Ferroptosis is an iron-dependent form of regulated cell death linking iron, lipid, and glutathione levels to degenerative processes and tumor suppression. By performing a genome-wide activation screen, we identified a cohort of genes antagonizing ferroptotic cell death, including GTP cyclohydrolase-1 (GCH1) and its metabolic derivatives tetrahydrobiopterin/dihydrobiopterin (BH4/BH2). Synthesis of BH4/BH2 by GCH1-expressing cells caused lipid remodeling, suppressing ferroptosis by selectively preventing depletion of phospholipids with two polyunsaturated fatty acyl tails. GCH1 expression level in cancer cell lines stratified susceptibility to ferroptosis, in accordance with its expression in human tumor samples. The GCH1-BH4-phospholipid axis acts as a master regulator of ferroptosis resistance, controlling endogenous production of the antioxidant BH4, abundance of CoQ10, and peroxidation of unusual phospholipids with two polyunsaturated fatty acyl tails. This demonstrates a unique mechanism of ferroptosis protection that is independent of the GPX4/glutathione system.

SUMMARY Complement dysregulation is a feature of many retinal diseases, yet mechanistic understanding at the cellular level is limited. Given this knowledge gap about which retinal cells express complement, we performed single-cell RNA sequencing on ~92,000 mouse retinal cells and validated our results in five major purified retinal cell types. We found evidence for a distributed cell-type-specific complement expression across 11 cell types. Notably, Müller cells are the major contributor of complement activators c1s, c3, c4, and cfb. Retinal pigment epithelium (RPE) mainly expresses cfh and the terminal complement components, whereas cfi and cfp transcripts are most abundant in neurons. Aging enhances c1s, cfb, cfp, and cfi expression, while cfh expression decreases. Transient retinal ischemia increases complement expression in microglia, Müller cells, and RPE. In summary, we report a unique complement expression signature for murine retinal cell types suggesting a well-orchestrated regulation of local complement expression in the retinal microenvironment.

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Lung fibrosis is characterized by excessive deposition of extracellular matrix (ECM), in particular collagens, by fibroblasts in the interstitium. Transforming growth factor-β1 (TGF-β1) alters the expression of many extracellular matrix (ECM) components produced by fibroblasts, but such changes in ECM composition as well as modulation of collagen post-translational modification (PTM) levels have not been comprehensively investigated. Here, we performed mass spectrometry (MS)-based proteomics analyses to assess changes in the ECM deposited by cultured lung fibroblasts from idiopathic pulmonary fibrosis (IPF) patients upon stimulation with transforming growth factor β1 (TGF-β1). In addition to the ECM changes commonly associated with lung fibrosis, MS-based label-free quantification revealed profound effects on enzymes involved in ECM crosslinking and turnover as well as multiple positive and negative feedback mechanisms of TGF-β1 signaling. Notably, the ECM changes observed in this in vitro model correlated significantly with ECM changes observed in patient samples. Because collagens are subject to multiple PTMs with major implications in disease, we implemented a new bioinformatic platform to analyze MS data that allows for the comprehensive mapping and site-specific quantitation of collagen PTMs in crude ECM preparations. These analyses yielded a comprehensive map of prolyl and lysyl hydroxylations as well as lysyl glycosylations for 15 collagen chains. In addition, site-specific PTM analysis revealed novel sites of prolyl-3-hydroxylation and lysyl glycosylation in type I collagen. Interestingly, the results show, for the first time, that TGF-β1 can modulate prolyl-3-hydroxylation and glycosylation in a site-specific manner. Taken together, this proof of concept study not only reveals unanticipated TGF-β1 mediated regulation of collagen PTMs and other ECM components but also lays the foundation for dissecting their key roles in health and disease. The proteomic data has been deposited to the ProteomeXchange Consortium via the MassIVE partner repository with the data set identifier MSV000082958.