Linkage equilibrium between rare mutations.

Recombination breaks down genetic linkage by reshuffling existing variants onto new genetic backgrounds. These dynamics are traditionally quantified by examining the correlations between alleles, and how they decay as a function of the recombination rate. However, the magnitudes of these correlations are strongly influenced by other evolutionary forces like natural selection and genetic drift, making it difficult to tease out the effects of recombination. Here we introduce a theoretical framework for analyzing an alternative family of statistics that measure the homoplasy produced by recombination. We derive analytical expressions that predict how these statistics depend on the rates of recombination and recurrent mutation, the strength of negative selection and genetic drift, and the present-day frequencies of the mutant alleles. We find that the degree of homoplasy can strongly depend on this frequency scale, which reflects the underlying timescales over which these mutations occurred. We show how these scaling properties can be used to isolate the effects of recombination, and discuss their implications for the rates of horizontal gene transfer in bacteria.

Dynamics of bacterial recombination in the human gut microbiome.

Horizontal gene transfer (HGT) is a ubiquitous force in microbial evolution. Previous work has shown that the human gut is a hotspot for gene transfer between species, but the more subtle exchange of variation within species-also known as recombination-remains poorly characterized in this ecosystem. Here, we show that the genetic structure of the human gut microbiome provides an opportunity to measure recent recombination events from sequenced fecal samples, enabling quantitative comparisons across diverse commensal species that inhabit a common environment. By analyzing recent recombination events in the core genomes of 29 human gut bacteria, we observed widespread heterogeneities in the rates and lengths of transferred fragments, which are difficult to explain by existing models of ecological isolation or homology-dependent recombination rates. We also show that natural selection helps facilitate the spread of genetic variants across strain backgrounds, both within individual hosts and across the broader population. These results shed light on the dynamics of in situ recombination, which can strongly constrain the adaptability of gut microbial communities.

Quantifying the adaptive landscape of commensal gut bacteria using high-resolution lineage tracking.

Gut microbiota can adapt to their host environment by rapidly acquiring new mutations. However, the dynamics of this process are difficult to characterize in dominant gut species in their complex in vivo environment. Here we show that the fine-scale dynamics of genome-wide transposon libraries can enable quantitative inferences of these in vivo evolutionary forces. By analyzing >400,000 lineages across four human Bacteroides strains in gnotobiotic mice, we observed positive selection on thousands of cryptic variants - most of which were unrelated to their original gene knockouts. The spectrum of fitness benefits varied between species, and displayed diverse tradeoffs over time and in different dietary conditions, enabling inferences of their underlying function. These results suggest that within-host adaptations arise from an intense competition between numerous contending variants, which can strongly influence their emergent evolutionary tradeoffs.

Predicting the First Steps of Evolution in Randomly Assembled Communities.

Microbial communities can self-assemble into highly diverse states with predictable statistical properties. However, these initial states can be disrupted by rapid evolution of the resident strains. When a new mutation arises, it competes for resources with its parent strain and with the other species in the community. This interplay between ecology and evolution is difficult to capture with existing community assembly theory. Here, we introduce a mathematical framework for predicting the first steps of evolution in large randomly assembled communities that compete for substitutable resources. We show how the fitness effects of new mutations and the probability that they coexist with their parent depends on the size of the community, the saturation of its niches, and the metabolic overlap between its members. We find that successful mutations are often able to coexist with their parent strains, even in saturated communities with low niche availability. At the same time, these invading mutants often cause extinctions of metabolically distant species. Our results suggest that even small amounts of evolution can produce distinct genetic signatures in natural microbial communities.

Competition for shared resources increases dependence on initial population size during coalescence of gut microbial communities.

