Benjamin H. Good

The ratio of nonsynonymous to synonymous substitutions (dN/dS) encodes important information about the selection pressures acting on protein-coding genes. In bacterial populations, dN/dS often declines with the sequence divergence between strains, but the mechanisms responsible for this broad empirical trend are still debated. Existing models have primarily focused on de novo mutations, overlooking the older genetic variants that are continually introduced through horizontal gene transfer and recombination. Here we introduce a phenomenological model of dN/dS in recombining populations of bacteria, which allows us to disentangle the effects of recombination among pairs of closely related strains. We find that clonally inherited regions of the genome exhibit consistently higher dN/dS ratios, and that the accumulation of recombined segments can quantitatively explain the majority of the decline in dN/dS. We use these observations to re-examine models of purifying selection and adaptive reversion in human gut bacteria, and uncover evidence for widespread weak selection at a large fraction of protein-coding sites. Our findings show that horizontal gene transfer can be an important factor in shaping genome-wide patterns of selective constraint, and raise new questions about the effectiveness of natural selection in complex bacterial populations.

In fluctuating environments, the fates of new mutations depend on the fitness tradeoffs they experience across multiple environmental conditions. Selection on these tradeoffs is well-understood when mutations compete in isolation, but much less is known in the empirically relevant case where multiple mutations compete at the same time. Here, we develop a theory to predict how rapidly adapting populations select on fitness tradeoffs at many linked genetic loci. We derive analytical expressions showing how the fixation probabilities of these mutations depend on their underlying fitness tradeoffs, the timescales of environmental variation, and the future mutations they produce over time. We find that in large populations, competition between linked mutations can strongly favor mutations that carry larger fitness tradeoffs, even when they have a lower geometric mean fitness. We show that this “specialist advantage” arises because transient benefits enhance the rate of producing future mutations – an effect that continues to compound over time even when local conditions shift. We also demonstrate that successful lineages acquire well-timed mutations that appear to anticipate future environments, which can boost the rate of adaptation. These results show how large populations balance competing demands in temporally fluctuating environments, and provide a baseline for interpreting fitness tradeoffs in many natural and experimental settings.

Gut bacteria exhibit striking variation across different human populations, but the evolutionary forces that have shaped this diversity are less well understood. Recent work has argued that many species of gut bacteria have codiversified with modern humans, based on the phylogenetic correlations between human and microbial genomes. Here, I re-analyze these data and show that the correlations between human and microbial phylogenies are often substantially weaker than those between unlinked human chromosomes and that similar correlations can arise through geographic structure alone. These results suggest that traditional codiversification has been limited in recent human history and highlight alternative strategies for quantifying the extent of human-microbe coevolution. IMPORTANCE: There is widespread interest in understanding the evolutionary history of our gut microbiota and how it varies within and among different human population groups. This Observation critically re-examines the hypothesis that many commensal gut bacteria have evolved in parallel (or “codiversified”) with modern humans, providing new evidence that the correlations between human and microbial genealogies are weaker than previously supposed. These findings have important evolutionary implications and also practical consequences, from the sourcing of probiotic therapies to the design of sequencing-based diagnostics.

Microbial populations have an enormous capacity for rapid evolutionary change. Some mutations increase the fitness of their lineage and compete with each other in a process known as clonal interference. Other mutations can evade competitive exclusion by diversifying into distinct ecological niches. Both processes are frequently observed in natural and experimental settings, yet little is known about how they interact in the parameter regimes most relevant for microbes. Here we address this gap by analyzing the dynamics of ecological diversification in a simple class of resource competition models, where individuals acquire mutations that alter their resource uptake rates. We focus on large adapting populations, where mutations occur so frequently that their ecological and evolutionary timescales overlap. In this regime, we show that the competition between linked mutations causes the population to self-organize into a smaller number of distinct ecotypes, driven by an emergent priority effect that favors the resident strains. We demonstrate that these priority effects bias the long-term metabolic structure of the population, producing qualitative departures from existing ecological theory. We argue that similar dynamics should arise for other rapidly evolving ecosystems, where adaptive mutations accumulate at many linked genetic loci.

Recovery of the gut microbiome after antibiotic exposure is often incomplete and variable, and the processes underlying this variation remain unclear. We performed longitudinal shotgun metagenomic sequencing of 2876 daily fecal samples from replicated humanized and conventional mouse cohorts exposed to controlled antibiotic perturbations. Metagenomic profiling recapitulated ecological trajectories previously observed by 16S sequencing, while revealing extensive strain-level dynamics, including reproducible sweeps of standing variants and de novo mutations in antibiotic target sites and regulatory loci. We also identified genetic changes whose effects depended on community composition, competitive release, and perturbation history. Cross-housing experiments revealed bidirectional strain transfer, with antibiotic-induced niche clearance enabling replacement of resident strains. In parallel, phage dynamics were heterogeneous and clustered by cage. Together, these findings show that post-antibiotic microbiome recovery is a path-dependent process shaped by selection, transmission, and phage activity, producing divergent outcomes even among closely matched communities exposed to the same perturbations.

