Metabolic flux is a determinant of the evolutionary rates of enzyme-encoding genes

Weaker selection on genes with treatment-specific expression consistent with a limit on plasticity evolution in Arabidopsis thaliana

Differential gene expression between environments often underlies phenotypic plasticity. However, environment-specific expression patterns are hypothesized to relax selection on genes, and thus limit plasticity evolution. We collated over 27 terabases of RNA-sequencing data on Arabidopsis thaliana from over 300 peer-reviewed studies and 200 treatment conditions to investigate this hypothesis. Consistent with relaxed selection, genes with more treatment-specific expression have higher levels of nucleotide diversity and divergence at nonsynonymous sites but lack stronger signals of positive selection. This result persisted even after controlling for expression level, gene length, GC content, the tissue specificity of expression, and technical variation between studies. Overall, our investigation supports the existence of a hypothesized trade-off between the environment specificity of a gene's expression and the strength of selection on said gene in A. thaliana. Future studies should leverage multiple genome-scale datasets to tease apart the contributions of many variables in limiting plasticity evolution.

Evolution of enzyme levels in metabolic pathways: A theoretical approach. Part 2

Metabolism is essential for cell function and adaptation. Because of their central role in metabolism, kinetic parameters and enzyme concentrations are under constant selective pressure to adapt the fluxes of the metabolic networks to the needs of the organism. In line with various studies dealing with enzyme evolution, we recently developed a model of the evolution of enzyme concentrations under selection for increased flux, considered as a proxy for fitness (Coton et al., 2022). With this model, taking into account two realistic cellular constraints, competition for resources and co-regulation, we determined the evolutionary equilibria and range of neutral variations of enzyme concentrations. In this article, we expanded this model by considering that the enzymes in a pathway can belong to different co-regulation groups. We determined the equilibria and showed that the constraints modify the adaptive landscape by limiting the number of independent dimensions. We also showed that any trade-off between enzyme concentrations is sufficient to limit the flux and relax selection for increasing the concentration of other enzymes. Even though this model is based on simplifying assumptions, the complexity of the relationship between enzyme concentrations prevents the formal analysis of the range of neutral variation of enzyme concentrations. However, we could show that selection for maximizing the flux results in selective neutrality for all enzymes regardless the constraints applied, giving generality to the prediction of Hartl et al. (1985).

Evolution of enzyme levels in metabolic pathways: A theoretical approach

The central role of metabolism in cell functioning and adaptation has given rise to countless studies on the evolution of enzyme-coding genes and network topology. However, very few studies have addressed the question of how enzyme concentrations change in response to positive selective pressure on the flux, considered a proxy of fitness. In particular, the way cellular constraints, such as resource limitations and co-regulation, affect the adaptive landscape of a pathway under selection has never been analyzed theoretically. To fill this gap, we developed a model of the evolution of enzyme concentrations that combines metabolic control theory and an adaptive dynamics approach, and integrates possible dependencies between enzyme concentrations. We determined the evolutionary equilibria of enzyme concentrations and their range of neutral variation, and showed that they differ with the properties of the enzymes, the constraints applied to the system and the initial enzyme concentrations. Simulations of long-term evolution confirmed all analytical and numerical predictions, even though we relaxed the simplifying assumptions used in the analytical treatment.

Patterns and Constraints in the Evolution of Sperm Individualization Genes in Insects, with an Emphasis on Beetles

Gene expression profiles can change dramatically between sexes and sex bias may contribute specific macroevolutionary dynamics for sex-biased genes. However, these dynamics are poorly understood at large evolutionary scales due to the paucity of studies that have assessed orthology and functional homology for sex-biased genes and the pleiotropic effects possibly constraining their evolutionary potential. Here, we explore the correlation of sex-biased expression with macroevolutionary processes that are associated with sex-biased genes, including duplications and accelerated evolutionary rates. Specifically, we examined these traits in a group of 44 genes that orchestrate sperm individualization during spermatogenesis, with both unbiased and sex-biased expression. We studied these genes in the broad evolutionary framework of the Insecta, with a particular focus on beetles (order Coleoptera). We studied data mined from 119 insect genomes, including 6 beetle models, and from 19 additional beetle transcriptomes. For the subset of physically and/or genetically interacting proteins, we also analyzed how their network structure may condition the mode of gene evolution. The collection of genes was highly heterogeneous in duplication status, evolutionary rates, and rate stability, but there was statistical evidence for sex bias correlated with faster evolutionary rates, consistent with theoretical predictions. Faster rates were also correlated with clocklike (insect amino acids) and non-clocklike (beetle nucleotides) substitution patterns in these genes. Statistical associations (higher rates for central nodes) or lack thereof (centrality of duplicated genes) were in contrast to some current evolutionary hypotheses, highlighting the need for more research on these topics.

