Biology subjects

Shoemaker, W. R.

Publications and source records attributed to Shoemaker, W. R..

16 recordsLinked to original sources

bioRxiv2026

Leveraging DNA and RNA oscillatory dynamics to investigate the ecology and physiology of a freshwater microbial community

The dynamics of microbial communities in temporally varying environments are often mediated by the physiological responses of their members. However, physiological measurements remain difficult to obtain \textit{in situ} from diverse communities in nature, limiting our understanding of microbial community dynamics in changing environments. Here, we investigate the physiological dynamics of a microbial community by applying a macroecological approach to a multi-year timeseries of paired ribosomal RNA (rRNA) and DNA (rDNA) measurements from a freshwater community, interpreting their relationship by developing a model of microbial physiology. Leveraging the existence of seasonal oscillations, we developed a data-driven minimal model that provided macroecological predictions and interpretations of rDNA, rRNA, and their relationship. Using this model, we examined two macroecological patterns with physiological interpretations: 1) time averaged rRNA:rDNA as a measure of a community member's steady-state and 2) the temporal ordering of rRNA fluctuations relative to rDNA. We found that rRNA:rDNA increased with the number of 16S rRNA operon copies, which in the context of our model suggests a superlinear effect of copy number. Temporal fluctuations of rRNA tended to \textit{precede} those of rDNA, consistent with the view that increases in ribosomal content can lead to future biomass. We then identified environmental variables where rRNA and rRNA:rDNA displayed greater sensitivity than rDNA, reasoning that rRNA:rDNA, as a reflection of the growth rate, may respond more strongly to environmental change. The ratio rRNA:rDNA provided greater sensitivity than rDNA for the majority of the aquatic environmental variables tested, particularly those reflecting the degree of eutrophy vs. oligotrophy. The results of this work indicate that the ratio rRNA:rDNA may be underutilized as a measure of the physiological state of natural communities.

microbiology↗

bioRxiv2025

A balance between environmental filtering and competitive exclusion modulates the macroecology of alternative stable states in microbial communities

Predicting the assembly and stability of microbial ecosystems is fundamentally challenged by the stochas-ticity inherent in historical contingencies. Although these dynamics often appear reproducible at coarse taxonomic or functional scales, the mechanisms governing fine-grained species-level variation and the emergence of alternative stable states remain an unresolved problem in ecology. Bridging the gap between individual species variability and the emergence of predictable community-level attractors is essential for a mechanistic understanding of ecosystem resilience. Here, by analyzing replicate microbial communities assembled in vitro, we demonstrate that community structure is built upon individual species exhibiting robustly bimodal abundance distributions. Each taxon exists in either a high- or low-abundance state. We show that the collective configuration of these binary species states--a phenomenon also observed in natural systems--drives the correlation structure between community members and defines a set of discrete, alternative community-level attractors. By examining the prevalence of species across these attractors, we uncover a striking taxonomic signal: phylogenetically close relatives are significantly more likely to display reciprocal prevalence patterns--where the dominance of one relative necessitates the suppression of the other--than expected by chance. This discovery directly rejects models based on simple functional redundancy. Instead, it proves that state-dependent competitive exclusion is a primary driver of community divergence, where the identity of the "winner" is contingent on the collective state of the entire community. Our work reframes microbial community structure through the lens of discrete population states, providing a predictive framework for understanding ecosystem stability and the engineering of community functions.

ecology↗

bioRxiv2025

Evolutionary bioenergetics of sporulation

Energy is required for the expression and maintenance of complex traits. In many habitats, however, free energy available to support biosynthesis is in vanishingly short supply. As a result, many taxa have evolved persistence strategies that support survival in unfavorable environments. Among these is sporulation, an ancient bacterial program governed by a large genetic network that requires energy for both regulation and execution. Yet sporulation is a last resort, initiated when cellular energy is nearly exhausted. To resolve this paradox, we quantified the energetic cost of sporulation in units of ATP by integrating time-resolved genome, transcriptome, and proteome profiles. The full cost of the spore cycle, including both formation and revival, ranks among the most energy-intensive processes in the bacterial cell, requiring almost 1010 ATP and consuming about 10% of the total energy budget. The majority of this cost arises from translation, membrane synthesis, and protein turnover. Despite its considerable upfront investment, sporulation enables long-term survival and becomes optimal when harsh conditions extend over timescales of months or longer. This trade-off between immediate cost and delayed benefit helps explain when sporulation is maintained or replaced by alternative strategies. By incorporating our estimates into mechanistic models, we show how metabolic constraints shape sporulation efficiency, while genome-wide mutation accumulation data reveal that even modest energetic burdens can become visible to selection, influencing the evolutionary fate of this complex and widespread trait.

evolutionary biology↗

bioRxiv2025

Longitudinal dynamics of ethanol-resistant microbes and sporulation in the human gut

