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Adaptation limits ecological diversification and promotes ecological tinkering during the competition for substitutable resources
Edited by Boris I. Shraiman, University of California, Santa Barbara, CA, and approved September 21, 2018 (received for review May 1, 2018)

Significance
Most mutations are subject to competitive exclusion: Their descendants will either take over the population or go extinct. In special cases, a mutant may evade competitive exclusion by exploiting a different ecological niche. Both types of mutations can be found in large microbial populations, yet little is known about how they interact. By generalizing consumer-resource theory to include heritable beneficial mutations, we show that interactions between diversification and competitive exclusion can produce dramatic departures from existing models of evolution or ecology alone. These results suggest that short-term evolutionary processes could play an important role in shaping the structure of microbial communities.
Abstract
Microbial communities can evade competitive exclusion by diversifying into distinct ecological niches. This spontaneous diversification often occurs amid a backdrop of directional selection on other microbial traits, where competitive exclusion would normally apply. Yet despite their empirical relevance, little is known about how diversification and directional selection combine to determine the ecological and evolutionary dynamics within a community. To address this gap, we introduce a simple, empirically motivated model of eco-evolutionary feedback based on the competition for substitutable resources. Individuals acquire heritable mutations that alter resource uptake rates, either by shifting metabolic effort between resources or by increasing the overall growth rate. While these constitutively beneficial mutations are trivially favored to invade, we show that the accumulated fitness differences can dramatically influence the ecological structure and evolutionary dynamics that emerge within the community. Competition between ecological diversification and ongoing fitness evolution leads to a state of diversification–selection balance, in which the number of extant ecotypes can be pinned below the maximum capacity of the ecosystem, while the ecotype frequencies and genealogies are constantly in flux. Interestingly, we find that fitness differences generate emergent selection pressures to shift metabolic effort toward resources with lower effective competition, even in saturated ecosystems. We argue that similar dynamical features should emerge in a wide range of models with a mixture of directional and diversifying selection.
Ecological diversification and competitive exclusion are opposing evolutionary forces. Conventional wisdom suggests that most new mutations are subject to competitive exclusion, while ecological diversification occurs only under highly specialized conditions (1). Recent empirical evidence from microbial, plant, and animal populations has started to challenge this assumption, suggesting that the breakdown of competitive exclusion is a more common and malleable process than is often assumed (2⇓–4). Particularly striking examples have been observed in laboratory evolution experiments, in which primitive forms of ecology evolve from a single ancestor over years (5), months (6), and even days (7).
In the simplest cases, the population splits into a pair of lineages, or “ecotypes,” that stably coexist with each other due to frequency-dependent selection, leading to a breakdown of competitive exclusion (5, 6, 8⇓–10). The mechanism of coexistence can often be traced to differences in resource utilization or to the accessibility of privileged spatial or temporal niches. Interestingly, these microbes rarely cease their evolution once ecological diversification has been achieved. Sequencing studies have shown that adaptive mutations continue to accumulate within each ecotype, even when population-wide fixations are rare (11⇓–13). This additional evolution can cause the ecological equilibrium to wander over longer timescales, as observed in the shifting population frequencies of the two ecotypes (5, 13). In certain cases, these evolutionary perturbations can even drive one of the original lineages to extinction, either through the outright elimination of the niche (9) or by the invasion of individuals that mutate from the opposing ecotype (12).
Pairwise coexistence is the simplest form of community structure, but similar dynamics have been observed in more complex communities as well. Some laboratory experiments diversify into three or more ecotypes (7, 14, 15), and it is likely that previously undetected ecotypes may be present in existing experiments (13). Moreover, many natural microbial populations evolve in communities with tens or hundreds of ecotypes engaged in various degrees of competition and coexistence (16⇓–18). Although the evolutionary dynamics within these communities are less well characterized, recent work suggests that similar short-term evolutionary processes can occur in these natural populations as well (19⇓–21).
