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Staphylococcus aureus is an important pathogen, giving rise to antimicrobialresistance in cell strains such as Methicillin Resistant S. aureus (MRSA). Herewe report an image analysis framework for automated detection and imagesegmentation of cells in S. aureus cell clusters, and explicit identificationof their cell division planes. We use a new combination of several existinganalytical tools of image analysis to detect cellular and subcellularmorphological features relevant to cell division from millisecond time scalesampled images of live pathogens at a detection precision of single molecules.We demonstrate this approach using a fluorescent reporter GFP fused to theprotein EzrA that localises to a mid-cell plane during division and is involvedin regulation of cell size and division. This image analysis framework presentsa valuable platform from which to study candidate new antimicrobials whichtarget the cell division machinery, but may also have more general applicationin detecting morphologically complex structures of fluorescently labelledproteins present in clusters of other types of cells.

physical biology

An automated image analysis framework for segmentation and division  plane detection of single live Staphylococcus aureus cells which can operate  at millisecond sampling time scales using bespoke Slimfield microscopy