ArticleJournal of proteome research2014
Off-Line Multidimensional Liquid Chromatography and Auto Sampling Result in Sample Loss in LC/LC-MS/MS.
Article in Journal of proteome research, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.
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Who cites it
28 citing papers in PubMed.
- Article
- Targeted Livestock Metabolomics: A Review of Liquid chromatography-Mass Spectrometry-Based Approaches.Journal of agricultural and food chemistry · 2026Review
- High-Throughput Testing for Unknown Mutagens and Cytotoxica via Duplex Planar Ames-Cytotoxicity Bioassay Including Metabolic S9 Activation.Analytical chemistry · 2026Article
- Comparison of the Trapping Efficiency for Tryptic Peptides on Particle-Packed and Micro-Pillar Trap Columns for Proteomics Analyses.Proteomes · 2026Article
- Targeting infection-specific peptides in immunopeptidomics studies for vaccine target discovery.The Journal of experimental medicine · 2025Article
- Article
- Novel Insights into the Antimicrobial and Antibiofilm Activity of Pyrroloquinoline Quinone (PQQ);Biomolecules · 2024Article
- Repurposed 3D Printer Allows Economical and Programmable Fraction Collection for Proteomics of Nanogram Scale Samples.Analytical chemistry · 2024Article
- Proteomics and metabolomics analyses of Streptococcus agalactiae isolates from human and animal sources.Scientific reports · 2023Article
- Establishing Quality Control Procedures for Large-Scale Plasma Proteomics Analyses.Journal of the American Society for Mass Spectrometry · 2023Article
- Open source fraction collector/MALDI spotter for proteomics.HardwareX · 2022Article
- RETRACTED: Curcumin-InjectedMolecules (Basel, Switzerland) · 2022Article
- Capillary zone electrophoresis-mass spectrometry for top-down proteomics.Trends in analytical chemistry : TRAC · 2019Article
- Primary Step Towards In Situ Detection of Chemical Biomarkers in the UNIVERSE via Liquid-Based Analytical System: Development of an Automated Online Trapping/Liquid Chromatography System.Molecules (Basel, Switzerland) · 2019Article
- Broad range of missense error frequencies in cellular proteins.Nucleic acids research · 2019Article
- More Is Not Always Better: Evaluation of 1D and 2D-LC-MS/MS Methods for Metaproteomics.Frontiers in microbiology · 2019Article
- Application of Displacement Chromatography to Online Two-Dimensional Liquid Chromatography Coupled to Tandem Mass Spectrometry Improves Peptide Separation Efficiency and Detectability for the Analysis of Complex Proteomes.Analytical chemistry · 2018Article
- Quantitative analysis of newly synthesized proteins.Nature protocols · 2018Article
- Offline pentafluorophenyl (PFP)-RP prefractionation as an alternative to high-pH RP for comprehensive LC-MS/MS proteomics and phosphoproteomics.Analytical and bioanalytical chemistry · 2017Article
- Towards comprehensive and quantitative proteomics for diagnosis and therapy of human disease.Proteomics · 2017Review
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4 authors.
Funding
Abstract
Large-scale proteomics often employs two orthogonal separation methods to fractionate complex peptide mixtures. Fractionation can involve ion exchange separation coupled to reversed-phase separation or, more recently, two reversed-phase separations performed at different pH values. When multidimensional separations are combined with tandem mass spectrometry for protein identification, the strategy is often referred to as multidimensional protein identification technology (MudPIT). MudPIT has been used in either an automated (online) or manual (offline) format. In this study, we evaluated the performance of different MudPIT strategies by both label-free and tandem mass tag (TMT) isobaric tagging. Our findings revealed that online MudPIT provided more peptide/protein identifications and higher sequence coverage than offline platforms. When employing an off-line fractionation method with direct loading of samples onto the column from an eppendorf tube via a high-pressure device, a 5.3% loss in protein identifications is observed. When off-line fractionated samples are loaded via an autosampler, a 44.5% loss in protein identifications is observed compared with direct loading of samples onto a triphasic capillary column. Moreover, peptide recovery was significantly lower after offline fractionation than in online fractionation. Signal-to-noise (S/N) ratio, however, was not significantly altered between experimental groups. It is likely that offline sample collection results in stochastic peptide loss due to noncovalent adsorption to solid surfaces. Therefore, the use of the offline approaches should be considered carefully when processing minute quantities of valuable samples.
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