While the interactions between microbial adaptation and ecology are known to be important empirically, our theoretical understanding of this process remains limited in comparison. Early work in the field of adaptive dynamics (22) showed how ecological diversification emerges under very general models of frequency-dependent trait evolution, which are thought to describe the limiting behavior of a wide class of ecological interactions near the point of diversification. Numerous studies have also investigated the effects of evolution on ecological diversification and stability using computer simulations, in which the parameters of a particular ecological model are allowed to evolve over time (23⇓⇓⇓⇓⇓–29). Yet while both approaches can reproduce some of the qualitative behaviors observed in experiments, it has been difficult to forge a more quantitative connection between these models and the large amount of molecular data that is now available.
One reason that quantitative comparisons have been difficult is that evolution also selects for other traits that are not directly involved in diversification. For example, natural selection always works to maintain essential cellular functions, and there may be a benefit to removing costly functions that are not needed in the current environment. As a result, mutations that influence an ecologically relevant phenotype like acetate metabolism might have to compete with constitutively beneficial mutations that are only tangentially related to metabolism [e.g., the loss of the yeast mating pathway (30)]. In some experiments, these constitutively beneficial mutations may even compose the bulk of the mutations that reach observable frequencies (12, 13, 31). Although many models exist for describing constitutively beneficial or deleterious mutations in the absence of ecology (32), we lack even a basic theoretical understanding of how they behave when they are linked to ecological phenotypes and vice versa. The absence of quantitative theoretical predictions makes it difficult to draw any inferences from the vast molecular data that are now available.
To start to bridge this gap, we introduce a simple, empirically motivated model that describes the interplay between ecological diversification and directional selection at a large number of linked loci. The ecological interactions derive from a well-studied class of consumer resource models (33⇓⇓–36), in which individuals compete for multiple substitutable resources (e.g., different carbon sources) in a well-mixed environment. We extend this ecological model to allow for heritable mutations in resource uptake rates, which can either divert metabolic effort between resources or increase the growth rate on all resources. The latter class of mutations provides a natural way to model adaptation at linked genomic loci.
Constitutively beneficial mutations might seem like an ecologically trivial addition to the model, since they are always favored to invade on short timescales. On longer timescales, however, we show that these accumulated fitness differences can dramatically influence both the ecological structure and the evolutionary dynamics that take place within the community. By focusing on the weak mutation limit, we derive analytical expressions for these dynamics in the two-resource case, and we show how our results extend to larger communities as well. These analytical results provide a general framework for integrating ecological and population-genetic processes in evolving microbial communities and suggest ways in which these processes might be inferred from time-resolved molecular data.
Evolutionary Model of Resource Competition
To investigate the interactions between ecological diversification and directional selection, we focus on a simple ecological model in which individuals compete for an assortment of externally supplied resources in a well-mixed, chemostat-like environment (Fig. 1). This resource-based model aims to capture some of the key ecological features observed in certain microbial evolution experiments (5, 8), as well as more complex ecosystems such as the gut microbiome (18), while remaining as analytically tractable as possible.
