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Evaluating the Assembly Dynamics in the Human Vaginal Microbiomes With Niche-Neutral Hybrid Modeling

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...

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Detalles Bibliográficos
Autor principal: Ma, Zhanshan (Sam)
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8417885/
https://www.ncbi.nlm.nih.gov/pubmed/34489890
http://dx.doi.org/10.3389/fmicb.2021.699939
Descripción
Sumario: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.