Wang Qian, Dong Ang, Zhao Jinshuai, Wang Chen, Griffin Christipher, Gragnoli Claudia, Xue Fengxia, Wu Rongling
Department of Obstetrics and Gynecology, Tianjin Medical University General Hospital, Tianjin, China.
Tianjin Key Laboratory of Female Reproductive Health and Eugenics, Tianjin, China.
Front Microbiol. 2022 Oct 20;13:998813. doi: 10.3389/fmicb.2022.998813. eCollection 2022.
Aerobic vaginitis (AV) is a complex vaginal dysbiosis that is thought to be caused by the micro-ecological change of the vaginal microbiota. While most studies have focused on how changes in the abundance of individual microbes are associated with the emergence of AV, we still do not have a complete mechanistic atlas of the microbe-AV link. Network modeling is central to understanding the structure and function of any microbial community assembly. By encapsulating the abundance of microbes as nodes and ecological interactions among microbes as edges, microbial networks can reveal how each microbe functions and how one microbe cooperate or compete with other microbes to mediate the dynamics of microbial communities. However, existing approaches can only estimate either the strength of microbe-microbe link or the direction of this link, failing to capture full topological characteristics of a network, especially from high-dimensional microbial data. We combine allometry scaling law and evolutionary game theory to derive a functional graph theory that can characterize bidirectional, signed, and weighted interaction networks from any data domain. We apply our theory to characterize the causal interdependence between microbial interactions and AV. From functional networks arising from different functional modules, we find that, as the only favorable genus from Firmicutes among all identified genera, the role of in maintaining vaginal microbial symbiosis is enabled by upregulation from other microbes, rather than through any intrinsic capacity. Among species, the proportion of to is positively associated with more healthy acid vaginal ecosystems. In a less healthy alkaline ecosystem, establishes a contradictory relationship with other microbes, leading to population decrease relative to . We identify topological changes of vaginal microbiota networks when the menstrual cycle of women changes from the follicular to luteal phases. Our network tool provides a mechanistic approach to disentangle the internal workings of the microbiota assembly and predict its causal relationships with human diseases including AV.
需氧性阴道炎（AV）是一种复杂的阴道生态失调，被认为是由阴道微生物群的微生态变化引起的。虽然大多数研究都集中在个体微生物丰度的变化如何与AV的出现相关联，但我们仍然没有一个完整的微生物与AV关联的机制图谱。网络建模对于理解任何微生物群落组装的结构和功能至关重要。通过将微生物的丰度封装为节点，将微生物之间的生态相互作用封装为边，微生物网络可以揭示每个微生物的功能以及一个微生物如何与其他微生物合作或竞争以介导微生物群落的动态变化。然而，现有的方法只能估计微生物-微生物联系的强度或这种联系的方向，无法捕捉网络的完整拓扑特征，尤其是从高维微生物数据中。我们结合异速生长比例定律和进化博弈论，推导出一种功能图论，该理论可以从任何数据域中表征双向、有符号和加权的相互作用网络。我们应用我们的理论来表征微生物相互作用与AV之间的因果相互依存关系。从不同功能模块产生的功能网络中，我们发现，作为所有已鉴定属中厚壁菌门唯一有利的属，其在维持阴道微生物共生中的作用是由其他微生物的上调实现的，而不是通过任何内在能力。在物种中，与的比例与更健康的酸性阴道生态系统呈正相关。在不太健康的碱性生态系统中，与其他微生物建立了矛盾关系，导致相对于的种群数量减少。我们确定了女性月经周期从卵泡期到黄体期时阴道微生物群网络的拓扑变化。我们的网络工具提供了一种机制方法来解开微生物群落组装的内部运作，并预测其与包括AV在内的人类疾病的因果关系。
