ArticleProteomics2023
JUMPptm: Integrated software for sensitive identification of post-translational modifications and its application in Alzheimer's disease study.
Article in Proteomics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 14 citations in OpenAlex.
- Article
- Longitudinal Proteomics Analysis of Cerebrospinal Fluid in Survivors of Childhood Acute Lymphoblastic Leukemia.Scientific data · 2026Article
- Largely Distinct Post-Translational Modifications Differentiate Skeletal Muscle Wasting Caused by Cancer, Dexamethasone and Aging.Journal of cachexia, sarcopenia and muscle · 2026Article
- Proteomic landscape of Alzheimer's disease: emerging technologies, advances and insights (2021 - 2025).Molecular neurodegeneration · 2025Review
- Monitoring Functional Posttranslational Modifications Using a Data-Driven Proteome Informatic Pipeline.Proteomics · 2025Article
- Article
- Identifying Sex-Specific Serum Patterns of Alzheimer's Mice through Deep TMT Profiling and a Concentration-Dependent Concatenation Strategy.Journal of proteome research · 2023Article
- An adaptive stress response that confers cellular resilience to decreased ubiquitination.Nature communications · 2023Article
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Authors and funding
6 authors at 1 institution in 1 country.
Funding
Abstract
backgroundMass spectrometry (MS)-based proteomic analysis of posttranslational modifications (PTMs) usually requires the pre-enrichment of modified proteins or peptides. However, recent ultra-deep whole proteome profiling generates millions of spectra in a single experiment, leaving many unassigned spectra, some of which may be derived from PTM peptides.
methodsHere we present JUMPptm, an integrative computational pipeline, to extract PTMs from unenriched whole proteome. JUMPptm combines the advantages of JUMP, MSFragger and Comet search engines, and includes de novo tags, customized database search and peptide filtering, which iteratively analyzes each PTM by a multi-stage strategy to improve sensitivity and specificity.
resultsWe applied JUMPptm to the deep brain proteome of Alzheimer's disease (AD), and identified 34,954 unique peptides with phosphorylation, methylation, acetylation, ubiquitination, and others. The phosphorylated peptides were validated by enriched phosphoproteome from the same sample. TMT-based quantification revealed 482 PTM peptides dysregulated at different stages during AD progression. For example, the acetylation of numerous mitochondrial proteins is significantly decreased in AD. A total of 60 PTM sites are found in the pan-PTM map of the Tau protein.
conclusionThe JUMPptm program is an effective tool for pan-PTM analysis and the resulting AD pan-PTM profile serves as a valuable resource for AD research.
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