Rajagopal Mithila, Martin Melissa J, Santiago Marina, Lee Wonsik, Kos Veronica N, Meredith Tim, Gilmore Michael S, Walker Suzanne
Department of Microbiology and Immunobiology, Harvard Medical School, Boston, Massachusetts, USA Department of Chemistry and Chemical Biology, Harvard University, Cambridge, Massachusetts, USA.
Department of Ophthalmology, Harvard Medical School, Massachusetts Eye and Ear Infirmary, Boston, Massachusetts, USA.
mBio. 2016 Aug 16;7(4):e00950-16. doi: 10.1128/mBio.00950-16.
Staphylococcus aureus is a leading cause of life-threatening infections worldwide. The MIC of an antibiotic against S. aureus, as well as other microbes, is determined by the affinity of the antibiotic for its target in addition to a complex interplay of many other cellular factors. Identifying nontarget factors impacting resistance to multiple antibiotics could inform the design of new compounds and lead to more-effective antimicrobial strategies. We examined large collections of transposon insertion mutants in S. aureus using transposon sequencing (Tn-Seq) to detect transposon mutants with reduced fitness in the presence of six clinically important antibiotics-ciprofloxacin, daptomycin, gentamicin, linezolid, oxacillin, and vancomycin. This approach allowed us to assess the relative fitness of many mutants simultaneously within these libraries. We identified pathways/genes previously known to be involved in resistance to individual antibiotics, including graRS and vraFG (graRS/vraFG), mprF, and fmtA, validating the approach, and found several to be important across multiple classes of antibiotics. We also identified two new, previously uncharacterized genes, SAOUHSC_01025 and SAOUHSC_01050, encoding polytopic membrane proteins, as important in limiting the effectiveness of multiple antibiotics. Machine learning identified similarities in the fitness profiles of graXRS/vraFG, SAOUHSC_01025, and SAOUHSC_01050 mutants upon antibiotic treatment, connecting these genes of unknown function to modulation of crucial cell envelope properties. Therapeutic strategies that combine a known antibiotic with a compound that targets these or other intrinsic resistance factors may be of value for enhancing the activity of existing antibiotics for treating otherwise-resistant S. aureus strains.
Bacterial resistance to every major class of antibiotics has emerged, and we are entering a "post-antibiotic era" where relatively minor infections can lead to serious complications or even death. The utility of an antibiotic for a specific pathogen is limited by both intrinsic and acquired factors. Identifying the repertoire of intrinsic resistance factors of an antibiotic for Staphylococcus aureus, a leading cause of community- and hospital-acquired infections, would inform the design of new drugs as well as the identification of compounds that enhance the activity of existing drugs. To identify factors that limit the activity of antibiotics against S. aureus, we used Tn-Seq to simultaneously assess fitness of transposon mutants in every nonessential gene in the presence of six clinically important antibiotics. This work provides an efficient approach for identifying promising targets for drugs that can enhance susceptibility or restore sensitivity to existing antibiotics.
金黄色葡萄球菌是全球危及生命感染的主要病因。抗生素对金黄色葡萄球菌以及其他微生物的最低抑菌浓度(MIC),除了受许多其他细胞因子复杂的相互作用影响外,还取决于抗生素对其靶点的亲和力。识别影响对多种抗生素耐药性的非靶点因素可为新化合物的设计提供依据,并带来更有效的抗菌策略。我们使用转座子测序(Tn-Seq)检查了金黄色葡萄球菌中转座子插入突变体的大量集合,以检测在六种临床重要抗生素(环丙沙星、达托霉素、庆大霉素、利奈唑胺、苯唑西林和万古霉素)存在下适应性降低的转座子突变体。这种方法使我们能够同时评估这些文库中许多突变体的相对适应性。我们鉴定出了先前已知参与对个别抗生素耐药的途径/基因,包括graRS和vraFG(graRS/vraFG)、mprF和fmtA,验证了该方法,并发现其中一些在多种抗生素类别中都很重要。我们还鉴定出两个新的、以前未表征的基因SAOUHSC_01025和SAOUHSC_01050,它们编码多跨膜蛋白,在限制多种抗生素的有效性方面很重要。机器学习确定了graXRS/vraFG、SAOUHSC_01025和SAOUHSC_01050突变体在抗生素处理后的适应性谱中的相似性,将这些功能未知的基因与关键细胞包膜特性的调节联系起来。将已知抗生素与靶向这些或其他固有耐药因子的化合物联合使用的治疗策略,可能对增强现有抗生素治疗原本耐药的金黄色葡萄球菌菌株的活性具有价值。
细菌对每一类主要抗生素都已出现耐药性,我们正进入一个“后抗生素时代”,相对轻微的感染都可能导致严重并发症甚至死亡。抗生素对特定病原体的效用受到固有因素和获得性因素的限制。确定金黄色葡萄球菌(社区和医院获得性感染的主要病因)对抗生素的固有耐药因子库,将为新药设计以及增强现有药物活性的化合物的鉴定提供依据。为了确定限制抗生素对金黄色葡萄球菌活性的因素,我们使用Tn-Seq在六种临床重要抗生素存在的情况下同时评估转座子突变体在每个非必需基因中的适应性。这项工作为识别有前景的药物靶点提供了一种有效方法,这些靶点可增强对现有抗生素的敏感性或恢复其敏感性。