Improved proteome coverage by using iTRAQ labelling and peptide OFFGEL fractionation

Background  

The development of mass spectrometric techniques and fractionation methods now allows the investigation of very complex protein mixtures ranging from subcellular structures to tissues. Nevertheless, this work is particularly difficult due to the wide dynamic range of protein concentration in eukaryotic tissues. In this paper, we present a shotgun method whereby the peptides are fractionated using OFFGEL electrophoresis after iTRAQ labelling.     

Efficient fractionation and improved protein identification by peptide OFFGEL electrophoresis

The sample fractionation steps conducted prior to mass detection are critically important for the comprehensive analysis of complex protein mixtures. This paper illustrates the effectiveness of OFFGEL electrophoresis with the Agilent 3100 OFFGEL Fractionator for the fractionation of peptides. An Escherichia coli tryptic digest was separated in 24 fractions, and peptides were identified by reversed-phase liquid chromatography on a microfluidic device with mass spectrometric detection. About 90% of the identified individual peptides were found in only one or two fractions. The distribution of the calculated isoelectric points for the peptides identified in each fraction was especially narrow in the acidic pH range. Standard deviations approached the size of the pH segment covered by the respective fraction. The experimental peptide isoelectric point measured by OFFGEL electrophoresis was used as an additional filter for validation of peptide identifications.     

Two‐step OFFGEL approach for effective peptide separation compatible with iTRAQ labeling

Shotgun proteomic analyses are increasingly becoming methods of choice for complex samples. The development of effective methods for fractionating peptides to reduce the complexity of the sample before mass analysis is a key point in this strategy. The OFFGEL technology has recently become a tool of choice in proteomic analysis at peptide level. This OFFGEL electrophoresis (OGE) approach allows the in‐solution separation of peptides from various biological sources by isoelectric focusing in highly resolved 24 fractions. It was also demonstrated that OGE technology is a filtering tool for pI‐based validation of peptide identification. As peptide OGE is compatible with iTRAQ labeling, OGE is finding valuable applications in quantitative proteomics as well. The aim of this study is to explain a new 2D‐OGE approach that improves the proteomic coverage of complex mixtures such as colorectal cell line lysates, and which is compatible with iTRAQ labeling.     

Modeling the isoelectric focusing of peptides in an OFFGEL multicompartment cell

In proteomic analysis of complex samples at the peptide level (termed shotgun proteomics), an effective prefractionation is crucial to decrease the complexity of the peptide mixture for further analysis. In this perspective, the high-resolving power of the IEF fractionation step is a determining parameter, in order to obtain well-defined fractions and correct information on peptide isoelectric points, to provide an additional filter for protein identification. Here, we explore the resolving power of OFFGEL IEF as a prefractionation tool to separate peptides. By modeling the peak width evolution versus the peptide charge gradient at pI, we demonstrate that for the three proteomes considered in silico (Deinococcus radiodurans, Saccharomyces cerevisiae, and Homo sapiens), 90% of the peptides should be correctly focused and recovered in two wells at most. This result strongly suggests OFFGEL to be used as a powerful fractionation tool in shotgun proteomics. The influence of the height and shape of the compartments is also investigated, to give the optimal cell dimensions for an enhanced peptide recovery and fast focusing time.     

Purification of plant complex protein extracts in non-denaturing conditions by in-solution isoelectric focusing

An alternative approach for plant complex protein extracts pre-purification by in-solution isoelectric focusing in non-denaturing conditions is presented. The separation of biologically active proteins, in narrow ranges of isoelectric point (pI) was obtained by a modified OFFGEL electrophoresis. Two different water-soluble protein extracts from Phragmites leaves were fractionated into 24 fractions within a 3–10 pI range at 10 °C in the absence of denaturing/reducing agents. One-dimensional electrophoretic analysis revealed different protein distribution patterns and the effective fractionation of both protein extracts. Peroxidase activity of each fraction confirmed that proteins remained active and pre-purification occurred. Biological triplicates assured the needed reproducibility.     

