Adaptive dynamics of microbial populations: Physiological models of growth

微生物种群的适应性动态：生长的生理模型

• 批准号: 0517954
• 负责人: Sergei Pilyugin
• 金额: --
• 依托单位: University of Florida
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-08-01 至 2009-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0517954&HistoricalAwards=false
• 关键词: Adaptive; dynamics; microbial; populations; Physiological

The growth of multiple microorganisms in environments containing a mixture of growth-limiting substrates is a problem of fundamental ecological importance. Although the literature is abundant with mathematical theories of competition in mixed environments, many mathematical models fall short of directly addressing the dynamics of physiological adaptations exhibited by microbial species in response to environmental fluctuations. In our previous work, we have laid foundations for developing a comprehensive mathematical theory that fulfills this modeling niche. We have shown that predictions of these models are in close agreement with experimental data. In this project, we will provide a solid mathematical background behind the physiological theory of microbial adaptation and further extend the modeling framework to include the key physiological variables and intracellular processes that we did not consider previously. This work will provide the molecular basis for understanding extinction, coexistence, and physiological heterogeneity in complex microbial communities. This project will also address the impact of environmental perturbations on adaptive microbial ecosystems.Many of the modern biotechnologies including food processing and waste water treatment are based on the controlled growth of microbial cultures, an adaptive process that is sensitive to environmental perturbations. This project will contribute towards our understanding of the key factors that drive the physiological adaptation of microorganisms and greatly enhance our ability to control and optimize the performance of industrial bioreactors. In addition, this work will have an educational impact on graduate (and possibly undergraduate) students both through direct involvement, and through the set of research-based educational materials in microbial growth kinetics and adaptive population dynamics developed at the University of Florida.

多种微生物在含有生长限制基质的混合物的环境中的生长是具有基本生态重要性的问题。虽然文献中有丰富的数学理论在混合环境中的竞争，许多数学模型不直接解决微生物物种在响应环境波动所表现出的生理适应的动态。在我们以前的工作中，我们已经为开发一个全面的数学理论奠定了基础，以满足这个建模利基。我们已经表明，这些模型的预测与实验数据非常吻合。在这个项目中，我们将提供一个坚实的数学背景背后的微生物适应的生理理论，并进一步扩展建模框架，包括关键的生理变量和细胞内过程，我们没有考虑以前。这项工作将为理解复杂微生物群落中的灭绝、共存和生理异质性提供分子基础。本项目还将探讨环境扰动对适应性微生物生态系统的影响，许多现代生物技术，包括食品加工和废水处理，都是基于微生物培养物的受控生长，这是一个对环境扰动敏感的适应性过程。 该项目将有助于我们了解驱动微生物生理适应的关键因素，并大大提高我们控制和优化工业生物反应器性能的能力。此外，这项工作将通过直接参与和通过佛罗里达大学开发的微生物生长动力学和适应性种群动力学的一套基于研究的教育材料对研究生（可能还有本科生）产生教育影响。