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Jiang X, Yeung D, Liu Y, Spicer V, Afshari H, Lao Y, Lin F, Krokhin O, Zahedi RP. Accelerating Proteomics Using Broad Specificity Proteases. J Proteome Res 2024; 23:1360-1369. [PMID: 38457694 DOI: 10.1021/acs.jproteome.3c00852] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/10/2024]
Abstract
Trypsin is the gold-standard protease in bottom-up proteomics, but many sequence stretches of the proteome are inaccessible to trypsin and standard LC-MS approaches. Thus, multienzyme strategies are used to maximize sequence coverage in post-translational modification profiling. We present fast and robust SP3- and STRAP-based protocols for the broad-specificity proteases subtilisin, proteinase K, and thermolysin. All three enzymes are remarkably fast, producing near-complete digests in 1-5 min, and cost 200-1000× less than proteomics-grade trypsin. Using FragPipe resolved a major challenge by drastically reducing the duration of the required "unspecific" searches. In-depth analyses of proteinase K, subtilisin, and thermolysin Jurkat digests identified 7374, 8178, and 8753 unique proteins with average sequence coverages of 21, 29, and 37%, including 10,000s of amino acids not reported in PeptideAtlas' >2400 experiments. While we could not identify distinct cleavage patterns, machine learning could distinguish true protease products from random cleavages, potentially enabling the prediction of cleavage products. Finally, proteinase K, subtilisin, and thermolysin enabled label-free quantitation of 3111, 3659, and 4196 unique Jurkat proteins, which in our hands is comparable to trypsin. Our data demonstrate that broad-specificity proteases enable quantitative proteomics of uncharted areas of the proteome. Their fast kinetics may allow "on-the-fly" digestion of samples in the future.
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Affiliation(s)
- Xuehui Jiang
- Manitoba Centre for Proteomics and Systems Biology, Health Science Centre, Winnipeg, Manitoba R3E 3P4, Canada
| | - Darien Yeung
- Manitoba Centre for Proteomics and Systems Biology, Health Science Centre, Winnipeg, Manitoba R3E 3P4, Canada
- Department of Biochemistry and Medical Genetics, University of Manitoba, Winnipeg, Manitoba R3E 0J9, Canada
| | - Yang Liu
- Department of Physics and Astronomy, University of Manitoba, Winnipeg, Manitoba R3T 2N2, Canada
| | - Victor Spicer
- Manitoba Centre for Proteomics and Systems Biology, Health Science Centre, Winnipeg, Manitoba R3E 3P4, Canada
| | - Havva Afshari
- Manitoba Centre for Proteomics and Systems Biology, Health Science Centre, Winnipeg, Manitoba R3E 3P4, Canada
- Department of Biochemistry and Medical Genetics, University of Manitoba, Winnipeg, Manitoba R3E 0J9, Canada
| | - Ying Lao
- Manitoba Centre for Proteomics and Systems Biology, Health Science Centre, Winnipeg, Manitoba R3E 3P4, Canada
| | - Francis Lin
- Department of Physics and Astronomy, University of Manitoba, Winnipeg, Manitoba R3T 2N2, Canada
| | - Oleg Krokhin
- Manitoba Centre for Proteomics and Systems Biology, Health Science Centre, Winnipeg, Manitoba R3E 3P4, Canada
- Department of Biochemistry and Medical Genetics, University of Manitoba, Winnipeg, Manitoba R3E 0J9, Canada
- Department of Internal Medicine, University of Manitoba, Winnipeg, Manitoba R3A 1R9, Canada
| | - René P Zahedi
- Manitoba Centre for Proteomics and Systems Biology, Health Science Centre, Winnipeg, Manitoba R3E 3P4, Canada
- Department of Biochemistry and Medical Genetics, University of Manitoba, Winnipeg, Manitoba R3E 0J9, Canada
- Department of Internal Medicine, University of Manitoba, Winnipeg, Manitoba R3A 1R9, Canada
- Paul Albrechtsen Research Institute, Cancer Care Manitoba, Winnipeg, Manitoba R3E 0 V9, Canada
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