Contribution of altered lipid metabolism to resistance to cell envelope-targeting antimicrobials in MRSA

项目摘要 由“超级细菌”耐甲氧西林金黄色葡萄球菌（MRSA）引起的侵入性感染是导致 比美国任何其他耐药细菌病原体的死亡人数都多。糖肽（GP），万古霉素- 抗生素是治疗MRSA的标准护理，但治疗失败是常见的。万古霉素 与另外两类对治疗MRSA感染也很重要的抗生素密切相关， 脂肽（LP）和脂糖肽（LGP）。这些类别中的每一种药物都可以选择用于交叉- 不同程度地抵抗其他人，但这种交叉抗性背后的机制并不完全相同， 理解。此外，迫切需要开发新的诊断方法，可以预测对GP的药物反应， LP和LGP抗菌剂，并开发可调节耐药性的新疗法。最近，使用一个 创新的脂质组学方法，我们已经观察到脂质代谢的显著和特征性变化， 与对每一类药物（GP、LP和LGP）的耐药性有关。我们假设脂质组学特征 反映了特定的抗生素耐药性机制，这些脂质组学特征可以 被其他小分子修饰以有利于易感表型。我们建议全面整合-- 罗盖特MRSA对GP、LP和LGP抗菌剂的耐药和交叉耐药机制， 整合脂质组学、基因组学和转录组学。在AIM 1中，我们的战略将侧重于阐明 在体外选择的菌株中，脂质代谢的改变导致了耐药表型的发展， 支持GP，LP和/或LGP使用全面的脂质组学，加上基因组学，转录组学，标准 ard和先进的敏感性测试，以及细胞壁和细胞膜的定量生物物理评估- 膜性质每个基因突变对耐药表型的贡献将通过类似的方法阐明。 通过等位基因置换产生的单基因突变体的表征。在AIM 2中，我们将测试假设 β-内酰胺类药物至少部分通过改变脂质， 细菌的组成。我们将检查研究药物和β- 通过整合组学方法对β-内酰胺类抗生素进行了研究，这将有助于深入了解β-内酰胺类抗生素的协同作用机制 与这些药物和β-内酰胺的“跷跷板效应”。在AIM 3中，我们将评估我们的脂质组学的灵敏度。 鉴定敏感性亚MIC差异并预测对临床相关GP、LP LGP曝光我们预计，这一战略将产生有价值的洞察改变脂质代谢的作用， 禁忌症产生抗菌素耐药性。这项工作是重要的，因为被确定为关键的途径- 对抗性敏感和对调节敏感的基因将为进一步的研究奠定基础， 预防性治疗和先进的诊断，这反过来又会改善人类健康。在- 这一建议的核心包括新的脂质组学方法，整合组学方法，和核心， 脂质组学特征与临床相关药效学终点的关系。

Project Summary Invasive infections due to the “superbug” methicillin-resistant Staphylococcus aureus (MRSA) are responsible for more deaths than any other drug-resistant bacterial pathogen in the USA. The glycopeptide (GP), vanco- mycin, is the standard of care for the treatment of MRSA, but therapeutic failures are common. Vancomycin is closely related to two other classes of antibiotics that are also important for the treatment of MRSA infections, the lipopeptides (LP) and the lipoglycopeptides (LGP). Drugs from each of these classes can select for cross- resistance to the others to various degrees, but the mechanisms behind this cross-resistance are not well un- derstood. In addition, there is a critical need to develop new diagnostics that can predict drug response to GP, LP, and LGP antimicrobials, and to develop novel therapies that can modulate resistance. Recently, using an innovative lipidomic approach we have observed significant and characteristic changes in lipid metabolism as- sociated with resistance to each class of drugs (GP, LP, and LGP). We hypothesize that lipidomic signatures in the cell membrane reflect specific antibiotic resistance mechanisms and that these lipidomic signatures can be modified by other small molecules to favor a susceptible phenotype. We propose to comprehensively inter- rogate the mechanisms of resistance and cross-resistance to GP, LP, and LGP antimicrobials in MRSA by in- tegrated lipidomics, genomics, and transcriptomics. In AIM 1, our strategy will focus on elucidating the role of altered lipid metabolism in the development of resistant phenotypes in in vitro-selected strains that are re- sistant to GP, LP, and/or LGP using comprehensive lipidomics, coupled with genomics, transcriptomics, stand- ard and advanced susceptibility testing, and quantitative biophysical assessment of cell wall and cell mem- brane properties. Contribution of each gene mutation to the resistant phenotypes will be elucidated by similar characterization of single-gene mutants generated by allelic replacement. In AIM 2, we will test the hypothesis that β-lactams modulate the susceptibility of MRSA to GP, LP, and LGP, at least in part, by modifying the lipid composition of the bacteria. We will examine the synergistic interactions between the study drugs and β- lactams by the integrated omics approach, which would yield insights into the mechanisms of β-lactam synergy with these agents and the β-lactam “seesaw effect”. In AIM 3, we will evaluate the sensitivity of our lipidomic technique to identify sub-MIC differences in susceptibility and predict response to clinically relevant GP, LP, and LGP exposures. We anticipate that this strategy will yield valuable insight into the role of altered lipid me- tabolism in producing antimicrobial resistance. This work is significant because the pathways identified as crit- ical to resistance and susceptible to modulation will lay the foundation for further studies that could lead to re- sistance prevention therapeutics and advanced diagnostics, which in turn will improve human health. The in- novation of this proposal includes the novel lipidomics methodology, the integrated omics approach, and cor- relation of lipidomic signatures with clinically relevant pharmacodynamics endpoints.