Browsing by Author "Agustin, Debby"

Antimicrobial resistance (AMR) is a crucial problem in the clinical field worldwide. The need for novel antimicrobials to tackle AMR is imminent. Image-derived data can be used to understand the mechanism of action (MoA) of newly discovered compounds and classify them within known classes of antibiotics. This study aimed to develop a simple image-based measurement method for screening new antimicrobials and simultaneously defining the MoA. In the process, Escherichia coli ATCC 25292 was selected as a model strain from the Gram-negative bacterial group. This strain was treated with antibiotics belonging to different classes. Treated bacteria were imaged with Cytation 5 Cell Imaging Reader and analyzed using ImageJ2 software. The developed workflow was validated by testing the pipeline to be applied for some ESKAPE strains categorized as antibiotic-resistant bacteria. The results revealed that this pipeline enables us to observe the bacterial single-cell phenotypic changes in response to antimicrobials, such as the elongation caused by ampicillin and ciprofloxacin treatments, which are cell wall synthesis and DNA replication inhibitors, respectively. The treated bacterial cells were significantly longer than untreated cells from the sample without antibiotic. Thus, the image-based-high throughput assay can support the drug discovery by identifying the preliminary MoA of new antimicrobials against AMR bacteria. Promising data obtained on E. coli and some pathogenic bacteria allow for pursuing similar approach with other AMR Gram-negative bacterial species.