Highly Reproducible Automated Proteomics Sample Preparation Workflow for Quantitative Mass Spectrometry

Area of Science:

• Biochemistry
• Analytical Chemistry
• Proteomics

Background:

• Protein quantification via mass spectrometry involves complex, time-consuming sample preparation steps.
• Manual processing introduces technical variability, hindering scalability for large sample sets.

Purpose of the Study:

• To develop and validate an automated sample preparation workflow for mass spectrometry-based protein quantification.
• To assess the reproducibility and scalability of the automated workflow across various conditions.

Main Methods:

• Established an automated workflow encompassing denaturation, reduction, alkylation, and trypsin digestion.
• Integrated online peptide cleanup during LC/MS/MS analysis.
• Validated the workflow using selected reaction monitoring (SRM) assays with plasma and serum samples.

Main Results:

• Achieved a total processing time of 5 hours for 96 samples, including a 2-hour trypsin digestion.
• Demonstrated high reproducibility with <20% coefficient of variation (CV) for intraday and interday assays.
• Confirmed workflow performance with >90% of peptides showing <20% CV across replicates, days, and between two laboratory sites.

Conclusions:

• The automated trypsin digestion workflow provides uniformly processed samples efficiently.
• The approach ensures reproducible peptide quantification, proving its broad applicability in diverse laboratory settings.