Quantitative Analysis of mTRAQ-Labeled Proteome Using Full MS Scans

Enhanced Multiplexing Technology for Proteomics

The identification of thousands of proteins and their relative levels of expression has furthered understanding of biological processes and disease and stimulated new systems biology hypotheses. Quantitative proteomics workflows that rely on analytical assays such as mass spectrometry have facilitated high-throughput measurements of proteins partially due to multiplexing. Multiplexing allows proteome differences across multiple samples to be measured simultaneously, resulting in more accurate quantitation, increased statistical robustness, reduced analysis times, and lower experimental costs. The number of samples that can be multiplexed has evolved from as few as two to more than 50, with studies involving more than 10 samples being denoted as enhanced multiplexing or hyperplexing. In this review, we give an update on emerging multiplexing proteomics techniques and highlight advantages and limitations for enhanced multiplexing strategies.

Quantification of Serum Metabolites in Early Colorectal Adenomas Using Isobaric Labeling Mass Spectrometry

A major challenge in reducing the death rate of colorectal cancer is to screen patients using low-invasive testing. A blood test shows a high compliance rate with reduced invasiveness. In this work, a multiplex isobaric tag labeling strategy coupled with mass spectrometry is adopted to relatively quantify primary and secondary amine-containing metabolites in serum for the discovery of metabolite level changes of colorectal cancer. Serum samples from patients at different risk statuses and colorectal cancer growth statuses are studied. Metabolite identification is based on accurate mass matching and/or retention time of labeled metabolite standards. We quantify 40 metabolites across all the serum samples, including 18 metabolites validated with standards. We find significantly decreased levels of threonine and asparagine in the patients with growing adenomas or high-risk adenomas (p < 0.05). Glutamine levels decrease in patients with adenomas of unknown growth status or high-risk adenomas. In contrast, arginine levels are elevated in patients with low-risk adenoma. Receiver operating characteristic analysis shows high sensitivity and specificity of these metabolites for detecting growing adenomas. Based on these results, we conclude that a few metabolites identified here might contribute to distinguishing colorectal patients with growing adenomas from normal individuals and patients with unknown growth status of adenomas.

Chemical isotope labeling for quantitative proteomics

Advancements in liquid chromatography and mass spectrometry over the last decades have led to a significant development in mass spectrometry-based proteome quantification approaches. An increasingly attractive strategy is multiplex isotope labeling, which significantly improves the accuracy, precision and throughput of quantitative proteomics in the data-dependent acquisition mode. Isotope labeling-based approaches can be classified into MS1-based and MS2-based quantification. In this review, we give an overview of approaches based on chemical isotope labeling and discuss their principles, benefits, and limitations with the goal to give insights into fundamental questions and provide a useful reference for choosing a method for quantitative proteomics. As a perspective, we discuss the current possibilities and limitations of multiplex, isotope labeling approaches for the data-independent acquisition mode, which is increasing in popularity.

Increasing the throughput of sensitive proteomics by plexDIA

Current mass spectrometry methods enable high-throughput proteomics of large sample amounts, but proteomics of low sample amounts remains limited in depth and throughput. To increase the throughput of sensitive proteomics, we developed an experimental and computational framework, called plexDIA, for simultaneously multiplexing the analysis of peptides and samples. Multiplexed analysis with plexDIA increases throughput multiplicatively with the number of labels without reducing proteome coverage or quantitative accuracy. By using three-plex non-isobaric mass tags, plexDIA enables quantification of threefold more protein ratios among nanogram-level samples. Using 1-hour active gradients, plexDIA quantified ~8,000 proteins in each sample of labeled three-plex sets and increased data completeness, reducing missing data more than twofold across samples. Applied to single human cells, plexDIA quantified ~1,000 proteins per cell and achieved 98% data completeness within a plexDIA set while using ~5 minutes of active chromatography per cell. These results establish a general framework for increasing the throughput of sensitive and quantitative protein analysis.

Optimization of the use of Py-Tag for next generation derivatization reagents in imaging mass spectrometry

To demonstrate the accurate analysis of catecholamines and amino acid using derivatization reagents, we investigated the reaction conditions for 2,4,6-triethyl-3,5-dimethyl pyrylium trifluoromethanesulfonate (Py-Tag), derivatization of the targets dopamine (DA) and γ-aminobutyric acid (GABA) on tissue sections, and constructed an optimized reaction compartment. Ten different Py-Tag reaction conditions with the targets were considered. The optimal condition for the Py-Tag reaction with the targets was identified as a 70% methanol with 5% trimethylamine (v/v) solution at 60 °C under homogenous conditions. To reproduce this reaction on tissue sections, we constructed a reaction compartment to maintain humidity levels and facilitate the derivatization reaction. Moreover, visualization of DA and GABA was archived by derivatized-imaging mass spectrometry. Brain sections of unilateral 6-OHDA lesioned Parkinson's disease model rats showed Py-Tag DA (m/z 328.3) in the unilateral striatum and Py-Tag GABA (m/z 278.3) in the cerebral cortex, striatum, hippocampus and hypothalamus. Using the Parkinson's disease model rat brain, images with left-right differences were obtained for the localization of DA and GABA. These findings indicate that it is important to consider the reaction conditions that allow high reaction efficiency between DA or GABA and Py-Tag as well as high quality imaging of sections.

