JXB Advance Access originally published online on March 30, 2006
Journal of Experimental Botany 2006 57(7):1501-1508; doi:10.1093/jxb/erj168
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
RESEARCH PAPER |
A perspective on the use of iTRAQTM reagent technology for protein complex and profiling studies
Applied Biosystems, 850 Lincoln Centre Drive, Foster City, CA 94404, USA
*E-mail: zieskelr{at}appliedbiosystems.com
Received 23 August 2005; Accepted 20 February 2006
| Abstract |
|---|
|
|
|---|
Proteomic research includes the characterization of protein mixtures in order to understand complex biological systems and determine relationships between proteins, their function, and proteinprotein interactions. Often the goal of such research is to monitor changes of proteins in perturbed systems, a type of study referred to as differential expression analysis. To perform these studies requires the ability to execute some type of differential comparison of a given protein state in reference to some type of a control. The iTRAQTM reagents are a set of isobaric reagents which are amine specific and allow for the identification and quantitation of up to four different samples simultaneously. The amine specificity of these reagents makes most peptides in a sample amenable to this labeling strategy with no loss of information from samples involving post-translational modifications, such as the scrutiny of signal transduction pathways that often involve phosphorylation phenomena. In addition, the multiplexing capacity of these reagents allows for information replication within certain LC-MS/MS experimental regimes, providing additional statistical validation within any given experiment. The results presented herein demonstrate a few examples of the wide variety of quantitative information that can be realized when undertaking such experimental approaches. These include temporal analysis of drug-induced-protein expression, discovery and elucidation of disease markers, and proteinprotein interactions in multi-protein complexes.
Key words: Differential expression, iTRAQ reagents, protein profiling, stable isotope labelling
| Introduction |
|---|
|
|
|---|
Quite often, in order to understand the function and/or interactions of proteins in biological systems, it is necessary to study the expression of these proteins in perturbed systems. These perturbations can be due to any variety of factors within a system, ranging from differences in growth conditions for micro-organisms to temporal differences at stages of a cell-cycle. External stimuli such as drug intervention for therapeutic studies can also alter expression levels when studying phenomena such as phosphorylation and signal transduction pathways when looking for protein markers as potential drug targets.
All these studies require the ability to perform some type of differential comparison of protein expression with reference to a control state. Although tools like nucleic acid microarrays are widely used to compare changes in gene expression levels between diseased and normal samples, these tools do not always tell the whole story. Whilst these data are useful, differences in gene expression do not necessarily correspond directly to differences in protein expression. Expression of proteins is heavily governed by the rate of transcription concomitant with rates of degradation not evidently obvious from mRNA levels. There is also considerable variability on protein concentration versus mRNA concentrations. In addition, many differential effects on proteins themselves come from post-translational modifications such as phosphorylation or glycosylation. These cannot be measured or identified by looking at the mRNA levels. In essence, proteins are effector molecules and therefore measuring these, as opposed to nucleic acid expression, will contribute to a better understanding of disease function/processes as well as drug treatment and therapeutics.
There are several technologies that exist today to assess more accurately protein levels between two biological states. The most frequently used approach utilizes the well-characterized 2D-gel technique, where differentially expressed spots are excised and analysed by mass spectrometry (MS). Not all types of proteins are amenable to gels and the dynamic range is somewhat limited and this method often falls short for low-abundance proteins. There are also chip-based MS approaches, which have a relatively higher throughput, but the actual identification of the proteins of interest is time-consuming, often relying on off-line techniques to purify the potential marker(s) implied by the qualitative information from the MS analyses. Chromatographic approaches also exist in order to assess protein differential expression levels, but are subject to diminished sample throughput as well as reproducibility between samples and replicates.
To overcome some of the shortcomings of the above approaches a number of advances involving stable isotope technology for quantitative profiling via mass spectrometry have been established. The most widely known is the ICAT (Isotope Coded Affinity Tags) approach developed by Reudi Aebersold and colleagues at the University of Washington, Seattle, in the late 1990s (Gygi et al., 1999), and later commercialized and developed into the cleavable ICAT® Reagents by Applied Biosystems. In this approach, two samples are labelled with chemically identical tags that differ only in isotopic composition (heavy and light pairs) and contain a thiol-reactive group (which covalently links to cysteine residues) and a biotin moiety. The samples are combined, enzymatically digested, and the labelled peptides are selectively enriched via biotin-avidin affinity chromatography. Because the ICAT-labelled peptide fragments differ in mass by a known amount, they can be separated, and quantified via mass spectrometry. By specifically labelling only cysteine residues of any given protein sample, complex samples are simplified, thus allowing the analysis of an increased dynamic range of peptides. In addition, as it is a solution-phase labelling, those proteins not amenable to 2D-gels, such as very acidic/basic, too large/small proteins can now be analysed using an LC-MS workflow.
