Genetic regulation

描述(申请人提供)：实验和定量分析研究表明，人类阴道细菌群落经历了物种组成的特殊变化和各种物种相对丰度的广泛波动。不可否认，这些波动与特定的环境驱动因素有关，然而，对这种关联和波动发生背后的机制、生态过程和进化路线的理解仍然是一个重要的知识差距。这项工作的长期目标是开发一个新颖的、数据驱动的建模框架，该框架将能够识别导致阴道微生物区系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，拟议的研究将应用于更好地了解细菌性阴道病(以群落转移和生物失调为特征)等疾病的原因，以及制定将其发生和相关风险降至最低的策略。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方面的作用，这些变化塑造了整个社区的稳定特性。我们将利用一套独特的超过9400个样本和相关的元数据，这些样本和相关的元数据是135名妇女在10周内每天自我收集的。拟议研究的基本原理是，通过在社区动力学模型中嵌入随机性，可以开发出一个统一的框架，该框架不仅考虑到社区在面对扰动时的弹性(向平衡的回报率)和反应能力，而且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来自生态学和进化生物学第一原理的随机模型相结合来检验这一假设，并实现以下三个具体目标：1)开发一个新的建模框架，使用多变量Ornstein-Uhlenbeck随机过程来预测复杂的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；以及3)探索导致群落类型转变的生态和进化机制。这项拟议的研究具有创新性，将使人们更深入地了解控制人类阴道细菌群落的物种组成、结构和功能的过程。此外，将填补理论和实践知识的空白，以便更好地确定与人类相关微生物生态系统的干扰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.