Combination of peptide OFFGEL fractionation and label-free quantitation facilitated proteomics profiling of extraocular muscle

Several label-free quantitation strategies have been introduced that obliterate the need for expensive isotopically labeled molecules. However label-free approaches have considerably higher demands in respect of repeatability of sample preparation and fractionation than multiplexing isotope labeling-based strategies. OFFGEL fractionation promises the necessary separation efficiency and repeatability. To test this platform, 12-fraction peptide OFFGEL electrophoresis and online reversed-phase LC connected to a quadrupole TOF mass spectrometer were used to determine differences of the physiological, pathological and biochemical distinct extraocular muscle allotype in comparison to hind-limb muscle. Close to 70% of the peptides separated by OFFGEL electrophoresis were detected only in a single fraction. To determine the separation repeatability of four samples, we compared the ion volumes of multiple peptides deriving from the thick filament-associated protein titin over several fractions and determined a coefficient of variation below 20%. Of the 474 proteins identified, 61 proteins were differently expressed between the two muscle allotypes and were involved in metabolism, muscle contraction, stress response, or gene expression. Several expression differences were validated using immunohistochemistry and Western blot analysis. We therefore consider peptide OFFGEL fractionation an effective and efficient addition to our label-free quantitative proteomics workflow.     

Mass Spectrometric Identification of Proteotypic Peptides from Clinically Used Tumor Markers

Introduction

With the rapid development of mass spectrometry-based technologies such as multiple reaction monitoring and heavy-isotope-labeled-peptide standards, quantitative analysis of biomarker proteins using mass spectrometry is rapidly progressing toward detection of target proteins/peptides from clinical samples. Proteotypic peptides are a few peptides that are repeatedly and consistently identified from a protein in a mixture and are used for quantitative analysis of the protein in a complex biological sample by mass spectrometry.

Materials and Methods

Using mass spectrometry, we identified peptide sequences and provided a list of tryptic peptides and glycopeptides as proteotypic peptides from five clinically used tumor markers, including prostate-specific antigen, carcinoembryonic antigen, Her-2, human chorionic gonadotropin, and CA125.

Conclusion

These proteotypic peptides have potential for targeted detection as well as heavy-isotope-peptide standards for quantitative analysis of marker proteins in clinical specimens using a highly specific, sensitive, and high-throughout mass spectrometry-based analysis method.     

Defining,Comparing, and Improving iTRAQ Quantification in Mass Spectrometry Proteomics Data

