Evidence of selection for low cognate amino acid bias in amino acid biosynthetic enzymes

A Theoretical Framework for Evolutionary Cell Biology

One of the last uncharted territories in evolutionary biology concerns the link with cell biology. Because all phenotypes ultimately derive from events at the cellular level, this connection is essential to building a mechanism-based theory of evolution. Given the impressive developments in cell biological methodologies at the structural and functional levels, the potential for rapid progress is great. The primary challenge for theory development is the establishment of a quantitative framework that transcends species boundaries. Two approaches to the problem are presented here: establishing the long-term steady-state distribution of mean phenotypes under specific regimes of mutation, selection, and drift and evaluating the energetic costs of cellular structures and functions. Although not meant to be the final word, these theoretical platforms harbor potential for generating insight into a diversity of unsolved problems, ranging from genome structure to cellular architecture to aspects of motility in organisms across the Tree of Life.

Ancestral Reconstruction of a Pre-LUCA Aminoacyl-tRNA Synthetase Ancestor Supports the Late Addition of Trp to the Genetic Code

The genetic code was likely complete in its current form by the time of the last universal common ancestor (LUCA). Several scenarios have been proposed for explaining the code's pre-LUCA emergence and expansion, and the relative order of the appearance of amino acids used in translation. One co-evolutionary model of genetic code expansion proposes that at least some amino acids were added to the code by the ancient divergence of aminoacyl-tRNA synthetase (aaRS) families. Of all the amino acids used within the genetic code, Trp is most frequently claimed as a relatively recent addition. We observe that, since TrpRS and TyrRS are paralogous protein families retaining significant sequence similarity, the inferred sequence composition of their ancestor can be used to evaluate this co-evolutionary model of genetic code expansion. We show that ancestral sequence reconstructions of the pre-LUCA paralog ancestor of TyrRS and TrpRS have several sites containing Tyr, yet a complete absence of sites containing Trp. This is consistent with the paralog ancestor being specific for the utilization of Tyr, with Trp being a subsequent addition to the genetic code facilitated by a process of aaRS divergence and neofunctionalization. Only after this divergence could Trp be specifically encoded and incorporated into proteins, including the TyrRS and TrpRS descendant lineages themselves. This early absence of Trp is observed under both homogeneous and non-homogeneous models of ancestral sequence reconstruction. Simulations support that this observed absence of Trp is unlikely to be due to chance or model bias. These results support that the final stages of genetic code evolution occurred well within the "protein world," and that the presence-absence of Trp within conserved sites of ancient protein domains is a likely measure of their relative antiquity, permitting the relative timing of extremely early events within protein evolution before LUCA.

Amino Acid metabolism conflicts with protein diversity

The 20 protein-coding amino acids are found in proteomes with different relative abundances. The most abundant amino acid, leucine, is nearly an order of magnitude more prevalent than the least abundant amino acid, cysteine. Amino acid metabolic costs differ similarly, constraining their incorporation into proteins. On the other hand, a diverse set of protein sequences is necessary to build functional proteomes. Here, we present a simple model for a cost-diversity trade-off postulating that natural proteomes minimize amino acid metabolic flux while maximizing sequence entropy. The model explains the relative abundances of amino acids across a diverse set of proteomes. We found that the data are remarkably well explained when the cost function accounts for amino acid chemical decay. More than 100 organisms reach comparable solutions to the trade-off by different combinations of proteome cost and sequence diversity. Quantifying the interplay between proteome size and entropy shows that proteomes can get optimally large and diverse.

Evolution of a genome-encoded bias in amino acid biosynthetic pathways is a potential indicator of amino acid dynamics in the environment

Overcoming the stress of starvation is one of an organism’s most challenging phenotypic responses. Those organisms that frequently survive the challenge, by virtue of their fitness, will have evolved genomes that are shaped by their specific environments. Understanding this genotype–environment–phenotype relationship at a deep level will require quantitative predictive models of the complex molecular systems that link these aspects of an organism’s existence. Here, we treat one of the most fundamental molecular systems, protein synthesis, and the amino acid biosynthetic pathways involved in the stringent response to starvation. These systems face an inherent logical dilemma: Building an amino acid biosynthetic pathway to synthesize its product—the cognate amino acid of the pathway—may require that very amino acid when it is no longer available. To study this potential “catch-22,” we have created a generic model of amino acid biosynthesis in response to sudden starvation. Our mathematical analysis and computational results indicate that there are two distinctly different outcomes: Partial recovery to a new steady state, or full system failure. Moreover, the cell’s fate is dictated by the cognate bias, the number of cognate amino acids in the corresponding biosynthetic pathway relative to the average number of that amino acid in the proteome. We test these implications by analyzing the proteomes of over 1,800 sequenced microbes, which reveals statistically significant evidence of low cognate bias, a genetic trait that would avoid the biosynthetic quandary. Furthermore, these results suggest that the pattern of cognate bias, which is readily derived by genome sequencing, may provide evolutionary clues to an organism’s natural environment.

