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.     

TiSH - a robust and sensitive global phosphoproteomics strategy employing a combination of TiO(2), SIMAC, and HILIC

Large scale quantitative phosphoproteomics depends upon multidimensional strategies for peptide fractionation, phosphopeptide enrichment, and mass spectrometric analysis. Previously, most robust comprehensive large-scale phosphoproteomics strategies have relied on milligram amounts of protein. We have set up a multi-dimensional phosphoproteomics strategy combining a number of well-established enrichment and fraction methods: An initial TiO(2) phosphopeptide pre-enrichment step is followed by post-fractionation using sequential elution from IMAC (SIMAC) to separate multi- and mono-phosphorylated peptides, and hydrophilic interaction liquid chromatography (HILIC) of the mono-phosphorylated peptides (collectively abbreviated "TiSH"). The advantages of the strategy include a high specificity and sample preparation workload reduction due to the TiO(2) pre-enrichment step, as well as low adsorptive losses. We demonstrate the capability of this strategy by quantitative investigation of early interferon-γ signaling in low quantities of insulinoma cells. We identified ~6600 unique phosphopeptides from 300μg of peptides/condition (22 unique phosphopeptides/μg) in a duplex dimethyl labeling experiment, with an enrichment specificity>94%. When doing network analysis of putative phosphorylation changes it could be noted that the identified protein interaction network centered upon proteins known to be affected by the interferon-γ pathway, thereby supporting the utility of this global phosphoproteomics strategy. This strategy thus shows great potential for interrogating signaling networks from low amounts of sample with high sensitivity and specificity.     

Analytical strategies for phosphoproteomics

Protein phosphorylation is a key regulator of cellular signaling pathways. It is involved in most cellular events in which the complex interplay between protein kinases and protein phosphatases strictly controls biological processes such as proliferation, differentiation, and apoptosis. Defective or altered signaling pathways often result in abnormalities leading to various diseases, emphasizing the importance of understanding protein phosphorylation. Phosphorylation is a transient modification, and phosphoproteins are often very low abundant. Consequently, phosphoproteome analysis requires highly sensitive and specific strategies. Today, most phosphoproteomic studies are conducted by mass spectrometric strategies in combination with phospho‐specific enrichment methods. This review presents an overview of different analytical strategies for the characterization of phosphoproteins. Emphasis will be on the affinity methods utilized specifically for phosphoprotein and phosphopeptide enrichment prior to MS analysis, and on recent applications of these methods in cell biological applications.     

Proteomic approaches for the global analysis of proteins

Improvements in technology that allow miniaturization and high-throughput analyses of thousand of genes and gene products have changed the focus and scope of research and development in both academia and industry. It is now possible to study entire proteomes with the goals of elucidating protein expression, subcellular localization, biochemical activities, and their regulation. Alterations in different cell types and conditions and in normal and disease states can be revealed. This wealth of information not only has facilitated our basic understanding of many biological processes but also has enormous potential for drug discovery and development.     

The methylome: approaches for global DNA methylation profiling

DNA methylation plays a critical role in genome function both in health and disease. Almost 60 years after the discovery of 5-methyl cytosine and approximately 25 years since the discovery that altered DNA methylation plays a role in disease, the first high-resolution DNA methylation profile (or methylome) of any genome--Arabidopsis thaliana--was determined. Although only approximately 20% of the typical size of mammalian genomes, this milestone demonstrated that the methylomes of the human and similarly large genomes are now within reach. Here, we review current and emerging technologies that hold promise to deliver the first mammalian methylome and to facilitate comprehensive profiling of essentially any cell type in the context of development, disease and the environment.     

