Podosomes are actin-enriched adhesion structures important for multiple cellular processes, including migration, bone remodeling, and phagocytosis. Here, we characterized the structure and organization of phagocytic podosomes using interferometric photoactivated localization microscopy (iPALM), a super-resolution microscopy technique capable of 15-20 nm resolution, together with structured illumination microscopy (SIM) and localization-based superresolution microscopy. Phagocytic podosomes were observed during frustrated phagocytosis, a model in which cells attempt to engulf micro-patterned IgG antibodies. For circular patterns, this resulted in regular arrays of podosomes with well-defined geometry. Using persistent homology, we developed a pipeline for semi-automatic identification and measurement of podosome features. These studies revealed an "hourglass" shape of the podosome actin core, a protruding "knob" at the bottom of the core, and two actin networks extending from the core. Additionally, the distributions of paxillin, talin, myosin II, α-actinin, cortactin, and microtubules relative to actin were characterized.

Advances in microscopy hold great promise for allowing quantitative and precise readouts of morphological and molecular phenomena at the single cell level in bacteria. However, the potential of this approach is ultimately limited by the availability of methods to perform unbiased cell segmentation, defined as the ability to faithfully identify cells independent of their morphology or optical characteristics. In this study, we present a new algorithm, Omnipose, which accurately segments samples that present significant challenges to current algorithms, including mixed bacterial cultures, antibiotic-treated cells, and cells of extended or branched morphology. We show that Omnipose achieves generality and performance beyond leading algorithms and its predecessor, Cellpose, by virtue of unique neural network outputs such as the gradient of the distance field. Finally, we demonstrate the utility of Omnipose in the characterization of extreme morphological phenotypes that arise during interbacterial antagonism and on the segmentation of non-bacterial objects. Our results distinguish Omnipose as a uniquely powerful tool for answering diverse questions in bacterial cell biology.