Engineering microbial social interactions: Towards new anti-biofilm therapies

描述(由申请人提供) 摘要：抗生素耐药性在全球范围内是一个日益严重的问题，这损害了这些药物作为我们对抗微生物感染的主要防御措施的使用。抗生素本身就是一种选择性的耐药性压力，目前开发新的抗生素类别的解决方案只会推迟问题，直到出现新的耐药性。我的目标是开发全新的策略，通过瞄准致病过程中涉及的社会相互作用来对抗病原菌。这一目标的动机是认识到，大多数病原体不是孤立的有机体，而是生活在称为生物膜的多细胞群落中，在那里细胞与细胞的相互作用是必不可少的。我们最近将社会进化理论应用于微生物学，已经表明生物膜的形成、群体感应和毒力分泌高度依赖于细胞之间的相互作用，而合作相互作用的命运受到竞争菌株的存在的挑战。因此，我假设以社会互动为目标的疗法可以降低细菌种群的毒力，而不会产生强大的耐药性选择。我将在铜绿假单胞菌中检验这一假设，这是一种条件人类病原体，通过形成抗药性生物膜感染囊性纤维化患者的肺部而臭名昭著。强健生物膜的形成需要鼠李糖脂生物表面活性剂的良好分泌，鼠李糖脂生物表面活性剂是自行产生的分散剂，在生物膜三维结构的形成中起着重要作用。我将调查导致鼠李糖脂分泌不受调控的条件，作为自我诱导生物膜扩散的潜在策略。在本奖项期间，我将开展三个互补的研究途径，将定量-实验和计算方法相结合：(1)我将表征铜绿假单胞菌分泌生物表面活性物质的群体感应调节的动态响应。我将通过选择性地删除调控途径中的基因并使用报告融合来测量系统反应来实现这一点。(2)开发下一代逼真的三维生物膜计算模型。我将应用这些模型来合理地设计诱导自我促进的生物膜扩散的策略。(3)我将量化社会互动的网络，并通过实验测试通过干扰这些互动来分散生物膜的策略。这些研究将定量社会进化的应用扩展到分子和细胞生物学，并将首次提供微生物群体的系统观点，将对细胞间遗传和表型多样性的动态观察与细胞合作的重要性结合起来。该项目利用了我在工程学、系统生物学和进化论方面的独特专业知识，并将这些专业知识应用于对抗微生物感染的新疗法。

DESCRIPTION (Provided by the applicant) Abstract: Antibiotic resistance is a mounting problem at the global scale that compromises the use of these drugs as our main defense against microbial infections. The antibiotics themselves act as a selective pressure for resistance, and the present solution of developing new antibiotic classes only delays the problem until new resistance emerges. My goal is to develop entirely new strategies to fight pathogenic bacteria by targeting the social interactions involved in pathogenesis. The goal is motivated by the realization that most pathogenic bacteria are not isolated organisms, but rather live in multicellular communities called biofilms where cell-cell interactions are essential. Our recent applications of social evolutionary theory to microbiology have already shown that biofilm formation, quorum sensing and virulent secretions are highly dependent on interactions among cells and that the fate of cooperative interactions is challenged by the presence of competing strains. Therefore, I hypothesize that therapies that target social interactions can reduce the virulence of bacterial populations without creating strong selection for resistance. I will test this hypothesis in the bacterium Pseudomonas aeruginosa, an opportunistic human pathogen notorious for infecting the lungs of cystic fibrosis patients by forming antibiotic resistant biofilms. The formation of robust biofilms requires well-regulated secretion of rhamnolipid biosurfactants, which are self-produced dispersants that play a major role in shaping biofilm 3-D structure. I will investigate the conditions that lead to unregulated rhamnolipid secretion as potential strategies for self-induced biofilm dispersal. For the period of this award I will carry out three complementary research avenues that will combine quantitative-experimental and computational methods: (1) I will characterize the dynamic response of the quorum sensing regulation of biosurfactant secretion in P. aeruginosa. I will carry this out by selectively deleting genes in the regulatory pathway and measuring system response using reporter fusions. (2) I will develop the next generation of realistic 3-D computational biofilm models. I will apply these models to rationally design strategies that induce self-promoted biofilm dispersal. (3) I will quantify the networks of social interactions and test experimentally strategies that disperse biofilms by perturbing those interactions. These studies expand the applications of quantitative social evolution to molecular and cell biology, and will provide for the first time a systems view of microbial groups that integrates the dynamic observations of genetic and phenotypic diversity among cells with the importance of cellular cooperation. The project leverages my unique expertise at the interface of engineering, systems biology and evolution, and applies this expertise towards new therapies against microbial infection.