Multi-laboratory assessment of reproducibility, qualitative and quantitative performance of SWATH-mass spectrometry
Ben C. Collins,
Christie L Hunter,
Samuel L Bader,
Daniel W Chan,
Bradford W. Gibson,
Jason M Held,
Mark P Molloy,
Robert L. Moritz,
Stefani N. Thomas,
Posted 14 Sep 2016
bioRxiv DOI: 10.1101/074567 (published DOI: 10.1038/s41467-017-00249-5)
Posted 14 Sep 2016
Quantitative proteomics employing mass spectrometry has become an indispensable tool in basic and applied life science research. Methods based on data-dependent acquisition have proved extremely valuable for qualitative proteome analysis but historically have struggled to achieve reproducible quantitative data if large sample cohorts are comparatively analyzed. Targeted proteomics, most commonly implemented as selected reaction monitoring, has emerged as a powerful alternative and succeeded in providing a data independent approach for reproducible quantitative proteomics data but is limited in the number of proteins quantified. SWATH-MS is a recently introduced technique consisting of a data-independent acquisition and a targeted data analysis strategy that aims to maintain the favorable quantitative characteristics (accuracy, sensitivity, specificity) achieved in targeted proteomics but on the scale of thousands of proteins. While previous SWATH-MS studies have shown high intra-lab reproducibility, this has not been evaluated on an inter-lab basis. In this multi-laboratory evaluation study using data from 11 sites worldwide, we have demonstrated that using SWATH-MS we can consistently detect and quantify more than 4,000 proteins from HEK293 cells and that the quantitative protein data generated across laboratories is reproducible. Using synthetic peptide dilution series, we have shown that the sensitivity, dynamic range and reproducibility established with SWATH-MS methods are also uniformly achieved across labs. This study demonstrates that SWATH-MS is a reproducible and accurate technique that can be confidently deployed for large-scale protein quantification in life science research.
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