Experimental evolution of propanediol oxidoreductase in Escherichia coli comparative analysis of the wild-type and mutant enzymes

A model for the study of experimental evolution is provided by the novel metabolic system responsible for the progressive utilization of l-1,2-propanediol by mutants of Escherichia coli (strains 3 and 430). In these mutant strains, propanediol oxidoreductase, which serves as l-lactaldehyde reductase in fucose fermentation by wild-type cells, became a key enzyme for aerobic catabolism of propanediol. In the wild-type strain (strain 1), the enzyme is inducible only anaerobically; in strains 3 and 430, the enzyme is synthesized constitutively even in the presence of air. The propanediol oxidoreductase from all three strains was purified to homogeneity by the same procedure. The enzyme of strain 3 clearly differed from that of strain 1 in several respects: K_m and V in both directions of the reaction, energy of activation, thermal stability, pH optimum and substrate specificity. However, no difference in any of the above characteristics was found between the enzymes of strains 3 and 430. All three enzymes presented the same electrophoretic mobility. According to immunological data, all three strains differed in their intracellular enzyme level.     

Modeling of uncertainties in biochemical reactions

Mathematical modeling is an indispensable tool for research and development in biotechnology and bioengineering. The formulation of kinetic models of biochemical networks depends on knowledge of the kinetic properties of the enzymes of the individual reactions. However, kinetic data acquired from experimental observations bring along uncertainties due to various experimental conditions and measurement methods. In this contribution, we propose a novel way to model the uncertainty in the enzyme kinetics and to predict quantitatively the responses of metabolic reactions to the changes in enzyme activities under uncertainty. The proposed methodology accounts explicitly for mechanistic properties of enzymes and physico‐chemical and thermodynamic constraints, and is based on formalism from systems theory and metabolic control analysis. We achieve this by observing that kinetic responses of metabolic reactions depend: (i) on the distribution of the enzymes among their free form and all reactive states; (ii) on the equilibrium displacements of the overall reaction and that of the individual enzymatic steps; and (iii) on the net fluxes through the enzyme. Relying on this observation, we develop a novel, efficient Monte Carlo sampling procedure to generate all states within a metabolic reaction that satisfy imposed constrains. Thus, we derive the statistics of the expected responses of the metabolic reactions to changes in enzyme levels and activities, in the levels of metabolites, and in the values of the kinetic parameters. We present aspects of the proposed framework through an example of the fundamental three‐step reversible enzymatic reaction mechanism. We demonstrate that the equilibrium displacements of the individual enzymatic steps have an important influence on kinetic responses of the enzyme. Furthermore, we derive the conditions that must be satisfied by a reversible three‐step enzymatic reaction operating far away from the equilibrium in order to respond to changes in metabolite levels according to the irreversible Michelis–Menten kinetics. The efficient sampling procedure allows easy, scalable, implementation of this methodology to modeling of large‐scale biochemical networks. Biotechnol. Bioeng. 2011;108: 413–423. © 2010 Wiley Periodicals, Inc.     

Metabolic control at the cytosol–mitochondria interface in different growth phases of CHO cells

Metabolism at the cytosol–mitochondria interface and its regulation is of major importance particularly for efficient production of biopharmaceuticals in Chinese hamster ovary (CHO) cells but also in many diseases. We used a novel systems-oriented approach combining dynamic metabolic flux analysis and determination of compartmental enzyme activities to obtain systems level information with functional, spatial and temporal resolution. Integrating these multiple levels of information, we were able to investigate the interaction of glycolysis and TCA cycle and its metabolic control. We characterized metabolic phases in CHO batch cultivation and assessed metabolic efficiency extending the concept of metabolic ratios. Comparing in situ enzyme activities including their compartmental localization with in vivo metabolic fluxes, we were able to identify limiting steps in glycolysis and TCA cycle. Our data point to a significant contribution of substrate channeling to glycolytic regulation. We show how glycolytic channeling heavily affects the availability of pyruvate for the mitochondria. Finally, we show that the activities of transaminases and anaplerotic enzymes are tailored to permit a balanced supply of pyruvate and oxaloacetate to the TCA cycle in the respective metabolic states. We demonstrate that knowledge about metabolic control can be gained by correlating in vivo metabolic flux dynamics with time and space resolved in situ enzyme activities.     

