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.     

LTQ‐iQuant: A freely available software pipeline for automated and accurate protein quantification of isobaric tagged peptide data from LTQ instruments

Pulsed Q dissociation enables combining LTQ ion trap instruments with isobaric peptide tagging. Unfortunately, this combination lacks a technique which accurately reports protein abundance ratios and is implemented in a freely available, flexible software pipeline. We developed and implemented a technique assigning collective reporter ion intensity‐based weights to each peptide abundance ratio and calculating a protein's weighted average abundance ratio and p‐value. Using an iTRAQ‐labeled standard mixture, we compared our technique's performance to the commercial software MASCOT, finding that it performed better than MASCOT's nonweighted averaging and median peptide ratio techniques, and equal to its weighted averaging technique. We also compared performance of the LTQ‐Orbitrap plus our technique to 4800 MALDI TOF/TOF plus Protein Pilot, by analyzing an iTRAQ‐labeled stem cell lysate. We found highly correlated protein abundance ratios, indicating that the LTQ‐Orbitrap plus our technique yields results comparable to the current standard. We implemented our technique in a freely available, automated software pipeline, called LTQ‐iQuant, which is mzXML‐compatible; supports iTRAQ 4‐plex and 8‐plex LTQ data; and can be modified for and have weights trained to a user's LTQ and other isobaric peptide tagging methods. LTQ‐iQuant should make LTQ instruments and isobaric peptide tagging accessible to more proteomic researchers.     

iTRAQ as a method for optimization: Enhancing peptide recovery after gel fractionation

At the dawn of a new era in label‐free quantitation on high‐resolution MS instruments, classical methods such as iTRAQ continue to provide very useful insights in comparative proteomics. The potential to multiplex samples makes this reporter‐based labeling technique highly suited for method optimization as demonstrated here by a set of standard series. Instead of studying ratios of annotated proteins, we propose an alternative method, based on the analysis of the average reporter ratios of all the spectra from a sample or a large distinct subset herein. This strategy circumvents the bias, associated with the annotation and iTRAQ quantitation, leading to increased adequacy in measuring yield differences between workflows. As gel electrophoresis prior to MS analysis is highly beneficial, for example, as a fractionation step, the approach was applied to evaluate the influence of several parameters of the established in‐gel digestion protocol. We quantified the negative effect of SYPRO Ruby staining and the positive effect of gel fixation prior to digestion on peptide yield. Finally, we emphasize the benefits of adding CaCl₂ and ACN to a tryptic in‐gel digest, resulting in an up to tenfold enhanced peptide recovery and fewer trypsin missed cleavages.     

Qualitative and quantitative analysis of the adult Drosophila melanogaster proteome

Drosophila melanogaster is one of the most widely used model organisms in life sciences. Mapping its proteome is of great significance for understanding the biological characteristics and tissue functions of this species. However, the comprehensive coverage of its proteome remains a challenge. Here, we describe a high‐coverage analysis of whole fly through a 1D gel electrophoresis and LC‐MS/MS approach. By combining the datasets of two types of SDS‐PAGE and two kinds of tagmata, the high‐coverage analysis resulted in the identification of 5262 genes, which correspond to 38.23% of the entire coding genes. Moreover, we found that the fly head and body have different molecular weight distributions of their proteomes when the proteins were resolved with SDS‐PAGE and image analysis of the stained gel. This phenomenon was further confirmed by both label‐free and isobaric tags for relative and absolute quantitation‐based quantitative approaches. The consistent results of the two different quantitation methods also demonstrated the stability and accuracy of the LC‐MS/MS platform. The MS proteomics data have been deposited to the ProteomeXchange with identifiers PXD000454 and PXD000455 ( http://proteomecentral.proteomexchange.org/dataset/PXD000454 ; ( http://proteomecentral.proteomexchange.org/dataset/PXD000455 ).     

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.     

