ArticleJournal of proteome research2023
Potential of Negative-Ion-Mode Proteomics: An MS1-Only Approach.
Article in Journal of proteome research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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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
7 citing papers in PubMed, 12 citations in OpenAlex.
- Transfer learning in DeepLC improves LC retention time prediction across substantially different modifications and setups.Nature communications · 2026Article
- Nucleation dynamics in amyloid-beta dimerization revealed by single-molecule fingerprinting.Cell reports. Physical science · 2025Article
- Peptide Analysis by Soft X-ray Atmospheric Pressure Photoionization Mass Spectrometry.Journal of the American Society for Mass Spectrometry · 2025Article
- Optimization of Capillary Vibrating Sharp-Edge Spray Ionization for Native Mass Spectrometry of Triplex DNA.ACS omega · 2025Article
- Classifying Dry Eye Disease Patients from Healthy Controls Using Machine Learning and Metabolomics Data.Diagnostics (Basel, Switzerland) · 2024Article
- Sequencing of Phosphopeptides Using a Sequential Charge Inversion Ion/Ion Reaction and Electron Capture Dissociation Workflow.Journal of the American Society for Mass Spectrometry · 2024Article
- Exploring the Potential of Bioactive Peptides: From Natural Sources to Therapeutics.International journal of molecular sciences · 2024Review
Corrections and comments
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Authors and funding
5 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Current proteomics approaches rely almost exclusively on using the positive ionization mode, resulting in inefficient ionization of many acidic peptides. This study investigates protein identification efficiency in the negative ionization mode using the DirectMS1 method. DirectMS1 is an ultrafast data acquisition method based on accurate peptide mass measurements and predicted retention times. Our method achieves the highest rate of protein identification in the negative ion mode to date, identifying over 1000 proteins in a human cell line at a 1% false discovery rate. This is accomplished using a single-shot 10 min separation gradient, comparable to lengthy MS/MS-based analyses. Optimizing separation and experimental conditions was achieved by utilizing mobile buffers containing 2.5 mM imidazole and 3% isopropanol. The study emphasized the complementary nature of data obtained in positive and negative ion modes. Combining the results from all replicates in both polarities increased the number of identified proteins to 1774. Additionally, we analyzed the method's efficiency using different proteases for protein digestion. Among the four studied proteases (LysC, GluC, AspN, and trypsin), trypsin and LysC demonstrated the highest protein identification yield. This suggests that digestion procedures utilized in positive-mode proteomics can be effectively applied in the negative ion mode. Data are deposited to ProteomeXchange: PXD040583.
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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.