Evolution of regulatory genes and patterns: Relationships to evolutionary rates and to metabolic functions

In an effort to understand the forces shaping evolution of regulatory genes and patterns, we have compared data on interspecific differences in enzyme expression patterns among the rapidly evolving Hawaiian picture-winged Drosophila to similar data on the more conservative virilis species group. Divergence of regulatory patterns is significantly more common in the former group, but cause and effect are difficult to discern. Random fixation of regulatory variants in small populations and/or during speciation may be somewhat more likely than divergence driven by selection. Within the picture-winged group, we also have compared enzymes that fulfill different metabolic roles. There are highly significant differences between individual enzymes, but no obvious correlations to functional categories. Correspondence to: W.J. Dickinson     

Extending biochemical databases by metabolomic surveys

Metabolomics can map the large metabolic diversity in species, organs, or cell types. In addition to gains in enzyme specificity, many enzymes have retained substrate and reaction promiscuity. Enzyme promiscuity and the large number of enzymes with unknown enzyme function may explain the presence of a plethora of unidentified compounds in metabolomic studies. Cataloguing the identity and differential abundance of all detectable metabolites in metabolomic repositories may detail which compounds and pathways contribute to vital biological functions. The current status in metabolic databases is reviewed concomitant with tools to map and visualize the metabolome.     

Chemical and genomic evolution of enzyme-catalyzed reaction networks

There is a tendency that a unit of enzyme genes in an operon-like structure in the prokaryotic genome encodes enzymes that catalyze a series of consecutive reactions in a metabolic pathway. Our recent analysis shows that this and other genomic units correspond to chemical units reflecting chemical logic of organic reactions. From all known metabolic pathways in the KEGG database we identified chemical units, called reaction modules, as the conserved sequences of chemical structure transformation patterns of small molecules. The extracted patterns suggest co-evolution of genomic units and chemical units. While the core of the metabolic network may have evolved with mechanisms involving individual enzymes and reactions, its extension may have been driven by modular units of enzymes and reactions.     

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.     

Sequence,Structure, and Evolution of Cellulases in Glycoside Hydrolase Family 48

Currently, the cost of cellulase enzymes remains a key economic impediment to commercialization of biofuels (1). Enzymes from glycoside hydrolase family 48 (GH48) are a critical component of numerous natural lignocellulose-degrading systems. Although computational mining of large genomic data sets is a promising new approach for identifying novel cellulolytic activities, current computational methods are unable to distinguish between cellulases and enzymes with different substrate specificities that belong to the same protein family. We show that by using a robust computational approach supported by experimental studies, cellulases and non-cellulases can be effectively identified within a given protein family. Phylogenetic analysis of GH48 showed non-monophyletic distribution, an indication of horizontal gene transfer. Enzymatic function of GH48 proteins coded by horizontally transferred genes was verified experimentally, which confirmed that these proteins are cellulases. Computational and structural studies of GH48 enzymes identified structural elements that define cellulases and can be used to computationally distinguish them from non-cellulases. We propose that the structural element that can be used for in silico discrimination between cellulases and non-cellulases belonging to GH48 is an ω-loop located on the surface of the molecule and characterized by highly conserved rare amino acids. These markers were used to screen metagenomics data for “true” cellulases.     

