Antibiotic Susceptibility of Bacteria in Biofilms

描述(申请人提供)：当细菌附着在表面并以生物膜的形式生长时，它们受到抗生素的保护，不会被杀死。生物膜的形成越来越被认为是各种感染持续存在的一个因素。该项目的目标是通过开发第一个全面的、现象学的生物膜降低对抗生素杀死的敏感性的模型，来补充正在进行的生物膜中抗生素耐药性的实验研究。现有的生物膜发展数学模型将扩展到包括四种假想的保护机制。这些机制解决了抗生素渗透迟缓，局部营养耗竭导致部分生物膜代谢活性或生长减少，一些生物膜细菌的应激反应激活，以及一些生物膜细胞分化为类似于孢子形成的休眠持久状态。基于对生物膜作为粘弹性流体的力学分析，将通过开发细胞从生物膜中释放的数学表达式来改进该模型。最后，将模型结果与实验数据进行比较。实验将在铜绿假单胞菌实验系统中进行，以测量抗生素治疗的时空反应，包括杀死和脱落，并将这些结果与数学模型的输出进行比较。在理解面对抗生素化疗时生物被膜感染的顽固持久性方面的进展令人惊讶地缓慢。这一建模工作将通过整合必须考虑的许多组成现象，并作为必须沟通以解决这一问题的不同学科之间对话的工具，来加速这一努力。该模型最终将成为一种工具，用于研究假想的耐药性机制的后果，设计实验来测试这些机制，确定新的治疗策略，并确定最佳抗生素剂量方案。该项目将为三名参与的研究生提供丰富的跨学科培训经验。

DESCRIPTION (provided by applicant): When bacteria attach to a surface and grow as a biofilm they are protected from killing by antibiotics. Biofilm formation is increasingly recognized as a factor in the persistence of varied infections. The goal of this project is to complement ongoing experimental investigations of antibiotic resistance in biofilms by developing the first comprehensive, phenomenological model of biofilm reduced susceptibility to killing by antibiotics. An existing mathematical model of biofilm development will be expanded to include four hypothesized protective mechanisms. These mechanisms address retarded antibiotic penetration, reduced metabolic activity or growth in parts of the biofilm due to local nutrient depletion, stress response activation by some biofilm bacteria, and differentiation of some biofilm cells into a dormant persister state analogous to spore formation. The model will be improved by developing mathematical expressions for the release of cells from the biofilm based on a mechanical analysis of the biofilm as a viscoelastic fluid. Finally, model results will be compared to experimental data. Experiments will be performed to measure spatio-temporal responses, including both killing and detachment, to antibiotic treatment in a P. aeruginosa experimental system, and these results will be compared with output of the mathematical model. Progress in understanding the stubborn persistence of biofilm infections in the face of antibiotic chemotherapy has been surprisingly slow. This modeling effort will accelerate this effort by integrating the many constituent phenomena that must be considered and serving as a vehicle for dialogue between the diverse disciplines that must communicate to solve this problem. The model will ultimately be a tool for investigating the consequences of hypothesized resistance mechanisms, designing experiments to test these mechanisms, identifying novel treatment strategies, and determining optimal antibiotic dosing protocols. This project will afford a rich interdisciplinary training experience for the three participating graduate students.