Simultaneous analysis of relative protein expression levels across multiple samples using iTRAQ isobaric tags with 2D nano LC-MS/MS

In this paper, we describe the use of iTRAQ (isobaric Tags for Relative and Absolute Quantitation) tags for comparison of protein expression levels between multiple samples. These tags label all peptides in a protein digest before labeled samples are pooled, fractionated and analyzed using mass spectrometry (MS). As the tags are isobaric, the intensity of each peak is the sum of the intensity of this peptide from all samples, providing a moderate enhancement in sensitivity. On peptide fragmentation, amino-acid sequence ions also show this summed intensity, providing a sensitivity enhancement. However, the distinct distribution of isotopes in the tags is such that, on further fragmentation, a tag-specific reporter ion is released. The relative intensities of these ions represent the relative amount of peptide in the analytes. Integration of the relative quantification data for the peptides allows relative quantification of the protein. This protocol discusses the rationale behind design, optimization and performance of experiments, comparing protein samples using iTRAQ chemistries combined with strong cation exchange chromatographic fractionation and MS.     

Isobaric Labeling and Data Normalization without Requiring Protein Quantitation

Isobaric multiplexed quantitative proteomics can complement high-resolution sample isolation techniques. Here, we report a simple workflow exponentially modified protein abundance index (emPAI)-MW deconvolution (EMMOL) for normalizing isobaric reporter ratios within and between experiments, where small or unknown amounts of protein are used. EMMOL deconvolutes the isobaric tags for relative and absolute quantification (iTRAQ) data to yield the quantity of each protein of each sample in the pool, a new approach that enables the comparison of many samples without including a channel of reference standard. Moreover, EMMOL allows using a sufficient quantity of control sample to facilitate the peptide fractionation (isoelectric-focusing was used in this report), and mass spectrometry MS/MS sequencing yet relies on the broad dynamic range of iTRAQ quantitation to compare relative protein abundance. We demonstrated EMMOL by comparing four pooled samples with 20-fold range differences in protein abundance and performed data normalization without using prior knowledge of the amounts of proteins in each sample, simulating an iTRAQ experiment without protein quantitation prior to labeling. We used emPAI,¹ the target protein MW, and the iTRAQ reporter ratios to calculate the amount of each protein in each of the four channels. Importantly, the EMMOL-delineated proteomes from separate iTRAQ experiments can be assorted for comparison without using a reference sample. We observed no compression of expression in iTRAQ ratios over a 20-fold range for all protein abundances. To complement this ability to analyze minute samples, we report an optimized iTRAQ labeling protocol for using 5 μg protein as the starting material.     

Optimization of iTRAQ labelling coupled to OFFGEL fractionation as a proteomic workflow to the analysis of microsomal proteins of Medicago truncatula roots

Background

Shotgun proteomics represents an attractive technical framework for the study of membrane proteins that are generally difficult to resolve using two-dimensional gel electrophoresis. The use of iTRAQ, a set of amine-specific isobaric tags, is currently the labelling method of choice allowing multiplexing of up to eight samples and the relative quantification of multiple peptides for each protein. Recently the hyphenation of different separation techniques with mass spectrometry was used in the analysis of iTRAQ labelled samples. OFFGEL electrophoresis has proved its effectiveness in isoelectric point-based peptide and protein separation in solution. Here we describe the first application of iTRAQ-OFFGEL-LC-MS/MS on microsomal proteins from plant material. The investigation of the iTRAQ labelling effect on peptide electrofocusing in OFFGEL fractionator was carried out on Medicago truncatula membrane protein digests.

Results

In-filter protein digestion, with easy recovery of a peptide fraction compatible with iTRAQ labelling, was successfully used in this study. The focusing quality in OFFGEL electrophoresis was maintained for iTRAQ labelled peptides with a higher than expected number of identified peptides in basic OFFGEL-fractions. We furthermore observed, by comparing the isoelectric point (pI) fractionation of unlabelled versus labelled samples, a non-negligible pI shifts mainly to higher values.

Conclusions

The present work describes a feasible and novel protocol for in-solution protein digestion in which the filter unit permits protein retention and buffer removal. The data demonstrates an impact of iTRAQ labelling on peptide electrofocusing behaviour in OFFGEL fractionation compared to their native counterpart by the induction of a substantial, generally basic pI shift. Explanations for the occasionally observed acidic shifts are likewise presented.     

