The DOI matches its Crossref record; 41 of the 41 references it cites were found in a registry or an index.
Systematic Comparison of Label-Free, Metabolic Labeling, and Isobaric Chemical Labeling for Quantitative Proteomics on LTQ Orbitrap Velos
Abstract
A variety of quantitative proteomics methods have been developed, including label-free, metabolic labeling, and isobaric chemical labeling using iTRAQ or TMT. Here, these methods were compared in terms of the depth of proteome coverage, quantification accuracy, precision, and reproducibility using a high-performance hybrid mass spectrometer, LTQ Orbitrap Velos. Our results show that (1) the spectral counting method provides the deepest proteome coverage for identification, but its quantification performance is worse than labeling-based approaches, especially the quantification reproducibility; (2) metabolic labeling and isobaric chemical labeling are capable of accurate, precise, and reproducible quantification and provide deep proteome coverage for quantification; isobaric chemical labeling surpasses metabolic labeling in terms of quantification precision and reproducibility; and (3) iTRAQ and TMT perform similarly in all aspects compared in the current study using a CID-HCD dual scan configuration. On the basis of the unique advantages of each method, we provide guidance for selection of the appropriate method for a quantitative proteomics study.
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
High resolution two-dimensional electrophoresis of proteins.
O'Farrell, P. (1975) · Journal of Biological Chemistry · doi:10.1016/s0021-9258(19)41496-8 · Cited by 19,246
Eng, J. K., McCormack, A. L., & Yates, J. R. (1994) · Journal of the American Society for Mass Spectrometry · doi:10.1016/1044-0305(94)80016-2 · Cited by 6,484
Ong, S.-E., Blagoev, B., Kratchmarova, I., Kristensen, D. B., Steen, H., Pandey, A., & Mann, M. (2002) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m200025-mcp200 · Cited by 5,574
Large-scale analysis of the yeast proteome by multidimensional protein identification technology
Washburn, M. P., Wolters, D., & Yates, J. R. (2001) · Nature Biotechnology · doi:10.1038/85686 · Cited by 4,752
Quantitative analysis of complex protein mixtures using isotope-coded affinity tags
Gygi, S. P., Rist, B., Gerber, S. A., Turecek, F., Gelb, M. H., & Aebersold, R. (1999) · Nature Biotechnology · doi:10.1038/13690 · Cited by 4,683
Ross, P. L., Huang, Y. N., Marchese, J. N., Williamson, B., Parker, K., Hattan, S., Khainovski, N., Pillai, S., Dey, S., Daniels, S., et al. (2004) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m400129-mcp200 · Cited by 4,401
Thompson, A., Schäfer, J., Kuhn, K., Kienle, S., Schwarz, J., Schmidt, G., Neumann, T., & Hamon, C. (2003) · Analytical Chemistry · doi:10.1021/ac0262560 · Cited by 2,378
Quantitative mass spectrometry in proteomics: a critical review
Bantscheff, M., Schirle, M., Sweetman, G., Rick, J., & Kuster, B. (2007) · Analytical and Bioanalytical Chemistry · doi:10.1007/s00216-007-1486-6 · Cited by 1,669
Peng, J., Elias, J. E., Thoreen, C. C., Licklider, L. J., & Gygi, S. P. (2003) · Journal of Proteome Research · doi:10.1021/pr025556v · Cited by 1,647
Mass spectrometry–based proteomics turns quantitative
Ong, S.-E., & Mann, M. (2005) · Nature Chemical Biology · doi:10.1038/nchembio736 · Cited by 1,572
Tabb, D. L., McDonald, W. H., & Yates, J. R. (2002) · Journal of Proteome Research · doi:10.1021/pr015504q · Cited by 1,367
Evaluation of two-dimensional gel electrophoresis-based proteome analysis technology
Gygi, S. P., Corthals, G. L., Zhang, Y., Rochon, Y., & Aebersold, R. (2000) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.160270797 · Cited by 1,319
Comparison of Label-free Methods for Quantifying Human Proteins by Shotgun Proteomics
