Plant P450s as versatile drivers for evolution of species-specific chemical diversity

The irreversible nature of reactions catalysed by P450s makes these enzymes landmarks in the evolution of plant metabolic pathways. Founding members of P450 families are often associated with general (i.e. primary) metabolic pathways, restricted to single copy or very few representatives, indicative of purifying selection. Recruitment of those and subsequent blooms into multi-member gene families generates genetic raw material for functional diversification, which is an inherent characteristic of specialized (i.e. secondary) metabolism. However, a growing number of highly specialized P450s from not only the CYP71 clan indicate substantial contribution of convergent and divergent evolution to the observed general and specialized metabolite diversity. We will discuss examples of how the genetic and functional diversification of plant P450s drives chemical diversity in light of plant evolution. Even though it is difficult to predict the function or substrate of a P450 based on sequence similarity, grouping with a family or subfamily in phylogenetic trees can indicate association with metabolism of particular classes of compounds. Examples will be given that focus on multi-member gene families of P450s involved in the metabolic routes of four classes of specialized metabolites: cyanogenic glucosides, glucosinolates, mono- to triterpenoids and phenylpropanoids.     

代谢基因工程提高作物产量的分子靶标

应用基因工程技术对植物细胞内的代谢途径进行遗传修饰,已成功地使细胞代谢发生改变或合成新的化合物。光合作用,淀粉合成,氮素同化和水分利用等是形成作物产量的基础代谢。对这些代谢途径中的关键步骤和靶分子进行基因修饰以提高作物产量的研究已取得长足的进展,并正在发展成为提高作物产量的新途径。本文着重论述应用代谢基因工程提高作物产量的技术策略,研究现状,存在的问题,所面临的挑战和应用前景。     

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.     

Metabolic rates,genetic constraints,and the evolution of endothermy

The metabolic distinction between endotherms and ectotherms is profound. Whereas the ecology of metabolic rates is well studied, how endotherms evolved from their ectothermic ancestors remains unclear. The aerobic capacity model postulates that a genetic constraint between resting and maximal metabolism was essential for the evolution of endothermy. Using the multivariate breeders’ equation, I illustrate how the (i) relative sizes of genetic variances and (ii) relative magnitudes of selection gradients for resting and maximal metabolism affect the genetic correlation needed for endothermy to have evolved via a correlated response to selection. If genetic variances in existing populations are representative of ancestral conditions, then the aerobic capacity model is viable even if the genetic correlation was modest. The analyses reveal how contemporary data on selection and genetic architecture can be used to test hypotheses about the evolution of endothermy, and they show the benefits of explicitly linking physiology and quantitative genetic theory.     

昼夜节律钟调控代谢的研究进展

生理和行为的昼夜节律性调控对健康生活是必需的。越来越多的流行病学和遗传学证据显示昼夜节律的破坏与代谢紊乱性疾病相关联。在分子水平上,昼夜节律受到时钟蛋白组成的转录一翻译负反馈环的调控。时钟蛋白通过以下两种途径调节代谢：首先,时钟蛋白作为转录因子直接调节一些代谢关键步骤的限速酶和代谢相关核受体的表达,其次作为代谢相关核受体的辅调节因子来激活或抑制其转录活性。虽然时钟蛋白对代谢途径的调节导致代谢物水平呈昼夜节律振荡,但是产生的代谢物反过来又可以影响昼夜节律钟基因的表达,进而影响昼夜节律钟。深入研究昼夜节律钟与代谢的交互调节可能为治疗某些代谢紊乱性疾病提供新的治疗方案。     

植物次生代谢物途径及其研究进展

植物次生代谢是植物在长期进化过程中与环境相互作用的结果,由初生代谢派生。萜类、生物碱类、苯丙烷类为植物次生代谢物的主要类型,其代谢途径多以代谢频道形式存在,具有种属、生长发育期等特异性。从植物次生代谢物的分类、代谢途径及代谢调控基因工程等方面展开论述,重点介绍了次生代谢物的生物合成途径,以及利用基因工程等技术对植物次生代谢途径进行遗传改良等方面的研究进展,为全面认识植物代谢网络、合理定位次生代谢及其关键酶、促进野生植物资源可持续利用等提供理论依据。     