The specificity of the ICAT reagents for cysteine residues, which significantly reduces the complexity of the sample and its resulting mass spectrum, is also one of its drawbacks. Because the ICAT reagents can only be used to analyse proteins that contain a cysteine residue, many important proteins, including those with post-translational modifications, are overlooked by this technique.
Another similar approach that involves comparative profiling of proteins in mammalian cells is Stable Isotope Labelling by Amino Acids in Cell Culture (SILAC), developed by Matthias Mann, of the University of Southern Denmark, and colleagues in 2002 (Ong et al., 2002), and recently commercialized by the InvitrogenTM Corporation. This method incorporates isotopic labels into proteins via metabolic labelling in the cell culture itself, rather than using a covalently linked tag. Thus, cell samples to be compared are grown separately in media containing either a heavy or light form of an essential amino acid (e.g. one that cannot be synthesized by the cell). The advantages of SILAC are that it has higher fidelity than ICAT (incorporating nearly 100% efficiency) and does not require multiple chemical processing and purification steps, thus ensuring that the samples to be compared have been subjected to similar conditions throughout the experiment. This approach, however, requires viable active cell lines to allow for the incorporation of the respective heavy/light amino acids into the protein samples and may not always be available for all experimental samples.
Despite the broad range of biological questions that the above approaches successfully address, there is still a need for technologies that can speak to issues such as global peptide labelling, retention of post-translational modification (PTM) information, and simultaneous multiplexed (more than two samples) analyses. The development of the iTRAQTM Reagents, a new class of isobaric reagents, by Darryl Pappin and colleagues at Applied Biosystems in 2004 (Ross et al., 2004) can be used for multiplexed protein profiling of up to four different samples. This unique approach labels samples with four independent reagents of the same mass that, upon fragmentation in MS/MS, give rise to four unique reporter ions (m/z =114117) that are subsequently used to quantify the four different samples, respectively.
| Multiplexed, isobaric stable isotope tags |
|---|
|
|
|---|
The reagents were designed as isobaric tags consisting of a charged reporter group that is unique to each of the four reagents, a peptide reactive group, and a neutral balance portion to maintain an overall mass of 145 (Fig. 1). These unique reagents, upon MS/MS fragmentation give rise to four unique reporter ions (m/z=114117) that are used to quantify their respective samples. MS/MS fragmentation, in addition to giving strong reporter ion signals, also yields strong signature y- and b- ions without changing the charge state of any given peptide to allow for more confident protein identification simultaneously with the quantification.
|
The peptide reactive group was designed to react with all primary amines, including the N-terminus and the
-amino group of the lysine side-chain, to label all peptides in up to four different biological samples thus enhancing peptide coverage for any given protein, while allowing for retention of other important structural information such as post-translational modifications (PTMs). The selection of the reporter region, Fig. 2, in the low mass area was selected for two primary reasons: (i) to keep the additive mass to the fragments as negligible as possible in order to minimize any effect in either the MS or MS/MS modes and (ii) to eliminate any interference with other immonium or fragment ions allowing for the highest degree of confidence in interpretation.
|
The general workflow is depicted in Fig. 3 for four different samples. Each individual sample is reduced, alkylated, and enzymatically digested with trypsin. The resulting peptide pool(s) are then labelled with one member of the multiplex set, respectively, in a parallel set of reactions and combined and subsequently analysed by LC-MS/MS.
|
The resultant mixture gives rise to a set of single unresolved additive precursor ions in MS, thus allowing for the enhancement of individual protein(s) that may be in low abundance in any given sample. Following collision-induced dissociation (CID) of the parent fragment produced in MS (e.g. MS/MS), the four reporter group ions appear as distinct masses between m/z 114117, while the remainder of the sequence informative y- and b- ions remain as additive isobaric signals.
| Results and discussion |
|---|
|
|
|---|
The following examples are included here to help demonstrate the effectiveness of the iTRAQ reagents and the flexibility they offer in experimental design. The examples include: (i) a temporal quantitation of mutant Kit tyrosine kinase signalling attenuated by a novel thiophene kinase inhibitor (Petti et al., 2005), (ii) the discovery and identification of cancer markers in endometrial carcinoma (DeSouza et al., 2005), and the determination and quantitation of proteins from affinity pull-downs in order to determine species involved in proteinprotein interactions.
