  Staphylococcus aureus is an important pathogen, giving rise to antimicrobial
resistance in cell strains such as Methicillin Resistant S. aureus (MRSA). Here
we report an image analysis framework for automated detection and image
segmentation of cells in S. aureus cell clusters, and explicit identification
of their cell division planes. We use a new combination of several existing
analytical tools of image analysis to detect cellular and subcellular
morphological features relevant to cell division from millisecond time scale
sampled images of live pathogens at a detection precision of single molecules.
We demonstrate this approach using a fluorescent reporter GFP fused to the
protein EzrA that localises to a mid-cell plane during division and is involved
in regulation of cell size and division. This image analysis framework presents
a valuable platform from which to study candidate new antimicrobials which
target the cell division machinery, but may also have more general application
in detecting morphologically complex structures of fluorescently labelled
proteins present in clusters of other types of cells.
