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The One Hour Yeast Proteome
Open accessAbstract
We describe the comprehensive analysis of the yeast proteome in just over one hour of optimized analysis. We achieve this expedited proteome characterization with improved sample preparation, chromatographic separations, and by using a new Orbitrap hybrid mass spectrometer equipped with a mass filter, a collision cell, a high-field Orbitrap analyzer, and, finally, a dual cell linear ion trap analyzer (Q-OT-qIT, Orbitrap Fusion). This system offers high MS(2) acquisition speed of 20 Hz and detects up to 19 peptide sequences within a single second of operation. Over a 1.3 h chromatographic method, the Q-OT-qIT hybrid collected an average of 13,447 MS(1) and 80,460 MS(2) scans (per run) to produce 43,400 (x) peptide spectral matches and 34,255 (x) peptides with unique amino acid sequences (1% false discovery rate (FDR)). On average, each one hour analysis achieved detection of 3,977 proteins (1% FDR). We conclude that further improvements in mass spectrometer scan rate could render comprehensive analysis of the human proteome within a few hours.
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“Currently, benchtop Orbitrap mass spectrometers are the most common instrument for proteomics as they bypass the need for cryogenic cooling (which is needed for the magnets of FTICR instruments) while still offering high-resolution and faster acquisition speeds [98,99].”
From Top-down proteomics: challenges, innovations, and applications in basic and clinical research (2020) · cites this paper as [99]
In the citing paper
“intact protein MS cannot match the analysis throughput typically obtainable through BUP (i.e., thousands of protein families identified in a single experiment).15”
From Proton Transfer Charge Reduction Enables High-Throughput Top-Down Analysis of Large Proteoforms (2019) · cites this paper as [15]
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Cites
Quantitative Monitoring of Gene Expression Patterns with a Complementary DNA Microarray
Schena, M., Shalon, D., Davis, R. W., & Brown, P. O. (1995) · Science · doi:10.1126/science.270.5235.467 · Cited by 9,609 · cited 1×
“Owing to cost, speed, and accessibility, transcriptomic analysis is often used as a proteomic proxy (3, 4).”
MethodUniversal 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
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
Exploring the metabolic and genetic control of gene expression on a genomic scale.
Derisi, J., Iyer, V., & Brown, P. (1997) · Science · doi:10.1126/science.278.5338.680 · Cited by 4,832
Large-scale analysis of the yeast proteome by multidimensional protein identification technology
Washburn, M. P., Wolters, D. A., & Yates, J. R. (2001) · Nature Biotechnology · doi:10.1038/85686 · Cited by 4,768
Correlation between Protein and mRNA Abundance in Yeast
Gygi, S. P., Rochon, Y., Franza, B. R., & Aebersold, R. (1999) · Molecular and Cellular Biology · doi:10.1128/mcb.19.3.1720 · Cited by 3,819
Global analysis of protein expression in yeast
Ghaemmaghami, S., Huh, W.-K., Bower, K., Howson, R. W., Belle, A., Dephoure, N., O'Shea, E. K., & Weissman, J. S. (2003) · Nature · doi:10.1038/nature02046 · Cited by 3,750
Direct analysis of protein complexes using mass spectrometry
Link, A. J., Eng, J. K., Schieltz, D. M., Carmack, E., Mize, G. J., Morris, D. R., Garvik, B. M., & Yates, J. R. (1999) · Nature Biotechnology · doi:10.1038/10890 · Cited by 2,218
Saccharomyces Genome Database: the genomics resource of budding yeast
Cherry, J., Hong, E., Amundsen, C., Balakrishnan, R., Binkley, G., Chan, E. T., Christie, K., Costanzo, M., Dwight, S., Engel, S., et al. (2011) · Nucleic Acids Res. · doi:10.1093/nar/gkr1029 · Cited by 1,886 · cited 1×
“Historically yeast, with its 6600 open reading frames, has been the preferred proteomic technology test-bed (8).”