Ecological and evolutionary dynamics in a simplified consumer-resource model. (A) Schematic depiction of ecological dynamics. Substitutable resources are supplied to the chemostat at constant rates
In our idealized setting, individuals compete for R substitutable resources, which are supplied by the environment at fixed rates (Fig. 1). Individuals are characterized by a resource utilization vector
We assume that individuals reproduce asexually, so that the state of the ecosystem can be described by the number of individuals
However, the essential features of Eq. 1 are not limited to this consumer-resource framing. In SI Appendix, section 1.4, we argue that Eq. 1 captures the limiting behavior of a much larger class of models in the limit that
The ecological model in Eq. 1 describes only the competition between a fixed set of strains. To incorporate evolution, we also allow for new strains to be created through the process of mutation. We show that it is useful to distinguish between two broad classes of mutations. The first class consists of mutations that alter an individual’s resource uptake strategy (“strategy mutations”). For simplicity, we assume that these mutations constitute a perfect tradeoff, so that the overall fitness X remains unchanged (although we eventually relax this assumption below). We assume that strategy mutations occur at a per-genome rate
We note that this division into fitness and strategy mutations is neither exhaustive nor unambiguous. Some changes in resource strategy may also incur a fitness cost, and one can simulate a pure fitness mutation by shifting metabolic effort away from resources that are not present in the current environment (i.e., those with
For example, pure fitness mutations might seem like an ecologically trivial addition to the model, because they are always favored to invade. However, computer simulations show that these accumulated fitness differences can still have a dramatic influence on both the ecological structure and the evolutionary dynamics that arise in a given population. Fig. 1 depicts individual-based simulations of four populations, which are subject to the same environmental conditions and the same supply of strategy mutations, but have different values of
To understand these different behaviors and how they depend on the underlying parameters, we start by analyzing the simplest nontrivial scenario, in which the strains evolve in an environment with just two resources. In this case, the environmental supply rates and resource uptake strategies can be described by scalar parameters
Analysis
Selection for Ecosystem to Match Environment, Stable Coexistence.
We begin by considering the dynamics in the absence of fitness differences (
We begin by considering a single strategy mutation that occurs in a clonal population of type
At long times, the ecological dynamics will lead to one of two final states: Either the mutant will replace the wild type (competitive exclusion) or the two will coexist at some intermediate frequency (Fig. 2A). The latter scenario will occur if and only if the wild type can reinvade a population of mutants, which requires that the reciprocal invasion fitness,
Schematic illustration of key eco-evolutionary processes in a two-resource ecosystem. (A) Ecological diversification from a clonal ancestor. In the absence of fitness mutations, strains coexist at a stable equilibrium (
Once this ecological equilibrium is attained, number fluctuations will continuously perturb the true frequency away from
Diversification Load.
We are now in a position to analyze how fitness alters the basic picture above. We begin by revisiting the invasion of a mutant strain in an initially clonal population, this time allowing for a fitness difference
Fitness Differences Perturb Ecological Equilibria.
In addition to shifting the invasion fitness of a new mutation, fitness differences can also alter the long-term ecological equilibrium between mutant and wild type in Eq. 6. In the extreme limit, this can disrupt the stable coexistence altogether. If the mutant is less fit than the wild type (
When
Further Fitness Evolution and Diversification–Selection Balance.
Once the population achieves the stable ecology in Eq. 10, additional fitness mutations will occur in each strain with probability proportional to the equilibrium frequency
Similar behavior can occur when
Once the ecosystem collapses, there will be a strong selection pressure for the winning clade to rediversify through additional strategy mutations and restart this process from the beginning (Fig. 2B). To gain insight into these dynamics, we first consider the case where the resource strategies are controlled by a single genetic locus, with fixed phenotypes
Invading Ecotypes Can Delay Ecosystem Collapse.
Strictly speaking, the derivation of Eq. 13 is valid only in the limit that
To analyze this process, we note that successful invasion events will occur as an inhomogeneous Poisson process with rate
Finally, when
Fitness Differences Create Opportunities for Ecological Tinkering.
Our derivation of Eqs. 12 and 14 assumed that the two ecotypes were fixed by the genetic architecture of the organism. Individuals could mutate between
To investigate these selection pressures, we consider a population that is currently described by the steady state in Eq. 10. We then consider strategy mutations that occur on the background of
The direction of selection is determined by the sign of
Invasion fitness landscape for additional strategy mutations in a two-resource ecosystem. The two resident ecotypes are illustrated by blue circles, while red circles denote mutant strains created by strategy mutations on one of the ecotype backgrounds. The solid black line denotes the effective mean fitness,
Once a successful strategy mutation arises, it will sweep through part of the population and alter the ecological equilibrium (Fig. 3). Mutations in the less-fit clade are straightforward to analyze. Since these are always directed away from both β and
Beyond Pairwise Coexistence.