The Divergence and Natural Selection of Autocatalytic Primordial Metabolic Systems

The diversity of the central metabolism of modern organisms is caused by the existence of a few metabolic modules, combination of which produces multiple metabolic pathways. This paper analyzes biomimetically reconstructed coupled autocatalytic cycles as the basis of ancestral metabolic systems. The mechanism for natural selection and evolution in autocatalytic chemical systems may be affected by natural homeostatic parameters such as ambient chemical potentials, temperature, and pressure. Competition between separate parts of an autocatalytic network with positive-plus-negative feedback resulted in the formation of primordial autotrophic, mixotrophic, and heterotrophic metabolic systems. This work examined the last common ancestor of a set of coupled metabolic cycles in a population of protocells. Physical-chemical properties of these cycles determined the main principles of natural selection for the ancestral Bacteria and Archaea taxa.     

Theory for the systemic definition of metabolic pathways and their use in interpreting metabolic function from a pathway-oriented perspective

Cellular metabolism is most often described and interpreted in terms of the biochemical reactions that make up the metabolic network. Genomics is providing near complete information regarding the genes/gene products participating in cellular metabolism for a growing number of organisms. As the true functional units of metabolic systems are its pathways, the time has arrived to define metabolic pathways in the context of whole-cell metabolism for the analysis of the structural design and capabilities of the metabolic network. In this study, we present the theoretical foundations for the identification of the unique set of systemically independent biochemical pathways, termed extreme pathways, based on system stochiometry and limited thermodynamics. These pathways represent the edges of the steady-state flux cone derived from convex analysis, and they can be used to represent any flux distribution achievable by the metabolic network. An algorithm is presented to determine the set of extreme pathways for a system of any complexity and a classification scheme is introduced for the characterization of these pathways. The property of systemic independence is discussed along with its implications for issues related to metabolic regulation and the evolution of cellular metabolic networks. The underlying pathway structure that is determined from the set of extreme pathways now provides us with the ability to analyse, interpret, and perhaps predict metabolic function from a pathway-based perspective in addition to the traditional reaction-based perspective. The algorithm and classification scheme developed can be used to describe the pathway structure in annotated genomes to explore the capabilities of an organism.     

The tragedy of the commons in microbial populations: insights from theoretical, comparative and experimental studies

First principles of thermodynamics imply that metabolic pathways are faced with a trade-off between the rate and yield of ATP production. Simple evolutionary models argue that this trade-off generates a fundamental social conflict in microbial populations: average fitness in a population is highest if all individuals exploit common resources efficiently, but individual reproductive rate is maximized by consuming common resources at the highest possible rate, a scenario known as the tragedy of the commons. In this paper, I review studies that have addressed two key questions: What is the evidence that the rate-yield trade-off is an evolutionary constraint on metabolic pathways? And, if so, what determines evolutionary outcome of the conflicts generated by this trade-off? Comparative studies and microbial experiments provide evidence that the rate-yield trade-off is an evolutionary constraint that is driven by thermodynamic constraints that are common to all metabolic pathways and pathway-specific constraints that reflect the evolutionary history of populations. Microbial selection experiments show that the evolutionary consequences of this trade-off depend on both kin selection and biochemical constraints. In well-mixed populations with low relatedness, genotypes with rapid and efficient metabolism can coexist as a result of negative frequency-dependent selection generated by density-dependent biochemical costs of rapid metabolism. Kin selection can promote the maintenance of efficient metabolism in structured populations with high relatedness by ensuring that genotypes with efficient metabolic pathways gain an indirect fitness benefit from their competitive restraint. I conclude by suggesting avenues for future research and by discussing the broader implications of this work for microbial social evolution.     

