Open-source method of image cytometry in dorsal root ganglia tissue with immunofluorescence

Abstract

Immunohistochemistry (IHC) is a valuable tool in clinical and biological research for evaluating proteins and other antigens in spatially bound tissue. In neuroinflammatory pain research, primary afferent neurons of the dorsal root ganglion (DRG) are studied to understand molecular signaling mechanisms involved in nociception (pain) and inflammation. Measuring IHC (immunofluorescence) in DRG neurons requires manual hand tracing of nuclear and somatic boundaries, which is laborious, error-prone, and may require several weeks to collect the appropriate sample size with a mouse or pen-input display monitor. To overcome these limitations and increase standardization of sampling and measurement, we employed a reliable neuronal cytoplasmic reporter, exclusive to DRG neuronal soma, in a semi-automated algorithm-based approach of Image Cytometry in rat DRG (IC-DRG). The resulting output images are binary nuclear and somatic masks of DRG neurons, defining boundaries of measurement for CellProfiler and manually scored at 94% accurate. Herein, we successfully show a novel approach of automated image analysis for DRG neurons using a robust ImageJ/FIJI script, overcoming morphological variability and imaging artifacts native to imaging frozen tissue sections processed with immunofluorescence.