Temporal quantitation
The effects of a drug candidate, OSI-930, on the Kit protein were studied over three time points (1, 4, and 24 h) referenced from time = 0 (Control). Figure 4A shows the reporter ion spectra of the phosphotyrosine-containing peptide from the combined multiplexed samples following exposure to the inhibitor, OSI-930. The reproducibility of this quantitation is also demonstrated in Fig. 4B. As all peptides are labelled using these reagents, multiple peptides per protein are used for both identification and quantitation of the given protein. Overall, there were 21 peptides used to identify the single Kit protein, each with quantitative data adding not only increased confidence in identity, but also statistical validation of the results. The phosphorylation-induced inhibition is associated with the phosphopeptide containing the phosphotyrosine residue in position 703 within the kinase domain of Kit and Fig. 5 shows the identification and quantitation of the Kit phosphopeptide over the time-course studied.
|
|
Because all peptides of the protein are labelled, the difference between changes in expression can be distinguished from changes in phosphorylation levels, thus enabling estimations on mechanisms of action. Proteins from equivalent cell populations isolated by phosphotyrosine capture, multiplexed over four time points, generated over 200 proteins that were identified and quantified. The retention of PTM information meant that drug inhibition of other phosphoproteins could also be studied. Several proteins involved in the Kit signal transduction pathway were also identified and quantified, such as MAPK (Erk) and Tyrosine protein kinase (SYK), supporting the suitability of this technique for pathway analyses (Petti et al., 2005).
Cancer markers in endometrial tissues
The work done by DeSouza et al. (2005) has led to a total of nine potential markers for endometrial cancer (EmCa) using a combination of analytical approaches. The search for markers in EmCa, however, presents a particularly difficult challenge due to the normal physiological variability in protein expression levels as a result of normal menstrual cycling. The iTRAQ reagents are particularly suited to this task as a result of their ability to multiplex and thus one can simultaneously analyse samples from both governing phases of the endometrial cycle, broadly classified as the proliferative and secretory phases.
The general workflow for multiplexing is shown in Fig. 6. Since normal endometrium consist of two phases according to the monthly cycle, there is a need not only to measure the differences between cancerous versus normal, but also to monitor any variations in the normal tissues dependent upon cycling.
|
Previous work (Yang et al., 2004) had shown that chaperonin 10, a heat shock protein, is a potential cancer marker via a MALDI/SELDI MS workflow followed by offline separation, preconcentration, trypsinization, and MS/MS. This particular marker was verified by applying the workflow indicated, using the iTRAQ reagents (Fig. 7).
|
Using a single approach, in this case, one could simultaneously quantify and identify the marker of interest. Conversely, the previous approach required a profiling approach via a chip-based technology that indicated change, yet yielded little information as to the identity of that change. Identity had to be determined separately, via the offline methodologies mentioned above. Interestingly enough, this particular marker does not contain a cysteine residue in its entire structure, therefore an approach involving enrichment of cysteine-containing peptides via cleavable ICAT reagent technology would have missed this important marker completely.
Protein interactions in multi-protein complexes
Systematic studies of proteinprotein interactions have been reported with Saccharomyces cerevisiae using a wide array of bait proteins to pull out interacting partners followed by tandem affinity purification method (Gavin et al., 2002; Ho et al., 2002). However, a significant number of non-specific interactors can still remain with the complex and cause a number of false positives. To improve the discrimination between true versus non-specific interactions of grb2 (Fig. 8) and to simplify the interpretation of the pull-down results, the iTRAQ reagents have been used to reduce the rate of false positives and achieve high throughput, automated workflows.
|
The use of the iTRAQ reagents permits the measurement of the relative quantitation with true specific interacting proteins as indicated by a singlet or a ratio heavily biased towards the heavy (m/z=116) reagent, in this case. Figure 9A shows an example of a typical true interaction. Conversely, non-specific interactions are indicated by doublets or proteins having ratios near 1:1 as shown in Fig. 9B for the protein carbonyl reductase.
