Shotgun proteomic methods involving isobaric tagging of peptides enable high-throughput proteomic analysis. iTRAQ reagents allow simultaneous identification and quantitation of proteins in four different samples using tandem mass spectrometry (MS). In this article, we provide a brief description of proteome analysis using iTRAQ reagents and review the current applications of these reagents in proteomic studies. We also compare different aspects of protein identification including protein sequence coverage and proteome coverage obtained using iTRAQ reagents with those using other shotgun proteomic techniques. We briefly discuss the issue of isotope purity correction in measured peak areas during protein quantitation using iTRAQ reagents. Finally, we conclude with some of the current challenges in MS-based proteomic analysis that are limiting protein identifications obtained by different shotgun proteomic methods.

A comparison of the consistency of proteome quantitation using two-dimensional electrophoresis and shotgun isobaric tagging in Escherichia coli cellsAn important consideration in the measurement of quantitative changes in protein expression is the consistency of the observations for a given technique as well as the reproducibility of the experiment. A quantitative assessment of the technical and biological variability is crucial to avoid erroneous inferences and conclusions. Two methods for measuring quantitative changes in protein expression are two-dimensional electrophoresis (2-DE) and shotgun proteomics of isobaric-tagged samples using iTRAQ  reagents. An assessment of changes in Escherichia coli protein expression in response to rhsA induction demonstrates that half of the quantified protein expression ratios have a coefficent of variation (CV) less than 0.31 using 2-DE and less than 0.24 using isobaric tags; whereas 95% of the quantified protein expression ratios have a CV less than 0.81 using 2-DE and less than 0.53 using isobaric tags. The selective removal of outlier data points from the shotgun method using Grubb's and Rosner's statistical outlier tests improves the consistency of the quantitation data obtained.

Developments in high-throughput measurement technologies for biological molecules have created a paradigm shift in modern life science research. The field of systems biology attempts to provide a systems-level understanding by systematically organising the genomic, functional genomic and proteomic data obtained from genetic and environmental perturbations of interest and using the data to build a descriptive and mechanistic model of the biological phenomena. The goal is to build a mathematical framework with some predictive abilities. This review highlights the need for system-level understanding, lists some of the high-throughput measurement tools of importance in systems biology, reviews various types of experimental and computational approaches being used in systems biology research and attempts to address some of the challenges facing this research community.

We describe the use of amine-specific isobaric tags for protein expression quantification to study the effect of rhsA element over-expression in Escherichia coli. The use of an isobaric tagging strategy facilitates a shotgun approach to proteomic analysis and enables quantitation of up to four samples in parallel, based on the reporter ion series using tandem mass spectrometry (MS/MS). Using a liquid chromatography matrix-assisted laser desorption/ionization approach, 23,139 MS/MS spectra were collected. Five thousand sixty-three peptides derived from 780 proteins were quantified including several lower abundance proteins, such as transcription factors, DnaB and DnaG. More than 65% of the proteins had at least two high confidence peptide matches per protein (p<0.05). Further, a statistical test based on the Grubb's and Rosner's tests was able to discriminate outlier data. The removal of outlier data had no significant effect on the functional categories of proteins that were represented in the study.

Chest Research Foundation, Council of Scientific and Industrial Research-Institute of Genomics and Integrated Biology (CSIR-IGIB), and Cipla Ltd.