Next-generation genomic sequencing has shown potential as a predictor of phenotype and for understanding genes thought to confer antimicrobial resistance (AMR) in bacterial communities. Despite the availability of genome sequencing and improvements to proteomic workflows enabling robust, sensitive and comprehensive discovery and quantitation of biomolecules, there are still little to no experimental studies evaluating how the bacterial proteome responds to antimicrobial challenge in the case of AMR.
Our research aims to understand the AMR capabilities of an isolate on a molecular level through examination of its genome and proteome, with and without antibiotic challenge. This research seeks to evaluate how effectively genome sequences predict the phenotype by connecting AMR genes to gene end-products on the proteoform-level, which has yet to be experimentally shown using a systems biology approach.
Long- and short-read genomic sequencing and assembly was conducted in-house on multi-drug resistant E. coli isolates to confirm the presence of AMR-related genes. A shotgun LC/MS/MS proteomics pipeline measured proteome changes with and without antibiotic challenge. PEAKS Studio X, UniProt, and STRING databases was used to analyse data.
Several proteins related to AMR were found to be upregulated, despite no antibiotic challenge, including multi-drug resistance proteins. Additionally, several proteins previously annotated as hypothetical were observed.
Our research findings are one of the first to experimentally link an AMR-related gene to the AMR-related protein using a systems biology approach, providing evidence that the genotype and the phenotype do differ. Results highlight that more proteoform-level evidence is required to validate the insights made by genomic sequencing projects, especially in cases which define the “resistance” status of an isolate based on the presence or absence of particular gene elements. Finally, this study supports genomic sequencing as having a strong potential to replace current clinical tests and provide more specificity in antibiotic selection in the clinic.