Investigation of carbapenem-resistant Enterobacterales isolates at a tertiary laboratory in Pretoria, South Africa

Ramashia, Mbudzeni and Phofa, Thabiso D. and Nkawane, Granny M. and Nogbou, Noel-David and Bolukaoto, John Y. and Nchabeleng, Maphoshane and Musyoki, Andrew M. (2023) Investigation of carbapenem-resistant Enterobacterales isolates at a tertiary laboratory in Pretoria, South Africa. ACTA MICROBIOLOGICA ET IMMUNOLOGICA HUNGARICA, 70 (4). pp. 295-303. ISSN 1217-8950

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Abstract

This study aimed to investigate phenotypic and genotypic characteristics of carbapenem-resistant Enterobacterales isolates (CRE) at a tertiary laboratory in South Africa. A total of 99 CRE isolates were collected between 2019 and 2021. Carbapenemase production was tested using modified carbapenem inhibitory method. Colistin susceptibility testing was performed using the ComASPTM Colistin broth microdilution method. Conventional PCR assays were conducted for detection of mcr-1 gene and common carbapenemase genes (blaVIM, blaNDM, blaIMP, blaKPC, blaOXA-23, blaOXA-51 and blaOXA-48). Rep-PCR assay was conducted to determine the genetic relatedness of the study isolates. Majority of the isolates were Klebsiella pneumoniae (83%). Carbapenem resistant K. pneumoniae cluster was observed from ICU and surgical ward samples. Colistin resistance was observed in 13% (12/93) of the isolates namely, in 11 K. pneumoniae and one Enterobacter cloacae. The blaOXA-48 (65%) was the most prevalent gene detected followed by blaNDM (25%) and blaVIM (22%). Several K. pneumoniae isolates concomitantly carried multiple carbapenemase genes with one isolate carry up to 5 five genes blaVIM, blaNDM, blaOXA-48, blaOXA23 and blaOXA-51. The mcr-1 gene was not detected in the isolates. Rep-PCR assay showed that most isolates matched cluster A (50%). The high prevalence of blaOXA-48, blaNDM and emerging colistin resistant isolates is of concern for patient management at this institution and needs close monitoring. RepPCR is a valuable tool in establishing infection clusters in resource-limited settings.

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