高精度相对和绝对定量的等量异位标签在定量蛋白质组学研究中的新进展

蛋白质组学逐渐从定性研究转向定量研究。在定量蛋白质组学技术中,相对和绝对定量的等量异位标签(Isobaric tags for relative and absolute quantitation,iTRAQ)是应用最广泛的技术之一,具有通量高、稳定性强及不受样品来源制约等优点,几乎可以对任意样品进行标记,而且可以同时对多达8个样品进行定量分析,有效地提高了通量。iTRAQ技术不断改进,其定量准确性显著提高,适用的平台越来越多,为微生物、动物、植物、生物医学领域蛋白质及其翻译后修饰组研究创造了条件。文中综述了高精度iTRAQ技术在定量蛋白质组学研究中的最新发展及其应用。     

Aberrant Mucin5B expression in lung adenocarcinomas detected by iTRAQ labeling quantitative proteomics and immunohistochemistry

Background

Lung cancer is the number one cause of cancer-related deaths in the United States and worldwide. The complex protein changes and/or signature of protein expression in lung cancer, particularly in non-small cell lung cancer (NSCLC) has not been well defined. Although several studies have investigated the protein profile in lung cancers, the knowledge is far from complete. Among early studies, mucin5B (MUC5B) has been suggested to play an important role in the tumor progression. MUC5B is the major gel-forming mucin in the airway. In this study, we investigated the overall protein profile and MUC5B expression in lung adenocarcinomas, the most common type of NSCLCs.

Methods

Lung adenocarcinoma tissue in formalin-fixed paraffin-embedded (FFPE) blocks was collected and microdissected. Peptides from 8 tumors and 8 tumor-matched normal lung tissue were extracted and labeled with 8-channel iTRAQ reagents. The labeled peptides were identified and quantified by LC-MS/MS using an LTQ Orbitrap Velos mass spectrometer. MUC5B expression identified by iTRAQ labeling was further validated using immunohistochemistry (IHC) on tumor tissue microarray (TMA).

Results

A total of 1288 peptides from 210 proteins were identified and quantified in tumor tissues. Twenty-two proteins showed a greater than 1.5-fold differences between tumor and tumor-matched normal lung tissues. Fifteen proteins, including MUC5B, showed significant changes in tumor tissues. The aberrant expression of MUC5B was further identified in 71.1% of lung adenocarcinomas in the TMA.

Discussions

A subset of tumor-associated proteins was differentially expressed in lung adenocarcinomas. The differential expression of MUC5B in lung adenocarcinomas suggests its role as a potential biomarker in the detection of adenocarcinomas.     

A technically detailed and pragmatic protocol for quantitative serum proteomics using iTRAQ

Blood is recognised as a highly important source of disease-related biomarkers, and proteomic approaches for identifying novel blood-borne biomarkers are in demand. The complexity and dynamic protein concentration range of plasma/serum however complicates the analysis process. A number of strategies for simplification of blood prior to proteomic analysis have been developed. In addition, methods for quantifying the levels of proteins in samples, such as isobaric tags for relative and absolute quantification (iTRAQ) are emerging. However, the successful application of these procedures is not always straightforward and technical hurdles must be overcome. Here we provide a technically detailed working protocol for iTRAQ-based quantification of serum proteins following immunodepletion of high abundance proteins. To improve the number of proteins identified and quantified we have introduced several modifications to the standard iTRAQ protocol. We report identifications of 217 proteins (5773 peptides) with a false discovery rate of 1% or 254 proteins with 95% confidence, respectively. Relative quantification data were obtained for 234 (95% confidence) serum proteins, including species present in the concentration range of tissue leakage factors. The samples described here relate to pancreatic cancer; however the protocol can be applied to serum from other control or disease types.     

