Literature DB >> 29083196

Highly Reproducible Automated Proteomics Sample Preparation Workflow for Quantitative Mass Spectrometry.

Qin Fu1, Michael P Kowalski2, Mitra Mastali1, Sarah J Parker1, Kimia Sobhani3, Irene van den Broek1, Christie L Hunter4, Jennifer E Van Eyk1.   

Abstract

Sample preparation for protein quantification by mass spectrometry requires multiple processing steps including denaturation, reduction, alkylation, protease digestion, and peptide cleanup. Scaling these procedures for the analysis of numerous complex biological samples can be tedious and time-consuming, as there are many liquid transfer steps and timed reactions where technical variations can be introduced and propagated. We established an automated sample preparation workflow with a total processing time for 96 samples of 5 h, including a 2 h incubation with trypsin. Peptide cleanup is accomplished by online diversion during the LC/MS/MS analysis. In a selected reaction monitoring (SRM) assay targeting 6 plasma biomarkers and spiked β-galactosidase, mean intraday and interday cyclic voltammograms (CVs) for 5 serum and 5 plasma samples over 5 days were <20%. In a highly multiplexed SRM assay targeting more than 70 proteins, 90% of the transitions from 6 plasma samples repeated on 3 separate days had total CVs below 20%. Similar results were obtained when the workflow was transferred to a second site: 93% of peptides had CVs below 20%. An automated trypsin digestion workflow yields uniformly processed samples in less than 5 h. Reproducible quantification of peptides was observed across replicates, days, instruments, and laboratory sites, demonstrating the broad applicability of this approach.

Entities:  

Keywords:  automation; high throughput; liquid chromatography selected reaction monitoring; liquid chromatography-tandem mass spectrometry; protein sample preparation; reproducibility

Mesh:

Substances:

Year:  2017        PMID: 29083196      PMCID: PMC6845026          DOI: 10.1021/acs.jproteome.7b00623

Source DB:  PubMed          Journal:  J Proteome Res        ISSN: 1535-3893            Impact factor:   4.466


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