Virtual Expert Mass Spectrometrist: iTRAQ tool for database‐dependent search,quantitation and result storage

A frequent goal of MS‐based proteomics experiments nowadays is to quantify changes in the abundance of proteins across several biological samples. The iTRAQ labeling method is a powerful technique; when combined with LC coupled to MS/MS it allows relative quantitation of up to eight different samples simultaneously. Despite the usefulness of iTRAQ current software solutions have limited functionality and require the combined use of several software programs for analysis of the data from different MS vendors. We developed an integrated tool, now available in the virtual expert mass spectrometrist (VEMS) program, for database‐dependent search of MS/MS spectra, quantitation and database storage for iTRAQ‐labeled samples. VEMS also provides useful alternative report types for large‐scale quantitative experiments. The implemented statistical algorithms build on quantitative algorithms previously used in proposed iTRAQ tools as described in detail herein. We propose a new algorithm, which provides more accurate peptide ratios for data that show an intensity‐dependent saturation. The accuracy of the proposed iTRAQ algorithm and the performance of VEMS are demonstrated by comparing results from VEMS, MASCOT and PEAKS Q obtained by analyzing data from a reference mixture of six proteins. Users can download VEMS and test data from “ http://www.portugene.com/software.html ”.     

A quantitative proteomic analysis of biofilm adaptation by the periodontal pathogen Tannerella forsythia

Tannerella forsythia is a Gram‐negative anaerobe that is one of the most prominent inhabitants of the sub‐gingival plaque biofilm, which is crucial for causing periodontitis. We have used iTRAQ proteomics to identify and quantify alterations in global protein expression of T. forsythia during growth in a biofilm. This is the first proteomic study concentrating on biofilm growth in this key periodontal pathogen, and this study has identified several changes in protein expression. Moreover, we introduce a rigorous statistical method utilising peptide‐level intensities of iTRAQ reporters to determine which proteins are significantly regulated. In total, 348 proteins were identified and quantified with the expression of 44 proteins being significantly altered between biofilm and planktonic cells. We identified proteins from all cell compartments, and highlighted a marked upregulation in the relative abundances of predicted outer membrane proteins in biofilm cells. These included putative transport systems and the T. forsythia S‐layer proteins. These data and our finding that the butyrate production pathway is markedly downregulated in biofilms indicate possible alterations in host interaction capability. We also identified upregulation of putative oxidative stress response proteins, and showed that biofilm cells are 10 to 20 fold more resistant to oxidative stress. This may represent an important adaptation of this organism to prolonged persistence and immune evasion in the oral cavity.     

Isobaric protein and peptide quantification: perspectives and issues

An important challenge for proteomics is the ability to compare protein levels across biological samples. Since their introduction, isotopic and isobaric peptide labeling have played an important role in relative quantitative comparisons of proteomes. One important drawback of most of the isotopic-labeling techniques is an increase in sample complexity. This problem was successfully addressed with the construction of isobaric labeling strategies, such as isobaric tag for relative and absolute quantification (iTRAQ), tandem mass tagging, the cleavable isobaric affinity tag, dimethylated leucines and isobaric peptide termini labeling. Furthermore, numerous applications for multiplexing using iTRAQ and tandem mass tagging have been reported.     

Isobaric protein and peptide quantification: perspectives and issues

An important challenge for proteomics is the ability to compare protein levels across biological samples. Since their introduction, isotopic and isobaric peptide labeling have played an important role in relative quantitative comparisons of proteomes. One important drawback of most of the isotopic-labeling techniques is an increase in sample complexity. This problem was successfully addressed with the construction of isobaric labeling strategies, such as isobaric tag for relative and absolute quantification (iTRAQ), tandem mass tagging, the cleavable isobaric affinity tag, dimethylated leucines and isobaric peptide termini labeling. Furthermore, numerous applications for multiplexing using iTRAQ and tandem mass tagging have been reported.     