Isotopic N,N-dimethyl leucine tags for absolute quantification of clusterin and apolipoprotein E in Alzheimer's disease

Alzheimer's disease (AD) is the most common form of dementia and one of the leading causes of death in the United States. In the past decades, extensive efforts have been devoted to biomarker discovery for early diagnosis and treatment of AD. Herein, this study aims to quantify clusterin (CLU) and apolipoprotein E (APOE) in blood samples from AD patients and evaluate these two proteins as potential biomarkers in AD diagnosis. In-house synthesized 5-plex isotopic N,N-dimethyl leucine (iDiLeu) tags were used to label target peptide standards at different concentrations to construct standard curves. Our study revealed that the levels of CLU and APOE exhibited clear differences in male vs. female AD groups but not in male vs. female non-AD groups. In contrast, the levels of serum CLU and APOE did not show statistically significant differences in the AD groups and non-AD groups. Principal component analysis (PCA) with CLU and APOE showed some separation between the AD and non-AD participants. Significance: Dissecting CLU and APOE heterogeneity in AD pathogenesis may therefore facilitate delineating the pathological relevance for sex-related pathways, leading to personalized medicine in the future. Collectively, this study introduces a cost-effective absolute quantitative proteomics strategy for target protein quantitation and lays the foundation for future investigation of CLU and APOE as potential biomarkers for AD. SIGNIFICANCE STATEMENT: As blood-based biomarkers for AD diagnosis are cost-effective and introduce less invasiveness, discovery and validation of biomarkers in the blood samples of AD patients have become a hot topic in Alzheimer's and dementia research. Thus far, amyloid β (Aβ), total-tau and phosphorylated tau (p-tau) in blood show great accuracy and specificity in diagnosis of AD. However, the underlying mechanism of AD pathology remains to be elusive and complex. Besides these well studied proteins, many other proteins, such as clusterin (CLU) and apolipoprotein E (APOE) have also been found to be related to AD development. It has been implicated that these two proteins are involved in Aβ clearance and deposition. In this study, we measure the absolute concentrations of these two proteins in blood and shed some light on the potential roles of CLU and APOE in AD pathology. Dissecting CLU and APOE heterogeneity in AD pathogenesis may therefore facilitate delineating the pathological relevance for specific pathways between different genders, leading to personalized medicine in the future. Collectively, this study introduces a cost-effective absolute quantitative proteomics strategy for target protein quantitation and lays the foundation for future investigation of CLU and APOE as potential biomarkers for AD.

MON-2, a Golgi protein, mediates autophagy-dependent longevity in Caenorhabditis elegans

The Golgi apparatus plays a central role in trafficking cargoes such as proteins and lipids. Defects in the Golgi apparatus lead to various diseases, but its role in organismal longevity is largely unknown. Using a quantitative proteomic approach, we found that a Golgi protein, MON-2, was up-regulated in long-lived Caenorhabditis elegans mutants with mitochondrial respiration defects and was required for their longevity. Similarly, we showed that DOP1/PAD-1, which acts with MON-2 to traffic macromolecules between the Golgi and endosome, contributed to the longevity of respiration mutants. Furthermore, we demonstrated that MON-2 was required for up-regulation of autophagy, a longevity-associated recycling process, by activating the Atg8 ortholog GABARAP/LGG-1 in C. elegans. Consistently, we showed that mammalian MON2 activated GABARAPL2 through physical interaction, which increased autophagic flux in mammalian cells. Thus, the evolutionarily conserved role of MON2 in trafficking between the Golgi and endosome is an integral part of autophagy-mediated longevity.

Proteomic Interrogation in Cancer Biomarker

Biomarkers factor into the diagnosis and treatment of almost every patient with cancer. The innovation in proteomics follows improvement of mass spectrometry techniques and data processing strategy. Recently, proteomics and typical biological studies have been the answer for clinical applications. The clinical proteomics techniques are now actively adapted to protein identification in large patient cohort, biomarker development for more sensitive and specific screening based on quantitative data. And, it is important for clinical, translational researchers to be acutely aware of the issues surrounding appropriate biomarker development, in order to facilitate entry of clinically useful biomarkers into the clinic. Here, we discuss in detail include the case research for clinical proteomics. Furthermore, we give an overview on the current developments and novel findings in proteomics-based cancer biomarker research.

Analyzing Ribosome Remodeling in Health and Disease

Increasing evidence suggests that ribosomes actively regulate protein synthesis. However, much of this evidence is indirect, leaving this layer of gene regulation largely unexplored, in part due to methodological limitations. Indeed, evidence is reviewed demonstrating that commonly used methods, such as transcriptomics, are inadequate because the variability in mRNAs coding for ribosomal proteins (RP) does not necessarily correspond to RP variability. Thus protein remodeling of ribosomes should be investigated by methods that allow direct quantification of RPs, ideally of isolated ribosomes. Such methods are reviewed, focusing on mass spectrometry and emphasizing method-specific biases and approaches to control these biases. It is argued that using multiple complementary methods can help reduce the danger of interpreting reproducible systematic biases as evidence for ribosome remodeling.

Secretome Proteomic Approaches for Biomarker Discovery: An Update on Colorectal Cancer

Searching for new cancer-related biomarkers is a key priority for the early detection of solid tumors, such as colorectal cancer (CRC), in clinically relevant biological fluids. The cell line and/or tumor tissue secretome represents a valuable resource for discovering novel protein markers secreted by cancer cells. The advantage of a secretome analysis is the reduction of the large dynamic range characterizing human plasma/serum, and the simultaneous enrichment of low abundance cancer-secreted proteins, thereby overcoming the technical limitations underlying the direct search in blood samples. In this review, we provided a comprehensive overview of recent studies on the CRC secretome for biomarker discovery, focusing both on methodological and technical aspects of secretome proteomic approaches and on biomarker-independent validation in CRC patient samples (blood and tissues). Secretome proteomics are mainly based on LC-MS/MS analyses for which secretome samples are either in-gel or in-solution trypsin-digested. Adequate numbers of biological and technical replicates are required to ensure high reproducibility and robustness of the secretome studies. Moreover, another major challenge is the accuracy of proteomic quantitative analysis performed by label-free or labeling methods. The analysis of differentially expressed proteins in the CRC secretome by using bioinformatic tools allowed the identification of potential biomarkers for early CRC detection. In this scenario, this review may help to follow-up the recent secretome studies in order to select promising circulating biomarkers to be validated in larger screenings, thereby contributing toward a complete translation in clinical practice.

Progress and pitfalls of using isobaric mass tags for proteome profiling

Introduction: Quantitative proteomics using mass spectrometry is performed via label-free or label-based approaches. Labeling strategies rely on the incorporation of stable heavy isotopes by metabolic, enzymatic, or chemical routes. Isobaric labeling uses chemical labels of identical masses but of different fragmentation behaviors to allow the relative quantitative comparison of peptide/protein abundances between biological samples.Areas covered: We have carried out a systematic review on the use of isobaric mass tags in proteomic research since their inception in 2003. We focused on their quantitative performances, their multiplexing evolution, as well as their broad use for relative quantification of proteins in pre-clinical models and clinical studies. Current limitations, primarily linked to the quantitative ratio distortion, as well as state-of-the-art and emerging solutions to improve their quantitative readouts are discussed.Expert opinion: The isobaric mass tag technology offers a unique opportunity to compare multiple protein samples simultaneously, allowing higher sample throughput and internal relative quantification for improved trueness and precision. Large studies can be performed when shared reference samples are introduced in multiple experiments. The technology is well suited for proteome profiling in the context of proteomic discovery studies.

