The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Mass Spectrometric Quantitation of Peptides and Proteins Using Stable Isotope Standards and Capture by Anti-Peptide Antibodies (SISCAPA)
Abstract
A method (denoted SISCAPA) for quantitation of peptides in complex digests is described. In the method, anti-peptide antibodies immobilized on 100 nanoliter nanoaffinity columns are used to enrich specific peptides along with spiked stable-isotope-labeled internal standards of the same sequence. Upon elution from the anti-peptide antibody supports, electrospray mass spectrometry is used to quantitate the peptides (natural and labeled). In a series of pilot experiments, tryptic test peptides were chosen for four proteins of human plasma (hemopexin, alpha1 antichymotrypsin, interleukin-6, and tumor necrosis factor-alpha) from a pool of 10,203 in silico tryptic peptide candidates representing 237 known plasma components. Rabbit polyclonal antibodies raised against the chosen peptide sequences were affinity purified and covalently immobilized on POROS supports. Binding and elution from these supports was shown to provide an average 120-fold enrichment of the antigen peptide relative to others, as measured by selected ion monitoring (SIM) or selected reaction monitoring (SRM) electrospray mass spectrometry. The columns could be recycled with little loss in binding capacity, and generated peptide ion current measurements with cycle-to-cycle coefficients of variation near 5%. Anti-peptide antibody enrichment will contribute to increased sensitivity of MS-based assays, particularly for lower abundance proteins in plasma, and may ultimately allow substitution of a rapid bind/elute process for the time-consuming reverse phase separation now used as a prelude to online MS peptide assays. The method appears suitable for rapid generation of assays for defined proteins, and should find application in the validation of diagnostic protein panels in large sample sets.
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
Self-citation
Cited by
Protein biomarker discovery and validation: the long and uncertain path to clinical utility
Rifai, N., Gillette, M. A., & Carr, S. A. (2006) · Nature Biotechnology · doi:10.1038/nbt1235 · Cited by 1,867
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
Selected reaction monitoring–based proteomics: workflows, potential, pitfalls and future directions
Picotti, P., & Aebersold, R. (2012) · Nature Methods · doi:10.1038/nmeth.2015 · Cited by 1,302
Quantitative mass spectrometric multiple reaction monitoring assays for major plasma proteins
Anderson, L., & Hunter, C. L. (2006) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m500331-mcp200 · Cited by 1,230
Addona, T. A., Abbatiello, S. E., Schilling, B., Skates, S. J., Mani, D. R., Bunk, D. M., Spiegelman, C. H., Zimmerman, L. J., Ham, A.-J. L., Keshishian, H., et al. (2009) · Nature Biotechnology · doi:10.1038/nbt.1546 · Cited by 1,037
Self-citationRevisiting biomarker discovery by plasma proteomics
Geyer, P. E., Holdt, L. M., Teupser, D., & Mann, M. (2017) · Molecular Systems Biology · doi:10.15252/msb.20156297 · Cited by 917
Quantitative, High-Resolution Proteomics for Data-Driven Systems Biology
Cox, J., & Mann, M. (2011) · Annual Review of Biochemistry · doi:10.1146/annurev-biochem-061308-093216 · Cited by 685
Aptamers from Cell-Based Selection for Bioanalytical Applications
Tan, W., Donovan, M. J., & Jiang, J. (2013) · Chemical Reviews · doi:10.1021/cr300468w · Cited by 649
The fundamental flaws of immunoassays and potential solutions using tandem mass spectrometry
Hoofnagle, A. N., & Wener, M. H. (2009) · Journal of Immunological Methods · doi:10.1016/j.jim.2009.06.003 · Cited by 561
Kuzyk, M. A., Smith, D., Yang, J., Cross, T. J., Jackson, A. M., Hardie, D. B., Anderson, N. L., & Borchers, C. H. (2009) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m800540-mcp200 · Cited by 515
Self-citationVidova, V., & Spacil, Z. (2017) · Analytica Chimica Acta · doi:10.1016/j.aca.2017.01.059 · Cited by 352
Human SRMAtlas: A Resource of Targeted Assays to Quantify the Complete Human Proteome
Kusebauch, U., Campbell, D. S., Deutsch, E. W., Chu, C. S., Spicer, D. A., Brusniak, M.-Y., Slagel, J., Sun, Z., Stevens, J., Grimes, B., et al. (2016) · Cell · doi:10.1016/j.cell.2016.06.041 · Cited by 310
Whiteaker, J. R., Zhao, L., Anderson, L., & Paulovich, A. G. (2010) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m900254-mcp200 · Cited by 323
Hoofnagle, A. N., Becker, J. O., Wener, M. H., & Heinecke, J. W. (2008) · Clinical Chemistry · doi:10.1373/clinchem.2008.109652 · Cited by 314
“We thereforetestedamethoddevelopedbyAndersonetal. ( 22 ), termed “stable isotope standards and capture by antipeptide antibodies,” that combines immunoaffinity peptide purification with tandem mass spectrometry.”