Mixed-effects statistical model for comparative LC-MS proteomics studies

Comparing a protein's concentrations across two or more treatments is the focus of many proteomics studies. A frequent source of measurements for these comparisons is a mass spectrometry (MS) analysis of a protein's peptide ions separated by liquid chromatography (LC) following its enzymatic digestion. Alas, LC-MS identification and quantification of equimolar peptides can vary significantly due to their unequal digestion, separation, and ionization. This unequal measurability of peptides, the largest source of LC-MS nuisance variation, stymies confident comparison of a protein's concentration across treatments. Our objective is to introduce a mixed-effects statistical model for comparative LC-MS proteomics studies. We describe LC-MS peptide abundance with a linear model featuring pivotal terms that account for unequal peptide LC-MS measurability. We advance fitting this model to an often incomplete LC-MS data set with REstricted Maximum Likelihood (REML) estimation, producing estimates of model goodness-of-fit, treatment effects, standard errors, confidence intervals, and protein relative concentrations. We illustrate the model with an experiment featuring a known dilution series of a filamentous ascomycete fungus Trichoderma reesei protein mixture. For 781 of the 1546 T. reesei proteins with sufficient data coverage, the fitted mixed-effects models capably described the LC-MS measurements. The LC-MS measurability terms effectively accounted for this major source of uncertainty. Ninety percent of the relative concentration estimates were within 0.5-fold of the true relative concentrations. Akin to the common ratio method, this model also produced biased estimates, albeit less biased. Bias decreased significantly, both absolutely and relative to the ratio method, as the number of observed peptides per protein increased. Mixed-effects statistical modeling offers a flexible, well-established methodology for comparative proteomics studies integrating common experimental designs with LC-MS sample processing plans. It favorably accounts for the unequal LC-MS measurability of peptides and produces informative quantitative comparisons of a protein's concentration across treatments with objective measures of uncertainties.     

iTRAQ is a useful method to screen for membrane-bound proteins differentially expressed in human natural killer cell types

We are interested in the biological as well as the molecular processes involved in natural killer (NK) cell development and function. Determining the proteomic complement could be a useful tool in predicting cellular function and fate. For the first time shown here, we have utilized iTRAQ, a new method that allows identification and quantification of proteins between multiple samples, to determine the expression of membrane-bound proteins in two previously characterized human NK cell populations. One population was derived from umbilical cord blood (UCB) stem cells (CD34+38-Lin-) and the other from expanded CD3-depleted adult peripheral blood. iTRAQ was employed for multiplex peptide labeling of proteins from fractionated membranes followed by two-dimensional high-performance liquid chromatography (2D-HPLC), and tandem mass spectrometry was used to identify protein signatures. We were able to identify and quantify differences in expression levels of 400-800 proteins in a typical experiment. Ontology analysis showed the majority of the proteins to be involved in cell signaling, nucleic acid binding, or mitochondrial function. Nearly all proteins were associated with the plasma membrane, membrane-bound organelle (lysosome or mitochondria), or nucleus. We found several novel proteins highly expressed in UCB stem cell derived NK cells compared to adult NK cells including CD9, alpha-2 macroglobulin, brain abundant signaling protein (BASP1), and allograft inflammatory factor-1 (AIF-1). In addition, we were able to confirm several of our iTRAQ results by RT-PCR, Western blot, and fluorescence-activated cell-sorting (FACS) analysis. This is the first demonstration and verification using iTRAQ to screen for membrane-bound protein differences in human NK cells and represents a powerful new tool in the field of proteomics.     

Dynamic Proteomic Characteristics and Network Integration Revealing Key Proteins for Two Kernel Tissue Developments in Popcorn

The formation and development of maize kernel is a complex dynamic physiological and biochemical process that involves the temporal and spatial expression of many proteins and the regulation of metabolic pathways. In this study, the protein profiles of the endosperm and pericarp at three important developmental stages were analyzed by isobaric tags for relative and absolute quantification (iTRAQ) labeling coupled with LC-MS/MS in popcorn inbred N04. Comparative quantitative proteomic analyses among developmental stages and between tissues were performed, and the protein networks were integrated. A total of 6,876 proteins were identified, of which 1,396 were nonredundant. Specific proteins and different expression patterns were observed across developmental stages and tissues. The functional annotation of the identified proteins revealed the importance of metabolic and cellular processes, and binding and catalytic activities for the development of the tissues. The whole, endosperm-specific and pericarp-specific protein networks integrated 125, 9 and 77 proteins, respectively, which were involved in 54 KEGG pathways and reflected their complex metabolic interactions. Confirmation for the iTRAQ endosperm proteins by two-dimensional gel electrophoresis showed that 44.44% proteins were commonly found. However, the concordance between mRNA level and the protein abundance varied across different proteins, stages, tissues and inbred lines, according to the gene cloning and expression analyses of four relevant proteins with important functions and different expression levels. But the result by western blot showed their same expression tendency for the four proteins as by iTRAQ. These results could provide new insights into the developmental mechanisms of endosperm and pericarp, and grain formation in maize.     