Exploring skyline for both MSE‐based label‐free proteomics and HRMS quantitation of small molecules

The MS^E (where MS^E is low energy (MS) and elevated energy (E) mode of acquisition) acquisition method commercialized by Waters on its Q‐TOF instruments is regarded as a unique data‐independent fragmentation approach that improves the accuracy and dynamic range of label‐free proteomic quantitation. Due to its special format, MS^E acquisition files cannot be independently analyzed with most widely used open‐source proteomic software specialized for processing data‐dependent acquisition files. In this study, we established a workflow integrating Skyline, a popular and versatile peptide‐centric quantitation program, and a statistical tool DiffProt to fulfill MS^E‐based proteomic quantitation. Comparison with the vendor software package for analyzing targeted phosphopeptides and global proteomic datasets reveals distinct advantages of Skyline in MS^E data mining, including sensitive peak detection, flexible peptide filtering, and transparent step‐by‐step workflow. Moreover, we developed a new procedure such that Skyline MS1 filtering was extended to small molecule quantitation for the first time. This new utility of Skyline was examined in a protein–ligand interaction experiment to identify multiple chemical compounds specifically bound to NDM‐1 (where NDM is New Delhi metallo‐β‐lactamase 1), an antibiotics‐resistance target. Further improvement of the current weaknesses in Skyline MS1 filtering is expected to enhance the reliability of this powerful program in full scan‐based quantitation of both peptides and small molecules.     

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.     

Evaluation of different peptide fragmentation types and mass analyzers in data‐dependent methods using an Orbitrap Fusion Lumos Tribrid mass spectrometer

One of the major additions in MS technology has been the irruption of the Orbitrap mass analyzer, which has boosted the proteomics analyses of biological complex samples since its introduction. Here, we took advantage of the capabilities of the new Orbitrap Fusion Lumos Tribrid mass spectrometer to assess the performance of different data‐dependent acquisition methods for the identification and quantitation of peptides and phosphopeptides in single‐shot analysis of human whole cell lysates. Our study explored the capabilities of tri‐hibrid mass spectrometers for (phospho‐) peptide identification and quantitation using different gradient lengths, sample amounts, and combinations of different peptide fragmentation types and mass analyzers. Moreover, the acquisition of the same complex sample with different acquisition methods resulted in the generation of a dataset to be used as a reference for further analyses, and a starting point for future optimizations in particular applications.     

Characterization of a high field Orbitrap mass spectrometer for proteome analysis

The field of proteomics continues to be driven by improvements in analytical technology, notably in peptide separation, quantitative MS, and informatics. In this study, we have characterized a hybrid linear ion trap high field Orbitrap mass spectrometer (Orbitrap Elite) for proteomic applications. The very high resolution available on this instrument allows 95% of all peptide masses to be measured with sub‐ppm accuracy that in turn improves protein identification by database searching. We further confirm again that mass accuracy in tandem mass spectra is a valuable parameter for improving the success of protein identification. The new CID rapid scan type of the Orbitrap Elite achieves similar performance as higher energy collision induced dissociation fragmentation and both allow the identification of hundreds of proteins from as little as 0.1 ng of protein digest on column. The new instrument outperforms its predecessor the Orbitrap Velos by a considerable margin on each metric assessed that makes it a valuable and versatile tool for MS‐based proteomics.     

Morpheus Spectral Counter: A computational tool for label‐free quantitative mass spectrometry using the Morpheus search engine

Label‐free quantitative MS based on the Normalized Spectral Abundance Factor (NSAF) has emerged as a straightforward and robust method to determine the relative abundance of individual proteins within complex mixtures. Here, we present Morpheus Spectral Counter (MSpC) as the first computational tool that directly calculates NSAF values from output obtained from Morpheus, a fast, open‐source, peptide‐MS/MS matching engine compatible with high‐resolution accurate‐mass instruments. NSAF has distinct advantages over other MS‐based quantification methods, including a greater dynamic range as compared to isobaric tags, no requirement to align and re‐extract MS1 peaks, and increased speed. MSpC features an easy‐to‐use graphic user interface that additionally calculates both distributed and unique NSAF values to permit analyses of both protein families and isoforms/proteoforms. MSpC determinations of protein concentration were linear over several orders of magnitude based on the analysis of several high‐mass accuracy datasets either obtained from PRIDE or generated with total cell extracts spiked with purified Arabidopsis 20S proteasomes. The MSpC software was developed in C# and is open sourced under a permissive license with the code made available at http://dcgemperline.github.io/Morpheus_SpC/ .     

