Molecular evolution of protein atomic composition

Stoichiogenomics: the evolutionary ecology of macromolecular elemental composition

The new field of 'stoichiogenomics' integrates evolution, ecology and bioinformatics to reveal surprising patterns of the differential usage of key elements [e.g. nitrogen (N)] in proteins and nucleic acids. Because the canonical amino acids as well as nucleotides differ in element counts, natural selection owing to limited element supplies might bias monomer usage to reduce element costs. For example, proteins that respond to N limitation in microbes use a lower proportion of N-rich amino acids, whereas proteome- and transcriptome-wide element contents differ significantly for plants as compared with animals, probably because of the differential severity of element limitations. In this review, we show that with these findings, new directions for future investigations are emerging, particularly via the increasing availability of diverse metagenomic and metatranscriptomic data sets.

A novel approach for determining environment-specific protein costs: the case of Arabidopsis thaliana

Motivation: Comprehensive understanding of cellular processes requires development of approaches which consider the energetic balances in the cell. The existing approaches that address this problem are based on defining energy-equivalent costs which do not include the effects of a changing environment. By incorporating these effects, one could provide a framework for integrating ‘omics’ data from various levels of the system in order to provide interpretations with respect to the energy state and to elicit conclusions about putative global energy-related response mechanisms in the cell.

Results: Here we define a cost measure for amino acid synthesis based on flux balance analysis of a genome-scale metabolic network, and develop methods for its integration with proteomics and metabolomics data. This is a first measure which accounts for the effect of different environmental conditions. We applied this approach to a genome-scale network of Arabidopsis thaliana and calculated the costs for all amino acids and proteins present in the network under light and dark conditions. Integration of function and process ontology terms in the analysis of protein abundances and their costs indicates that, during the night, the cell favors cheaper proteins compared with the light environment. However, this does not imply that there is squandering of resources during the day. The results from the association analysis between the costs, levels and well-defined expenses of amino acid synthesis, indicate that our approach not only captures the adjustment made at the switch of conditions, but also could explain the anticipation of resource usage via a global energy-related regulatory mechanism of amino acid and protein synthesis.

Contact:nikoloski@mpimp-golm.mpg.de

Supplementary information:Supplementary data are available at Bioinformatics online.

Global regulation of gene expression in response to cysteine availability in Clostridium perfringens

Background

Cysteine has a crucial role in cellular physiology and its synthesis is tightly controlled due to its reactivity. However, little is known about the sulfur metabolism and its regulation in clostridia compared with other firmicutes. In Clostridium perfringens, the two-component system, VirR/VirS, controls the expression of the ubiG operon involved in methionine to cysteine conversion in addition to the expression of several toxin genes. The existence of links between the C. perfringens virulence regulon and sulfur metabolism prompted us to analyze this metabolism in more detail.

Results

We first performed a tentative reconstruction of sulfur metabolism in C. perfringens and correlated these data with the growth of strain 13 in the presence of various sulfur sources. Surprisingly, C. perfringens can convert cysteine to methionine by an atypical still uncharacterized pathway. We further compared the expression profiles of strain 13 after growth in the presence of cystine or homocysteine that corresponds to conditions of cysteine depletion. Among the 177 genes differentially expressed, we found genes involved in sulfur metabolism and controlled by premature termination of transcription via a cysteine specific T-box system (cysK-cysE, cysP1 and cysP2) or an S-box riboswitch (metK and metT). We also showed that the ubiG operon was submitted to a triple regulation by cysteine availability via a T-box system, by the VirR/VirS system via the VR-RNA and by the VirX regulatory RNA.

In addition, we found that expression of pfoA (theta-toxin), nagL (one of the five genes encoding hyaluronidases) and genes involved in the maintenance of cell redox status was differentially expressed in response to cysteine availability. Finally, we showed that the expression of genes involved in [Fe-S] clusters biogenesis and of the ldh gene encoding the lactate dehydrogenase was induced during cysteine limitation.

Conclusion

Several key functions for the cellular physiology of this anaerobic bacterium were controlled in response to cysteine availability. While most of the genes involved in sulfur metabolism are regulated by premature termination of transcription, other still uncharacterized mechanisms of regulation participated in the induction of gene expression during cysteine starvation.

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.