Seasonal and Regional Variations in Metal Contamination and Condition Indicators in Yellow Perch (Perca flavescens) along Two Polymetallic Gradients. III. Energetic and Physiological Indicators

The influences of metal contamination, fish size, season, and region on tissue metabolic capacities and protein concentrations were examined in yellow perch from two metal gradients (Sudbury, Ontario, and Rouyn-Noranda, Québec, Canada) in two seasons (spring and summer). In general, increased tissue Cu and Cd contamination was associated with lower aerobic capacities, suggesting direct metal inhibition of aerobic enzymes. However, our data also revealed that tissue Ni contamination positively affected aerobic capacities, possibly due to oxidative damage to mitochondrial membranes leading to compensatory increases in the activity of mitochondrial enzymes. Tissue aerobic capacities decreased, but anaerobic capacities increased, with size. Tissue protein concentrations and metabolic capacities were also influenced by season. A novel finding of this study is that size-corrected tissue enzyme activities can differ markedly in yellow perch sampled in the same season in similar lakes, but separated by a few hundred kilometers. Overall, the results from this large dataset support that tissue metabolic capacities are under seasonal and regional influences, but are also affected by metal contamination. Our study indicates that tissue metabolic enzyme activities should be considered as a tool for ecological risk assessment studies aiming at detecting metal stress in wild fish. However, fish should be sampled over a short period, and reference sites should be close to contaminated sites.     

Understanding specificity in metabolic pathways—Structural biology of human nucleotide metabolism

Interactions are the foundation of life at the molecular level. In the plethora of activities in the cell, the evolution of enzyme specificity requires the balancing of appropriate substrate affinity with a negative selection, in order to minimize interactions with other potential substrates in the cell. To understand the structural basis for enzyme specificity, the comparison of structural and biochemical data between enzymes within pathways using similar substrates and effectors is valuable.Nucleotide metabolism is one of the largest metabolic pathways in the human cell and is of outstanding therapeutic importance since it activates and catabolises nucleoside based anti-proliferative drugs and serves as a direct target for anti-proliferative drugs. In recent years the structural coverage of the enzymes involved in human nucleotide metabolism has been dramatically improved and is approaching completion. An important factor has been the contribution from the Structural Genomics Consortium (SGC) at Karolinska Institutet, which recently has solved 33 novel structures of enzymes and enzyme domains in human nucleotide metabolism pathways and homologs thereof. In this review we will discuss some of the principles for substrate specificity of enzymes in human nucleotide metabolism illustrated by a selected set of enzyme families where a detailed understanding of the structural determinants for specificity is now emerging.     

Effects of maternal thiamine deficiency on the development of thiamine-dependent enzymes in regions of the rat brain

Previous studies suggest that developing rat brain is susceptible to reduced thiamine intake. In order to assess the metabolic basis for this susceptibility, activities of three thiamine-dependent enzymes (pyruvate dehydrogenase complex, -ketoglutarate dehydrogenase and transketolase) were measured in homogenates of brain tissue from the offspring of thiamine-deficient mothers. Control groups of animals were pair-fed to equal food consumption with the thiamine-deficient animals. The study revealed region-selective delays in the establishment of adult activities of thiamine-dependent enzymes as a result of maternal thiamine deficiency. Pyruvate dehydrogenase complex activities in cerebral cortex were significantly reduced (by 20% P < 0.05); -ketoglutarate dehydrogenase activities were also reduced in cerebral cortex (by 30% P < 0.05). In the case of transketolase, enzyme activities were significantly reduced in cerebral cortex, cerebellum and brainstem. Following thiamine replenishment, defective enzyme activities were restored to normal in all cases. However, since thiamine-dependent enzymes are important for the establishment of adult patterns of cerebral energy metabolism and also in myelin synthesis, maternal thiamine deficiency resulting in reductions of thiamine-dependent enzymes at a vulnerable period in brain development could have serious metabolic consequences leading to permanent neurological sequellae in the offspring.     

