ArticleJournal of proteomics & bioinformatics2015
Multidimensional Separation Using HILIC and SCX Pre-fractionation for RP LC-MS/MS Platform with Automated Exclusion List-based MS Data Acquisition with Increased Protein Quantification.
Article in Journal of proteomics & bioinformatics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 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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Who cites it
6 citing papers in PubMed, 13 citations in OpenAlex.
- Proteomics for Microalgae Extracts by High-Resolution Mass Spectrometry.Methods in molecular biology (Clifton, N.J.) · 2024Article
- Comparative Transcriptome and Proteome Analysis Provides New Insights Into the Mechanism of Protein Synthesis in Kenaf (Frontiers in plant science · 2022Article
- The potential of tear proteomics for diagnosis and management of orbital inflammatory disorders including Graves' ophthalmopathy.Experimental eye research · 2021Review
- Integrative transcriptome and proteome analyses provide new insights into different stages ofBiotechnology for biofuels · 2020Article
- Strategic Combination of Isocratic and Gradient Elution for Simultaneous Separation of Polar Compounds in Traditional Chinese Medicines by HPLC.Journal of analytical methods in chemistry · 2018Article
- Imbalanced Rab3D versus Rab27 increases cathepsin S secretion from lacrimal acini in a mouse model of Sjögren's Syndrome.American journal of physiology. Cell physiology · 2016Article
Corrections and comments
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
Abstract
Liquid chromatography-mass spectrometry (LC-MS) based proteomics is one of the most widely used analytical platforms for global protein discovery and quantification. One of the challenges is the difficulty of identifying low abundance biomarker proteins from limited biological samples. Extensive fractionation could expand proteomics dynamic range, however, at the cost of high sample and time consumption. Extensive fractionation would increase the sample need and the labeling cost. Also quantitative proteomics depending on high resolution MS have the limitation of spectral acquisition speed. Those practical problems hinder the in-depth quantitative proteomics analysis such as tandem mass tag (TMT) experiments. We found the joint use of hydrophilic interaction liquid chromatography (HILIC) and strong cation exchange Chromatography (SCX) prefractionation at medium level could improve MS/MS efficiency, increase proteome coverage, shorten analysis time and save valuable samples. In addition, we scripted a program, Exclusion List Convertor (ELC), which automates and streamlines data acquisition workflow using the precursor ion exclusion (PIE) method. PIE reduces redundancy of high abundance MS/MS analyses by running replicates of the sample. The precursor ions detected in the initial run(s) are excluded for MS/MS in the subsequent run. We compared PIE methods with standard data dependent acquisition (DDA) methods running replicates without PIE for their effectiveness in quantifying TMT-tagged peptides and proteins in mouse tears. We quantified a total of 845 proteins and 1401 peptides using the PIE workflow, while the DDA method only resulted in 347 proteins and 731 peptides. This represents a 144% increase of protein identifications as a result of PIE analysis.
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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.