Comparative Analysis of Label-Free and 8-Plex iTRAQ Approach for Quantitative Tissue Proteomic Analysis

High resolution proteomics approaches have been successfully utilized for the comprehensive characterization of the cell proteome. However, in the case of quantitative proteomics an open question still remains, which quantification strategy is best suited for identification of biologically relevant changes, especially in clinical specimens. In this study, a thorough comparison of a label-free approach (intensity-based) and 8-plex iTRAQ was conducted as applied to the analysis of tumor tissue samples from non-muscle invasive and muscle-invasive bladder cancer. For the latter, two acquisition strategies were tested including analysis of unfractionated and fractioned iTRAQ-labeled peptides. To reduce variability, aliquots of the same protein extract were used as starting material, whereas to obtain representative results per method further sample processing and MS analysis were conducted according to routinely applied protocols. Considering only multiple-peptide identifications, LC-MS/MS analysis resulted in the identification of 910, 1092 and 332 proteins by label-free, fractionated and unfractionated iTRAQ, respectively. The label-free strategy provided higher protein sequence coverage compared to both iTRAQ experiments. Even though pre-fraction of the iTRAQ labeled peptides allowed for a higher number of identifications, this was not accompanied by a respective increase in the number of differentially expressed changes detected. Validity of the proteomics output related to protein identification and differential expression was determined by comparison to existing data in the field (Protein Atlas and published data on the disease). All methods predicted changes which to a large extent agreed with published data, with label-free providing a higher number of significant changes than iTRAQ. Conclusively, both label-free and iTRAQ (when combined to peptide fractionation) provide high proteome coverage and apparently valid predictions in terms of differential expression, nevertheless label-free provides higher sequence coverage and ultimately detects a higher number of differentially expressed proteins. The risk for receiving false associations still exists, particularly when analyzing highly heterogeneous biological samples, raising the need for the analysis of higher sample numbers and/or application of adjustment for multiple testing.     

A proteomic approach for plasma biomarker discovery with 8-plex iTRAQ labeling and SCX-LC-MS/MS

Plasma is recognized as a promising source of disease-related biomarkers, and proteomic approaches for identifying novel plasma biomarkers are in great demand. However, the complexity and dynamic protein concentration range of plasma remain the main obstacles for current research in this field. In this study, plasma proteins were prefractioned by immunodepletion and Protein Equalizer Technology to remove high abundant proteins, then labeled with an 8-plex isobaric tags for relative and absolute quantitation (iTRAQ) to improve the peptide ionization, and analyzed by strong-cation-exchange(SCX) coupled with liquid chromatography-tandem mass spectrometry (LC-MS/MS). Our results showed that both prefraction methods were complementary, with regard to the number of identified proteins. Good chromatographic technique is important to further fractionate the iTRAQ labeling peptides, which allowed 320 and 248 different proteins to be characterized from two prefraction methods, respectively, encompassing a wide array of biological functions and a broad dynamic range of 10⁷. Furthermore, the accuracy of iTRAQ relative quantitation for differentially expressed proteins is associated with the number of peptides hits per protein.     

Comparison of 4-plex to 8-plex iTRAQ quantitative measurements of proteins in human plasma samples

Methods for isobaric tagging of peptides, iTRAQ or TMT, are commonly used platforms in mass spectrometry based quantitative proteomics. These two methods are very often used to quantitate proteins in complex samples, e.g., serum/plasma or CSF supporting biomarker discovery studies. The success of these studies depends on multiple factors, including the accuracy of ratios of reporter ions reflecting quantitative changes of proteins. Because reporter ions are generated during peptide fragmentation, the differences of chemical structure of iTRAQ balance groups may have an effect on how efficiently these groups are fragmented and thus how differences in protein expression will be measured. Because 4-plex and 8-plex iTRAQ reagents do have different structures of balanced groups, it has been postulated that indeed differences in protein identification and quantitation exist between these two reagents. In this study we controlled the ratios of tagged samples and compared quantitation of proteins using 4-plex versus 8-plex reagents in the context of a highly complex sample of human plasma using ABSciex 4800 MALDI-TOF/TOF mass spectrometer and ProteinPilot 4.0 software. We observed that 8-plex tagging provides more consistent ratios than 4-plex without compromising protein identification, thus allowing investigation of eight experimental conditions in one analytical experiment.     

