The tragedy of the commons in microbial populations: insights from theoretical, comparative and experimental studies

First principles of thermodynamics imply that metabolic pathways are faced with a trade-off between the rate and yield of ATP production. Simple evolutionary models argue that this trade-off generates a fundamental social conflict in microbial populations: average fitness in a population is highest if all individuals exploit common resources efficiently, but individual reproductive rate is maximized by consuming common resources at the highest possible rate, a scenario known as the tragedy of the commons. In this paper, I review studies that have addressed two key questions: What is the evidence that the rate-yield trade-off is an evolutionary constraint on metabolic pathways? And, if so, what determines evolutionary outcome of the conflicts generated by this trade-off? Comparative studies and microbial experiments provide evidence that the rate-yield trade-off is an evolutionary constraint that is driven by thermodynamic constraints that are common to all metabolic pathways and pathway-specific constraints that reflect the evolutionary history of populations. Microbial selection experiments show that the evolutionary consequences of this trade-off depend on both kin selection and biochemical constraints. In well-mixed populations with low relatedness, genotypes with rapid and efficient metabolism can coexist as a result of negative frequency-dependent selection generated by density-dependent biochemical costs of rapid metabolism. Kin selection can promote the maintenance of efficient metabolism in structured populations with high relatedness by ensuring that genotypes with efficient metabolic pathways gain an indirect fitness benefit from their competitive restraint. I conclude by suggesting avenues for future research and by discussing the broader implications of this work for microbial social evolution.     

Divergence and redundancy of transport and metabolic rate-yield strategies in a single Escherichia coli population

The energetic efficiency of nutrient uptake and conversion into biomass is a key factor in the ecological behavior of microorganisms. The constraints shaping the metabolic rate-yield trade-off in bacteria are not well understood. To examine whether metabolic rate-yield settings and physiological strategies evolve toward a particular optimum in a constant environment, we studied multiple Escherichia coli isolates evolving in a glucose-limited chemostat population. A major divergence in transport and metabolic strategies was observed, and the isolates included inefficient rate strategists (polluters or cheaters) and yield strategists (conservationists), as well as various hybrid rate-yield strategists and alternative ecotypes (dropouts). Sugar transport assays, strain comparisons based on metabolomics, and Biolog profiling revealed variance to the point of individuality within an evolving population. Only 68 of 177 metabolites assayed were not affected in 10 clonally related strains. The parallel enrichment of rate and yield strategists and the divergence in metabolic phylogenies indicate that bacteria do not converge on a particular rate-yield balance or unique evolutionary solutions. Redundancies in transport and metabolic pathways are proposed to have laid the framework for the multiplicity of bacterial adaptations.     

How Biochemical Constraints of Cellular Growth Shape Evolutionary Adaptations in Metabolism

Evolutionary adaptations in metabolic networks are fundamental to evolution of microbial growth. Studies on unneeded-protein synthesis indicate reductions in fitness upon nonfunctional protein synthesis, showing that cell growth is limited by constraints acting on cellular protein content. Here, we present a theory for optimal metabolic enzyme activity when cells are selected for maximal growth rate given such growth-limiting biochemical constraints. We show how optimal enzyme levels can be understood to result from an enzyme benefit minus cost optimization. The constraints we consider originate from different biochemical aspects of microbial growth, such as competition for limiting amounts of ribosomes or RNA polymerases, or limitations in available energy. Enzyme benefit is related to its kinetics and its importance for fitness, while enzyme cost expresses to what extent resource consumption reduces fitness through constraint-induced reductions of other enzyme levels. A metabolic fitness landscape is introduced to define the fitness potential of an enzyme. This concept is related to the selection coefficient of the enzyme and can be expressed in terms of its fitness benefit and cost.     

