Please use this identifier to cite or link to this item: https://ahro.austin.org.au/austinjspui/handle/1/25515
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dc.contributor.authorGiulieri, Stefano G-
dc.contributor.authorGuérillot, Romain-
dc.contributor.authorKwong, Jason C-
dc.contributor.authorMonk, Ian R-
dc.contributor.authorHayes, Ashleigh S-
dc.contributor.authorDaniel, Diane-
dc.contributor.authorBaines, Sarah-
dc.contributor.authorSherry, Norelle L-
dc.contributor.authorHolmes, Natasha E-
dc.contributor.authorWard, Peter-
dc.contributor.authorGao, Wei-
dc.contributor.authorSeemann, Torsten-
dc.contributor.authorStinear, Timothy P-
dc.contributor.authorHowden, Benjamin P-
dc.date2020-12-08-
dc.date.accessioned2020-12-15T04:27:57Z-
dc.date.available2020-12-15T04:27:57Z-
dc.date.issued2020-12-08-
dc.identifier.citationmBio 2020; 11(6): 02882-20en_US
dc.identifier.urihttps://ahro.austin.org.au/austinjspui/handle/1/25515-
dc.description.abstractAntistaphylococcal penicillins such as oxacillin are the key antibiotics in the treatment of invasive methicillin-susceptible Staphylococcus aureus (MSSA) infections; however, mec gene-independent resistance adaptation can cause treatment failure. Despite its clinical relevance, the basis of this phenomenon remains poorly understood. Here, we investigated the genomic adaptation to oxacillin at an unprecedented scale using a large collection of 503 clinical mec-negative isolates and 30 in vitro-adapted isolates from independent oxacillin exposures. By combining comparative genomics, evolutionary convergence, and genome-wide association analysis, we found 21 genetic loci associated with low-level oxacillin resistance, underscoring the polygenic nature of this phenotype. Evidence of adaptation was particularly strong for the c-di-AMP signal transduction pathways (gdpP and dacA) and in the clpXP chaperone-protease complex. The role of mutations in gdpP in conferring low-level oxacillin resistance was confirmed by allele-swapping experiments. We found that resistance to oxacillin emerges at high frequency in vitro (median, 2.9 × 10-6; interquartile range [IQR], 1.9 × 10-6 to 3.9 × 10-6), which is consistent with a recurrent minimum inhibitory concentration (MIC) increase across the global phylogeny of clinical isolates. Nevertheless, adaptation in clinical isolates appears sporadically, with no stably adapted lineages, suggesting a high fitness cost of resistance, confirmed by growth assessment of mutants in rich media. Our data provide a broader understanding of the emergence and dynamics of oxacillin resistance adaptation in S. aureus and a framework for future surveillance of this clinically important phenomenon.IMPORTANCE The majority of Staphylococcus aureus strains causing human disease are methicillin-susceptible (MSSA) and can be treated with antistaphylococcal penicillins (such as oxacillin). While acquisition of the mec gene represents the main resistance mechanism to oxacillin, S. aureus can acquire low-level resistance through adaptive mutations in other genes. In this study, we used genomic approaches to understand the basis of S. aureus adaption to oxacillin and its dynamic at the population level. By combining a genome analysis of clinical isolates from persistent MSSA infections, in vitro selection of oxacillin resistance, and genome-wide association analysis on a large collection of isolates, we identified 21 genes linked to secondary oxacillin resistance. Adaptive mutations in these genes were easy to select when S. aureus was exposed to oxacillin, but they also came at a substantial cost in terms of bacterial fitness, suggesting that this phenotype emerges preferentially in the setting of sustained antibiotic exposure.en_US
dc.language.isoeng
dc.subjectStaphylococcus aureusen_US
dc.subjectantibiotic resistanceen_US
dc.subjectgenomicsen_US
dc.subjectβ-lactamsen_US
dc.titleComprehensive Genomic Investigation of Adaptive Mutations Driving the Low-Level Oxacillin Resistance Phenotype in Staphylococcus aureus.en_US
dc.typeJournal Articleen_US
dc.identifier.journaltitlemBioen_US
dc.identifier.affiliationDepartment of Microbiology and Immunology, The University of Melbourne at the Doherty Institute for Infection and Immunity, Melbourne, Australiaen_US
dc.identifier.affiliationMicrobiologyen_US
dc.identifier.affiliationDepartment of Microbiology and Immunology, The University of Melbourne at the Doherty Institute for Infection and Immunity, Melbourne, Australiaen_US
dc.identifier.affiliationMicrobiological Diagnostic Unit Public Health Laboratory, The University of Melbourne at the Doherty Institute for Infection and Immunity, Melbourne, Australiaen_US
dc.identifier.affiliationInfectious Diseasesen_US
dc.identifier.doi10.1128/mBio.02882-20en_US
dc.type.contentTexten_US
dc.identifier.orcid0000-0003-2926-7561en_US
dc.identifier.orcid0000-0002-0557-0518en_US
dc.identifier.orcid0000-0003-0150-123Xen_US
dc.identifier.orcid0000-0003-0237-1473en_US
dc.identifier.pubmedid33293382
local.name.researcherGiulieri, Stefano G
item.grantfulltextnone-
item.openairetypeJournal Article-
item.languageiso639-1en-
item.fulltextNo Fulltext-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.cerifentitytypePublications-
crisitem.author.deptInfectious Diseases-
crisitem.author.deptInfectious Diseases-
crisitem.author.deptInfectious Diseases-
crisitem.author.deptInfectious Diseases-
crisitem.author.deptData Analytics Research and Evaluation (DARE) Centre-
crisitem.author.deptInfectious Diseases-
crisitem.author.deptMicrobiology-
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