Multicopy suppression underpins metabolic evolvability

Factors driving metabolic diversity in the budding yeast subphylum

Background

Associations between traits are prevalent in nature, occurring across a diverse range of taxa and traits. Individual traits may co-evolve with one other, and these correlations can be driven by factors intrinsic or extrinsic to an organism. However, few studies, especially in microbes, have simultaneously investigated both across a broad taxonomic range. Here we quantify pairwise associations among 48 traits across 784 diverse yeast species of the ancient budding yeast subphylum Saccharomycotina, assessing the effects of phylogenetic history, genetics, and ecology.

Results

We find extensive negative (traits that tend to not occur together) and positive (traits that tend to co-occur) pairwise associations among traits, as well as between traits and environments. These associations can largely be explained by the biological properties of the traits, such as overlapping biochemical pathways. The isolation environments of the yeasts explain a minor but significant component of the variance, while phylogeny (the retention of ancestral traits in descendant species) plays an even more limited role. Positive correlations are pervasive among carbon utilization traits and track with chemical structures (e.g., glucosides and sugar alcohols) and metabolic pathways, suggesting a molecular basis for the presence of suites of traits. In several cases, characterized genes from model organisms suggest that enzyme promiscuity and overlapping biochemical pathways are likely mechanisms to explain these macroevolutionary trends. Interestingly, fermentation traits are negatively correlated with the utilization of pentose sugars, which are major components of the plant biomass degraded by fungi and present major bottlenecks to the production of cellulosic biofuels. Finally, we show that mammalian pathogenic and commensal yeasts have a suite of traits that includes growth at high temperature and, surprisingly, the utilization of a narrowed panel of carbon sources.

Conclusions

These results demonstrate how both intrinsic physiological factors and extrinsic ecological factors drive the distribution of traits present in diverse organisms across macroevolutionary timescales.

Electronic supplementary material

The online version of this article (10.1186/s12915-018-0498-3) contains supplementary material, which is available to authorized users.

Artificial Gene Amplification in Escherichia coli Reveals Numerous Determinants for Resistance to Metal Toxicity

When organisms are subjected to environmental challenges, including growth inhibitors and toxins, evolution often selects for the duplication of endogenous genes, whose overexpression can provide a selective advantage. Such events occur both in natural environments and in clinical settings. Microbial cells-with their large populations and short generation times-frequently evolve resistance to a range of antimicrobials. While microbial resistance to antibiotic drugs is well documented, less attention has been given to the genetic elements responsible for resistance to metal toxicity. To assess which overexpressed genes can endow gram-negative bacteria with resistance to metal toxicity, we transformed a collection of plasmids overexpressing all E. coli open reading frames (ORFs) into naive cells, and selected for survival in toxic concentrations of six transition metals: Cd, Co, Cu, Ni, Ag, Zn. These selections identified 48 hits. In each of these hits, the overexpression of an endogenous E. coli gene provided a selective advantage in the presence of at least one of the toxic metals. Surprisingly, the majority of these cases (28/48) were not previously known to function in metal resistance or homeostasis. These findings highlight the diverse mechanisms that biological systems can deploy to adapt to environments containing toxic concentrations of metals.

Advances in gap-filling genome-scale metabolic models and model-driven experiments lead to novel metabolic discoveries

With rapid improvements in next-generation sequencing technologies, our knowledge about metabolism of many organisms is rapidly increasing. However, gaps in metabolic networks exist due to incomplete knowledge (e.g., missing reactions, unknown pathways, unannotated and misannotated genes, promiscuous enzymes, and underground metabolic pathways). In this review, we discuss recent advances in gap-filling algorithms based on genome-scale metabolic models and the importance of both high-throughput experiments and detailed biochemical characterization, which work in concert with in silico methods, to allow a more accurate and comprehensive understanding of metabolism.

A two-step evolutionary process establishes a non-native vitamin B6 pathway in Bacillus subtilis

Pyridoxal 5'-phosphate (PLP), the most important form of vitamin B6 serves as a cofactor for many proteins. Two alternative pathways for de novo PLP biosynthesis are known: the short deoxy-xylulose-5-phosphate (DXP)-independent pathway, which is present in the Gram-positive model bacterium Bacillus subtilis and the longer DXP-dependent pathway, which has been intensively studied in the Gram-negative model bacterium Escherichia coli. Previous studies revealed that bacteria contain many promiscuous enzymes causing a so-called 'underground metabolism', which can be important for the evolution of novel pathways. Here, we evaluated the potential of B. subtilis to use a truncated non-native DXP-dependent PLP pathway from E. coli for PLP synthesis. Adaptive laboratory evolution experiments revealed that two non-native enzymes catalysing the last steps of the DXP-dependent PLP pathway and two genomic alterations are sufficient to allow growth of vitamin B6 auxotrophic bacteria as rapid as the wild type. Thus, the existence of an underground metabolism in B. subtilis facilitates the generation of a pathway for synthesis of PLP using parts of a non-native vitamin B6 pathway. The introduction of non-native enzymes into a metabolic network and rewiring of native metabolism could be helpful to generate pathways that might be optimized for producing valuable substances.

Emerging and evolving concepts in gene essentiality

Gene essentiality is a founding concept of genetics with important implications in both fundamental and applied research. Multiple screens have been performed over the years in bacteria, yeasts, animals and more recently in human cells to identify essential genes. A mounting body of evidence suggests that gene essentiality, rather than being a static and binary property, is both context dependent and evolvable in all kingdoms of life. This concept of a non-absolute nature of gene essentiality changes our fundamental understanding of essential biological processes and could directly affect future treatment strategies for cancer and infectious diseases.

Limitations of a metabolic network-based reverse ecology method for inferring host-pathogen interactions

Background

Host–pathogen interactions are important in a wide range of research fields. Given the importance of metabolic crosstalk between hosts and pathogens, a metabolic network-based reverse ecology method was proposed to infer these interactions. However, the validity of this method remains unclear because of the various explanations presented and the influence of potentially confounding factors that have thus far been neglected.

Results

We re-evaluated the importance of the reverse ecology method for evaluating host–pathogen interactions while statistically controlling for confounding effects using oxygen requirement, genome, metabolic network, and phylogeny data. Our data analyses showed that host–pathogen interactions were more strongly influenced by genome size, primary network parameters (e.g., number of edges), oxygen requirement, and phylogeny than the reserve ecology-based measures.

Conclusion

These results indicate the limitations of the reverse ecology method; however, they do not discount the importance of adopting reverse ecology approaches altogether. Rather, we highlight the need for developing more suitable methods for inferring host–pathogen interactions and conducting more careful examinations of the relationships between metabolic networks and host–pathogen interactions.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-017-1696-7) contains supplementary material, which is available to authorized users.