Competition as a source of constraint on life history evolution in natural populations

Competition among individuals is central to our understanding of ecology and population dynamics. However, it could also have major implications for the evolution of resource-dependent life history traits (for example, growth, fecundity) that are important determinants of fitness in natural populations. This is because when competition occurs, the phenotype of each individual will be causally influenced by the phenotypes, and so the genotypes, of competitors. Theory tells us that indirect genetic effects arising from competitive interactions will give rise to the phenomenon of ‘evolutionary environmental deterioration'', and act as a source of evolutionary constraint on resource-dependent traits under natural selection. However, just how important this constraint is remains an unanswered question. This article seeks to stimulate empirical research in this area, first highlighting some patterns emerging from life history studies that are consistent with a competition-based model of evolutionary constraint, before describing several quantitative modelling strategies that could be usefully applied. A recurrent theme is that rigorous quantification of a competition''s impact on life history evolution will require an understanding of the causal pathways and behavioural processes by which genetic (co)variance structures arise. Knowledge of the G-matrix among life history traits is not, in and of itself, sufficient to identify the constraints caused by competition.     

Evolutionary vestigialization of sex in a clonal plant: selection versus neutral mutation in geographically peripheral populations

The loss of traits that no longer contribute to fitness is widespread; however, the causative evolutionary mechanisms are poorly understood. Vestigialization could proceed through the fixation of selectively neutral degenerative mutations via genetic drift. Alternatively, selection may facilitate vestigialization if trait loss results in enhanced fitness. We tested these hypotheses using Decodon verticillatus, a clonal plant in which sexual sterility has arisen repeatedly in populations across the northern geographical range limit. We compared growth and survival of replicated genotypes from 7 sexually fertile and 18 sterile populations, over 3 years in a common environment. Survival of sterile genotypes was 53% greater than for fertile genotypes, but there was no difference in biomass accumulation. Almost all mortality, and hence increased performance of sterile genotypes, occurred during simulated overwinter dormancy. These observations suggest that selection has facilitated the vestigialization of sex, and thus do not support the neutral mutation hypothesis. The selective mechanism probably involves the relaxation of a genetic trade-off between sexual reproduction and survival: alleles that increase vegetative performance at the expense of sexual fertility are selected in geographically peripheral populations where sexual reproduction is suppressed by adverse environmental conditions.     

Constraints on microbial metabolism drive evolutionary diversification in homogeneous environments

Understanding the evolution of microbial diversity is an important and current problem in evolutionary ecology. In this paper, we investigated the role of two established biochemical trade-offs in microbial diversification using a model that connects ecological and evolutionary processes with fundamental aspects of biochemistry. The trade-offs that we investigated are as follows:(1) a trade-off between the rate and affinity of substrate transport; and (2) a trade-off between the rate and yield of ATP production. Our model shows that these biochemical trade-offs can drive evolutionary diversification under the simplest possible ecological conditions: a homogeneous environment containing a single limiting resource. We argue that the results of a number of microbial selection experiments are consistent with the predictions of our model.     

Antagonism between sexual and natural selection in experimental populations of Saccharomyces cerevisiae

Trade-offs between life-history components are a central concept of evolution and ecology. Sexual and natural selection seem particularly apt to impose antagonistic selective pressures. When sex is not integrated into reproduction, as in Saccharomyces cerevisiae, natural selection can impair or even eliminate it. In this study, a genetic trade-off between the sexual and asexual phases of the yeast life cycle was suggested by sharp declines in the mating and sporulation abilities of unrelated genotypes that were propagated asexually in minimal growth medium and in mice. When sexual selection was applied to populations that had previously evolved asexually, sexual fitness increased but asexual fitness declined. No such negative correlation was observed when sexual selection was applied to an ancestral strain: sexual and asexual fitness both increased. Thus, evolutionary history affected the evolution of genetic correlations, as fitness increases in a population already well adapted to the environment were more likely to come at the expense of sexual functions.     