BackgroundPeng, J., Elias, J. E., Thoreen, C. C., Licklider, L., & Gygi, S. P. (2002) · Journal of Proteome Research · doi:10.1021/pr025556v · Cited by 1,652
Ion Suppression in Mass Spectrometry
Annesley, T. M. (2003) · Clinical Chemistry · doi:10.1373/49.7.1041 · Cited by 1,598
Shevchenko, A., Jensen, O. N., Podtelejnikov, A. V., Sagliocco, F. A., Wilm, M. S., Vorm, O., Mortensen, P. M., Shevchenko, A., Boucherie, H., & Mann, M. (1996) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.93.25.14440 · Cited by 1,429
Large-scale characterization of HeLa cell nuclear phosphoproteins
Beausoleil, S. A., Jedrychowski, M. P., Schwartz, D., Elias, J. E., Villén, J., Li, J., Cohn, M. A., Cantley, L. C., & Gygi, S. P. (2004) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0404720101 · Cited by 1,376
Peterson, A. C., Russell, J. D., Bailey, D. J., Westphall, M. S., & Coon, J. J. (2012) · Molecular & Cellular Proteomics · doi:10.1074/mcp.o112.020131 · Cited by 1,288 · cited 1×
“We also note that the system, with its quadrupole mass filter, offers considerable promise for parallel reaction monitoring (44, 45).”
BackgroundSelf-citationMechanistic investigation of ionization suppression in electrospray ionization
King, R. C., Bonfiglio, R., Fernández‐Metzler, C., Miller‐Stein, C. M., & Olah, T. V. (2000) · Journal of the American Society for Mass Spectrometry · doi:10.1016/s1044-0305(00)00163-x · Cited by 1,089
Interpretation of Shotgun Proteomic Data
Nesvizhskii, A. I., & Aebersold, R. (2005) · Molecular & Cellular Proteomics · doi:10.1074/mcp.r500012-mcp200 · Cited by 1,025
Deep proteome and transcriptome mapping of a human cancer cell line
Nagaraj, N., Wisniewski, J. R., Geiger, T., Cox, J., Kircher, M., Kelso, J., Pääbo, S., & Mann, M. (2011) · Molecular Systems Biology · doi:10.1038/msb.2011.81 · Cited by 979
Comprehensive mass-spectrometry-based proteome quantification of haploid versus diploid yeast
de Godoy, L. M. F., Olsen, J. V., Cox, J., Nielsen, M. L., Hubner, N. C., Fröhlich, F., Walther, T. C., & Mann, M. (2008) · Nature · doi:10.1038/nature07341 · Cited by 873 · cited 1×
“yeast proteome by identifying nearly 4000 proteins (10).”
BackgroundThe quantitative proteome of a human cell line
Beck, M., Schmidt, A., Malmstroem, J., Claassen, M., Ori, A., Szymborska, A., Herzog, F., Rinner, O., Ellenberg, J., & Aebersold, R. (2011) · Molecular Systems Biology · doi:10.1038/msb.2011.82 · Cited by 816
Full dynamic range proteome analysis of S. cerevisiae by targeted proteomics
Picotti, P., Bodenmiller, B., Mueller, L. N., Domon, B., & Aebersold, R. (2009) · Cell · doi:10.1016/j.cell.2009.05.051 · Cited by 744 · cited 1×
“targeted 152 yeast proteins, spanning the full concentration range including several proteins never observed in public proteomic data sets, using synthetic peptides and triple quadrupole MRM technology (43).”