The purpose of this study was to generate a basis for the decision of what protein quantities are reliable and find a way for accurate and precise protein quantification. To investigate this we have used thousands of peptide measurements to estimate variance and bias for quantification by iTRAQ (isobaric tags for relative and absolute quantification) mass spectrometry in complex human samples. A549 cell lysate was mixed in the proportions 2:2:1:1:2:2:1:1, fractionated by high resolution isoelectric focusing and liquid chromatography and analyzed by three mass spectrometry platforms; LTQ Orbitrap Velos, 4800 MALDI-TOF/TOF and 6530 Q-TOF. We have investigated how variance and bias in the iTRAQ reporter ions data are affected by common experimental variables such as sample amount, sample fractionation, fragmentation energy, and instrument platform. Based on this, we have suggested a concept for experimental design and a methodology for protein quantification. By using duplicate samples in each run, each experiment is validated based on its internal experimental variation. The duplicates are used for calculating peptide weights, unique to the experiment, which is used in the protein quantification. By weighting the peptides depending on reporter ion intensity, we can decrease the relative error in quantification at the protein level and assign a total weight to each protein that reflects the protein quantitation confidence. We also demonstrate the usability of this methodology in a cancer cell line experiment as well as in a clinical data set of lung cancer tissue samples. In conclusion, we have in this study developed a methodology for improved protein quantification in shotgun proteomics and introduced a way to assess quantification for proteins with few peptides. The experimental design and developed algorithms decreased the relative protein quantification error in the analysis of complex biological samples.Recent developments in methods and instruments for mass spectrometry enable quantitative proteomics analysis of complex samples with good coverage (1–4). Several techniques for quantification by mass spectrometry exist, both using isotopic labeling and label free methods (5, 6). Quantification by isotopic labeling can be done on precursor ion level or by quantifying isobaric label fragments in fragment spectra. Isotope-coded affinity tag (7), isobaric tags for relative and absolute quantification (iTRAQ)¹ (8), and stable isotope labeling by amino acids in cell culture (SILAC) (9) are among the most commonly used labeling methods based on stable isotopes. iTRAQ allows for simultaneous relative quantification of up to eight samples within a single run. Quantification by mass spectrometry is however a challenge, and several factors contribute to the uncertainty in the quantitative estimate; differences in labeling efficiency, protein digestion, precursor mixing, ion suppression, peak detection, data preprocessing, and data analysis (10). The quality of quantitation methods can be measured in terms of precision and accuracy. Precision is affected by random errors, that is, random fluctuations around the true value (variance). Lack of accuracy is caused by systematic errors, that is, differences between true and observed values (bias).Several studies have shown that iTRAQ labeling is associated with bias; fold changes are compressed toward one (11–14). It has been suggested that this underestimation of fold change is caused by co-eluting peptides with similar m/z values that are isolated together, creating mixed iTRAQ intensities in complex samples (14). Concerning precision, iTRAQ data has been reported to exhibit variance heterogeneity. The coefficient of variance (CV) of the signal depends on the intensity, with larger CV for low intensity peaks (11, 12, 15, 16). Measurements of iTRAQ intensities for quantification are made in the MS/MS spectra of the peptides, and thereafter combined to calculate a summarized relative protein quantity. There are several different approaches for combining the iTRAQ peptide data to compute a reliable protein ratio. Methods to improve the protein quantification by addressing the variance heterogeneity have been based on excluding low intensity peptide data (17, 18), weighting the peptide data according to intensity (18–21) or stabilizing the variance (12).Quantitative studies of complex human samples are subject to even more challenges related to large biological variation, large and unknown complexity of the human proteome and a large concentration range of proteins. This in turn results in many peptides and a large variety of peptides that can cause interference and related problems in the mass spectrometry analysis. In, for example, biomarker discovery research the goal is to measure quantitative changes or differences in protein levels between two or more clinical conditions. It is therefore crucial to achieve as accurate and precise quantitative information from the data as possible as well as to correctly estimate the limitations of the quantification. Setting adequate standards for quantitative proteomics analysis is hence essential for being able to detect relevant changes in protein abundance, select important proteins, and further use those proteins to interpret the biological and clinical meaning (10, 22). Selecting a protein as significant and taking it to further validation in other clinical material using complementary techniques is time consuming and costly (23). For successful use of iTRAQ labeling in biomarker discovery, and to avoid false discoveries, it is hence essential to assess the accuracy and precision of the methodology.A common approach to study variance and bias in mass spectrometry based protein quantification is to spike a set of standard proteins into a sample and then measure the CV and bias of the intensities of those peptides. Spike-in of proteins has the benefit of looking at a small controlled set of peptides and how they behave in the studied system. This strategy has been used in several of the previously mentioned papers that address iTRAQ quantification (11–14). However, the number of data points studied may be unlikely to represent the complexity of a real biological sample, which often contains thousands of proteins (24). In the current study, all peptides detected in a complex human cell line sample (A549) are used to get an estimate of the quantitative accuracy and precision. This experimental setup is hence more similar to a real biomarker discovery study with high complex human proteome samples. The quality of the protein quantifications is compared among several different mass spectrometers in this work; also the influence of different loaded peptide amounts and the use of different methods for sample separation are examined. Factors such as variance and bias of peptide quantification by iTRAQ are systematically evaluated in those high complex samples. Further, methods for improving the protein quantification are investigated; by filtering on the peptide level to remove low quality intensities and by weighting the peptide values to account for the higher risk of errors at low intensities (20).We have described the factors contributing to bias and variance in protein quantification by iTRAQ labeling. This has generated guidelines for how to estimate the accuracy of protein quantities, which will be an essential tool in both biomarker discovery and studies of biological systems. Based on the results, we suggest an experimental design where each labeling set (e.g., iTRAQ) includes duplicate samples, and we describe how these duplicates are used for calculating peptide weights that can be used in addressing the accuracy of protein quantities. This novel approach is shown to improve protein quantification by iTRAQ in six data sets of A431 cell line samples treated with drug and a clinical data set of lung cancer tissue samples.     

