MS3 eliminates ratio distortion in isobaric multiplexed quantitative proteomics
Open accessAbstract
Quantitative mass spectrometry-based proteomics is highly versatile but not easily multiplexed. Isobaric labeling strategies allow mass spectrometry-based multiplexed proteome quantification; however, ratio distortion owing to protein quantification interference is a common effect. We present a two-proteome model (mixture of human and yeast proteins) in a sixplex isobaric labeling system to fully document the interference effect, and we report that applying triple-stage mass spectrometry (MS3) almost completely eliminates interference.
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Ratio compression during TMT quantification due to peptide co-elution can be addressed by MS3, extensive LC fractionation, MS optimization, and computational correction.
“Although ratio compression occurs during quantification because of peptide co-elution, the limitation can be addressed by the introduction of the MS3 method [23], extensive LC fractionation, MS optimization, and computational correction [24], to allow deep proteomic analysis [18, 25, 26].”
From Integrated analysis of ultra-deep proteomes in cortex, cerebrospinal fluid and serum reveals a mitochondrial signature in Alzheimer’s disease (2020) · cites this paper as [23]
For MS3 spectra, only those with an average signal-to-noise value greater than 40 per reporter ion and an isolation specificity greater than 0.75 were quantified.
“For MS3 spectra, only those with an average signal-to-noise value > 40 per reporter ion and an isolation specificity86 > 0.75 were quantified.”
From LKB1 regulates JNK-dependent stress signaling and apoptotic dependency of KRAS-mutant lung cancers (2025) · cites this paper as [86]
The Online Methods sections on quantitative data analysis and isolation specificity describe how reporter-ion intensities and isolation specificity were calculated, but do not state the claimed cutoffs. Searches for a signal-to-noise threshold of 40 and an isolation-specificity threshold of 0.75 found no passage establishing them as requirements for quantifying MS3 spectra. No page numbers are available in our copy. (LLM, conf=0.76)
Experimental — accuracy not yet measuredA number of studies have shown that while levels of many proteins are strongly correlated with their transcript levels, with coincident eQTL and pQTL, the correlations for most protein-transcript pairs are modest.
“A number of studies have now shown that while levels of many proteins are strongly correlated with their transcript levels, with coincident eQTL and protein QTL (pQTL), the correlations for most protein–transcript pairs are modest [51–58].”
From Multi-omics approaches to disease (2017) · cites this paper as [56]
One strategy to minimize the missing value problem is to measure peptide and protein levels using a multiplex tagging approach with isobaric tandem mass tags (TMTs).
“One strategy to minimize the missing value problem is to measure peptide and protein levels using a multiplex tagging approach with isobaric tandem mass tags (TMTs) [8–11].”
From Deep proteomic network analysis of Alzheimer’s disease brain reveals alterations in RNA binding proteins and RNA splicing associated with disease (2018) · cites this paper as [8]
Using an appropriate pooled sample study design and mass spectrometry instrumentation that can perform MS3 reporter quantitation, missing values can be minimized within an experimental cohort using a TMT approach while avoiding dynamic range compression effects.
“Using an appropriate pooled sample study design and mass spectrometry instrumentation that can perform MS3 reporter quantitation, missing values can be minimized within an experimental cohort using a TMT approach while avoiding dynamic range compression effects [8].”
From Deep proteomic network analysis of Alzheimer’s disease brain reveals alterations in RNA binding proteins and RNA splicing associated with disease (2018) · cites this paper as [8]
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Self-citation
- Authors
- Ting, L., Rad, R., Gygi, S. P., & Haas, W.
- Affiliations
- Harvard University (US)
- Corresponding author
- Gygi, Steven P
- Haas, Wilhelm
- Venue
- Nature Methods
- Published
- 2011-10-02
- Volume
- 8
- Issue
- 11
- Pages
- 937-940
- ISSN
- 1548-7091 (ISSN-L)
- 1548-7105
- PMC
- PMC3205343
- OpenAlex
- W2012626734
- Cited by
- 1,009
- References
- 15
- Citations by year
- 2026: 40 · 2025: 49 · 2024: 59 · 2023: 80 · 2022: 88 · 2021: 102 · 2020: 92 · 2019: 80 · 2018: 71 · 2017: 72 · 2016: 56 · 2015: 62 · 2014: 66 · 2013: 46 · 2012: 41
- FWCI
- 22.76
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Nature Methods (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Human Genome Research Institute (HG3456, R01HG003456)
- National Institute of General Medical Sciences (GM 67945, R01GM067945)
- 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
- isobaric labeling, quantitative proteomics
- MeSH terms
- HeLa Cells, Humans, Saccharomyces cerevisiae, Mass Spectrometry, Proteomics
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