Transcriptional plasticity through differential assembly of a multiprotein activation complex

Cell adaptation to the environment often involves induction of complex gene expression programs under the control of specific transcriptional activators. For instance, in response to cadmium, budding yeast induces transcription of the sulfur amino acid biosynthetic genes through the basic-leucine zipper activator Met4, and also launches a program of substitution of abundant glycolytic enzymes by isozymes with a lower content in sulfur. We demonstrate here that transcriptional induction of PDC6, which encodes a pyruvate decarboxylase isoform with low sulfur content, is directly controlled by Met4 and its DNA-binding cofactors the basic-helix-loop-helix protein Cbf1 and the two homologous zinc finger proteins Met31 and Met32. Study of Cbf1 and Met31/32 association with PDC6 allowed us to find a new mechanism of recruitment of Met4, which allows PDC6 being differentially regulated compared to sulfur amino acid biosynthetic genes. Our findings provide a new example of mechanism allowing transcriptional plasticity within a regulatory network thanks to a definite toolbox comprising a unique master activator and several dedicated DNA-binding cofactors. We also show evidence suggesting that integration of PDC6 to the Met4 regulon may have occurred recently in the evolution of the Saccharomyces cerevisiae lineage.

Dissection of combinatorial control by the Met4 transcriptional complex

Met4 is the transcriptional activator of the sulfur metabolic network in Saccharomyces cerevisiae. Lacking DNA-binding ability, Met4 must interact with proteins called Met4 cofactors to target promoters for transcription. Two types of DNA-binding cofactors (Cbf1 and Met31/Met32) recruit Met4 to promoters and one cofactor (Met28) stabilizes the DNA-bound Met4 complexes. To dissect this combinatorial system, we systematically deleted each category of cofactor(s) and analyzed Met4-activated transcription on a genome-wide scale. We defined a core regulon for Met4, consisting of 45 target genes. Deletion of both Met31 and Met32 eliminated activation of the core regulon, whereas loss of Met28 or Cbf1 interfered with only a subset of targets that map to distinct sectors of the sulfur metabolic network. These transcriptional dependencies roughly correlated with the presence of Cbf1 promoter motifs. Quantitative analysis of in vivo promoter binding properties indicated varying levels of cooperativity and interdependency exists between members of this combinatorial system. Cbf1 was the only cofactor to remain fully bound to target promoters under all conditions, whereas other factors exhibited different degrees of regulated binding in a promoter-specific fashion. Taken together, Met4 cofactors use a variety of mechanisms to allow differential transcription of target genes in response to various cues.

Evolutionary formation of new protein folds is linked to metallic cofactor recruitment

To explore whether the generation of new protein folds could be linked to metallic cofactor recruitment, we identified the oldest examples of folds for manganese, iron, zinc, and copper proteins by analyzing their fold-domain mapping patterns. We discovered that the generation of these folds was tightly coupled to corresponding metals. We found that the emerging order for these folds, i.e., manganese and iron protein folds appeared earlier than zinc and copper counterparts, coincides with the putative bioavailability of the corresponding metals in the ancient anoxic ocean. Therefore, we conclude that metallic cofactors, like organic cofactors, play an evolutionary role in the formation of new protein folds. This link could be explained by the emergence of protein structures with novel folds that could fulfill the new protein functions introduced by the metallic cofactors. These findings not only have important implications for understanding the evolutionary mechanisms of protein architectures, but also provide a further interpretation for the evolutionary story of superoxide dismutases.

Signatures of nitrogen limitation in the elemental composition of the proteins involved in the metabolic apparatus

Nitrogen (N) is a fundamental component of nucleotides and amino acids and is often a limiting nutrient in natural ecosystems. Thus, study of the N content of biomolecules may establish important connections between ecology and genomics. However, while significant differences in the elemental composition of whole organisms are well documented, how the flux of nutrients in the cell has shaped the evolution of different cellular processes remains poorly understood. By examining the elemental composition of major functional classes of proteins in four multicellular eukaryotic model organisms, we find that the catabolic machinery shows substantially lower N content than the anabolic machinery and the rest of the proteome. This pattern suggests that ecological selection for N conservation specifically targets cellular components that are highly expressed in response to nutrient limitation. We propose that the RNA component of the anabolic machineries is the mechanistic force driving the elemental imbalance we found, and that RNA functions as an intracellular nutrient reservoir that is degraded and recycled during starvation periods. A comparison of the elemental composition of the anabolic and catabolic machineries in species that have experienced different levels of N limitation in their evolutionary history (animals versus plants) suggests that selection for N conservation has preferentially targeted the catabolic machineries of plants, resulting in a lower N content of the proteins involved in their catabolic processes. These findings link the composition of major cellular components to the environmental factors that trigger the activation of those components, suggesting that resource availability has constrained the atomic composition and the molecular architecture of the biotic processes that enable cells to respond to reduced nutrient availability.