Comparison of mixed-model approaches for association mapping

Association-mapping methods promise to overcome the limitations of linkage-mapping methods. The main objectives of this study were to (i) evaluate various methods for association mapping in the autogamous species wheat using an empirical data set, (ii) determine a marker-based kinship matrix using a restricted maximum-likelihood (REML) estimate of the probability of two alleles at the same locus being identical in state but not identical by descent, and (iii) compare the results of association-mapping approaches based on adjusted entry means (two-step approaches) with the results of approaches in which the phenotypic data analysis and the association analysis were performed in one step (one-step approaches). On the basis of the phenotypic and genotypic data of 303 soft winter wheat (Triticum aestivum L.) inbreds, various association-mapping methods were evaluated. Spearman's rank correlation between P-values calculated on the basis of one- and two-stage association-mapping methods ranged from 0.63 to 0.93. The mixed-model association-mapping approaches using a kinship matrix estimated by REML are more appropriate for association mapping than the recently proposed QK method with respect to (i) the adherence to the nominal alpha-level and (ii) the adjusted power for detection of quantitative trait loci. Furthermore, we showed that our data set could be analyzed by using two-step approaches of the proposed association-mapping method without substantially increasing the empirical type I error rate in comparison to the corresponding one-step approaches.     

基于SH2超亲体的微量样品酪氨酸磷酸化蛋白质组学技术研究进展及应用

酪氨酸磷酸化是生物体内一种重要的蛋白质磷酸化修饰类型,参与细胞信号转导、细胞迁移、凋亡等众多的生命活动过程.在磷酸化蛋白质组学研究中,由于酪氨酸磷酸化蛋白丰度低且有时起始样品量有限,传统的磷酸化蛋白质组富集方法用于酪氨酸磷酸化肽富集效率较低.微量样品的制备技术以及SH2超亲体的引入正在改变酪氨酸磷酸化蛋白质组研究的现状...     

Advances in phosphopeptide enrichment techniques for phosphoproteomics

Phosphoproteomics is increasingly used to address a wide range of biological questions. However, despite some success, techniques for phosphoproteomics are not without challenges. Phosphoproteins are present in cells in low abundance relative to their unphosphorylated counterparts; therefore phosphorylated proteins (or phosphopeptides after protein digestion) are rarely detected in standard shotgun proteomics experiments. Thus, extraction of phosphorylated polypeptides from complex mixtures is a critical step in the success of phosphoproteomics experiments. Intense research over the last decade has resulted in the development of powerful techniques for phosphopeptide enrichment prior to analysis by mass spectrometry. Here, we review how the development of IMAC, MOAC, chemical derivatization and antibody affinity purification and chromatography is contributing to the evolution of phosphoproteomics techniques. Although further developments are needed for the technology to reach maturity, current state-of-the-art techniques can already be used as powerful tools for biological research.     

Analytical strategies for shotgun phosphoproteomics: Status and prospects

New analytical strategies for phosphoproteomics, both experimental and computational, have been rapidly introduced in recent years, leading to novel biological findings on the role of protein phosphorylation, which have in turn stimulated further development of the analytical techniques. In this review, we describe the development of analytical strategies for LC–MS/MS-based phosphoproteomics, focusing particularly on recent progress in phosphopeptide enrichment, LC–MS/MS measurement and the subsequent computational analysis. High-coverage analysis of the phosphoproteome has largely been achieved by combining pre-fractionation methods with multiple phosphopeptide enrichment approaches, at some cost in LC–MS/MS measurement time and increased sample loss. Key points for the future will be to further increase the selectivity and the recovery of enrichment methods to achieve higher sensitivity and efficiency in LC–MS/MS analysis in order to detect protein phosphorylation comprehensively, including low-abundance proteins. This is expected to lead to a more detailed understanding of the mechanisms and interactions of phosphorylation-mediated regulatory pathways in biological systems.     

Systems approaches in global change and biogeochemistry research

Systems approaches have great potential for application in predictive ecology. In this paper, we present a range of examples, where systems approaches are being developed and applied at a range of scales in the field of global change and biogeochemical cycling. Systems approaches range from Bayesian calibration techniques at plot scale, through data assimilation methods at regional to continental scales, to multi-disciplinary numerical model applications at country to global scales. We provide examples from a range of studies and show how these approaches are being used to address current topics in global change and biogeochemical research, such as the interaction between carbon and nitrogen cycles, terrestrial carbon feedbacks to climate change and the attribution of observed global changes to various drivers of change. We examine how transferable the methods and techniques might be to other areas of ecosystem science and ecology.     

