Ma Zhanshan Sam, Li Lianwei
Computational Biology and Medical Ecology Lab, State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China.
PeerJ. 2017 Jun 27;5:e3366. doi: 10.7717/peerj.3366. eCollection 2017.
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 of Mariadassou, Pichon & Ebert (2015) and the (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.
拉韦尔等人(2011年)首次确定的五种社区状态类型(CSTs)为分类人类阴道微生物群落(HVMC)的状态提供了一个有力的方案。这种分类是一项重大进展,因为它设计了一种有效的方法来处理个体间巨大的异质性和/或个体内的时间变异性,对其进行量化极其困难,但却至关重要,例如对于理解细菌性阴道病(BV)的病因。事实上,可以说解释BV病因最合理的生态假说很大程度上依赖于CST分类(加耶尔等人,2012年;马、福尔尼和拉韦尔,2012年;拉韦尔等人,2011年)。然而,CSTs的当前形式仍然是定性的,缺乏确定CSTs的定量标准。在本文中,我们开发了一种定量工具,通过应用玛丽亚达苏、皮雄和埃伯特(2015年)的方法以及我们在本研究中提出的特异性指数(SAI),能够可靠地区分CSTs。这个新工具准确地刻画了最初用于制定CST方案的400例横断面队列研究(拉韦尔等人,2011年)和32例纵向队列研究(加耶尔等人,2012年)中五种CSTs的分类。此外,它通过引入物种适应和分布的特异性连续体范式,对原始的CST方案进行了机理解释。我们所取得的进展不仅可能有助于CST方案的准确应用,还可能为微生物群落分型的有效工具提供线索,比如对肠道肠型进行分类。