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.

Ecological nitrogen limitation shapes the DNA composition of plant genomes

Phenotypes and behaviors respond to resource constraints via adaptation, but the influence of ecological limitations on the composition of eukaryotic genomes is still unclear. We trace connections between plant ecology and genomes through their elemental composition. Inorganic sources of nitrogen (N) are severely limiting to plants in natural ecosystems. This constraint would favor the use of N-poor nucleotides in plant genomes. We show that the transcribed segments of undomesticated plant genomes are the most N poor, with genomes and proteomes bearing signatures of N limitation. Consistent with the predictions of natural selection for N conservation, the precursors of transcriptome show the greatest deviations from Chargaff's second parity rule. Furthermore, crops show higher N contents than undomesticated plants, likely due to the relaxation of natural selection owing to the use of N-rich fertilizers. These findings indicate a fundamental role of N limitation in the evolution of plant genomes, and they link the genomes with the ecosystem context within which biota evolve.

Low contents of carbon and nitrogen in highly abundant proteins: evidence of selection for the economy of atomic composition

Proteins that assimilate particular elements were found to avoid using amino acids containing the element, which indicates that the metabolic constraints of amino acids may influence the evolution of proteins. We suspected that low contents of carbon, nitrogen, and sulfur may also be selected for economy in highly abundant proteins that consume large amounts of the resources of cells. By analyzing recently available proteomic data in Escherichia coli, Saccharomyces cerevisiae, and Schizosaccharomyces pombe, we found that at least the carbon and nitrogen contents in amino acid side chains are negatively correlated with protein abundance. An amino acid with a high number of carbon atoms in its side chain generally requires relatively more energy for its synthesis. Thus, it may be selected against in highly abundant proteins either because of economy in building blocks or because of economy in energy. Previous studies showed that highly abundant proteins preferentially use cheap (in terms of energy) amino acids. We found that the carbon content is still negatively correlated with protein abundance after controlling for the energetic cost of the amino acids. However, the negative correlation between protein abundance and energetic cost disappeared after controlling for carbon content. Building blocks seem to be more restricted than energy. It seems that the amino acid sequences of highly abundant proteins have to compromise between optimization for their biological functions and reducing the consumption of limiting resources. By contrast, the amino acid sequences of weakly expressed proteins are more likely to be optimized for their biological functions.

Association between the availability of environmental resources and the atomic composition of organismal proteomes: evidence from Prochlorococcus strains living at different depths

The cyanobacteria Prochlorococcus is a cyanbacterial genus, with some strains adapted to sea surface environments, which are poor in nutrients and have high-light intensity, and some strains adapted to deep sea conditions, which have relatively higher concentrations of nitrogen and phosphorus and lower light intensity. Here, we report pairwise comparisons between strains isolated from different depths of the same sea, which reveal a close association between atomic composition of the proteome and the availability nitrogen and phosphorus in the environment. The atomic composition of proteomes differs significantly among Prochlorococcus strains with different supplies of nitrogen in vivo; these different supplies result from different capacities for nitrogen assimilation. We repeated our whole-proteome analysis with the core proteomes of Prochlorococcus and obtained similar results. Our findings indicate that the elemental composition of proteomes is shaped by the availability of resources in the environment.

Tracking the molecular evolution of photosynthesis through characterization of atomic contents of the photosynthetic units

Oxygen molecules have a great impact on protein evolution. We have performed a comparative study of key photosynthetic proteins in order to seek the answer to the question; did the evolutionary substitution of oxygen- and nitrogen-containing residues in the photosynthetic proteins correspond to nutrient constraints and metabolic optimization? The D1 peptide in RC II complexes has higher oxygen-containing amino acid residues and PufL/PufM have lower oxygen content in their peptides. In this article, we also discuss the possible influences of micro-environment and the available nutrients on the protein structure and their atomic distribution.

