Estimating the Distribution of Protein Post-Translational Modification States by Mass Spectrometry
Open accessAbstract
Post-translational modifications (PTMs) of proteins play a central role in cellular information encoding, but the complexity of PTM state has been challenging to unravel. A single molecule can exhibit a “modform” or combinatorial pattern of co-occurring PTMs across multiple sites, and a molecular population can exhibit a distribution of amounts of different modforms. How can this “modform distribution” be estimated by mass spectrometry (MS)? Bottom-up MS, based on cleavage into peptides, destroys correlations between PTMs on different peptides, but it is conceivable that multiple proteases with appropriate patterns of cleavage could reconstruct the modform distribution. We introduce a mathematical language for describing MS measurements and show, on the contrary, that no matter how many distinct proteases are available, the shortfall in information required for reconstruction worsens exponentially with increasing numbers of sites. Whereas top-down MS on intact proteins can do better, current technology cannot prevent the exponential worsening. However, our analysis also shows that all forms of MS yield linear equations for modform amounts. This permits different MS protocols to be integrated and the modform distribution to be constrained within a high-dimensional “modform region”, which may offer a feasible proxy for analyzing information encoding.
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Top-down proteomics has the theoretical capacity to bypass the protein inference issue that affects bottom-up proteomics.
“TDP can theoretically overcome5 the well-known “protein inference” problem afflicting bottom-up proteomics (BUP),6”
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Proton Transfer Charge Reduction Enables High-Throughput Top-Down Analysis of Large Proteoforms
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- Authors
- Compton, P. D., Kelleher, N. L., & Gunawardena, J.
- Affiliations
- Northwestern University (US)
- Harvard University (US)
- Corresponding author
- Kelleher, Neil L.
- Gunawardena, Jeremy
- Venue
- Journal of Proteome Research
- Publisher
- American Chemical Society (ACS)
- Published
- 2018-06-27
- Volume
- 17
- Issue
- 8
- Pages
- 2727-2734
- ISSN
- 1535-3893 (ISSN-L)
- 1535-3907
- PMC
- PMC6076341
- OpenAlex
- W2809710814
- Cited by
- 30
- References
- 34
- Citations by year
- 2026: 1 · 2025: 1 · 2024: 1 · 2023: 4 · 2022: 2 · 2021: 7 · 2020: 3 · 2019: 7 · 2018: 3 · 2016: 1
- FWCI
- 2.16
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Licence
- Locations
- Journal of Proteome Research (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- Paul G. Allen Family Foundation (11715)
- National Institute of General Medical Sciences (P41 GM108569, R01 GM105375)
- 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 › Redox biology and oxidative stress
- Keywords
- post-translational modification, top-down mass spectrometry, bottom-up mass spectrometry, protease cleavage
- MeSH terms
- Animals, Humans, Models, Theoretical, Peptide Hydrolases, Protein Processing, Post-Translational, Mass Spectrometry, Statistical Distributions, Computational Biology, Proteomics
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