ABSTRACT
Protein disulfide isomerases (PDIs) function in forming the correct disulfide bonds in client proteins, thereby aiding the folding of proteins that enter the secretory pathway. Recently, several PDIs have been identified as targets of organic electrophiles, yet the client proteins of specific PDIs remain largely undefined. Here, we report that PDIs expressed in Saccharomyces cerevisiae are targets of divinyl sulfone (DVSF) and other thiol-reactive protein cross-linkers. Using DVSF, we identified the interaction partners that were cross-linked to Pdi1 and Eug1, finding that both proteins form cross-linked complexes with other PDIs, as well as vacuolar hydrolases, proteins involved in cell wall biosynthesis and maintenance, and many ER proteostasis factors involved ER stress signaling and ER-associated protein degradation (ERAD). The latter discovery prompted us to examine the effects of DVSF on ER quality control, where we found that DVSF inhibits the degradation of the ERAD substrate CPY*, in addition to covalently modifying Ire1 and blocking the activation of the unfolded protein response. Our results reveal that DVSF targets many proteins within the ER proteostasis network and suggest that these proteins may be suitable targets for covalent therapeutic development in the future.
Subject(s)
Cross-Linking Reagents/metabolism , Protein Disulfide-Isomerases/metabolism , Saccharomyces cerevisiae/enzymology , Sulfhydryl Compounds/metabolism , Cross-Linking Reagents/chemistry , Endoplasmic Reticulum/drug effects , Endoplasmic Reticulum/metabolism , Molecular Structure , Protein Disulfide-Isomerases/antagonists & inhibitors , Protein Disulfide-Isomerases/chemistry , Proteolysis/drug effects , Proteostasis/drug effects , Sulfhydryl Compounds/chemistry , Sulfones/pharmacologyABSTRACT
The kidney is composed of heterogeneous groups of epithelial, endothelial, immune, and stromal cells, all in close anatomic proximity. Spatial transcriptomic technologies allow the interrogation of in situ expression signatures in health and disease, overlaid upon a histologic image. However, some spatial gene expression platforms have not yet reached single-cell resolution. As such, deconvolution of spatial transcriptomic spots is important to understand the proportion of cell signature arising from these varied cell types in each spot. This article reviews the various deconvolution strategies discussed in the 2021 Indiana O'Brien Center for Microscopy workshop. The unique features of Seurat transfer score methodology, SPOTlight, Robust Cell Type Decomposition, and BayesSpace are reviewed. The application of normalization and batch effect correction across spatial transcriptomic samples is also discussed.
