Rapoport (1974). Eur. J. Biochem.42, 89-95) has been extensively used to describe the response of metabolic concentrations and fluxes to small (infinitesimal) changes in enzyme concentrations and effectors. Similarly, metabolic control design (Acerenza (1993). J. theor. Biol.165, 63-85) has been proposed to design small metabolic responses. These approaches have the limitation that they were not devised to deal with large (non-infinitesimal) responses. Here we develop a strategy to design large changes in the metabolic variables. The only assumption made is that, for all the parameter values under consideration, the system has a unique stable steady state. The procedure renders the kinetic parameters of the rate equations that when embedded in the metabolic network produce the pattern of large changes in the steady-state variables that we aim to design. Structural and kinetic constraints impose restrictions on the type of responses that could be designed. We show that these conditions can be transformed into the language of mean-sensitivity coefficients and, as a consequence, a sensitivity analysis of large metabolic responses can be performed after the system has been designed. The mean-sensitivity coefficients fulfil conservation and summation relationships that in the limit reduce to the well-known theorems for infinitesimal changes. Finally, it is shown that the same procedure that was used to design metabolic responses and analyse their sensitivity properties can also be used to determine the values of kinetic parameters of the rate laws operating "in situ".     

Alterations of metabolic genes and metabolites in cancer

Altered metabolic regulation has long been observed in human cancer and broadly used in the clinic for tumor detection. Two recent findings--the direct regulation of metabolic enzymes by frequently mutated cancer genes and frequent mutations of several metabolic enzymes themselves in cancer--have renewed interest in cancer metabolism. Supporting a causative role of altered metabolic enzymes in tumorigenesis, abnormal levels of several metabolites have been found to play a direct role in cancer development. The alteration of metabolic genes and metabolites offer not only new biomarkers for diagnosis and prognosis, but also potential new targets for cancer therapy.     

Increasing the flux in metabolic pathways: A metabolic control analysis perspective

The problems of engineering increased flux in metabolic pathways are analyzed in terms of the understanding provided by metabolic control analysis. Over-expression of a single enzyme is unlikely to be effective unless it is known to have a high flux control coefficient, which can be used as an approximate predictive tool. This is likely to rule out enzymes subject to feedback inhibition, because it transfers control downstream from the inhibited enzyme to the enzymes utilizing the feedback metabolite. Although abolishing feedback inhibition can restore flux control to an enzyme, it is also likely to cause large increases in the concentrations of metabolic intermediates. Simultaneous and coordinated over-expression of most of the enzymes in a pathway can, in principle, produce substantial flux increases without changes in metabolite levels, though technically it may be difficult to achieve. It is, however, closer to the method used by cells to change flux levels, where coordinated changes in the level of activity of pathway enzymes are the norm. Another option is to increase the demand for the pathway product, perhaps by increasing its rate of excretion or removal. Copyright 1998 John Wiley & Sons, Inc.     

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.     

Comparing methods for metabolic network analysis and an application to metabolic engineering

Bioinformatics tools have facilitated the reconstruction and analysis of cellular metabolism of various organisms based on information encoded in their genomes. Characterization of cellular metabolism is useful to understand the phenotypic capabilities of these organisms. It has been done quantitatively through the analysis of pathway operations. There are several in silico approaches for analyzing metabolic networks, including structural and stoichiometric analysis, metabolic flux analysis, metabolic control analysis, and several kinetic modeling based analyses. They can serve as a virtual laboratory to give insights into basic principles of cellular functions. This article summarizes the progress and advances in software and algorithm development for metabolic network analysis, along with their applications relevant to cellular physiology, and metabolic engineering with an emphasis on microbial strain optimization. Moreover, it provides a detailed comparative analysis of existing approaches under different categories.     

Update on olfactory mucosal metabolic enzymes: age-related changes and N-acetyltransferase activities

We have expanded previous observations on olfactory metabolic enzymes by examining the content of various metabolic enzymes in the olfactory mucosa of the male Long-Evans rat at different ages. Age-related changes in metabolic enzyme content may be related to changes in susceptibility to toxicants with age and may also contribute to altered odorant perception in the elderly. While some enzymes did not vary over the age range examined, decreases in the microsomal content of other enzymes were observed. While mRNA for acetyltransferase enzymes has previously been described in olfactory mucosa, the markedly higher activity of olfactory acetyltransferases compared to liver had not previously been described. Acetyltransferases are important in the metabolism of drugs and toxicants that are aromatic amine derivatives and may contribute to the bioactivation of rodent olfactory mucosal carcinogens such as 2,6-dimethylaniline and alachlor. These studies show that the olfactory mucosa varies in its metabolic capacity with age, and characterize another class of metabolic enzymes in the olfactory mucosa, both of which may impact significantly on responses to toxicants and therapeutic agents in the nasal cavity.     