Relationship between fitness and heterogeneity in exponentially growing microbial populations

Despite major environmental and genetic differences, microbial metabolic networks are known to generate consistent physiological outcomes across vastly different organisms. This remarkable robustness suggests that, at least in bacteria, metabolic activity may be guided by universal principles. The constrained optimization of evolutionarily motivated objective functions, such as the growth rate, has emerged as the key theoretical assumption for the study of bacterial metabolism. While conceptually and practically useful in many situations, the idea that certain functions are optimized is hard to validate in data. Moreover, it is not always clear how optimality can be reconciled with the high degree of single-cell variability observed in experiments within microbial populations. To shed light on these issues, we develop an inverse modeling framework that connects the fitness of a population of cells (represented by the mean single-cell growth rate) to the underlying metabolic variability through the maximum entropy inference of the distribution of metabolic phenotypes from data. While no clear objective function emerges, we find that, as the medium gets richer, the fitness and inferred variability for Escherichia coli populations follow and slowly approach the theoretically optimal bound defined by minimal reduction of variability at given fitness. These results suggest that bacterial metabolism may be crucially shaped by a population-level trade-off between growth and heterogeneity.     

Genotype networks shed light on evolutionary constraints

An evolutionary constraint is a bias or limitation in phenotypic variation that a biological system produces. One can distinguish physicochemical, selective, genetic and developmental causes of such constraints. Here, I discuss these causes in three classes of system that bring forth many phenotypic traits and evolutionary innovations: regulatory circuits, macromolecules and metabolic networks. In these systems, genotypes with the same phenotype form large genotype networks that extend throughout a vast genotype space. Such genotype networks can help unify different causes of evolutionary constraints. They can show that these causes ultimately emerge from the process of development; that is, how phenotypes form from genotypes. Furthermore, they can explain important consequences of constraints, such as punctuated stasis and canalization.     

PLEIOTROPY CAUSES LONG-TERM GENETIC CONSTRAINTS ON LIFE-HISTORY EVOLUTION IN BRASSICA RAPA

Fundamental, long-term genetic trade-offs constrain life-history evolution in wild crucifer populations. I studied patterns of genetic constraint in Brassica rapa by estimating genetic correlations among life-history components by quantitative genetic analyses among ten wild populations, and within four populations. Genetic correlations between age and size at first reproduction were always greater than +0.8 within and among all populations studied. Although quantitative genetics might provide insight about genetic constraints if genetic parameters remain approximately constant, little evidence has been available to determine the constancy of genetic correlations. I found strong and consistent estimates of genetic correlations between life-history components, which were very similar within four natural populations. Population differentiation also showed these same trade-offs, resulting from long-term genetic constraint. For some traits, evolutionary changes among populations were incompatible with a model of genetic drift. Historical patterns of natural selection were inferred from population differentiation, suggesting that correlated response to selection has caused some traits to evolve opposite to the direct forces of natural selection. Comparison with Arabidopsis suggests that these life-history trade-offs are caused by genes that regulate patterns of resource allocation to different components of fitness. Ecological and energetic models may correctly predict these trade-offs because there is little additive genetic variation for rates of resource acquisition, but resource allocation is genetically variable.     

Fundamental Escherichia coli biochemical pathways for biomass and energy production: identification of reactions

Cells grow by oxidizing nutrients using a complex network of biochemical reactions. During this process new biological material is produced along with energy used for maintaining cellular organization. Because the metabolic network is highly branched, these tasks can be accomplished using a wide variety of unique reaction sequences. However, evolutionary pressures under carbon-limited growth conditions likely select organisms that utilize highly efficient pathways. Using elementary-mode analysis, we demonstrate that the metabolism of the bacterium Escherichia coli contains four unique pathways that most efficiently convert glucose and oxygen into new cells and maintenance energy under any level of oxygen limitation. Observed regulatory patterns and experimental findings suggest growing cells use these highly efficient pathways. It is predicted that five knockout mutations generate a strain that supports growth using only the most efficient reaction sequence. The analysis approach should be generally useful for predicting metabolic capabilities and efficient network designs based on only genomic information.     

Growing with siblings: a common ground for cooperation or for fiercer competition among plants?

