Dataset Information

Quantifying the human vaginal community state types (CSTs) with the species specificity index.

ABSTRACT: The five community state types (CSTs) first identified by Ravel et al. (2011) offered a powerful scheme to classify the states of human vaginal microbial communities (HVMC). The classification is a significant advance because it devised an effective handle to deal with the enormous inter-subject heterogeneity and/or intra-subject temporal variability, the quantification of which is extremely difficult but of critical importance such as the understanding of BV (bacterial vaginosis) etiology. Indeed, arguably the most plausible ecological hypothesis for interpreting the BV etiology heavily depends on the CST classification (Gajer et al., 2012; Ma, Forney & Ravel, 2012; Ravel et al., 2011). Nevertheless, the current form of CSTs is still qualitative and lacks a quantitative criterion to determine the CSTs. In this article, we develop a quantitative tool that can reliably distinguish the CSTs by applying the species specificity of Mariadassou, Pichon & Ebert (2015) and the specificity aggregation index (SAI) we propose in this study. The new tool accurately characterized the classifications of the five CSTs with both 400-crosssectional cohort (Ravel et al., 2011) and 32-longitudinal cohort (Gajer et al., 2012) studies originally utilized to develop the CST scheme. Furthermore, it offers a mechanistic interpretation of the original CST scheme by invoking the paradigm of specificity continuum for species adaptation and distribution. The advances we made may not only facilitate the accurate applications of the CST scheme, but also offer hints towards an effective tool for microbiome typing such as classifying gut enterotypes.

SUBMITTER: Ma ZS

PROVIDER: S-EPMC5490466 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

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Quantifying the human vaginal community state types (CSTs) with the species specificity index.

Ma Zhanshan Sam ZS Li Lianwei L

PeerJ 20170627

The five community state types (CSTs) first identified by Ravel et al. (2011) offered a powerful scheme to classify the states of human vaginal microbial communities (HVMC). The classification is a significant advance because it devised an effective handle to deal with the enormous inter-subject heterogeneity and/or intra-subject temporal variability, the quantification of which is extremely difficult but of critical importance such as the understanding of BV (bacterial vaginosis) etiology. Inde ...[more]

PMID: 28674641

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Project description:Abnormal vaginal microbiota (AVM), including bacterial vaginosis (BV), is caused by a microbiota imbalance. Nugent scoring is the gold standard for the laboratory diagnosis of BV; however, it is somewhat subjective to interpret, and challenging to distinguish bacteria. Hence, there is a need for improved technologies for the accurate diagnosis of AVM. To this end, next-generation sequencing (NGS) technology has been shown to yield comprehensive information on the pathophysiology of AVM. Hence, to evaluate the relationship between microbiota composition and the pathophysiology of AVM and its clinical significance, we characterized vaginal swab samples from 212 pregnant Korean women using both Nugent scoring and NGS analysis. Of these, the Nugent scoring identified 175 subjects (82.5%; 175/212) with normal flora (NF), 20 (9.4%; 20/212) with intermediate flora (IF), and 17 (8.0%; 17/212) with BV. NGS analysis followed by the characterization of vaginal microbiota composition, as represented by alpha and beta diversity, revealed the relative abundance of specific bacterial taxa at the genus and species level. Moreover, we identified all five predominant community state types (CSTs) along with three smaller CSTs. Analysis of the vaginal microbiota revealed the dominance of one or two Lactobacillus spp. in the NF group. Meanwhile, the IF and BV groups were dominated by the genera Gardnerella, Prevotella, and Atopobium. These two groups also showed higher alpha diversity than the NF group (p < 0.05). Principal coordinate analysis (PCoA) indicated that the NF group was significantly different from the AVM groups (p < 0.05), whereas no significant difference was observed between IF and BV groups (p = 0.25). Lastly, to investigate the characteristics of vaginal microbiota based on taxonomic composition, the IF and BV groups (AVM groups) were reclassified using the unweighted pair group method with arithmetic mean (UPGMA) clustering. Consequently, they were reclassified into BV1 (Lactobacillus iners-dominated), BV2-1 (Bifidobacterium breve-dominated), BV2-2 (Gardnerella vaginalis s1 or s2 and Atopobium vaginae-dominated), and BV3 [mixed population of G. vaginalis, L. iners, and other bacteria (p < 0.05)]. Collectively, these findings could serve to advance the current understanding regarding AVM pathophysiology.

Project description:Bacterial communities colonizing the reproductive tracts of primates (including humans) impact the health, survival and fitness of the host, and thereby the evolution of the host species. Despite their importance, we currently have a poor understanding of primate microbiomes. The composition and structure of microbial communities vary considerably depending on the host and environmental factors. We conducted comparative analyses of the primate vaginal microbiome using pyrosequencing of the 16S rRNA genes of a phylogenetically broad range of primates to test for factors affecting the diversity of primate vaginal ecosystems. The nine primate species included: humans (Homo sapiens), yellow baboons (Papio cynocephalus), olive baboons (Papio anubis), lemurs (Propithecus diadema), howler monkeys (Alouatta pigra), red colobus (Piliocolobus rufomitratus), vervets (Chlorocebus aethiops), mangabeys (Cercocebus atys) and chimpanzees (Pan troglodytes). Our results indicated that all primates exhibited host-specific vaginal microbiota and that humans were distinct from other primates in both microbiome composition and diversity. In contrast to the gut microbiome, the vaginal microbiome showed limited congruence with host phylogeny, and neither captivity nor diet elicited substantial effects on the vaginal microbiomes of primates. Permutational multivariate analysis of variance and Wilcoxon tests revealed correlations among vaginal microbiota and host species-specific socioecological factors, particularly related to sexuality, including: female promiscuity, baculum length, gestation time, mating group size and neonatal birth weight. The proportion of unclassified taxa observed in nonhuman primate samples increased with phylogenetic distance from humans, indicative of the existence of previously unrecognized microbial taxa. These findings contribute to our understanding of host-microbe variation and coevolution, microbial biogeography, and disease risk, and have important implications for the use of animal models in studies of human sexual and reproductive diseases.

Dataset Information

Quantifying the human vaginal community state types (CSTs) with the species specificity index.

Publications

Quantifying the human vaginal community state types (CSTs) with the species specificity index.

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