The origin and evolution of modern metabolism

One fundamental goal of current research is to understand how complex biomolecular networks took the form that we observe today. Cellular metabolism is probably one of the most ancient biological networks and constitutes a good model system for the study of network evolution. While many evolutionary models have been proposed, a substantial body of work suggests metabolic pathways evolve fundamentally by recruitment, in which enzymes are drawn from close or distant regions of the network to perform novel chemistries or use different substrates. Here we review how structural and functional genomics has impacted our knowledge of evolution of modern metabolism and describe some approaches that merge evolutionary and structural genomics with advances in bioinformatics. These include mining the data on structure and function of enzymes for salient patterns of enzyme recruitment. Initial studies suggest modern metabolism originated in enzymes of nucleotide metabolism harboring the P-loop hydrolase fold, probably in pathways linked to the purine metabolic subnetwork. This gateway of recruitment gave rise to pathways related to the synthesis of nucleotides and cofactors for an ancient RNA world. Once the TIM beta/alpha-barrel fold architecture was discovered, it appears metabolic activities were recruited explosively giving rise to subnetworks related to carbohydrate and then amino acid metabolism. Remarkably, recruitment occurred in a layered system reminiscent of Morowitz's prebiotic shells, supporting the notion that modern metabolism represents a palimpsest of ancient metabolic chemistries.     

Cysteine and iron accelerate the formation of ribose-5-phosphate,providing insights into the evolutionary origins of the metabolic network structure

The structure of the metabolic network is highly conserved, but we know little about its evolutionary origins. Key for explaining the early evolution of metabolism is solving a chicken–egg dilemma, which describes that enzymes are made from the very same molecules they produce. The recent discovery of several nonenzymatic reaction sequences that topologically resemble central metabolism has provided experimental support for a “metabolism first” theory, in which at least part of the extant metabolic network emerged on the basis of nonenzymatic reactions. But how could evolution kick-start on the basis of a metal catalyzed reaction sequence, and how could the structure of nonenzymatic reaction sequences be imprinted on the metabolic network to remain conserved for billions of years? We performed an in vitro screening where we add the simplest components of metabolic enzymes, proteinogenic amino acids, to a nonenzymatic, iron-driven reaction network that resembles glycolysis and the pentose phosphate pathway (PPP). We observe that the presence of the amino acids enhanced several of the nonenzymatic reactions. Particular attention was triggered by a reaction that resembles a rate-limiting step in the oxidative PPP. A prebiotically available, proteinogenic amino acid cysteine accelerated the formation of RNA nucleoside precursor ribose-5-phosphate from 6-phosphogluconate. We report that iron and cysteine interact and have additive effects on the reaction rate so that ribose-5-phosphate forms at high specificity under mild, metabolism typical temperature and environmental conditions. We speculate that accelerating effects of amino acids on rate-limiting nonenzymatic reactions could have facilitated a stepwise enzymatization of nonenzymatic reaction sequences, imprinting their structure on the evolving metabolic network.

The evolutionary origins of metabolism are largely unknown. This study shows that the prebiotically available proteinogenic amino acid cysteine can promote the metabolism-like rate-limiting formation of ribose-5-phosphate, suggesting that early metabolic pathways could have emerged thought the stepwise enzymatization of non-enzymatic reaction sequences.     

Why metabolic enzymes are essential or nonessential for growth of Escherichia coli K12 on glucose

The genes encoding metabolic enzymes involved in glucose metabolism, the TCA cycle, and biosynthesis of amino acids, purines, pyrimidines, and cofactors would be expected to be essential for growth of Escherichia coli on glucose because the cells must synthesize all of the building blocks for cellular macromolecules. Surprisingly, 80 of 227 of these genes are not essential. Analysis of why these genes are not essential provides insights into the metabolic sophistication of E. coli and into the evolutionary pressures that have shaped its physiology. Alternative routes enabled by interconnecting pathways can allow a defective step to be bypassed. Isozymes, alternative enzymes, broad-specificity enzymes, and multifunctional enzymes can often substitute for a missing enzyme. We expect that the apparent redundancy in these metabolic pathways has arisen due to the need for E. coli to survive in a variety of habitats and therefore to have a metabolism that allows optimal exploitation of varying environmental resources and synthesis of small molecules when they cannot be obtained from the environment.     

