The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
Feasibility of Large-Scale Phosphoproteomics with Higher Energy Collisional Dissociation Fragmentation
Open accessAbstract
Mass spectrometry (MS)-based proteomics now enables the analysis of thousands of phosphorylation sites in single projects. Among a wide range of analytical approaches, the combination of high resolution MS scans in an Orbitrap analyzer with low resolution MS/MS scans in a linear ion trap has proven to be particularly successful ("high-low" strategy). Here we investigate if the improved sensitivity of higher energy collisional dissociation (HCD) on an LTQ-Orbitrap Velos instrument allows a "high-high" strategy. A high resolution MS scan was followed by up to 10 HCD MS/MS scans, and we achieved cycle times of about 3 s making the method compatible with chromatographic time scales. Fragment mass accuracy increased about 50-fold compared to the "high-low" strategy. Unexpectedly, the HCD approach mapped up to 16,000 total phosphorylation sites in one day's measuring time--the same or better than the standard high-low strategy. Reducing the target values from a standard of 30,000 to 5000 ions did not severely affect identification rates but did decrease identification and localization scores for phosphorylation sites. We conclude that HCD in the new configuration is now a viable method for large-scale phosphoproteome analysis alongside collisional induced dissociation, (CID) and electron capture/transfer dissociation (ECD/ETD).
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Cox, J., & Mann, M. (2008) · Nature Biotechnology · doi:10.1038/nbt.1511 · Cited by 14,855
Self-citationUniversal sample preparation method for proteome analysis
Wiśniewski, J. R., Zougman, A., Nagaraj, N., & Mann, M. (2009) · Nature Methods · doi:10.1038/nmeth.1322 · Cited by 8,352
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
A 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
Self-citation
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
Self-citationPhosphoproteomics in the Age of Rapid and Deep Proteome Profiling
Riley, N. M., & Coon, J. J. (2016) · Analytical Chemistry · doi:10.1021/acs.analchem.5b04123 · Cited by 265
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
Metadata
- Authors
- Nagaraj, N., D’Souza, R. C. J., Cox, J., Olsen, J. V., & Mann, M.
- Venue
- Journal of Proteome Research
- Publisher
- American Chemical Society (ACS)
- Published
- 2010-10-26
- Volume
- 9
- Issue
- 12
- Pages
- 6786-6794
- ISSN
- 1535-3893 (ISSN-L)
- 1535-3907
- OpenAlex
- W2018247248
- Cited by
- 163
- References
- 4
- FWCI
- 10.64
- Type
- journal article
- Language
- en
- Open access
- green
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Feasibility of Large-Scale Phosphoproteomics with Higher Energy Collisional Dissociation Fragmentation. https://app.cochat.ai/papers/10.1021/pr100637q
- The paper
- Nagaraj, N., D’Souza, R. C. J., Cox, J., Olsen, J. V., & Mann, M. (2010). Feasibility of Large-Scale Phosphoproteomics with Higher Energy Collisional Dissociation Fragmentation. Journal of Proteome Research. https://doi.org/10.1021/pr100637q
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.