Label-free quantitative proteomics identifies Smarca4 is involved in vascular calcification

Vascular calcification (VC) is a pathological process characterized by abnormal deposition of calcium phosphate, hydroxyapatite and other mineral substances in the vascular wall. Hyperphosphorus is an important risk factor associated with VC in the general population and patients with chronic kidney disease (CKD). However, there is still a lack of early biomarkers for hyperphosphorus induced VC. We established a calcific rat aorta vascular smooth muscle cells (RASMCs) model by stimulating with β-glycerophosphate. Then we performed label-free quantitative proteomics combined with liquid chromatograph–mass spectrometer/mass spectrometer (LC-2D-MS/MS）analysis and bioinformatics analysis to find the potential biomarkers for VC. In the current study, we identified 113 significantly proteins. Fifty six of these proteins were significantly up-regulated and the other 57 proteins were significantly decreased in calcific RASMCs, compared to that of normal control cells (fold-change (fc)>1.2, p < .05). Bioinformatics analysis indicated that these significant proteins mainly involved in the placenta blood vessel development and liver regeneration. Their molecule function was cell adhesion molecule binding. Among them, Smarca4 is significantly up-regulated in calcific RASMCs with fc = 2.72 and p = .01. In addition, we also established VC rat model. Real-time quantitative PCR analysis confirmed that the expression of Smarca4 was significantly increased in the aorta of calcified rat. Consistent with the up-regulation of Smarca4, the expression of VC associated microRNA such as miR-133b and miR-155 was also increased. Consequently, our study demonstrates that Smarca4 is involved in hyperphosphorus-induced VC. This finding may contribute to the early diagnosis and prevention of VC.

Trends in the Design of New Isobaric Labeling Reagents for Quantitative Proteomics

Modern mass spectrometry is one of the most frequently used methods of quantitative proteomics, enabling determination of the amount of peptides in a sample. Although mass spectrometry is not inherently a quantitative method due to differences in the ionization efficiency of various analytes, the application of isotope-coded labeling allows relative quantification of proteins and proteins. Over the past decade, a new method for derivatization of tryptic peptides using isobaric labels has been proposed. The labels consist of reporter and balanced groups. They have the same molecular weights and chemical properties, but differ in the distribution of stable heavy isotopes. These tags are designed in such a way that during high energy collision induced dissociation (CID) by tandem mass spectrometry, the isobaric tag is fragmented in the specific linker region, yielding reporter ions with different masses. The mass shifts among the reporter groups are compensated by the balancing groups so that the overall mass is the same for all forms of the reagent. Samples of peptides are labeled with the isobaric mass tags in parallel and combined for analysis. Quantification of individual peptides is achieved by comparing the intensity of reporter ions in the tandem mass (MS/MS) spectra. Isobaric markers have found a wide range of potential applications in proteomics. However, the currently available isobaric labeling reagents have some drawbacks, such as high cost of production, insufficient selectivity of the derivatization, and relatively limited enhancement of sensitivity of the analysis. Therefore, efforts have been devoted to the development of new isobaric markers with increased usability. The search for new isobaric markers is focused on developing a more selective method of introducing a tag into a peptide molecule, increasing the multiplexicity of markers, lowering the cost of synthesis, and increasing the sensitivity of measurement by using ionization tags containing quaternary ammonium salts. Here, the trends in the design of new isobaric labeling reagents for quantitative proteomics isobaric derivatization strategies in proteomics are reviewed, with a particular emphasis on isobaric ionization tags. The presented review focused on different types of isobaric reagents used in quantitative proteomics, their chemistry, and advantages offer by their application.

A Strategy for Discovery and Verification of Candidate Biomarkers in Cerebrospinal Fluid of Preclinical Alzheimer's Disease

Alzheimer's disease (AD), a progressive neurodegenerative disease, is characterized by the accumulation of senile plaques, neurofibrillary tangles, and loss of synapses and neurons in the brain. The pathophysiological process of AD begins with a long asymptomatic phase, which provides a potential opportunity for early therapeutic intervention. Therefore, it is crucial to define putative biomarkers via reliable and validated methods for early diagnosis of AD. Here, we characterized candidate biomarkers by discovery proteomics analysis of cerebrospinal fluid (CSF), revealing that 732 and 704 proteins with more than one unique peptide were identified in healthy controls and preclinical AD patients, respectively. Among them, 79 and 98 proteins were significantly altered in preclinical AD for women and men, respectively, many of which have been demonstrated with consistent regulation pattern in patients with mild cognitive impairment or AD dementia. In-house developed 5-plex isotopic N,N-dimethyl leucine (iDiLeu) tags were further utilized to verify candidate biomarkers, neurosecretory protein VGF (VGF) and apolipoprotein E (apoE). By labeling peptide standards with different iDiLeu tags, a four-point internal calibration curve was constructed to allow for determination of the absolute amount of target analytes in CSF through a single liquid chromatography-mass spectrometry run.

Development of a parallel microbore hollow fiber enzyme reactor platform for online 18O-labeling: Application to lectin-specific lung cancer N-glycoproteome

We introduce a simple online ¹⁸O-labeling protocol for protein samples that uses a parallelizing microbore hollow fiber enzyme reactor (mHFER) as an alternative tool for online proteolytic digestion. Online ¹⁸O-labeling is performed by separately attaching two mHFERs in parallel to a 10-port switching valve with a high-pressure syringe pump and two syringes containing ¹⁶O- or ¹⁸O-water. ¹⁶O-/¹⁸O-labeled peptides are formed in this manner and simultaneously analyzed online using nanoflow liquid chromatography-tandem mass spectrometry (nLC-MS/MS) without any residual trypsin activity. The usefulness of a parallel mHFER platform (P-mHFER) in ¹⁸O-labeling was tested using both cytochrome C and alpha-1-acid-glycoprotein to verify the incorporation level of two ¹⁸O atoms into tryptic peptides and to provide a quantitative assessment with varied mixing ratios. Additionally, our ¹⁸O-labeling approach was used to study the serum N-glycoproteome from lung cancer patients and controls to evaluate the applicability of lectin-based quantitative N-glycoproteomics. We successfully quantified 76 peptides (from 62 N-glycoproteins). Nineteen of these peptides from lung cancer serum were up-/down-regulated at least 2.5-fold compared to controls. As a result, the P-mHFER-based online ¹⁸O-labeling platform presented here can be a simple and reproducible way to allow quantitative proteomic analysis of diverse proteome samples.