A Non-natural Protein Rescues Cells Deleted for a Key Enzyme in Central Metabolism

An important goal of synthetic biology is to create novel proteins that provide life-sustaining functions in living organisms. Recent attempts to produce novel proteins have focused largely on rational design involving significant computational efforts. In contrast, nature does not design sequences a priori. Instead, nature relies on Darwinian evolution to select biologically functional sequences from nondesigned sequence space. To mimic natural selection in the laboratory, we combed through libraries of novel sequences and selected proteins that rescue E. coli cells deleted for conditionally essential genes. One such gene, gltA, encodes citrate synthase, the enzyme responsible for metabolic entry into the citric acid cycle. The de novo protein SynGltA was isolated as a rescuer of ΔgltA. However, SynGltA is not an enzyme. Instead, SynGltA allows cells to recover from a defect in central carbon and energy metabolism by altering the regulation of an alternative metabolic pathway. Specifically, SynGltA dramatically enhances the expression of prpC, a gene encoding methylcitrate synthase in the propionate degradation pathway. This endogenous protein has promiscuous catalytic activity, which when overexpressed, compensates for the deletion of citrate synthase. While the molecular details responsible for this overexpression have not been elucidated, the results clearly demonstrate that non-natural proteins-unrelated to sequences in nature-can provide life-sustaining functions by altering gene regulation in natural organisms.

Elucidating dynamic metabolic physiology through network integration of quantitative time-course metabolomics

The increasing availability of metabolomics data necessitates novel methods for deeper data analysis and interpretation. We present a flux balance analysis method that allows for the computation of dynamic intracellular metabolic changes at the cellular scale through integration of time-course absolute quantitative metabolomics. This approach, termed "unsteady-state flux balance analysis" (uFBA), is applied to four cellular systems: three dynamic and one steady-state as a negative control. uFBA and FBA predictions are contrasted, and uFBA is found to be more accurate in predicting dynamic metabolic flux states for red blood cells, platelets, and Saccharomyces cerevisiae. Notably, only uFBA predicts that stored red blood cells metabolize TCA intermediates to regenerate important cofactors, such as ATP, NADH, and NADPH. These pathway usage predictions were subsequently validated through ¹³C isotopic labeling and metabolic flux analysis in stored red blood cells. Utilizing time-course metabolomics data, uFBA provides an accurate method to predict metabolic physiology at the cellular scale for dynamic systems.

A genome wide dosage suppressor network reveals genomic robustness

Genomic robustness is the extent to which an organism has evolved to withstand the effects of deleterious mutations. We explored the extent of genomic robustness in budding yeast by genome wide dosage suppressor analysis of 53 conditional lethal mutations in cell division cycle and RNA synthesis related genes, revealing 660 suppressor interactions of which 642 are novel. This collection has several distinctive features, including high co-occurrence of mutant-suppressor pairs within protein modules, highly correlated functions between the pairs and higher diversity of functions among the co-suppressors than previously observed. Dosage suppression of essential genes encoding RNA polymerase subunits and chromosome cohesion complex suggests a surprising degree of functional plasticity of macromolecular complexes, and the existence of numerous degenerate pathways for circumventing the effects of potentially lethal mutations. These results imply that organisms and cancer are likely able to exploit the genomic robustness properties, due the persistence of cryptic gene and pathway functions, to generate variation and adapt to selective pressures.

Refined experimental annotation reveals conserved corrinoid autotrophy in chloroform-respiring Dehalobacter isolates

Two novel chlorinated alkane-respiring Dehalobacter restrictus strains CF and DCA were isolated from the same enrichment culture, ACT-3, and characterized. The closed genomes of these highly similar sister strains were previously assembled from metagenomic sequence data and annotated. The isolation of the strains enabled experimental verification of predicted annotations, particularly focusing on irregularities or predicted gaps in central metabolic pathways and cofactor biosynthesis. Similar to D. restrictus strain PER-K23, strains CF and DCA require arginine, histidine and threonine for growth, although the corresponding biosynthesis pathways are predicted to be functional. Using strain CF to experimentally verify annotations, we determined that the predicted defective serine biosynthesis pathway can be rescued with a promiscuous serine hydroxymethyltransferase. Strain CF grew without added thiamine although the thiamine biosynthesis pathway is predicted to be absent; intracellular thiamine diphosphate, the cofactor of carboxylases in central metabolism, was not detected in cell extracts. Thus, strain CF may use amino acids to replenish central metabolites, portending entangled metabolite exchanges in ACT-3. Consistent with annotation, strain CF possesses a functional corrinoid biosynthesis pathway, demonstrated by increasing corrinoid content during growth and guided cobalamin biosynthesis in corrinoid-free medium. Chloroform toxicity to corrinoid-producing methanogens and acetogens may drive the conservation of corrinoid autotrophy in Dehalobacter strains. Heme detection in strain CF cell extracts suggests the 'archaeal' heme biosynthesis pathway also functions in anaerobic Firmicutes. This study reinforces the importance of incorporating enzyme promiscuity and cofactor availability in genome-scale functional predictions and identifies essential nutrient interdependencies in anaerobic dechlorinating microbial communities.

The Genome-Wide Interaction Network of Nutrient Stress Genes in Escherichia coli

Conventional efforts to describe essential genes in bacteria have typically emphasized nutrient-rich growth conditions. Of note, however, are the set of genes that become essential when bacteria are grown under nutrient stress. For example, more than 100 genes become indispensable when the model bacterium Escherichia coli is grown on nutrient-limited media, and many of these nutrient stress genes have also been shown to be important for the growth of various bacterial pathogens in vivo To better understand the genetic network that underpins nutrient stress in E. coli, we performed a genome-scale cross of strains harboring deletions in some 82 nutrient stress genes with the entire E. coli gene deletion collection (Keio) to create 315,400 double deletion mutants. An analysis of the growth of the resulting strains on rich microbiological media revealed an average of 23 synthetic sick or lethal genetic interactions for each nutrient stress gene, suggesting that the network defining nutrient stress is surprisingly complex. A vast majority of these interactions involved genes of unknown function or genes of unrelated pathways. The most profound synthetic lethal interactions were between nutrient acquisition and biosynthesis. Further, the interaction map reveals remarkable metabolic robustness in E. coli through pathway redundancies. In all, the genetic interaction network provides a powerful tool to mine and identify missing links in nutrient synthesis and to further characterize genes of unknown function in E. coli Moreover, understanding of bacterial growth under nutrient stress could aid in the development of novel antibiotic discovery platforms.