iTRAQ reagent-based quantitative proteomic analysis on a linear ion trap mass spectrometer

For proteomic analysis using tandem mass spectrometry, linear ion trap instruments provide unsurpassed sensitivity but unreliably detect low mass peptide fragments, precluding their use with iTRAQ reagent-labeled samples. Although the popular LTQ linear ion trap supports analyzing iTRAQ reagent-labeled peptides via pulsed Q dissociation, PQD, its effectiveness remains questionable. Using a standard mixture, we found careful tuning of relative collision energy necessary for fragmenting iTRAQ reagent-labeled peptides, and increasing microscan acquisition and repeat count improves quantification but identifies somewhat fewer peptides. We developed software to calculate abundance ratios via summing reporter ion intensities across spectra matching to each protein, thereby providing maximized accuracy. Testing found that results closely corresponded between analysis using optimized LTQ-PQD settings plus our software and using a Qstar instrument. Thus, we demonstrate the effectiveness of LTQ-PQD analyzing iTRAQ reagent-labeled peptides, and provide guidelines for successful quantitative proteomic studies.     

Comparison of iTRAQ and SWATH in a clinical study with multiple time points

Background

Advances in mass spectrometry have accelerated biomarker discovery in many areas of medicine. The purpose of this study was to compare two mass spectrometry (MS) methods, isobaric tags for relative and absolute quantitation (iTRAQ) and sequential window acquisition of all theoretical fragment ion spectra (SWATH), for analytical efficiency in biomarker discovery when there are multiple methodological constraints such as limited sample size and several time points for each patient to be analyzed.

Methods

A total of 140 tear samples were collected from 28 glaucoma patients at 5 time points in a glaucoma drug switch study. Samples were analyzed with iTRAQ and SWATH methods using NanoLC-MSTOF mass spectrometry.

Results

We discovered that even though iTRAQ is faster than SWATH with respect to analysis time per sample, it loses in sensitivity, reliability and robustness. While SWATH analysis yielded complete data of 456 proteins in all samples, with iTRAQ we were able to quantify 477 proteins in total but on average only 125 proteins were quantified in a sample. 283 proteins were common in the datasets produced by the two methods. Repeatability of the methods was assessed by calculating percent relative standard deviation (% RSD) between replicate MS analyses: SWATH was more repeatable (56% of proteins?<?20% RSD), compared to iTRAQ (43% of proteins?<?20% RSD). Despite the overall benefits of SWATH, both methods showed less than 1 log fold change difference in the expression of 74% common proteins. In addition, comparison to MS/MS peptide results using 8 isotopically labeled peptide standards, SWATH and iTRAQ showed similar results in terms of accuracy. Moreover, both methods detected similar trends in a longitudinal analysis of protein expression of two known tear biomarkers.

Conclusions

Overall, we conclude that SWATH should be preferred for biomarker discovery studies when analyzing limited volumes of clinical samples collected at multiple time points.

Trial Registeration

The study was approved by the Ethics Committee at Tampere University Hospital and was registered in EU clinical trials register (EudraCT Number: 2010-021039-14).

     

iTRAQ experimental design for plasma biomarker discovery

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.     

Amine-reactive isobaric tagging reagents: requirements for absolute quantification of proteins and peptides

Amine-reactive isobaric tagging reagents such as iTRAQ (isobaric tags for relative and absolute quantitation) have recently become increasing popular for relative protein quantification, cell expression profiling, and biomarker discovery. This is due mainly to the possibility of simultaneously identifying and quantifying multiple samples. The principles of iTRAQ may also be applied to absolute protein quantification with the use of synthetic peptides as standards. The prerequisites that must be fulfilled to perform absolute quantification of proteins by iTRAQ have been investigated and are described here. Three samples of somatropin were quantified using iTRAQ and synthetic peptides as standards, corresponding to a portion of the protein sequence. The results were compared with those obtained by quantification of the same protein solutions using double exact matching isotope dilution mass spectrometry (IDMS). To obtain reliable results, the appropriate standard peptides needed to be selected carefully and enzymatic digestion needed to be optimized to ensure complete release of the peptides from the protein. The kinetics and efficiency of the iTRAQ derivatization reaction of the standard peptides and digested proteins with isobaric tagging reagents were studied using a mixture of seven synthetic peptides and their corresponding labeled peptides. The implications of incomplete derivatization are also presented.