MSSimulator: Simulation of mass spectrometry data

Mass spectrometry coupled to liquid chromatography (LC-MS and LC-MS/MS) is commonly used to analyze the protein content of biological samples in large scale studies, enabling quantitation and identification of proteins and peptides using a wide range of experimental protocols, algorithms, and statistical models to analyze the data. Currently it is difficult to compare the plethora of algorithms for these tasks. So far, curated benchmark data exists for peptide identification algorithms but data that represents a ground truth for the evaluation of LC-MS data is limited. Hence there have been attempts to simulate such data in a controlled fashion to evaluate and compare algorithms. We present MSSimulator, a simulation software for LC-MS and LC-MS/MS experiments. Starting from a list of proteins from a FASTA file, the simulation will perform in-silico digestion, retention time prediction, ionization filtering, and raw signal simulation (including MS/MS), while providing many options to change the properties of the resulting data like elution profile shape, resolution and sampling rate. Several protocols for SILAC, iTRAQ or MS(E) are available, in addition to the usual label-free approach, making MSSimulator the most comprehensive simulator for LC-MS and LC-MS/MS data.     

CysTRAQ - A combination of iTRAQ and enrichment of cysteinyl peptides for uncovering and quantifying hidden proteomes

Shotgun proteomics is capable of characterizing differences in both protein quality and quantity, and has been applied in various biomedical applications. Unfortunately, the high complexity and dynamic range of proteins in studied samples, clinical in particular, often hinders the identification of relevant proteins. Indeed, information-rich, low abundance proteins often remain undetected, whereas repeatedly reported altered concentrations in high abundance proteins are often ambiguous and insignificant. Several techniques have therefore been developed to overcome this obstacle and provide a deeper insight into the proteome. Here we report a novel approach, which enables iTRAQ reagent quantitation of peptides fractionated based on presence of a cysteine residue (thus CysTRAQ). For the first time, we prove that iTRAQ quantitation is fully compatible with cysteinyl peptide enrichment and is not influenced by the fractionation process. Moreover, the employment of the method combined with high-resolution TripleTOF 5600 mass spectrometer for very fast MS/MS acquisition in human amniotic fluid analysis significantly increased the number of identified proteins, which were simultaneously quantified owing to the introduction of iTRAQ labeling. We herein show that CysTRAQ is a robust and straightforward method with potential application in quantitative proteomics experiments, i.e. as an alternative to the ICAT reagent approach.     

Differential Proteomic Analysis of Acute Contusive Spinal Cord Injury in Rats Using iTRAQ Reagent Labeling and LC–MS/MS

In this experimental study, differential labeling with isobaric tags for relative and absolute quantitation (iTRAQ) reagents followed by liquid chromatography (LC) and tandem mass spectrometry (MS/MS) proteomic approach was used to investigate differences in the proteome of rat spinal cord at 24 h following a moderate contusion injury. Spinal cord protein samples from the injury epicenter (or from sham controls) were trypsinized and differentially labeled with iTRAQ isotopic reagents. The differentially labeled samples were then combined into one sample mixture, separated by LC, and analyzed using MS/MS. Proteins were quantified by comparing the peak areas of iTRAQ reporter fragment ions in MS/MS spectra. The outcome of this analysis revealed that proteins involved in ubiquitination, endocytosis and exocytosis, energy metabolism, inflammatory response, oxidative stress, cytoskeletal disruption, and vascular damage were significantly altered at 24 h following spinal cord injury (SCI). This study demonstrates the utility of the iTRAQ method in proteomic studies and provides further insights into secondary events that occur during acute times following SCI.     

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.     

VEMS 3.0: algorithms and computational tools for tandem mass spectrometry based identification of post-translational modifications in proteins

Protein and peptide mass analysis and amino acid sequencing by mass spectrometry is widely used for identification and annotation of post-translational modifications (PTMs) in proteins. Modification-specific mass increments, neutral losses or diagnostic fragment ions in peptide mass spectra provide direct evidence for the presence of post-translational modifications, such as phosphorylation, acetylation, methylation or glycosylation. However, the commonly used database search engines are not always practical for exhaustive searches for multiple modifications and concomitant missed proteolytic cleavage sites in large-scale proteomic datasets, since the search space is dramatically expanded. We present a formal definition of the problem of searching databases with tandem mass spectra of peptides that are partially (sub-stoichiometrically) modified. In addition, an improved search algorithm and peptide scoring scheme that includes modification specific ion information from MS/MS spectra was implemented and tested using the Virtual Expert Mass Spectrometrist (VEMS) software. A set of 2825 peptide MS/MS spectra were searched with 16 variable modifications and 6 missed cleavages. The scoring scheme returned a large set of post-translationally modified peptides including precise information on modification type and position. The scoring scheme was able to extract and distinguish the near-isobaric modifications of trimethylation and acetylation of lysine residues based on the presence and absence of diagnostic neutral losses and immonium ions. In addition, the VEMS software contains a range of new features for analysis of mass spectrometry data obtained in large-scale proteomic experiments. Windows binaries are available at http://www.yass.sdu.dk/.     