Our previous analysis focused on environments with only two substitutable resources, where at most two strains can coexist at equilibrium. In this case, the structure of the stable ecosystem was simple enough to admit a full analytical solution, which we could use to derive explicit predictions for many evolutionary quantities of interest. However, many microbial communities are found in environments with large numbers of potential resources and flexible gene pools that allow them to alter their resource uptake rates through horizontal gene transfer (41). It is therefore natural to ask how our results generalize to these more complicated environments as well. A full analysis of this case is beyond the scope of the present work, as there are even fewer constraints on the space of ecological and evolutionary parameters compared with the two-resource case. Nevertheless, it is still useful to know whether our qualitative results extend beyond
For a general ecological equilibrium, a mutation that alters the phenotype of a resident strain from
The invasion fitness in Eq. 16 depends on the current community composition only through the intensive variables
In this limit, the steady-state frequencies
While the saturated case is particularly simple, we saw above that fitness mutations can drive the number of surviving species below this saturated value. In contrast to the two-resource case, these “unsaturated ecosystems” can now harbor multiple coexisting strains when
Diversification–selection balance when
In a nearly uniform environment [
(A and B) Schematic of (A) ecological and (B) genealogical structure at the evolutionary steady state described in Eq. 19. In B, blue circles represent pure fitness mutations and red circles represent loss-of-function strategy mutations.
The dynamics of this process can be characterized analytically in the weak mutation limit, yielding a simple heuristic expression for the diversification–selection balance,
This suggests that the relative frailty of the diversification–selection balance in Eq. 19 may be a pathological feature of the simple genetic architecture that we have assumed, in which fit generalist phenotypes are easily accessible. If we instead impose an upper limit
Discussion
In microbial populations, primitive ecological interactions can evolve spontaneously over years (5), months (6), and even days (7). Yet this process rarely takes place in isolation. In rapidly evolving populations, diversifying selection must compete with directional selection acting on other loci throughout the genome. Here, we have introduced a simple mathematical framework to model the interactions between these two processes in asexually reproducing organisms.
The ecological interactions in our model emerge from the competition for substitutable resources (e.g., different carbon sources), according to a well-studied class of models from theoretical ecology (33⇓⇓–36). To incorporate evolution into this model, we assumed that individuals can acquire mutations that alter their resource uptake rates. We showed that it is useful to distinguish between two characteristic types of mutations: (i) strategy mutations, which divert metabolic effort from one resource to another, and (ii) fitness mutations, which increase the overall growth rate but leave the relative uptake rates unchanged. Strategy mutations enable ecological diversification, while fitness mutations capture the effects of directional selection at other genomic loci.
This classification scheme is best viewed as a conceptual tool, rather than a statement about the underlying biology. We have mostly focused on mutations with either a perfect tradeoff or a perfect benefit, but Eqs. 7 and 16 apply equally well in more realistic cases where a shift in resource strategy is accompanied by a change in the overall growth rate. These expressions can be used to predict when the costs of an opportunistic mutation will outweigh its ecological benefits or vice versa. Similarly, true fitness mutations (e.g., an increase in ATP efficiency) are assumed to be rare in nature, since they could have fixed in the population long ago. In practice, effective fitness mutations are more likely to correspond to strategy mutations whose tradeoffs are simply not exposed by the current environmental conditions. In this picture, the overall fitness
The creation of new strains via mutation bears a superficial resemblance to immigration from a fixed species pool, which is the traditional scenario considered in theoretical ecology. However, this analogy is exact only in the absence of inheritance, when the phenotypes of nearby genotypes are uncorrelated from each other. In contrast, when the effects of mutations are heritable, we have seen that directional selection can produce dramatic departures from traditional ecological predictions.
