Modeling microbial heterogeneity under antibiotic treatment

本研究项目的主要目标是将传统的微生物动力学建模的数学框架扩展到对异质细菌种群的系统研究。将从动力学系统、常微分方程和偏微分方程以及随机过程开发新的应用，以建立和研究一类新的数学模型，专注于决定细菌异质性的生理方面。这些模型将使用分析和数值方法相结合的方法进行仔细检查，并与文献中的实验数据进行比较。该项目不仅将推进微生物种群的一般数学理论，而且还将产生一些理论结论和预测，这些结论和预测将对生物学家在实验室环境中研究微生物异质性有用。这项研究项目将作为未来跨学科科学家的培训基地。首席研究员将开发一套以研究为基础的教育材料，研究异质细菌种群的动力学。对抗生素具有遗传耐药性的病原菌的进化和传播在抗菌化疗失败中起着重要作用。然而，对于许多急性和慢性细菌感染，无论是治疗失败还是抗生素有效所需的长时间都不能归因于细菌群体中的遗传(遗传)耐药性。基因同源的细菌种群实际上是异质的，因为它们包括由于各种生理和生态原因而对抗生素耐药的亚群。通常，细菌种群在其新陈代谢方面也是异质性的。这项研究项目将把建模、实验和分析方法整合成一个描述生理异质性细菌种群的综合理论。所得理论将有助于优化抗菌药物治疗的效率，并为估计最佳药物剂量提供可靠的量化基础。新理论的另一个应用将包括工业生物反应器和废水处理厂的合理设计和控制。

The main goal of this research project is to extend the traditional mathematical framework for modeling microbial kinetics to a systematic study of heterogeneous bacterial populations.New applications from dynamical systems, ordinary and partial differential equations, and stochastic processes will be developed to formulate and study a new class of mathematical models focusing on physiological aspects determining bacterial heterogeneity. The models will be scrutinized using a combination of analytical and numerical methods, and compared to experimental data in the literature. This project will not only advance the general mathematical theory of microbial populations, but it will also produce a number of theoretical conclusions and predictions presented in a way that would be useful for biologists studying microbial heterogeneity in the laboratory setting. This research project will serve as a training ground for future interdisciplinary scientists. The principal investigator will develop a research-based set of educational materials in dynamics of heterogeneous bacterial populations.The evolution and spread of pathogenic bacteria that are genetically resistant to antibiotics plays a significant role in the failure of antibacterial chemotherapy. However, for many acute and chronic bacterial infections neither treatment failure nor the extensive time needed for antibiotics to be effective can be attributed to inherited (genetic) drug resistance in the bacterial populations. Genetically homogenous populations of bacteria are in fact heterogeneous because they include subpopulations that for various physiological and ecological reasons are refractory to antibiotics. Frequently, bacterial populations are also heterogeneous with respect to their metabolism. This research project will integrate the modeling, experimental and analytic approaches into a comprehensive theory describing the physiologically heterogeneous bacterial populations. The resulting theory will aid in optimizing the efficiency of antibacterial drug treatment and develop a sound quantitative basis for estimating optimal drug dosages. Another application of the new theory will include the rational design and control of industrial bioreactors and wastewater treatment plants.