Integrating titania enrichment,iTRAQ labeling,and Orbitrap CID‐HCD for global identification and quantitative analysis of phosphopeptides

Recent advances in MS instrumentation and progresses in phosphopeptide enrichment, in conjunction with more powerful data analysis tools, have facilitated unbiased characterization of thousands of site‐specific phosphorylation events. Combined with stable isotope labeling by amino acids in cell culture metabolic labeling, these techniques have made it possible to quantitatively evaluate phosphorylation changes in various physiological states in stable cell lines. However, quantitative phosphoproteomics in primary cells and tissues remains a major technical challenge due to the lack of adequate techniques for accurate quantification. Here, we describe an integrated strategy allowing for large scale quantitative profiling of phosphopeptides in complex biological mixtures. In this technique, the mixture of proteolytic peptides was subjected to phosphopeptide enrichment using a titania affinity column, and the purified phosphopeptides were subsequently labeled with iTRAQ reagents. After further fractionation by strong‐cation exchange, the peptides were analyzed by LC‐MS/MS on an Orbitrap mass spectrometer, which collects CID and high‐energy collisional dissociation (HCD) spectra sequentially for peptide identification and quantitation. We demonstrate that direct phosphopeptide enrichment of protein digests by titania affinity chromatography substantially improves the efficiency and reproducibility of phosphopeptide proteomic analysis and is compatible with downstream iTRAQ labeling. Conditions were optimized for HCD normalized collision energy to balance the overall peptide identification and quantitation using the relative abundances of iTRAQ reporter ions. Using this approach, we were able to identify 3557 distinct phosphopeptides from HeLa cell lysates, of which 2709 were also quantified from HCD scans.     

High-coverage quantitative proteomics using amine-specific isotopic labeling

Peptide dimethylation with isotopically coded formaldehydes was evaluated as a potential alternative to techniques such as the iTRAQ method for comparative proteomics. The isotopic labeling strategy and custom-designed protein quantitation software were tested using protein standards and then applied to measure proteins levels associated with Alzheimer's disease (AD). The method provided high accuracy (10% error), precision (14% RSD) and coverage (70%) when applied to the analysis of a standard solution of BSA by LC-MS/MS. The technique was then applied to measure protein abundance levels in brain tissue afflicted with AD relative to normal brain tissue. 2-D LC-MS analysis identified 548 unique proteins (p<0.05). Of these, 349 were quantified with two or more peptides that met the statistical criteria used in this study. Several classes of proteins exhibited significant changes in abundance. For example, elevated levels of antioxidant proteins and decreased levels of mitochondrial electron transport proteins were observed. The results demonstrate the utility of the labeling method for high-throughput quantitative analysis.     

IsobariQ: software for isobaric quantitative proteomics using IPTL, iTRAQ, and TMT

Isobaric peptide labeling plays an important role in relative quantitative comparisons of proteomes. Isobaric labeling techniques utilize MS/MS spectra for relative quantification, which can be either based on the relative intensities of reporter ions in the low mass region (iTRAQ and TMT) or on the relative intensities of quantification signatures throughout the spectrum due to isobaric peptide termini labeling (IPTL). Due to the increased quantitative information found in MS/MS fragment spectra generated by the recently developed IPTL approach, new software was required to extract the quantitative information. IsobariQ was specifically developed for this purpose; however, support for the reporter ion techniques iTRAQ and TMT is also included. In addition, to address recently emphasized issues about heterogeneity of variance in proteomics data sets, IsobariQ employs the statistical software package R and variance stabilizing normalization (VSN) algorithms available therein. Finally, the functionality of IsobariQ is validated with data sets of experiments using 6-plex TMT and IPTL. Notably, protein substrates resulting from cleavage by proteases can be identified as shown for caspase targets in apoptosis.     