BackgroundA considerable proportion of human gut bacteria use some form of dormancy to survive unfavorable conditions such as oxygen exposure, antibiotic treatment, and inflammation. Dormancy strategies enable persistence, allow recolonization following disruptions, and facilitate transmission between individuals. In this study, we explored the composition, characteristics, and longitudinal dynamics of the dormant community in the gut as determined by ethanol resistance. We conducted a six-month longitudinal study on nine healthy male adults, who were sampled every two weeks. Gut microbiota composition was determined with 16S rRNA amplicon sequencing in untreated (bulk microbiota) and ethanol treated samples. A rigorous algorithm was implemented to determine the ethanol-resistant and non-resistant community within the gut microbiota. ResultsWe detected ethanol-resistant gut bacteria in eight distinct phyla, with the highest number of OTUs observed in the phylum Bacillota, and substantial representation in Actinomycetota and Pseudomonadota. In general, ethanol-resistant taxa exhibited higher relative abundance and longer within-individual persistence compared to non-resistant taxa. Ethanol resistance indicated a higher rate of sharing between individuals, independent of phylum. Ethanol-resistant Bacillota also exhibited longer persistence within the gut over the six-months period in comparison to ethanol non-resistant Bacillota and other ethanol-resistant or ethanol non-resistant phyla. Finally, the analysis of sporulation frequency of highly prevalent ethanol-resistant Bacillota members revealed that sporulation occurred in each individual synchronously among different community members but varied significantly between individuals. Major shifts in sporulation frequency were associated with well-known disturbances such as antibiotic therapy and travel. ConclusionOur findings highlight that sporulation of Bacillota members and alternative dormancy strategies employed by non-Bacillota members contribute to bacterial persistence in the human gut and facilitate transmission between unrelated individuals. Moreover, we show that sporulation frequency (specific to Bacillota) is a dynamic, community-level process shaped by host- and time-specific environmental factors rather than intrinsic, species-specific traits.

ecology↗

bioRxiv2025

The macroecological dynamics of sojourn trajectories in the human gut microbiome

The human gut microbiome is a dynamic ecosystem. Host behaviors (e.g., diet) provide a regular source of environmental variation that induces fluctuations in the abundances of resident microbiota. Despite these displacements, microbial community members remain highly resilient. Population abundances tend to fluctuate around characteristic steady-state abundances over long timescales in healthy human hosts. These temporary excursions from steady-state abundances, known as sojourn trajectories, have the potential to inform our understanding of the fundamental dynamics of the microbiome. However, to our knowledge, the macroecology of sojourn trajectories has yet to be systematically characterized. In this study, we leverage theoretical tools from the study of random walks to characterize the duration of sojourn trajectories, their shape, and the degree that diverse community members exhibit similar qualitative and quantitative dynamics. We apply the Stochastic Logistic Model as a theoretical lens for interpreting our empirical observations. We find that the typical timescale of a sojourn trajectory does not depend on the mean abundance of a community member (i.e., carrying capacity), although it is strongly related to its coefficient of variation (i.e., environmental noise). This work provides fundamental insight into the dynamics, timescales, and fluctuations exhibited by diverse microbial communities. ImportanceMicroorganisms in the human gut often fluctuate around a characteristic abundance in healthy hosts over extended periods of time. These typical abundances can be viewed as steady-states, meaning that fluctuating abundances do not continue towards extinction or dominance, but rather return to a specific value over a typical timescale. Here we empirically characterize the 1) length (i.e., number of days), 2) relationship between length and area, and 3) typical deviation of a sojourn trajectory. These three patterns can be explained and unified through an established minimal model of ecological dynamics, the Stochastic Logistic Model of growth.

ecology↗

bioRxiv2023

Macroecological laws in experimental microbial systems

Ecology has historically benefited from the characterization of statistical patterns of biodiversity within and across communities, an approach known as macroecology. Within microbial ecology, macroecological approaches have identified universal patterns of diversity and abundance that can be captured by effective models. Experimentation has simultaneously played a crucial role, as the advent of high-replication community time-series has allowed researchers to investigate underlying ecological forces. However, there remains a gap between experiments performed in the laboratory and macroecological patterns documented in natural systems, as we do not know whether these patterns can be recapitulated in the lab and whether experimental manipulations produce macroecological effects. This work aims at bridging the gap between experimental ecology and macroecology. Using high-replication time-series, we demonstrate that microbial macroecological patterns observed in nature exist in a laboratory setting, despite controlled conditions, and can be unified under the Stochastic Logistic Model of growth (SLM). We find that demographic manipulations (e.g., migration) impact observed macroecological patterns. By modifying the SLM to incorporate said manipulations alongside experimental details (e.g., sampling), we obtain predictions that are consistent with macroecological outcomes. By combining high-replication experiments with ecological models, microbial macroecology can be viewed as a predictive discipline.

ecology↗

bioRxiv2023

Macroecological patterns in coarse-grained microbial communities

The structure and diversity of microbial communities is 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 predicted by the Diversity Begets Diversity (DBD) hypothesis. We found that the relationship between richness estimates at different scales can be quantitatively predicted assuming independence among community members.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.