Do phosphorus requirements for RNA limit genome size in crustacean zooplankton?

As for most other organisms, genome size in zooplankton differs widely. This may have a range of consequences for growth rate, development, and life history strategies, yet the causes of this pronounced variability are not settled. Here we propose that small genome size may be an evolutionary consequence of phosphorus (P) allocation from DNA to RNA under P deficiency. To test this hypothesis we have compared the two major groups of zooplankton, copepods and cladocerans, that have overlapping niches and body size. Relative to the cladocerans, copepods have a more complex life history and a lower mass-specific P content, while cladocerans tend to have higher P and RNA contents and higher specific growth rates and frequently experience P-limited growth, likely due to a shortage of P for ribosome synthesis. Cladocerans also generally have smaller genomes than copepods (1C = 0.17–0.63 pg DNA·cell–1vs. 1C = 0.10–10 pg DNA·cell–1). Furthermore, cladocerans have a higher slope of the relationship of body size with DNA content (1.5 vs. 0.28 in copepods) and present almost 15-fold higher RNA:DNA ratios (24.8 in cladocerans vs. 1.6 in copepods). Hence, small genome size in cladocerans could reflect an evolutionary pressure towards “efficient” genomes to conserve a key element needed to maximize growth rate. We do not claim that this is a universal cause of genome size variability, but propose that streamlining of genomes could be related to P conservation rather than energy conservation. This could be relevant for a range of organisms that may suffer P-limited growth rates.

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.

[Stoichiometric, my dear Watson!]

Living organisms can be seen as complex chemicals interacting with their environment through chemical reactions. As such, they are subjected to the laws of stoichiometry: their constitutive elements (atoms) cannot be created (they must be found in their environment) nor destroyed. Acknowledging these rules led ecologists to the concept of "biological stoichiometry". In this review, I want to show that combining (1) the study of the elemental composition of biopolymers and (2) the ecologist's point of view, particularly the concept of biological stoichiometry, benefits molecular biology. In particular, this coupled approach unveils parts of the history of organisms, helps interpreting transcriptional profiles and sheds a different light on the growth of carcinogenic tumors.

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.

Yct1p, a novel, high-affinity, cysteine-specific transporter from the yeast Saccharomyces cerevisiae

Cysteine transport in the yeast Saccharomyces cerevisiae is mediated by at least eight different permeases, none of which are specific for cysteine. We describe a novel, high-affinity, (K(m) = 55 microM), cysteine-specific transporter encoded by the ORF YLL055w that was initially identified by a combined strategy of data mining, bioinformatics, and genetic analysis. Null mutants of YLL055w, but not of the other genes encoding for transporters that mediate cysteine uptake such as GAP1, GNP1, MUP1, or AGP1 in a met15Delta background, resulted in a growth defect when cysteine, at low concentrations, was provided as the sole sulfur source. Transport experiments further revealed that Yll055wp was the major contributor to cysteine transport under these conditions. The contributions of the other transporters became relevant only at higher concentrations of cysteine or when YLL055w was either deleted or repressed. YLL055w expression was repressed by organic sulfur sources and was mediated by the Met4p-dependent sulfur regulatory network. The results reveal that YLL055w encodes the principal cysteine transporter in S. cerevisiae, which we have named YCT1 (yeast cysteine transporter). Interestingly, Yct1p belongs to the Dal5p family of transporters rather than the amino acid permease family to which all the known amino acid transporters belong.

Protein carbon content evolves in response to carbon availability and may influence the fate of duplicated genes

Natural selection can influence even the lowest level of biological organization, the atomic composition of biological macromolecules. In analysing genome-scale gene expression data, we find that ancestral yeast strains preferentially express proteins with low carbon content during carbon limitation, relative to strains selected in the laboratory under carbon limitation. The likely reason is that the artificially selected strains acquire adaptations that refine their response to the limitation or partly circumvent the limiting condition. This finding extends previous work which shows that natural selection can act on the atomic costs of proteins. We also show that genes with high carbon and nitrogen content are less likely to have duplicates, indicating that atomic composition also plays a role in evolution by gene duplication. Taken together, our results contribute to the emerging view that protein atomic composition influences genome and transcriptome evolution.