BackgroundBioanalytical Chemistry of Cytokines–a Review
Stenken, J. A., & Poschenrieder, A. J. (2015) · Analytica Chimica Acta · doi:10.1016/j.aca.2014.10.009 · Cited by 302
Keshishian, H., Addona, T., Burgess, M., Mani, D. R., Shi, X., Kuhn, E., Sabatine, M. S., Gerszten, R. E., & Carr, S. A. (2009) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m900140-mcp200 · Cited by 286
Abbatiello, S. E., Schilling, B., Mani, D. R., Zimmerman, L. J., Hall, S. C., MacLean, B., Albertolle, M., Allen, S., Burgess, M., Cusack, M. P., et al. (2015) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m114.047050 · Cited by 215
Clinical potential of mass spectrometry-based proteogenomics
Zhang, B., Whiteaker, J. R., Hoofnagle, A. N., Baird, G. S., Rodland, K. D., & Paulovich, A. G. (2019) · Nature Reviews Clinical Oncology · doi:10.1038/s41571-018-0135-7 · Cited by 210
Kennedy, J. J., Abbatiello, S. E., Kim, K., Yan, P., Whiteaker, J. R., Lin, C., Kim, J. S., Zhang, Y., Wang, X., Ivey, R. G., et al. (2014) · Nature Methods · doi:10.1038/nmeth.2763 · Cited by 184
Applications of targeted proteomics in systems biology and translational medicine
Ebhardt, H. A., Root, A., Sander, C., & Aebersold, R. (2015) · PROTEOMICS · doi:10.1002/pmic.201500004 · Cited by 184
Agger, S. A., Marney, L. C., & Hoofnagle, A. N. (2010) · Clinical Chemistry · doi:10.1373/clinchem.2010.152264 · Cited by 143
Neubert, H., Shuford, C. M., Olah, T. V., Garofolo, F., Schultz, G. A., Jones, B. R., Amaravadi, L., Laterza, O. F., Xu, K., & Ackermann, B. L. (2020) · Clinical Chemistry · doi:10.1093/clinchem/hvz022 · Cited by 109
Applications of MALDI Mass Spectrometry in Clinical Chemistry
Duncan, M. W., Nedelkov, D., Walsh, R., & Hattan, S. J. (2016) · Clinical Chemistry · doi:10.1373/clinchem.2015.239491 · Cited by 96
Simon, R., Girod, M., Fonbonne, C., Salvador, A., Clément, Y., Lantéri, P., Amouyel, P., Lambert, J. C., & Lemoine, J. (2012) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m112.018861 · Cited by 92
Carvalho, V. M. (2012) · Journal of Chromatography B · doi:10.1016/j.jchromb.2011.08.027 · Cited by 90
Identification of genetic variants influencing the human plasma proteome
Johansson, Å., Enroth, S., Palmblad, M., Deelder, A. M., Bergquist, J., & Gyllensten, U. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1217238110 · Cited by 82
Thyroglobulin measurement in the management of patients with differentiated thyroid cancer
Algeciras-Schimnich, A. (2018) · Critical Reviews in Clinical Laboratory Sciences · doi:10.1080/10408363.2018.1450830 · Cited by 63
Applications and challenges of forensic proteomics
Merkley, E. D., Wunschel, D. S., Wahl, K. L., & Jarman, K. H. (2019) · Forensic Science International · doi:10.1016/j.forsciint.2019.01.022 · Cited by 64
Björnson, E., Packard, C. J., Adiels, M., Andersson, L., Matikainen, N., Söderlund, S., Kahri, J., Sihlbom, C., Thorsell, A., Zhou, H., et al. (2019) · Journal of Internal Medicine · doi:10.1111/joim.12877 · Cited by 54
Trenchevska, O., Schaab, M. R., Nelson, R. W., & Nedelkov, D. (2015) · Methods · doi:10.1016/j.ymeth.2015.02.020 · Cited by 47
The continuing evolution of cardiac troponin I biomarker analysis: from protein to proteoform
Soetkamp, D., Raedschelders, K., Mastali, M., Sobhani, K., Bairey Merz, C. N., & Van Eyk, J. (2017) · Expert Review of Proteomics · doi:10.1080/14789450.2017.1387054 · Cited by 36
Proteins and Proteoforms: New Separation Challenges
Regnier, F. E., & Kim, J. (2018) · Analytical Chemistry · doi:10.1021/acs.analchem.7b05007 · Cited by 36
Quality requirements for quantitative clinical chemistry proteomics
(2014) · Translational Proteomics · doi:10.1016/j.trprot.2013.10.001 · Cited by 11
Froehlich, B. C., Popp, R., Sobsey, C. A., Ibrahim, S., LeBlanc, A. M., Mohammed, Y., Aguilar‐Mahecha, A., Poetz, O., Chen, M. X., Spatz, A., et al. (2020) · PROTEOMICS – Clinical Applications · doi:10.1002/prca.202000034 · Cited by 9
Metadata
- Authors
- Anderson, N. L., Anderson, N. G., Haines, L. R., Hardie, D. B., Olafson, R. W., & Pearson, T. W.
- Venue
- Journal of Proteome Research
- Publisher
- American Chemical Society (ACS)
- Published
- 2004-02-06
- Volume
- 3
- Issue
- 2
- Pages
- 235-244
- ISSN
- 1535-3893 (ISSN-L)
- 1535-3907
- OpenAlex
- W2035037428
- Cited by
- 804
- References
- 1
- FWCI
- 7.12
- Type
- journal article
- Language
- en
- Open access
- closed
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
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.