MS-specific noise model reveals the potential of iTRAQ in quantitative proteomics

MOTIVATION: Mass spectrometry (MS) data are impaired by noise similar to many other analytical methods. Therefore, proteomics requires statistical approaches to determine the reliability of regulatory information if protein quantification is based on ion intensities observed in MS. RESULTS: We suggest a procedure to model instrument and workflow-specific noise behaviour of iTRAQ reporter ions that can provide regulatory information during automated peptide sequencing by LC-MS/MS. The established mathematical model representatively predicts possible variations of iTRAQ reporter ions in an MS data-dependent manner. The model can be utilized to calculate the robustness of regulatory information systematically at the peptide level in so-called bottom-up proteome approaches. It allows to determine the best fitting regulation factor and in addition to calculate the probability of alternative regulations. The result can be visualized as likelihood curves summarizing both the quantity and quality of regulatory information. Likelihood curves basically can be calculated from all peptides belonging to different regions of proteins if they are detected in LC-MS/MS experiments. Therefore, this approach renders excellent opportunities to detect and statistically validate dynamic post-translational modifications usually affecting only particular regions of the whole protein. The detection of known phosphorylation events at protein kinases served as a first proof of concept in this study and underscores the potential for noise models in quantitative proteomics.     

Performance of isobaric and isotopic labeling in quantitative plant proteomics

Mass spectrometry has become indispensable for peptide and protein quantification in proteomics studies. When proteomics technologies are applied to understand the biology of plants, two-dimensional gel electrophoresis is still the prevalent method for protein fractionation, identification, and quantitation. In the present work, we have used LC-MS to compare an isotopic (ICPL) and isobaric (iTRAQ) chemical labeling technique to quantify proteins in the endosperm of Ricinus communis seeds at three developmental stages (IV, VI, and X). Endosperm proteins of each stage were trypsin-digested in-solution, and the same amount of peptides was labeled with ICPL and iTRAQ tags in two orders (forward and reverse). Each sample was submitted to nanoLC coupled to an LTQ-Orbitrap high-resolution mass spectrometer. Comparing labeling performance, iTRAQ was able to label 99.8% of all identified unique peptides, while 94.1% were labeled by ICPL. After statistical analysis, it was possible to quantify 309 (ICPL) and 321 (iTRAQ) proteins, from which 95 are specific to ICPL, 107 to iTRAQ, and 214 common to both labeling strategies. We noted that the iTRAQ quantification could be influenced by the tag. Even though the efficiency of the iTRAQ and ICPL in protein quantification depends on several parameters, both labeling methods were able to successfully quantify proteins present in the endosperm of castor bean during seed development and, when combined, increase the number of quantified proteins.     

Protein profiling of human lung telocytes and microvascular endothelial cells using iTRAQ quantitative proteomics

Telocytes (TCs) are described as a particular type of cells of the interstitial space ( www.telocytes.com ). Their main characteristics are the very long telopodes with alternating podoms and podomers. Recently, we performed a comparative proteomic analysis of human lung TCs with fibroblasts, demonstrating that TCs are clearly a distinct cell type. Therefore, the present study aims to reinforce this idea by comparing lung TCs with endothelial cells (ECs), since TCs and ECs share immunopositivity for CD34. We applied isobaric tag for relative and absolute quantification (iTRAQ) combined with automated 2‐D nano‐ESI LC‐MS/MS to analyse proteins extracted from TCs and ECs in primary cell cultures. In total, 1609 proteins were identified in cell cultures. 98 proteins (the 5th day), and 82 proteins (10th day) were confidently quantified (screened by two‐sample t‐test, P < 0.05) as up‐ or down‐regulated (fold change >2). We found that in TCs there are 38 up‐regulated proteins at the 5th day and 26 up‐regulated proteins at the 10th day. Bioinformatics analysis using Panther revealed that the 38 proteins associated with TCs represented cellular functions such as intercellular communication (via vesicle mediated transport) and structure morphogenesis, being mainly cytoskeletal proteins and oxidoreductases. In addition, we found 60 up‐regulated proteins in ECs e.g.: cell surface glycoprotein MUC18 (15.54‐fold) and von Willebrand factor (5.74‐fold). The 26 up‐regulated proteins in TCs at 10th day, were also analysed and confirmed the same major cellular functions, while the 56 down‐regulated proteins confirmed again their specificity for ECs. In conclusion, we report here the first extensive comparison of proteins from TCs and ECs using a quantitative proteomics approach. Our data show that TCs are completely different from ECs. Protein expression profile showed that TCs play specific roles in intercellular communication and intercellular signalling. Moreover, they might inhibit the oxidative stress and cellular ageing and may have pro‐proliferative effects through the inhibition of apoptosis. The group of proteins identified in this study needs to be explored further for the role in pathogenesis of lung disease.     

