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TMT Labeling for the Masses: A Robust and Cost-efficient, In-solution Labeling Approach
Open accessAbstract
Isobaric stable isotope labeling using, for example, tandem mass tags (TMTs) is increasingly being applied for large-scale proteomic studies. Experiments focusing on proteoform analysis in drug time course or perturbation studies or in large patient cohorts greatly benefit from the reproducible quantification of single peptides across samples. However, such studies often require labeling of hundreds of micrograms of peptides such that the cost for labeling reagents represents a major contribution to the overall cost of an experiment. Here, we describe and evaluate a robust and cost-effective protocol for TMT labeling that reduces the quantity of required labeling reagent by a factor of eight and achieves complete labeling. Under- and overlabeling of peptides derived from complex digests of tissues and cell lines were systematically evaluated using peptide quantities of between 12.5 and 800 μg and TMT-to-peptide ratios (wt/wt) ranging from 8:1 to 1:2 at different TMT and peptide concentrations. When reaction volumes were reduced to maintain TMT and peptide concentrations of at least 10 mm and 2 g/l, respectively, TMT-to-peptide ratios as low as 1:1 (wt/wt) resulted in labeling efficiencies of > 99% and excellent intra- and interlaboratory reproducibility. The utility of the optimized protocol was further demonstrated in a deep-scale proteome and phosphoproteome analysis of patient-derived xenograft tumor tissue benchmarked against the labeling procedure recommended by the TMT vendor. Finally, we discuss the impact of labeling reaction parameters for N-hydroxysuccinimide ester-based chemistry and provide guidance on adopting efficient labeling protocols for different peptide quantities.
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Andromeda: A Peptide Search Engine Integrated into the MaxQuant Environment
Cox, J., Neuhauser, N., Michalski, A., Scheltema, R. A., Olsen, J. V., & Mann, M. (2011) · Journal of Proteome Research · doi:10.1021/pr101065j · Cited by 5,500
The MaxQuant computational platform for mass spectrometry-based shotgun proteomics
Tyanova, S., Temu, T., & Cox, J. (2016) · Nature Protocols · doi:10.1038/nprot.2016.136 · Cited by 4,797
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: 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
Li, S., Shen, D., Shao, J., Crowder, R., Liu, W., Prat, A., He, X., Liu, S., Hoog, J., Lu, C., et al. (2013) · Cell Reports · doi:10.1016/j.celrep.2013.08.022 · Cited by 626
A summary of the measured p K values of the ionizable groups in folded proteins
Grimsley, G. R., Scholtz, J. M., & Pace, C. N. (2009) · Protein Science · doi:10.1002/pro.19 · Cited by 528
Mertins, P., Tang, L. C., Krug, K., Clark, D. J., Gritsenko, M. A., Chen, L., Clauser, K. R., Clauss, T. R., Shah, P., Gillette, M. A., et al. (2018) · Nature Protocols · doi:10.1038/s41596-018-0006-9 · Cited by 479
Self-citationEnglander, S. W., Downer, N. W., & Teitelbaum, H. (1972) · Annual Review of Biochemistry · doi:10.1146/annurev.bi.41.070172.004351 · Cited by 435
Navarrete-Perea, J., Yu, Q., Gygi, S. P., & Paulo, J. A. (2018) · Journal of Proteome Research · doi:10.1021/acs.jproteome.8b00217 · Cited by 339
Chemical cross‐linking with NHS esters: a systematic study on amino acid reactivities
Mädler, S., Bich, C., Touboul, D., & Zenobi, R. (2009) · Journal of Mass Spectrometry · doi:10.1002/jms.1544 · Cited by 305
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Metadata
- Authors
- Zecha, J., Satpathy, S., Kanashova, T., Avanessian, S. C., Kane, M. H., Clauser, K. R., Mertins, P., Carr, S. A., & Kuster, B.
- Venue
- Molecular & Cellular Proteomics
- Publisher
- Elsevier BV
- Published
- 2019-07
- Volume
- 18
- Issue
- 7
- Pages
- 1468-1478
- ISSN
- 1535-9476 (ISSN-L)
- OpenAlex
- W2937573806
- Cited by
- 403
- References
- 24
- FWCI
- 15.47
- Type
- journal article
- Language
- en
- Open access
- hybrid
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- Zecha, J., Satpathy, S., Kanashova, T., Avanessian, S. C., Kane, M. H., Clauser, K. R., Mertins, P., Carr, S. A., & Kuster, B. (2019). TMT Labeling for the Masses: A Robust and Cost-efficient, In-solution Labeling Approach. Molecular & Cellular Proteomics. https://doi.org/10.1074/mcp.tir119.001385
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