Global metabolic regulation analysis for<Emphasis Type="Italic"> Escherichia coli</Emphasis> K12 based on protein expression by 2-dimensional electrophoresis and enzyme activity measurement

Regulation of the main metabolic pathways of Escherichia coli K12 was investigated based on 2-dimensional electrophoresis (2DE) and the measurement of enzyme activities. The cells were grown aerobically in different carbon sources, such as glucose, acetate, gluconate or glycerol. Microaerobic cultivation was also conducted with glucose as a carbon source. Fifty-two proteins could be identified based on 2DE, and 26 enzyme activities from the main metabolic pathways-including glycolysis, pentose phosphate pathway, TCA cycle, Entner-Doudoroff pathway and fermentative pathway-were assayed. These enzyme activities, together with global and quantitative protein expression, gave us a clear picture of metabolic regulation. The results show that, compared with the control experiment with glucose as a carbon source under aerobic conditions, glycolytic enzymes were slightly up-regulated (<2-fold), TCA cycle enzymes were significantly down-regulated (2- to 10-fold), and fermentative enzymes such as pfl and adhE were highly up-regulated (>10-fold) under microaerobic conditions in glucose medium. When acetate was used as a carbon source, pfkA, pykF, ppc and zwf were down-regulated, while fbp, pckA, ppsA and mez were significantly up-regulated. Glyoxylate enzymes such as aceA and aceB were strongly up-regulated (>10-fold) and TCA-cycle-related enzymes were also up-regulated to some extent. With gluconate as a carbon source, edd, eda, fbp and TCA cycle enzymes were up-regulated. With glycerol as a carbon source, fbp and TCA cycle enzymes were up-regulated, while ackA was significantly down-regulated. Protein abundance obtained by 2DE correlated well with enzyme activity, with a few exceptions (e.g., isocitrate dehydrogenase), during aerobic growth on acetate.     

Thematic minireview series on enzyme evolution in the post-genomic era

The emergence of genomics; ongoing computational advances; and the development of large-scale sequence, structural, and functional databases have created important new interdisciplinary linkages between molecular evolution, molecular biology, and enzymology. The five minireviews in this series survey advances and challenges in this burgeoning field from complementary perspectives. The series has three major themes. The first is the evolution of enzyme superfamilies, in which members exhibit increasing sequence, structural, and functional divergence with increasing time of divergence from a common ancestor. The second is the evolutionary role of promiscuous enzymes, which, in addition to their primary function, have adventitious secondary activities that frequently provide the starting point for the evolution of new enzymes. The third is the importance of in silico approaches to the daunting challenge of assigning and predicting the functions of the many uncharacterized proteins in the large-scale sequence and structural databases that are now available. A recent computational advance, the use of protein similarity networks that map functional data onto proteins clustered by similarity, is presented as an approach that can improve functional insight and inference. The three themes are illustrated with several examples of enzyme superfamilies, including the amidohydrolase, metallo-β-lactamase, and enolase superfamilies.     

Variation among Extracted Lines of Drosophila Melanogaster in Triacylglycerol and Carbohydrate Storage

Whole larvae and whole adult extracts from 26 second chromosome replacement lines of Drosophila melanogaster were analyzed to determine the amounts of stored triacylglycerols and carbohydrates as well as the activities of 13 enzymes in relevant biochemical pathways. Analysis of covariance revealed significant differences among lines in stored lipids and carbohydrates, as well as in activities of most of the enzymes. Significant broad-sense genetic correlations (among adjusted line means) were detected for a number of enzyme pairs. Multiple regression techniques were applied to assess the extent to which the amounts of stored triacylglycerols and carbohydrates could be predicted from the enzyme activities. Significant regressions were found in both adults and larvae, suggesting that modulation of enzyme activities is reflected in different sizes of storage pools. The population genetic consequences of natural selection acting on a phenotype such as energy storage is considered in light of models of metabolic flux in biochemical pathways.     

