Plasmidome AMR screening (PAMRS) workflow: a rapid screening workflow for phenotypic characterization of antibiotic resistance in plasmidomes

Author:

Duedu Kwabena ObengORCID,Mends Joana Qwansima,Ayivor-Djanie ReubenORCID,Essandoh Priscilla Efua,Nattah Emmanuel MawuliORCID,Gyamfi JonesORCID,Kpeli Grace Semabia

Abstract

Background: Phenotypic characterization of antimicrobial resistance (AMR) in bacteria has remained the gold standard for investigation and monitoring of what resistance is present in an organism. However, the process is laborious and not attractive for screening multiple plasmids from a microbial community (plasmidomes). Instead, genomic tools are used, but a major bottle neck that presence of genes does not always translate into phenotypes. Methods: We designed the plasmidome AMR screening (PAMRS) workflow to investigate the presence of antibiotic resistant phenotypes in a plasmidome using Escherichia coli as a host organism. Plasmidomes were extracted from the faecal matter of chicken, cattle and humans using commercial plasmid extraction kits. Competent E. coli cells were transformed and evaluated using disk diffusion. Thirteen antibiotic resistant phenotypes were screened. Results: Here, we show that multiple antibiotic resistant phenotypes encoded by plasmids can be rapidly screened simultaneously using the PAMRS workflow. E. coli was able to pick up to 7, 5 or 8 resistant phenotypes from a single plasmidome from chicken, cattle or humans, respectively. Resistance to ceftazidime was the most frequently picked up phenotype in humans (52.6%) and cattle (90.5%), whereas in chickens, the most picked up resistant phenotype was resistance to co-trimoxazole, ceftriaxone and ampicillin (18.4% each). Conclusions: This workflow is a novel tool that could facilitate studies to evaluate the occurrence and expression of plasmid-encoded antibiotic resistance in microbial communities and their associated plasmid-host ranges. It could find application in the screening of plasmid-encoded virulence genes.

Funder

The World Academy of Sciences

African Academy of Sciences

Bill and Melinda Gates Foundation

Publisher

F1000 Research Ltd

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