Lso2 is a conserved ribosome-bound protein required for translational recovery in yeast

Ribosome-binding proteins function broadly in protein synthesis, gene regulation, and cellular homeostasis, but the complete complement of functional ribosome-bound proteins remains unknown. Using quantitative mass spectrometry, we identified late-annotated short open reading frame 2 (Lso2) as a ribosome-associated protein that is broadly conserved in eukaryotes. Genome-wide crosslinking and immunoprecipitation of Lso2 and its human ortholog coiled-coil domain containing 124 (CCDC124) recovered 25S ribosomal RNA in a region near the A site that overlaps the GTPase activation center. Consistent with this location, Lso2 also crosslinked to most tRNAs. Ribosome profiling of yeast lacking LSO2 (lso2Δ) revealed global translation defects during recovery from stationary phase with translation of most genes reduced more than 4-fold. Ribosomes accumulated at start codons, were depleted from stop codons, and showed codon-specific changes in occupancy in lso2Δ. These defects, and the conservation of the specific ribosome-binding activity of Lso2/CCDC124, indicate broadly important functions in translation and physiology.

Translation, or the production of protein from messenger RNA (mRNA), is catalyzed by a universally conserved macromolecular machine known as the ribosome. Ribosome-binding factors are also required for all substeps of translation, from initial recruitment of mRNA to peptide chain elongation to release of the mature polypeptide. However, many ribosome interactors have been identified whose effects on translation and physiology are unknown. Here, we show that the uncharacterized yeast protein late-annotated short open reading frame 2 (Lso2) crosslinks to a region of the ribosome that underlies accurate progression through all substeps of translation, the GTPase activation center. This specific binding activity is conserved in the human ortholog of Lso2, coiled-coil domain containing 124 (CCDC124). Null mutants of lso2 also show severe translation defects during recovery from extended starvation, including failure to initiate on most mRNAs and a general block to peptide chain elongation. We propose that these defects could arise from a function for Lso2 in modulating the activity or integrity of the ribosome GTPase activation center during challenging growth regimes.

Systematic analysis of protein turnover in primary cells

A better understanding of proteostasis in health and disease requires robust methods to determine protein half-lives. Here we improve the precision and accuracy of peptide ion intensity-based quantification, enabling more accurate protein turnover determination in non-dividing cells by dynamic SILAC-based proteomics. This approach allows exact determination of protein half-lives ranging from 10 to >1000 h. We identified 4000-6000 proteins in several non-dividing cell types, corresponding to 9699 unique protein identifications over the entire data set. We observed similar protein half-lives in B-cells, natural killer cells and monocytes, whereas hepatocytes and mouse embryonic neurons show substantial differences. Our data set extends and statistically validates the previous observation that subunits of protein complexes tend to have coherent turnover. Moreover, analysis of different proteasome and nuclear pore complex assemblies suggests that their turnover rate is architecture dependent. These results illustrate that our approach allows investigating protein turnover and its implications in various cell types.

Nanoparticle-Assisted Laser Desorption/Ionization Mass Spectrometry (Nano-PALDI MS) with Py-Tag for the Analysis of Small Molecules

We compared two ionization methods, matrix assisted laser desorption/ionization (MALDI) and nanoparticle assisted laser desorption/ionization (Nano-PALDI) mass spectrometry (MS), for the analysis of amino acids derivatized with Py-Tag™ that consists pyrylium-based compound. Py-Tag is a useful stable derivatization reagent due to wide mass differences (using ¹³C as the sole stable labelling isotope). For Py-Tag labelled lysine, sensitive signals that showed less noise with a ten times higher sensitivity, showed a wider mass difference by Nano-PALDI MS compared to MALDI MS.

Mass Defect-Based N,N-Dimethyl Leucine Labels for Quantitative Proteomics and Amine Metabolomics of Pancreatic Cancer Cells

Mass spectrometry-based stable isotope labeling has become a key technology for protein and small-molecule analyses. We developed a multiplexed quantification method for simultaneous proteomics and amine metabolomics analyses via nano reversed-phase liquid chromatography-tandem mass spectrometry (nanoRPLC-MS/MS), called mass defect-based N,N-dimethyl leucine (mdDiLeu) labeling. The duplex mdDiLeu reagents were custom-synthesized with a mass difference of 20.5 mDa, arising from the subtle variation in nuclear binding energy between the two DiLeu isotopologues. Optimal MS resolving powers were determined to be 240K for labeled peptides and 120K for labeled metabolites on the Orbitrap Fusion Lumos instrument. The mdDiLeu labeling does not suffer from precursor interference and dynamic range compression, providing excellent accuracy for MS¹-centric quantification. Quantitative information is only revealed at high MS resolution without increasing spectrum complexity and overlapping isotope distribution. Chromatographic performance of polar metabolites was dramatically improved by mdDiLeu labeling with modified hydrophobicity, enhanced ionization efficiency, and picomole levels of detection limits. Paralleled proteomics and amine metabolomics analyses using mdDiLeu were systematically evaluated and then applied to pancreatic cancer cells.