Metabolic systems cost-benefit analysis for interpreting network structure and regulation

MOTIVATION

Interpretation of bioinformatics data in terms of cellular function is a major challenge facing systems biology. This question is complicated by robust metabolic networks filled with structural features like parallel pathways and isozymes. Under conditions of nutrient sufficiency, metabolic networks are well known to be regulated for thermodynamic efficiency however; efficient biochemical pathways are anabolically expensive to construct. While parameters like thermodynamic efficiency have been extensively studied, a systems-based analysis of anabolic proteome synthesis 'costs' and the cellular function implications of these costs has not been reported.

RESULTS

A cost-benefit analysis of an in silico Escherichia coli network revealed the relationship between metabolic pathway proteome synthesis requirements, DNA-coding sequence length, thermodynamic efficiency and substrate affinity. The results highlight basic metabolic network design principles. Pathway proteome synthesis requirements appear to have shaped biochemical network structure and regulation. Under conditions of nutrient scarcity and other general stresses, E. coli expresses pathways with relatively inexpensive proteome synthesis requirements instead of more efficient but also anabolically more expensive pathways. This evolutionary strategy provides a cellular function-based explanation for common network motifs like isozymes and parallel pathways and possibly explains 'overflow' metabolisms observed during nutrient scarcity.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Oxygen content of transmembrane proteins over macroevolutionary time scales

We observe that the time of appearance of cellular compartmentalization correlates with atmospheric oxygen concentration. To explore this correlation, we predict and characterize the topology of all transmembrane proteins in 19 taxa and correlate differences in topology with historical atmospheric oxygen concentrations. Here we show that transmembrane proteins, individually and as a group, were probably selectively excluding oxygen in ancient ancestral taxa, and that this constraint decreased over time when atmospheric oxygen levels rose. As this constraint decreased, the size and number of communication-related transmembrane proteins increased. We suggest the hypothesis that atmospheric oxygen concentrations affected the timing of the evolution of cellular compartmentalization by constraining the size of domains necessary for communication across membranes.

Signatures of Ecological Resource Availability in the Animal and Plant Proteomes

Although substantial and ecologically significant differences in elemental composition are well documented for whole organisms, little is known about whether such differences extend to lower levels of biological organization, such as the elemental composition of major molecules. In a proteome-scale investigation of 9 plant genomes and 9 animal genomes, we find that the nitrogen (N) content of plant proteins is lower than that in animal proteins. Furthermore, protein N content declines with the intensity of gene expression for plants, whereas the N content of animal proteins shows no consistent pattern with expression. Additional analyses indicate that the differences in N content between plant and animal proteomes and in plant proteins as a function of gene expression cannot be attributed to protein size, GC content, gene function, or amino acid properties. These patterns suggest that ecophysiological selection has operated to conserve N in plants via decreased reliance on N-rich amino acids. This inference was supported by an analysis of conserved and variable sites indicating that the N content of plant amino acids coded by variable sites is similar to that of the sites conserved between plant and animal genomes and shows no association with expression level. In contrast, in animals, the N content of amino acids coded by variable sites is significantly higher than that for conserved sites, suggesting relaxation of selective constraints for N usage in the animal lineage. This constitutes the first evidence for an influence of environmental resource availability on proteomes of multicellular organisms.

Variation among species in proteomic sulphur content is related to environmental conditions

The elemental composition of proteins influences the quantities of different elements required by organisms. Here, we considered variation in the sulphur content of whole proteomes among 19 Archaea, 122 Eubacteria and 10 eukaryotes whose genomes have been fully sequenced. We found that different species vary greatly in the sulphur content of their proteins, and that average sulphur content of proteomes and genome base composition are related. Forces contributing to variation in proteomic sulphur content appear to operate quite uniformly across the proteins of different species. In particular, the sulphur content of orthologous proteins was frequently correlated with mean proteomic sulphur contents. Among prokaryotes, proteomic sulphur content tended to be greater in anaerobes, relative to non-anaerobes. Thermophiles tended to have lower proteomic sulphur content than non-thermophiles, consistent with the thermolability of cysteine and methionine residues. This work suggests that persistent environmental growth conditions can influence the evolution of elemental composition of whole proteomes in a manner that may have important implications for the amount of sulphur used by living organisms to build proteins. It extends previous studies that demonstrated links between transient changes in environmental conditions and the elemental composition of subsets of proteins expressed under these conditions.