The long-term success of introduced populations depends on their initial size and ability to compete against existing residents, but it remains unclear how these factors collectively shape colonization. Here, we investigate how initial population (propagule) size and resource competition interact during community coalescence by systematically mixing eight pairs of in vitro microbial communities at ratios that vary over six orders of magnitude, and we compare our results to a neutral ecological model. Although the composition of the resulting co-cultures deviated substantially from neutral expectations, each co-culture contained species whose relative abundance depended on propagule size even after ~40 generations of growth. Using a consumer-resource model, we show that this dose-dependent colonization can arise when resident and introduced species have high niche overlap and consume shared resources at similar rates. This model predicts that propagule size will have larger, longer-lasting effects in diverse communities in which niche overlap is higher, and we experimentally confirm that strain isolates show stronger dose dependence when introduced into diverse communities than in pairwise co-culture. This work shows how neutral-like colonization dynamics can emerge from non-neutral resource competition and have lasting effects on the outcomes of community coalescence.

Eco-evolutionary feedbacks in the human gut microbiome.

Gut microbiota can evolve within their hosts on human-relevant timescales, but little is known about how these changes influence (or are influenced by) the composition of their local community. Here, by combining ecological and evolutionary analyses of a large cohort of human gut metagenomes, we show that the short-term evolution of the microbiota is linked with shifts in its ecological structure. These correlations are not simply explained by expansions of the evolving species, and often involve additional fluctuations in distantly related taxa. We show that similar feedbacks naturally emerge in simple resource competition models, even in the absence of cross-feeding or predation. These results suggest that the structure and function of host microbiota may be shaped by their local evolutionary history, which could have important implications for personalized medicine and microbiome engineering.

Prolonged delays in human microbiota transmission after a controlled antibiotic perturbation.

Humans constantly encounter new microbes, but few become long-term residents of the adult gut microbiome. Classical theories predict that colonization is determined by the availability of open niches, but it remains unclear whether other ecological barriers limit commensal colonization in natural settings. To disentangle these effects, we used a controlled perturbation with the antibiotic ciprofloxacin to investigate the dynamics of gut microbiome transmission in 22 households of healthy, cohabiting adults. Colonization was rare in three-quarters of antibiotic-taking subjects, whose resident strains rapidly recovered in the week after antibiotics ended. In contrast, the remaining antibiotic-taking subjects exhibited lasting responses, with extensive species losses and transient expansions of potential opportunistic pathogens. These subjects experienced elevated rates of commensal colonization, but only after long delays: many new colonizers underwent sudden, correlated expansions months after the antibiotic perturbation. Furthermore, strains that had previously transmitted between cohabiting partners rarely recolonized after antibiotic disruptions, showing that colonization displays substantial historical contingency. This work demonstrates that there remain substantial ecological barriers to colonization even after major microbiome disruptions, suggesting that dispersal interactions and priority effects limit the pace of community change.

Quantifying the local adaptive landscape of a nascent bacterial community.

The fitness effects of all possible mutations available to an organism largely shape the dynamics of evolutionary adaptation. Yet, whether and how this adaptive landscape changes over evolutionary times, especially upon ecological diversification and changes in community composition, remains poorly understood. We sought to fill this gap by analyzing a stable community of two closely related ecotypes ("L" and "S") shortly after they emerged within the E. coli Long-Term Evolution Experiment (LTEE). We engineered genome-wide barcoded transposon libraries to measure the invasion fitness effects of all possible gene knockouts in the coexisting strains as well as their ancestor, for many different, ecologically relevant conditions. We find consistent statistical patterns of fitness effect variation across both genetic background and community composition, despite the idiosyncratic behavior of individual knockouts. Additionally, fitness effects are correlated with evolutionary outcomes for a number of conditions, possibly revealing shifting patterns of adaptation. Together, our results reveal how ecological and epistatic effects combine to shape the adaptive landscape in a nascent ecological community.

Within-host evolution of the gut microbiome.

Gut bacteria inhabit a complex environment that is shaped by interactions with their host and the other members of the community. While these ecological interactions have evolved over millions of years, mounting evidence suggests that gut commensals can evolve on much shorter timescales as well, by acquiring new mutations within individual hosts. In this review, we highlight recent progress in understanding the causes and consequences of short-term evolution in the mammalian gut, from experimental evolution in murine hosts to longitudinal tracking of human cohorts. We also discuss new opportunities for future progress by expanding the repertoire of focal species, hosts, and surrounding communities, and by combining deep-sequencing technologies with quantitative frameworks from population genetics.