Dynamic optimization identifies optimal programmes for pathway regulation in prokaryotes

To survive in fluctuating environmental conditions, microorganisms must be able to quickly react to environmental challenges by upregulating the expression of genes encoding metabolic pathways. Here we show that protein abundance and protein synthesis capacity are key factors that determine the optimal strategy for the activation of a metabolic pathway. If protein abundance relative to protein synthesis capacity increases, the strategies shift from the simultaneous activation of all enzymes to the sequential activation of groups of enzymes and finally to a sequential activation of individual enzymes along the pathway. In the case of pathways with large differences in protein abundance, even more complex pathway activation strategies with a delayed activation of low abundance enzymes and an accelerated activation of high abundance enzymes are optimal. We confirm the existence of these pathway activation strategies as well as their dependence on our proposed constraints for a large number of metabolic pathways in several hundred prokaryotes.

Chlamydia exploit the mammalian tryptophan-depletion defense strategy as a counter-defensive cue to trigger a survival state of persistence

We previously proposed that in Chlamydiaceae rapid vegetative growth and a quiescent state of survival (persistence) depend upon alternative protein translational profiles dictated by host tryptophan (Trp) availability. These alternative profiles correspond, respectively, with a set of chlamydial proteins having higher-than-predicted contents of Trp ("Up-Trp" selection), or with another set exhibiting lower-than-predicted contents of Trp ("Down-Trp" selection). A comparative evaluation of Chlamydiaceae proteomes for Trp content has now been extended to a number of other taxon families within the Chlamydiales Order. At the Order level, elevated Trp content occurs for transporters of nucleotides, S-adenosylmethionine (SAM), dicarboxylate substrates, and Trp itself. For Trp and nucleotide transporters, this is even more pronounced in other chlamydiae families (Parachlamydiaceae, Waddliaceae, and Simkaniaceae) due to extensive paralog expansion. This suggests that intracellular Trp availability served as an ancient survival cue for enhancement or restraint of chlamydial metabolism in the common Chlamydiales ancestor. The Chlamydiaceae Family further strengthened Up-Trp selection for proteins that function in cell division, lipopolysaccharide biosynthesis, and methyltransferase reactions. Some proteins that exhibit Up-Trp selection are uniquely present in the Chlamydiaceae, e.g., cytotoxin and the paralog families of polymorphic membrane proteins (Pmp's). A striking instance of Down-Trp selection in the Chlamydiaceae is the chorismate biosynthesis pathway and the connecting menaquinone pathway. The newly recognized 1,4-dihydroxy-6-napthoate pathway of menaquinone biosynthesis operates in Chlamydiaceae, whereas the classic 2-napthoate pathway is used in the other Chlamydiales families. Because of the extreme Down-Trp selection, it would appear that menaquinone biosynthesis is particularly important to the integrity of the persistent state maintained under conditions of severe Trp limitation, and may thus be critical for perpetuation of chronic disease states.

Relative amino acid composition signatures of organisms and environments

BACKGROUND

Identifying organism-environment interactions at the molecular level is crucial to understanding how organisms adapt to and change the chemical and molecular landscape of their habitats. In this work we investigated whether relative amino acid compositions could be used as a molecular signature of an environment and whether such a signature could also be observed at the level of the cellular amino acid composition of the microorganisms that inhabit that environment.

METHODOLOGIES/PRINCIPAL FINDINGS

To address these questions we collected and analyzed environmental amino acid determinations from the literature, and estimated from complete genomic sequences the global relative amino acid abundances of organisms that are cognate to the different types of environment. Environmental relative amino acid abundances clustered into broad groups (ocean waters, host-associated environments, grass land environments, sandy soils and sediments, and forest soils), indicating the presence of amino acid signatures specific for each environment. These signatures correlate to those found in organisms. Nevertheless, relative amino acid abundance of organisms was more influenced by GC content than habitat or phylogeny.

