Journal Article

·2024 OPEN ACCESS

Detection of antimicrobial-induced survival/dead bacteria via mEos4b photoconversion: a preliminary study

Ilknur Yilmaz YTU , Humeyra Demir YTU , Aleyna Eslem Tureyen YTU , Tülin Özbek YTU

Methods and Applications in Fluorescence

Abstract

Abstract The escalating prevalence of hospital-acquired infections poses a critical challenge for healthcare systems worldwide. Effective management requires rapid identification of pathogens and their antibiotic resistance profiles. In this study, we utilized the photoconvertible mEos4b protein, which transitions from green to red fluorescence upon blue light exposure, to distinguish live from dead bacteria. The mEos4b gene was cloned into a prokaryotic vector and expressed in Escherichia coli BL21. The Minimum Inhibitory Concentration (MIC) of the transgenic bacteria was determined for five antibiotics, followed by a post-antibiotic effect assessment over a two-hour exposure period. The optimal photoconversion time for mEos4b was established as 90 s, and confocal microscopy was used to visualize live (green) and dead (red) cells post-exposure. The mEos4b-TR system proved highly specific, accurately distinguishing live and dead bacteria without producing false positives, even in control groups, which is a common issue in commercial live-dead kits. By relying on cellular metabolic activity rather than dyes, this system minimizes nonspecific interactions and contamination, making it more reliable than traditional methods prone to false readings. These results highlight the potential of the mEos4b-TR system as a superior alternative for rapid, precise bacterial viability assessments, particularly in determining antibiotic susceptibility. This preliminary study demonstrates the system’s differentiation of viable and non-viable cells, suggesting its potential application in future studies involving novel antibacterial agents to refine antibiotic sensitivity testing.

Keywords

Antibiotics Bacteria Antimicrobial Microbiology Escherichia coli Minimum inhibitory concentration Biology Antibiotic resistance False positive paradox Gene Biochemistry Genetics Computer science

Subject Areas

Vibrio bacteria research studies ·Endocrinology ·Life Sciences
Cell Image Analysis Techniques ·Biophysics ·Life Sciences
Bacillus and Francisella bacterial research ·Molecular Biology ·Life Sciences

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