Protein design in metabolic engineering and synthetic biology

Starting from experimental data on sequence, structure or biochemical properties of enzymes, protein design seeks to construct enzymes with desired activity, stability, specificity and selectivity. Two strategies are widely used to investigate sequence-structure-function relationships: statistical methods to analyse protein families or mutant libraries, and molecular modelling methods to study proteins and their interaction with ligands or substrates. On the basis of these methods, protein design has been successfully applied to fine-tune bottleneck enzymes in metabolic engineering and to design enzymes with new substrate spectra and new functions. However, constructing efficient metabolic pathways by integrating individual enzymes into a complex system is challenging. The field of synthetic biology is still in its infancy, but promising results have demonstrated the feasibility and usefulness of the concept.     

Multi-criteria optimization of regulation in metabolic networks

Determining the regulation of metabolic networks at genome scale is a hard task. It has been hypothesized that biochemical pathways and metabolic networks might have undergone an evolutionary process of optimization with respect to several criteria over time. In this contribution, a multi-criteria approach has been used to optimize parameters for the allosteric regulation of enzymes in a model of a metabolic substrate-cycle. This has been carried out by calculating the Pareto set of optimal solutions according to two objectives: the proper direction of flux in a metabolic cycle and the energetic cost of applying the set of parameters. Different Pareto fronts have been calculated for eight different "environments" (specific time courses of end product concentrations). For each resulting front the so-called knee point is identified, which can be considered a preferred trade-off solution. Interestingly, the optimal control parameters corresponding to each of these points also lead to optimal behaviour in all the other environments. By calculating the average of the different parameter sets for the knee solutions more frequently found, a final and optimal consensus set of parameters can be obtained, which is an indication on the existence of a universal regulation mechanism for this system.The implications from such a universal regulatory switch are discussed in the framework of large metabolic networks.     

Topological analysis of metabolic control

A topological approach is presented for the analysis of control and regulation in metabolic pathways. In this approach, the control structure of a metabolic pathway is represented by a weighted directed graph. From an inspection of the topology of the graph, the control coefficients of the enzymes are evaluated in a heuristic manner in terms of the enzyme elasticities. The major advantage of the topological approach is that it provides a visual framework for (1) calculating the control coefficients of the enzymes, (2) analyzing the cause-effect relationships of the individual enzymes, (3) assessing the relative importance of the enzymes in metabolic regulation, and (4) simplifying the structure of a given pathway, from a regulatory viewpoint. Results are obtained for (a) an unbranched pathway in the absence of feedback the feedforward regulation and (b) an unbranched pathway with feedback inhibition. Our formulation is based on the metabolic control theory of Kacser and Burns (1973) and Heinrich and Rapoport (1974).     

Diverse strategies adopted by nature for regulating purine biosynthesis via fine-tuning of purine metabolic enzymes

Purine nucleotides, generated by de novo synthesis and salvage pathways, are essential for metabolism and act as building blocks of genetic material. To avoid an imbalance in the nucleotide pool, nature has devised several strategies to regulate/tune the catalytic performance of key purine metabolic enzymes. Here, we discuss some recent examples, such as stress-regulating alarmones that bind to select pathway enzymes, huge ensembles like dynamic metabolons and self-assembled filaments that highlight the layered fine-control prevalent in the purine metabolic pathway to fulfill requisite purine demands. Examples of enzymes that turn-on only under allosteric control, are regulated via long-distance communication that facilitates transient conduits have additionally been explored.     

A 'top-down' approach to the determination of control coefficients in metabolic control theory

A new approach to the determination of flux and concentration control coefficients in metabolic pathways is outlined. Linear pathways are conceptually divided in two around an intermediate metabolite (or group or metabolites) and the control coefficients of the two parts are derived from the elasticity coefficients of the two parts to the intermediate. Branched pathways are treated similarly, the control coefficients of the branches being derived either from the elasticities of the branches to their common intermediate or from the relative flux changes of the branches. Repeating this analysis around other intermediates in the pathway allows the control coefficients of smaller and smaller groups of enzymes to be determined. In complex systems this approach to describing control may have several advantages over determining the control coefficients of individual enzymes and is a potentially useful complementary approach.     