IMPORTANCE

With the rise of antibiotic drug resistance, there is an urgent need for new antibacterial drugs. Here, we studied a group of genes that are essential for the growth of Escherichia coli under nutrient limitation, culture conditions that arguably better represent nutrient availability during an infection than rich microbiological media. Indeed, many such nutrient stress genes are essential for infection in a variety of pathogens. Thus, the respective proteins represent a pool of potential new targets for antibacterial drugs that have been largely unexplored. We have created all possible double deletion mutants through a genetic cross of nutrient stress genes and the E. coli deletion collection. An analysis of the growth of the resulting clones on rich media revealed a robust, dense, and complex network for nutrient acquisition and biosynthesis. Importantly, our data reveal new genetic connections to guide innovative approaches for the development of new antibacterial compounds targeting bacteria under nutrient stress.

A comparative study of the evolution of cellobiose utilization in Escherichia coli and Shigella sonnei

The chb operon of Escherichia coli is involved in the utilization of chitooligosaccharides. While acquisition of two classes of mutations leading to altered regulation of the chb operon is necessary to confer the ability to utilize the glucose disaccharide cellobiose to wild-type strains of E. coli, in the closely related organism Shigella sonnei, Cel⁺ mutants arise relatively faster, requiring only a single mutational event. In Type I mutants, the insertion of IS600 at -21 leads to ChbR regulator-independent, constitutive expression of the operon. In Type II mutants, the insertion of IS2/600 within the distal binding site of the negative regulator NagC leads to ChbR-dependent cellobiose-inducible expression of the operon. These studies underscore the significance of strain background, specifically the diversity of transposable elements, in the evolution of novel metabolic functions. Constitutive expression of the chb operon also enables utilization of the aromatic β-glucosides arbutin and salicin, implying that the chb structural genes are inherently promiscuous.

Enhanced protein and biochemical production using CRISPRi-based growth switches

Production of proteins and biochemicals in microbial cell factories is often limited by carbon and energy spent on excess biomass formation. To address this issue, we developed several genetic growth switches based on CRISPR interference technology. We demonstrate that growth of Escherichia coli can be controlled by repressing the DNA replication machinery, by targeting dnaA and oriC, or by blocking nucleotide synthesis through pyrF or thyA. This way, total GFP-protein production could be increased by up to 2.2-fold. Single-cell dynamic tracking in microfluidic systems was used to confirm functionality of the growth switches. Decoupling of growth from production of biochemicals was demonstrated for mevalonate, a precursor for isoprenoid compounds. Mass yield of mevalonate was increased by 41%, and production was maintained for more than 45h after activation of the pyrF-based growth switch. The developed methods represent a promising approach for increasing production yield and titer for proteins and biochemicals.

Candidate Essential Genes in Burkholderia cenocepacia J2315 Identified by Genome-Wide TraDIS

Burkholderia cenocepacia infection often leads to fatal cepacia syndrome in cystic fibrosis patients. However, antibiotic therapy rarely results in complete eradication of the pathogen due to its intrinsic resistance to many clinically available antibiotics. Recent attention has turned to the identification of essential genes as the proteins encoded by these genes may serve as potential targets for development of novel antimicrobials. In this study, we utilized TraDIS (Transposon Directed Insertion-site Sequencing) as a genome-wide screening tool to facilitate the identification of B. cenocepacia genes essential for its growth and viability. A transposon mutant pool consisting of approximately 500,000 mutants was successfully constructed, with more than 400,000 unique transposon insertion sites identified by computational analysis of TraDIS datasets. The saturated library allowed for the identification of 383 genes that were predicted to be essential in B. cenocepacia. We extended the application of TraDIS to identify conditionally essential genes required for in vitro growth and revealed an additional repertoire of 439 genes to be crucial for B. cenocepacia growth under nutrient-depleted conditions. The library of B. cenocepacia mutants can subsequently be subjected to various biologically related conditions to facilitate the discovery of genes involved in niche adaptation as well as pathogenicity and virulence.

Mechanistic and Evolutionary Insights from the Reciprocal Promiscuity of Two Pyridoxal Phosphate-dependent Enzymes

Enzymes that utilize the cofactor pyridoxal 5′-phosphate play essential roles in amino acid metabolism in all organisms. The cofactor is used by proteins that adopt at least five different folds, which raises questions about the evolutionary processes that might explain the observed distribution of functions among folds. In this study, we show that a representative of fold type III, the Escherichia coli alanine racemase (ALR), is a promiscuous cystathionine β-lyase (CBL). Furthermore, E. coli CBL (fold type I) is a promiscuous alanine racemase. A single round of error-prone PCR and selection yielded variant ALR(Y274F), which catalyzes cystathionine β-elimination with a near-native Michaelis constant (K_m = 3.3 mm) but a poor turnover number (k_cat ≈10 h⁻¹). In contrast, directed evolution also yielded CBL(P113S), which catalyzes l-alanine racemization with a poor K_m (58 mm) but a high k_cat (22 s⁻¹). The structures of both variants were solved in the presence and absence of the l-alanine analogue, (R)-1-aminoethylphosphonic acid. As expected, the ALR active site was enlarged by the Y274F substitution, allowing better access for cystathionine. More surprisingly, the favorable kinetic parameters of CBL(P113S) appear to result from optimizing the pK_a of Tyr-111, which acts as the catalytic acid during l-alanine racemization. Our data emphasize the short mutational routes between the functions of pyridoxal 5′-phosphate-dependent enzymes, regardless of whether or not they share the same fold. Thus, they confound the prevailing model of enzyme evolution, which predicts that overlapping patterns of promiscuity result from sharing a common multifunctional ancestor.

Exometabolomics Assisted Design and Validation of Synthetic Obligate Mutualism

Synthetic microbial ecology has the potential to enhance the productivity and resiliency of biotechnology processes compared to approaches using single isolates. Engineering microbial consortia is challenging; however, one approach that has attracted significant attention is the creation of synthetic obligate mutualism using auxotrophic mutants that depend on each other for exchange or cross-feeding of metabolites. Here, we describe the integration of mutant library fitness profiling with mass spectrometry based exometabolomics as a method for constructing synthetic mutualism based on cross-feeding. Two industrially important species lacking known ecological interactions, Zymomonas mobilis and Escherichia coli, were selected as the test species. Amino acid exometabolites identified in the spent medium of Z. mobilis were used to select three corresponding E. coli auxotrophs (proA, pheA and IlvA), as potential E. coli counterparts for the coculture. A pooled mutant fitness assay with a Z. mobilis transposon mutant library was used to identify mutants with improved growth in the presence of E. coli. An auxotroph mutant in a gene (ZMO0748) with sequence similarity to cysteine synthase A (cysK), was selected as the Z. mobilis counterpart for the coculture. Exometabolomic analysis of spent E. coli medium identified glutathione related metabolites as potentially available for rescue of the Z. mobilis cysteine synthase mutant. Three sets of cocultures between the Z. mobilis auxotroph and each of the three E. coli auxotrophs were monitored by optical density for growth and analyzed by flow cytometry to confirm high cell counts for each species. Taken together, our methods provide a technological framework for creating synthetic mutualisms combining existing screening based methods and exometabolomics for both the selection of obligate mutualism partners and elucidation of metabolites involved in auxotroph rescue.