Continuous culture--making a comeback?

The heyday of continuous culture was in the 1960s, when its versatility and reproducibility were used to address fundamental problems in diverse microbiological fields such as biochemistry, ecology, genetics and physiology. The advent of molecular genetics in the 1970s and 1980s led to a decline in the popularity of continuous culture as a standard laboratory tool. The current trend of studying global proteomics, transcriptomics and metabolomics requires reproducible, reliable and biologically homogeneous datasets with which to approach a given problem. The use of continuous culture techniques can aid the acquisition of such data, and continuous cultures offer advantages over biologically heterogeneous batch cultures, where secondary growth and stress effects can often mask subtle physiological differences and trends. This review is intended to remind microbiologists of the value of continuous cultivation in a wide range of biological investigations, and describes some advantages and recent advances in applications of continuous culture in post-genomic studies.

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

If the enzymes responsible for biosynthesis of a given amino acid are repressed and the cognate amino acid pool suddenly depleted, then derepression of these enzymes and replenishment of the pool would be problematic, if the enzymes were largely composed of the cognate amino acid. In the proverbial "Catch 22", cells would lack the necessary enzymes to make the amino acid, and they would lack the necessary amino acid to make the needed enzymes. Based on this scenario, we hypothesize that evolution would lead to the selection of amino acid biosynthetic enzymes that have a relatively low content of their cognate amino acid. We call this the "cognate bias hypothesis". Here we test several implications of this hypothesis directly using data from the proteome of Escherichia coli. Several lines of evidence show that low cognate bias is evident in 15 of the 20 amino acid biosynthetic pathways. Comparison with closely related Salmonella typhimurium shows similar results. Comparison with more distantly related Bacillus subtilis shows general similarities as well as significant differences in the detailed profiles of cognate bias. Thus, selection for low cognate bias plays a significant role in shaping the amino acid composition for a large class of cellular proteins.

Nitrogen versus carbon use in prokaryotic genomes and proteomes

There is growing recognition that the elemental composition of genomes and proteins can be related to resource limitation. We examine the possibility that the elemental composition of nucleic acids and the amino acids (and proteins) they encode are correlated. We report a positive association between the stoichiometric ratio of N/C content of individual amino acids and their codons. Potentially, this is an outcome of chemical interactions between amino acids and anticodons that influenced the evolution of the genetic code. We also find a strong, positive relationship between N/C values of whole genomes and proteomes, across 94 prokaryotic species. This relationship is part of a spectrum in nitrogen versus carbon use across genomes and proteomes, which is correlated with genomic GC content. GC content is correlated positively with average nitrogen use, and negatively with average carbon use, across both genomes and proteomes.

Evolution of cross-feeding in microbial populations

Although limited by a single resource, microbial populations that grow for long periods in continuous culture (chemostat) frequently evolve stable polymorphisms. These polymorphisms may be maintained by cross-feeding, where one strain partially degrades the primary energy resource and excretes an intermediate that is used as an energy resource by a second strain. It is unclear what selective advantage cross-feeding strains have over a single competitor that completely degrades the primary resource. Here we show that cross-feeding may evolve in microbial populations as a consequence of the following optimization principles: the rate of ATP production is maximized, the concentration of enzymes of the pathway is minimized, and the concentration of intermediates of the pathway is minimized.

Intimate evolution of proteins. Proteome atomic content correlates with genome base composition

Discerning the significant relations that exist within and among genome sequences is a major step toward the modeling of biopolymer evolution. Here we report the systematic analysis of the atomic composition of proteins encoded by organisms representative of each kingdoms. Protein atomic contents are shown to vary largely among species, the larger variations being observed for the main architectural component of proteins, the carbon atom. These variations apply to the bulk proteins as well as to subsets of ortholog proteins. A pronounced correlation between proteome carbon content and genome base composition is further evidenced, with high G+C genome content being related to low protein carbon content. The generation of random proteomes and the examination of the canonical genetic code provide arguments for the hypothesis that natural selection might have driven genome base composition.

