Identification and quantification of protein nitration sites in human coronary artery smooth muscle cells in the absence and presence of peroxynitrous acid/peroxynitrite

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Peroxynitrous acid/peroxynitrite (ONOOH/ONOO) is a powerful oxidizing/nitrating system formed at sites of inflammation, which can modify biological targets, and particularly proteins. Here, we show that multiple proteins from primary human coronary artery smooth muscle cells are nitrated, with LC-MS peptide mass mapping providing data on the sites and extents of changes on cellular and extracellular matrix (ECM) proteins. Evidence is presented for selective and specific nitrations at Tyr and Trp on 11 cellular proteins (out of 3668, including 205 ECM species) in the absence of added reagent ONOOH/ONOO, with this being consistent with low-level endogenous nitration. A number of these have key roles in cell signaling/sensing and protein turnover. With added ONOOH/ONOO, more proteins were modified (84 total; with 129 nitrated Tyr and 23 nitrated Trp, with multiple modifications on some proteins), with this occurring at the same and additional sites to endogenous modification. With low concentrations of ONOOH/ONOO (50 μM) nitration occurs on specific proteins at particular sites, and is not driven by protein or Tyr/Trp abundance, with modifications detected on some low abundance proteins. However, with higher ONOOH/ONOO concentrations (500 μM), modification is primarily driven by protein abundance. ECM species are major targets and over-represented in the pool of modified proteins, with fibronectin and thrombospondin-1 being particularly heavily modified (12 sites in each case). Both endogenous and exogenous nitration of cell- and ECM-derived species may have significant effects on cell and protein function, and potentially be involved in the development and exacerbation of diseases such as atherosclerosis.

OriginalsprogEngelsk
Artikelnummer102799
TidsskriftRedox Biology
Vol/bind64
Antal sider13
ISSN2213-2317
DOI
StatusUdgivet - 2023

Bibliografisk note

Funding Information:
This work was supported by the Novo Nordisk Foundation (Laureate Research Grants: NNF13OC0004294 and NNF20SA0064214 to MJD) and the China Scholarship Council (PhD scholarship 201806270237 to Shuqi Xu). We thank Xiuxiu Qin and Dr. Lasse G. Lorentzen for valuable scientific discussions and advice on the data analysis and visualization.

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© 2023 The Authors

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