Stochiometric quantification of the thiol redox proteome of macrophages reveals subcellular compartmentalization and susceptibility to oxidative perturbations

巨噬细胞硫醇氧化还原蛋白质组的化学计量定量分析揭示了其亚细胞区室化及其对氧化扰动的敏感性

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Abstract

Posttranslational modifications of protein cysteine thiols play a significant role in redox regulation and the pathogenesis of human diseases. Herein, we report the characterization of the cellular redox landscape in terms of quantitative, site-specific occupancies of both S-glutathionylation (SSG) and total reversible thiol oxidation (total oxidation) in RAW 264.7 macrophage cells under basal conditions. The occupancies of thiol modifications for ~4000 cysteine sites were quantified, revealing a mean site occupancy of 4.0% for SSG and 11.9% for total oxidation, respectively. Correlations between site occupancies and structural features such as pKa, relative residue surface accessibility, and hydrophobicity were observed. Proteome-wide site occupancy analysis revealed that the average occupancies of SSG and total oxidation in specific cellular compartments correlate well with the expected redox potentials of respective organelles in macrophages, consistent with the notion of redox compartmentalization. The lowest average occupancies were observed in more reducing organelles such as the mitochondria (non-membrane) and nucleus, while the highest average occupancies were found in more oxidizing organelles such as endoplasmic reticulum (ER) and lysosome. Furthermore, a pattern of subcellular susceptibility to redox changes was observed under oxidative stress induced by exposure to engineered metal oxide nanoparticles. Peroxisome, ER, and mitochondria (membrane) are the organelles which exhibit the most significant redox changes; while mitochondria (non-membrane) and Golgi were observed as the organelles being most resistant to oxidative stress. Finally, it was observed that Cys residues at enzymatic active sites generally had a higher level of occupancy compared to non-active Cys residues within the same proteins, suggesting site occupancy as a potential indicator of protein functional sites. The raw data are available via ProteomeXchange with identifier PXD019913.

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