Soluble nanopolymer-based phosphoproteomics for studying protein phosphatase

Protein phosphorylation is a vital reversible post-translational modification that regulates protein-protein interactions, enzymatic activity, subcellular localization, complex formation and protein stability. The emerging field of mass spectrometry-based proteomics allows us to investigate phosphorylation and dephosphorylation on a global scale. In this review, we describe a new strategy based on soluble nanopolymers that have been used to selectively isolate phosphopeptides for mass spectrometric analysis. Functionalized soluble nanopolymers provide a homogeneous environment and linear reaction kinetics for chemical derivatization to isolate phosphopeptides with high specificity. Combined with phosphatase inhibitors and stable isotopic labeling, the approach has the capability of quantitatively measuring phosphorylation and dephosphorylation on individual sites. We provide experimental details for the approach and describe some other complementary techniques that can be used.     

Sample preparation and analytical strategies for large-scale phosphoproteomics experiments

Reversible protein phosphorylation is an important post-translational modification that controls a wide range of protein functions including enzyme activity, subcellular localisation, protein degradation, intra- and inter-molecular protein interactions. Significant advances in both phosphopeptide enrichment methods and sensitive mass spectrometry instrumentation have been achieved over the past decade to facilitate the large-scale identification of protein phosphorylation in humans and different animal and microbial model systems. While mass spectrometry provides the ability to identify thousands of phosphorylation sites in a single experiment, the further understanding of the functional significance of this modification on protein substrates requires detailed information on the changes in phosphorylation stoichiometry and protein abundance across experimental paradigms. This review presents different sample preparation methods and analytical strategies used in mass spectrometry-based phosphoproteomics to profile protein phosphorylation and unravel the regulation of this modification on protein function.     

Proteomics and phosphoproteomics for the mapping of cellular signalling networks

Proteomics is transitioning from inventory mapping to the mapping of functional cellular contexts. This has been enabled by progress in technologies as well as conceptual strategies. Here, we review recent advances in this area with focus on cellular signalling pathways. We discuss genetics-based methods such as yeast two hybrid methods as well as biochemistry-based methods such as two-dimensional gel electrophoresis, quantitative proteomics, interaction proteomics, and phosphoproteomics. A central tenet is that by its ability to capture dynamic changes in protein expression, localisation and modification modern proteomics has become a powerful tool to map signal transduction pathways and deliver the functional information that will promote insights in cell biology and systems biology.     

Comparison of different approaches for dose response analysis

Characterizing an appropriate dose‐response relationship and identifying the right dose in a clinical trial are two main goals of early drug‐development. MCP‐Mod is one of the pioneer approaches developed within the last 10 years that combines the modeling techniques with multiple comparison procedures to address the above goals in clinical drug development. The MCP‐Mod approach begins with a set of potential dose‐response models, tests for a significant dose‐response effect (proof of concept, PoC) using multiple linear contrasts tests and selects the “best” model among those with a significant contrast test. A disadvantage of the method is that the parameter values of the candidate models need to be fixed a priori for the contrasts tests. This may lead to a loss in power and unreliable model selection. For this reason, several variations of the MCP‐Mod approach and a hierarchical model selection approach have been suggested where the parameter values need not be fixed in the proof of concept testing step and can be estimated after the model selection step. This paper provides a numerical comparison of the different MCP‐Mod variants and the hierarchical model selection approach with regard to their ability of detecting the dose‐response trend, their potential to select the correct model and their accuracy in estimating the dose response shape and minimum effective dose. Additionally, as one of the approaches is based on two‐sided model comparisons only, we make it more consistent with the common goals of a PoC study, by extending it to one‐sided comparisons between the constant and alternative candidate models in the proof of concept step.     

Global phosphoproteomics pinpoints uncharted Gcn2-mediated mechanisms of translational control

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Quantitative phosphoproteomics by mass spectrometry: past, present, and future

Protein phosphorylation-mediated signaling networks regulate much of the cellular response to external stimuli, and dysregulation in these networks has been linked to multiple disease states. Significant advancements have been made over the past decade to enable the analysis and quantification of cellular protein phosphorylation events, but comprehensive analysis of the phosphoproteome is still lacking, as is the ability to monitor signaling at the network level while comprehending the biological implications of each phosphorylation site. In this review we highlight many of the technological advances over the past decade and describe some of the latest applications of these tools to uncover signaling networks in a variety of biological settings. We finish with a concise discussion of the future of the field, including additional advances that are required to link protein phosphorylation analysis with biological insight.