Old, W. M., Meyer-Arendt, K., Aveline-Wolf, L., Pierce, K. G., Mendoza, A., Sevinsky, J. R., Resing, K. A., & Ahn, N. G. (2005) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m500084-mcp200 · Cited by 1,206
Statistical Analysis of Membrane Proteome Expression Changes in Saccharomyces cerevisiae
Zybailov, B., Mosley, A. L., Sardiu, M. E., Coleman, M. K., Florens, L., & Washburn, M. P. (2006) · Journal of Proteome Research · doi:10.1021/pr060161n · Cited by 1,029
Automated approach for quantitative analysis of complex peptide mixtures from tandem mass spectra
Venable, J. D., Dong, M.-Q., Wohlschlegel, J., Dillin, A., & Yates, J. R. (2004) · Nature Methods · doi:10.1038/nmeth705 · Cited by 794
Proteolytic 18O Labeling for Comparative Proteomics: Model Studies with Two Serotypes of Adenovirus
Yao, X., Freas, A., Ramirez, J., Demirev, P. A., & Fenselau, C. (2001) · Analytical Chemistry · doi:10.1021/ac001404c · Cited by 759
Wang, W., Zhou, H., Lin, H., Roy, S., Shaler, T. A., Hill, L. R., Norton, S., Kumar, P., Anderle, M., & Becker, C. H. (2003) · Analytical Chemistry · doi:10.1021/ac026468x · Cited by 653
Dayon, L., Hainard, A., Licker, V., Turck, N., Kuhn, K., Hochstrasser, D. F., Burkhard, P. R., & Sanchez, J.-C. (2008) · Analytical Chemistry · doi:10.1021/ac702422x · Cited by 561
Shotgun metaproteomics of the human distal gut microbiota
Verberkmoes, N. C., Russell, A. L., Shah, M., Godzik, A., Rosenquist, M., Halfvarson, J., Lefsrud, M. G., Apajalahti, J., Tysk, C., Hettich, R. L., et al. (2009) · The ISME Journal · doi:10.1038/ismej.2008.108 · Cited by 539
Self-citationAddressing Accuracy and Precision Issues in iTRAQ Quantitation
Karp, N. A., Huber, W., Sadowski, P. G., Charles, P. D., Hester, S. V., & Lilley, K. S. (2010) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m900628-mcp200 · Cited by 495
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
Gan, C. S., Chong, P. K., Pham, T. K., & Wright, P. C. (2007) · Journal of Proteome Research · doi:10.1021/pr060474i · Cited by 404
Label-free, normalized quantification of complex mass spectrometry data for proteomic analysis
Griffin, N. M., Yu, J., Long, F., Oh, P., Shore, S., Li, Y., Koziol, J. A., & Schnitzer, J. E. (2010) · Nature Biotechnology · doi:10.1038/nbt.1592 · Cited by 402
A Comparison of Labeling and Label-Free Mass Spectrometry-Based Proteomics Approaches
Patel, V. J., Thalassinos, K., Slade, S. E., Connolly, J. B., Crombie, A., Murrell, J. C., & Scrivens, J. H. (2009) · Journal of Proteome Research · doi:10.1021/pr900080y · Cited by 258
Pichler, P., Köcher, T., Holzmann, J., Mazanek, M., Taus, T., Ammerer, G., & Mechtler, K. (2010) · Analytical Chemistry · doi:10.1021/ac100890k · Cited by 175
Köcher, T., Pichler, P., Schutzbier, M., Stingl, C., Kaul, A., Teucher, N., Hasenfuss, G. P., Penninger, J. M., & Mechtler, K. (2009) · Journal of Proteome Research · doi:10.1021/pr900451u · Cited by 156
iTRAQ Reagent-Based Quantitative Proteomic Analysis on a Linear Ion Trap Mass Spectrometer
Griffin, T. J., Xie, H., Bandhakavi, S., Popko, J., Mohan, A., Carlis, J. V., & Higgins, L. (2007) · Journal of Proteome Research · doi:10.1021/pr070291b · Cited by 152
Impact of Replicate Types on Proteomic Expression Analysis
Karp, N. A., Spencer, M., Lindsay, H. A., O'Dell, K., & Lilley, K. S. (2005) · Journal of Proteome Research · doi:10.1021/pr050084g · Cited by 147
Ow, S. Y., Cardona, T., Taton, A., Magnuson, A., Lindblad, P. C., Stensjö, K., & Wright, P. C. (2008) · Journal of Proteome Research · doi:10.1021/pr700604v · Cited by 127
Optimized orbitrap HCD for quantitative analysis of phosphopeptides
Zhang, Y., Ficarro, S. B., Li, S., & Marto, J. A. (2009) · Journal of the American Society for Mass Spectrometry · doi:10.1016/j.jasms.2009.03.019 · Cited by 105
XDIA: improving on the label-free data-independent analysis