Electrostatic repulsion-hydrophilic interaction chromatography (ERLIC) versus strong cation exchange (SCX) for fractionation of iTRAQ-labeled peptides

The iTRAQ technique is popular for the comparative analysis of proteins in different complex samples. To increase the dynamic range and sensitivity of peptide identification in shotgun proteomics, SCX chromatography is generally used for the fractionation of iTRAQ-labeled peptides before LC-MS/MS analysis. However, SCX suffers from clustering of similarly charged peptides and the need to desalt fractions. In this report, SCX is compared with the alternative ERLIC method for fractionating iTRAQ-labeled peptides. The simultaneous effect of electrostatic repulsion and hydrophilic interaction in ERLIC results in peptide elution in order of decreasing pI and GRAVY values (increasing polarity). Volatile solvents can be used. We applied ERLIC to iTRAQ-labeled peptides from rat liver tissue, and 2745 proteins and 30,016 unique peptides were identified with high confidence from three technical replicates. This was 12.9 and 49.4% higher, respectively, than was obtained using SCX. In addition, ERLIC is appreciably better at the identification of highly hydrophobic peptides. The results indicate that ERLIC is a more convenient and more effective alternative to SCX for the fractionation of iTRAQ-labeled peptides. Quantification data show that both SCX and ERLIC fractionation have no significant effect on protein quantification by iTRAQ.     

Visualisation tool for peptide fractionation data in proteomics: application to OFFGEL isoelectric focussing

Background  

OFFGEL isoelectric focussing (IEF) has become a popular tool in proteomics to fractionate peptides or proteins. As a consequence there is a need for software solutions supporting data mining, interpretation and characterisation of experimental quality.     

Shift in the isoelectric-point of milk proteins as a consequence of adaptive divergence between the milks of mammalian species

Background

Milk proteins are required to proceed through a variety of conditions of radically varying pH, which are not identical across mammalian digestive systems. We wished to investigate if the shifts in these requirements have resulted in marked changes in the isoelectric point and charge of milk proteins during evolution.

Results

We investigated nine major milk proteins in 13 mammals. In comparison with a group of orthologous non-milk proteins, we found that 3 proteins κ-casein, lactadherin, and muc1 have undergone the highest change in isoelectric point during evolution. The pattern of non-synonymous substitutions indicate that selection has played a role in the isoelectric point shift, since residues that show significant evidence of positive selection are much more likely to be charged (p = 0.03 for κ-casein; p < 10^-8 for muc1). However, this selection does not appear to be solely due to adaptation to the diversity of mammalian digestive systems, since striking changes are seen among species that resemble each other in terms of their digestion.

Conclusion

The changes in charge are most likely due to changes of other protein functions, rather than an adaptation to the different mammalian digestive systems. These functions may include differences in bioactive peptide releases in the gut between different mammals, which are known to be a major contributing factor in the functional and nutritional value of mammalian milk. This raises the question of whether bovine milk is optimal in terms of particular protein functions, for human nutrition and possibly disease resistance. This article was reviewed by Fyodor Kondrashov, David Liberles (nominated by David Ardell), and Christophe Lefevre (nominated by Mark Ragan).     

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).

     

Temperature sensitive influenza A virus genome replication results from low thermal stability of polymerase-cRNA complexes

Background

Although many vaccinia virus proteins have been identified and studied in detail, only a few studies have attempted a comprehensive survey of the protein composition of the vaccinia virion. These projects have identified the major proteins of the vaccinia virion, but little has been accomplished to identify the unknown or less abundant proteins. Obtaining a detailed knowledge of the viral proteome of vaccinia virus will be important for advancing our understanding of orthopoxvirus biology, and should facilitate the development of effective antiviral drugs and formulation of vaccines.

