Project description:Using 2,733 longitudinal vaginal microbiome samples (representing local microbial communities) from 79 individuals (representing meta-communities) in the states of healthy, BV (bacterial vaginosis) and pregnancy, we assess and interpret the relative importance of stochastic forces (e.g., stochastic drifts in bacteria demography, and stochastic dispersal) vs. deterministic selection (e.g., host genome, and host physiology) in shaping the dynamics of human vaginal microbiome (HVM) diversity by an integrated analysis with multi-site neutral (MSN) and niche-neutral hybrid (NNH) modeling. It was found that, when the traditional "default" P-value = 0.05 was specified, the neutral drifts were predominant (≥50% metacommunities indistinguishable from the MSN prediction), while the niche differentiations were moderate (<20% from the NNH prediction). The study also analyzed two challenging uncertainties in testing the neutral and/or niche-neutral hybrid models, i.e., lack of full model specificity - non-unique fittings of same datasets to multiple models with potentially different mechanistic assumptions - and lack of definite rules for setting the P-value thresholds (also noted as P t -value when referring to the threshold of P-value in this article) in testing null hypothesis (model). Indeed, the two uncertainties can be interdependent, which further complicates the statistical inferences. To deal with the uncertainties, the MSN/NNH test results under a series of P-values ranged from 0.05 to 0.95 were presented. Furthermore, the influence of P-value threshold-setting on the model specificity, and the effects of woman's health status on the neutrality level of HVM were examined. It was found that with the increase of P-value threshold from 0.05 to 0.95, the overlap (non-unique) fitting of MSN and NNH decreased from 29.1 to 1.3%, whereas the specificity (uniquely fitted to data) of MSN model was kept between 55.7 and 82.3%. Also with the rising P-value threshold, the difference between healthy and BV groups become significant. These findings suggested that traditional single P-value threshold (such as the de facto standard P-value = 0.05) might be insufficient for testing the neutral and/or niche neutral hybrid models.

Project description:Inference involving diversity gradients typically is gathered by mechanistic tests involving single dimensions of biodiversity such as species richness. Nonetheless, because traits such as geographic range size, trophic status or phenotypic characteristics are tied to a particular species, mechanistic effects driving broad diversity patterns should manifest across numerous dimensions of biodiversity. We develop an approach of stronger inference based on numerous dimensions of biodiversity and apply it to evaluate one such putative mechanism: the mid-domain effect (MDE). Species composition of 10,000-km(2) grid cells was determined by overlaying geographic range maps of 133 noctilionoid bat taxa. We determined empirical diversity gradients in the Neotropics by calculating species richness and three indices each of phylogenetic, functional and phenetic diversity for each grid cell. We also created 1,000 simulated gradients of each examined metric of biodiversity based on a MDE model to estimate patterns expected if species distributions were randomly placed within the Neotropics. For each simulation run, we regressed the observed gradient onto the MDE-expected gradient. If a MDE drives empirical gradients, then coefficients of determination from such an analysis should be high, the intercept no different from zero and the slope no different than unity. Species richness gradients predicted by the MDE fit empirical patterns. The MDE produced strong spatially structured gradients of taxonomic, phylogenetic, functional and phenetic diversity. Nonetheless, expected values generated from the MDE for most dimensions of biodiversity exhibited poor fit to most empirical patterns. The MDE cannot account for most empirical patterns of biodiversity. Fuller understanding of latitudinal gradients will come from simultaneous examination of relative effects of random, environmental and historical mechanisms to better understand distribution and abundance of the current biota.

Project description:The aerodigestive tract (ADT) is the primary portal through which pathogens and other invading microbes enter the body. As the direct interface with the environment, we hypothesize that the ADT microbiota possess biosynthetic gene clusters (BGCs) for antibiotics and other specialized metabolites to compete with both endogenous and exogenous microbes. From 1,214 bacterial genomes, representing 136 genera and 387 species that colonize the ADT, we identified 3,895 BGCs. To determine the distribution of BGCs and bacteria in different ADT sites, we aligned 1,424 metagenomes, from nine different ADT sites, onto the predicted BGCs. We show that alpha diversity varies across the ADT and that each site is associated with distinct bacterial communities and BGCs. We identify specific BGC families enriched in the buccal mucosa, external naris, gingiva, and tongue dorsum despite these sites harboring closely related bacteria. We reveal BGC enrichment patterns indicative of the ecology at each site. For instance, aryl polyene and resorcinol BGCs are enriched in the gingiva and tongue, which are colonized by many anaerobes. In addition, we find that streptococci colonizing the tongue and cheek possess different ribosomally synthesized and posttranslationally modified peptide BGCs. Finally, we highlight bacterial genera with BGCs but are underexplored for specialized metabolism and demonstrate the bioactivity of Actinomyces against other bacteria, including human pathogens. Together, our results demonstrate that specialized metabolism in the ADT is extensive and that by exploring these microbiomes further, we will better understand the ecology and biogeography of this system and identify new bioactive natural products. IMPORTANCE Bacteria produce specialized metabolites to compete with other microbes. Though the biological activities of many specialized metabolites have been determined, our understanding of their ecology is limited, particularly within the human microbiome. As the aerodigestive tract (ADT) faces the external environment, bacteria colonizing this tract must compete both among themselves and with invading microbes, including human pathogens. We analyzed the genomes of ADT bacteria to identify biosynthetic gene clusters (BGCs) for specialized metabolites. We found that the majority of ADT BGCs are uncharacterized and the metabolites they encode are unknown. We mapped the distribution of BGCs across the ADT and determined that each site is associated with its own distinct bacterial community and BGCs. By further characterizing these BGCs, we will inform our understanding of ecology and biogeography across the ADT, and we may uncover new specialized metabolites, including antibiotics.

Dataset Information

Niche-neutral theoretic approach to mechanisms underlying the biodiversity and biogeography of human microbiomes.

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Niche-neutral theoretic approach to mechanisms underlying the biodiversity and biogeography of human microbiomes.

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