A random forest model based on core genome allelic profiles of MRSA for penicillin plus potassium clavulanate susceptibility prediction.

ABSTRACT: Treatment failure of methicillin-resistant Staphylococcus aureus (MRSA) infections remains problematic in clinical practice because therapeutic options are limited. Penicillin plus potassium clavulanate combination (PENC) was shown to have potential for treating some MRSA infections. We investigated the susceptibility of MRSA isolates and constructed a drug susceptibility prediction model for the phenotype of the PENC. We determined the minimum inhibitory concentration of PENC for MRSA (n=284) in a teaching hospital (SRRSH-MRSA). PENC susceptibility genotypes were analysed using a published genotyping scheme based on the mecA sequence. mecA expression in MRSA isolates was analysed by qPCR. We established a random forest model for predicting PENC-susceptible phenotypes using core genome all

SUBMITTER: Zhuang H 

PROVIDER: S-EPMC8715440 | biostudies-literature | 2021 Sep

REPOSITORIES: biostudies-literature