Results

In order to accomplish this task, purified vaccinia virions were fractionated into a soluble protein enriched fraction (membrane proteins and lateral bodies) and an insoluble protein enriched fraction (virion cores). Each of these fractions was subjected to further fractionation by either sodium dodecyl sulfate-polyacrylamide gel electophoresis, or by reverse phase high performance liquid chromatography. The soluble and insoluble fractions were also analyzed directly with no further separation. The samples were prepared for mass spectrometry analysis by digestion with trypsin. Tryptic digests were analyzed by using either a matrix assisted laser desorption ionization time of flight tandem mass spectrometer, a quadrupole ion trap mass spectrometer, or a quadrupole-time of flight mass spectrometer (the latter two instruments were equipped with electrospray ionization sources). Proteins were identified by searching uninterpreted tandem mass spectra against a vaccinia virus protein database created by our lab and a non-redundant protein database.

Conclusion

Sixty three vaccinia proteins were identified in the virion particle. The total number of peptides found for each protein ranged from 1 to 62, and the sequence coverage of the proteins ranged from 8.2% to 94.9%. Interestingly, two vaccinia open reading frames were confirmed as being expressed as novel proteins: E6R and L3L.     

Working without a blindfold: the critical role of diagnostics in malaria control

Background

The insertion of parasite antigens into the host erythrocyte membrane and the structure and distribution of Plasmodium falciparum adhesion receptors on that membrane are poorly understood. Laser scanning confocal microscopy (LSCM) and a novel labelling and fixation method have been used to obtain high resolution immuno-fluorescent images of erythrocyte surface PfEMP1 and internal antigens which allow analysis of the accumulation of PfEMP1 on the erythrocyte membrane during asexual development.

Methods

A novel staining technique has been developed which permits distinction between erythrocyte surface PfEMP1 and intracellular PfEMP1, in parasites whose nuclear material is exceptionally well resolved. Primary antibody detection by fluorescence is carried out on the live parasitized erythrocyte. The surface labelled cells are then fixed using paraformaldehyde and permeabilized with a non-ionic detergent to permit access of antibodies to internal parasite antigens. Differentiation between surface and internal antigens is achieved using antibodies labelled with different fluorochromes and confocal microscopy

Results

Surface exposed PfEMP1 is first detectable by antibodies at the trophozoite stage of intracellular parasite development although the improved detection method indicates that there are differences between different laboratory isolates in the kinetics of accumulation of surface-exposed PfEMP1.

Conclusion

A sensitive method for labelling surface and internal PfEMP1 with up to three different fluorochromes has been developed for laser scanning confocal optical microscopy and the analysis of the developmental expression of malaria adhesion antigens.     

Cancer Biomarker Discovery via Targeted Profiling of Multiclass Tumor Tissue-Derived Proteomes

Introduction

Tumor-derived proteins and naturally occurring peptides represent a rich source of potential cancer markers for multiclass cancer distinction.

Materials and Methods

In this study, proteomes/peptidomes derived from primary colon cancer, kidney cancer, liver cancer, and glioblastoma were analyzed by liquid chromatography coupled with mass spectrometry to identify multiclass cancer discriminative protein and peptide candidates. Spectral counting and peptidomic analyses found two biomarker panels, one with 12 proteins and the other with 53 peptides, both capable of multiclass cancer detection and classification.

Results and Discussion

Shed from tumor tissues through apoptosis/necrosis, cell secretion, or tumor-specific degradation of extracellular matrix proteins, these proteins/peptides are likely to enter into circulation and, therefore, have the potential to be configured into practical serological diagnostic and prognostic utilities.     

iTRAQ labeling is superior to mTRAQ for quantitative global proteomics and phosphoproteomics