Integrating the universal metabolism into a phylogenetic analysis

The darwinian concept of "descent with modification" applies to metabolic pathways: pathways sharing similarities must have inherited them from an exclusive, hypothetical ancestral pathway. Comparative anatomy of biochemical pathways is performed using five criteria of homology. Primary homologies of "type I" were defined as several pathways sharing the same enzyme with high specificity for its substrate. Primary homologies of "type II" were defined as the sharing of similar enzymatic functions, cofactors, functional family, or recurrence of a set of reactions. Standard cladistic analysis is used to infer the evolutionary history of metabolic development and the relative ordering of biochemical reactions through time, from a single matrix integrating the whole basic universal metabolism. The cladogram shows that the earliest pathways to emerge are metabolism of amino acids of groups I and II (Asp, Asn, Glu, and Gln). The earliest enzymatic functions are mostly linked to amino acid catabolism: deamination, transamination, and decarboxylation. For some amino acids, catabolism and biosynthesis occur at the same time (Asp, Glu, Lys, and Met). Catabolism precedes anabolism for Asn, Gln, Arg, Trp, His, Tyr, and Phe, and anabolism precedes catabolism for Pro, Ala, Leu, Val, Ile, Cys, Gly, Ser, and Thr. The urea cycle evolves from arginine synthesis. Metabolism of fatty acids and sugars develops after the full development of metabolism of amino acids of groups I and II, and they are associated with the anabolism of amino acids of groups III and IV. Syntheses of aromatic amino acids are branched within sugar metabolism. The Krebs cycle occurs relatively late after the setting of metabolism of amino acids of groups I and II. One portion of the Krebs cycle has a catabolic origin, whereas the other portion has an anabolic origin in pathways of amino acids of groups III and IV. It is not possible to order glycolysis and gluconeogenesis with regard to the Krebs cycle, as they all belong to "period 6." Pentose-phosphate and Calvin cycles are later (periods 7 and 8, respectively). Cladistic analysis of the structure of biochemical pathways makes hypotheses in biochemical evolution explicit and parsimonious.     

The enzymatic and metabolic capabilities of early life

We introduce the concept of metaconsensus and employ it to make high confidence predictions of early enzyme functions and the metabolic properties that they may have produced. Several independent studies have used comparative bioinformatics methods to identify taxonomically broad features of genomic sequence data, protein structure data, and metabolic pathway data in order to predict physiological features that were present in early, ancestral life forms. But all such methods carry with them some level of technical bias. Here, we cross-reference the results of these previous studies to determine enzyme functions predicted to be ancient by multiple methods. We survey modern metabolic pathways to identify those that maintain the highest frequency of metaconsensus enzymes. Using the full set of modern reactions catalyzed by these metaconsensus enzyme functions, we reconstruct a representative metabolic network that may reflect the core metabolism of early life forms. Our results show that ten enzyme functions, four hydrolases, three transferases, one oxidoreductase, one lyase, and one ligase, are determined by metaconsensus to be present at least as late as the last universal common ancestor. Subnetworks within central metabolic processes related to sugar and starch metabolism, amino acid biosynthesis, phospholipid metabolism, and CoA biosynthesis, have high frequencies of these enzyme functions. We demonstrate that a large metabolic network can be generated from this small number of enzyme functions.     

Evolution of enzymes in metabolism: a network perspective

Several models have been proposed to explain the origin and evolution of enzymes in metabolic pathways. Initially, the retro-evolution model proposed that, as enzymes at the end of pathways depleted their substrates in the primordial soup, there was a pressure for earlier enzymes in pathways to be created, using the later ones as initial template, in order to replenish the pools of depleted metabolites. Later, the recruitment model proposed that initial templates from other pathways could be used as long as those enzymes were similar in chemistry or substrate specificity. These two models have dominated recent studies of enzyme evolution. These studies are constrained by either the small scale of the study or the artificial restrictions imposed by pathway definitions. Here, a network approach is used to study enzyme evolution in fully sequenced genomes, thus removing both constraints. We find that homologous pairs of enzymes are roughly twice as likely to have evolved from enzymes that are less than three steps away from each other in the reaction network than pairs of non-homologous enzymes. These results, together with the conservation of the type of chemical reaction catalyzed by evolutionarily related enzymes, suggest that functional blocks of similar chemistry have evolved within metabolic networks. One possible explanation for these observations is that this local evolution phenomenon is likely to cause less global physiological disruptions in metabolism than evolution of enzymes from other enzymes that are distant from them in the metabolic network.     

Metabolites: a helping hand for pathway evolution?

