Abstract
ABSTRACTStaphylococcus 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.
Highlights
Staphylococcus aureus is a leading cause of life-threatening infections worldwide
Methicillin-resistant S. aureus (MRSA) strains have acquired the mobile staphylococcal cassette chromosome mec element (SCCmec), encoding a transpeptidase, PBP2A, which is naturally resistant to -lactams, enabling the organism to make cross-linked peptidoglycan when the native transpeptidases are inactivated by the -lactams [1,2,3]
Two different transposon libraries constructed in methicillin-susceptible S. aureus (MSSA) strain HG003 were used in initial screens for mutants exhibiting either enhanced resistance or enhanced susceptibility to an antibiotic [14, 26]
Summary
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. The most attractive candidates for targeting are those factors that hinder the activity of multiple classes of antibiotics To identify such candidates, as well as additional factors contributing to the resistance of specific individual antibiotics, we used the massively parallel approach of transposon sequencing (Tn-Seq) [13,14,15] to examine large pools of S. aureus transposon mutants for fitness defects upon exposure to multiple classes of antibiotics. We have performed Tn-Seq analysis using transposon libraries treated with six different antibiotics to identify genes with significantly fewer mapped reads than were seen with an untreated control These genes, which we refer to as intrinsic resistance factors, render the bacteria more sensitive to the antibiotic tested when inactivated. In addition to previously identified factors, we have identified two hitherto-uncharacterized factors as important intrinsic resistance factors for multiple antibiotics
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