MethodCalorie restriction and SIRT3 trigger global reprogramming of the mitochondrial protein acetylome
Hebert, A. S., Dittenhafer-Reed, K. E., Yu, W., Bailey, D. J., Selen, E. S., Boersma, M. D., Carson, J. J., Tonelli, M., Balloon, A. J., Higbee, A. J., et al. (2013) · Molecular Cell · doi:10.1016/j.molcel.2012.10.024 · Cited by 636
Self-citationTargeted Proteomic Quantification on Quadrupole-Orbitrap Mass Spectrometer
Gallien, S., Duriez, E., Crone, C., Kellmann, M., Moehring, T., & Domon, B. (2012) · Molecular & Cellular Proteomics · doi:10.1074/mcp.o112.019802 · Cited by 510 · cited 1×
“We also note that the system, with its quadrupole mass filter, offers considerable promise for parallel reaction monitoring (44, 45).”
BackgroundValue of Using Multiple Proteases for Large-Scale Mass Spectrometry-Based Proteomics
Swaney, D. L., Wenger, C. D., & Coon, J. J. (2010) · Journal of Proteome Research · doi:10.1021/pr900863u · Cited by 469 · cited 1×
“tensive fractionation (24) and triplicate analysis of each frac-”
Self-citationProteomics: a pragmatic perspective
Mallick, P., & Küster, B. (2010) · Nature Biotechnology · doi:10.1038/nbt.1658 · Cited by 440 · cited 1×
“The ability to measure differences in protein expression has become key to understanding biological phenomena (1, 2).”
BackgroundMass spectrometry–based proteomics in cell biology
Walther, T. C., & Mann, M. (2010) · The Journal of Cell Biology · doi:10.1083/jcb.201004052 · Cited by 425 · cited 1×
“The ability to measure differences in protein expression has become key to understanding biological phenomena (1, 2).”
BackgroundAccurate and Sensitive Peptide Identification with Mascot Percolator
Brosch, M., Yu, L., Hubbard, T., & Choudhary, J. S. (2009) · Journal of Proteome Research · doi:10.1021/pr800982s · Cited by 414 · cited 14×
“For the one hour experiments, between three and eight dubious ORFs were identified per dataset (Table I), confirming these data are indeed well below the 1% FDR threshold.”
MethodInfluentialNagaraj, N., Alexander Kulak, N., Cox, J., Neuhauser, N., Mayr, K., Hoerning, O., Vorm, O., & Mann, M. (2012) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m111.013722 · Cited by 392 · cited 2×
“Previous single-shot yeast proteome analyses utilized long capillary LC columns (50 cm) and lengthy gradients (240 min) (25, 40, 41) We aimed to achieve comparable or better coverage using a much shorter gradient (70 min).”
MethodMichalski, A., Damoc, E., Lange, O., Denisov, E., Nolting, D., Müller, M., Viner, R., Schwartz, J., Remes, P., Belford, M., et al. (2012) · Molecular & Cellular Proteomics · doi:10.1074/mcp.o111.013698 · Cited by 373
The Coming Age of Complete, Accurate, and Ubiquitous Proteomes
Mann, M., Kulak, N. A., Nagaraj, N., & Cox, J. (2013) · Molecular Cell · doi:10.1016/j.molcel.2013.01.029 · Cited by 350
Syka, J. E. P., Marto, J. A., Bai, D. L., Horning, S. R., Senko, M. W., Schwartz, J. C., Ueberheide, B. M., Garcia, B. A., Busby, S. A., Muratore‐Schroeder, T. L., et al. (2004) · Journal of Proteome Research · doi:10.1021/pr0499794 · Cited by 349
Deep and Highly Sensitive Proteome Coverage by LC-MS/MS Without Prefractionation
Thakur, S. S., Geiger, T., Chatterjee, B., Bandilla, P., Fröhlich, F., Cox, J., & Mann, M. (2011) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m110.003699 · Cited by 349 · cited 1×
“Previous single-shot yeast proteome analyses utilized long capillary LC columns (50 cm) and lengthy gradients (240 min) (25, 40, 41) We aimed to achieve comparable or better coverage using a much shorter gradient (70 min).”