B cells producing high-affinity antibodies arise through affinity maturation within germinal centers (GCs), where selection is driven by T follicular helper (T _FH ) cells. Recent studies have shown that, like GC B cells, T _FH cells also undergo antigen-dependent selection, with competition among T _FH clones dictated by their ability to recognize and stimulate B cells. This sensitivity-dependent selection process leads to dynamic remodeling of the T _FH repertoire over time. Despite the essential role of T _FH cells in B cell selection, the functional consequences of the time evolution of the T _FH cell population remains poorly understood. To address this gap, we developed a population dynamics model that explicitly incorporates key T _FH cell properties and dynamics. Our analysis predicts that dynamic feedback between B and T _FH cell populations provides robust homeostatic regulation of their numbers in the GC, yielding a stable lymphocyte ratio that we verify experimentally. Moreover, our model predicts that T _FH clone sensitivity dictates distinct evolutionary strategies during affinity maturation, with low-sensitivity T _FH cells accelerating affinity gain at the expense of B cell diversity, while high-sensitivity T _FH cells slow affinity maturation but preserve a broader B cell repertoire. These findings highlight the importance of co-regulation between T _FH and B cells and suggest that reciprocal stimulation allows the immune system to tune the tradeoff between the speed of affinity gain and the breadth of B cell diversity—a principle that may extend to other adaptive systems. Significance Statement: Effector B cells that secrete high-affinity antibodies and form immunological memory are essential for humoral immunity and arise from germinal center (GC) reactions. Within GCs, B cells undergo an accelerated version of Darwinian evolution to enhance antibody affinity. This process is orchestrated by T follicular helper (T _FH ) cells which provide stimulatory signals to selected B cells and undergo their own antigen-driven selection. To investigate this co-evolutionary process, we developed a tractable population-level model of the GC reaction. Our analysis reveals that the reciprocal stimulation of B and T _FH cells provides a robust mechanism for regulating the B:T _FH ratio and tuning the tradeoff between the speed of affinity maturation and the diversity of the antibody response.

Complex microbial ecosystems harbor extensive intra-species diversity, but the fitness consequences of this genetic variation are poorly understood in community settings. Here we address this question by competing in vitro gut communities derived from different human donors, revealing the emergent fitness differences between conspecific strains as they competed within larger communities. Most pairs of strains experienced strong and context-dependent selection, even when their parent communities were originally selected in the same nutrient environment. However, these fitness differences typically attenuated over time due to biotic interactions within the community, leading to extended coexistence within many species, and competitive exclusion in others. These results support the view that conspecific strains can fulfill distinct ecological roles when competing within a diverse community, even when their genomic diversity exhibits the hallmarks of a single biological species.

Affinity maturation enhances B cell binding within germinal centers, where spatial structure preserves sequence diversity by restricting cell movement. While recent studies show that some B cell lineages span multiple germinal centers, the sources, rates and consequences of this spreading process remain unknown. Here, we show that the spatial arrangement of B cells in the human tonsil is driven by local migration during affinity maturation. Through an evolutionary re-analysis of spatial transcriptomics data, we demonstrate that these local migrations follow a clock-like process, in which cells migrate at an average rate of ∼1/50 cell divisions that is consistent across lineages and time. Migrating cells continue to evolve and diversify in their new germinal centers at similar rates, such that the largest lineages in each germinal center often originate from another. These results suggest that affinity maturation operates in a regime of pervasive but intermediate migration, balancing diversity and selection.

Microbial populations have an enormous capacity for rapid evolutionary change. Some mutations increase the fitness of their lineage and compete with each other in a process known as clonal interference. Other mutations can evade competitive exclusion by diversifying into distinct ecological niches. Both processes are frequently observed in natural and experimental settings, yet little is known about how they interact in the parameter regimes most relevant for microbes. Here we address this gap by analyzing the dynamics of ecological diversification in a simple class of resource competition models, where individuals acquire mutations that alter their resource uptake rates. We focus on large adapting populations, where mutations occur so frequently that their ecological and evolutionary timescales overlap. In this regime, we show that the competition between linked mutations causes the population to self-organize into a smaller number of distinct ecotypes, driven by an emergent priority effect that favors the resident strains. We demonstrate that these priority effects bias the long-term metabolic structure of the population, producing qualitative departures from existing ecological theory. We argue that similar dynamics should arise for other rapidly evolving ecosystems, where adaptive mutations accumulate at many linked genetic loci.