Emergent evolutionary forces in spatial models of luminal growth and their application to the human gut microbiota.

The genetic composition of the gut microbiota is constantly reshaped by ecological and evolutionary forces. These strain-level dynamics are challenging to understand because they depend on complex spatial growth processes that take place within a host. Here we introduce a population genetic framework to predict how stochastic evolutionary forces emerge from simple models of microbial growth in spatially extended environments like the intestinal lumen. Our framework shows how fluid flow and longitudinal variation in growth rate combine to shape the frequencies of genetic variants in simulated fecal samples, yielding analytical expressions for the effective generation times, selection coefficients, and rates of genetic drift. We find that over longer timescales, the emergent evolutionary dynamics can often be captured by well-mixed models that lack explicit spatial structure, even when there is substantial spatial variation in species-level composition. By applying these results to the human colon, we find that continuous fluid flow and simple forms of wall growth alone are unlikely to create sufficient bottlenecks to allow large fluctuations in mutant frequencies within a host. We also find that the effective generation times may be significantly shorter than expected from traditional average growth rate estimates. Our results provide a starting point for quantifying genetic turnover in spatially extended settings like the gut microbiota and may be relevant for other microbial ecosystems where unidirectional fluid flow plays an important role.

Competition for fluctuating resources reproduces statistics of species abundance over time across wide-ranging microbiotas.

Across diverse microbiotas, species abundances vary in time with distinctive statistical behaviors that appear to generalize across hosts, but the origins and implications of these patterns remain unclear. Here, we show that many of these macroecological patterns can be quantitatively recapitulated by a simple class of consumer-resource models, in which the metabolic capabilities of different species are randomly drawn from a common statistical distribution. Our model parametrizes the consumer-resource properties of a community using only a small number of global parameters, including the total number of resources, typical resource fluctuations over time, and the average overlap in resource-consumption profiles across species. We show that variation in these macroscopic parameters strongly affects the time series statistics generated by the model, and we identify specific sets of global parameters that can recapitulate macroecological patterns across wide-ranging microbiotas, including the human gut, saliva, and vagina, as well as mouse gut and rice, without needing to specify microscopic details of resource consumption. These findings suggest that resource competition may be a dominant driver of community dynamics. Our work unifies numerous time series patterns under a simple model, and provides an accessible framework to infer macroscopic parameters of effective resource competition from longitudinal studies of microbial communities.

Population genetics of polymorphism and divergence in rapidly evolving populations.

In rapidly evolving populations, numerous beneficial and deleterious mutations can arise and segregate within a population at the same time. In this regime, evolutionary dynamics cannot be analyzed using traditional population genetic approaches that assume that sites evolve independently. Instead, the dynamics of many loci must be analyzed simultaneously. Recent work has made progress by first analyzing the fitness variation within a population, and then studying how individual lineages interact with this traveling fitness wave. However, these "traveling wave" models have previously been restricted to extreme cases where selection on individual mutations is either much faster or much slower than the typical coalescent timescale Tc. In this work, we show how the traveling wave framework can be extended to intermediate regimes in which the scaled fitness effects of mutations (Tcs) are neither large nor small compared to one. This enables us to describe the dynamics of populations subject to a wide range of fitness effects, and in particular, in cases where it is not immediately clear which mutations are most important in shaping the dynamics and statistics of genetic diversity. We use this approach to derive new expressions for the fixation probabilities and site frequency spectra of mutations as a function of their scaled fitness effects, along with related results for the coalescent timescale Tc and the rate of adaptation or Muller's ratchet. We find that competition between linked mutations can have a dramatic impact on the proportions of neutral and selected polymorphisms, which is not simply summarized by the scaled selection coefficient Tcs. We conclude by discussing the implications of these results for population genetic inferences.

Linkage disequilibrium between rare mutations.