The evolution of enzymes and pathways is under debate. Recent studies show that recruitment of single enzymes from different pathways could be the driving force for pathway evolution. Other mechanisms of evolution, such as pathway duplication, enzyme specialization, de novo invention of pathways or retro-evolution of pathways, appear to be less abundant. Twenty percent of enzyme superfamilies are quite variable, not only in changing reaction chemistry or metabolite type but in changing both at the same time. These variable superfamilies account for nearly half of all known reactions. The most frequently occurring metabolites provide a helping hand for such changes because they can be accommodated by many enzyme superfamilies. Thus, a picture is emerging in which new pathways are evolving from central metabolites by preference, thereby keeping the overall topology of the metabolic network.     

Kinetic, dynamic, and pathway studies of glycerol metabolism by Klebsiella pneumoniae in anaerobic continuous culture: II. Analysis of metabolic rates and pathways under oscillation and steady-state conditions

The oscillation phenomena reported in the preceding article for the anaerobic continuous fermentation of glycerol by Klebsiella pneumoniae are analyzed in terms of metabolic fluxes (metabolic rates and yields) and stoichiometry of pathways. Significant oscillations in the fluxes of CO(2), H(2), formic acid, ethanol, and reducing equivalents are observed which show obvious relationships to each other. Changes in the consumption or production rates of glycerol, acetic acid, 1,3-propanediol, and ATP are irregular and have relatively small amplitudes compared with their absolute values. By comparing the metabolic fluxes under oscillation and steady state that have nearly the same environmental conditions it could be shown that pyruvate metabolism is the main step affected under oscillation conditions. The specific formation rates of all the products originating from pyruvate metabolism (CO(2), H(2), formic acid, ethanol, acetic acid, lactic acid, and 2,3-butanediol) show significant differences under conditions of oscillation and steady state. In contrast, the specific rates of substrate uptake, ATP generation, and formation of products deriving either directly from glycerol (1,3-propanediol) or from the upstream of pyruvate metabolism (e.g., succinic acid) are not, or at least not significantly, affected during oscillation. Stoichiometric analysis of metabolic pathways confirms that other enzyme systems, in addition to pyruvate: formate-lyase, must be simultaneously involved in the pyruvate decarboxylation under both oscillation and steady-state conditions. The results strongly suggest oscillations of activities of these enzymes under oscillation conditions. It appears that the reason for the occurrence of oscillation and hysteresis lies in an unstable regulation of pyruvate metabolism of different enzymes triggered by substrate excess and drastic change(s) of environmental conditions. (c) 1996 John Wiley & Sons, Inc.     

Total cell protein concentration as an evolutionary constraint on the metabolic control distribution in cells.

Cell protein occupies 15-35% of cell volume. This level is argued to be the maximum compatible with cell function. Because of this constraint, selection pressure during evolution is likely to have maximized pathway fluxes for minimum total protein level. Pathways optimized in this way are shown to have the following characteristics: (1) the "simple" flux control coefficients of all enzymes are equal, (2) the normal flux control coefficients depend on the relative kinetic constants of the enzymes, such that enzymes with low specific activity are present at relatively high levels and have high flux control, (3) the normal flux control coefficients are proportional to enzyme levels. A single rate limiting step located at the first step in a pathway is likely to be inefficient in terms of protein levels, and the major metabolic pathways are therefore expected to have control distributed throughout the pathway. This has important implications for metabolic control.     

Analysis of metabolic networks using a pathway distance metric through linear programming

The solution of the shortest path problem in biochemical systems constitutes an important step for studies of their evolution. In this paper, a linear programming (LP) algorithm for calculating minimal pathway distances in metabolic networks is studied. Minimal pathway distances are identified as the smallest number of metabolic steps separating two enzymes in metabolic pathways. The algorithm deals effectively with circularity and reaction directionality. The applicability of the algorithm is illustrated by calculating the minimal pathway distances for Escherichia coli small molecule metabolism enzymes, and then considering their correlations with genome distance (distance separating two genes on a chromosome) and enzyme function (as characterised by enzyme commission number). The results illustrate the effectiveness of the LP model. In addition, the data confirm that propinquity of genes on the genome implies similarity in function (as determined by co-involvement in the same region of the metabolic network), but suggest that no correlation exists between pathway distance and enzyme function. These findings offer insight into the probable mechanism of pathway evolution.     

A substrate ambiguous enzyme facilitates genome reduction in an intracellular symbiont

Background

Genome evolution in intracellular microbial symbionts is characterized by gene loss, generating some of the smallest and most gene-poor genomes known. As a result of gene loss these genomes commonly contain metabolic pathways that are fragmented relative to their free-living relatives. The evolutionary retention of fragmented metabolic pathways in the gene-poor genomes of endosymbionts suggests that they are functional. However, it is not always clear how they maintain functionality. To date, the fragmented metabolic pathways of endosymbionts have been shown to maintain functionality through complementation by host genes, complementation by genes of another endosymbiont and complementation by genes in host genomes that have been horizontally acquired from a microbial source that is not the endosymbiont. Here, we demonstrate a fourth mechanism.