CONCLUSIONS

Our results suggest that relative amino acid composition can be used as a signature of an environment. In addition, we observed that the relative amino acid composition of organisms is not highly determined by environment, reinforcing previous studies that find GC content to be the major factor correlating to amino acid composition in living organisms.

Evolution of complete proteomes: guanine-cytosine pressure, phylogeny and environmental influences blend the proteomic architecture

Background

Guanine-cytosine (GC) composition is an important feature of genomes. Likewise, amino acid composition is a distinct, but less valued, feature of proteomes. A major concern is that it is not clear what valuable information can be acquired from amino acid composition data. To address this concern, in-depth analyses of the amino acid composition of the complete proteomes from 63 archaea, 270 bacteria, and 128 eukaryotes were performed.

Results

Principal component analysis of the amino acid matrices showed that the main contributors to proteomic architecture were genomic GC variation, phylogeny, and environmental influences. GC pressure drove positive selection on Ala, Arg, Gly, Pro, Trp, and Val, and adverse selection on Asn, Lys, Ile, Phe, and Tyr. The physico-chemical framework of the complete proteomes withstood GC pressure by frequency complementation of GC-dependent amino acid pairs with similar physico-chemical properties. Gln, His, Ser, and Val were responsible for phylogeny and their constituted components could differentiate archaea, bacteria, and eukaryotes. Environmental niche was also a significant factor in determining proteomic architecture, especially for archaea for which the main amino acids were Cys, Leu, and Thr. In archaea, hyperthermophiles, acidophiles, mesophiles, psychrophiles, and halophiles gathered successively along the environment-based principal component. Concordance between proteomic architecture and the genetic code was also related closely to genomic GC content, phylogeny, and lifestyles.

Conclusions

Large-scale analyses of the complete proteomes of a wide range of organisms suggested that amino acid composition retained the trace of GC variation, phylogeny, and environmental influences during evolution. The findings from this study will help in the development of a global understanding of proteome evolution, and even biological evolution.

Putrescine catabolism is a metabolic response to several stresses in Escherichia coli

Genes whose products degrade arginine and ornithine, precursors of putrescine synthesis, are activated by either regulators of the nitrogen-regulated (Ntr) response or σ(S) -RNA polymerase. To determine if dual control regulates a complete putrescine catabolic pathway, we examined expression of patA and patD, which specify the first two enzymes of one putrescine catabolic pathway. Assays of PatA (putrescine transaminase) activity and β-galactosidase from cells with patA-lacZ transcriptional and translational fusions indicate dual control of patA transcription and putrescine-stimulated patA translation. Similar assays for PatD indicate that patD transcription required σ(S) -RNA polymerase, and Nac, an Ntr regulator, enhanced the σ(S) -dependent transcription. Since Nac activation via σ(S) -RNA polymerase is without precedent, transcription with purified components was examined and the results confirmed this conclusion. This result indicates that the Ntr regulon can intrude into the σ(S) regulon. Strains lacking both polyamine catabolic pathways have defective responses to oxidative stress, high temperature and a sublethal concentration of an antibiotic. These defects and the σ(S) -dependent expression indicate that polyamine catabolism is a core metabolic response to stress.

Polymerization of non-complementary RNA: systematic symmetric nucleotide exchanges mainly involving uracil produce mitochondrial RNA transcripts coding for cryptic overlapping genes

Usual DNA→RNA transcription exchanges T→U. Assuming different systematic symmetric nucleotide exchanges during translation, some GenBank RNAs match exactly human mitochondrial sequences (exchange rules listed in decreasing transcript frequencies): C↔U, A↔U, A↔U+C↔G (two nucleotide pairs exchanged), G↔U, A↔G, C↔G, none for A↔C, A↔G+C↔U, and A↔C+G↔U. Most unusual transcripts involve exchanging uracil. Independent measures of rates of rare replicational enzymatic DNA nucleotide misinsertions predict frequencies of RNA transcripts systematically exchanging the corresponding misinserted nucleotides. Exchange transcripts self-hybridize less than other gene regions, self-hybridization increases with length, suggesting endoribonuclease-limited elongation. Blast detects stop codon depleted putative protein coding overlapping genes within exchange-transcribed mitochondrial genes. These align with existing GenBank proteins (mainly metazoan origins, prokaryotic and viral origins underrepresented). These GenBank proteins frequently interact with RNA/DNA, are membrane transporters, or are typical of mitochondrial metabolism. Nucleotide exchange transcript frequencies increase with overlapping gene densities and stop densities, indicating finely tuned counterbalancing regulation of expression of systematic symmetric nucleotide exchange-encrypted proteins. Such expression necessitates combined activities of suppressor tRNAs matching stops, and nucleotide exchange transcription. Two independent properties confirm predicted exchanged overlap coding genes: discrepancy of third codon nucleotide contents from replicational deamination gradients, and codon usage according to circular code predictions. Predictions from both properties converge, especially for frequent nucleotide exchange types. Nucleotide exchanging transcription apparently increases coding densities of protein coding genes without lengthening genomes, revealing unsuspected functional DNA coding potential.