ecology↗

bioRxiv2023

Coevolution with a seed bank

Dormancy is as an adaptation to living in fluctuating environments. It can also influence species interactions, for example, by providing organisms with a refuge from predators and parasites. Here we test the hypothesis that dormancy generates a seed bank of protected individuals that can modify antagonistic coevolutionary dynamics. We experimentally evolved a spore-forming bacterial host along with a phage parasite that can infect active but not dormant cells. Seed banks buffered population dynamics against phage infection and retained phenotypic diversity that was otherwise lost to directional selection. By storing genetic diversity, seed banks also altered the distribution of host alleles, which contributed to dampened coevolutionary dynamics. Our findings demonstrate that dormancy generates a seed bank that can modify the eco-evolutionary outcomes of host-parasite systems.

evolutionary biology↗

bioRxiv2022

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.

ecology↗

bioRxiv2021

Seed Banks Alter the Rate and Direction of Molecular Evolution in Bacillus subtilis

Fluctuations in the availability of resources constrains the growth and reproduction of individuals, which subsequently effects 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.

evolutionary biology↗

bioRxiv2021

Ecological Stability Emerges at the Level of Strains in the Human Gut Microbiome

The human gut microbiome harbors substantial ecological diversity at the species level, as well as at the strain level within species. In healthy hosts, species abundance fluctuations in the microbiome are thought to be stable, and these fluctuations can be described by macroecological laws. However, it is less clear how strain abundances change over time. An open question is whether individual strains behave like species themselves, exhibiting stability and following the macroecological relationships known to hold at the species level, or whether strains have different dynamics, perhaps due to the relatively close phylogenetic relatedness of co-colonizing lineages. Here, we analyze the daily dynamics of intra-specific genetic variation in the gut microbiomes of four healthy, densely longitudinally sampled hosts. First, we find that overall genetic diversity in a large majority of species is stationary over time, despite short-term fluctuations. Next, we show that fluctuations in abundances in approximately 80% of strains analyzed can be predicted with a stochastic logistic model (SLM)--an ecological model of a population experiencing environmental fluctuations around a fixed carrying capacity which has previously been shown to capture statistical properties of species abundance fluctuations. The success of this model indicates that strain abundances typically fluctuate around a fixed carrying capacity, suggesting that most strains are dynamically stable. Finally, we find that the strain abundances follow several empirical macroecological laws known to hold at the species level. Together, our results suggest that macroecological properties of the human gut microbiome, including its stability, emerge at the level of strains.

ecology↗

bioRxiv2021

Comparative Population Genetics in the Human Gut Microbiome

The 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 co-existing species in this 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 re-analyzed 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.

evolutionary biology↗

bioRxiv2021

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 while 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 biology↗

bioRxiv2021

Microbial population dynamics and evolutionary outcomes under extreme energy-limitation

As the most abundant and diverse form of life on Earth, microorganisms commonly inhabit energy-limited environments where cellular maintenance and growth is highly constrained. To gain insight into how microorganisms persist under such conditions, we derived demographic parameters from a diverse collection of bacteria by censusing 100 populations in a closed system for 1,000 days. All but one taxon survived prolonged resource scarcity, yielding estimated times-to-extinction ranging over four orders of magnitude from 100 - 105 years. These findings corroborate reports of long-lived bacteria that have been recovered from ancient environmental samples, while providing insight into mechanisms of persistence. Critically, we found that as death rates declined over time, lifespan was extended through the scavenging of dead cells. Although growth and reproduction were dramatically suppressed in the absence of an exogenous resource supply, bacterial populations continued to evolve. Hundreds of mutations were acquired, contributing to genome-wide signatures of negative selection as well as molecular signals of adaptation. Remarkable consistency in the 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.

microbiology↗

bioRxiv2020

Quantifying Parallel Evolution

The degree that the environment determines what genes contribute towards adaptation is a fundamental question in microbial evolution. Microbial populations are often experimentally passaged in different environments and sequenced in order to identify candidates for adaptation in a particular environment. However, there remains the need to develop an appropriate statistical framework to identify genes that acquired more mutations in one environment over the other (i.e., divergent evolution). Here we demonstrate how the evolutionary outcomes among replicate populations in the same environment, known as parallel evolution, can be leveraged to construct an intuitive statistical test for identifying the genes that contribute towards divergent evolution. To accomplish this task, we examined publicly available evolve-and-resequence experiment datasets and found that the distribution of mutation counts among genes can be predicted using an ensemble of independent Poisson random variables. 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 towards divergent evolution. IMPORTANCE: There is currently no existing framework that can be leveraged to identify genes that contribute towards divergent evolution in microbial evolution experiments. To correct for this absence, we investigated the distribution of mutation counts among genes in order to identify an appropriate null model. Our observations suggest that divergent evolution within a given gene can be modeled as the difference in the total number of mutations observed between two environments. This quantity is described 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 towards divergent evolution in evolution experiments.

evolutionary biology↗

bioRxiv2017

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 sub-optimal 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 microbial evolutionary dynamics.

microbiology↗