A novel quantitative proteomics workflow by isobaric terminal labeling

Quantification by series of b, y fragment ion pairs generated from isobaric-labeled peptides in MS2 spectra has recently been considered an accurate strategy in quantitative proteomics. Here we developed a novel MS2 quantification approach named quantitation by isobaric terminal labeling (QITL) by coupling (18)O labeling with dimethylation. Trypsin-digested peptides were labeled with two (16)O or (18)O atoms at their C-termini in H(2)(16)O or H(2)(18)O. After blocking all ε-amino groups of lysines through guanidination, the N-termini of the peptides were accordingly labeled with formaldehyde-d(2) or formaldehyde. These indistinguishable, isobaric-labeled peptides in MS1 spectra produce b, y fragment ion pairs in the whole mass range of MS2 spectra that can be used for quantification. In this study, the feasibility of QITL was first demonstrated using standard proteins. An accurate and reproducible quantification over a wide dynamic range was achieved. Then, complex rat liver samples were used to verify the applicability of QITL for large-scale quantitative analysis. Finally, QITL was applied to profile the quantitative proteome of hepatocellular carcinoma (HCC) and adjacent non-tumor liver tissues. Given its simplicity, low-cost, and accuracy, QITL can be widely applied in biological samples (cell lines, tissues, and body fluids, etc.) for quantitative proteomic research.     

Metabolic labeling of C. elegans and D. melanogaster for quantitative proteomics

A crucial issue in comparative proteomics is the accurate quantification of differences in protein expression levels. To achieve this, several methods have been developed in which proteins are labeled with stable isotopes either in vivo via metabolic labeling or in vitro by protein derivatization. Although metabolic labeling is the only way to obtain labeling of all proteins, it has thus far only been applied to single- celled organisms and cells in culture. Here we describe quantitative 15N metabolic labeling of the multicellular organisms Caenorhabditis elegans, a nematode, and Drosophila melanogaster, the common fruit fly, achieved by feeding them on 15N-labeled Escherichia coli and yeast, respectively. The relative abundance of individual proteins obtained from different samples can then be determined by mass spectrometry (MS). The applicability of the method is exemplified by the comparison of protein expression levels in two C. elegans strains, one with and one without a germ line. The methodology described provides tools for accurate quantitative proteomic studies in these model organisms.     

Protein labeling by iTRAQ: a new tool for quantitative mass spectrometry in proteome research

A novel, MS-based approach for the relative quantification of proteins, relying on the derivatization of primary amino groups in intact proteins using isobaric tag for relative and absolute quantitation (iTRAQ) is presented. Due to the isobaric mass design of the iTRAQ reagents, differentially labeled proteins do not differ in mass; accordingly, their corresponding proteolytic peptides appear as single peaks in MS scans. Because quantitative information is provided by isotope-encoded reporter ions that can only be observed in MS/MS spectra, we analyzed the fragmentation behavior of ESI and MALDI ions of peptides generated from iTRAQ-labeled proteins using a TOF/TOF and/or a QTOF instrument. We observed efficient liberation of reporter ions for singly protonated peptides at low-energy collision conditions. In contrast, increased collision energies were required to liberate the iTRAQ label from lysine side chains of doubly charged peptides and, thus, to observe reporter ions suitable for relative quantification of proteins with high accuracy. We then developed a quantitative strategy that comprises labeling of intact proteins by iTRAQ followed by gel electrophoresis and peptide MS/MS analyses. As proof of principle, mixtures of five different proteins in various concentration ratios were quantified, demonstrating the general applicability of the approach presented here to quantitative MS-based proteomics.     