Results

We investigate the evolutionary retention of a fragmented pathway for the essential nutrient pantothenate (vitamin B5) in the pea aphid, Acyrthosiphon pisum endosymbiosis with Buchnera aphidicola. Using quantitative analysis of gene expression we present evidence for complementation of the Buchnera pantothenate biosynthesis pathway by host genes. Further, using complementation assays in an Escherichia coli mutant we demonstrate functional replacement of a pantothenate biosynthesis enzyme, 2-dehydropantoate 2-reductase (E.C. 1.1.1.169), by an endosymbiont gene, ilvC, encoding a substrate ambiguous enzyme.

Conclusions

Earlier studies have speculated that missing enzyme steps in fragmented endosymbiont metabolic pathways are completed by adaptable endosymbiont enzymes from other pathways. Here, we experimentally demonstrate completion of a fragmented endosymbiont vitamin biosynthesis pathway by recruitment of a substrate ambiguous enzyme from another pathway. In addition, this work extends host/symbiont metabolic collaboration in the aphid/Buchnera symbiosis from amino acid metabolism to include vitamin biosynthesis.

     

Targeting amino acid metabolism in cancer growth and anti-tumor immune response

Recent advances in amino acid metabolism have revealed that targeting amino acid metabolic enzymes in cancer therapy is a promising strategy for the development of novel therapeutic agents. There are currently several drugs in clinical trials that specifically target amino acid metabolic pathways in tumor cells. In the context of the tumor microenvironment,however,tumor cells form metabolic relationships with immune cells,and they oftencompete for common nutrients. Many tumors evolved to escape immune surveillance by taking advantage of their metabolic flexibility and redirecting nutrients for their own advantage. This review outlines the most recent advances in targeting amino acid metabolic pathways in cancer therapy while giving consideration to the impact these pathways may have on the anti-tumor immune response.     

Biochemical pathways and mechanisms nitrogen, amino acid, and carbon metabolism

For both nitrogen and carbon metabolism there exist specific regulatory mechanisms to enable cells to assimilate a wide variety of nitrogen and carbon sources. Superimposed are regulatory circuits, the so called nitrogen and carbon catabolite regulation, to allow for selective use of “rich” sources first and “poor” sources later. Evidence points to the importance of specific regulatory mechanisms for short term adaptations, while generalized control circuits are used for long term modulation of nitrogen and carbon metabolism. Similarly a variety of regulatory mechanisms operate in amino acid metabolism. Modulation of enzyme activity and modulation of enzyme levels are the outstanding regulatory mechanisms. In prokaryotes, attenuation and repressor/operator control are predominant, besides a so called “metabolic control” which integrates amino acid metabolism into the overall nutritional status of the cells. In eukaryotic cells compartmentation of amino acid metabolites as well as of part of the pathways becomes an additional regulatory factor; pathway specific controls seem to be rare, but a complex regulatory network, the “general control of amino acid biosynthesis”, coordinates the synthesis of enzymes of a number of amino acid biosynthetic pathways.     

Origins of specificity and promiscuity in metabolic networks

How enzymes have evolved to their present form is linked to the question of how pathways emerged and evolved into extant metabolic networks. To investigate this mechanism, we have explored the chemical diversity present in a largely unbiased data set of catalytic reactions processed by modern enzymes across the tree of life. In order to get a quantitative estimate of enzyme chemical diversity, we measure enzyme multispecificity or promiscuity using the reaction molecular signatures. Our main finding is that reactions that are catalyzed by a highly specific enzyme are shared by poorly divergent species, suggesting a later emergence of this function during evolution. In contrast, reactions that are catalyzed by highly promiscuous enzymes are more likely to appear uniformly distributed across species in the tree of life. From a functional point of view, promiscuous enzymes are mainly involved in amino acid and lipid metabolisms, which might be associated with the earliest form of biochemical reactions. In this way, results presented in this paper might assist us with the identification of primeval promiscuous catalytic functions contributing to life's minimal metabolism.     