The tragedy of the commons in microbial populations: insights from theoretical, comparative and experimental studies

First principles of thermodynamics imply that metabolic pathways are faced with a trade-off between the rate and yield of ATP production. Simple evolutionary models argue that this trade-off generates a fundamental social conflict in microbial populations: average fitness in a population is highest if all individuals exploit common resources efficiently, but individual reproductive rate is maximized by consuming common resources at the highest possible rate, a scenario known as the tragedy of the commons. In this paper, I review studies that have addressed two key questions: What is the evidence that the rate-yield trade-off is an evolutionary constraint on metabolic pathways? And, if so, what determines evolutionary outcome of the conflicts generated by this trade-off? Comparative studies and microbial experiments provide evidence that the rate-yield trade-off is an evolutionary constraint that is driven by thermodynamic constraints that are common to all metabolic pathways and pathway-specific constraints that reflect the evolutionary history of populations. Microbial selection experiments show that the evolutionary consequences of this trade-off depend on both kin selection and biochemical constraints. In well-mixed populations with low relatedness, genotypes with rapid and efficient metabolism can coexist as a result of negative frequency-dependent selection generated by density-dependent biochemical costs of rapid metabolism. Kin selection can promote the maintenance of efficient metabolism in structured populations with high relatedness by ensuring that genotypes with efficient metabolic pathways gain an indirect fitness benefit from their competitive restraint. I conclude by suggesting avenues for future research and by discussing the broader implications of this work for microbial social evolution.     

The cost of enzyme synthesis in the genetics of energy balance and physiological performance

The study of metabolism has traditionally focused upon factors that influence metabolic rate, at levels of both the metabolic pathway and the whole organism. This paper focuses on the cost, and thereby the efficiency, of metabolic processes. The genotype-dependent cost of enzyme turnover is proposed as a biochemical genetic mechanism for relating genetic variation at single genes to phenotypic variation in quantitative traits of energy metabolism. Decreased costs of maintenance metabolism can accompany artificial selection for increased production (e.g. growth, reproduction, etc.) and lower maintenance is correlated with multiple locus heterozygosity in outbred populations. In both cases, high production has been associated with lower rates of protein turnover. Several factors influence the ATP-equivalent cost of enzyme turnover. These factors are used to calculate the cost of turnover for a single enzyme. This cost can conservatively constitute up to several percent of the total daily mass-specific energy demands of maintenance metabolism. Genetic variants of an enzyme can differ in the cost of turnover. These differences can constitute the basis for metabolic changes associated with artificial selection for production and the metabolic differences that are associated with individual levels of heterozygosity. The metabolic and evolutionary significance of genotype-dependent turnover costs is a function of individual energy balance. The strength of selection against increases in cost will be an inverse function of individual energy balance and is therefore influenced by both environmental and genetic factors.     

Metabolic investigation in psychiatric disorders

A multiplicity of theories have been proposed over the years that aim to conceptualize the pathophysiology of neuropsychiatric disorders, including impaired neurotransmission, viral infections, genetic mutation, energy metabolism deficiency, excitotoxicity, oxidative stress, and others. It is likely that complex disorders such as schizophrenia, bipolar disorder, and major depression are associated with multiple etiologies and pathogenetic mechanisms. In light of the interwoven biochemistry of human organs, identifying a network of multiple interacting biochemical pathways that account for the constellation of clinical and biological features would advance our understanding of these disorders. One such approach is to evaluate simultaneously the multiple metabolites in order to uncover the dynamic relations in the relevant biochemical systems. These metabolites are a group of low-molecular-weight, redox-active compounds, such as antioxidants, amino acids, catecholamines vitamins, lipids, and nucleotides, which reflect the metabolic processes, including anabolism and catabolism as well as other related cellular processes (e.g., signal transduction, regulation, detoxification, etc.). Such an analytic approach has the potential to yield valuable insights into the likely complex pathophysiological mechanisms that affect multiple metabolic pathways and thereby offer multiple windows of therapeutic opportunities.     

