Biology subjects

Herren, C.

Publications and source records attributed to Herren, C..

4 recordsLinked to original sources

bioRxiv2018

Expected differences in diversity and rarity between communities containing sexually versus asexually reproducing taxa

Recent studies evaluating the community structures of microorganisms and macro-organisms have found greater diversity and rarity within micro-scale communities, compared to macro-scale communities. However, reproductive method has been a confounding factor in these comparisons; the microbes considered generally reproduce asexually, while the macro-organisms considered generally reproduce sexually. Sexual reproduction imposes the constraint of mate finding, which can have significant demographic consequences by depressing birth rates at low population sizes. Here, I examine theoretically how the effects of mate finding in sexual populations translate to the emergent community properties of diversity, rarity, and dominance. Using continuous-time Markov chain models, I compare communities with and without constraints of mate limitation. In mate-limited sexual populations, the decreased growth rates at low population densities translates to a much higher extinction rate. In communities consisting of sexually reproducing taxa, the increased extinction rate due to mate limitation decreases expected diversity. Furthermore, mate limitation has a disproportionately strong effect on taxa with low population density, leading to fewer rare taxa. These shifts in community structure mirror recent empirical studies of micro versus macro communities, indicating that reproductive method may contribute to observed differences in emergent properties between communities at these two scales.

ecology↗

bioRxiv2018

Stronger connectivity of the resident gut microbiome lends resistance to invading bacteria

Bacterial infection in the gut is often due to successful invasion of the host microbiome by an introduced pathogen. Ecological theory indicates that resident community members and their interactions should be strong determinants of whether an invading taxon can persist in a community. In the context of the gut microbiome, this suggests colonization resistance against newly introduced bacteria should depend on the instantaneous bacterial community composition within the gut and interactions between these constituent members. Here we develop a mathematical model of how metabolite-dependent biotic interactions between resident bacteria mediate invasion, and find that stronger biotic connectivity from metabolite cross-feeding and competition increases colonization resistance. We then introduce a statistical method for identifying invasive taxa in the human gut, and show empirically that greater connectivity of the resident gut microbiome is related to increased resistance to invading bacteria. Finally, we examined patient outcomes after fecal microbiota transplant (FMT) for recurring Clostridium difficile infection. Patients with lower connectivity of the gut microbiome after treatment were more likely to relapse, experiencing a later infection. Thus, simulation models and data from human subjects support the hypothesis that stronger interactions between bacteria in the gut repel invaders. These results demonstrate how ecological invasion theory can be applied to the gut microbiome, which might inform targeted microbiome manipulations and interventions. More broadly, this study provides evidence that low connectivity in gut microbial communities is a hallmark of community instability and susceptibility to invasion.

microbiology↗

bioRxiv2017

Small subsets of highly connected taxa predict compositional change in microbial communities

For decades, ecological theory has predicted that the complexity of communities should be related to their stability. However, this prediction has rarely been tested empirically, because of both the difficulty of finding suitable systems where the question is tractable and the trouble of defining \"stability\" in real systems. Microbial communities provide the opportunity to investigate a related question: how does community connectivity relate to the rate of compositional turnover? We used a newly developed metric called community \"cohesion\" to test how microbial community connectivity relates to Bray-Curtis dissimilarity through time. In three long-term datasets, we found that stronger connectivity corresponded to lower rates of compositional turnover. Using two case studies of disturbed and reference communities, we found that the predictive power of community connectivity was diminished by external disturbance. Finally, we tested whether the highly connected taxa were disproportionately important in explaining compositional turnover. We found that subsets of highly connected \"keystone\" taxa, generally comprising 1-5% of community richness, explained community turnover better than using all taxa. Our results suggest that stronger biotic interactions within microbial community dynamics are stabilizing to community composition, and that highly connected taxa are good indicators of pending community shifts.

microbiology↗

bioRxiv2017

Cohesion: A method for quantifying the connectivity of microbial communities

The ability to predict microbial community dynamics lags behind the quantity of data available in these systems. Most predictive models use only environmental parameters, although a long history of ecological literature suggests that community complexity should also be an informative parameter. Thus, we hypothesize that incorporating information about a communitys complexity might improve predictive power in microbial models. Here, we present a new metric, called community \"cohesion,\" that quantifies the degree of connectivity of a microbial community. We validate our approach using long-term (10+ year) phytoplankton datasets, where absolute abundance counts are available. As a case study of our metrics utility, we show that community cohesion is a strong predictor of Bray-Curtis dissimilarity (R2 = 0.47) between phytoplankton communities in Lake Mendota, WI, USA. Our cohesion metrics outperform a model built using all available environmental data collected during a long-term sampling program. The result that cohesion corresponds strongly to Bray-Curtis dissimilarity is consistent across the five lakes analyzed here. Our cohesion metrics can be used as a predictor for many community-level properties, such as phylogenetic diversity, nutrient fluxes, or ecosystem services. We explain here the calculation of our cohesion metrics and their potential uses in microbial ecology.\n\nConflict of InterestThe authors declare no conflict of interest.

microbiology↗