Eco-evolutionary dynamics: The repeatability of diversification in an experimental microbial community.

Understanding the evolution and subsequent maintenance of ecological diversity is a daunting task. Using a historical microbial evolution experiment, a new paper demonstrates the extent to which diversity can re-emerge in reduced communities and the traits through which rediversification occurs.

Investigating macroecological patterns in coarse-grained microbial communities using the stochastic logistic model of growth.

The structure and diversity of microbial communities are intrinsically hierarchical due to the shared evolutionary history of their constituents. This history is typically captured through taxonomic assignment and phylogenetic reconstruction, sources of information that are frequently used to group microbes into higher levels of organization in experimental and natural communities. Connecting community diversity to the joint ecological dynamics of the abundances of these groups is a central problem of community ecology. However, how microbial diversity depends on the scale of observation at which groups are defined has never been systematically examined. Here, we used a macroecological approach to quantitatively characterize the structure and diversity of microbial communities among disparate environments across taxonomic and phylogenetic scales. We found that measures of biodiversity at a given scale can be consistently predicted using a minimal model of ecology, the Stochastic Logistic Model of growth (SLM). This result suggests that the SLM is a more appropriate null-model for microbial biodiversity than alternatives such as the Unified Neutral Theory of Biodiversity. Extending these within-scale results, we examined the relationship between measures of biodiversity calculated at different scales (e.g. genus vs. family), an empirical pattern previously evaluated in the context of the Diversity Begets Diversity (DBD) hypothesis (Madi et al., 2020). We found that the relationship between richness estimates at different scales can be quantitatively predicted assuming independence among community members, demonstrating that the DBD can be sufficiently explained using the SLM as a null model of ecology. Contrastingly, only by including correlations between the abundances of community members (e.g. as the consequence of interactions) can we predict the relationship between estimates of diversity at different scales. The results of this study characterize novel microbial patterns across scales of organization and establish a sharp demarcation between recently proposed macroecological patterns that are not and are affected by ecological interactions.

A macroecological perspective on genetic diversity in the human gut microbiome.

While the human gut microbiome has been intensely studied, we have yet to obtain a sufficient understanding of the genetic diversity that it harbors. Research efforts have demonstrated that a considerable fraction of within-host genetic variation in the human gut is driven by the ecological dynamics of co-occurring strains belonging to the same species, suggesting that an ecological lens may provide insight into empirical patterns of genetic diversity. Indeed, an ecological model of self-limiting growth and environmental noise known as the Stochastic Logistic Model (SLM) was recently shown to successfully predict the temporal dynamics of strains within a single human host. However, its ability to predict patterns of genetic diversity across human hosts has yet to be tested. In this manuscript I determine whether the predictions of the SLM explain patterns of genetic diversity across unrelated human hosts for 22 common microbial species. Specifically, the stationary distribution of the SLM explains the distribution of allele frequencies across hosts and predicts the fraction of hosts harboring a given allele (i.e., prevalence) for a considerable fraction of sites. The accuracy of the SLM was correlated with independent estimates of strain structure, suggesting that patterns of genetic diversity in the gut microbiome follow statistically similar forms across human hosts due to the existence of strain-level ecology.

Bacteria-phage coevolution with a seed bank.

Dormancy is an adaptation to living in fluctuating environments. It allows individuals to enter a reversible state of reduced metabolic activity when challenged by unfavorable conditions. Dormancy can also influence species interactions by providing organisms with a refuge from predators and parasites. Here we test the hypothesis that, by generating a seed bank of protected individuals, dormancy can modify the patterns and processes of antagonistic coevolution. We conducted a factorially designed experiment where we passaged a bacterial host (Bacillus subtilis) and its phage (SPO1) in the presence versus absence of a seed bank consisting of dormant endospores. Owing in part to the inability of phages to attach to spores, seed banks stabilized population dynamics and resulted in minimum host densities that were 30-fold higher compared to bacteria that were unable to engage in dormancy. By supplying a refuge to phage-sensitive strains, we show that seed banks retained phenotypic diversity that was otherwise lost to selection. Dormancy also stored genetic diversity. After characterizing allelic variation with pooled population sequencing, we found that seed banks retained twice as many host genes with mutations, whether phages were present or not. Based on mutational trajectories over the course of the experiment, we demonstrate that seed banks can dampen bacteria-phage coevolution. Not only does dormancy create structure and memory that buffers populations against environmental fluctuations, it also modifies species interactions in ways that can feed back onto the eco-evolutionary dynamics of microbial communities.