Rapid bursts and slow declines: on the possible evolutionary trajectories of enzymes

The evolution of enzymes is often viewed as following a smooth and steady trajectory, from barely functional primordial catalysts to the highly active and specific enzymes that we observe today. In this review, we summarize experimental data that suggest a different reality. Modern examples, such as the emergence of enzymes that hydrolyse human-made pesticides, demonstrate that evolution can be extraordinarily rapid. Experiments to infer and resurrect ancient sequences suggest that some of the first organisms present on the Earth are likely to have possessed highly active enzymes. Reconciling these observations, we argue that rapid bursts of strong selection for increased catalytic efficiency are interspersed with much longer periods in which the catalytic power of an enzyme erodes, through neutral drift and selection for other properties such as cellular energy efficiency or regulation. Thus, many enzymes may have already passed their catalytic peaks.

A protein constructed de novo enables cell growth by altering gene regulation

Recent advances in protein design rely on rational and computational approaches to create novel sequences that fold and function. In contrast, natural systems selected functional proteins without any design a priori. In an attempt to mimic nature, we used large libraries of novel sequences and selected for functional proteins that rescue Escherichia coli cells in which a conditionally essential gene has been deleted. In this way, the de novo protein SynSerB3 was selected as a rescuer of cells in which serB, which encodes phosphoserine phosphatase, an enzyme essential for serine biosynthesis, was deleted. However, SynSerB3 does not rescue the deleted activity by catalyzing hydrolysis of phosphoserine. Instead, SynSerB3 up-regulates hisB, a gene encoding histidinol phosphate phosphatase. This endogenous E. coli phosphatase has promiscuous activity that, when overexpressed, compensates for the deletion of phosphoserine phosphatase. Thus, the de novo protein SynSerB3 rescues the deletion of serB by altering the natural regulation of the His operon.

Ancestral Protein Reconstruction Yields Insights into Adaptive Evolution of Binding Specificity in Solute-Binding Proteins

The promiscuous functions of proteins are an important reservoir of functional novelty in protein evolution, but the molecular basis for binding promiscuity remains elusive. We used ancestral protein reconstruction to experimentally characterize evolutionary intermediates in the functional expansion of the polar amino acid-binding protein family, which has evolved to bind a variety of amino acids with high affinity and specificity. High-resolution crystal structures of an ancestral arginine-binding protein in complex with l-arginine and l-glutamine show that the promiscuous binding of l-glutamine is enabled by multi-scale conformational plasticity, water-mediated interactions, and selection of an alternative conformational substate productive for l-glutamine binding. Evolution of specialized glutamine-binding proteins from this ancestral protein was achieved by displacement of water molecules from the protein-ligand interface, reducing the entropic penalty associated with the promiscuous interaction. These results provide a structural and thermodynamic basis for the co-option of a promiscuous interaction in the evolution of binding specificity.

Long-Term Persistence of Bi-functionality Contributes to the Robustness of Microbial Life through Exaptation

Modern enzymes are highly optimized biocatalysts that process their substrates with extreme efficiency. Many enzymes catalyze more than one reaction; however, the persistence of such ambiguities, their consequences and evolutionary causes are largely unknown. As a paradigmatic case, we study the history of bi-functionality for a time span of approximately two billion years for the sugar isomerase HisA from histidine biosynthesis. To look back in time, we computationally reconstructed and experimentally characterized three HisA predecessors. We show that these ancient enzymes catalyze not only the HisA reaction but also the isomerization of a similar substrate, which is commonly processed by the isomerase TrpF in tryptophan biosynthesis. Moreover, we found that three modern-day HisA enzymes from Proteobacteria and Thermotogae also possess low TrpF activity. We conclude that this bi-functionality was conserved for at least two billion years, most likely without any evolutionary pressure. Although not actively selected for, this trait can become advantageous in the case of a gene loss. Such exaptation is exemplified by the Actinobacteria that have lost the trpF gene but possess the bi-functional HisA homolog PriA, which adopts the roles of both HisA and TrpF. Our findings demonstrate that bi-functionality can perpetuate in the absence of selection for very long time-spans.

The term exaptation describes the process by which a trait that is initially just a by-product of another function may become important in a later evolutionary phase. For example, feathers served to insulate dinosaurs before helping birds fly. On the level of enzymes, bi-functionality can contribute to microbial evolution through exaptation. However, bi-functional enzymes may cause metabolic conflicts, if they are involved in different metabolic pathways. By characterizing properties of modern and computationally reconstructed ancestral variants of the sugar isomerase HisA, we demonstrate that it has been a bi-functional enzyme for the last two billion years. Most likely, bi-functionality persisted because the remaining TrpF activity is not harmful or its elimination would concurrently compromise HisA activity. Moreover, this substrate ambiguity is advantageous, as it allows compensating a gene loss as exemplified by the Actinobacteria. These microbes have lost the isomerase TrpF but possess the bi-functional HisA homolog PriA, which takes over the roles of both HisA and TrpF. Our results argue to view bi-functionality not as an evolutionary disadvantage but rather as a contribution to the evolvability of novel functions via exaptation.

Systems-Wide Prediction of Enzyme Promiscuity Reveals a New Underground Alternative Route for Pyridoxal 5'-Phosphate Production in E. coli

Recent insights suggest that non-specific and/or promiscuous enzymes are common and active across life. Understanding the role of such enzymes is an important open question in biology. Here we develop a genome-wide method, PROPER, that uses a permissive PSI-BLAST approach to predict promiscuous activities of metabolic genes. Enzyme promiscuity is typically studied experimentally using multicopy suppression, in which over-expression of a promiscuous 'replacer' gene rescues lethality caused by inactivation of a 'target' gene. We use PROPER to predict multicopy suppression in Escherichia coli, achieving highly significant overlap with published cases (hypergeometric p = 4.4e-13). We then validate three novel predicted target-replacer gene pairs in new multicopy suppression experiments. We next go beyond PROPER and develop a network-based approach, GEM-PROPER, that integrates PROPER with genome-scale metabolic modeling to predict promiscuous replacements via alternative metabolic pathways. GEM-PROPER predicts a new indirect replacer (thiG) for an essential enzyme (pdxB) in production of pyridoxal 5'-phosphate (the active form of Vitamin B6), which we validate experimentally via multicopy suppression. We perform a structural analysis of thiG to determine its potential promiscuous active site, which we validate experimentally by inactivating the pertaining residues and showing a loss of replacer activity. Thus, this study is a successful example where a computational investigation leads to a network-based identification of an indirect promiscuous replacement of a key metabolic enzyme, which would have been extremely difficult to identify directly.

