Genetic regulation

描述（由申请人提供）：实验和定量分析研究表明，人类阴道细菌群落在物种组成和各种物种的相对丰度方面经历了特殊的变化。不可否认，这些波动与特定的环境驱动因素有关，然而，对这些关联和波动成因背后的机制、生态过程和进化途径的理解仍然是一个重要的知识缺口。这项工作的长期目标是开发一种新的，数据驱动的建模框架，该框架将允许识别负责阴道微生物群复杂微生物群落动态的基本生物学过程以及导致群落变化的机制。最终，拟议的研究将有助于更好地理解细菌性阴道病（以群落转移和生态失调为特征）的原因，以及制定策略以尽量减少其发生和相关风险。为了实现这一目标，我们建议开发和测试一种新的随机建模方法，以评估环境驱动因素在预测物种丰度和组成变化中的作用，这些变化会影响整个群落的稳定性。我们将利用一组独特的9400多个样本和相关的元数据，这些样本是135名女性在10周内每天自行收集的。该研究的基本原理是，通过将随机性嵌入到群落动态模型中，可以建立一个统一的框架，该框架不仅考虑到群落面对扰动时的弹性（均衡收益率）和反应性，还考虑到自然和特殊的变化趋势。我们的中心假设是，人类阴道微生物群落的稳定性、多样性和波动机制可以使用一套特定的生态过程和进化动力学之间相互作用的随机模型来预测和评估。我们将通过将人类阴道微生物群落细菌种类组成的时间序列数据与基于生态学和进化生物学第一原理的随机模型相结合来验证这一假设，并实现以下三个具体目标：1)开发一种新的建模框架，该框架使用多元Ornstein-Uhlenbeck随机过程来预测复杂微生物群落动态的展开；2)描述人类阴道细菌群落的稳定性、结构和生态相互作用的多样性；3)探讨导致群落类型转变的生态和进化机制。拟议的研究是创新的，将导致对人类阴道中细菌群落的物种组成、结构和功能的过程有更深入的了解。此外，将填补理论和实践知识的空白，以便更好地确定与对人类相关微生物生态系统干扰的反应有关的疾病风险。

DESCRIPTION (provided by applicant): Experimental and quantitative analytical studies have shown that human vaginal bacterial communities undergo idiosyncratic changes in species composition and wide fluctuations in the relative abundances of various species. These fluctuations are undeniably associated with specific environmental drivers, however, an understanding of the mechanisms, ecological processes and evolutionary routes behind the genesis of such associations and fluctuations remain an important knowledge gap. The long-term goal of this work is to develop a novel, data driven modeling framework that will allow the identification of fundamental biological processes responsible for the complex microbial community dynamics of the vaginal microbiota and the mechanisms that lead to community shifts. Ultimately, the proposed research would have application in better understanding the causes of conditions such as bacterial vaginosis (characterized by a community shift and dysbiosis), as well as devising strategies to minimize its occurrence and associated risks. To achieve this goal we propose to develop and test a novel stochastic modeling approach to assess the role of environmental drivers in predicting changes in species abundances and composition that shape community-wide stability properties. We will leverage a unique set of over 9,400 samples and associated metadata that were self- collected daily by 135 women for 10 weeks. The rationale for the proposed research is that by embedding stochasticity in community dynamics models a unified framework can be developed that takes into account not only the resilience (return rates to equilibrium) and the reactivity of communities in the face of perturbations, but also the natural and idiosyncratic tendencies to change. Our central hypothesis is that stability properties, diversity and fluctuation regimes of human vaginal microbial communities can be predicted and assessed using a suite of specific stochastic models of the interplay between ecological processes and evolutionary dynamics. We will test this hypothesis by combining time series data of bacterial species composition of human vaginal microbial communities with stochastic models derived from first principles of ecology and evolutionary biology and achieving the following three specific aims: 1) Develop a novel modeling framework that uses a multivariate Ornstein-Uhlenbeck stochastic process to predict the unfolding of complex microbial community dynamics; 2) Characterize the stability properties, architecture, and diversity of ecological interactions within human vaginal bacterial communities; and 3) Probe the ecological and evolutionary mechanisms that lead to community type shifts. The proposed research is innovative and will lead to a deeper understanding of the processes governing species composition, structure and function of bacterial communities in the human vagina. In addition, a theoretical and practical knowledge gap will be filled so that the risk to diseases associated with responses to disturbances of human-associated microbial ecosystems can be better defined.