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.     

EBP, a program for protein identification using multiple tandem mass spectrometry datasets

MS/MS combined with database search methods can identify the proteins present in complex mixtures. High throughput methods that infer probable peptide sequences from enzymatically digested protein samples create a challenge in how best to aggregate the evidence for candidate proteins. Typically the results of multiple technical and/or biological replicate experiments must be combined to maximize sensitivity. We present a statistical method for estimating probabilities of protein expression that integrates peptide sequence identifications from multiple search algorithms and replicate experimental runs. The method was applied to create a repository of 797 non-homologous zebrafish (Danio rerio) proteins, at an empirically validated false identification rate under 1%, as a resource for the development of targeted quantitative proteomics assays. We have implemented this statistical method as an analytic module that can be integrated with an existing suite of open-source proteomics software.     

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.     

Isobaric tags for relative and absolute quantitation (iTRAQ) reproducibility: Implication of multiple injections

We analyzed 10 isobaric tags for relative and absolute quantitation (iTRAQ) experiments using three different model organisms across the domains of life: Saccharomyces cerevisiae KAY446, Sulfolobussolfataricus P2, and Synechocystis sp. PCC6803. A double database search strategy was employed to minimize the rate of false positives to less than 3% for all organisms. The reliability of proteins with single-peptide identification was also assessed using the search strategy, coupled with multiple analyses of samples into LC-MS/MS. The outcomes of the three LC-MS/MS analyses provided higher proteome coverage with an average increment in total proteins identified of 6%, 33%, and 50% found in S. cerevisiae, S. solfataricus, and Synechocystis sp., respectively. The iTRAQ quantification values were found to be highly reproducible across the injections, with an average coefficient of variation (CV) of 0.09 (scattering from 0.14 to 0.04) calculated based on log mean average ratio for all three organisms. Hence, we recommend multiple analyses of iTRAQ samples for greater proteome coverage and precise quantification.     

A comparison of MS/MS‐based,stable‐isotope‐labeled,quantitation performance on ESI‐quadrupole TOF and MALDI‐TOF/TOF mass spectrometers

The peptide‐based quantitation accuracy and precision of LC‐ESI (QSTAR Elite) and LC‐MALDI (4800 MALDI TOF/TOF) were compared by analyzing identical Escherichia coli tryptic digests containing iTRAQ‐labeled peptides of defined abundances (1:1, 2.5:1, 5:1, and 10:1). Only 51.4% of QSTAR spectra were used for quantitation by ProteinPilot Software versus 66.7% of LC‐MALDI spectra. The average protein sequence coverages for LC‐ESI and LC‐MALDI were 24.0 and 18.2% (14.9 and 8.4 peptides per protein), respectively. The iTRAQ‐based expression ratios determined by ProteinPilot from the 57 467 ESI‐MS/MS and 26 085 MALDI‐MS/MS spectra were analyzed for measurement accuracy and reproducibility. When the relative abundances of peptides within a sample were increased from 1:1 to 10:1, the mean ratios calculated on both instruments differed by only 0.7–6.7% between platforms. In the 10:1 experiment, up to 64.7% of iTRAQ ratios from LC‐ESI MS/MS spectra failed S/N thresholds and were excluded from quantitation, while only 0.1% of the equivalent LC‐MALDI iTRAQ ratios were rejected. Re‐analysis of an archived LC‐MALDI sample set stored for 5 months generated 3715 MS/MS spectra for quantitation, compared with 3845 acquired originally, and the average ratios differed by only 3.1%. Overall, MS/MS‐based peptide quantitation performance of offline LC‐MALDI was comparable with on‐line LC‐ESI, which required threefold less time. However, offline LC‐MALDI allows the re‐analysis of archived HPLC‐separated samples.     

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 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.     

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。     

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.     

LFQuant: A label‐free fast quantitative analysis tool for high‐resolution LC‐MS/MS proteomics data

Database searching based methods for label‐free quantification aim to reconstruct the peptide extracted ion chromatogram based on the identification information, which can limit the search space and thus make the data processing much faster. The random effect of the MS/MS sampling can be remedied by cross‐assignment among different runs. Here, we present a new label‐free fast quantitative analysis tool, LFQuant, for high‐resolution LC‐MS/MS proteomics data based on database searching. It is designed to accept raw data in two common formats (mzXML and Thermo RAW), and database search results from mainstream tools (MASCOT, SEQUEST, and X!Tandem), as input data. LFQuant can handle large‐scale label‐free data with fractionation such as SDS‐PAGE and 2D LC. It is easy to use and provides handy user interfaces for data loading, parameter setting, quantitative analysis, and quantitative data visualization. LFQuant was compared with two common quantification software packages, MaxQuant and IDEAL‐Q, on the replication data set and the UPS1 standard data set. The results show that LFQuant performs better than them in terms of both precision and accuracy, and consumes significantly less processing time. LFQuant is freely available under the GNU General Public License v3.0 at http://sourceforge.net/projects/lfquant/ .     

