Sample collection and handling considerations for peptidomic studies in whole saliva; implications for biomarker discovery

Ebbing P. de Jong, Susan K. van Riper, Joseph S. Koopmeiners, John V. Carlis, Timothy J. Griffin

Research output: Contribution to journalArticlepeer-review

34 Scopus citations


Background: Proteomic studies in saliva have demonstrated its potential as a diagnostic biofluid, however the salivary peptidome is less studied. Here we study the effects of several sample collection and handling factors on salivary peptide abundance levels. Methods: Salivary peptides were isolated using an ultrafiltration device and analyzed by tandem mass spectrometry. A panel of 41 peptides common after various treatments were quantified and normalized. We evaluated the effects of freezing rate of the samples, nutritional status of the donors (fed vs. fasted), and room-temperature sample degradation on peptide abundance levels. Repeatability of our sample processing method and our instrumental analysis method were investigated. Results: Increased sample freezing rate produced higher levels of peptides. Donor nutritional status had no influence on the levels of measured peptides. No significant difference was detected in donors' saliva following 5, 10 and 15. min of room-temperature degradation. Sample processing and instrumental variability were relatively small, with median CVs of 9.6 and 6.6. Conclusions: Peptide abundance levels in saliva are rather forgiving towards variations in sample handling and donor nutritional status. Differences in freezing methods may affect peptide abundance, so consistency in freezing samples is preferred. Our results are valuable for standardizing sample collection and handling methods for peptidomic-based biomarker studies in saliva.

Original languageEnglish (US)
Pages (from-to)2284-2288
Number of pages5
JournalClinica Chimica Acta
Issue number23-24
StatePublished - Nov 20 2011

Bibliographical note

Funding Information:
This research was funded in part by NIH grant 1R01DE017734 . We also thank Dr. Matthew Stone and the Center for Mass Spectrometry and Proteomics for instrumental support and maintenance and the Minnesota Supercomputing Institute for computational proteomics support.


  • Normalization LC-MS/MS
  • Peptidomics
  • Saliva
  • Sample handling
  • Stability


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