Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/107411
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Title: A protein suspension-trapping sample preparation for tear proteomics by liquid chromatography-tandem mass spectrometry
Authors: Tse, JSH 
Sze, YH 
Cheung, JKW 
Li, KK 
Lam, TC 
Issue Date: 2023
Source: Journal of visualized experiments, 2023, v. 202, e64617
Abstract: Tear fluid is one of the easily accessible biofluids that can be collected non-invasively. Tear proteomics has the potential to discover biomarkers for several ocular diseases and conditions. The suspension trapping column has been reported to be an efficient and user-friendly sample preparation workflow for the broad application of downstream proteomic analysis. Yet, this strategy has not been well-studied in the analysis of human tear proteome. The present protocol describes an integrated workflow from clinical human tear samples to purified peptides for non-invasive tear protein biomarker research using mass spectrometry, which provides insights into disease biomarkers and monitoring when combined with bioinformatics analysis. A protein suspension trapping sample preparation was applied and demonstrated the discovery of tear proteome with fast, reproducible, and user-friendly procedures, as a universal, optimized sample preparation for human tear fluid analysis. In particular, the suspension trapping procedure outperformed in-solution sample preparation in terms of peptide recovery, protein identification, and shorter sample preparation time.
Publisher: Journal of Visualized Experiments
Journal: Journal of visualized experiments 
EISSN: 1940-087X
DOI: 10.3791/64617
Rights: Copyright © 2023 JoVE Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported License (https://creativecommons.org/licenses/by/3.0/)
The following publication Tse, J. S., Sze, Y., Ka-Wai Cheung, J., Li, K., Lam, T. C. A Protein Suspension-Trapping Sample Preparation for Tear Proteomics by Liquid Chromatography-Tandem Mass Spectrometry. J. Vis. Exp. (202), e64617 is available at https://doi.org/10.3791/64617 (2023).
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