Hyperplexing: a method for higher-order multiplexed quantitative proteomics provides a map of the dynamic response to rapamycin in yeast
Open accessAbstract
Large-scale quantitative proteomics can provide a near-global view of cellular protein abundance. Yet, the time, effort, and expertise required to achieve reasonable protein coverage and reliable quantification have limited the broad application of this technology. To fully leverage mass spectrometry for the elucidation of biological systems requires sufficient throughput to monitor dynamic changes across conditions and to enable replicate analysis to provide statistical power. We report a straightforward approach to increase the multiplexing capacity of quantitative mass spectrometry, which provides a platform for the analysis of cellular signaling pathways. Using triplex metabolic labeling and six-plex isobaric tags, we monitored changes in protein abundance from 18 samples simultaneously, performing biological triplicates of a six-point time course of rapamycin-stimulated yeast. The data set provides temporal abundance profiles for thousands of yeast proteins, highlighting the complex cellular roles of the TOR (target of rapamycin) pathway.
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There is no limit on the number of samples that can be compared in label-free quantification, in contrast to the finite number of plexes available for label-based methods.
“In addition, there is no limit on the number of samples that can be compared, in contrast to the finite number of “plexes” available for label-based methods (7).”
From Accurate proteome-wide label-free quantification by delayed normalization and maximal peptide ratio extraction, termed MaxLFQ (2014) · cites this paper as [7]
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References 25 · Cited by 153
- Authors
- Dephoure, N., & Gygi, S. P.
- Affiliations
- Harvard University (US)
- Corresponding author
- Gygi, Steven P.
- Venue
- Science Signaling
- Published
- 2012-03-27
- Volume
- 5
- Issue
- 217
- Pages
- rs2-rs2
- ISSN
- 1937-9145 (ISSN-L)
- 1945-0877
- PMC
- PMC5292868
- OpenAlex
- W1980760081
- Cited by
- 153
- References
- 25
- Citations by year
- 2026: 2 · 2025: 2 · 2024: 5 · 2023: 12 · 2022: 7 · 2021: 9 · 2020: 15 · 2019: 11 · 2018: 7 · 2017: 10 · 2016: 9 · 2015: 26 · 2014: 12 · 2013: 20 · 2012: 6
- FWCI
- 9.04
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Science Signaling (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Human Genome Research Institute (HG003456, R01HG003456)
- National Institute of General Medical Sciences (R01GM067945, GM-067945)
- 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 › Ubiquitin and proteasome pathways
- Keywords
- quantitative proteomics, multiplexing, rapamycin, TOR signaling, Saccharomyces cerevisiae, protein abundance, isobaric tags, metabolic labeling, time course, signal transduction
- MeSH terms
- Amino Acids, Carbon Isotopes, Cations, Chromatography, Ion Exchange, Immunosuppressive Agents, Isotope Labeling, Nitrogen Isotopes, Saccharomyces cerevisiae, Mass Spectrometry, Immunoblotting, Reproducibility of Results, Sirolimus, Proteome, Saccharomyces cerevisiae Proteins, Proteomics
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