Application of systems biology for bioprocess development

Random mutagenesis or genetic modification of an organism without consideration of its consequences to the entire system might cause unwanted changes in cellular metabolism. Systems metabolic engineering thus aims to develop strains by performing metabolic engineering within a systems biology framework, in which entire cellular networks are optimized and fermentation and downstream processes are considered at early stages. Thus, regulatory, metabolic and other cellular networks are engineered in an integrated manner. Here, we review the applications of systems biology for the development of strains and bioprocesses by means of several successful examples and, furthermore, discuss future prospects.     

超嗜热古菌整合性遗传元件的研究进展

细菌中整合性遗传元件与DNA修饰和防御、毒力因子传播以及次级代谢等生理功能存在关联,而相关研究在超嗜热古菌中尚处于起步阶段。本文综述了超嗜热古菌中整合性病毒、质粒及基因组岛等整合性遗传元件的分类、整合及维持机制。展示了整合性遗传元件参与的水平基因转移过程在超嗜热古菌基因组演化中扮演的重要角色。整合性遗传元件相关功能基因组学研究为理解超嗜热古菌的多样性及其环境适应性机制提供了新的视角。     

The sociobiology of molecular systems

It is often assumed that molecular systems are designed to maximize the competitive ability of the organism that carries them. In reality, natural selection acts on both cooperative and competitive phenotypes, across multiple scales of biological organization. Here I ask how the potential for social effects in evolution has influenced molecular systems. I discuss a range of phenotypes, from the selfish genetic elements that disrupt genomes, through metabolism, multicellularity and cancer, to behaviour and the organization of animal societies. I argue that the balance between cooperative and competitive evolution has shaped both form and function at the molecular scale.     

Autophagy in obesity and atherosclerosis: Interrelationships between cholesterol homeostasis,lipoprotein metabolism and autophagy in macrophages and other systems

The incidence of diseases characterized by a dysregulation of lipid metabolism such as obesity, diabetes and atherosclerosis is rising at alarming rates, driving research to uncover new therapies to manage dyslipidemias and resolve the metabolic syndrome conundrum. Autophagy and lipid homeostasis – both ancient cellular pathways – have seemingly co-evolved to share common regulatory elements, and autophagy has emerged as a prominent mechanism involved in the regulation of lipid metabolism. This review highlights recent findings on the role of autophagy in the regulation of cellular cholesterol homeostasis and lipoprotein metabolism, with special emphasis on macrophages. From modulation of inflammation to regulation of cellular cholesterol levels, a protective role for autophagy in atherosclerosis is emerging. The manipulation of autophagic activity represents a new possible therapeutic approach for the treatment complex metabolic disorders such as obesity and the metabolic syndrome.     

Metabolic complexity in the RNA world and implications for the origin of protein synthesis

Summary A model is presented for the evolution of metabolism and protein synthesis in a primitive, acellular RNA world. It has been argued previously that the ability to perform metabolic functions logically must have preceded the evolution of a message-dependent protein synthetic machinery and that considerable metabolic complexity was achieved by ribo-organisms (i.e., organisms in which both genome and enzymes are comprised of RNA). The model proposed here offers a mechanism to account for the gradual development of sophisticated metabolic activities by ribo-organisms and explains how such metabolic complexity would lead subsequently to the synthesis of genetically encoded polypeptides. RNA structures ancestral to modern ribosomes, here termed metabolosomes, are proposed to have functioned as organizing centers that coordinated, using base-pairing interactions, the order and nature of adaptor-mounted substrate/catalyst interactions in primitive metabolic pathways. In this way an ancient genetic code for metabolism is envisaged to have predated the specialized modern genetic code for protein synthesis. Thus, encoded amino acids initially would have been used, in conjunction with other encoded metabolites, as building blocks for biosynthetic pathways, a role that they retain in the metabolism of contemporary organisms. At a later stage the encoded amino acids would have been condensed together on similar RNA metabolosome structures to form the first genetically determined, and therefore biologically meaningful, polypeptides. On the basis of codon distributions in the modern genetic code it is argued that the first proteins to have been synthesized and used by ribo-organisms were predominantly hydrophobic and likely to have performed membrane-related functions (such as forming simple pore structures), activities essential for the evolution of membrane-enclosed cells.