Comparative genomics of bacterial zinc regulons: enhanced ion transport, pathogenesis, and rearrangement of ribosomal proteins

Zinc is an important component of many proteins, but in large concentrations it is poisonous to the cell. Thus its transport is regulated by zinc repressors ZUR of proteobacteria and Gram-positive bacteria from the Bacillus group and AdcR of bacteria from the Streptococcus group. Comparative computational analysis allowed us to identify binding signals of ZUR repressors GAAATGTTATANTATAACATTTC for gamma-proteobacteria, GTAATGTAATAACATTAC for the Agrobacterium group, GATATGTTATAACATATC for the Rhododoccus group, TAAATCGTAATNATTACGATTTA for Gram-positive bacteria, and TTAACYRGTTAA of the streptococcal AdcR repressor. In addition to known transporters and their paralogs, zinc regulons were predicted to contain a candidate component of the ATP binding cassette, zinT (b1995 in Escherichia coli and yrpE in Bacillus subtilis). Candidate AdcR-binding sites were identified upstream of genes encoding pneumococcal histidine triad (PHT) proteins from a number of pathogenic streptococci. Protein functional analysis of this family suggests that PHT proteins are involved in the invasion process. Finally, repression by zinc was predicted for genes encoding a variety of paralogs of ribosomal proteins. The original copies of all these proteins contain zinc-ribbon motifs and thus likely bind zinc, whereas these motifs are destroyed in zinc-regulated paralogs. We suggest that the induction of these paralogs in conditions of zinc starvation leads to their incorporation in a fraction of ribosomes instead of the original ribosomal proteins; the latter are then degraded with subsequent release of some zinc for the utilization by other proteins. Thus we predict a mechanism for maintaining zinc availability for essential enzymes.

Translational selection and yeast proteome evolution

The primary structures of peptides may be adapted for efficient synthesis as well as proper function. Here, the Saccharomyces cerevisiae genome sequence, DNA microarray expression data, tRNA gene numbers, and functional categorizations of proteins are employed to determine whether the amino acid composition of peptides reflects natural selection to optimize the speed and accuracy of translation. Strong relationships between synonymous codon usage bias and estimates of transcript abundance suggest that DNA array data serve as adequate predictors of translation rates. Amino acid usage also shows striking relationships with expression levels. Stronger correlations between tRNA concentrations and amino acid abundances among highly expressed proteins than among less abundant proteins support adaptation of both tRNA abundances and amino acid usage to enhance the speed and accuracy of protein synthesis. Natural selection for efficient synthesis appears to also favor shorter proteins as a function of their expression levels. Comparisons restricted to proteins within functional classes are employed to control for differences in amino acid composition and protein size that reflect differences in the functional requirements of proteins expressed at different levels.

MultiTag: multiple error-tolerant sequence tag search for the sequence-similarity identification of proteins by mass spectrometry

The characterization of proteomes by mass spectrometry is largely limited to organisms with sequenced genomes. To identify proteins from organisms with unsequenced genomes, database sequences from related species must be employed for sequence-similarity protein identifications. Peptide sequence tags (Mann, 1994) have been used successfully for the identification of proteins in sequence databases using partially interpreted tandem mass spectra of tryptic peptides. We have extended the ability of sequence tag searching to the identification of proteins whose sequences are yet unknown but are homologous to known database entries. The MultiTag method presented here assigns statistical significance to matches of multiple error-tolerant sequence tags to a database entry and ranks alignments by their significance. The MultiTag approach has the distinct advantage over other sequence-similarity approaches of being able to perform sequence-similarity identifications using only very short (2-4) amino acid residue stretches of peptide sequences, rather than complete peptide sequences deduced by de novo interpretation of tandem mass spectra. This feature facilitates the identification of low abundance proteins, since noisy and low-intensity tandem mass spectra can be utilized.

The genome-wide transcriptional responses of Saccharomyces cerevisiae grown on glucose in aerobic chemostat cultures limited for carbon, nitrogen, phosphorus, or sulfur

