iTRAQ Experimental Design for Plasma Biomarker Discovery Xiaomin Song, † Julia Bandow, ‡ Jamie Sherman, † J. David Baker, ‡ Paul W. Brown, § Michael T. McDowell, ‡ and Mark P. Molloy* ,†,| Australian Proteome Analysis Facility Ltd., Macquarie University, Sydney, Australia, Pfizer Global Research and Development, Ann Arbor, Michigan, 48105, Pfizer Global Research and Development, St. Louis, Missouri, 63006, and Department of Chemistry & Biomolecular Sciences, Macquarie University, Sydney, Australia Received January 30, 2008 There is considerable interest in using mass spectrometry for biomarker discovery in human blood plasma. We investigated aspects of experimental design for large studies that require analysis of multiple sample sets using iTRAQ reagents for sample multiplexing and quantitation. Immunodepleted plasma samples from healthy volunteers were compared to immunodepleted plasma from patients with osteoarthritis in eight separate iTRAQ experiments. Our analyses utilizing ProteinPilot software for peptide identification and quantitation showed that the methodology afforded excellent reproducibility from run to run for determining protein level ratios (coefficient of variation 11.7%), in spite of considerable quantitative variances observed between different peptides for a given protein. Peptides with high variances were associated with lower intensity iTRAQ reporter ions, while immunodepletion prior to sample analysis had a negligible affect on quantitative variance. We examined the influence of different reference samples, such as pooled samples or individual samples on calculating quantitative ratios. Our findings are discussed in the context of optimizing iTRAQ experimental design for robust plasma-based biomarker discovery. Keywords: mass spectrometry • plasma • biomarker • quantitation • experimental design Introduction Several different mass spectrometry (MS) approaches have been described for conducting comparative quantitative pro- teomics. Commonly, these approaches employ protein/peptide labeling strategies to enable relative sample quantitation, although some nonlabeling approaches have also been de- scribed. 1–4 The three most widespread approaches for protein/ peptide labeling are chemical derivatization (e.g., Isotope coded affinity tags (ICAT) and Isobaric Tags for Relative and Absolute Quantitation (iTRAQ) 5,6 ), metabolic labeling (e.g., Stable isotope labeling of amino acids in culture (SILAC) 7,8 ) and enzymatic labeling during protein digestion using deuterated water. 9,10 iTRAQ is a chemical labeling approach that incorporates stable isotopes into an NHS-ester derivative amine tagging reagent that, when combined with mass spectrometry, allows com- parative, quantitative multiplexing analysis. In this study, we used the 4-plex iTRAQ reagent kit. Recently, an 8-plexed version of the iTRAQ reagents was introduced. Each protein sample is proteolytically digested with trypsin, labeled with one of the isobaric tags, mixed with the other different iTRAQ labeled samples, and analyzed by tandem mass spectrometry (MS/MS). Proteins are identified using the peptide product ion spectra and are quantified by the relative intensities of the 4-plex iTRAQ reporter ions detected in the 114-117 m/z region of the product ion spectra. At least one of the labeled samples is a reference sample allowing the relative quantities of each peptide in comparative samples to be determined as a ratio of the quantity of the same peptide in the reference sample. A scoring function is then used to determine the weighting contribution of each peptide ratio toward the final protein ratio. 11 iTRAQ is ideally suited for biomarker applications as it provides both quantitation and multiplexing in a single reagent and has been applied to the analysis of clinical samples such as human blood serum or plasma, cerebrospinal fluid, disease tissues, or for in vitro profiling of cells to identify differentially expressed proteins. 12–14 The experimental design of a large-scale biomarker discovery experiment weighs heavily toward its success, requiring a great deal of strategic consideration and planning. For iTRAQ experi- ments, some key variables that require consideration include sample size based on the degree of technical and biological variation, the type and composition of the reference sample, and whether sample pooling is a viable option. Currently, there is a lack of comprehensive information in the literature regarding these issues. Of the few available technical reports, Wu et al. 15 compared DIGE, ICAT, and iTRAQ to show that iTRAQ is the most sensitive proteomics quantitation method among the three techniques evaluated, based on the number of detected peptides. They used six standard proteins to determine quantitative reproducibility for iTRAQ experiments and reported standard deviations (SD) in the range of 0.088-0.145. Gan et al. 16 recently used cell lysate samples and * To whom correspondence should be addressed. Mark P. Molloy, Ph.D., Tel, +612 9850 6218; fax, +612 9850 6200; e-mail, mmolloy@proteome.org.au. † Australian Proteome Analysis Facility Ltd., Macquarie University. ‡ Pfizer Global Research and Development, Ann Arbor, MI. § Pfizer Global Research and Development, St. Louis, MO. | Department of Chemistry & Biomolecular Sciences, Macquarie University. 2952 Journal of Proteome Research 2008, 7, 2952–2958 10.1021/pr800072x CCC: $40.75  2008 American Chemical Society Published on Web 06/13/2008