Quantification of peptides using N-terminal isotope coding and C-terminal derivatization for sensitive analysis by micro liquid chromatography-tandem mass spectrometry

Stable isotope-coding coupled with mass spectrometry is a popular method for quantitative proteomics and peptide quantification. However, the efficiency of the derivatization reaction at a particular functional group, especially in complex structures, can affect accuracy. Here, we present a dual functional-group derivatization of bioactive peptides followed by micro liquid chromatography-tandem mass spectrometry (LC-MS/MS). By separating the sensitivity-enhancement and isotope-coding derivatization reactions, suitable chemistries can be chosen. The peptide amino groups were reductively alkylated with acetaldehyde or acetaldehyde-d₄ to afford N-alkylated products with different masses. This process is simple, quick and high-yield, and accurate comparative analysis can be achieved for the mass-differentiated peptides. Then, the carboxyl groups were derivatized with 1-(2-pyrimidinyl)piperazine to increase MS/MS sensitivity. Angiotensins I-IV, bradykinin and neurotensin were analyzed after online solid phase extraction by micro LC-MS/MS. In all instances, a greater than 17-fold increase in sensitivity was achieved, compared with the analyses of the underivatized peptides. Furthermore, the values obtained from the present method were in agreement with the result from isotope dilution quantification using isotopically labeled angiotensin I [Asp-Arg-(Val-d₈ )-Tyr-Ile-His-Pro-(Phe-d₈ )-His-Leu]. Copyright © 2016 John Wiley & Sons, Ltd.

Synthesis of d-labeled and unlabeled ethyl succinic anhydrides and application to quantitative analysis of peptides by isotope differential mass spectrometry

Ethyl succinic anhydride and its d₅-labeled version have been synthesized and applied to quantitative analysis of peptides in combination with MALDI or ESI mass spectrometry. These modifiers react with amino groups in the N-termini and lysine side chains in proteins, and therefore the combination of these modifiers was shown to be a useful tool for quantification of peptides and hence for proteomics research.

Quantitative Phosphoproteomics Analysis of ERBB3/ERBB4 Signaling

The four members of the epidermal growth factor receptor (EGFR/ERBB) family form homo- and heterodimers which mediate ligand-specific regulation of many key cellular processes in normal and cancer tissues. While signaling through the EGFR has been extensively studied on the molecular level, signal transduction through ERBB3/ERBB4 heterodimers is less well understood. Here, we generated isogenic mouse Ba/F3 cells that express full-length and functional membrane-integrated ERBB3 and ERBB4 or ERBB4 alone, to serve as a defined cellular model for biological and phosphoproteomics analysis of ERBB3/ERBB4 signaling. ERBB3 co-expression significantly enhanced Ba/F3 cell proliferation upon neuregulin-1 (NRG1) treatment. For comprehensive signaling studies we performed quantitative mass spectrometry (MS) experiments to compare the basal ERBB3/ERBB4 cell phosphoproteome to NRG1 treatment of ERBB3/ERBB4 and ERBB4 cells. We employed a workflow comprising differential isotope labeling with mTRAQ reagents followed by chromatographic peptide separation and final phosphopeptide enrichment prior to MS analysis. Overall, we identified 9686 phosphorylation sites which could be confidently localized to specific residues. Statistical analysis of three replicate experiments revealed 492 phosphorylation sites which were significantly changed in NRG1-treated ERBB3/ERBB4 cells. Bioinformatics data analysis recapitulated regulation of mitogen-activated protein kinase and Akt pathways, but also indicated signaling links to cytoskeletal functions and nuclear biology. Comparative assessment of NRG1-stimulated ERBB4 Ba/F3 cells revealed that ERBB3 did not trigger defined signaling pathways but more broadly enhanced phosphoproteome regulation in cells expressing both receptors. In conclusion, our data provide the first global picture of ERBB3/ERBB4 signaling and provide numerous potential starting points for further mechanistic studies.

EBprot: Statistical analysis of labeling-based quantitative proteomics data

Labeling-based proteomics is a powerful method for detection of differentially expressed proteins (DEPs). The current data analysis platform typically relies on protein-level ratios, which is obtained by summarizing peptide-level ratios for each protein. In shotgun proteomics, however, some proteins are quantified with more peptides than others, and this reproducibility information is not incorporated into the differential expression (DE) analysis. Here, we propose a novel probabilistic framework EBprot that directly models the peptide-protein hierarchy and rewards the proteins with reproducible evidence of DE over multiple peptides. To evaluate its performance with known DE states, we conducted a simulation study to show that the peptide-level analysis of EBprot provides better receiver-operating characteristic and more accurate estimation of the false discovery rates than the methods based on protein-level ratios. We also demonstrate superior classification performance of peptide-level EBprot analysis in a spike-in dataset. To illustrate the wide applicability of EBprot in different experimental designs, we applied EBprot to a dataset for lung cancer subtype analysis with biological replicates and another dataset for time course phosphoproteome analysis of EGF-stimulated HeLa cells with multiplexed labeling. Through these examples, we show that the peptide-level analysis of EBprot is a robust alternative to the existing statistical methods for the DE analysis of labeling-based quantitative datasets. The software suite is freely available on the Sourceforge website http://ebprot.sourceforge.net/. All MS data have been deposited in the ProteomeXchange with identifier PXD001426 (http://proteomecentral.proteomexchange.org/dataset/PXD001426/).

MTRAQ-based quantitative analysis combined with peptide fractionation based on cysteinyl peptide enrichment

In the present study, the fractionation scheme for cysteinyl peptide enrichment (CPE) was combined with the mass differential tags for relative and absolute quantification (mTRAQ) method to reduce sample complexity and increase proteome coverage. Cysteine residues of the proteins were first alkylated using iodoacetyl PEG2-biotin instead of other conventional alkylating agents such as iodoacetamide. After trypsin digestion, amine groups were labeled with mTRAQ, and these labeled peptides were fractionated according to the presence or absence of cysteine residues using avidin-biotin affinity chromatography. With these approaches, we were able to divide the peptides into the two fractions with more than 90% fractionation efficiency for standard protein and MCF7 cell lysate. When the fractionation strategy was applied to colorectal cancer tissue samples, we were able to obtain quantitative information that was consistent with the previous study based on mTRAQ quantification, implying that the cysteine-based fractionation method does not affect mTRAQ quantification. We expect that the mTRAQ-based quantitative analysis combined with peptide fractionation through the CPE strategy would allow for deep-down analysis of proteome samples and ultimately for increasing proteome coverage with simultaneous quantification for biomarker discovery.

