Varlamova, V. | Search bioRxiv

bioRxiv2026

Structure of zebrafish NLRP3 reveals a novel mode of inflammasome activation

NLRP3 is an innate immune sensor of a broad range of stimuli, which upon activation forms a multiprotein inflammasome complex triggering caspase-1 activation, IL-1{beta} and IL-18 maturation, and inflammatory cell death. The canonical NLRP3 activation pathway has been well characterized from a structural perspective. It involves the association of NLRP3 with membranes in the form of inactive oligomeric "cage" complexes, which, upon activation, convert to an active oligomeric NLRP3 disc. NLRP3 structural rearrangements during non-classical NLRP3 activation pathways, however, remain unknown. Here, we report a novel mode of NLRP3 activation utilized by the NLRP3 homolog from zebrafish. The cryo-EM structure of zebrafish NLRP3 shows that, unlike human NLRP3, it forms disc-shaped heptamers that undergo further trimerization, resulting in a 21-mer oligomeric arrangement. Surprisingly, a single zebrafish NLRP3 heptamer cannot arrange its PYD domains into a PYD helix and therefore requires a trimer of heptamers to form a PYD filament that enables ASC oligomerization. Furthermore, zebrafish NLRP3 does not associate with the Golgi network, nor does it form inactive "cage" oligomers or interact with NEK7. Thus, our data demonstrate an ancestral non-canonical structural mechanism of NLRP3 activation, which may shed light on alternative NLRP3 activation pathways present in humans.

immunology↗

bioRxiv2025

scPortrait integrates single-cell images into multimodal modeling

Machine learning increasingly uncovers rules of biology directly from data, enabled by large, standardized datasets. Microscopy images provide rich information on cellular architecture and are accessible at scale across biological systems, making them an ideal foundation for modeling cell behavior. However, a standardized image format does not exist at the single-cell level. Here we present scPortrait, an scverse software package for generation, storage, and application of single-cell image datasets. scPortrait reads, stitches and segments raw fields of view with out-of-core computation scaling to larger-than-memory datasets. Parallelization enables rapid extraction of individual cells into a standardized single-cell image format with fast access to accelerate machine learning. scPortrait enables analysis across modalities including images, proteomics and transcriptomics, identifying cancer-associated macrophage subpopulations by morphology and embedding single-cell images into transcriptome atlases. scPortrait turns microscopy images into a reusable resource for integrative cell modeling, establishing single-cell images as a core modality in systems biology.

systems biology↗