|
As stated above, several peptides per protein can be used for both identification and quantitation, increasing the confidence and statistical relevance in the results. For example, 26 different peptides were used to determine the average protein quantitation ratio for dynamin 3, a true interactor. Using this strategy, many known true interactors to grb2 or grb2-complexes (from HeLa call lysates) as well as known non-specific interactors have been determined. In addition, a number of novel or unknown interactions were indicated and are under investigation.
| Conclusions |
|---|
|
|
|---|
The development of the iTRAQ reagents has expanded the ability to study differential expression of proteins in perturbed systems. They provide quantitative information from numerous experimental approaches including affinity pull-downs, time-course analyses, and discovery and elucidation of disease markers. Since most peptides in a sample are amenable to this labelling strategy, there is no loss of information from samples involving post-translation modifications such as the scrutiny of signal transduction pathways that often involve phosphorylation phenomena. In addition, the reagent labelling enhances MS/MS fragmentation thus giving more confident results than previously encountered, which is especially important in the identification and quantification of native non-tryptic peptides such as those found in saliva (Hardt et al., 2005), serum or plasma. Finally, the multiplexing capacity of these reagents allows information replication within certain LC-MS/MS experimental regimes, providing additional statistical validation within any given experiment.
| Acknowledgements |
|---|
I wish to thank Subhasish Purkayastha, Philip Ross, Tony Hunt, Sally Webb, and Darryl Pappin from Applied Biosystems, John Haley from OSI Pharmaceuticals, KW Michael Siu and Leroi DeSouza from York University, and John Peltier, Yuejun Zhen, and Justin Savage from Prolexys Pharmaceuticals for providing samples and data as well as stimulating discussion during the preparation of this perspective.
| References |
|---|
|
|
|---|
, , , , , , . . . , .Search for cancer markers from endometrial tissues using differentially labeled tags iTRAQ and cICAT with multidimensional liquid chromatography and tandem mass spectrometry. Journal of Proteome Research (2005) 4:377386.[CrossRef][Web of Science][Medline]
, , , et al. . . , .Functional organization of the yeast proteome by systematic analysis of protein complexes. Nature (2002) 415:141147.[CrossRef][Medline]
, , , , , . . . , .Quantitative analysis of complex protein mixtures using isotope-coded affinity tags. Nature Biotechnology (1999) 17:994999.[CrossRef][Web of Science][Medline]
, , , , , , . . . , .Assessing the effects of circadian rhythm on the composition of human parotid saliva: quantitative analysis of native peptides using iTRAQ reagents. Analytical Chemistry (2005) 77:49474954.[Medline]
, , , et al. . . , .Systematic identification of protein complexes in Saccharomyces cerevisiae by mass spectrometry. Nature (2002) 415:180183.[CrossRef][Medline]
, , , , , , . . . , .Stable isotope labeling by amino acids in cell culture, SILAC, as a simple and accurate approach to expression proteomics. Molecular and Cellular Proteomics (2002) 1:376386.
, , , et al. . . , .Temporal quantitation of mutant Kit tyrosine kinase signaling attenuated by a novel thiophene kinase inhibitor OSI-930. Molecular Cancer Therapy (2005) 4:11861197.[CrossRef]
, , , et al. . . , .Multiplexed protein quantitation in Saccharomyces cerevisiae using amine-reactive isobaric tagging reagents. Molecular and Cellular Proteomics (2004) 3:11541169.
, , , , , , , . . . , .Expression profiling of endometrial cancer malignancies reveals new tumor marker. Journal of Proteome Research (2004) 3:636643.[Medline]
![]()
CiteULike
Connotea
Del.icio.us What's this?
