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An optimized workflow for MS-based quantitative proteomics of challenging clinical bronchoalveolar lavage fluid (BALF) samples

Authors :
Danielle O. Weise
Monica E. Kruk
LeeAnn Higgins
Todd W. Markowski
Pratik D. Jagtap
Subina Mehta
Alan Mickelson
Laurie L. Parker
Christine H. Wendt
Timothy J. Griffin
Source :
Clinical Proteomics. 20
Publication Year :
2023
Publisher :
Springer Science and Business Media LLC, 2023.

Abstract

Background Clinical bronchoalveolar lavage fluid (BALF) samples are rich in biomolecules, including proteins, and useful for molecular studies of lung health and disease. However, mass spectrometry (MS)-based proteomic analysis of BALF is challenged by the dynamic range of protein abundance, and potential for interfering contaminants. A robust, MS-based proteomics compatible sample preparation workflow for BALF samples, including those of small and large volume, would be useful for many researchers. Results We have developed a workflow that combines high abundance protein depletion, protein trapping, clean-up, and in-situ tryptic digestion, that is compatible with either qualitative or quantitative MS-based proteomic analysis. The workflow includes a value-added collection of endogenous peptides for peptidomic analysis of BALF samples, if desired, as well as amenability to offline semi-preparative or microscale fractionation of complex peptide mixtures prior to LC–MS/MS analysis, for increased depth of analysis. We demonstrate the effectiveness of this workflow on BALF samples collected from COPD patients, including for smaller sample volumes of 1–5 mL that are commonly available from the clinic. We also demonstrate the repeatability of the workflow as an indicator of its utility for quantitative proteomic studies. Conclusions Overall, our described workflow consistently provided high quality proteins and tryptic peptides for MS analysis. It should enable researchers to apply MS-based proteomics to a wide-variety of studies focused on BALF clinical specimens.

Details

ISSN :
15590275 and 15426416
Volume :
20
Database :
OpenAIRE
Journal :
Clinical Proteomics
Accession number :
edsair.doi.dedup.....d2721caddabb50126ff492ce2ca21c98