Combining low- and high-energy tandem mass spectra for optimized peptide quantification with isobaric tags

Isobaric tagging, via TMT or iTRAQ, is widely used in quantitative proteomics. To date, tandem mass spectrometric analysis of isobarically-labeled peptides with hybrid ion trap–orbitrap (LTQ-OT) instruments has been mainly carried out with higher-energy C-trap dissociation (HCD) or pulsed q dissociation (PQD). HCD provides good fragmentation of the reporter-ions, but peptide sequence-ion recovery is generally poor compared to collision-induced dissociation (CID). Herein, we describe an approach where CID and HCD spectra are combined. The approach ensures efficiently both identification and relative quantification of proteins. Tandem mass tags (TMTs) were used to label digests of human plasma and LC-MS/MS was performed with an LTQ-OT instrument. Different HCD collision energies were tested. The benefits to use CID and HCD with respect to HCD alone were demonstrated in terms of number of identifications, subsequent number of quantifiable proteins, and quantification accuracy. A program was developed to merge the peptide sequence-ion m/z range from CID spectra and the reporter-ion m/z range from HCD spectra, and alternatively to separate both spectral data into different files. As parallel CID in the LTQ almost doesn't affect the analysis duty cycle, the procedure should become a standard for quantitative analyses of proteins with isobaric tagging using LTQ-OT instruments.     

Comparative Proteomic Profiling of Methicillin‐Susceptible and Resistant Staphylococcus aureus

Staphylococcus aureus is a highly successful human pathogen responsible for a wide range of infections. This study provides insights into the virulence, pathogenicity, and antimicrobial resistance determinants of methicillin‐susceptible and methicillin‐resistant S. aureus (MSSA; MRSA) recovered from non‐healthcare environments. Three environmental MSSA and three environmental MRSA are selected for proteomic profiling using isobaric tag for relative and absolute quantitation tandem mass spectrometry (iTRAQ MS/MS). Gene Ontology annotation and Kyoto Encyclopedia of Genes and Genomes pathway annotation are applied to interpret the functions of the proteins detected. 792 proteins are identified in MSSA and MRSA. Comparative analysis of MRSA and MSSA reveals that 8 of out 792 proteins are upregulated and 156 are downregulated. Proteins that have differences in abundance are predominantly involved in catalytic and binding activity. Among 164 differently abundant proteins, 29 are involved in pathogenesis, antimicrobial resistance, stress response, mismatch repair, and cell wall synthesis. Twenty‐two proteins associated with pathogenicity including SPA, SBI, CLFA, and DLT are upregulated in MRSA. Moreover, the upregulated pathogenic protein ENTC2 in MSSA is determined to be a super antigen, potentially capable of triggering toxic shock syndrome in the host. Enhanced pathogenicity, antimicrobial resistance, and stress response are observed in MRSA compared to MSSA.     

An Integrated Proteomic Approach Uncovers Novel Substrates and Functions of the Lon Protease in Escherichia coli

Controlling the cellular abundance and proper function of proteins by proteolysis is a universal process in all living organisms. In Escherichia coli, the ATP‐dependent Lon protease is crucial for protein quality control and regulatory processes. To understand how diverse substrates are selected and degraded, unbiased global approaches are needed. We employed a quantitative Super‐SILAC (stable isotope labeling with amino acids in cell culture) mass spectrometry approach and compared the proteomes of a lon mutant and a strain producing the protease to discover Lon‐dependent physiological functions. To identify Lon substrates, we took advantage of a Lon trapping variant, which is able to translocate substrates but unable to degrade them. Lon‐associated proteins were identified by label‐free LC‐MS/MS. The combination of both approaches revealed a total of 14 novel Lon substrates. Besides the identification of known pathways affected by Lon, for example, the superoxide stress response, our cumulative data suggests previously unrecognized fundamental functions of Lon in sulfur assimilation, nucleotide biosynthesis, amino acid and central energy metabolism.     

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.     

ITMSQ: A software tool for N‐ and C‐terminal fragment ion pairs based isobaric tandem mass spectrometry quantification

Tandem MS (MS2) quantification using the series of N‐ and C‐terminal fragment ion pairs generated from isobaric‐labelled peptides was recently considered an accurate strategy in quantitative proteomics. However, the presence of multiplexed terminal fragment ion in MS2 spectra may reduce the efficiency of peptide identification, resulting in lower identification scores or even incorrect assignments. To address this issue, we developed a quantitative software tool, denoted isobaric tandem MS quantification (ITMSQ), to improve N‐ and C‐terminal fragment ion pairs based isobaric MS2 quantification. A spectrum splitting module was designed to separate the MS2 spectra from different samples, increasing the accuracy of both identification and quantification. ITMSQ offers a convenient interface through which parameters can be changed along with the labelling method, and the result files and all of the intermediate files can be exported. We performed an analysis of in vivo terminal amino acid labelling labelled HeLa samples and found that the numbers of quantified proteins and peptides increased by 13.64 and 27.52% after spectrum splitting, respectively. In conclusion, ITMSQ provides an accurate and reliable quantitative solutionfor N‐ and C‐terminal fragment ion pairs based isobaric MS2 quantitative methods.     