Essential Genome of the Metabolically Versatile Alphaproteobacterium Rhodopseudomonas palustris

Rhodopseudomonas palustris is an alphaproteobacterium that has served as a model organism for studies of photophosphorylation, regulation of nitrogen fixation, production of hydrogen as a biofuel, and anaerobic degradation of aromatic compounds. This bacterium is able to transition between anaerobic photoautotrophic growth, anaerobic photoheterotrophic growth, and aerobic heterotrophic growth. As a starting point to explore the genetic basis for the metabolic versatility of R. palustris, we used transposon mutagenesis and Tn-seq to identify 552 genes as essential for viability in cells growing aerobically on semirich medium. Of these, 323 have essential gene homologs in the alphaproteobacterium Caulobacter crescentus, and 187 have essential gene homologs in Escherichia coli. There were 24 R. palustris genes that were essential for viability under aerobic growth conditions that have low sequence identity but are likely to be functionally homologous to essential E. coli genes. As expected, certain functional categories of essential genes were highly conserved among the three organisms, including translation, ribosome structure and biogenesis, secretion, and lipid metabolism. R. palustris cells divide by budding in which a sessile cell gives rise to a motile swarmer cell. Conserved cell cycle genes required for this developmental process were essential in both C. crescentus and R. palustris. Our results suggest that despite vast differences in lifestyles, members of the alphaproteobacteria have a common set of essential genes that is specific to this group and distinct from that of gammaproteobacteria like E. coli.

IMPORTANCE

Essential genes in bacteria and other organisms are those absolutely required for viability. Rhodopseudomonas palustris has served as a model organism for studies of anaerobic aromatic compound degradation, hydrogen gas production, nitrogen fixation, and photosynthesis. We used the technique of Tn-seq to determine the essential genes of R. palustris grown under heterotrophic aerobic conditions. The transposon library generated in this study will be useful for future studies to identify R. palustris genes essential for viability under specialized growth conditions and also for survival under conditions of stress.

Habitat variability does not generally promote metabolic network modularity in flies and mammals

The evolution of species habitat range is an important topic over a wide range of research fields. In higher organisms, habitat range evolution is generally associated with genetic events such as gene duplication. However, the specific factors that determine habitat variability remain unclear at higher levels of biological organization (e.g., biochemical networks). One widely accepted hypothesis developed from both theoretical and empirical analyses is that habitat variability promotes network modularity; however, this relationship has not yet been directly tested in higher organisms. Therefore, I investigated the relationship between habitat variability and metabolic network modularity using compound and enzymatic networks in flies and mammals. Contrary to expectation, there was no clear positive correlation between habitat variability and network modularity. As an exception, the network modularity increased with habitat variability in the enzymatic networks of flies. However, the observed association was likely an artifact, and the frequency of gene duplication appears to be the main factor contributing to network modularity. These findings raise the question of whether or not there is a general mechanism for habitat range expansion at a higher level (i.e., above the gene scale). This study suggests that the currently widely accepted hypothesis for habitat variability should be reconsidered.

Rapid Increase in frequency of gene copy-number variants during experimental evolution in Caenorhabditis elegans

BACKGROUND

Gene copy-number variation (CNVs), which provides the raw material for the evolution of novel genes, is widespread in natural populations. We investigated whether CNVs constitute a common mechanism of genetic change during adaptation in experimental Caenorhabditis elegans populations. Outcrossing C. elegans populations with low fitness were evolved for >200 generations. The frequencies of CNVs in these populations were analyzed by oligonucleotide array comparative genome hybridization, quantitative PCR, PCR, DNA sequencing across breakpoints, and single-worm PCR.

RESULTS

Multiple duplications and deletions rose to intermediate or high frequencies in independent populations. Several lines of evidence suggest that these changes were adaptive: (i) copy-number changes reached high frequency or were fixed in a short time, (ii) many independent populations harbored CNVs spanning the same genes, and (iii) larger average size of CNVs in adapting populations relative to spontaneous CNVs. The latter is expected if larger CNVs are more likely to encompass genes under selection for a change in gene dosage. Several convergent CNVs originated in populations descended from different low fitness ancestors as well as high fitness controls.

CONCLUSIONS

We show that gene copy-number changes are a common class of adaptive genetic change. Due to the high rates of origin of spontaneous duplications and deletions, copy-number changes containing the same genes arose readily in independent populations. Duplications that reached high frequencies in these adapting populations were significantly larger in span. Many convergent CNVs may be general adaptations to laboratory conditions. These results demonstrate the great potential borne by CNVs for evolutionary adaptation.

Complete genome sequence, metabolic model construction and phenotypic characterization of Geobacillus LC300, an extremely thermophilic, fast growing, xylose-utilizing bacterium

We have isolated a new extremely thermophilic fast-growing Geobacillus strain that can efficiently utilize xylose, glucose, mannose and galactose for cell growth. When grown aerobically at 72 °C, Geobacillus LC300 has a growth rate of 2.15 h(-1) on glucose and 1.52 h(-1) on xylose (doubling time less than 30 min). The corresponding specific glucose and xylose utilization rates are 5.55 g/g/h and 5.24 g/g/h, respectively. As such, Geobacillus LC300 grows 3-times faster than E. coli on glucose and xylose, and has a specific xylose utilization rate that is 3-times higher than the best metabolically engineered organism to date. To gain more insight into the metabolism of Geobacillus LC300 its genome was sequenced using PacBio's RS II single-molecule real-time (SMRT) sequencing platform and annotated using the RAST server. Based on the genome annotation and the measured biomass composition a core metabolic network model was constructed. To further demonstrate the biotechnological potential of this organism, Geobacillus LC300 was grown to high cell-densities in a fed-batch culture, where cells maintained a high xylose utilization rate under low dissolved oxygen concentrations. All of these characteristics make Geobacillus LC300 an attractive host for future metabolic engineering and biotechnology applications.

