PeroxiDynA: A New Tool to Analyze Peroxisome Dynamics via 2D Image Processing

Abstract Peroxisomes are dynamic organelles that play important roles in cellular metabolic and signaling pathways and are implicated in several disease conditions. Although a detailed comprehension of peroxisome dynamics is crucial in various contexts of health and disease, its accurate assessment still presents significant challenges, mainly due to their morphological heterogeneity. Here, we discuss different strategies to study peroxisome dynamics and present a semi-automated macro, PeroxiDynA, that enables the analysis of peroxisome dynamics from single-plane confocal images of mammalian cells in ImageJ. Our findings confirm that PeroxiDynA can be successfully employed to determine relative peroxisome number and spatial distribution. A comparison between PeroxiDynA and other image analysis strategies reveals that it results in increased reliability in the analysis of peroxisome abundance and morphology. Although future improvements are still required to minimize the time and limitations imposed during analysis of peroxisomal features, we propose that PeroxiDynA is a useful tool for biomolecular studies, not only to analyze peroxisomes but also the dynamics of small biological structures in cells from mammals and other organisms.