The DOI matches its Crossref record; 8 of the 8 references it cites were found in a registry or an index.
Evaluation of HCD- and CID-type Fragmentation Within Their Respective Detection Platforms For Murine Phosphoproteomics
Open accessAbstract
Protein phosphorylation modulates a myriad of biological functions, and its regulation is vital for proper cellular activity. Mass spectrometry is the enabling tool for phosphopeptide analysis, where recent instrumentation advances in both speed and sensitivity in linear ion trap and orbitrap technologies may yield more comprehensive phosphoproteomic analyses in less time. Protein phosphorylation analysis by MS relies on structural information derived through controlled peptide fragmentation. Compared with traditional, ion-trap-based collision-induced dissociation (CID), a more recent type of fragmentation termed HCD (higher energy collisional dissociation) provides beam type CID tandem MS with detection of fragment ions at high resolution in the orbitrap mass analyzer. Here we compared HCD to traditional CID for large-scale phosphorylation analyses of murine brain under three separate experimental conditions. These included a same-precursor analysis where CID and HCD scans were performed back-to-back, separate analyses of a phosphotyrosine peptide immunoprecipitation experiment, and separate whole phosphoproteome analyses. HCD generally provided higher search engine scores with more peptides identified, thus out-performing CID for back-to-back experiments for most metrics tested. However, for phosphotyrosine IPs and in a full phosphoproteome study of mouse brain, the greater acquisition speed of CID-only analyses provided larger data sets. We reconciled our results with those in direct contradiction from Nagaraj N, D'Souza RCJ et al. (J. Proteome Res. 9:6786, 2010). We conclude, for large-scale phosphoproteomics, CID fragmentation with rapid detection in the ion trap still produced substantially richer data sets, but the back-to-back experiments demonstrated the promise of HCD and orbitrap detection for the future.
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Cites
Elias, J. E., & Gygi, S. P. (2007) · Nature Methods · doi:10.1038/nmeth1019 · Cited by 3,925
Self-citationPeptide and protein sequence analysis by electron transfer dissociation mass spectrometry
Syka, J. E. P., Coon, J. J., Schroeder, M. J., Shabanowitz, J., & Hunt, D. F. (2004) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0402700101 · Cited by 2,370
The molecular basis of CaMKII function in synaptic and behavioural memory
Lisman, J., Schulman, H., & Cline, H. (2002) · Nature Reviews Neuroscience · doi:10.1038/nrn753 · Cited by 1,860
Beausoleil, S. A., Villén, J., Gerber, S. A., Rush, J., & Gygi, S. P. (2006) · Nature Biotechnology · doi:10.1038/nbt1240 · Cited by 1,577
Self-citationMichalski, A., Damoc, E., Hauschild, J.-P., Lange, O., Wieghaus, A., Makarov, A., Nagaraj, N., Cox, J., Mann, M., & Horning, S. (2011) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m111.011015 · Cited by 832
Large-scale phosphorylation analysis of mouse liver
Villén, J., Beausoleil, S. A., Gerber, S. A., & Gygi, S. P. (2007) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0609836104 · Cited by 730
Self-citationA dual pressure linear ion trap orbitrap instrument with very high sequencing speed
Olsen, J. V., Schwartz, J. C., Griep-Raming, J., Nielsen, M. L., Damoc, E., Denisov, E., Lange, O., Remes, P., Taylor, D., Splendore, M., et al. (2009) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m900375-mcp200 · Cited by 464
Quantitative Analysis of Synaptic Phosphorylation and Protein Expression
Trinidad, J. C., Thalhammer, A., Specht, C. G., Lynn, A. J., Baker, P. R., Schoepfer, R., & Burlingame, A. L. (2008) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m700170-mcp200 · Cited by 194
Cited by
Protein Analysis by Shotgun/Bottom-up Proteomics
Zhang, Y., Fonslow, B. R., Shan, B., Baek, M.-C., & Yates, J. R. (2013) · Chemical Reviews · doi:10.1021/cr3003533 · Cited by 1,491
Toward a comprehensive characterization of a human cancer cell phosphoproteome
Zhou, H., Di Palma, S., Preisinger, C., Peng, M., Polat, A. N., Heck, A. J. R., & Mohammed, S. (2013) · Journal of Proteome Research · doi:10.1021/pr300630k · Cited by 438
Quantitative maps of protein phosphorylation sites across 14 different rat organs and tissues
Lundby, A., Secher, A., Lage, K., Nordsborg, N. B., Dmytriyev, A., Lundby, C., & Olsen, J. V. (2012) · Nature Communications · doi:10.1038/ncomms1871 · Cited by 343
Mass Spectrometry-Based Detection and Assignment of Protein Posttranslational Modifications
Doll, S., & Burlingame, A. L. (2015) · ACS Chemical Biology · doi:10.1021/cb500904b · Cited by 261
Fert-Bober, J., Murray, C. I., Parker, S. J., & Van Eyk, J. E. (2018) · Circulation Research · doi:10.1161/circresaha.118.310966 · Cited by 45
Metadata
- Authors
- Jedrychowski, M. P., Huttlin, E. L., Haas, W., Sowa, M. E., Rad, R., & Gygi, S. P.
- Venue
- Molecular & Cellular Proteomics
- Publisher
- Elsevier BV
- Published
- 2011-12
- Volume
- 10
- Issue
- 12
- Pages
- M111.009910
- ISSN
- 1535-9476 (ISSN-L)
- OpenAlex
- W2117903500
- Cited by
- 189
- References
- 8
- FWCI
- 8.62
- Type
- journal article
- Language
- en
- Open access
- hybrid
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- Jedrychowski, M. P., Huttlin, E. L., Haas, W., Sowa, M. E., Rad, R., & Gygi, S. P. (2011). Evaluation of HCD- and CID-type Fragmentation Within Their Respective Detection Platforms For Murine Phosphoproteomics. Molecular & Cellular Proteomics. https://doi.org/10.1074/mcp.m111.009910
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