The Impact of Non-Enzymatic Reactions and Enzyme Promiscuity on Cellular Metabolism during (Oxidative) Stress Conditions

Cellular metabolism assembles in a structurally highly conserved, but functionally dynamic system, known as the metabolic network. This network involves highly active, enzyme-catalyzed metabolic pathways that provide the building blocks for cell growth. In parallel, however, chemical reactivity of metabolites and unspecific enzyme function give rise to a number of side products that are not part of canonical metabolic pathways. It is increasingly acknowledged that these molecules are important for the evolution of metabolism, affect metabolic efficiency, and that they play a potential role in human disease—age-related disorders and cancer in particular. In this review we discuss the impact of oxidative and other cellular stressors on the formation of metabolic side products, which originate as a consequence of: (i) chemical reactivity or modification of regular metabolites; (ii) through modifications in substrate specificity of damaged enzymes; and (iii) through altered metabolic flux that protects cells in stress conditions. In particular, oxidative and heat stress conditions are causative of metabolite and enzymatic damage and thus promote the non-canonical metabolic activity of the cells through an increased repertoire of side products. On the basis of selected examples, we discuss the consequences of non-canonical metabolic reactivity on evolution, function and repair of the metabolic network.

Evolution of new functions de novo and from preexisting genes

How the enormous structural and functional diversity of new genes and proteins was generated (estimated to be 10(10)-10(12) different proteins in all organisms on earth [Choi I-G, Kim S-H. 2006. Evolution of protein structural classes and protein sequence families. Proc Natl Acad Sci 103: 14056-14061] is a central biological question that has a long and rich history. Extensive work during the last 80 years have shown that new genes that play important roles in lineage-specific phenotypes and adaptation can originate through a multitude of different mechanisms, including duplication, lateral gene transfer, gene fusion/fission, and de novo origination. In this review, we focus on two main processes as generators of new functions: evolution of new genes by duplication and divergence of pre-existing genes and de novo gene origination in which a whole protein-coding gene evolves from a noncoding sequence.

The proportion of genes in a functional category is linked to mass-specific metabolic rate and lifespan

Metabolic rate and lifespan are important biological parameters that are studied in a wide range of research fields. They are known to correlate with body mass, but their association with gene (protein) functions is poorly understood. In this study, we collected data on the metabolic rate and lifespan of various organisms and investigated the relationship of these parameters with their genomes. We showed that the proportion of genes in a functional category, but not genome size, was correlated with mass-specific metabolic rate and maximal lifespan. In particular, the proportion of genes in oxic reactions (which occur in the presence of oxygen) was significantly associated with these two biological parameters. Additionally, we found that temperature, taxonomy, and mode-of-life traits had little effect on the observed associations. Our findings emphasize the importance of considering the biological functions of genes when investigating the relationships between genome, metabolic rate, and lifespan. Moreover, this provides further insights into these relationships, and may be useful for estimating metabolic rate and lifespan in individuals and the ecosystem using a combination of body mass measurements and genomic data.

Dynamic metabolic engineering: New strategies for developing responsive cell factories

Metabolic engineering strategies have enabled improvements in yield and titer for a variety of valuable small molecules produced naturally in microorganisms, as well as those produced via heterologous pathways. Typically, the approaches have been focused on up- and downregulation of genes to redistribute steady-state pathway fluxes, but more recently a number of groups have developed strategies for dynamic regulation, which allows rebalancing of fluxes according to changing conditions in the cell or the fermentation medium. This review highlights some of the recently published work related to dynamic metabolic engineering strategies and explores how advances in high-throughput screening and synthetic biology can support development of new dynamic systems. Dynamic gene expression profiles allow trade-offs between growth and production to be better managed and can help avoid build-up of undesired intermediates. The implementation is more complex relative to static control, but advances in screening techniques and DNA synthesis will continue to drive innovation in this field.

Growth retardation of Escherichia coli by artificial increase of intracellular ATP

Overexpression of phosphoenolpyruvate carboxykinase (PCK) was reported to cause the harboring of higher intracellular ATP concentration in Escherichia coli, accompanied with a slower growth rate. For systematic determination of the relationship between the artificial increase of ATP and growth retardation, PCKWT enzyme was directly evolved in vitro and further overexpressed. The evolved PCK67 showed a 60% greater catalytic efficiency than that of PCKWT. Consequently, the PCK67-overexpressing E. coli showed the highest ATP concentration at the log phase of 1.45 μmol/gcell, with the slowest growth rate of 0.66 h(-1), while the PCKWT-overexpressing cells displayed 1.00 μmol/gcell ATP concentration with the growth rate of 0.84 h(-1) and the control had 0.28 μmol/gcell with 1.03 h(-1). To find a plausible reason, PCK-overexpressing cells in a steady state during chemostat growth were applied to monitor intracellular reactive oxygen species (ROS). Higher amount of intracellular ROS were observed as the ATP levels increased. To confirm the hypothesis of slower growth rate without perturbation of the carbon flux by PCK-overexpression, phototrophic Gloeobacter rhodopsin (GR) was expressed. The GR-expressing strain under illumination harbored 81% more ATP concentration along with 82% higher ROS, with a 54% slower maximum growth rate than the control, while both the GR-expressing strain under dark and dicarboxylate transporter (a control membrane protein)-expressing strain showed a lower ATP and increased ROS, and slower growth rate. Regardless of carbon flux changes, the artificial ATP increase was related to the ROS increase and it was reciprocally correlated to the maximum growth rate. To verify that the accumulated intracellular ROS were responsible for the growth retardation, glutathione was added to the medium to reduce the ROS. As a result, the growth retardation was restored by the addition of 0.1 mM glutathione. Anaerobic culture even enabled the artificial ATP-increased E. coli to grow faster than control. Collectively, it was concluded that artificial ATP increases inhibit the growth of E. coli due to the overproduction of ROS.

An alternate pathway of arsenate resistance in E. coli mediated by the glutathione S-transferase GstB

Microbial arsenate resistance is known to be conferred by specialized oxidoreductase enzymes termed arsenate reductases. We carried out a genetic selection on media supplemented with sodium arsenate for multicopy genes that can confer growth to E. coli mutant cells lacking the gene for arsenate reductase (E. coli ΔarsC). We found that overexpression of glutathione S-transferase B (GstB) complemented the ΔarsC allele and conferred growth on media containing up to 5 mM sodium arsenate. Interestingly, unlike wild type E. coli arsenate reductase, arsenate resistance via GstB was not dependent on reducing equivalents provided by glutaredoxins or a catalytic cysteine residue. Instead, two arginine residues, which presumably coordinate the arsenate substrate within the electrophilic binding site of GstB, were found to be critical for transferase activity. We provide biochemical evidence that GstB acts to directly reduce arsenate to arsenite with reduced glutathione (GSH) as the electron donor. Our results reveal a pathway for the detoxification of arsenate in bacteria that hinges on a previously undescribed function of a bacterial glutathione S-transferase.