Quantification of proteins using (13)C7-labeled and unlabeled iodoacetanilide by nano liquid chromatography/nanoelectrospray ionization and by selected reaction monitoring mass spectrometry

The combination of cysteine-specific modifiers, iodoacetanilide (IAA) and (13)C7-labeled iodoacetanilide ((13)C7-IAA), has been applied to absolute quantification of proteins. The selected reaction monitoring (SRM) with the use of nano liquid chromatography/nanoelectrospray ionization ion trap mass spectrometry (nano LC/nano-ESI-IT-MS) analysis was applied to precise quantification of three commercial proteins. Good correlation was observed between the theoretical ratios and observed ratios for all these proteins both in a simple buffer solution and in a complex protein environment. Due to efficient tagging, this method does not require separate synthesis of isotope-labeled peptides for the SRM studies. Therefore, this method is expected to be a useful tool for proteomics research.

Comparative proteomic analysis of outer membrane vesicles from Shigella flexneri under different culture conditions

The production of outer membrane vesicles (OMVs) is a common and regulated process of gram-negative bacteria. Nonetheless, the processes of Shigella flexneri OMV production still remain unclear. S. flexneri is the causative agent of endemic shigellosis in developing countries. The Congo red binding of strains is associated with increased infectivity of S. flexneri. Therefore, understanding the modulation pattern of OMV protein expression induced by Congo red will help to elucidate the bacterial pathogenesis. In the present study, we investigated the proteomic composition of OMVs and the change in OMV protein expression induced by Congo red using mTRAQ-based quantitative comparative proteomics. mTRAQ labelling increased the confidence in protein identification, and 148 total proteins were identified in S. flexneri-derived OMVs. These include a variety of important virulence factors, including Ipa proteins, TolC family, murein hydrolases, and members of the serine protease autotransporters of Enterobacteriaceae (SPATEs) family. Among the identified proteins, 28 and five proteins are significantly up- and down-regulated in the Congo red-induced OMV, respectively. Additionally, by comprehensive comparison with previous studies focused on DH5a-derived OMV, we identified some key node proteins in the protein-protein interaction network that may be involved in OMV biogenesis and are common to all gram-negative bacteria.

Discovery of melanotransferrin as a serological marker of colorectal cancer by secretome analysis and quantitative proteomics

To discover serological colorectal cancer (CRC) markers, we analyzed cell line secretome to gather proteins of higher potential to be secreted from tissues into circulation. A total of 898 human proteins were identified, of which 62.2% were predicted to be released or shed from cells. The identified proteins were compared with tissue proteomes to find candidate proteins whose expressions were elevated in tumor tissues compared with normal tissues as revealed by (i) quantitative proteomic analysis based on cICAT and mTRAQ or (ii) data mining of immunohistochemical images piled in Human Protein Atlas database. By applying various stringent criteria, 11 candidate proteins were selected. Among these, we validated an significant increase (p = 0.0018) of melanotransferrin (TRFM) at the plasma level of CRC patients through Western blotting, using 130 plasma samples containing 30 healthy controls, 80 CRC patients, and 20 patients of other diseases. Finally, we measured the expression level of TRFM in 325 plasma samples containing 77 healthy controls and 228 CRC patients (34.6 ± 4.2 ng/mL and 67.0 ± 6.4 ng/mL, p < 0.0001) through ELISA and demonstrated the area under the receiver operating characteristic curve of 0.723 (p < 0.0001) with a 92.5% specificity, 48.2% sensitivity, and 95.7% positive predictive value. Furthermore, unlike CEA and PAI-1, up-regulation of TRFM in pathological stages I & II groups compared with stages III & IV groups lead us to expect the use TRFM for early-stage diagnosis of CRC. In this study, we suggest TRFM as a potential serological marker for CRC and expect our discovery strategy to help identify highly cancer-specific and body-fluid-accessible biomarkers.

Isotope-coded carbamidomethylation for quantification of N-glycoproteins with online microbore hollow fiber enzyme reactor-nanoflow liquid chromatography-tandem mass spectrometry

This paper introduces a simple, inexpensive, and robust quantitative proteomic method for quantifying N-linked glycoproteins based on isotope-coded carbamidomethylation (iCCM) incorporated into an online microbore hollow fiber enzyme reactor and nanoflow liquid chromatography-tandem mass spectrometry (mHFER-nLC-MS/MS). The iCCM quantitation uses carbamidomethylation (CM; a routine protection of thiol groups before proteolysis) of the Cys residue of proteins with iodoacetamide (IAA) or its isotope (IAA-(13)C2,D2: 4 Da difference). CM-/iCCM-labeled proteome samples are mixed for proteolysis; then, online enrichment of N-glycopeptides using lectin affinity is carried out in an mHFER before nLC-MS/MS for quantification using multiple reaction monitoring (MRM). Initial evaluation of the iCCM method varying the mixing ratio of CM-/iCCM-labeled bovine serum albumin (BSA) standards yielded successful quantification of 18 peptides with less than 2% variation in the calculated ratio of light/heavy-labeled peptides. The iCCM quantitation with mHFER-nLC-MS/MS was evaluated with three standard glycoproteins (α-1-acid glycoproteins, fetuin and transferrin) and then applied to serum glycoproteins from liver cancer patients and controls, resulting in successful quantification of 73 N-glycopeptides (from 49 N-glycoproteins), among which 19 N-glycopeptides from 14 N-glycoproteins showed more than a 2.5-fold aberrant change in liver cancer patients' sera compared with the pooled control. Although iCCM quantitation with mHFER-nLC-MS/MS applies only to glycopeptides with Cys residue, the method can offer several advantages over other labeling methods when applied to targeted glycoproteins: The iCCM method does not require an additional labeling reaction under special conditions nor complicated procedures to purify labeled products using additional columns. Isotope labeling at the protein level can minimize potential uncertainty originating from unequal efficiencies in protein digestion in separate vials and retrieval of each labeled peptide when labeling takes place at the peptide level. In addition, the labeling reagents for the iCCM method are readily obtained at a reasonable cost, which can make protein quantification easily accessible.