Biochemical Systems Theory: A Review

Biochemical systems theory (BST) is the foundation for a set of analytical andmodeling tools that facilitate the analysis of dynamic biological systems. This paper depicts major developments in BST up to the current state of the art in 2012. It discusses its rationale, describes the typical strategies and methods of designing, diagnosing, analyzing, and utilizing BST models, and reviews areas of application. The paper is intended as a guide for investigators entering the fascinating field of biological systems analysis and as a resource for practitioners and experts.

The alternative translational profile that underlies the immune-evasive state of persistence in Chlamydiaceae exploits differential tryptophan contents of the protein repertoire

One form of immune evasion is a developmental state called "persistence" whereby chlamydial pathogens respond to the host-mediated withdrawal of L-tryptophan (Trp). A sophisticated survival mode of reversible quiescence is implemented. A mechanism has evolved which suppresses gene products necessary for rapid pathogen proliferation but allows expression of gene products that underlie the morphological and developmental characteristics of persistence. This switch from one translational profile to an alternative translational profile of newly synthesized proteins is proposed to be accomplished by maximizing the Trp content of some proteins needed for rapid proliferation (e.g., ADP/ATP translocase, hexose-phosphate transporter, phosphoenolpyruvate [PEP] carboxykinase, the Trp transporter, the Pmp protein superfamily for cell adhesion and antigenic variation, and components of the cell division pathway) while minimizing the Trp content of other proteins supporting the state of persistence. The Trp starvation mechanism is best understood in the human-Chlamydia trachomatis relationship, but the similarity of up-Trp and down-Trp proteomic profiles in all of the pathogenic Chlamydiaceae suggests that Trp availability is an underlying cue relied upon by this family of pathogens to trigger developmental transitions. The biochemically expensive pathogen strategy of selectively increased Trp usage to guide the translational profile can be leveraged significantly with minimal overall Trp usage by (i) regional concentration of Trp residue placements, (ii) amplified Trp content of a single protein that is required for expression or maturation of multiple proteins with low Trp content, and (iii) Achilles'-heel vulnerabilities of complex pathways to high Trp content of one or a few enzymes.

ANCAC: amino acid, nucleotide, and codon analysis of COGs--a tool for sequence bias analysis in microbial orthologs

BACKGROUND

The COG database is the most popular collection of orthologous proteins from many different completely sequenced microbial genomes. Per definition, a cluster of orthologous groups (COG) within this database exclusively contains proteins that most likely achieve the same cellular function. Recently, the COG database was extended by assigning to every protein both the corresponding amino acid and its encoding nucleotide sequence resulting in the NUCOCOG database. This extended version of the COG database is a valuable resource connecting sequence features with the functionality of the respective proteins.

RESULTS

Here we present ANCAC, a web tool and MySQL database for the analysis of amino acid, nucleotide, and codon frequencies in COGs on the basis of freely definable phylogenetic patterns. We demonstrate the usefulness of ANCAC by analyzing amino acid frequencies, codon usage, and GC-content in a species- or function-specific context. With respect to amino acids we, at least in part, confirm the cognate bias hypothesis by using ANCAC's NUCOCOG dataset as the largest one available for that purpose thus far.

CONCLUSIONS

Using the NUCOCOG datasets, ANCAC connects taxonomic, amino acid, and nucleotide sequence information with the functional classification via COGs and provides a GUI for flexible mining for sequence-bias. Thereby, to our knowledge, it is the only tool for the analysis of sequence composition in the light of physiological roles and phylogenetic context without requirement of substantial programming-skills.

