Analysis of intrinsic peptide detectability via integrated label-free and SRM-based absolute quantitative proteomics

Research output: Contribution to journalArticle

  • External authors:
  • Andrew Jarnuczak
  • Dave Lee
  • Craig Lawless
  • Stephen W Holman
  • Claire E Eyers


Quantitative mass spectrometry-based proteomics of complex biological samples remains challenging, in part due to the variability and charge competition arising during electrospray ionization (ESI) of peptides and the subsequent transfer and detection of ions. These issues preclude direct quantification from signal intensity alone in the absence of a standard. A deeper understanding of the governing principles of peptide ionisation, and exploitation of the inherent ionisation and detection parameters of individual peptides is thus of great value. Here, using the yeast proteome as a model system, we establish the concept of peptide F-factor as a measure of detectability, closely related to ionization efficiency. F-factor is calculated by normalising peptide precursor ion intensity by absolute abundance of the parent protein. We investigated F-factor characteristics in different shotgun proteomics experiments, including across multiple ESI-based LC-MS platforms. We show that F-factors mirror previously observed physicochemical predictors as peptide detectability, but demonstrate a non-linear relationship between hydrophobicity and peptide detectability. Similarly, we use F-factors to show how peptide ion co-elution adversely affects detectability and ionisation. We suggest that F-factors have great utility for understanding peptide detectability and gas-phase ion chemistry in complex peptide mixtures, selection of surrogate peptides in targeted MS studies, and for calibration of peptide ion signal in label-free workflows. Data are available via ProteomeXchange with identifier PXD003472.

Bibliographical metadata

Original languageEnglish
Pages (from-to)2945–2959
Number of pages15
JournalJournal of Proteome Research
Issue number9
StatePublished - 25 Jul 2016