Targeted quantitative proteomics for the analysis of 14 UGT1As and -2Bs in human liver using NanoUPLC-MS/MS with selected reaction monitoring

Targeted quantitative proteomics using heavy isotope dilution techniques is increasingly being utilized to quantify proteins, including UGT enzymes, in biological matrices. Here we present a multiplexed method using nanoLC-MS/MS and multiple reaction monitoring (MRM) to quantify 14 UGT1As and UGT2Bs in liver matrices. Where feasible, we employ two or more proteotypic peptides per protein, with only four proteins quantified with only one proteotypic peptide. We apply the method to analysis of a library of 60 human liver microsome (HLM) and matching S9 samples. Ten of the UGT isoforms could be detected in liver, and the expression of each was consistent with mRNA expression reported in the literature. UGT2B17 was unusual in that ∼30% of liver microsomes had no or little (<0.5 pmol/mg protein) content, consistent with a known common polymorphism. Liver S9 UGT concentrations were approximately 10-15% those of microsomes. The method was robust, precise, and reproducible and provides novel UGT expression data in human liver that will benefit rational approaches to evaluate metabolism in drug development.

Comparison of SILAC and mTRAQ quantification for phosphoproteomics on a quadrupole orbitrap mass spectrometer

Advances in mass spectrometric methodology and instrumentation have promoted a continuous increase in analytical performance in the field of phosphoproteomics. Here, we employed the recently introduced quadrupole Orbitrap (Q Exactive) mass spectrometer for quantitative signaling analysis to a depth of more than 15 000 phosphorylation sites. In parallel to the commonly used SILAC approach, we evaluated the nonisobaric chemical labeling reagent mTRAQ as an alternative quantification technique. Both enabled high phosphoproteome coverage in H3122 lung cancer cells. Replicate quantifications by mTRAQ identified almost as many significant phosphorylation changes upon treatment with ALK kinase inhibitor crizotinib as found by SILAC quantification. Overall, mTRAQ was slightly less precise than SILAC as evident from a somewhat higher variance of replicate phosphosite ratios. Direct comparison of SILAC- and mTRAQ-quantified phosphosites revealed that the majority of changes were detected by either quantification techniques, but also highlighted the aspect of false negative identifications in quantitative proteomics applications. Further inspection of crizotinib-regulated phosphorylation changes unveiled interference with multiple antioncogenic mechanisms downstream of ALK fusion kinase in H3122 cells. In conclusion, our results demonstrate a strong analytical performance of the Q Exactive in global phosphoproteomics, and establish mTRAQ quantification as a useful alternative to metabolic isotope labeling.

Multiple reaction monitoring of multiple low-abundance transcription factors in whole lung cancer cell lysates

Lung cancer-related transcription factors (TFs) were identified by integrating previously reported genomic, transcriptomic, and proteomic data and were quantified by multiple reaction monitoring (MRM) in various cell lines. All experiments were performed without affinity depletion or subfractionation of cell lysates. Since the target proteins were expected to be present in low abundance, we experimentally optimized MRM transition parameters with chemically synthesized peptides. Quantitation was based on stable isotope-labeled standard peptides (SIS peptides). Out of 288 MRM measurements (36 peptides representing 28 TFs × 8 cell lines), 241 were successfully obtained within a quantitation limit of 15 amol, 221 measurements (91.7%) showed coefficients of variation (CVs) of ≤ 20%, and 149 (61.8%) showed CVs of ≤ 10%, quantifying as low as 19.4 amol/μg protein for STAT2 with a CV of 6.3% in an A549 cell. Comparisons between MRM measurements and levels of the corresponding mRNAs revealed linear, nonlinear, or no relationship between protein and mRNA levels, indicating the need for an MRM assay. An integrative analysis of MRM and gene expression profiles from doxorubicin-resistant H69AR and sensitive H69 cells further showed that 14 differentially expressed TFs, such as STAT1 and SMAD4, regulated genes associated with drug resistance and cell differentiation-related processes. Thus, the analytical performance of MRM for the quantitation of low abundance TFs suggests its usefulness for biological application.

Cancer proteomics

Cancer presents high mortality and morbidity globally, largely due to its complex and heterogenous nature, and lack of biomarkers for early diagnosis. A proteomics study of cancer aims to identify and characterize functional proteins that drive the transformation of malignancy, and to discover biomarkers to detect early-stage cancer, predict prognosis, determine therapy efficacy, identify novel drug targets, and ultimately develop personalized medicine. The various sources of human samples such as cell lines, tissues, and plasma/serum are probed by a plethora of proteomics tools to discover novel biomarkers and elucidate mechanisms of tumorigenesis. Innovative proteomics technologies and strategies have been designed for protein identification, quantitation, fractionation, and enrichment to delve deeper into the oncoproteome. In addition, there is the need for high-throughput methods for biomarker validation, and integration of the various platforms of oncoproteome data to fully comprehend cancer biology.

Minireview: progress and challenges in proteomics data management, sharing, and integration

The proteome represents the identity, expression levels, interacting partners, and posttranslational modifications of proteins expressed within any given cell. Proteomic studies aim to census the quantitative and qualitative factors regulating the biological relationships of proteins acting in concert as functional cellular networks. In the field of endocrinology, proteomics has been of considerable value in determining the function and mechanism of action of endocrine signaling molecules in the cell membrane, cytoplasm, and nucleus and for the discovery of proteins as candidates for clinical biomarkers. The volume of data that can be generated by proteomics methodologies, up to gigabytes of data within a few hours, brings with it its own logistical hurdles and presents significant challenges to realizing the full potential of these datasets. In this minireview, we describe selected current proteomics methodologies and their application in basic and translational endocrinology before focusing on mass spectrometry as a model for current progress and challenges in data analysis, management, sharing, and integration.