A general definition of metabolic pathways useful for systematic organization and analysis of complex metabolic networks

A set of linear pathways often does not capture the full range of behaviors of a metabolic network. The concept of 'elementary flux modes' provides a mathematical tool to define and comprehensively describe all metabolic routes that are both stoichiometrically and thermodynamically feasible for a group of enzymes. We have used this concept to analyze the interplay between the pentose phosphate pathway (PPP) and glycolysis. The set of elementary modes for this system involves conventional glycolysis, a futile cycle, all the modes of PPP function described in biochemistry textbooks, and additional modes that are a priori equally entitled to pathway status. Applications include maximizing product yield in amino acid and antibiotic synthesis, reconstruction and consistency checks of metabolism from genome data, analysis of enzyme deficiencies, and drug target identification in metabolic networks.     

Evolutionary origin and functional diversification of aminotransferases

Aminotransferases (ATs) are pyridoxal 5′-phosphate–dependent enzymes that catalyze the transamination reactions between amino acid donor and keto acid acceptor substrates. Modern AT enzymes constitute ∼2% of all classified enzymatic activities, play central roles in nitrogen metabolism, and generate multitude of primary and secondary metabolites. ATs likely diverged into four distinct AT classes before the appearance of the last universal common ancestor and further expanded to a large and diverse enzyme family. Although the AT family underwent an extensive functional specialization, many AT enzymes retained considerable substrate promiscuity and multifunctionality because of their inherent mechanistic, structural, and functional constraints. This review summarizes the evolutionary history, diverse metabolic roles, reaction mechanisms, and structure–function relationships of the AT family enzymes, with a special emphasis on their substrate promiscuity and multifunctionality. Comprehensive characterization of AT substrate specificity is still needed to reveal their true metabolic functions in interconnecting various branches of the nitrogen metabolic network in different organisms.     

Genome-level and biochemical diversity of the acyl-activating enzyme superfamily in plants

In higher plants, the superfamily of carboxyl-CoA ligases and related proteins, collectively called acyl activating enzymes (AAEs), has evolved to provide enzymes for many pathways of primary and secondary metabolism and for the conjugation of hormones to amino acids. Across the superfamily there is only limited sequence similarity, but a series of highly conserved motifs, including the AMP-binding domain, make it easy to identify members. These conserved motifs are best understood in terms of the unique domain-rotation architecture that allows AAE enzymes to catalyze the two distinct steps of the CoA ligase reaction. Arabidopsis AAE sequences were used to identify the AAE gene families in the sequenced genomes of green algae, mosses, and trees; the size of the respective families increased with increasing degree of organismal cellular complexity, size, and generation time. Large-scale genome duplications and small-scale tandem gene duplications have contributed to AAE gene family complexity to differing extents in each of the multicellular species analyzed. Gene duplication and evolution of novel functions in Arabidopsis appears to have occurred rapidly, because acquisition of new substrate specificity is relatively easy in this class of proteins. Convergent evolution has also occurred between members of distantly related clades. These features of the AAE superfamily make it difficult to use homology searches and other genomics tools to predict enzyme function.     

The pattern of amino acid replacements in alpha/beta-barrels

The determinants of site-to-site variability in the rate of amino acid replacement in alpha/beta-barrel enzyme structures are investigated. Of 125 available alpha/beta-barrel structures, only 25 meet a variety of phylogenetic and statistical criteria necessary to ensure sufficient data for reliable analysis. These 25 enzyme structures (from a wide variety of taxa with diverse lifestyles in diverse habitats) differ greatly in size, number, and topology of domains in addition to the alpha/beta-barrel, quaternary structure, metabolic role, reaction catalyzed, presence of prosthetic groups, regulatory mechanisms, use of cofactors, and catalytic mechanisms. Yet, with the exception of ribulose-1,5-bisphosphate carboxylase, all structures have similar frequency distributions of amino acid replacement rates. Hence, site-specific variability in rates of evolution is largely independent of differences in biology, biochemistry, and molecular structure. A correlation between site-specific rate variation and (1) distance from the active site, (2) solvent accessibility, and (3) treating glycines in unusual main-chain conformations as a separate class, explains approximately half the causal variation. Secondary structure exerts little influence on the pattern and distribution of replacements. Additional domains and subunits, side-chain hydrogen bonds, unusual side-chain rotamers, nonplanar peptide bonds, strained main-chain conformations, and buried hydrophilic-charged residues contribute little to variability among sites because they are rare. Nonlinear models do not improve the fits. In several enzymes, deviations from the typical pattern of replacements suggest the possible action of natural selection. A statistical analysis shows that, in all cases, much of the remaining unexplained variation is not attributable to chance and that other, as yet unidentified, causal relations must exist.