Similar to immigration (36, 42), strategy mutations allow an initially clonal population to diversify into stably coexisting ecotypes, whose upper bound is set by the number of resources. Yet because fitness mutations are heritable, further evolution will lead to fitness differences between the clades, which can dynamically shift the ecological equilibrium over time and eventually drive less-fit clades to extinction. The mere observation that selection can disrupt coexistence is not surprising, since drug resistance or other harsh selection regimes provide striking examples of this effect. However, our quantitative analysis shows that this collapse can happen long before any clade is universally inferior to another and that it can result from the compound effect of many small-effect mutations that would not lead to extinction on their own. These results suggest that ongoing directional selection may have a larger impact on the structure of microbial communities than is often assumed. In particular, while previous ecological analyses suggest that the number of ecotypes should meet (35, 36) or even exceed (34) the number of resources, our results raise the possibility that they could also reside at a diversification–selection balance below the maximum capacity of the ecosystem.
In addition to their influence on coexistence, we also found that fitness differences accrued via directional selection will generate emergent selection pressures for continual evolution of the ecological phenotypes, even in a saturated ecosystem. While these internal selection pressures are reminiscent of the Red Queen effect (43), our quantitative analysis shows that they select for different phenotypes than in the standard predator–prey setting. In particular, less-fit clades do not experience increased selection pressure to narrow their fitness deficit by accumulating fitness mutations. Instead, selection favors mutations that divert metabolic effort toward resources with lower effective competition, even at the cost of widening the fitness deficit. Moreover, the direction of selection toward any given resource can shift dynamically as the fitness differences and resource uptake strategies evolve over time.
Most of our analysis focused on the strong-selection–weak-mutation regime, in which the current ecological equilibrium is attained before the next mutation occurs. In this limit, when the resource uptake strategies are sufficiently close to the supply rates, our model takes on a universal form that closely resembles traditional models of adaptive dynamics (22, 44). The key difference is that directional selection behaves as an additional trait dimension, which is effectively constrained to remain far from its optimum at all times (SI Appendix, Fig. S1 and section 4). Our results show that this simple broken symmetry can lead to dramatic deviations from the standard adaptive dynamics picture.
In contrast to adaptive dynamics, we also allow for mutations that have noninfinitesimal effects on resource uptake rates, which turn out to play a key role in controlling the dynamical behaviors that we observe. In practice, the genetic architectures of most ecological interactions remain poorly characterized empirically. In a few well-studied cases, ecological diversification can be traced to a single large-effect mutation (9, 45), while in others, a series of smaller mutations have been implicated (46). Our present analysis suggests potential ways to constrain this key parameter experimentally, either by analyzing fluctuations in ecotype frequencies on long timescales (13) or by measuring the joint distribution invasion fitness (
Of course, the present work has focused on a highly simplified model, which omits many of the complicating factors expected in either natural or laboratory settings. A particularly important limitation is our focus on the weak mutation limit (
It is also interesting to ask whether our results can be mapped onto more diverse modes of ecological interaction or whether there are other universality classes yet to be discovered. Since our model can be viewed as the simplest generalization of population genetics with multiple fitness axes, we hypothesize that it may capture the limiting behavior of a broader class of ecological interactions that are mediated by a small number of intensive variables. If so, its analytical tractability may offer a promising avenue for investigating the interactions between ecology and evolution more generally.
Acknowledgments
B.H.G. thanks Evgeni Frenkel and Ned Wingreen for discussions that inspired the development of the model. B.H.G. acknowledges support from the Miller Institute for Basic Research in Science at the University of California, Berkeley. O.H. acknowledges support from National Science Foundation Career Award 1555330, Simons Investigator Award 327934 from the Simons Foundation, and National Institutes of Health Grant R01GM115851. This research used resources of the National Energy Research Scientific Computing Center, a Department of Energy (DOE) Office of Science User Facility supported by the Office of Science of the US DOE under Contract DE-AC02-05CH11231.
Footnotes
- ↵1To whom correspondence should be addressed. Email: benjamin.h.good{at}berkeley.edu.
Author contributions: B.H.G., S.M., and O.H. designed research, performed research, and wrote the paper.
The authors declare no conflict of interest.
This article is a PNAS Direct Submission.
This article contains supporting information online at www.pnas.org/lookup/suppl/doi:10.1073/pnas.1807530115/-/DCSupplemental.
Published under the PNAS license.
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