Kuendig, T. | bioRxiv Science

bioRxiv2025

NLRP1 inflammasome activation in skin equivalents revealsmechanistic insights into the roles of keratinocytes in psoriasis

Psoriasis is a major inflammatory skin disease for which a causal therapy is still not available. The pro-inflammatory cytokines interleukin(IL)-1{beta} and IL-36{gamma} are key drivers of the disease phenotype, but the mechanisms underlying their regulation in psoriasis remain poorly understood. Generation of IL-1{beta} activity is regulated by protein complexes, termed inflammasomes. We activated the NLRP1 inflammasome in human keratinocytes cultivated in three-dimensional skin equivalents. NLRP1 activation induced histological and molecular features that are highly reminiscent of psoriasis. Mechanistically, the phenotype was dependent on IL-1, which triggered a pro-inflammatory epidermal-dermal crosstalk. This included induction of expression of IL-36{gamma}, which, together with IL-1{beta}, was released from keratinocytes through NLRP1-induced gasdermin D pores. The in vivo relevance of these findings is reflected by the expression of the NLRP1 sensor and signs of inflammasome activation in lesional skin of psoriatic patients. Finally, we discovered endogenous cytoplasmic double stranded (ds) RNA, recently associated with cellular perturbations in psoriasis, as a novel activator of the NLRP1 inflammasome in human keratinocytes. Our results identify a novel endogenous double-stranded RNA-mediated NLRP1-IL-1-IL-36{gamma} signaling axis relevant in psoriasis and suggest targeting of this pathway as a promising treatment strategy.

immunology↗

bioRxiv2021

Cell region fingerprints enable highly precise single-cell tracking and lineage reconstruction

Experimental studies of cell growth, inheritance, and their associated processes by microscopy require accurate single-cell observations of sufficient duration to reconstruct the genealogy. However, cell tracking--assigning identical cells on consecutive images to a track--is often challenging due to imperfect segmentation, moving cells, or focus drift, resulting in laborious manual verification. Here, we propose fingerprints to identify problematic assignments rapidly. A fingerprint distance measures the similarity between cells in two consecutive images by comparing the structural information contained in the low frequencies of a Fourier transform. We show that it is broadly applicable across cell types and image modalities, provided the image has sufficient structural information. Our tracker (TracX) uses the concept to reject unlikely assignments, thereby substantially increasing tracking performance on published and newly generated long-term data sets from various species. For S. cerevisiae, we propose a comprehensive model for cell size control at the single-cell and population level centered on the Whi5 regulator. It demonstrates how highly precise tracking can help uncover previously undescribed single-cell biology.

systems biology↗