Labeling of primary amines on peptides with reagents containing stable isotopes is a commonly used technique in quantitative mass spectrometry. Isobaric labeling techniques such as iTRAQ™ or TMT™ allow for relative quantification of peptides based on ratios of reporter ions in the low m/z region of spectra produced by precursor ion fragmentation. In contrast, nonisobaric labeling with mTRAQ™ yields precursors with different masses that can be directly quantified in MS1 spectra. In this study, we compare iTRAQ- and mTRAQ-based quantification of peptides and phosphopeptides derived from EGF-stimulated HeLa cells. Both labels have identical chemical structures, therefore precursor ion- and fragment ion-based quantification can be directly compared. Our results indicate that iTRAQ labeling has an additive effect on precursor intensities, whereas mTRAQ labeling leads to more redundant MS2 scanning events caused by triggering on the same peptide with different mTRAQ labels. We found that iTRAQ labeling quantified nearly threefold more phosphopeptides (12,129 versus 4,448) and nearly twofold more proteins (2,699 versus 1,597) than mTRAQ labeling. Although most key proteins in the EGFR signaling network were quantified with both techniques, iTRAQ labeling allowed quantification of twice as many kinases. Accuracy of reporter ion quantification by iTRAQ is adversely affected by peptides that are cofragmented in the same precursor isolation window, dampening observed ratios toward unity. However, because of tighter overall iTRAQ ratio distributions, the percentage of statistically significantly regulated phosphopeptides and proteins detected by iTRAQ and mTRAQ was similar. We observed a linear correlation of logarithmic iTRAQ to mTRAQ ratios over two orders of magnitude, indicating a possibility to correct iTRAQ ratios by an average compression factor. Spike-in experiments using peptides of defined ratios in a background of nonregulated peptides show that iTRAQ quantification is less accurate but not as variable as mTRAQ quantification.Stable isotope labeling techniques have become very popular in recent years to perform quantitative mass spectrometry experiments with high precision and accuracy. In contrast to label-free approaches, multiplexed isotopically labeled samples can be simultaneously analyzed resulting in increased reproducibility and accuracy for quantification of peptides and proteins from different biological states. Isotopic labeling strategies can be grouped into two major categories: isobaric labels and nonisobaric labels. In the former category are iTRAQ¹ (isobaric tags for relative and absolute quantification (1)) and TMT (tandem mass tags (2)) mass tags. In the nonisobaric labeling category are methods such as mTRAQ (mass differential tags for relative and absolute quantification), stable isotope labeling by amino acids in cell culture (SILAC (3)), and reductive dimethylation (4). Isobaric labeling techniques allow relative quantification of peptides based on ratios of low m/z reporter ions produced by fragmentation of the precursor ion, whereas nonisobaric labeling yields precursors with different masses that can be directly quantified from MS1 intensity. iTRAQ and mTRAQ reagents provide a great opportunity to directly compare capabilities of reporter and precursor ion quantification since both labels have identical chemical structures and differ only in their composition and number of ¹³C, ¹⁵N, and ¹⁸O atoms. In fact, iTRAQ-117 and mTRAQ-Δ4 are identical mass tags with a total mass of 145 Da (Fig. 1A). To achieve 4-plex quantification capabilities for iTRAQ labels, the composition of stable isotopes is arranged in a way to obtain the reporter ion/balancing group pairs 114/31, 115/30, 116/29, and 117/28 (1). Three nonisobaric mTRAQ labels were generated by adding or removing four neutrons to the mTRAQ-Δ4 label resulting in mTRAQ-Δ8 and mTRAQ-Δ0, respectively. Both iTRAQ and mTRAQ reagents are available as N-hydroxy-succinimide esters to facilitate primary amine labeling of peptides.Open in a separate windowFig. 1.A, Labeling strategy for comparative evaluation of iTRAQ and mTRAQ tags. Peptides were labeled with the indicated iTRAQ and mTRAQ reagents for combined phosphoproteome and proteome analysis. B, Selection of optimal instrument methods for analysis of iTRAQ- and mTRAQ-labeled peptides. Unfractionated proteome samples (1 ug) and phosphoproteome samples (enriched from 250 μg peptides) were analyzed for iTRAQ samples with a CID/HCD-Top8 method, whereas for mTRAQ we compared CID-Top16 acquisition to HCD-Top8. Note that duty cycle times were for all instrument methods ∼3.1 s.One potential advantage of an iTRAQ labeling strategy is its additive effect on precursor intensities when samples are multiplexed, resulting in increased sensitivity. However, iTRAQ ratios have been demonstrated to be prone to compression. This occurs when other nonregulated background peptides are co-isolated and cofragmented in the same isolation window of the peptide of interest and contribute fractional intensity to the reporter ions in MS2-scans (5–7). Because most peptides in an experiment are present at 1:1:1:1 ratios between multiplexed samples, all ratios in the experiment tend to be dampened toward unity when cofragmentation occurs. This inaccuracy led to the development of mTRAQ labels to facilitate accurate precursor-based quantification of proteins initially identified in iTRAQ discovery experiments with targeted assays, such as multiple reaction monitoring (MRM) (8). Although iTRAQ has been widely used in discovery-based proteomics studies, mTRAQ has only appeared in a small number of studies thus far (8).In this study we investigated the advantages and disadvantages of iTRAQ and mTRAQ labeling for proteome-wide analysis of protein phosphorylation and expression changes. We selected epidermal growth factor (EGF)-stimulated HeLa cells as a model system for our comparative evaluation of iTRAQ and mTRAQ labeling, as both changes in the phosphoproteome (9) as well as the proteome (10) are well described for EGF stimulation. We show that iTRAQ labeling yields superior results to mTRAQ in terms of numbers of quantified phosphopeptides, proteins and regulated components. By means of spike-in experiments with GluC generated peptides of known ratios we find that iTRAQ quantification is more precise but less accurate than mTRAQ due to ratio compression. We identify a linear relationship of observed versus expected logarithmic GluC generated peptide ratios as well as for logarithmic iTRAQ and mTRAQ ratios of the phosphoproteome and proteome analysis. This indicates a uniform degree of ratio compression over two orders of magnitude throughout iTRAQ data sets and explains why iTRAQ ratio compression does not compromise the ability to detect regulated elements in these experiments.     

