ArticleJournal of proteome research2019
Constructing Human Proteoform Families Using Intact-Mass and Top-Down Proteomics with a Multi-Protease Global Post-Translational Modification Discovery Database.
Article in Journal of proteome research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
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Who cites it
20 citing papers in PubMed.
- Defining proteoform-specific interactions for drug targeting in a native cell signalling environment.Nature chemistry · 2025Article
- Intact Mass Proteomics Using a Proteoform Atlas.Journal of proteome research · 2025Article
- Alternative proteoforms and proteoform-dependent assemblies in humans and plants.Molecular systems biology · 2024Article
- Instrumentation at the Leading Edge of Proteomics.Analytical chemistry · 2024Review
- Spectral averaging with outlier rejection algorithms to increase identifications in top-down proteomics.Proteomics · 2024Article
- Fast peak error correction algorithms for proteoform identification using top-down tandem mass spectra.Bioinformatics (Oxford, England) · 2024Article
- Cysteine Counting via Isotopic Chemical Labeling for Intact Mass Proteoform Identifications in Tissue.Analytical chemistry · 2023Article
- Characterization of Proteoform Post-Translational Modifications by Top-Down and Bottom-Up Mass Spectrometry in Conjunction with Annotations.Journal of proteome research · 2023Article
- Quantitative Aspects of the Human Cell Proteome.International journal of molecular sciences · 2023Review
- Enhanced Proteomic Data Analysis with MetaMorpheus.Methods in molecular biology (Clifton, N.J.) · 2023Article
- Deep top-down proteomics revealed significant proteoform-level differences between metastatic and nonmetastatic colorectal cancer cells.Science advances · 2022Article
- Proteoform-Selective Imaging of Tissues Using Mass Spectrometry.Angewandte Chemie (International ed. in English) · 2022Article
- The Human Proteoform Atlas: a FAIR community resource for experimentally derived proteoforms.Nucleic acids research · 2022Article
- Proteoform Analysis and Construction of Proteoform Families in Proteoform Suite.Methods in molecular biology (Clifton, N.J.) · 2022Article
- Internal Fragment Ions Disambiguate and Increase Identifications in Top-Down Proteomics.Journal of proteome research · 2021Article
- Automated Assignment of Proteoform Classification Levels.Journal of proteome research · 2021Article
- Mesh Fragmentation Improves Dissociation Efficiency in Top-down Proteomics.Journal of the American Society for Mass Spectrometry · 2021Article
- Spritz: A Proteogenomic Database Engine.Journal of proteome research · 2021Article
- Construction of Human Proteoform Families from 21 Tesla Fourier Transform Ion Cyclotron Resonance Mass Spectrometry Top-Down Proteomic Data.Journal of proteome research · 2021Article
- Improving Proteoform Identifications in Complex Systems Through Integration of Bottom-Up and Top-Down Data.Journal of proteome research · 2020Article
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Authors and funding
9 authors.
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Abstract
Complex human biomolecular processes are made possible by the diversity of human proteoforms. Constructing proteoform families, groups of proteoforms derived from the same gene, is one way to represent this diversity. Comprehensive, high-confidence identification of human proteoforms remains a central challenge in mass spectrometry-based proteomics. We have previously reported a strategy for proteoform identification using intact-mass measurements, and we have since improved that strategy by mass calibration based on search results, the use of a global post-translational modification discovery database, and the integration of top-down proteomics results with intact-mass analysis. In the present study, we combine these strategies for enhanced proteoform identification in total cell lysate from the Jurkat human T lymphocyte cell line. We collected, processed, and integrated three types of proteomics data (NeuCode-labeled intact-mass, label-free top-down, and multi-protease bottom-up) to maximize the number of confident proteoform identifications. The integrated analysis revealed 5950 unique experimentally observed proteoforms, which were assembled into 848 proteoform families. Twenty percent of the observed proteoforms were confidently identified at a 3.9% false discovery rate, representing 1207 unique proteoforms derived from 484 genes.
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