Quantitative microbiology with widefield microscopy: navigating optical artefacts for accurate interpretations

Abstract

Time-resolved live-cell imaging using widefield microscopy is instrumental in quantitative microbiology research. It allows us to track and measure the size, shape, and content of individual microbial cells over time. However, the small size of microbial cells poses a significant challenge in interpreting image data, as it approaches the dimensions of the microscopes depth of field and experiences diffraction effects. As a result, 2D widefield images of microbial cells contain projected 3D information, blurred by the 3D point spread function. In this study, we employ computer simulations and targeted experiments to investigate the impact of diffraction and projection on our ability to quantify the size and content of microbial cells from 2D microscopic images. This study points to some new and often unconsidered artefacts resulting from the interplay of projection and diffraction effects, within the context of quantitative microbiology. These artefacts introduce substantial errors and biases in size and fluorescence quantification, and even single-molecule counting, making the elimination of these errors a complex task. Awareness of these artefacts is crucial for designing strategies to accurately interpret micrographs of microbes. To address this, we present new experimental designs and machine learning based analysis methods that account for these effects, resulting in accurate quantification of microbiological processes.