MethodAndrews, G. L., Simons, B. L., Young, J. B., Hawkridge, A. M., & Muddiman, D. C. (2011) · Analytical Chemistry · doi:10.1021/ac200812d · Cited by 289 · cited 1×
“TripleTOF) operating at a much lower rate (20 Hz) MS(2) scan rate (26).”
BackgroundStatus of complete proteome analysis by mass spectrometry: SILAC labeled yeast as a model system
de Godoy, L. M., Olsen, J. V., de Souza, G. A., Li, G., Mortensen, P., & Mann, M. (2006) · Genome biology · doi:10.1186/gb-2006-7-6-r50 · Cited by 282
Senko, M. W., Remes, P. M., Canterbury, J. D., Mathur, R., Song, Q., Eliuk, S. M., Mullen, C., Earley, L., Hardman, M., Blethrow, J. D., et al. (2013) · Analytical Chemistry · doi:10.1021/ac403115c · Cited by 243
DMSO enhances electrospray response, boosting sensitivity of proteomic experiments
Hahne, H., Pachl, F., Ruprecht, B., Maier, S. K., Klaeger, S., Helm, D., Médard, G., Wilm, M. S., Lemeer, S., & Küster, B. (2013) · Nature Methods · doi:10.1038/nmeth.2610 · Cited by 238 · cited 2×
“described that addition of 5% DMSO to the mobile phase solvents boosted precursor S/N, providing up to a 20% increase in protein identifications (31, 32).”
BackgroundMethodFigeys, D., Ducret, A., Yates, J. R., & Aebersold, R. H. (1996) · Nature Biotechnology · doi:10.1038/nbt1196-1579 · Cited by 187
Neutron-encoded mass signatures for multiplexed proteome quantification
Hebert, A. S., Merrill, A. E., Bailey, D. J., Still, A., Westphall, M. S., Strieter, E. R., Pagliarini, D. J., & Coon, J. J. (2013) · Nature Methods · doi:10.1038/nmeth.2378 · Cited by 180
Self-citationWu, R., Dephoure, N., Haas, W., Huttlin, E. L., Zhai, B., Sowa, M. E., & Gygi, S. P. (2011) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m111.009654 · Cited by 179
Phosphoproteomics for the Masses
Grimsrud, P. A., Swaney, D. L., Wenger, C. D., Beauchene, N. A., & Coon, J. J. (2010) · ACS Chemical Biology · doi:10.1021/cb900277e · Cited by 164
Self-citationDephoure, N., & Gygi, S. P. (2012) · Science Signaling · doi:10.1126/scisignal.2002548 · Cited by 153
COMPASS: A suite of pre‐ and post‐search proteomics software tools for OMSSA
Wenger, C. D., Phanstiel, D. H., Lee, M. V., Bailey, D. J., & Coon, J. J. (2011) · PROTEOMICS · doi:10.1002/pmic.201000616 · Cited by 152
Self-citationRapid and Deep Human Proteome Analysis by Single-dimension Shotgun Proteomics
Pirmoradian, M., Budamgunta, H., Chingin, K., Zhang, B., Astorga-Wells, J., & Zubarev, R. A. (2013) · Molecular & Cellular Proteomics · doi:10.1074/mcp.o113.028787 · Cited by 144 · cited 2×
“Previous single-shot yeast proteome analyses utilized long capillary LC columns (50 cm) and lengthy gradients (240 min) (25, 40, 41) We aimed to achieve comparable or better coverage using a much shorter gradient (70 min).”
