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

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 het...

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Autores principales: Ma, Zhanshan (Sam), Li, Lianwei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5490466/
https://www.ncbi.nlm.nih.gov/pubmed/28674641
http://dx.doi.org/10.7717/peerj.3366
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author Ma, Zhanshan (Sam)
Li, Lianwei
author_facet Ma, Zhanshan (Sam)
Li, Lianwei
author_sort Ma, Zhanshan (Sam)
collection PubMed
description 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.
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spelling pubmed-54904662017-07-03 Quantifying the human vaginal community state types (CSTs) with the species specificity index Ma, Zhanshan (Sam) Li, Lianwei PeerJ Bioinformatics 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. PeerJ Inc. 2017-06-27 /pmc/articles/PMC5490466/ /pubmed/28674641 http://dx.doi.org/10.7717/peerj.3366 Text en ©2017 Ma and Li http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited.
spellingShingle Bioinformatics
Ma, Zhanshan (Sam)
Li, Lianwei
Quantifying the human vaginal community state types (CSTs) with the species specificity index
title Quantifying the human vaginal community state types (CSTs) with the species specificity index
title_full Quantifying the human vaginal community state types (CSTs) with the species specificity index
title_fullStr Quantifying the human vaginal community state types (CSTs) with the species specificity index
title_full_unstemmed Quantifying the human vaginal community state types (CSTs) with the species specificity index
title_short Quantifying the human vaginal community state types (CSTs) with the species specificity index
title_sort quantifying the human vaginal community state types (csts) with the species specificity index
topic Bioinformatics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5490466/
https://www.ncbi.nlm.nih.gov/pubmed/28674641
http://dx.doi.org/10.7717/peerj.3366
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