Quantitative Analysis of Microscopy Data to Evaluate Bacterial Responses to Antibiotic Treatment

Abstract

Microscopy is a powerful method to evaluate the direct effects of antibiotic action on the single cell level. As with other methodologies, microscopy data is obtained through sufficient biological and technical replicate experiments, where evaluation of the sample is generally followed over time. Even if a single antibiotic is tested for a defined time, the most certain outcome is large amounts of raw data that requires systematic analysis. Although microscopy is a helpful qualitative method, the recorded information is stored as defined quantifiable units, the pixels. When this information is transferred to diverse bioinformatic tools, it is possible to analyze the microscopy data while avoiding the inherent bias associated to manual quantification. Here, we briefly describe methods for the analysis of microscopy images using open-source programs, with a special focus on bacteria exposed to antibiotics.

Keywords: Antimicrobials; Bacillus subtilis; Convolved Average Projections (CAP); Fluorescence microscopy; Microscopy data analysis and quantification; Staphylococcus aureus; Time-lapse microscopy.