iTRAQ underestimation in simple and complex mixtures: "The good, the bad and the ugly"

Yen Ow Saw, Malinda Salim, Josselin Noirel, Caroline Evans Evans, Ishtiaq Rehman, Phillip C. Wright

Research output: Contribution to journalArticleResearchpeer-review

360 Citations (Scopus)


The increasing popularity of iTRAQ for quantitative proteomics applications makes it necessary to evaluate its relevance, accuracy, and precision for biological interpretation. Here, we have assessed (a) the accuracy and precision of iTRAQ quantification in a controlled experimental setup, using low-and high-complexity protein mixtures; and (b) the potential pitfalls that hamper the applicability and attainable dynamic range of iTRAQ: isotopic contamination, background interference, and signal-to-noise ratio. Our data suggest greater dynamic crosstalk between interfering factors affecting underestimations, and that these interferences were largely scenario-specific, dependent on sample complexity. The good is the potential for iTRAQ to provide accurate quantification spanning 2 orders of magnitude. This potential is however limited by two factors. (1) The bad: the existence of isotopic impurities that can be corrected for; provided accurate isotopic factors are at one's disposal. (2) The ugly: we demonstrate here the interference of mixed MS/MS contribution occurring during precursor selection, an issue that is currently very difficult to minimize. In light of our results, we propose a list of advice for iTRAQ data analysis that could routinely ameliorate quantitative interpretation of proteomic data sets.

Original languageEnglish
Pages (from-to)5347-5355
Number of pages9
JournalJournal of Proteome Research
Issue number11
Publication statusPublished - 6 Nov 2009
Externally publishedYes


  • High-throughput proteomics
  • iTRAQ
  • iTRAQ underestimations
  • Quantitative proteomics

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