Metabolic and translational efficiency in microbial organisms

Metabolic efficiency, as a selective force shaping proteomes, has been shown to exist in Escherichia coli and Bacillus subtilis and in a small number of organisms with photoautotrophic and thermophilic lifestyles. Earlier attempts at larger-scale analyses have utilized proxies (such as molecular weight) for biosynthetic cost, and did not consider lifestyle or auxotrophy. This study extends the analysis to all currently sequenced microbial organisms that are amenable to these analyses while utilizing lifestyle specific amino acid biosynthesis pathways (where possible) to determine protein production costs and compensating for auxotrophy. The tendency for highly expressed proteins (with adherence to codon usage bias as a proxy for expressivity) to utilize less biosynthetically expensive amino acids is taken as evidence of cost selection. A comprehensive analysis of sequenced genomes to identify those that exhibit strong translational efficiency bias (389 out of 1,700 sequenced organisms) is also presented.

Elemental economy: microbial strategies for optimizing growth in the face of nutrient limitation

Microorganisms play a dominant role in the biogeochemical cycling of nutrients. They are rightly praised for their facility for fixing both carbon and nitrogen into organic matter, and microbial driven processes have tangibly altered the chemical composition of the biosphere and its surrounding atmosphere. Despite their prodigious capacity for molecular transformations, microorganisms are powerless in the face of the immutability of the elements. Limitations for specific elements, either fleeting or persisting over eons, have left an indelible trace on microbial genomes, physiology, and their very atomic composition. We here review the impact of elemental limitation on microbes, with a focus on selected genetic model systems and representative microbes from the ocean ecosystem. Evolutionary adaptations that enhance growth in the face of persistent or recurrent elemental limitations are evident from genome and proteome analyses. These range from the extreme (such as dispensing with a requirement for a hard to obtain element) to the extremely subtle (changes in protein amino acid sequences that slightly, but significantly, reduce cellular carbon, nitrogen, or sulfur demand). One near-universal adaptation is the development of sophisticated acclimation programs by which cells adjust their chemical composition in response to a changing environment. When specific elements become limiting, acclimation typically begins with an increased commitment to acquisition and a concomitant mobilization of stored resources. If elemental limitation persists, the cell implements austerity measures including elemental sparing and elemental recycling. Insights into these fundamental cellular properties have emerged from studies at many different levels, including ecology, biological oceanography, biogeochemistry, molecular genetics, genomics, and microbial physiology. Here, we present a synthesis of these diverse studies and attempt to discern some overarching themes.

Bacterial growth rate reflects a bottleneck in resource allocation

BACKGROUND

Growth rate management in fast-growing bacteria is currently an active research area. In spite of the huge progress made in our understanding of the molecular mechanisms controlling the growth rate, fundamental questions concerning its intrinsic limitations are still relevant today. In parallel, systems biology claims that mathematical models could shed light on these questions.

METHODS

This review explores some possible reasons for the limitation of the growth rate in fast-growing bacteria, using a systems biology approach based on constraint-based modeling methods.

RESULTS

Recent experimental results and a new constraint-based modelling method named Resource Balance Analysis (RBA) reveal the existence of constraints on resource allocation between biological processes in bacterial cells. In this context, the distribution of a finite amount of resources between the metabolic network and the ribosomes limits the growth rate, which implies the existence of a bottleneck between these two processes. Any mechanism for saving resources increases the growth rate.

GENERAL SIGNIFICANCE

Consequently, the emergence of genetic regulation of metabolic pathways, e.g. catabolite repression, could then arise as a means to minimise the protein cost, i.e. maximising growth performance while minimising the resource allocation. This article is part of a Special Issue entitled Systems Biology of Microorganisms.

Sulfate-driven elemental sparing is regulated at the transcriptional and posttranscriptional levels in a filamentous cyanobacterium