Futile cycling increases sensitivity toward oxidative stress in Escherichia coli

Reactive oxygen species (ROS) are toxic molecules utilized by the immune system to combat invading pathogens. Recent evidence suggests that inefficiencies in ATP production or usage can lead to increased endogenous ROS production and sensitivity to oxidative stress in bacteria. With this as inspiration, and knowledge that ATP is required for a number of DNA repair mechanisms, we hypothesized that futile cycling would be an effective way to increase sensitivity to oxidative stress. We developed a mixed integer linear optimization framework to identify experimentally-tractable futile cycles, and confirmed metabolic modeling predictions that futile cycling depresses growth rate, and increases both O2 consumption and ROS production per biomass generated. Further, intracellular ATP was decreased and sensitivity to oxidative stress increased in all actively cycling strains compared to their catalytically inactive controls. This research establishes a fundamental connection between ATP metabolism, endogenous ROS production, and tolerance toward oxidative stress in bacteria.

Divergent evolution of a bifunctional de novo protein

Primordial proteins, the evolutionary ancestors of modern sequences, are presumed to have been minimally active and nonspecific. Following eons of selective pressure, these early progenitors evolved into highly active and specific proteins. While evolutionary trajectories from poorly active and multifunctional generalists toward highly active specialists likely occurred many times in evolutionary history, such pathways are difficult to reconstruct in natural systems, where primordial sequences are lost to time. To test the hypothesis that selection for enhanced activity leads to a loss of promiscuity, we evolved a de novo designed bifunctional protein. The parental protein, denoted Syn-IF, was chosen from a library of binary patterned 4-helix bundles. Syn-IF was shown previously to rescue two different auxotrophic strains of E. coli: ΔilvA and Δfes. These two strains contain deletions for proteins with very different biochemical functions; IlvA is involved in isoleucine biosynthesis, while Fes is involved in iron assimilation. In two separate experiments, Syn-IF, was evolved for faster rescue of either ΔilvA or Δfes. Following multiple rounds of mutagenesis, two new proteins were selected, each capable of rescuing the selected function significantly faster than the parental protein. In each case, the evolved protein also lost the ability to rescue the unselected function. In both evolutionary trajectories, the original bifunctional generalist was evolved into a monofunctional specialist with enhanced activity.

Evolution of aromatic β-glucoside utilization by successive mutational steps in Escherichia coli

The bglA gene of Escherichia coli encodes phospho-β-glucosidase A capable of hydrolyzing the plant-derived aromatic β-glucoside arbutin. We report that the sequential accumulation of mutations in bglA can confer the ability to hydrolyze the related aromatic β-glucosides esculin and salicin in two steps. In the first step, esculin hydrolysis is achieved through the acquisition of a four-nucleotide insertion within the promoter of the bglA gene, resulting in enhanced steady-state levels of the bglA transcript. In the second step, hydrolysis of salicin is achieved through the acquisition of a point mutation within the bglA structural gene close to the active site without the loss of the original catabolic activity against arbutin. These studies underscore the ability of microorganisms to evolve additional metabolic capabilities by mutational modification of preexisting genetic systems under selection pressure, thereby expanding their repertoire of utilizable substrates.

The redundant aminotransferases in lysine and arginine synthesis and the extent of aminotransferase redundancy in Escherichia coli

Aminotransferases can be redundant or promiscuous, but the extent and significance of these properties is not known in any organism, even in Escherichia coli. To determine the extent of redundancy, it was first necessary to identify the redundant aminotransferases in arginine and lysine synthesis, and then complement all aminotransferase-deficient mutants with genes for all aminotransferases. The enzymes with N-acetylornithine aminotransferase (ACOAT) activity in arginine synthesis were ArgD, AstC, GabT and PuuE; the major anaerobic ACOAT was ArgD. The major enzymes with N-succinyl-l,l-diaminopimelate aminotransferase (SDAP-AT) activity in lysine synthesis were ArgD, AstC, and SerC. Seven other aminotransferases, when overproduced, complemented the defect in a triple mutant. Lysine availability did not regulate synthesis of the major SDAP-ATs. Complementation analysis of mutants lacking aminotransferases showed that the SDAP-ATs and alanine aminotransferases were exceptionally redundant, and it is proposed that this redundancy may ensure peptidoglycan synthesis. An overview of all aminotransferase reactions indicates that redundancy and broad specificity are common properties of aminotransferases.

Molecular annotation of ketol-acid reductoisomerases from Streptomyces reveals a novel amino acid biosynthesis interlock mediated by enzyme promiscuity

The 6-phosphogluconate dehydrogenase superfamily oxidize and reduce a wide range of substrates, making their functional annotation challenging. Ketol-acid reductoisomerase (KARI), encoded by the ilvC gene in branched-chain amino acids biosynthesis, is a promiscuous reductase enzyme within this superfamily. Here, we obtain steady-state enzyme kinetic parameters for 10 IlvC homologues from the genera Streptomyces and Corynebacterium, upon eight selected chemically diverse substrates, including some not normally recognized by enzymes of this superfamily. This biochemical data suggested a Streptomyces biosynthetic interlock between proline and the branched-chain amino acids, mediated by enzyme substrate promiscuity, which was confirmed via mutagenesis and complementation analyses of the proC, ilvC1 and ilvC2 genes in Streptomyces coelicolor. Moreover, both ilvC orthologues and paralogues were analysed, such that the relationship between gene duplication and functional diversification could be explored. The KARI paralogues present in S. coelicolor and Streptomyces lividans, despite their conserved high sequence identity (97%), were shown to be more promiscuous, suggesting a recent functional diversification. In contrast, the KARI paralogue from Streptomyces viridifaciens showed selectivity towards the synthesis of valine precursors, explaining its recruitment within the biosynthetic gene cluster of valanimycin. These results allowed us to assess substrate promiscuity indices as a tool to annotate new molecular functions with metabolic implications.

Escherichia coli D-malate dehydrogenase, a generalist enzyme active in the leucine biosynthesis pathway

The enzymes of the β-decarboxylating dehydrogenase superfamily catalyze the oxidative decarboxylation of D-malate-based substrates with various specificities. Here, we show that, in addition to its natural function affording bacterial growth on D-malate as a carbon source, the D-malate dehydrogenase of Escherichia coli (EcDmlA) naturally expressed from its chromosomal gene is capable of complementing leucine auxotrophy in a leuB(-) strain lacking the paralogous isopropylmalate dehydrogenase enzyme. To our knowledge, this is the first example of an enzyme that contributes with a physiologically relevant level of activity to two distinct pathways of the core metabolism while expressed from its chromosomal locus. EcDmlA features relatively high catalytic activity on at least three different substrates (L(+)-tartrate, D-malate, and 3-isopropylmalate). Because of these properties both in vivo and in vitro, EcDmlA may be defined as a generalist enzyme. Phylogenetic analysis highlights an ancient origin of DmlA, indicating that the enzyme has maintained its generalist character throughout evolution. We discuss the implication of these findings for protein evolution.

