Genetic regulation

描述（由申请方提供）：实验和定量分析研究表明，人类阴道细菌群落在物种组成方面发生了特异质变化，各种物种的相对丰度也发生了大幅波动。这些波动必然与特定的环境驱动因素有关，然而，对这种关联和波动起源背后的机制、生态过程和进化路线的理解仍然是一个重要的知识空白。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过程以及导致群落变化的机制。最终，拟议的研究将用于更好地了解细菌性阴道病（以社区转变和生态失调为特征）等疾病的原因，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，这些变化塑造了整个社区的稳定性。我们将利用一套独特的超过9,400个样本和相关的元数据，这些样本和元数据是135名妇女在10周内每天自我收集的。拟议的研究的理由是，通过嵌入随机性的社区动态模型，可以开发一个统一的框架，不仅考虑到弹性（返回率平衡）和社区的反应，在面对扰动，但也自然和特质的变化趋势。我们的中心假设是，人类阴道微生物群落的稳定性，多样性和波动制度可以使用一套特定的随机模型的生态过程和进化动力学之间的相互作用进行预测和评估。我们将通过结合人类阴道微生物群落的细菌种类组成的时间序列数据与来自生态学和进化生物学第一原理的随机模型来验证这一假设，并实现以下三个具体目标：1）开发一种新的建模框架，该框架使用多变量Ornstein-Uhlenbeck随机过程来预测复杂微生物群落动态的展开; 2）表征人类阴道细菌群落内生态相互作用的稳定性，结构和多样性; 3）探索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，将导致更深入地了解人类阴道中细菌群落的物种组成，结构和功能的过程。此外，还将填补理论和实践知识空白，以便更好地确定与人类相关微生物生态系统干扰反应相关的疾病风险。

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.