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DOI 10.1016/j.mcpro.2022.100218

Медицинская библиотека · Molecular & cellular proteomics : MCP · 2022

SP3-Enabled Rapid and High Coverage Chemoproteomic Identification of Cell-State-Dependent Redox-Sensitive Cysteines.

Desai Heta S, Yan Tianyang, Yu Fengchao, Sun Alexander W, Villanueva Miranda, Nesvizhskii Alexey I, Backus Keriann M

СтатьяПоддержка исследования: вне правительства СШАПоддержка NIH: внешняя программаПеревод пока не подготовлен

Аннотация

Proteinaceous cysteine residues act as privileged sensors of oxidative stress. As reactive oxygen and nitrogen species have been implicated in numerous pathophysiological processes, deciphering which cysteines are sensitive to oxidative modification and the specific nature of these modifications is essential to understanding protein and cellular function in health and disease. While established mass spectrometry-based proteomic platforms have improved our understanding of the redox proteome, the widespread adoption of these methods is often hindered by complex sample preparation workflows, prohibitive cost of isotopic labeling reagents, and requirements for custom data analysis workflows. Here, we present the SP3-Rox redox proteomics method that combines tailored low cost isotopically labeled capture reagents with SP3 sample cleanup to achieve high throughput and high coverage proteome-wide identification of redox-sensitive cysteines. By implementing a customized workflow in the free FragPipe computational pipeline, we achieve accurate MS1-based quantitation, including for peptides containing multiple cysteine residues. Application of the SP3-Rox method to cellular proteomes identified cysteines sensitive to the oxidative stressor GSNO and cysteine oxidation state changes that occur during T cell activation.

Для цитирования: Desai Heta S, Yan Tianyang, Yu Fengchao, Sun Alexander W, Villanueva Miranda, Nesvizhskii Alexey I, Backus Keriann M. SP3-Enabled Rapid and High Coverage Chemoproteomic Identification of Cell-State-Dependent Redox-Sensitive Cysteines.. Molecular & cellular proteomics : MCP. 2022. DOI: 10.1016/j.mcpro.2022.100218.

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