ArticleMolecular & cellular proteomics : MCP2014
Maximizing peptide identification events in proteomic workflows using data-dependent acquisition (DDA).
Article in Molecular & cellular proteomics : MCP, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 51 papers.
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Who cites it
51 citing papers in PubMed.
- Proteogenomics: decoding cancer in multiple dimensions.MedScience · 2026Review
- Plasma-Derived Exosomal hsa-miR-3677-3p Induces Ferroptosis in Neurons by Targeting ABCB8 in Perioperative Neurocognitive Disorders After Prostate Surgery.Neurochemical research · 2026Article
- Mass Spectrometry Proteomics: A Key to Faster Drug Discovery.Journal of medicinal chemistry · 2026Review
- Developing Well-Annotated Species-Specific Protein Databases Using Comparative Proteogenomics: An Update.Advances in experimental medicine and biology · 2026Review
- Artificial Intelligence and the Evolving Landscape of Immunopeptidomics.Proteomics. Clinical applications · 2025Review
- Impact of Sample Preparation Strategies on the Quantitative Accuracy of Low-Abundance Serum Proteins in Shotgun Proteomics.Journal of proteome research · 2025Article
- Data-Independent Acquisition Mass Spectrometry as a Tool for Metaproteomics: Interlaboratory Comparison Using a Model Microbiome.Proteomics · 2025Article
- SWAPS: A Modular Deep-Learning Empowered Peptide Identity Propagation Framework Beyond Match-Between-Run.Journal of proteome research · 2025Article
- InstaNovo enables diffusion-powered de novo peptide sequencing in large-scale proteomics experiments.Nature machine intelligence · 2025Article
- Proteomics Can Rise to the Challenge of Pseudogenes' Coding Nature.Journal of proteome research · 2024Review
- Review
- Evaluation of Protein Identification and Quantification by the diaPASEF Method on timsTOF SCP.Journal of the American Society for Mass Spectrometry · 2024Article
- Evaluation of PAC and FASP Performance: DIA-Based Quantitative Proteomic Analysis.International journal of molecular sciences · 2024Article
- Proteomics for Microalgae Extracts by High-Resolution Mass Spectrometry.Methods in molecular biology (Clifton, N.J.) · 2024Article
- Spectra without stories: reporting 94% dark and unidentified ancient proteomes.Open research Europe · 2024Article
- A Current State of Proteomics in Adult and Pediatric Inflammatory Bowel Diseases: A Systematic Search and Review.International journal of molecular sciences · 2023Review
- Mass spectrometry-based retina proteomics.Mass spectrometry reviews · 2023Review
- Principles of phosphoproteomics and applications in cancer research.The Biochemical journal · 2023Article
- Data-Independent Acquisition (DIA) Is Superior for High Precision Phospho-Peptide Quantification inJournal of fungi (Basel, Switzerland) · 2022Article
- Omics and Multi-Omics Analysis for the Early Identification and Improved Outcome of Patients with Psoriatic Arthritis.Biomedicines · 2022Review
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7 authors.
Funding
Abstract
Current analytical strategies for collecting proteomic data using data-dependent acquisition (DDA) are limited by the low analytical reproducibility of the method. Proteomic discovery efforts that exploit the benefits of DDA, such as providing peptide sequence information, but that enable improved analytical reproducibility, represent an ideal scenario for maximizing measureable peptide identifications in "shotgun"-type proteomic studies. Therefore, we propose an analytical workflow combining DDA with retention time aligned extracted ion chromatogram (XIC) areas obtained from high mass accuracy MS1 data acquired in parallel. We applied this workflow to the analyses of sample matrixes prepared from mouse blood plasma and brain tissues and observed increases in peptide detection of up to 30.5% due to the comparison of peptide MS1 XIC areas following retention time alignment of co-identified peptides. Furthermore, we show that the approach is quantitative using peptide standards diluted into a complex matrix. These data revealed that peptide MS1 XIC areas provide linear response of over three orders of magnitude down to low femtomole (fmol) levels. These findings argue that augmenting "shotgun" proteomic workflows with retention time alignment of peptide identifications and comparative analyses of corresponding peptide MS1 XIC areas improve the analytical performance of global proteomic discovery methods using DDA.
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