The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Shotgun Glycopeptide Capture Approach Coupled with Mass Spectrometry for Comprehensive Glycoproteomics
Open accessAbstract
We present a robust and general shotgun glycoproteomics approach to comprehensively profile glycoproteins in complex biological mixtures. In this approach, glycopeptides derived from glycoproteins are enriched by selective capture onto a solid support using hydrazide chemistry followed by enzymatic release of the peptides and subsequent analysis by tandem mass spectrometry. The approach was validated using standard protein mixtures that resulted in a close to 100% capture efficiency. Our capture approach was then applied to microsomal fractions of the cisplatin-resistant ovarian cancer cell line IGROV-1/CP. With a Protein Prophet probability value greater than 0.9, we identified a total of 302 proteins with an average protein identification rate of 136 +/- 19 (n = 4) in a single linear quadrupole ion trap (LTQ) mass spectrometer nano-LC-MS experiment and a selectivity of 91 +/- 1.6% (n = 4) for the N-linked glycoconsensus sequence. Our method has several advantages. 1) Digestion of proteins initially into peptides improves the solubility of large membrane proteins and exposes all of the glycosylation sites to ensure equal accessibility to capture reagents. 2) Capturing glycosylated peptides can effectively reduce sample complexity and at the same time increase the confidence of MS-based protein identifications (more potential peptide identifications per protein). 3) The utility of sodium sulfite as a quencher in our capture approach to replace the solid phase extraction step in an earlier glycoprotein chemical capture approach for removing excess sodium periodate allows the overall capture procedure to be completed in a single vessel. This improvement minimizes sample loss, increases sensitivity, and makes our protocol amenable for high throughput implementation, a feature that is essential for biomarker identification and validation of a large number of clinical samples. 4) The approach is demonstrated here on the analysis of N-linked glycopeptides; however, it can be applied equally well to O-glycoprotein analysis.
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
Anderson, N. L., & Anderson, N. G. (2002) · Molecular & Cellular Proteomics · doi:10.1074/mcp.r200007-mcp200 · Cited by 4,414
Intracellular Functions of N-Linked Glycans
Helenius, A., & Aebi, A. M. (2001) · Science · doi:10.1126/science.291.5512.2364 · Cited by 2,405
Systems Biology and New Technologies Enable Predictive and Preventative Medicine
Hood, L., Heath, J. R., Phelps, M. E., & Lin, B. (2004) · Science · doi:10.1126/science.1104635 · Cited by 1,108 · cited 1×
“biology and biomedical sciences (6, 7), the ability to efficiently”
Self-citation
Cited by
High-sensitivity Analytical Approaches for the Structural Characterization of Glycoproteins
Alley, W. R., Mann, B. F., & Novotny, M. V. (2013) · Chemical Reviews · doi:10.1021/cr3003714 · Cited by 310
Metadata
- Authors
- Sun, B., Ranish, J. A., Utleg, A. G., White, J. T., Yan, X., Lin, B., & Hood, L.
- Venue
- Molecular & Cellular Proteomics
- Publisher
- Elsevier BV
- Published
- 2007-01
- Volume
- 6
- Issue
- 1
- Pages
- 141-149
- ISSN
- 1535-9476 (ISSN-L)
- OpenAlex
- W2122244375
- Cited by
- 165
- References
- 3
- FWCI
- 5.28
- Type
- journal article
- Language
- en
- Open access
- hybrid
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: Shotgun Glycopeptide Capture Approach Coupled with Mass Spectrometry for Comprehensive Glycoproteomics. https://app.cochat.ai/papers/10.1074/mcp.t600046-mcp200
- The paper
- Sun, B., Ranish, J. A., Utleg, A. G., White, J. T., Yan, X., Lin, B., & Hood, L. (2007). Shotgun Glycopeptide Capture Approach Coupled with Mass Spectrometry for Comprehensive Glycoproteomics. Molecular & Cellular Proteomics. https://doi.org/10.1074/mcp.t600046-mcp200
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.