Mutation-Selection Balance and Metabolic Control Theory

The evolution of metabolic control is examined with models that unify approaches of classical quantitative genetics and metabolic control theory. The quantitative traits considered are the activities of enzymes embedded within metabolic pathways. In the models, polygenic mutation alters the enzyme activities (Vmax/Km) according to prescribed distributions, and the population evolves following classical haploid viability selection. Stabilizing selection operates on global properties of the metabolic pathway, including either flux or metabolite pool concentration. Analytical results and numerical simulations demonstrate several important properties of these characters, including skewed, non-Gaussian equilibrium distributions, and an expected positive correlation between activities of enzymes flanking a substrate pool undergoing stabilizing selection. The house-of-cards approximation proved to be accurate in predicting the equilibrium distribution of allelic effects for a biologically reasonable segment of the parameter space. Further experimental and theoretical work is needed before a clear assessment can be made whether the observed variance in enzyme activities is explicable by a mutation-selection balance, and this system provides an excellent opportunity for such a test.     

Homeostatic regulation upon changes of enzyme activities in the Calvin cycle as an example for general mechanisms of flux control. What can we expect from transgenic plants?

In order to explain the mechanisms of Calvin-cycle regulation, the general properties of metabolic systems under homeostatic flux control are analyzed. It is shown that the main characteristic point for an enzyme in such a system can be the value of a sharp transition from some constant homeostatic flux to a limitation by this enzyme. A special method for the quantitative treatment of the experimental dependence of a metabolic flux such as photosynthesis on enzyme content is developed. It is pointed out that reactions close to a thermodynamic equilibrium under normal conditions can considerably limit the homeostatic fluxes with a decrease of the enzyme content. Calvin-cycle enzymes are classified as non-limiting, near-limiting and limiting. The deduced rules for the regulation of a homeostatic metabolic pathway are used to explain the data obtained for transgenic plants with reduced activities of Calvin-cycle enzymes. The role of compensating mechanisms that maintain the photosynthesis rate constant upon the changes of enzyme contents is analyzed for the Calvin cycle. The developed analysis explains the sharp transitions between limiting and non-limiting conditions that can be seen in transgenic plants with reduced content of some Calvin-cycle enzymes, and the limiting role of such reversible enzymes as aldolase, transketolase and others. The attempt is made to predict the properties of plants with increased enzyme contents in the Calvin cycle.     

Discovery metabolite profiling--forging functional connections between the proteome and metabolome

Of primary interest for every enzyme is the identification of its physiological substrates. However, the vast structural diversity of endogenous metabolites, coupled with the overlapping activities of numerous enzymes, makes it difficult to deduce the identity of natural substrates for a given enzyme based on in vitro experiments. To address this challenge, we recently introduced an LC-MS based analytical method termed discovery metabolite profiling (DMP) to evaluate the global metabolic effects of enzyme inactivation in vivo. We have applied DMP to study mice lacking the enzyme fatty acid amide hydrolase (FAAH), which degrades the endocannabinoid family of signaling lipids. DMP identified several previously uncharacterized FAAH substrates, including a structurally novel class of brain lipids that represent conjugates of very long chain fatty acids with the amino acid derivative taurine [N-acyl taurines (NATs)]. These findings show that DMP can establish direct connections between the proteome and metabolome and thus offers a powerful strategy to assign physiological functions to enzymes in the post-genomic era.     

Evolution of patterns of gene expression in Hawaiian picture-wingedDrosophila

Summary The tissue and stage specificity of expression of five enzymes was examined by electrophoretic analysis of relative enzyme levels in extracts of 13 larval and adult tissues in 27 species of Hawaiian picture-wingedDrosophila. The developmentally regulated patterns of enzyme expression thus characterized were compared to a modal standard phenotype. About 30% of the pattern features analyzed differed significantly from the standard in one or more species. Many of these regulatory differences are essentially qualitative, with tissue specific differences in enzyme activity in excess of 100 fold for some species pairs. The adaptive significance of these pattern differences is unknown, but the results provide strong direct evidence for rapid evolution of new patterns of gene regulation in this group of organisms.     

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.