Carvalho, P. C., Han, X., Xu, T., Cociorva, D., Carvalho, M. D. G., Barbosa, V. C., & Yates, J. R. (2010) · Bioinformatics · doi:10.1093/bioinformatics/btq031 · Cited by 97
Proteome‐wide systems analysis of a cellulosic biofuel‐producing microbe
Tolonen, A. C., Haas, W., Chilaka, A. C., Aach, J., Gygi, S. P., & Church, G. M. (2011) · Molecular Systems Biology · doi:10.1038/msb.2010.116 · Cited by 95
Pan, C., Kora, G. H., McDonald, W. H., Tabb, D. L., VerBerkmoes, N. C., Hurst, G. B., Pelletier, D. A., Samatova, N. F., & Hettich, R. L. (2006) · Analytical Chemistry · doi:10.1021/ac060654b · Cited by 94
Self-citationHendrickson, E. L., Xia, Q., Wang, T., Leigh, J. A., & Hackett, M. (2006) · The Analyst · doi:10.1039/b610957h · Cited by 91
Quantitative Tracking of Isotope Flows in Proteomes of Microbial Communities
Pan, C., Fischer, C. R., Hyatt, D., Bowen, B. P., Hettich, R. L., & Banfield, J. F. (2011) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m110.006049 · Cited by 84
Self-citationCollier, T. S., Sarkar, P., Franck, W. L., Rao, B. M., Dean, R. A., & Muddiman, D. C. (2010) · Analytical Chemistry · doi:10.1021/ac101978b · Cited by 84
Pan, C., Oda, Y., Lankford, P. K., Zhang, B., Samatova, N. F., Pelletier, D. A., Harwood, C. S., & Hettich, R. L. (2007) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m700147-mcp200 · Cited by 69
Self-citationProteomics reveals a core molecular response of Pseudomonas putida F1 to acute chromate challenge
Thompson, D. K., Chourey, K., Wickham, G. S., Thieman, S. B., VerBerkmoes, N. C., Zhang, B., McCarthy, A. T., Rudisill, M. A., Shah, M. B., & Hettich, R. L. (2010) · BMC Genomics · doi:10.1186/1471-2164-11-311 · Cited by 68
Self-citationDouble Standards in Quantitative Proteomics
Kolkman, A., Dirksen, E. H. C., Slijper, M., & Heck, A. (2005) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m400121-mcp200 · Cited by 64
Belnap, C. P., Pan, C., Denef, V. J., Samatova, N. F., Hettich, R. L., & Banfield, J. F. (2011) · The ISME Journal · doi:10.1038/ismej.2010.200 · Cited by 62
Self-citationAbraham, P. E., Adams, R. M., Giannone, R. J., Kalluri, U. C., Ranjan, P., Erickson, B. K., Shah, M. B., Tuskan, G. A., & Hettich, R. L. (2011) · Journal of Proteome Research · doi:10.1021/pr200851y · Cited by 34
Self-citation
Cited by
Quantitative mass spectrometry in proteomics: critical review update from 2007 to the present
Bantscheff, M., Lemeer, S., Savitski, M. M., & Kuster, B. (2012) · Analytical and Bioanalytical Chemistry · doi:10.1007/s00216-012-6203-4 · Cited by 801
A Quantitative Proteome Map of the Human Body
Jiang, L., Wang, M., Lin, S., Jian, R., Li, X., Chan, J., Dong, G., Fang, H., Robinson, A. E., Aguet, F., et al. (2020) · Cell · doi:10.1016/j.cell.2020.08.036 · Cited by 458
Macrophage-secreted granulin supports pancreatic cancer metastasis by inducing liver fibrosis
Nielsen, S. R., Quaranta, V., Linford, A., Emeagi, P., Rainer, C., Santos, A., Ireland, L., Sakai, T., Sakai, K., Kim, Y.-S., et al. (2016) · Nature Cell Biology · doi:10.1038/ncb3340 · Cited by 441
A Review on Quantitative Multiplexed Proteomics
Pappireddi, N., Martin, L., & Wühr, M. (2019) · ChemBioChem · doi:10.1002/cbic.201800650 · Cited by 299
Global quantitative analysis of the human brain proteome in Alzheimer’s and Parkinson’s Disease
Ping, L., Duong, D. M., Yin, L., Gearing, M., Lah, J. J., Levey, A. I., & Seyfried, N. T. (2018) · Scientific Data · doi:10.1038/sdata.2018.36 · Cited by 221
Metadata
- Authors
- Li, Z., Adams, R. M., Chourey, K., Hurst, G. B., Hettich, R. L., & Pan, C.
- Venue
- Journal of Proteome Research
- Publisher
- American Chemical Society (ACS)
- Published
- 2012-02-16
- Volume
- 11
- Issue
- 3
- Pages
- 1582-1590
- ISSN
- 1535-3893 (ISSN-L)
- 1535-3907
- OpenAlex
- W2063546126
- Cited by
- 302
- References
- 41
- FWCI
- 10.40
- 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.