Comparative profiling of plasma proteome from breast cancer patients reveals thrombospondin-1 and BRWD3 as serological biomarkers

Breast cancer is the most common cancer in women worldwide. It is necessary to identify biomarkers for early detection, to make accurate prognoses, and to monitor for any recurrence of the cancer. In order to identify potential breast cancer biomarkers, we analyzed the plasma samples of women diagnosed with breast cancer and age-matched normal healthy women by mTRAQ-based stable isotope-labeling mass spectrometry. We identified and quantified 204 proteins including thrombospondin-1 (THBS1) and bromodomain and WD repeat-containing protein 3 (BRWD3) which were increased by more than 5-fold in breast cancer plasma. The plasma levels of the two proteins were evaluated by Western blot assay to confirm for their diagnostic value as serum markers. A 1.8-fold increase in BRWD3 was observed while comparing the plasma levels of breast cancer patients (n = 54) with age-matched normal healthy controls (n = 30), and the area under the receiver operating characteristic curve (AUC) was 0.917. THBS1 was detected in pooled breast cancer plasma at the ratio similar to mTRAQ ratio (> 5-fold). The AUC value for THBS1 was 0.875. The increase of THBS1 was more prominent in estrogen receptor negative and progesterone receptor negative patients than receptor-positive patients. Our results are evidence of the diagnostic value of THBS1 in detecting breast cancer. Based on our findings, we suggest a proteomic method for protein identification and quantification lead to effective biomarker discovery.

Quantitative mass spectrometry-based proteomics: an overview

In recent years, mass spectrometry has moved more than ever before into the front line of protein-centered research. After being established at the qualitative level, the more challenging question of quantification of proteins and peptides using mass spectrometry has become a focus for further development. In this chapter, we discuss and review the strategies and problems of the methods currently in use for the quantitative analysis of peptides, proteins, and finally proteomes by mass spectrometry. The common themes, the differences, and the potential pitfalls of the main approaches are presented in order to provide a survey of the emerging field of quantitative, mass spectrometry-based proteomics.

Expression profiling of more than 3500 proteins of MSS-type colorectal cancer by stable isotope labeling and mass spectrometry

An efficient means of identifying protein biomarkers is essential to proper cancer management. A well-characterized proteome resource holds special promise for the discovery of novel biomarkers. However, quantification of the differences between physiological conditions together with deep down profiling has become increasingly challenging in proteomics. Here, we perform expression profiling of the colorectal cancer (CRC) proteome by stable isotope labeling and mass spectrometry. Quantitative analysis included performing mTRAQ and cICAT labeling in a pooled sample of three microsatellite stable (MSS) type CRC tissues and a pooled sample of their matched normal tissues. We identified and quantified a total of 3688 proteins. Among them, 1487 proteins were expressed differentially between normal and cancer tissues by higher than 2-fold; 1009 proteins showed increased expression in cancer tissue, whereas 478 proteins showed decreased expression. Bioinformatic analysis revealed that our data were largely consistent with known CRC relevant signaling pathways, such as the Wnt/β-catenin, caveolar-mediated endocytosis, and RAN signaling pathways. Mitochondrial dysfunction, known as the Waburg hypothesis, was also confirmed. Therefore, our data showing alterations in the proteomic profile of CRC constitutes a useful resource that may provide insights into tumor progression with later goal of identifying biologically and clinically relevant marker proteins. This article is part of a Special Issue entitled: Proteomics: The clinical link.

Assessing variability in gel-based proteomic analysis of Nitrosomonas europaea

Proteomics offers a unique look at the way protein expression changes in response to stimuli, and "gel-based" methods that utilize two-dimensional gel electrophoresis (2-DE) are key technologies in such studies. However, the many steps involved can be technically complex, and the resulting data are subject to variability from both technical and biological sources. Designing 2-DE proteomic studies can be challenging, as a set of standard methods or experimental designs has not been established. This being the case, it is especially important to identify and control sources of variability. Statistically significant results can be obtained if the experimental design includes a sufficient number of replicate 2-DE gels, and if the replicate gels are similar enough to be analyzed in the same experiment. While three or four replicates are often sufficient for compensation of variability, the pilot study illustrated in this chapter showed that statistically significant expression differences could be detected for 90% of the spots matched if six replicate experiments were done.

High-throughput peptide quantification using mTRAQ reagent triplex

BACKGROUND

Protein quantification is an essential step in many proteomics experiments. A number of labeling approaches have been proposed and adopted in mass spectrometry (MS) based relative quantification. The mTRAQ, one of the stable isotope labeling methods, is amine-specific and available in triplex format, so that the sample throughput could be doubled when compared with duplex reagents.

METHODS AND RESULTS

Here we propose a novel data analysis algorithm for peptide quantification in triplex mTRAQ experiments. It improved the accuracy of quantification in two features. First, it identified and separated triplex isotopic clusters of a peptide in each full MS scan. We designed a schematic model of triplex overlapping isotopic clusters, and separated triplex isotopic clusters by solving cubic equations, which are deduced from the schematic model. Second, it automatically determined the elution areas of peptides. Some peptides have similar atomic masses and elution times, so their elution areas can have overlaps. Our algorithm successfully identified the overlaps and found accurate elution areas. We validated our algorithm using standard protein mixture experiments.

CONCLUSIONS

We showed that our algorithm was able to accurately quantify peptides in triplex mTRAQ experiments. Its software implementation is compatible with Trans-Proteomic Pipeline (TPP), and thus enables high-throughput analysis of proteomics data.

Hexapeptide libraries for enhanced protein PTM identification and relative abundance profiling in whole human saliva

Dynamic range compression (DRC) by hexapeptide libraries increases MS/MS-based identification of lower-abundance proteins in complex mixtures. However, two unanswered questions impede fully realizing DRC's potential in shotgun proteomics. First, does DRC enhance identification of post-translationally modified proteins? Second, can DRC be incorporated into a workflow enabling relative protein abundance profiling? We sought to answer both questions analyzing human whole saliva. Addressing question one, we coupled DRC with covalent glycopeptide enrichment and MS/MS. With DRC we identified ∼2 times more N-linked glycoproteins and their glycosylation sites than without DRC, dramatically increasing the known salivary glycoprotein catalog. Addressing question two, we compared differentially stable isotope-labeled saliva samples pooled from healthy and metastatic breast cancer women using a multidimensional peptide fractionation-based workflow, analyzing in parallel one sample portion with DRC and one portion without. Our workflow categorizes proteins with higher absolute abundance, whose relative abundance ratios are altered by DRC, from proteins of lower absolute abundance detected only after DRC. Within each of these salivary protein categories, we identified novel abundance changes putatively associated with breast cancer, demonstrating feasibility and benefits of DRC for relative abundance profiling. Collectively, our results bring us closer to realizing the full potential of DRC for proteomic studies.