Seed banks alter the molecular evolutionary dynamics of Bacillus subtilis.

Fluctuations in the availability of resources constrain the growth and reproduction of individuals, which subsequently affects the evolution of their respective populations. Many organisms contend with such fluctuations by entering a reversible state of reduced metabolic activity, a phenomenon known as dormancy. This pool of dormant individuals (i.e. a seed bank) does not reproduce and is expected to act as an evolutionary buffer, though it is difficult to observe this effect directly over an extended evolutionary timescale. Through genetic manipulation, we analyze the molecular evolutionary dynamics of Bacillus subtilis populations in the presence and absence of a seed bank over 700 days. The ability of these bacteria to enter a dormant state increased the accumulation of genetic diversity over time and altered the trajectory of mutations, findings that were recapitulated using simulations based on a mathematical model of evolutionary dynamics. While the ability to form a seed bank did not alter the degree of negative selection, we found that it consistently altered the direction of molecular evolution across genes. Together, these results show that the ability to form a seed bank can affect the direction and rate of molecular evolution over an extended evolutionary timescale.

Predicting Parallelism and Quantifying Divergence in Microbial Evolution Experiments.

The degree to which independent populations subjected to identical environmental conditions evolve in similar ways is a fundamental question in evolution. To address this question, microbial populations are often experimentally passaged in a given environment and sequenced to examine the tendency for similar mutations to repeatedly arise. However, there remains the need to develop an appropriate statistical framework to identify genes that acquired more mutations in one environment than in another (i.e., divergent evolution), genes that serve as genetic candidates of adaptation. Here, we develop a mathematical model to evaluate evolutionary outcomes among replicate populations in the same environment (i.e., parallel evolution), which can then be used to identify genes that contribute to divergent evolution. Applying this approach to data sets from evolve-and-resequence experiments, we found that the distribution of mutation counts among genes can be predicted as an ensemble of independent Poisson random variables with zero free parameters. Building on this result, we propose that the degree of divergent evolution at a given gene between populations from two different environments can be modeled as the difference between two Poisson random variables, known as the Skellam distribution. We then propose and apply a statistical test to identify specific genes that contribute to divergent evolution. By focusing on predicting patterns among replicate populations in a given environment, we are able to identify an appropriate test for divergence between environments that is grounded in first principles. IMPORTANCE There is currently no universally accepted framework for identifying genes that contribute to molecular divergence between microbial populations in different environments. To address this absence, we developed a null model to describe the distribution of mutation counts among genes. We find that divergent evolution within a given gene can be modeled as the absolute difference in the total number of mutations observed between two environments. This quantity is effectively captured by a probability distribution known as the Skellam distribution, providing an appropriate statistical test for researchers seeking to identify the set of genes that contribute to divergent evolution in microbial evolution experiments.

An experimental test of disease resistance function in the skin-associated bacterial communities of three tropical amphibian species.