Sulfur is an essential nutrient that can exist at growth-limiting concentrations in freshwater environments. The freshwater cyanobacterium Fremyella diplosiphon (also known as Tolypothrix sp. PCC 7601) is capable of remodeling the composition of its light-harvesting antennae, or phycobilisomes, in response to changes in the sulfur levels in its environment. Depletion of sulfur causes these cells to cease the accumulation of two forms of a major phycobilisome protein called phycocyanin and initiate the production of a third form of phycocyanin, which possesses a minimal number of sulfur-containing amino acids. Since phycobilisomes make up approximately 50% of the total protein in these cells, this elemental sparing response has the potential to significantly influence the fitness of this species under low-sulfur conditions. This response is specific for sulfate and occurs over the physiological range of sulfate concentrations likely to be encountered by this organism in its natural environment. F. diplosiphon has two separate sulfur deprivation responses, with low sulfate levels activating the phycobilisome remodeling response and low sulfur levels activating the chlorosis or bleaching response. The phycobilisome remodeling response results from changes in RNA abundance that are regulated at both the transcriptional and posttranscriptional levels. The potential of this response, and the more general bleaching response of cyanobacteria, to provide sulfur-containing amino acids during periods of sulfur deprivation is examined.

Economical evolution: microbes reduce the synthetic cost of extracellular proteins

Protein evolution is not simply a race toward improved function. Because organisms compete for limited resources, fitness is also affected by the relative economy of an organism’s proteome. Indeed, many abundant proteins contain relatively high percentages of amino acids that are metabolically less taxing for the cell to make, thus reducing cellular cost. However, not all abundant proteins are economical, and many economical proteins are not particularly abundant. Here we examined protein composition and found that the relative synthetic cost of amino acids constrains the composition of microbial extracellular proteins. In Escherichia coli, extracellular proteins contain, on average, fewer energetically expensive amino acids independent of their abundance, length, function, or structure. Economic pressures have strategically shaped the amino acid composition of multicomponent surface appendages, such as flagella, curli, and type I pili, and extracellular enzymes, including type III effector proteins and secreted serine proteases. Furthermore, in silico analysis of Pseudomonas syringae, Mycobacterium tuberculosis, Saccharomyces cerevisiae, and over 25 other microbes spanning a wide range of GC content revealed a broad bias toward more economical amino acids in extracellular proteins. The synthesis of any protein, especially those rich in expensive aromatic amino acids, represents a significant investment. Because extracellular proteins are lost to the environment and not recycled like other cellular proteins, they present a greater burden on the cell, as their amino acids cannot be reutilized during translation. We hypothesize that evolution has optimized extracellular proteins to reduce their synthetic burden on the cell.

Microbes secrete proteins to perform essential interactions with their environment, such as motility, pathogenesis, biofilm formation, and resource acquisition. However, because microbes generally lack protein import systems, secretion is often a one-way street. Consequently, secreted proteins are less likely to be recycled by the cell due to environmental loss. We demonstrate that evolution has in turn selected these extracellular proteins for increased economy at the level of their amino acid composition. Compared to their cellular counterparts, extracellular proteins have fewer synthetically expensive amino acids and more inexpensive amino acids. The resulting bias lessens the loss of cellular resources due to secretion. Furthermore, this economical bias was observed regardless of the abundance, length, structure, or function of extracellular proteins. Thus, it appears that economy may address the compositional bias seen in many extracellular proteins and deliver further insight into the forces driving their evolution.

Identifying quantitative operation principles in metabolic pathways: a systematic method for searching feasible enzyme activity patterns leading to cellular adaptive responses

BACKGROUND

Optimization methods allow designing changes in a system so that specific goals are attained. These techniques are fundamental for metabolic engineering. However, they are not directly applicable for investigating the evolution of metabolic adaptation to environmental changes. Although biological systems have evolved by natural selection and result in well-adapted systems, we can hardly expect that actual metabolic processes are at the theoretical optimum that could result from an optimization analysis. More likely, natural systems are to be found in a feasible region compatible with global physiological requirements.

RESULTS

We first present a new method for globally optimizing nonlinear models of metabolic pathways that are based on the Generalized Mass Action (GMA) representation. The optimization task is posed as a nonconvex nonlinear programming (NLP) problem that is solved by an outer-approximation algorithm. This method relies on solving iteratively reduced NLP slave subproblems and mixed-integer linear programming (MILP) master problems that provide valid upper and lower bounds, respectively, on the global solution to the original NLP. The capabilities of this method are illustrated through its application to the anaerobic fermentation pathway in Saccharomyces cerevisiae. We next introduce a method to identify the feasibility parametric regions that allow a system to meet a set of physiological constraints that can be represented in mathematical terms through algebraic equations. This technique is based on applying the outer-approximation based algorithm iteratively over a reduced search space in order to identify regions that contain feasible solutions to the problem and discard others in which no feasible solution exists. As an example, we characterize the feasible enzyme activity changes that are compatible with an appropriate adaptive response of yeast Saccharomyces cerevisiae to heat shock

CONCLUSION

Our results show the utility of the suggested approach for investigating the evolution of adaptive responses to environmental changes. The proposed method can be used in other important applications such as the evaluation of parameter changes that are compatible with health and disease states.