Peptide length significantly influences in vitro affinity for MHC class II molecules

Background

Class II Major Histocompatibility Complex (MHC) molecules have an open-ended binding groove which can accommodate peptides of varying lengths. Several studies have demonstrated that peptide flanking residues (PFRs) which lie outside the core binding groove can influence peptide binding and T cell recognition. By using data from the AntiJen database we were able to characterise systematically the influence of PFRs on peptide affinity for MHC class II molecules.

Results

By analysing 1279 peptide elongation events covering 19 distinct HLA alleles it was observed that, in general, peptide elongation resulted in increased MHC class II molecule affinity. It was also possible to determine an optimal peptide length for MHC class II affinity of approximately 18–20 amino acids; elongation of peptides beyond this length resulted in a null or negative effect on affinity.

Conclusion

The observed relationship between peptide length and MHC class II affinity has significant implications for the design of vaccines and the study of the epitopic basis of immunological disease.     

Availability of MudPIT data for classification of biological samples

Background

Mass spectrometry is an important analytical tool for clinical proteomics. Primarily employed for biomarker discovery, it is increasingly used for developing methods which may help to provide unambiguous diagnosis of biological samples. In this context, we investigated the classification of phenotypes by applying support vector machine (SVM) on experimental data obtained by MudPIT approach. In particular, we compared the performance capabilities of SVM by using two independent collection of complex samples and different data-types, such as mass spectra (m/z), peptides and proteins.

Results

Globally, protein and peptide data allowed a better discriminant informative content than experimental mass spectra (overall accuracy higher than 87% in both collection 1 and 2). These results indicate that sequencing of peptides and proteins reduces the experimental noise affecting the raw mass spectra, and allows the extraction of more informative features available for the effective classification of samples. In addition, proteins and peptides features selected by SVM matched for 80% with the differentially expressed proteins identified by the MAProMa software.

Conclusions

These findings confirm the availability of the most label-free quantitative methods based on processing of spectral count and SEQUEST-based SCORE values. On the other hand, it stresses the usefulness of MudPIT data for a correct grouping of sample phenotypes, by applying both supervised and unsupervised learning algorithms. This capacity permit the evaluation of actual samples and it is a good starting point to translate proteomic methodology to clinical application.