B cell expansion hinders the stroma-epithelium regenerative cross talk during mucosal healing.

Therapeutic promotion of intestinal regeneration holds great promise, but defining the cellular mechanisms that influence tissue regeneration remains an unmet challenge. To gain insight into the process of mucosal healing, we longitudinally examined the immune cell composition during intestinal damage and regeneration. B cells were the dominant cell type in the healing colon, and single-cell RNA sequencing (scRNA-seq) revealed expansion of an IFN-induced B cell subset during experimental mucosal healing that predominantly located in damaged areas and associated with colitis severity. B cell depletion accelerated recovery upon injury, decreased epithelial ulceration, and enhanced gene expression programs associated with tissue remodeling. scRNA-seq from the epithelial and stromal compartments combined with spatial transcriptomics and multiplex immunostaining showed that B cells decreased interactions between stromal and epithelial cells during mucosal healing. Activated B cells disrupted the epithelial-stromal cross talk required for organoid survival. Thus, B cell expansion during injury impairs epithelial-stromal cell interactions required for mucosal healing, with implications for the treatment of IBD.

A genetic approach reveals different modes of action of prefoldins.

The prefoldin complex (PFDc) was identified in humans as a co-chaperone of the cytosolic chaperonin T-COMPLEX PROTEIN RING COMPLEX (TRiC)/CHAPERONIN CONTAINING TCP-1 (CCT). PFDc is conserved in eukaryotes and is composed of subunits PFD1-6, and PFDc-TRiC/CCT folds actin and tubulins. PFDs also participate in a wide range of cellular processes, both in the cytoplasm and in the nucleus, and their malfunction causes developmental alterations and disease in animals and altered growth and environmental responses in yeast and plants. Genetic analyses in yeast indicate that not all of their functions require the canonical complex. The lack of systematic genetic analyses in plants and animals, however, makes it difficult to discern whether PFDs participate in a process as the canonical complex or in alternative configurations, which is necessary to understand their mode of action. To tackle this question, and on the premise that the canonical complex cannot be formed if one subunit is missing, we generated an Arabidopsis (Arabidopsis thaliana) mutant deficient in the six PFDs and compared various growth and environmental responses with those of the individual mutants. In this way, we demonstrate that the PFDc is required for seed germination, to delay flowering, or to respond to high salt stress or low temperature, whereas at least two PFDs redundantly attenuate the response to osmotic stress. A coexpression analysis of differentially expressed genes in the sextuple mutant identified several transcription factors, including ABA INSENSITIVE 5 (ABI5) and PHYTOCHROME-INTERACTING FACTOR 4, acting downstream of PFDs. Furthermore, the transcriptomic analysis allowed assigning additional roles for PFDs, for instance, in response to higher temperature.

A comprehensive mouse kidney atlas enables rare cell population characterization and robust marker discovery.

The kidney's cellular diversity is on par with its physiological intricacy; yet identifying cell populations and their markers remains challenging. Here, we created a comprehensive atlas of the healthy adult mouse kidney (MKA: Mouse Kidney Atlas) by integrating 140.000 cells and nuclei from 59 publicly available single-cell and single-nuclei RNA-sequencing datasets from eight independent studies. To harmonize annotations across datasets, we built a hierarchical model of the cell populations. Our model allows the incorporation of novel cell populations and the refinement of known profiles as more datasets become available. Using MKA and the learned model of cellular hierarchies, we predicted previously missing cell annotations from several studies. The MKA allowed us to identify reproducible markers across studies for poorly understood cell types and transitional states, which we verified using existing data from micro-dissected samples and spatial transcriptomics.