The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.
MSModDetector: a tool for detecting mass shifts and post-translational modifications in individual ion mass spectrometry data
Open accessPublished version of a preprint
Abstract
Motivation: Post-translational modifications (PTMs) on proteins regulate protein structures and functions. A single protein molecule can possess multiple modification sites that can accommodate various PTM types, leading to a variety of different patterns, or combinations of PTMs, on that protein. Different PTM patterns can give rise to distinct biological functions. To facilitate the study of multiple PTMs on the same protein molecule, top-down mass spectrometry (MS) has proven to be a useful tool to measure the mass of intact proteins, thereby enabling even PTMs at distant sites to be assigned to the same protein molecule and allowing determination of how many PTMs are attached to a single protein. Results: We developed a Python module called MSModDetector that studies PTM patterns from individual ion mass spectrometry (I2MS) data. I2MS is an intact protein mass spectrometry approach that generates true mass spectra without the need to infer charge states. The algorithm first detects and quantifies mass shifts for a protein of interest and subsequently infers potential PTM patterns using linear programming. The algorithm is evaluated on simulated I2MS data and experimental I2MS data for the tumor suppressor protein p53. We show that MSModDetector is a useful tool for comparing a protein’s PTM pattern landscape across different conditions. An improved analysis of PTM patterns will enable a deeper understanding of PTM-regulated cellular processes. Availability and implementation: The source code is available at https://github.com/marjanfaizi/MSModDetector.
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Cites
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Metadata
- Authors
- Faizi, M., Fellers, R. T., Lu, D., Drown, B. S., Jambhekar, A., Lahav, G., Kelleher, N. L., & Gunawardena, J.
- Affiliations
- Harvard University (US)
- Northwestern University (US)
- Department of Systems Biology, Blavatnik Institute at Harvard Medical School , Boston, MA 02115, United States
- Corresponding author
- Gunawardena, Jeremy
- ORCID
- Venue
- Bioinformatics
- Publisher
- Oxford University Press (OUP)
- Published
- 2024-05-25
- Volume
- 40
- Issue
- 6
- ISSN
- 1367-4803 (ISSN-L)
- 1367-4811
- PMC
- PMC11157153
- OpenAlex
- W4399032435
- Cited by
- 4
- References
- 7
- Citations by year
- 2025: 2 · 2024: 2
- FWCI
- 0.50
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Bioinformatics (publishedVersion, cc-by)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- PubMed Central (submittedVersion)
- Funders
- German Research Foundation (445690853)
- 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 › Machine Learning in Bioinformatics
- Keywords
- post-translational modification, top-down mass spectrometry, linear programming, p53, protein modification sites
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