ArticleMolecular & cellular proteomics : MCP2024
A Causal Model of Ion Interference Enables Assessment and Correction of Ratio Compression in Multiplex Proteomics.
Article in Molecular & cellular proteomics : MCP, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Sexual Dimorphism and Intraspecific Toxin Variation in Crotalus durissus terrificus Venom: Insights from Proteomics, Peptidomics, and Structural Modeling.Journal of proteome research · 2026Article
- HSP90 differentially stabilizes plant ABCB-type auxin transporters on the plasma membrane.Nature communications · 2025Article
- Isobaric Labeling Update in MaxQuant.Journal of proteome research · 2025Article
- Genetic Landscape and Mitochondrial Metabolic Dysregulation in Patients Suffering From Severe Long COVID.Journal of medical virology · 2025Article
- Data acquisition approaches for single cell proteomics.Proteomics · 2025Review
- Challenges of MS-based small extracellular vesicles proteomics.Journal of extracellular vesicles · 2024Review
- The global phosphorylation landscape of mouse oocytes during meiotic maturation.The EMBO journal · 2024Article
- Automated single-cell proteomics providing sufficient proteome depth to study complex biology beyond cell type classifications.Nature communications · 2024Article
- Automated single-cell proteomics providing sufficient proteome depth to study complex biology beyond cell type classifications.bioRxiv : the preprint server for biology · 2024Article
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Authors and funding
6 authors.
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Abstract
Multiplex proteomics using isobaric labeling tags has emerged as a powerful tool for the simultaneous relative quantification of peptides and proteins across multiple experimental conditions. However, the quantitative accuracy of the approach is largely compromised by ion interference, a phenomenon that causes fold changes to appear compressed. The degree of compression is generally unknown, and the contributing factors are poorly understood. In this study, we thoroughly characterized ion interference at the MS2 level using a defined two-proteome experimental system with known ground-truth. We discovered remarkably poor agreement between the apparent precursor purity in the isolation window and the actual level of observed reporter ion interference in MS2 scans-a discrepancy that we found resolved by considering cofragmentation of peptide ions hidden within the spectral "noise" of the MS1 isolation window. To address this issue, we developed a regression modeling strategy to accurately predict reporter ion interference in any dataset. Finally, we demonstrate the utility of our procedure for improved fold change estimation and unbiased PTM site-to-protein normalization. All computational tools and code required to apply this method to any MS2 TMT dataset are documented and freely available.
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