This article has been cited by other articles:
![]() |
S. Zhong, S. P. Miller, D. E. Dykhuizen, and A. M. Dean Transcription, Translation, and the Evolution of Specialists and Generalists Mol. Biol. Evol., December 1, 2009; 26(12): 2661 - 2678. [Abstract] [Full Text] [PDF] |
||||
![]() |
S. Kuromitsu, H. Yokota, M. Hiramoto, M. Yuri, M. Naitou, N. Nakamura, S. Kawabata, M. Kobori, M. Katoh, K. Furuchi, et al. Combination of MS Protein Identification and Bioassay of Chromatographic Fractions to Identify Biologically Active Substances from Complex Protein Sources Mol. Cell. Proteomics, June 1, 2009; 8(6): 1318 - 1323. [Abstract] [Full Text] [PDF] |
||||
![]() |
A. Nilsson, M. Falth, X. Zhang, K. Kultima, K. Skold, P. Svenningsson, and P. E. Andren Striatal Alterations of Secretogranin-1, Somatostatin, Prodynorphin, and Cholecystokinin Peptides in an Experimental Mouse Model of Parkinson Disease Mol. Cell. Proteomics, May 1, 2009; 8(5): 1094 - 1104. [Abstract] [Full Text] [PDF] |
||||
![]() |
C.-M. Lee, J. Pohl, and E. T. Morgan Dual Mechanisms of CYP3A Protein Regulation by Proinflammatory Cytokine Stimulation in Primary Hepatocyte Cultures Drug Metab. Dispos., April 1, 2009; 37(4): 865 - 872. [Abstract] [Full Text] [PDF] |
||||
![]() |
M. Zhu, S. Dai, S. McClung, X. Yan, and S. Chen Functional Differentiation of Brassica napus Guard Cells and Mesophyll Cells Revealed by Comparative Proteomics Mol. Cell. Proteomics, April 1, 2009; 8(4): 752 - 766. [Abstract] [Full Text] [PDF] |
||||
![]() |
P. Dai, S. Y. Jeong, Y. Yu, T. Leng, W. Wu, L. Xie, and X. Chen Modulation of TLR Signaling by Multiple MyD88-Interacting Partners Including Leucine-Rich Repeat Fli-I-Interacting Proteins J. Immunol., March 15, 2009; 182(6): 3450 - 3460. [Abstract] [Full Text] [PDF] |
||||
![]() |
L. M. Chen, B. N. Tran, Q. Lin, T. K. Lim, F. Wang, and C.-L. Hew iTRAQ analysis of Singapore grouper iridovirus infection in a grouper embryonic cell line J. Gen. Virol., November 1, 2008; 89(11): 2869 - 2876. [Abstract] [Full Text] [PDF] |
||||
![]() |
S. P. Mirza and M. Olivier Methods and approaches for the comprehensive characterization and quantification of cellular proteomes using mass spectrometry Physiol Genomics, October 8, 2008; 33(1): 3 - 11. [Abstract] [Full Text] [PDF] |
||||
![]() |
U. Kruse, M. Bantscheff, G. Drewes, and C. Hopf Chemical and Pathway Proteomics: Powerful Tools for Oncology Drug Discovery and Personalized Health Care Mol. Cell. Proteomics, October 1, 2008; 7(10): 1887 - 1901. [Abstract] [Full Text] [PDF] |
||||
![]() |
W. Majeran, B. Zybailov, A. J. Ytterberg, J. Dunsmore, Q. Sun, and K. J. van Wijk Consequences of C4 Differentiation for Chloroplast Membrane Proteomes in Maize Mesophyll and Bundle Sheath Cells Mol. Cell. Proteomics, September 1, 2008; 7(9): 1609 - 1638. [Abstract] [Full Text] [PDF] |
||||
![]() |
K.-S. Park, J.-W. Yang, E. Seikel, and J. S. Trimmer Potassium Channel Phosphorylation in Excitable Cells: Providing Dynamic Functional Variability to a Diverse Family of Ion Channels Physiology, February 1, 2008; 23(1): 49 - 57. [Abstract] [Full Text] [PDF] |
||||
![]() |
J. Patterson, K. Ford, A. Cassin, S. Natera, and A. Bacic Increased Abundance of Proteins Involved in Phytosiderophore Production in Boron-Tolerant Barley Plant Physiology, July 1, 2007; 144(3): 1612 - 1631. [Abstract] [Full Text] [PDF] |
||||
![]() |
M. Jiang, S. M. Sullivan, A. K. Walker, J. R. Strahler, P. C. Andrews, and J. R. Maddock Identification of Novel Escherichia coli Ribosome-Associated Proteins Using Isobaric Tags and Multidimensional Protein Identification Techniques J. Bacteriol., May 1, 2007; 189(9): 3434 - 3444. [Abstract] [Full Text] [PDF] |
||||
![]() |
P. A. D. Champion, S. A. Stanley, M. M. Champion, E. J. Brown, and J. S. Cox C-terminal signal sequence promotes virulence factor secretion in Mycobacterium tuberculosis. Science, September 15, 2006; 313(5793): 1632 - 1636. [Abstract] [Full Text] [PDF] |
||||
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||


