Variation in the structure of host-associated microbial communities has been correlated with the occurrence and severity of disease in diverse host taxa, suggesting a key role of the microbiome in pathogen defense. However, whether these correlations are typically a cause or consequence of pathogen exposure remains an open question, and requires experimental approaches to disentangle. In amphibians, infection by the fungal pathogen Batrachochytrium dendrobatidis (Bd) alters the skin microbial community in some host species, whereas in other species, the skin microbial community appears to mediate infection dynamics. In this study, we completed experimental Bd exposures in three species of tropical frogs (Agalychnis callidryas, Dendropsophus ebraccatus,andCraugastor fitzingeri) that were sympatric with Bd at the time of the study. For all three species, we identified key taxa within the skin bacterial communities that were linked to Bd infection dynamics. We also measured higher Bd infection intensities in D. ebraccatus and C. fitzingeri that were associated with higher mortality in C. fitzingeri. Our findings indicate that microbially mediated pathogen resistance is a complex trait that can vary within and across host species, and suggest that symbiont communities that have experienced prior selection for defensive microbes may be less likely to be disturbed by pathogen exposure.

Comparative Population Genetics in the Human Gut Microbiome.

Genetic variation in the human gut microbiome is responsible for conferring a number of crucial phenotypes like the ability to digest food and metabolize drugs. Yet, our understanding of how this variation arises and is maintained remains relatively poor. Thus, the microbiome remains a largely untapped resource, as the large number of coexisting species in the microbiome presents a unique opportunity to compare and contrast evolutionary processes across species to identify universal trends and deviations. Here we outline features of the human gut microbiome that, while not unique in isolation, as an assemblage make it a system with unparalleled potential for comparative population genomics studies. We consciously take a broad view of comparative population genetics, emphasizing how sampling a large number of species allows researchers to identify universal evolutionary dynamics in addition to new genes, which can then be leveraged to identify exceptional species that deviate from general patterns. To highlight the potential power of comparative population genetics in the microbiome, we reanalyze patterns of purifying selection across ∼40 prevalent species in the human gut microbiome to identify intriguing trends which highlight functional categories in the microbiome that may be under more or less constraint.

Microbial population dynamics and evolutionary outcomes under extreme energy limitation.

Microorganisms commonly inhabit energy-limited ecosystems where cellular maintenance and reproduction is highly constrained. To gain insight into how individuals persist under such conditions, we derived demographic parameters from a collection of 21 heterotrophic bacterial taxa by censusing 100 populations in an effectively closed system for 1,000 d. All but one taxon survived prolonged resource scarcity, yielding estimated times to extinction ranging over four orders of magnitude from 100 to 105 y. Our findings corroborate reports of long-lived bacteria recovered from ancient environmental samples, while providing insight into mechanisms of persistence. As death rates declined over time, lifespan was extended through the scavenging of dead cells. Although reproduction was suppressed in the absence of exogenous resources, populations continued to evolve. Hundreds of mutations were acquired, contributing to genome-wide signatures of purifying selection as well as molecular signals of adaptation. Consistent ecological and evolutionary dynamics indicate that distantly related bacteria respond to energy limitation in a similar and predictable manner, which likely contributes to the stability and robustness of microbial life.

Molecular Evolutionary Dynamics of Energy Limited Microorganisms.

Microorganisms have the unique ability to survive extended periods of time in environments with extremely low levels of exploitable energy. To determine the extent that energy limitation affects microbial evolution, we examined the molecular evolutionary dynamics of a phylogenetically diverse set of taxa over the course of 1,000 days. We found that periodic exposure to energy limitation affected the rate of molecular evolution, the accumulation of genetic diversity, and the rate of extinction. We then determined the degree that energy limitation affected the spectrum of mutations as well as the direction of evolution at the gene level. Our results suggest that the initial depletion of energy altered the direction and rate of molecular evolution within each taxon, though after the initial depletion the rate and direction did not substantially change. However, this consistent pattern became diminished when comparisons were performed across phylogenetically distant taxa, suggesting that although the dynamics of molecular evolution under energy limitation are highly generalizable across the microbial tree of life, the targets of adaptation are specific to a given taxon.

Evolutionary determinants of genome-wide nucleotide composition.

One of the long-standing mysteries of evolutionary genomics is the source of the wide phylogenetic diversity in genome nucleotide composition (G + C versus A + T), which must be a consequence of interspecific differences in mutation bias, the efficiency of selection for different nucleotides or a combination of the two. We demonstrate that although genomic G + C composition is strongly driven by mutation bias, it is also substantially modified by direct selection and/or as a by-product of biased gene conversion. Moreover, G + C composition at fourfold redundant sites is consistently elevated above the neutral expectation-more so than for any other class of sites.