Gene connectivity and enzyme evolution in the human metabolic network

BACKGROUND

Determining the factors involved in the likelihood of a gene being under adaptive selection is still a challenging goal in Evolutionary Biology. Here, we perform an evolutionary analysis of the human metabolic genes to explore the associations between network structure and the presence and strength of natural selection in the genes whose products are involved in metabolism. Purifying and positive selection are estimated at interspecific (among mammals) and intraspecific (among human populations) levels, and the connections between enzymatic reactions are differentiated between incoming (in-degree) and outgoing (out-degree) links.

RESULTS

We confirm that purifying selection has been stronger in highly connected genes. Long-term positive selection has targeted poorly connected enzymes, whereas short-term positive selection has targeted different enzymes depending on whether the selective sweep has reached fixation in the population: genes under a complete selective sweep are poorly connected, whereas those under an incomplete selective sweep have high out-degree connectivity. The last steps of pathways are more conserved due to stronger purifying selection, with long-term positive selection targeting preferentially enzymes that catalyze the first steps. However, short-term positive selection has targeted enzymes that catalyze the last steps in the metabolic network. Strong signals of positive selection have been found for metabolic processes involved in lipid transport and membrane fluidity and permeability.

CONCLUSIONS

Our analysis highlights the importance of analyzing the same biological system at different evolutionary timescales to understand the evolution of metabolic genes and of distinguishing between incoming and outgoing links in a metabolic network. Short-term positive selection has targeted enzymes with a different connectivity profile depending on the completeness of the selective sweep, while long-term positive selection has targeted genes with fewer connections that code for enzymes that catalyze the first steps in the network.

REVIEWERS

This article was reviewed by Diamantis Sellis and Brandon Invergo.

Metabolic Determinants of Enzyme Evolution in a Genome-Scale Bacterial Metabolic Network

Different genes and proteins evolve at very different rates. To identify the factors that explain these differences is an important aspect of research in molecular evolution. One such factor is the role a protein plays in a large molecular network. Here, we analyze the evolutionary rates of enzyme-coding genes in the genome-scale metabolic network of Escherichia coli to find the evolutionary constraints imposed by the structure and function of this complex metabolic system. Central and highly connected enzymes appear to evolve more slowly than less connected enzymes, but we find that they do so as a by-product of their high abundance, and not because of their position in the metabolic network. In contrast, enzymes catalyzing reactions with high metabolic flux-high substrate to product conversion rates-evolve slowly even after we account for their abundance. Moreover, enzymes catalyzing reactions that are difficult to by-pass through alternative pathways, such that they are essential in many different genetic backgrounds, also evolve more slowly. Our analyses show that an enzyme's role in the function of a metabolic network affects its evolution more than its place in the network's structure. They highlight the value of a system-level perspective for studies of molecular evolution.

Evolutionary Perspectives of Genotype-Phenotype Factors in Leishmania Metabolism

The sandfly midgut and the human macrophage phagolysosome provide antagonistic metabolic niches for the endoparasite Leishmania to survive and populate. Although these environments fluctuate across developmental stages, the relative changes in both these environments across parasite generations might remain gradual. Such environmental restrictions might endow parasite metabolism with a choice of specific genotypic and phenotypic factors that can constrain enzyme evolution for successful adaptation to the host. With respect to the available cellular information for Leishmania species, for the first time, we measure the relative contribution of eight inter-correlated predictors related to codon usage, GC content, gene expression, gene length, multi-functionality, and flux-coupling potential of an enzyme on the evolutionary rates of singleton metabolic genes and further compare their effects across three Leishmania species. Our analysis reveals that codon adaptation, multi-functionality, and flux-coupling potential of an enzyme are independent contributors of enzyme evolutionary rates, which can together explain a large variation in enzyme evolutionary rates across species. We also hypothesize that a species-specific occurrence of duplicated genes in novel subcellular locations can create new flux routes through certain singleton flux-coupled enzymes, thereby constraining their evolution. A cross-species comparison revealed both common and species-specific genes whose evolutionary divergence was constrained by multiple independent factors. Out of these, previously known pharmacological targets and virulence factors in Leishmania were identified, suggesting their evolutionary reasons for being important survival factors to the parasite. All these results provide a fundamental understanding of the factors underlying adaptive strategies of the parasite, which can be further targeted.