Bacterial methionine biosynthesis

Methionine is essential in all organisms, as it is both a proteinogenic amino acid and a component of the cofactor, S-adenosyl methionine. The metabolic pathway for its biosynthesis has been extensively characterized in Escherichia coli; however, it is becoming apparent that most bacterial species do not use the E. coli pathway. Instead, studies on other organisms and genome sequencing data are uncovering significant diversity in the enzymes and metabolic intermediates that are used for methionine biosynthesis. This review summarizes the different biochemical strategies that are employed in the three key steps for methionine biosynthesis from homoserine (i.e. acylation, sulfurylation and methylation). A survey is presented of the presence and absence of the various biosynthetic enzymes in 1593 representative bacterial species, shedding light on the non-canonical nature of the E. coli pathway. This review also highlights ways in which knowledge of methionine biosynthesis can be utilized for biotechnological applications. Finally, gaps in the current understanding of bacterial methionine biosynthesis are noted. For example, the paper discusses the presence of one gene (metC) in a large number of species that appear to lack the gene encoding the enzyme for the preceding step in the pathway (metB), as it is understood in E. coli. Therefore, this review aims to move the focus away from E. coli, to better reflect the true diversity of bacterial pathways for methionine biosynthesis.

Metabolic networks are almost nonfractal: a comprehensive evaluation

Network self-similarity or fractality are widely accepted as an important topological property of metabolic networks; however, recent studies cast doubt on the reality of self-similarity in the networks. Therefore, we perform a comprehensive evaluation of metabolic network fractality using a box-covering method with an earlier version and the latest version of metabolic networks and demonstrate that the latest metabolic networks are almost self-dissimilar, while the earlier ones are fractal, as reported in a number of previous studies. This result may be because the networks were randomized because of an increase in network density due to database updates, suggesting that the previously observed network fractality was due to a lack of available data on metabolic reactions. This finding may not entirely discount the importance of self-similarity of metabolic networks. Rather, it highlights the need for a more suitable definition of network fractality and a more careful examination of self-similarity of metabolic networks.

Network-level architecture and the evolutionary potential of underground metabolism

A central unresolved issue in evolutionary biology is how metabolic innovations emerge. Low-level enzymatic side activities are frequent and can potentially be recruited for new biochemical functions. However, the role of such underground reactions in adaptation toward novel environments has remained largely unknown and out of reach of computational predictions, not least because these issues demand analyses at the level of the entire metabolic network. Here, we provide a comprehensive computational model of the underground metabolism in Escherichia coli. Most underground reactions are not isolated and 45% of them can be fully wired into the existing network and form novel pathways that produce key precursors for cell growth. This observation allowed us to conduct an integrated genome-wide in silico and experimental survey to characterize the evolutionary potential of E. coli to adapt to hundreds of nutrient conditions. We revealed that underground reactions allow growth in new environments when their activity is increased. We estimate that at least ∼20% of the underground reactions that can be connected to the existing network confer a fitness advantage under specific environments. Moreover, our results demonstrate that the genetic basis of evolutionary adaptations via underground metabolism is computationally predictable. The approach used here has potential for various application areas from bioengineering to medical genetics.

A genome-scale metabolic flux model of Escherichia coli K-12 derived from the EcoCyc database

BACKGROUND

Constraint-based models of Escherichia coli metabolic flux have played a key role in computational studies of cellular metabolism at the genome scale. We sought to develop a next-generation constraint-based E. coli model that achieved improved phenotypic prediction accuracy while being frequently updated and easy to use. We also sought to compare model predictions with experimental data to highlight open questions in E. coli biology.

RESULTS

We present EcoCyc-18.0-GEM, a genome-scale model of the E. coli K-12 MG1655 metabolic network. The model is automatically generated from the current state of EcoCyc using the MetaFlux software, enabling the release of multiple model updates per year. EcoCyc-18.0-GEM encompasses 1445 genes, 2286 unique metabolic reactions, and 1453 unique metabolites. We demonstrate a three-part validation of the model that breaks new ground in breadth and accuracy: (i) Comparison of simulated growth in aerobic and anaerobic glucose culture with experimental results from chemostat culture and simulation results from the E. coli modeling literature. (ii) Essentiality prediction for the 1445 genes represented in the model, in which EcoCyc-18.0-GEM achieves an improved accuracy of 95.2% in predicting the growth phenotype of experimental gene knockouts. (iii) Nutrient utilization predictions under 431 different media conditions, for which the model achieves an overall accuracy of 80.7%. The model's derivation from EcoCyc enables query and visualization via the EcoCyc website, facilitating model reuse and validation by inspection. We present an extensive investigation of disagreements between EcoCyc-18.0-GEM predictions and experimental data to highlight areas of interest to E. coli modelers and experimentalists, including 70 incorrect predictions of gene essentiality on glucose, 80 incorrect predictions of gene essentiality on glycerol, and 83 incorrect predictions of nutrient utilization.

CONCLUSION

Significant advantages can be derived from the combination of model organism databases and flux balance modeling represented by MetaFlux. Interpretation of the EcoCyc database as a flux balance model results in a highly accurate metabolic model and provides a rigorous consistency check for information stored in the database.

The EcoCyc Database

EcoCyc is a bioinformatics database available at EcoCyc.org that describes the genome and the biochemical machinery of Escherichia coli K-12 MG1655. The long-term goal of the project is to describe the complete molecular catalog of the E. coli cell, as well as the functions of each of its molecular parts, to facilitate a system-level understanding of E. coli. EcoCyc is an electronic reference source for E. coli biologists and for biologists who work with related microorganisms. The database includes information pages on each E. coli gene, metabolite, reaction, operon, and metabolic pathway. The database also includes information on E. coli gene essentiality and on nutrient conditions that do or do not support the growth of E. coli. The website and downloadable software contain tools for analysis of high-throughput data sets. In addition, a steady-state metabolic flux model is generated from each new version of EcoCyc. The model can predict metabolic flux rates, nutrient uptake rates, and growth rates for different gene knockouts and nutrient conditions. This review provides a detailed description of the data content of EcoCyc and of the procedures by which this content is generated.