UNiquant, a program for quantitative proteomics analysis using stable isotope labeling

Stable isotope labeling (SIL) methods coupled with nanoscale liquid chromatography and high resolution tandem mass spectrometry are increasingly useful for elucidation of the proteome-wide differences between multiple biological samples. Development of more effective programs for the sensitive identification of peptide pairs and accurate measurement of the relative peptide/protein abundance are essential for quantitative proteomic analysis. We developed and evaluated the performance of a new program, termed UNiquant, for analyzing quantitative proteomics data using stable isotope labeling. UNiquant was compared with two other programs, MaxQuant and Mascot Distiller, using SILAC-labeled complex proteome mixtures having either known or unknown heavy/light ratios. For the SILAC-labeled Jeko-1 cell proteome digests with known heavy/light ratios (H/L = 1:1, 1:5, and 1:10), UNiquant quantified a similar number of peptide pairs as MaxQuant for the H/L = 1:1 and 1:5 mixtures. In addition, UNiquant quantified significantly more peptides than MaxQuant and Mascot Distiller in the H/L = 1:10 mixtures. UNiquant accurately measured relative peptide/protein abundance without the need for postmeasurement normalization of peptide ratios, which is required by the other programs.     

评价新型稳定同位素赖氨酸标记在定量蛋白质组学中的应用

为了评价基于2-甲氧基-4,5-二氢-1氢-咪唑稳定同位素试剂在定量蛋白质组学中的应用价值,合成了轻型(D0)和重型(D4)的2-甲氧基-4,5-二氢-1氢-咪唑,通过对标准蛋白BSA酶解后产物的标记确认标记反应的特异性,并观察了标记物在MALDI-TOF-MS和LC-ESI-MS中定量的准确性,标记肽在串联质谱中的离子特点,以及对反相液相色谱行为的影响。结果表明,2-甲氧基-4,5-二氢-1氢-咪唑只与酶解后的肽段赖氨酸侧链氨基反应,具有良好的标记特异性;差异表达蛋白的定量可以通过MALDI和ESI电离模式实现;标记肽的串联质谱主要产生y离子,测序更为简便;反相液相色谱可以保持较好的分离效果,氘原子的引入不会影响保留时间,侧链修饰可以用于涉及液相色谱分离的蛋白质组学技术。2-甲氧基-4,5-二氢-1氢-咪唑稳定同位素试剂可以用于定量蛋白质组学。     

Systematic comparison of label-free, metabolic labeling, and isobaric chemical labeling for quantitative proteomics on LTQ Orbitrap Velos

A variety of quantitative proteomics methods have been developed, including label-free, metabolic labeling, and isobaric chemical labeling using iTRAQ or TMT. Here, these methods were compared in terms of the depth of proteome coverage, quantification accuracy, precision, and reproducibility using a high-performance hybrid mass spectrometer, LTQ Orbitrap Velos. Our results show that (1) the spectral counting method provides the deepest proteome coverage for identification, but its quantification performance is worse than labeling-based approaches, especially the quantification reproducibility; (2) metabolic labeling and isobaric chemical labeling are capable of accurate, precise, and reproducible quantification and provide deep proteome coverage for quantification; isobaric chemical labeling surpasses metabolic labeling in terms of quantification precision and reproducibility; and (3) iTRAQ and TMT perform similarly in all aspects compared in the current study using a CID-HCD dual scan configuration. On the basis of the unique advantages of each method, we provide guidance for selection of the appropriate method for a quantitative proteomics study.     

Comparison of full versus partial metabolic labeling for quantitative proteomics analysis in Arabidopsis thaliana