Dynamic sensitivity and nonlinear interactions influence the system-level evolutionary patterns of phototransduction proteins

Determining the influence of complex, molecular-system dynamics on the evolution of proteins is hindered by the significant challenge of quantifying the control exerted by the proteins on system output. We have employed a combination of systems biology and molecular evolution analyses in a first attempt to unravel this relationship. We employed a comprehensive mathematical model of mammalian phototransduction to predict the degree of influence that each protein in the system exerts on the high-level dynamic behaviour. We found that the genes encoding the most dynamically sensitive proteins exhibit relatively relaxed evolutionary constraint. We also investigated the evolutionary and epistatic influences of the many nonlinear interactions between proteins in the system and found several pairs to have coevolved, including those whose interactions are purely dynamical with respect to system output. This evidence points to a key role played by nonlinear system dynamics in influencing patterns of molecular evolution.

New views on the selection acting on genetic polymorphism in central metabolic genes

Studies of the polymorphism of central metabolic genes as a source of fitness variation in natural populations date back to the discovery of allozymes in the 1960s. The unique features of these genes and their enzymes and our knowledge base greatly facilitates the systems-level study of this group. The expectation that pathway flux control is central to understanding the molecular evolution of genes is discussed, as well as studies that attempt to place gene-specific molecular evolution and polymorphism into a context of pathway and network architecture. There is an increasingly complex picture of the metabolic genes assuming additional roles beyond their textbook anabolic and catabolic reactions. In particular, this review emphasizes the potential role of these genes as part of the energy-sensing machinery. It is underscored that the concentrations of key cellular metabolites are the reflections of cellular energy status and nutritional input. These metabolites are the top-down signaling messengers that set signaling through signaling pathways that are involved in energy economy. I propose that the polymorphisms in central metabolic genes shift metabolite concentrations and in that fashion act as genetic modifiers of the energy-state coupling to the transcriptional networks that affect physiological trade-offs with significant fitness consequences.

Flux Control in Glycolysis Varies Across the Tree of Life

Biochemical thought posits that rate-limiting steps (defined here as points of flux control) are strongly selected as points of pathway regulation and control and are thus expected to be evolutionarily conserved. Conversely, population genetic thought based upon the concepts of mutation-selection-drift balance at the pathway level might suggest variation in flux controlling steps over evolutionary time. Glycolysis, as one of the most conserved and best characterized pathways, was studied to evaluate its evolutionary conservation. The flux controlling step in glycolysis was found to vary over the tree of life. Further, phylogenetic analysis suggested at least 60 events of gene duplication and additional events of putative positive selection that might alter pathway kinetic properties. Together, these results suggest that even with presumed largely negative selection on pathway output on glycolysis, the co-evolutionary process under the hood is dynamic.

Characterizing selective pressures on the pathway for de novo biosynthesis of pyrimidines in yeast

Background

Selection on proteins is typically measured with the assumption that each protein acts independently. However, selection more likely acts at higher levels of biological organization, requiring an integrative view of protein function. Here, we built a kinetic model for de novo pyrimidine biosynthesis in the yeast Saccharomyces cerevisiae to relate pathway function to selective pressures on individual protein-encoding genes.

Results

Gene families across yeast were constructed for each member of the pathway and the ratio of nonsynonymous to synonymous nucleotide substitution rates (dN/dS) was estimated for each enzyme from S. cerevisiae and closely related species. We found a positive relationship between the influence that each enzyme has on pathway function and its selective constraint.

Conclusions

We expect this trend to be locally present for enzymes that have pathway control, but over longer evolutionary timescales we expect that mutation-selection balance may change the enzymes that have pathway control.

Electronic supplementary material

The online version of this article (doi:10.1186/s12862-015-0515-x) contains supplementary material, which is available to authorized users.