Evolution with a seed bank: The population genetic consequences of microbial dormancy.

Dormancy is a bet-hedging strategy that allows organisms to persist through conditions that are suboptimal for growth and reproduction by entering a reversible state of reduced metabolic activity. Dormancy allows a population to maintain a reservoir of genetic and phenotypic diversity (i.e., a seed bank) that can contribute to the long-term survival of a population. This strategy can be potentially adaptive and has long been of interest to ecologists and evolutionary biologists. However, comparatively little is known about how dormancy influences the fundamental evolutionary forces of genetic drift, mutation, selection, recombination, and gene flow. Here, we investigate how seed banks affect the processes underpinning evolution by reviewing existing theory, implementing novel simulations, and determining how and when dormancy can influence evolution as a population genetic process. We extend our analysis to examine how seed banks can alter macroevolutionary processes, including rates of speciation and extinction. Through the lens of population genetic theory, we can understand the extent that seed banks influence the evolutionary dynamics of microorganisms as well as other taxa.

A macroecological theory of microbial biodiversity.

Microorganisms are the most abundant, diverse and functionally important organisms on Earth. Over the past decade, microbial ecologists have produced the largest ever community datasets. However, these data are rarely used to uncover law-like patterns of commonness and rarity, test theories of biodiversity, or explore unifying explanations for the structure of microbial communities. Using a global scale compilation of >20,000 samples from environmental, engineered and host-related ecosystems, we test the power of competing theories to predict distributions of microbial abundance and diversity-abundance scaling laws. We show that these patterns are best explained by the synergistic interaction of stochastic processes that are captured by lognormal dynamics. We demonstrate that lognormal dynamics have predictive power across scales of abundance, a criterion that is essential to biodiversity theory. By understanding the multiplicative and stochastic nature of ecological processes, scientists can better understand the structure and dynamics of Earth's largest and most diverse ecological systems.

Direct and Indirect Horizontal Transmission of the Antifungal Probiotic Bacterium Janthinobacterium lividum on Green Frog (Lithobates clamitans) Tadpoles.

Amphibian populations worldwide are being threatened by the disease chytridiomycosis, which is caused by Batrachochytrium dendrobatidis To mitigate the effects of B. dendrobatidis, bioaugmentation of antifungal bacteria has been shown to be a promising strategy. One way to implement bioaugmentation is through indirect horizontal transmission, defined as the transfer of bacteria from a host to the environment and to another host. In addition, direct horizontal transmission among individuals can facilitate the spread of a probiotic in a population. In this study, we tested whether the antifungal bacterium Janthinobacterium lividum could be horizontally transferred, directly or indirectly, in a laboratory experiment using Lithobates clamitans tadpoles. We evaluated the ability of J. lividumto colonize the tadpoles' skin and to persist through time using culture-dependent and culture-independent techniques. We also tested whether the addition of J. lividum affected the skin community in L. clamitans tadpoles. We found that transmission occurred rapidly by direct and indirect horizontal transmission, but indirect transmission that included a potential substrate was more effective. Even though J. lividum colonized the skin, its relative abundance on the tadpole skin decreased over time. The inoculation of J. lividum did not significantly alter the skin bacterial diversity of L. clamitans tadpoles, which was dominated by Pseudomonas Our results show that indirect horizontal transmission can be an effective bioaugmentation method. Future research is needed to determine the best conditions, including the presence of substrates, under which a probiotic can persist on the skin so that bioaugmentation becomes a successful strategy to mitigate chytridiomycosis.

Genome Sequence of the Soil Bacterium Janthinobacterium sp. KBS0711.

We present a draft genome of Janthinobacterium sp. KBS0711 that was isolated from agricultural soil. The genome provides insight into the ecological strategies of this bacterium in free-living and host-associated environments.