ReviewBriefings in functional genomics & proteomics2009
18O stable isotope labeling in MS-based proteomics.
Review in Briefings in functional genomics & proteomics, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
41 citing papers in PubMed, 121 citations in OpenAlex.
- Mass Spectrometry Proteomics: A Key to Faster Drug Discovery.Journal of medicinal chemistry · 2026Review
- Targeted Metabolomic Methods forJournal of proteome research · 2025Article
- Isotope Labeling Techniques for Virus-Infected Cells.Methods in molecular biology (Clifton, N.J.) · 2025Review
- Deciphering Cancer Complexity: Integrative Proteogenomics and Proteomics Approaches for Biomarker Discovery.Methods in molecular biology (Clifton, N.J.) · 2025Review
- HyperSCP: Combining Isotopic and Isobaric Labeling for Higher Throughput Single-Cell Proteomics.Analytical chemistry · 2023Article
- Simple In VitroInternational journal of molecular sciences · 2023Article
- Advancements in Oncoproteomics Technologies: Treading toward Translation into Clinical Practice.Proteomes · 2023Review
- Analysis ofInternational journal of molecular sciences · 2022Article
- Polyphosphate Dynamics in Cable Bacteria.Frontiers in microbiology · 2022Article
- Quantitative Proteomics Using Isobaric Labeling: A Practical Guide.Genomics, proteomics & bioinformatics · 2021Review
- N-Linked Glycosylation on Anthrax Toxin Receptor 1 Is Essential for Seneca Valley Virus Infection.Viruses · 2021Article
- Adsorption separation of heavier isotope gases in subnanometer carbon pores.Nature communications · 2021Article
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- Collagen: quantification, biomechanics, and role of minor subtypes in cartilage.Nature reviews. Materials · 2020Article
- A comprehensive overview of proteomics approach for COVID 19: new perspectives in target therapy strategies.Journal of proteins and proteomics · 2020Review
- Oxidation of difluorocarbene and subsequent trifluoromethoxylation.Nature communications · 2019Article
- Proteomics: a powerful tool to study plant responses to biotic stress.Plant methods · 2019Review
- Simultaneous Visualization of Enzymatic Activity in the Cytoplasm and at Polyphosphate Inclusions inmSphere · 2018Article
- Protein Dynamics in Solution by Quantitative Crosslinking/Mass Spectrometry.Trends in biochemical sciences · 2018Review
- Article
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
Abstract
A variety of stable isotope labeling techniques have been developed and used in mass spectrometry (MS)-based proteomics, primarily for relative quantitation of changes in protein abundances between two compared samples, but also for qualitative characterization of differentially labeled proteomes. Differential (16)O/(18)O coding relies on the (18)O exchange that takes place at the C-terminal carboxyl group of proteolytic fragments, where two (16)O atoms are typically replaced by two (18)O atoms by enzyme-catalyzed oxygen-exchange in the presence of H(2)(18)O. The resulting mass shift between differentially labeled peptide ions permits identification, characterization and quantitation of proteins from which the peptides are proteolytically generated. This review focuses on the utility of (16)O/(18)O labeling within the context of mass spectrometry-based proteome research. Different strategies employing (16)O/(18)O are examined in the context of global comparative proteome profiling, targeted subcellular proteomics, analysis of post-translational modifications and biomarker discovery. Also discussed are analytical issues related to this technique, including variable (18)O exchange along with advantages and disadvantages of (16)O/(18)O labeling in comparison with other isotope-coding techniques.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.