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

项目摘要 由耐甲氧西林金黄色葡萄球菌(MRSA)引起的侵袭性感染是原因之一 比美国其他任何耐药细菌病原体的死亡人数都多。糖肽(GP)，Vanco- 霉素A是治疗耐甲氧西林金黄色葡萄球菌的标准药物，但治疗失败的情况很常见。万古霉素是 与另外两类抗生素密切相关，这两类抗生素对治疗MRSA感染也很重要， 脂多肽(LP)和脂糖肽(LGP)。这些类别中的每一类药物都可以选择用于交叉- 对其他抗性有不同程度的抗性，但这种交叉抗性背后的机制并不很好。 他站起来了。此外，迫切需要开发新的诊断方法来预测药物对GP的反应， LP和LGP抗菌剂，并开发可以调节耐药性的新疗法。最近，使用一个 创新的脂肪组学方法我们观察到了脂代谢的显著和特征性变化，如- 与每一类药物(GP、LP和LGP)的耐药性有关。我们假设脂肪组织的签名 在细胞膜中反映了特定的抗生素耐药机制，这些脂体特征可以 被其他小分子修饰以有利于易感表型。我们建议全面开展国际合作 目的探讨耐甲氧西林金黄色葡萄球菌(MRSA)对GP、LP、LGP耐药及交叉耐药的机制。 整合了脂类组学、基因组学和转录组学。在目标1中，我们的战略将侧重于阐明 脂代谢改变在体外选择的菌株耐药表型发展中的作用 抗GP、LP和/或LGP使用全面的脂质组学，结合基因组学、转录组学、标准- ARD和高级药敏试验，以及细胞壁和细胞膜的定量生物物理评估- 膜特性。每个基因突变对耐药表型的贡献将通过类似的 等位基因置换产生的单基因突变的特征。在目标2中，我们将检验假设 β-内酰胺类药物至少部分地通过改变脂质来调节耐甲氧西林金黄色葡萄球菌对糖蛋白、脂蛋白和糖蛋白的敏感性 细菌的组成。我们将研究研究药物与β之间的协同作用。 β-内酰胺类药物协同作用机制的研究 与这些制剂和β-内酰胺类药物一起产生的“翘翘板效应”。在AIM 3中，我们将评估我们的脂质体的敏感性 识别亚MIC敏感性差异并预测对临床相关GP，LP， 和LGP暴露。我们预计，这一策略将对脂代谢改变的作用产生有价值的见解- 产生抗菌素耐药性中的代谢作用。这项工作意义重大，因为被识别为Crit- 对抗性和对调控的敏感性将为进一步的研究奠定基础，从而可能导致重新 抗药性预防疗法和先进的诊断方法，这反过来又将改善人类健康。在- 这一建议的创新包括新的脂质组学方法学、集成组学方法和COR。 脂体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.