The statistical associations between mutations, collectively known as linkage disequilibrium, encode important information about the evolutionary forces acting within a population. Yet in contrast to single-site analogues like the site frequency spectrum, our theoretical understanding of linkage disequilibrium remains limited. In particular, little is currently known about how mutations with different ages and fitness costs contribute to expected patterns of linkage disequilibrium, even in simple settings where recombination and genetic drift are the major evolutionary forces. Here, I introduce a forward-time framework for predicting linkage disequilibrium between pairs of neutral and deleterious mutations as a function of their present-day frequencies. I show that the dynamics of linkage disequilibrium become much simpler in the limit that mutations are rare, where they admit a simple heuristic picture based on the trajectories of the underlying lineages. I use this approach to derive analytical expressions for a family of frequency-weighted linkage disequilibrium statistics as a function of the recombination rate, the frequency scale, and the additive and epistatic fitness costs of the mutations. I find that the frequency scale can have a dramatic impact on the shapes of the resulting linkage disequilibrium curves, reflecting the broad range of time scales over which these correlations arise. I also show that the differences between neutral and deleterious linkage disequilibrium are not purely driven by differences in their mutation frequencies and can instead display qualitative features that are reminiscent of epistasis. I conclude by discussing the implications of these results for recent linkage disequilibrium measurements in bacteria. This forward-time approach may provide a useful framework for predicting linkage disequilibrium across a range of evolutionary scenarios.

Quantifying rapid bacterial evolution and transmission within the mouse intestine.

Due to limitations on high-resolution strain tracking, selection dynamics during gut microbiota colonization and transmission between hosts remain mostly mysterious. Here, we introduced hundreds of barcoded Escherichia coli strains into germ-free mice and quantified strain-level dynamics and metagenomic changes. Mutations in genes involved in motility and metabolite utilization are reproducibly selected within days. Even with rapid selection, coprophagy enforced similar barcode distributions across co-housed mice. Whole-genome sequencing of hundreds of isolates revealed linked alleles that demonstrate between-host transmission. A population-genetics model predicts substantial fitness advantages for certain mutants and that migration accounted for ∼10% of the resident microbiota each day. Treatment with ciprofloxacin suggests interplay between selection and transmission. While initial colonization was mostly uniform, in two mice a bottleneck reduced diversity and selected for ciprofloxacin resistance in the absence of drug. These findings highlight the interplay between environmental transmission and rapid, deterministic selection during evolution of the intestinal microbiota.

Longitudinal linked-read sequencing reveals ecological and evolutionary responses of a human gut microbiome during antibiotic treatment.

Gut microbial communities can respond to antibiotic perturbations by rapidly altering their taxonomic and functional composition. However, little is known about the strain-level processes that drive this collective response. Here, we characterize the gut microbiome of a single individual at high temporal and genetic resolution through a period of health, disease, antibiotic treatment, and recovery. We used deep, linked-read metagenomic sequencing to track the longitudinal trajectories of thousands of single nucleotide variants within 36 species, which allowed us to contrast these genetic dynamics with the ecological fluctuations at the species level. We found that antibiotics can drive rapid shifts in the genetic composition of individual species, often involving incomplete genome-wide sweeps of pre-existing variants. These genetic changes were frequently observed in species without obvious changes in species abundance, emphasizing the importance of monitoring diversity below the species level. We also found that many sweeping variants quickly reverted to their baseline levels once antibiotic treatment had concluded, demonstrating that the ecological resilience of the microbiota can sometimes extend all the way down to the genetic level. Our results provide new insights into the population genetic forces that shape individual microbiomes on therapeutically relevant timescales, with potential implications for personalized health and disease.

Evolutionary dynamics of bacteria in the gut microbiome within and across hosts.

