Proteomic analysis of FACS-enriched whole nematocysts from the colonial hydrozoan Hydractinia symbiolongicarpus

Cnidarians possess a cell-based venom system in the form of nematocytes or “stinging cells” that are found across various tissues. The scattered distribution of these venom-containing cells makes isolation difficult, particularly for proteomic studies. These challenges can be circumvented in laboratory systems with efficient culturing conditions and robust molecular resources for downstream validation, such as exists for Hydra and Nematostella. The colonial hydrozoan Hydractinia symbiolongicarpus is an established laboratory model and an emerging candidate for functional studies of the venom system. Here, we present a proteome derived from a fluorescence-activated cell sorted cell population of developing and mature nematocytes from an established Hydractinia transgenic line. We detected a total of 8,470 proteins, of which 2,232 could be statistically quantified across two different fluorescence-activated cell sorting gating strategies. We found that 165 proteins were enriched within a more lenient, low-cell bias strategy while 760 proteins were enriched using a more stringent gating strategy with greater predicted cell viability. We compared this dataset to a previously assembled nematocyst-enriched transcriptome, as well as two different single-cell RNA-sequencing datasets for Hydractinia, to validate the enrichment of protein candidates in the nematocyte lineage. Furthermore, we evaluated orthologous clusters shared between our Hydractinia proteome, a well-established nematocyst proteome from Hydra, and nematocyst-enriched proteomes from two other cnidarians. Through these comparisons, we revealed substantial shared clusters across these four cnidarian species as well as multiple hydrozoan-specific clusters. Overall, our proteomic analysis provides an integral, complementary resource to the established molecular and laboratory tools available in Hydractinia, advancing its utility as a functional venom systems model.