Amino acid metabolic origin as an evolutionary influence on protein sequence in yeast

The metabolic cycle of Saccharomyces cerevisiae consists of alternating oxidative (respiration) and reductive (glycolysis) energy-yielding reactions. The intracellular concentrations of amino acid precursors generated by these reactions oscillate accordingly, attaining maximal concentration during the middle of their respective yeast metabolic cycle phases. Typically, the amino acids themselves are most abundant at the end of their precursor's phase. We show that this metabolic cycling has likely biased the amino acid composition of proteins across the S. cerevisiae genome. In particular, we observed that the metabolic source of amino acids is the single most important source of variation in the amino acid compositions of functionally related proteins and that this signal appears only in (facultative) organisms using both oxidative and reductive metabolism. Periodically expressed proteins are enriched for amino acids generated in the preceding phase of the metabolic cycle. Proteins expressed during the oxidative phase contain more glycolysis-derived amino acids, whereas proteins expressed during the reductive phase contain more respiration-derived amino acids. Rare amino acids (e.g., tryptophan) are greatly overrepresented or underrepresented, relative to the proteomic average, in periodically expressed proteins, whereas common amino acids vary by a few percent. Genome-wide, we infer that 20,000 to 60,000 residues have been modified by this previously unappreciated pressure. This trend is strongest in ancient proteins, suggesting that oscillating endogenous amino acid availability exerted genome-wide selective pressure on protein sequences across evolutionary time.

An assessment of the impacts of molecular oxygen on the evolution of proteomes

Oxygen is not only one of life's essential elements but also a source of protein damage, mutagenesis, and ageing. Many proteome adaptations have been proposed to tackle such stresses and we assessed them using comparative genomics in a phylogenetic context. First, we find that aerobiosis is a trait with important phylogenetic inertia but that oxygen content in proteins is not. Instead, oxygen content is close to the expected values given the nucleotide composition. Accordingly, we find no evidence of oxygen being a scarce resource for protein synthesis even among anaerobes. Second, we searched for counterselection of amino acids more prone to oxidation among aerobes. Only cysteine follows the expected trend, whereas tryptophan follows the inverse one. When analyzing composition in the context of protein structures and residue accessibility, we find that all oxidable residues are avoided at the surface of proteins. Yet, there is no difference between aerobes and anaerobes in this respect, and the effect might be explained by the hydrophobicity of these residues. Third, we revisited the hypothesis that atmospheric enrichment in molecular oxygen led to the development of the communication capabilities of eukaryotes. With a larger data set and adequate controls, we confirm the trend of longer oxygen-rich outer domains in transmembrane proteins of eukaryotes. Yet, we find no significant association between oxygen concentration in the environment and this trait within prokaryotes, suggesting that this difference is clade specific and independent of oxygen availability. We find that genes involved in cellular responses to oxygen are much more frequent among aerobes, and we suggest that they erase most expected differences in terms of proteome composition between organisms facing high and low oxygen concentrations.

Evolutionarily conserved optimization of amino acid biosynthesis

The "cognate bias hypothesis" states that early in evolutionary history the biosynthetic enzymes for amino acid x gradually lost residues of x, thereby reducing the threshold for deleterious effects of x scarcity. The resulting reduction in cognate amino acid composition of the enzymes comprising a particular amino acid biosynthetic pathway is predicted to confer a selective growth advantage on cells. Bioinformatic evidence from protein-sequence data of two bacterial species previously demonstrated reduced cognate bias in amino acid biosynthetic pathways. Here we show that cognate bias in amino acid biosynthesis is present in the other domains of life-Archaebacteria and Eukaryota. We also observe evolutionarily conserved underrepresentations (e.g., glycine in methionine biosynthesis) and overrepresentations (e.g., tryptophan in asparagine biosynthesis) of amino acids in noncognate biosynthetic pathways, which can be explained by secondary amino acid metabolism. Additionally, we experimentally validate the cognate bias hypothesis using the yeast Saccharomyces cerevisiae. Specifically, we show that the degree to which growth declines following amino acid deprivation is negatively correlated with the degree to which an amino acid is underrepresented in the enzymes that comprise its cognate biosynthetic pathway. Moreover, we demonstrate that cognate fold representation is more predictive of growth advantage than a host of other potential growth-limiting factors, including an amino acid's metabolic cost or its intracellular concentration and compartmental distribution.