Profiles of genome-wide transcriptional events for a given environmental condition can be of importance in the diagnosis of poorly defined environments. To identify clusters of genes constituting such diagnostic profiles, we characterized the specific transcriptional responses of Saccharomyces cerevisiae to growth limitation by carbon, nitrogen, phosphorus, or sulfur. Microarray experiments were performed using cells growing in steady-state conditions in chemostat cultures at the same dilution rate. This enabled us to study the effects of one particular limitation while other growth parameters (pH, temperature, dissolved oxygen tension) remained constant. Furthermore, the composition of the media fed to the cultures was altered so that the concentrations of excess nutrients were comparable between experimental conditions. In total, 1881 transcripts (31% of the annotated genome) were significantly changed between at least two growth conditions. Of those, 484 were significantly higher or lower in one limitation only. The functional annotations of these genes indicated cellular metabolism was altered to meet the growth requirements for nutrient-limited growth. Furthermore, we identified responses for several active transcription factors with a role in nutrient assimilation. Finally, 51 genes were identified that showed 10-fold higher or lower expression in a single condition only. The transcription of these genes can be used as indicators for the characterization of nutrient-limited growth conditions and provide information for metabolic engineering strategies.

Species-specific protein sequence and fold optimizations

BACKGROUND

An organism's ability to adapt to its particular environmental niche is of fundamental importance to its survival and proliferation. In the largest study of its kind, we sought to identify and exploit the amino-acid signatures that make species-specific protein adaptation possible across 100 complete genomes.

RESULTS

Environmental niche was determined to be a significant factor in variability from correspondence analysis using the amino acid composition of over 360,000 predicted open reading frames (ORFs) from 17 archaea, 76 bacteria and 7 eukaryote complete genomes. Additionally, we found clusters of phylogenetically unrelated archaea and bacteria that share similar environments by amino acid composition clustering. Composition analyses of conservative, domain-based homology modeling suggested an enrichment of small hydrophobic residues Ala, Gly, Val and charged residues Asp, Glu, His and Arg across all genomes. However, larger aromatic residues Phe, Trp and Tyr are reduced in folds, and these results were not affected by low complexity biases. We derived two simple log-odds scoring functions from ORFs (CG) and folds (CF) for each of the complete genomes. CF achieved an average cross-validation success rate of 85 +/- 8% whereas the CG detected 73 +/- 9% species-specific sequences when competing against all other non-redundant CG. Continuously updated results are available at http://genome.mshri.on.ca.

CONCLUSION

Our analysis of amino acid compositions from the complete genomes provides stronger evidence for species-specific and environmental residue preferences in genomic sequences as well as in folds. Scoring functions derived from this work will be useful in future protein engineering experiments and possibly in identifying horizontal transfer events.

Sulfur sparing in the yeast proteome in response to sulfur demand

Genome-wide studies have recently revealed the unexpected complexity of the genetic response to apparently simple physiological changes. Here, we show that when yeast cells are exposed to Cd(2+), most of the sulfur assimilated by the cells is converted into glutathione, a thiol-metabolite essential for detoxification. Cells adapt to this vital metabolite requirement by modifying globally their proteome to reduce the production of abundant sulfur-rich proteins. In particular, some abundant glycolytic enzymes are replaced by sulfur-depleted isozymes. This global change in protein expression allows an overall sulfur amino acid saving of 30%. This proteomic adaptation is essentially regulated at the mRNA level. The main transcriptional activator of the sulfate assimilation pathway, Met4p, plays an essential role in this sulfur-sparing response.

Metabolic efficiency and amino acid composition in the proteomes of Escherichia coli and Bacillus subtilis

Biosynthesis of an Escherichia coli cell, with organic compounds as sources of energy and carbon, requires approximately 20 to 60 billion high-energy phosphate bonds [Stouthamer, A. H. (1973) Antonie van Leeuwenhoek 39, 545-565]. A substantial fraction of this energy budget is devoted to biosynthesis of amino acids, the building blocks of proteins. The fueling reactions of central metabolism provide precursor metabolites for synthesis of the 20 amino acids incorporated into proteins. Thus, synthesis of an amino acid entails a dual cost: energy is lost by diverting chemical intermediates from fueling reactions and additional energy is required to convert precursor metabolites to amino acids. Among amino acids, costs of synthesis vary from 12 to 74 high-energy phosphate bonds per molecule. The energetic advantage to encoding a less costly amino acid in a highly expressed gene can be greater than 0.025% of the total energy budget. Here, we provide evidence that amino acid composition in the proteomes of E. coli and Bacillus subtilis reflects the action of natural selection to enhance metabolic efficiency. We employ synonymous codon usage bias as a measure of translation rates and show increases in the abundance of less energetically costly amino acids in highly expressed proteins.