Protocol | Published:

Quantitative, multiplexed workflow for deep analysis of human blood plasma and biomarker discovery by mass spectrometry

Nature Protocols volume 12, pages 16831701 (2017) | Download Citation

Abstract

Proteomic characterization of blood plasma is of central importance to clinical proteomics and particularly to biomarker discovery studies. The vast dynamic range and high complexity of the plasma proteome have, however, proven to be serious challenges and have often led to unacceptable tradeoffs between depth of coverage and sample throughput. We present an optimized sample-processing pipeline for analysis of the human plasma proteome that provides greatly increased depth of detection, improved quantitative precision and much higher sample analysis throughput as compared with prior methods. The process includes abundant protein depletion, isobaric labeling at the peptide level for multiplexed relative quantification and ultra-high-performance liquid chromatography coupled to accurate-mass, high-resolution tandem mass spectrometry analysis of peptides fractionated off-line by basic pH reversed-phase (bRP) chromatography. The overall reproducibility of the process, including immunoaffinity depletion, is high, with a process replicate coefficient of variation (CV) of <12%. Using isobaric tags for relative and absolute quantitation (iTRAQ) 4-plex, >4,500 proteins are detected and quantified per patient sample on average, with two or more peptides per protein and starting from as little as 200 μl of plasma. The approach can be multiplexed up to 10-plex using tandem mass tags (TMT) reagents, further increasing throughput, albeit with some decrease in the number of proteins quantified. In addition, we provide a rapid protocol for analysis of nonfractionated depleted plasma samples analyzed in 10-plex. This provides 600 quantified proteins for each of the ten samples in 5 h of instrument time.

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Acknowledgements

We thank N. Udeshi for reading the manuscript and providing valuable feedback. This work was supported in part by grants from the National Institutes of Health: HHSN268201000033C and R01HL096738 from the National Heart, Lung, and Blood Institute (NHLBI; to S.A.C.) and grants U24CA160034 from the National Cancer Institute (NCI) Clinical Proteomics Tumor Analysis Consortium initiative and U01CA152990 from the NCI Early Detection Research Network program (to M.A.G.).

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Author notes

    • Hasmik Keshishian
    •  & Michael W Burgess

    These authors contributed equally to this work.

Affiliations

  1. Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA.

    • Hasmik Keshishian
    • , Michael W Burgess
    • , Harrison Specht
    • , Luke Wallace
    • , Karl R Clauser
    • , Michael A Gillette
    •  & Steven A Carr
  2. Massachusetts General Hospital, Boston, USA.

    • Michael A Gillette

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Contributions

H.K., M.W.B., H.S., K.R.C., M.A.G. and S.A.C. developed the protocol. L.W., M.W.B. and H.S. optimized and ran QC checks on many aspects of the protocol. H.K., M.W.B., H.S., K.R.C., M.A.G. and S.A.C. wrote the manuscript.

Competing interests

The authors declare no competing financial interests.

Corresponding authors

Correspondence to Hasmik Keshishian or Steven A Carr.

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DOI

https://doi.org/10.1038/nprot.2017.054

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