Proteomics pp 199-221 | Cite as

Pathway-Informed Discovery and Targeted Proteomic Workflows Using Mass Spectrometry

Part of the Methods in Molecular Biology book series (MIMB, volume 1550)


Recent advancements in mass spectrometry (MS) and data analysis software have enabled new strategies for biological discovery using proteomics. Proteomics has evolved from routine discovery and identification of proteins to integrated multi-omics projects relating specific proteins to their genes and metabolites. Using additional information, such as that contained in biological pathways, has enabled the use of targeted protein quantitation for monitoring fold changes in expression as well as biomarker discovery. Here we discuss a full proteomic workflow from discovery proteomics on a quadrupole Time-of-Flight (Q-TOF) MS to targeted proteomics using a triple quadrupole (QQQ) MS. A discovery proteomics workflow encompassing acquisition of data-dependent proteomics data on a Q-TOF and protein database searching will be described which uses the protein abundances from identified proteins for subsequent statistical analysis and pathway visualization. From the active pathways, a protein target list is created for use in a peptide-based QQQ assay. These peptides are used as surrogates for target protein quantitation. Peptide-based QQQ assays provide sensitivity and selectivity allowing rapid and robust analysis of large batches of samples. These quantitative results are then statistically compared and visualized on the original biological pathways with a more complete coverage of proteins in the studied pathways.

Key words

Mass spectrometry Proteomics QTOF QQQ Time-of-flight Quadrupole Proteins Informatics Data-dependent acquisition Protein quantitation 


  1. 1.
    Wong CC, Cociorva D, Miller CA et al (2013) Proteomics of Pyrococcus Furiosus (Pfu): identification of extracted proteins by three independent methods. J Proteome Res 12(2):763–770CrossRefPubMedPubMedCentralGoogle Scholar
  2. 2.
    Vaudel M, Burkhart JM, Breiter D et al (2012) A complex standard for protein identification, designed by evolution. J Proteome Res 11(10):5065–5071CrossRefPubMedGoogle Scholar
  3. 3.
    Yang Y, Bhat V, Miller CA. (2015) Jet Stream proteomics for sensitive and robust standard flow LC/MS. Agilent Technical Overview 5991-5687EN Accessed 31 August 2015
  4. 4.
    Miller CA, Jenkins S, Sana TR, et al. (2013) Proteomics in multi-omics workflows using yeast as a model system. Agilent Application Note 5991-2484EN 31 August 2015
  5. 5.
    Buckenmaier S, Mora J, van de GoorT, et al. (2012) Enhanced chromatography with the Agilent Polaris-HR-Chip-3C18 improved LC/MS/MS proteomics results. Agilent Technical Overview 5991-0735EN Accessed 31 August 2015
  6. 6.
    Percy AJ, Chambers AG, Borchers CH, (2014) Application kits for standardizing MRM-based quantitative plasma proteomic workflows on the Agilent 6490 LC/MS system. Agilent Application Note 5991-3601EN Accessed 31 August 2015
  7. 7.
    Percy AJ, Chambers AG, Yang J et al (2012) Comparison of standard-and nano-flow liquid chromatography platforms for MRM-based quantitation of putative plasma biomarker proteins. Anal Bioanal Chem 404(4):1089–1101CrossRefPubMedGoogle Scholar
  8. 8.
    Percy AJ, Mohammed Y, Yang J, Borchers CH (2015) A standardized kit for automated quantitative assessment of candidate protein biomarkers in human plasma. Bioanalysis, 7(23):2991–3004Google Scholar

Copyright information

© Springer Science+Business Media LLC 2017

Authors and Affiliations

  1. 1.Agilent Technologies, Inc.5301 Stevens Creek BlvdSanta ClaraUSA

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