Recent work has shown that certain plants can identify their kin in competitive settings through root recognition, and react by decreasing root growth when competing with relatives. Although this may be a necessary step in kin selection, no clear associated improvement in individual or group fitness has been reported to qualify as such. We designed an experiment to address whether genetic relatedness between neighbouring plants affects individual or group fitness in artificial populations. Seeds of Lupinus angustifolius were sown in groups of siblings, groups of different genotypes from the same population and groups of genotypes from different populations. Both plants surrounded by siblings and by genotypes from the same population had lower individual fitness and produced fewer flowers and less vegetative biomass as a group. We conclude that genetic relatedness entails decreased individual and group fitness in L. angustifolius. This, together with earlier work, precludes the generalization that kin recognition may act as a widespread, major microevolutionary mechanism in plants.     

Perspective: Sign epistasis and genetic constraint on evolutionary trajectories

Epistasis for fitness means that the selective effect of a mutation is conditional on the genetic background in which it appears. Although epistasis is widely observed in nature, our understanding of its consequences for evolution by natural selection remains incomplete. In particular, much attention focuses only on its influence on the instantaneous rate of changes in frequency of selected alleles via epistatic contribution to the additive genetic variance for fitness. Thus, in this framework epistasis only has evolutionary importance if the interacting loci are simultaneously segregating in the population. However, the selective accessibility of mutational trajectories to high fitness genotypes may depend on the genetic background in which novel mutations appear, and this effect is independent of population polymorphism at other loci. Here we explore this second influence of epistasis on evolution by natural selection. We show that it is the consequence of a particular form of epistasis, which we designate sign epistasis. Sign epistasis means that the sign of the fitness effect of a mutation is under epistatic control; thus, such a mutation is beneficial on some genetic backgrounds and deleterious on others. Recent experimental innovations in microbial systems now permit assessment of the fitness effects of individual mutations on multiple genetic backgrounds. We review this literature and identify many examples of sign epistasis, and we suggest that the implications of these results may generalize to other organisms. These theoretical and empirical considerations imply that strong genetic constraint on the selective accessibility of trajectories to high fitness genotypes may exist and suggest specific areas of investigation for future research.     

Patterns of variation during adaptation in functionally linked loci

An understanding of the distribution of natural patterns of genetic variation is relevant to such fundamental biological fields as evolution and development. One recent approach to understanding such patterns has been to focus on the constraints that may arise as a function of the network or pathway context in which genes are embedded. Despite theoretical expectations of higher evolutionary constraint for genes encoding upstream versus downstream enzymes in metabolic pathways, empirical results have varied. Here we combine two complementary models from population genetics and enzyme kinetics to explore genetic variation as a function of pathway position when selection acts on whole-pathway flux. We are able to qualitatively reproduce empirically observed patterns of polymorphism and divergence and suggest that expectations should vary depending on the evolutionary trajectory of a population. Upstream genes are initially more polymorphic and diverge faster after an environmental change, while we see the opposite trend as the population approaches its fitness optimum.     

Proteomics-inferred genome typing (PIGT) demonstrates inter-population recombination as a strategy for environmental adaptation

Analyses of ecological and evolutionary processes that shape microbial consortia are facilitated by comprehensive studies of ecosystems with low species richness. In the current study we evaluated the role of recombination in altering the fitness of chemoautotrophic bacteria in their natural environment. Proteomics-inferred genome typing (PIGT) was used to genotype the dominant Leptospirillum group II populations in 27 biofilms sampled from six locations in the Richmond Mine acid mine drainage system (Iron Mountain, CA) over a 4-year period. We observed six distinct genotypes that are recombinants comprised of segments from two 'parental' genotypes. Community genomic analyses revealed additional low abundance recombinant variants. The dominance of some genotypes despite a larger available genome pool, and patterns of spatiotemporal distribution within the ecosystem, indicate selection for distinct recombinants. Genes involved in motility, signal transduction and transport were over-represented in the tens to hundreds of kilobase recombinant blocks, whereas core metabolic functions were significantly under-represented. Our findings demonstrate the power of PIGT and reveal that recombination is a mechanism for fine-scale adaptation in this system.     