BackgroundMethodSolid Tumor Proteome and Phosphoproteome Analysis by High Resolution Mass Spectrometry
Zanivan, S. R., Gnad, F., Wickström, S. A., Geiger, T., Maček, B., Cox, J., Fässler, R., & Mann, M. (2008) · Journal of Proteome Research · doi:10.1021/pr800599n · Cited by 131
Ledvina, A. R., Beauchene, N. A., McAlister, G. C., Syka, J. E. P., Schwartz, J. C., Griep‐Raming, J., Westphall, M. S., & Coon, J. J. (2010) · Analytical Chemistry · doi:10.1021/ac1020358 · Cited by 70
Self-citationMeyer, J. G., & Komives, E. A. (2012) · Journal of the American Society for Mass Spectrometry · doi:10.1007/s13361-012-0404-0 · Cited by 68 · cited 2×
“described that addition of 5% DMSO to the mobile phase solvents boosted precursor S/N, providing up to a 20% increase in protein identifications (31, 32).”
BackgroundMethodModified MuDPIT Separation Identified 4488 Proteins in a System-wide Analysis of Quiescence in Yeast
Webb, K. J., Xu, T., Park, S. K., & Yates, J. R. (2013) · Journal of Proteome Research · doi:10.1021/pr400027m · Cited by 67
Geromanos, S. J., Hughes, C. J., Ciavarini, S. J., Vissers, J. P. C., & Langridge, J. (2012) · Analytical and Bioanalytical Chemistry · doi:10.1007/s00216-012-6197-y · Cited by 61 · cited 1×
“Other studies using TOF technologies report similar results (27, 28).”
ResultCristobal, A., Hennrich, M. L., Giansanti, P., Goerdayal, S. S., Heck, A. J. R., & Mohammed, S. (2012) · The Analyst · doi:10.1039/c2an35445d · Cited by 52 · cited 1×
“Other studies using TOF technologies report similar results (27, 28).”
Result
Cited by
Sorted by citations
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Mass-spectrometric exploration of proteome structure and function
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Hughes, C. S., Föehr, S., Garfield, D. A., Furlong, E. E. M., Steinmetz, L. M., & Krijgsveld, J. (2014) · Molecular Systems Biology · doi:10.15252/msb.20145625 · Cited by 1,226
Collins, B. C., Hunter, C. L., Liu, Y., Schilling, B., Rosenberger, G., Bader, S. L., Chan, D. W., Gibson, B. W., Gingras, A.-C., Held, J. M., et al. (2017) · Nature Communications · doi:10.1038/s41467-017-00249-5 · Cited by 576
Protein Phosphorylation: A Major Switch Mechanism for Metabolic Regulation
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Metadata
- Authors
- Hebert, A. S., Richards, A. L., Bailey, D. J., Ulbrich, A., Coughlin, E. E., Westphall, M. S., & Coon, J. J.
- Affiliations
- University of Wisconsin–Madison (US)
- Corresponding author
- Coon, Joshua J.
- Venue
- Molecular & Cellular Proteomics
- Publisher
- Elsevier BV
- Published
- 2014-01
- Volume
- 13
- Issue
- 1
- Pages
- 339-347
- ISSN
- 1535-9476 (ISSN-L)
- PMC
- PMC3879625
- OpenAlex
- W1991502938
- Cited by
- 528
- References
- 48
- Citations by year
- 2026: 9 · 2025: 13 · 2024: 18 · 2023: 26 · 2022: 23 · 2021: 47 · 2020: 40 · 2019: 49 · 2018: 44 · 2017: 55 · 2016: 77 · 2015: 60 · 2014: 64
- FWCI
- 30.34
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Molecular & Cellular Proteomics (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Human Genome Research Institute (T32HG002760)
- National Institute of General Medical Sciences (R01GM080148)
- Topics
- Physical Sciences › Chemistry › Spectroscopy › Advanced Proteomics Techniques and Applications
- Physical Sciences › Chemistry › Spectroscopy › Mass Spectrometry Techniques and Applications
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Metabolomics and Mass Spectrometry Studies
- Keywords
- yeast proteome, peptide identification, sample preparation optimization, chromatographic separation, human proteome
- MeSH terms
- Amino Acid Sequence, Humans, Molecular Weight, Peptides, Saccharomyces cerevisiae, Proteome, Tandem Mass Spectrometry
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