Subtleties in control by metabolic channelling and enzyme organization

Because of its importance to cell function, the free-energy metabolism of the living cell is subtly and homeostatically controlled. Metabolic control analysis enables a quantitative determination of what controls the relevant fluxes. However, the original metabolic control analysis was developed for idealized metabolic systems, which were assumed to lack enzyme-enzyme association and direct metabolite transfer between enzymes (channelling). We here review the recently developed molecular control analysis, which makes it possible to study non-ideal (channelled, organized) systems quantitatively in terms of what controls the fluxes, concentrations, and transit times. We show that in real, non-ideal pathways, the central control laws, such as the summation theorem for flux control, are richer than in ideal systems: the sum of the control of the enzymes participating in a non-ideal pathway may well exceed one (the number expected in the ideal pathways), but may also drop to values below one. Precise expressions indicate how total control is determined by non-ideal phenomena such as ternary complex formation (two enzymes, one metabolite), and enzyme sequestration. The bacterial phosphotransferase system (PTS), which catalyses the uptake and concomitant phosphorylation of glucose (and also regulates catabolite repression) is analyzed as an experimental example of a non-ideal pathway. Here, the phosphoryl group is channelled between enzymes, which could increase the sum of the enzyme control coefficients to two, whereas the formation of ternary complexes could decrease the sum of the enzyme control coefficients to below one. Experimental studies have recently confirmed this identification, as well as theoretically predicted values for the total control. Macromolecular crowding was shown to be a major candidate for the factor that modulates the non-ideal behaviour of the PTS pathway and the sum of the enzyme control coefficients.     

The reconstruction and analysis of tissue specific human metabolic networks

Human tissues have distinct biological functions. Many proteins/enzymes are known to be expressed only in specific tissues and therefore the metabolic networks in various tissues are different. Though high quality global human metabolic networks and metabolic networks for certain tissues such as liver have already been studied, a systematic study of tissue specific metabolic networks for all main tissues is still missing. In this work, we reconstruct the tissue specific metabolic networks for 15 main tissues in human based on the previously reconstructed Edinburgh Human Metabolic Network (EHMN). The tissue information is firstly obtained for enzymes from Human Protein Reference Database (HPRD) and UniprotKB databases and transfers to reactions through the enzyme-reaction relationships in EHMN. As our knowledge of tissue distribution of proteins is still very limited, we replenish the tissue information of the metabolic network based on network connectivity analysis and thorough examination of the literature. Finally, about 80% of proteins and reactions in EHMN are determined to be in at least one of the 15 tissues. To validate the quality of the tissue specific network, the brain specific metabolic network is taken as an example for functional module analysis and the results reveal that the function of the brain metabolic network is closely related with its function as the centre of the human nervous system. The tissue specific human metabolic networks are available at .     

PPAR家族及其与代谢综合征的关系

过氧化物酶体增殖物激活受体(peroxisome proliferator-activated receptors,PPARs)是配体激活的转录因子核受体超家族成员之一。目前已知有三种亚型：PPARα、-β／δ和-γ。它们在脂肪生成、脂质代谢、胰岛素敏感性、炎症和血压调节中起着关键作用,因而近年来倍受关注。越来越多的研究表明,PPARs与代谢综合征,包括胰岛素抵抗、糖耐量受损、2型糖尿病、肥胖、高脂血症、高血压病、动脉粥样硬化和蛋白尿之间存在因果关系。重要的是,PPARα的激动剂如贝丁酸类降脂药(Fibrate)和PPARγ的激动剂如噻唑烷二酮(Thiazolidinedione,TZD)均已被证实有改善代谢综合征的作用。此外,三种PPAR亚型在2型糖尿病及糖尿病肾病的发展中均有重要作用。不断增加的证据提示,PPARs有可能成为代谢综合征及其相关并发症的潜在治疗靶点。本文将就PPARs的生物学活性、配体选择性和生理学功能作一综述,并对其在代谢综合征发病机制中的作用和PPAR配体对2型糖尿病的治疗效用进行重点讨论。