Gut microbiota are shaped by a combination of ecological and evolutionary forces. While the ecological dynamics have been extensively studied, much less is known about how species of gut bacteria evolve over time. Here, we introduce a model-based framework for quantifying evolutionary dynamics within and across hosts using a panel of metagenomic samples. We use this approach to study evolution in approximately 40 prevalent species in the human gut. Although the patterns of between-host diversity are consistent with quasi-sexual evolution and purifying selection on long timescales, we identify new genealogical signatures that challenge standard population genetic models of these processes. Within hosts, we find that genetic differences that accumulate over 6-month timescales are only rarely attributable to replacement by distantly related strains. Instead, the resident strains more commonly acquire a smaller number of putative evolutionary changes, in which nucleotide variants or gene gains or losses rapidly sweep to high frequency. By comparing these mutations with the typical between-host differences, we find evidence that some sweeps may be seeded by recombination, in addition to new mutations. However, comparisons of adult twins suggest that replacement eventually overwhelms evolution over multi-decade timescales, hinting at fundamental limits to the extent of local adaptation. Together, our results suggest that gut bacteria can evolve on human-relevant timescales, and they highlight the connections between these short-term evolutionary dynamics and longer-term evolution across hosts.

Effective models and the search for quantitative principles in microbial evolution.

Microbes evolve rapidly. Yet they do so in idiosyncratic ways, which depend on the specific mutations that are beneficial or deleterious in a given situation. At the same time, some population-level patterns of adaptation are strikingly similar across different microbial systems, suggesting that there may also be simple, quantitative principles that unite these diverse scenarios. We review the search for simple principles in microbial evolution, ranging from the biophysical level to emergent evolutionary dynamics. A key theme has been the use of effective models, which coarse-grain over molecular and cellular details to obtain a simpler description in terms of a few effective parameters. Collectively, these theoretical approaches provide a set of quantitative principles that facilitate understanding, prediction, and potentially control of evolutionary phenomena, though formidable challenges remain due to the ecological complexity of natural populations.

Adaptation limits ecological diversification and promotes ecological tinkering during the competition for substitutable resources.

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.

The Effect of Strong Purifying Selection on Genetic Diversity.

Purifying selection reduces genetic diversity, both at sites under direct selection and at linked neutral sites. This process, known as background selection, is thought to play an important role in shaping genomic diversity in natural populations. Yet despite its importance, the effects of background selection are not fully understood. Previous theoretical analyses of this process have taken a backward-time approach based on the structured coalescent. While they provide some insight, these methods are either limited to very small samples or are computationally prohibitive. Here, we present a new forward-time analysis of the trajectories of both neutral and deleterious mutations at a nonrecombining locus. We find that strong purifying selection leads to remarkably rich dynamics: neutral mutations can exhibit sweep-like behavior, and deleterious mutations can reach substantial frequencies even when they are guaranteed to eventually go extinct. Our analysis of these dynamics allows us to calculate analytical expressions for the full site frequency spectrum. We find that whenever background selection is strong enough to lead to a reduction in genetic diversity, it also results in substantial distortions to the site frequency spectrum, which can mimic the effects of population expansions or positive selection. Because these distortions are most pronounced in the low and high frequency ends of the spectrum, they become particularly important in larger samples, but may have small effects in smaller samples. We also apply our forward-time framework to calculate other quantities, such as the ultimate fates of polymorphisms or the fitnesses of their ancestral backgrounds.

The dynamics of molecular evolution over 60,000 generations.

The outcomes of evolution are determined by a stochastic dynamical process that governs how mutations arise and spread through a population. However, it is difficult to observe these dynamics directly over long periods and across entire genomes. Here we analyse the dynamics of molecular evolution in twelve experimental populations of Escherichia coli, using whole-genome metagenomic sequencing at five hundred-generation intervals through sixty thousand generations. Although the rate of fitness gain declines over time, molecular evolution is characterized by signatures of rapid adaptation throughout the duration of the experiment, with multiple beneficial variants simultaneously competing for dominance in each population. Interactions between ecological and evolutionary processes play an important role, as long-term quasi-stable coexistence arises spontaneously in most populations, and evolution continues within each clade. We also present evidence that the targets of natural selection change over time, as epistasis and historical contingency alter the strength of selection on different genes. Together, these results show that long-term adaptation to a constant environment can be a more complex and dynamic process than is often assumed.