MilQuant: a free, generic software tool for isobaric tagging-based quantitation

Isobaric tagging techniques such as iTRAQ and TMT are widely used in quantitative proteomics and especially useful for samples that demand in vitro labeling. Due to diversity in choices of MS acquisition approaches, identification algorithms, and relative abundance deduction strategies, researchers are faced with a plethora of possibilities when it comes to data analysis. However, the lack of generic and flexible software tool often makes it cumbersome for researchers to perform the analysis entirely as desired. In this paper, we present MilQuant, mzXML-based isobaric labeling quantitator, a pipeline of freely available programs that supports native acquisition files produced by all mass spectrometer types and collection approaches currently used in isobaric tagging based MS data collection. Moreover, aside from effective normalization and abundance ratio deduction algorithms, MilQuant exports various intermediate results along each step of the pipeline, making it easy for researchers to customize the analysis. The functionality of MilQuant was demonstrated by four distinct datasets from different laboratories. The compatibility and extendibility of MilQuant makes it a generic and flexible tool that can serve as a full solution to data analysis of isobaric tagging-based quantitation.     

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.     

ICPLQuant – A software for non‐isobaric isotopic labeling proteomics

The main goal of many proteomics experiments is an accurate and rapid quantification and identification of regulated proteins in complex biological samples. The bottleneck in quantitative proteomics remains the availability of efficient software to evaluate and quantify the tremendous amount of mass spectral data acquired during a proteomics project. A new software suite, ICPLQuant, has been developed to accurately quantify isotope‐coded protein label (ICPL)‐labeled peptides on the MS level during LC‐MALDI and peptide mass fingerprint experiments. The tool is able to generate a list of differentially regulated peptide precursors for subsequent MS/MS experiments, minimizing time‐consuming acquisition and interpretation of MS/MS data. ICPLQuant is based on two independent units. Unit 1 performs ICPL multiplex detection and quantification and proposes peptides to be identified by MS/MS. Unit 2 combines MASCOT MS/MS protein identification with the quantitative data and produces a protein/peptide list with all the relevant information accessible for further data mining. The accuracy of quantification, selection of peptides for MS/MS‐identification and the automated output of a protein list of regulated proteins are demonstrated by the comparative analysis of four different mixtures of three proteins (Ovalbumin, Horseradish Peroxidase and Rabbit Albumin) spiked into the complex protein background of the DGPF Proteome Marker.     

Mascot file parsing and quantification (MFPaQ), a new software to parse, validate, and quantify proteomics data generated by ICAT and SILAC mass spectrometric analyses: application to the proteomics study of membrane proteins from primary human endothelial cells

Proteomics strategies based on nanoflow (nano-) LC-MS/MS allow the identification of hundreds to thousands of proteins in complex mixtures. When combined with protein isotopic labeling, quantitative comparison of the proteome from different samples can be achieved using these approaches. However, bioinformatics analysis of the data remains a bottleneck in large scale quantitative proteomics studies. Here we present a new software named Mascot File Parsing and Quantification (MFPaQ) that easily processes the results of the Mascot search engine and performs protein quantification in the case of isotopic labeling experiments using either the ICAT or SILAC (stable isotope labeling with amino acids in cell culture) method. This new tool provides a convenient interface to retrieve Mascot protein lists; sort them according to Mascot scoring or to user-defined criteria based on the number, the score, and the rank of identified peptides; and to validate the results. Moreover the software extracts quantitative data from raw files obtained by nano-LC-MS/MS, calculates peptide ratios, and generates a non-redundant list of proteins identified in a multisearch experiment with their calculated averaged and normalized ratio. Here we apply this software to the proteomics analysis of membrane proteins from primary human endothelial cells (ECs), a cell type involved in many physiological and pathological processes including chronic inflammatory diseases such as rheumatoid arthritis. We analyzed the EC membrane proteome and set up methods for quantitative analysis of this proteome by ICAT labeling. EC microsomal proteins were fractionated and analyzed by nano-LC-MS/MS, and database searches were performed with Mascot. Data validation and clustering of proteins were performed with MFPaQ, which allowed identification of more than 600 unique proteins. The software was also successfully used in a quantitative differential proteomics analysis of the EC membrane proteome after stimulation with a combination of proinflammatory mediators (tumor necrosis factor-alpha, interferon-gamma, and lymphotoxin alpha/beta) that resulted in the identification of a full spectrum of EC membrane proteins regulated by inflammation.