MS‐based ligand binding assays with speed,sensitivity, and specificity

Immunoassays are widely used in biochemical/clinical laboratories owing to their simplicity, speed, and sensitivity. We combined self‐assembled monolayer‐based immunoassays with MALDI‐TOF MS to show that high‐fidelity surface preparations with a novel matrix deposition/crystallization technique permits quantitative analysis of monolayer‐bound antigens at picomolar detection limits. Calibration curves for intact proteins are possible over a broad concentration range and improved specificity of MS‐immunoassays is highlighted by simultaneous label‐free quantitation of ligand‐bound protein complexes.     

Sequential protein extraction as an efficient method for improved proteome coverage in larvae of Atlantic salmon (Salmo salar)

Understanding diet‐ and environmentally induced physiological changes in fish larvae is a major goal for the aquaculture industry. Proteomic analysis of whole fish larvae comprising multiple tissues offers considerable potential but is challenging due to the very large dynamic range of protein abundance. To extend the coverage of the larval phase of the Atlantic salmon (Salmo salar) proteome, we applied a two‐step sequential extraction (SE) method, based on differential protein solubility, using a nondenaturing buffer containing 150 mM NaCl followed by a denaturing buffer containing 7 M urea and 2 M thiourea. Extracts prepared using SE and one‐step direct extraction were characterized via label‐free shotgun proteomics using nanoLC‐MS/MS (LTQ‐Orbitrap). SE partitioned the proteins into two fractions of approximately equal amounts, but with very distinct protein composition, leading to identification of ～40% more proteins than direct extraction. This fractionation strategy enabled the most detailed characterization of the salmon larval proteome to date and provides a platform for greater understanding of physiological changes in whole fish larvae. The MS data are available via the ProteomeXchange Consortium PRIDE partner repository, dataset PXD003366.     

Label‐free profiling of skeletal muscle using high‐definition mass spectrometry

We report automated and time‐efficient (2 h per sample) profiling of muscle using ultra‐performance LC coupled directly with high‐definition MS (HDMS^E). Soluble proteins extracted from rat gastrocnemius (n = 10) were digested with trypsin and analyzed in duplicate using a 90 min RPLC gradient. Protein identification and label‐free quantitation were performed from HDMS^E spectra analyzed using Progenesis QI for Proteomics software. In total 1514 proteins were identified. Of these, 811 had at least three unique peptides and were subsequently used to assess the dynamic range and precision of LC‐HDMS^E label‐free profiling. Proteins analyzed by LC‐HDMS^E encompass the entire complement of glycolytic, β‐oxidation, and tricarboxylic acid enzymes. In addition, numerous components of the electron transport chain and protein kinases involved in skeletal muscle regulation were detected. The dynamic range of protein abundances spanned four orders of magnitude. The correlation between technical replicates of the ten biological samples was R² = 0.9961 ± 0.0036 (95% CI = 0.9940 – 0.9992) and the technical CV averaged 7.3 ± 6.7% (95% CI = 6.87 – 7.79%). This represents the most sophisticated label‐free profiling of skeletal muscle to date.     

Improved Methodology for Sensitive and Rapid Quantitative Proteomic Analysis of Adult‐Derived Mouse Microglia: Application to a Novel In Vitro Mouse Microglial Cell Model

Microglia, as the resident brain immune cells, can exhibit a broad range of activation phenotypes, which have been implicated in a multitude of central nervous system disorders. Current widely studied microglial cell lines are mainly derived from neonatal rodent brain that can limit their relevance to homeostatic function and disease‐related neuroimmune responses in the adult brain. Recently, an adult mouse brain‐derived microglial cell line has been established; however, a comprehensive proteome dataset remains lacking. Here, an optimization method for sensitive and rapid quantitative proteomic analysis of microglia is described that involves suspension trapping (S‐Trap) for efficient and reproducible protein extraction from a limited number of microglial cells expected from an adult mouse brain (≈300 000). Using a 2‐h gradient on a 75‐cm UPLC column with a modified data dependent acquisition method on a hybrid quadrupole‐Orbitrap mass spectrometer, 4855 total proteins have been identified where 4698 of which are quantifiable by label‐free quantitation with a median and average coefficient of variation (CV) of 6.7% and 10.6%, respectively. This dataset highlights the high depth of proteome coverage and related quantitation precision of the adult‐derived microglial proteome including proteins associated with several key pathways related to immune response. Data are available via ProteomeXchange with identifier PXD012006.