We assess the reliability of isobaric-tags for relative and absolute quantitation (iTRAQ), based on different types of replicate analyses taking into account technical, experimental, and biological variations. In total, 10 iTRAQ experiments were analyzed across three domains of life involving Saccharomyces cerevisiae KAY446, Sulfolobus solfataricus P2, and Synechocystis sp. PCC 6803. The coverage of protein expression of iTRAQ analysis increases as the variation tolerance increases. In brief, a cutoff point at +/-50% variation (+/-0.50) would yield 88% coverage in quantification based on an analysis of biological replicates. Technical replicate analysis produces a higher coverage level of 95% at a lower cutoff point of +/-30% variation. Experimental or iTRAQ variations exhibit similar behavior as biological variations, which suggest that most of the measurable deviations come from biological variations. These findings underline the importance of replicate analysis as a validation tool and benchmarking technique in protein expression analysis.

We analyzed 10 isobaric tags for relative and absolute quantitation (iTRAQ) experiments using three different model organisms across the domains of life: Saccharomyces cerevisiae KAY446, Sulfolobussolfataricus P2, and Synechocystis sp. PCC6803. A double database search strategy was employed to minimize the rate of false positives to less than 3% for all organisms. The reliability of proteins with single-peptide identification was also assessed using the search strategy, coupled with multiple analyses of samples into LC-MS/MS. The outcomes of the three LC-MS/MS analyses provided higher proteome coverage with an average increment in total proteins identified of 6%, 33%, and 50% found in S. cerevisiae, S. solfataricus, and Synechocystis sp., respectively. The iTRAQ quantification values were found to be highly reproducible across the injections, with an average coefficient of variation (CV) of 0.09 (scattering from 0.14 to 0.04) calculated based on log mean average ratio for all three organisms. Hence, we recommend multiple analyses of iTRAQ samples for greater proteome coverage and precise quantification.

To identify novel tyrosine kinase substrates that have never been implicated in cancer, we studied the phosphoproteomic changes in the MCF10AT model of breast cancer progression using a combination of phosphotyrosyl affinity enrichment, iTRAQ TM technology, and LC-MS/MS. Using complementary MALDI-and ESI-based mass spectrometry, 57 unique proteins comprising tyrosine kinases, phosphatases, and other signaling proteins were detected to undergo differential phosphorylation during disease progression. Seven of these proteins (SPAG9, Toll-interacting protein (TOLLIP), WBP2, NSFL1C, SLC4A7, CYFIP1, and RPS2) were validated to be novel tyrosine kinase substrates. SPAG9, TOLLIP, WBP2, and NSFL1C were further proven to be authentic targets of epidermal growth factor signaling and Iressa (gefitinib). A closer examination revealed that the expression of SLC4A7, a bicarbonate transporter, was down-regulated in 64% of the 25 matched normal and tumor clinical samples. The expression of TOLLIP in clinical breast cancers was heterogeneous with 25% showing higher expression in tumor compared with normal tissues and 35% showing the reverse trend. Preliminary studies on SPAG9, on the other hand, did not show differential expression between normal and diseased states. This is the first time SLC4A7 and TOLLIP have been discovered as novel tyrosine kinase substrates that are also associated with human cancer development. Future molecular and functional studies will provide novel insights into the roles of TOLLIP and SLC4A7 in the molecular etiology of breast cancer.

Interethnic difference in VKORC1 haplotypes accounts for the difference in warfarin requirements between Chinese, Malays, and Indians, providing interesting insights into genetic variation between ethnogeographically distinct Asian groups.