Modelling the evolution of the archeal tryptophan synthase

Background

Microorganisms and plants are able to produce tryptophan. Enzymes catalysing the last seven steps of tryptophan biosynthesis are encoded in the canonical trp operon. Among the trp genes are most frequently trpA and trpB, which code for the alpha and beta subunit of tryptophan synthase. In several prokaryotic genomes, two variants of trpB (named trpB1 or trpB2) occur in different combinations. The evolutionary history of these trpB genes is under debate.

Results

In order to study the evolution of trp genes, completely sequenced archeal and bacterial genomes containing trpB were analysed. Phylogenetic trees indicated that TrpB sequences constitute four distinct groups; their composition is in agreement with the location of respective genes. The first group consisted exclusively of trpB1 genes most of which belonged to trp operons. Groups two to four contained trpB2 genes. The largest group (trpB2_o) contained trpB2 genes all located outside of operons. Most of these genes originated from species possessing an operon-based trpB1 in addition. Groups three and four pertain to trpB2 genes of those genomes containing exclusively one or two trpB2 genes, but no trpB1. One group (trpB2_i) consisted of trpB2 genes located inside, the other (trpB2_a) of trpB2 genes located outside the trp operon. TrpA and TrpB form a heterodimer and cooperate biochemically. In order to characterise trpB variants and stages of TrpA/TrpB cooperation in silico, several approaches were combined. Phylogenetic trees were constructed for all trp genes; their structure was assessed via bootstrapping. Alternative models of trpB evolution were evaluated with parsimony arguments. The four groups of trpB variants were correlated with archeal speciation. Several stages of TrpA/TrpB cooperation were identified and trpB variants were characterised. Most plausibly, trpB2 represents the predecessor of the modern trpB gene, and trpB1 evolved in an ancestral bacterium.

Conclusion

In archeal genomes, several stages of trpB evolution, TrpA/TrpB cooperation, and operon formation can be observed. Thus, archeal trp genes may serve as a model system for studying the evolution of protein-protein interactions and operon formation.

Evolution of protein lipograms: A bioinformatics problem

A protein lacking one of the 20 common amino acids is a protein lipogram. This open-ended problem-based learning assignment deals with the evolution of proteins with biased amino acid composition. It has students query protein and metabolic databases to test the hypothesis that natural selection has reduced the frequency of each amino acid specifically in the enzymes required for its biosynthesis. Student groups work in parallel on different amino acids and share strategies. Aside from content objectives that integrate knowledge of protein structure, function, synthesis, and evolution, this problem incorporates oral and written presentations, statistical analysis, and substantial decision making. The point of the problem described here is that a deficiency or absence of a particular amino acid in a protein may be more than a chance occurrence and may be driven by natural selection. The challenge is to demonstrate the difference.

Regulation of tryptophan operon expression in the archaeon Methanothermobacter thermautotrophicus

Conserved trp genes encode enzymes that catalyze tryptophan biosynthesis in all three biological domains, and studies of their expression in Bacteria and eukaryotes have revealed a variety of different regulatory mechanisms. The results reported here provide the first detailed description of an archaeal trp gene regulatory system. We have established that the trpEGCFBAD operon in Methanothermobacter thermautotrophicus is transcribed divergently from a gene (designated trpY) that encodes a tryptophan-sensitive transcription regulator. TrpY binds to TRP box sequences (consensus, TGTACA) located in the overlapping promoter regions between trpY and trpE, inhibiting trpY transcription in the absence of tryptophan and both trpY and trpEGCFBAD transcription in the presence of tryptophan. TrpY apparently inhibits trpY transcription by blocking RNA polymerase access to the site of trpY transcription initiation and represses trpEGCFBAD transcription by preventing TATA box binding protein (TBP) binding to the TATA box sequence. Given that residue 2 (W2) is the only tryptophan in TrpY and in TrpY homologues in other Euryarchaea and that there is only one tryptophan codon in the entire trpEGCFBAD operon (trpB encodes W175), expression of the trp operon may also be regulated in vivo by the supply of charged tRNA(Trp) available to translate the second codon of the trpY mRNA.