Expanding Metabolic Capabilities Using Novel Pathway Designs: Computational Tools and Case Studies

Design and selection of efficient metabolic pathways is critical for the success of metabolic engineering endeavors. Convenient pathways should not only produce the target metabolite in high yields but also are required to be thermodynamically feasible under production conditions, and to prefer efficient enzymes. To support the design and selection of such pathways, different computational approaches have been proposed for exploring the feasible pathway space under many of the above constraints. In this review, an overview of recent constraint‐based optimization frameworks for metabolic pathway prediction, as well as relevant pathway engineering case studies that highlight the importance of rational metabolic designs is presented. Despite the availability and suitability of in silico design tools for metabolic pathway engineering, scarce—although increasing—application of computational outcomes is found. Finally, challenges and limitations hindering the broad adoption and successful application of these tools in metabolic engineering projects are discussed.     

Experimental social evolution with Myxococcus xanthus

Genetically-based social behaviors are subject to evolutionary change in response to natural selection. Numerous microbial systems provide not only the opportunity to understand the genetic mechanisms underlying specific social interactions, but also to observe evolutionary changes in sociality over short time periods. Here we summarize experiments in which behaviors of the social bacterium Myxococcus xanthus changed extensively during evolutionary adaptation to two relatively asocial laboratory environments. M. xanthus moves cooperatively, exhibits cooperative multicellular development upon starvation and also appears to prey cooperatively on other bacteria. Replicate populations of M. xanthus were evolved in both structured (agar plate) and unstructured (liquid) environments that contained abundant resources. The importance of social cooperation for evolutionary fitness in these habitats was limited by the absence of positive selection for starvation-induced spore production or predatory efficiency. Evolved populations showed major losses in all measured categories of social proficiency- motility, predation, fruiting ability, and sporulation. Moreover, several evolved genotypes were observed to exploit the social behavior of their ancestral parent when mixed together during the developmental process. These experiments that resulted in both socially defective and socially exploitative genotypes demonstrate the power of laboratory selection experiments for studying social evolution at the microbial level. Results from additional selection experiments that place positive selection pressure on social phenotypes can be integrated with direct study of natural populations to increase our understanding of principles that underlie the evolution of microbial social behavior. This revised version was published online in August 2006 with corrections to the Cover Date.     

Phylogenetic analysis based on genome-scale metabolic pathway reaction content

Phylogenetic classifications based on single genes such as rRNA genes do not provide a complete and accurate picture of evolution because they do not account for evolutionary leaps caused by gene transfer, duplication, deletion and functional replacement. Here, we present a whole-genome-scale phylogeny based on metabolic pathway reaction content. From the genome sequences of 42 microorganisms, we deduced the metabolic pathway reactions and used the relatedness of these contents to construct a phylogenetic tree that represents the similarity of metabolic profiles (relatedness) as well as the extent of metabolic pathway similarity (evolutionary distance). This method accounts for horizontal gene transfer and specific gene loss by comparison of whole metabolic subpathways, and allows evaluation of evolutionary relatedness and changes in metabolic pathways. Thus, a tree based on metabolic pathway content represents both the evolutionary time scale (changes in genetic content) and the evolutionary process (changes in metabolism).     

Relatedness in spatially structured populations with empty sites: An approach based on spatial moment equations

Taking into account the interplay between spatial ecological dynamics and selection is a major challenge in evolutionary ecology. Although inclusive fitness theory has proven to be a very useful tool to unravel the interactions between spatial genetic structuring and selection, applications of the theory usually rely on simplifying demographic assumptions. In this paper, I attempt to bridge the gap between spatial demographic models and kin selection models by providing a method to compute approximations for relatedness coefficients in a spatial model with empty sites. Using spatial moment equations, I provide an approximation of nearest-neighbour relatedness on random regular networks, and show that this approximation performs much better than the ordinary pair approximation. I discuss the connection between the relatedness coefficients I define and those used in population genetics, and sketch some potential extensions of the theory.