In recent years a variety of quantitative proteomics techniques have been developed, allowing characterization of changes in protein abundance in a variety of organisms under various biological conditions. Because it allows excellent control for error at all steps in sample preparation and analysis, full metabolic labeling using (15)N has emerged as an important strategy for quantitative proteomics, having been applied in a variety of organisms from yeast to Arabidopsis and even rats. However, challenges associated with complete replacement of (14)N with (15)N can make its application in many complex eukaryotic systems impractical on a routine basis. Extending a concept proposed by Whitelegge et al. (Whitelegge, J. P., Katz, J. E., Pihakari, K. A., Hale, R., Aguilera, R., Gomez, S. M., Faull, K. F., Vavilin, D., and Vermaas, W. (2004) Subtle modification of isotope ratio proteomics; an integrated strategy for expression proteomics. Phytochemistry 65, 1507-1515), we investigate an alternative strategy for quantitative proteomics that relies upon the subtle changes in isotopic envelope shape that result from partial metabolic labeling to compare relative abundances of labeled and unlabeled peptides in complex mixtures. We present a novel algorithm for the automated quantitative analysis of partial incorporation samples via LC-MS. We then compare the performance of partial metabolic labeling with traditional full metabolic labeling for quantification of controlled mixtures of labeled and unlabeled Arabidopsis peptides. Finally we evaluate the performance of each technique for comparison of light- versus dark-grown Arabidopsis with respect to reproducibility and numbers of peptide and protein identifications under more realistic experimental conditions. Overall full metabolic labeling and partial metabolic labeling prove to be comparable with respect to dynamic range, accuracy, and reproducibility, although partial metabolic labeling consistently allows quantification of a higher percentage of peptide observations across the dynamic range. This difference is especially pronounced at extreme ratios. Ultimately both full metabolic labeling and partial metabolic labeling prove to be well suited for quantitative proteomics characterization.     

18O labeling over a coffee break: a rapid strategy for quantitative proteomics

Proteomics-based quantification methods for differential protein expression measurements are among the most important and challenging techniques in the field of mass spectrometry. Though numerous quantification methods have been established, no method meets all the demands for measuring accurate protein expression levels. Of the various relative quantification methods by isotopic labeling, (18)O labeling method has been shown to be simple, specific, cost-effective and applicable to a wide range of analyses. However, some researchers refrain from using the method due to long incubation periods required during the labeling process. To address this problem, we demonstrate a method by which the labeling procedure can be completed in 15 min. We digested and labeled samples using immobilized trypsin on micro-spin columns to speed up the enzyme-mediated oxygen substitution, thereby completing the labeling process within 15 min with high labeling efficiency. We demonstrate the efficiency and accuracy of the method using a four protein mixture and whole cell lysate from rat vascular endothelial cells.     

Peptides OFFGEL electrophoresis: a suitable pre-analytical step for complex eukaryotic samples fractionation compatible with quantitative iTRAQ labeling

Background  

The proteomes of mammalian biological fluids, cells and tissues are complex and composed of proteins with a wide dynamic range. The effective way to overcome the complexity of these proteomes is to combine several fractionation steps. OFFGEL fractionation, recently developed by Agilent Technologies, provides the ability to pre-fractionate peptides into discrete liquid fractions and demonstrated high efficiency and repeatability necessary for the analysis of such complex proteomes.     

Stable isotope labeling of Arabidopsis thaliana cells and quantitative proteomics by mass spectrometry

Quantitative analysis of protein expression is an important tool for the examination of complex biological systems. Albeit its importance, quantitative proteomics is still a challenging task because of the high dynamic range of protein amounts in the cell and the variation in the physical properties of proteins. Stable isotope labeling by amino acids in cell culture (SILAC) has been successfully used in yeast and mammalian cells to measure relative protein abundance by mass spectrometry. Here we show for the first time that proteins from Arabidopsis thaliana cell cultures can be selectively isotope-labeled in vivo by growing cells in the presence of a single stable isotope-labeled amino acid. Among the tested amino acids ([2H3]-leucine, [13C6]arginine, and [2H4]lysine), [13C6]arginine proved to be the most suitable. Incorporation of [13C6]arginine into the proteome was homogeneous and reached efficiencies of about 80%. [13C6]Arginine-labeled A. thaliana suspension cells were used to study the regulation of glutathione S-transferase expression in response to abiotic stress caused by salicylic acid and to identify proteins that bind specifically to phosphorylated 14-3-3 binding motifs on synthesized bait peptides in affinity purification experiments. In conclusion, the combination of stable isotope labeling of plant cells and mass spectrometry is a powerful technology that can be applied to study complex biological processes that involve changes in protein expression such as cellular responses to various kinds of stress or activation of cell signaling.