Evaluation of strong cation exchange versus isoelectric focusing of peptides for multidimensional liquid chromatography-tandem mass spectrometry

Shotgun Proteomics of Human Dentin with Different Prefractionation Methods

Human dentin is not only a composite material of a collagenous matrix and mineral to provide strength and elasticity to teeth, but also a precious reservoir full of bioactive proteins. They are released after demineralization caused by bacterial acids in carious lesions, by decalcifying irrigants or dental materials and they modulate tissue responses in the underlying dental pulp. This work describes a first-time analysis of the proteome of human dentin using a shotgun proteomic approach that combines three different protein fractionation methods. Dentin matrix proteins were extracted by EDTA and separated by sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE), OFFGEL isoelectric focusing (IEF) or strong cation exchange chromatography (SCX). Liquid chromatography tandem mass spectrometry (LC-MS/MS) identified 813 human proteins with high confidence, however, isoelectric focusing turned out to be the most beneficial prefractionation method. All Proteins were categorized based on the PANTHER system and representation analysis revealed 31 classes and subclasses to be overrepresented. The acquired knowledge provides a comprehensive insight into the number of proteins in human dentin as well as their physiological and pathological functions. Thus, the data presented paves the way to the analysis of specific functions of dentin matrix proteins in vivo and their potential in tissue engineering approaches to regenerate dental pulp.

Preparation and Immunoaffinity Depletion of Fresh Frozen Tissue Homogenates for Mass Spectrometry-Based Proteomics in the Context of Drug Target/Biomarker Discovery

The discovery of novel drug targets and biomarkers via mass spectrometry (MS)-based proteomic analysis of clinical specimens has proven to be challenging. The wide dynamic range of protein concentration in clinical specimens and the high background/noise originating from highly abundant proteins in tissue homogenates and serum/plasma encompass two major analytical obstacles. Immunoaffinity depletion of highly abundant blood-derived proteins from serum/plasma is a well-established approach adopted by numerous researchers; however, the utilization of this technique for immunodepletion of tissue homogenates obtained from fresh frozen clinical specimens is lacking. We first developed immunoaffinity depletion of highly abundant blood-derived proteins from tissue homogenates, using renal cell carcinoma as a model disease, and followed this study by applying it to different tissue types. Tissue homogenate immunoaffinity depletion of highly abundant proteins may be equally important as is the recognized need for depletion of serum/plasma, enabling more sensitive MS-based discovery of novel drug targets, and/or clinical biomarkers from complex clinical samples. Provided is a detailed protocol designed to guide the researcher through the preparation and immunoaffinity depletion of fresh frozen tissue homogenates for two-dimensional liquid chromatography, tandem mass spectrometry (2D-LC-MS/MS)-based molecular profiling of tissue specimens in the context of drug target and/or biomarker discovery.

Metaproteomic strategies and applications for gut microbial research

The human intestine hosts various complex microbial communities that are closely associated with multiple health and disease processes. Determining the composition and function of these microbial communities is critical to unveil disease mechanisms and promote human health. Recently, meta-omic strategies have been developed that use high-throughput techniques to provide a wealth of information, thus accelerating the study of gut microbes. Metaproteomics is a newly emerged analytical approach that aims to identify proteins on a large scale in complex environmental microbial communities (e.g., the gut microbiota). This review introduces the recent analytical strategies and applications of metaproteomics, with a focus on advances in gut microbiota research, including a discussion of the limitations and challenges of these approaches.

Reproducibility of Differential Proteomic Technologies in CPTAC Fractionated Xenografts

The NCI Clinical Proteomic Tumor Analysis Consortium (CPTAC) employed a pair of reference xenograft proteomes for initial platform validation and ongoing quality control of its data collection for The Cancer Genome Atlas (TCGA) tumors. These two xenografts, representing basal and luminal-B human breast cancer, were fractionated and analyzed on six mass spectrometers in a total of 46 replicates divided between iTRAQ and label-free technologies, spanning a total of 1095 LC-MS/MS experiments. These data represent a unique opportunity to evaluate the stability of proteomic differentiation by mass spectrometry over many months of time for individual instruments or across instruments running dissimilar workflows. We evaluated iTRAQ reporter ions, label-free spectral counts, and label-free extracted ion chromatograms as strategies for data interpretation (source code is available from http://homepages.uc.edu/~wang2x7/Research.htm ). From these assessments, we found that differential genes from a single replicate were confirmed by other replicates on the same instrument from 61 to 93% of the time. When comparing across different instruments and quantitative technologies, using multiple replicates, differential genes were reproduced by other data sets from 67 to 99% of the time. Projecting gene differences to biological pathways and networks increased the degree of similarity. These overlaps send an encouraging message about the maturity of technologies for proteomic differentiation.

Discovery of potential colorectal cancer serum biomarkers through quantitative proteomics on the colonic tissue interstitial fluids from the AOM-DSS mouse model

Quantitative proteomic analysis was performed using iTRAQ to discover colorectal cancer (CRC)-related proteins in tissue interstitial fluids (TIFs). A typical inflammation-related CRC mouse model was generated using azoxymethane-dextran sodium sulfate (AOM-DSS), and TIFs were collected from these mice in four stages during CRC development. Using stringent criteria, a total of 144 proteins displayed changes in their abundances during tumor growth, including 45 that consecutively increased, 17 that consecutively decreased and 82 that changed irregularly. Of these 144 proteins, 24 of the consecutively changed proteins were measured using MRM in individual TIF samples, and 18 were verified. Twelve proteins verified to be consecutively increased in TIFs were examined using MRM to evaluate changes in their abundance in individual mouse serum samples. The abundances of leucine-rich alpha-2-glycoprotein 1 (LRG1), tubulin beta-5 chain (TUBB5) and immunoglobulin J chain (IGJ) were significantly higher in CRC mice than in control mice. Using clinical samples and MRM, we further verified that LRG1 and TUBB5 are potential CRC serum biomarkers. These data demonstrate that coupling dynamic TIF proteomics with targeted serum proteomics in an animal model is a promising avenue for pursuing the discovery of tumor serum biomarkers.

BIOLOGICAL SIGNIFICANCE

Colorectal cancer (CRC) is one of the most dangerous diseases worldwide. However, few of CRC biomarkers possess satisfied specificity and sensitivity in clinical practices. Exploration of more CRC biomarkers, especially in serum, is an urgent and also a time-consuming campaign in the CRC study. Our study demonstrates that quantitatively evaluating the phase-dependent proteins in colonic tissue interstitial fluids from AOM-DSS mice is a feasible and effective way for exploration of the CRC-related proteins and the potential serum biomarkers. We identified two proteins, LRG1 and TUBB5, which may be practicable in human clinical samples as CRC serum biomarkers. To sum up, this study provides a novel angle to explore the critical factors in tumorigenesis and a new pipeline for potential serum biomarker discovery and verification.

Differential proteomics of monosodium urate crystals-induced inflammatory response in dissected murine air pouch membranes by iTRAQ technology

The precipitation of monosodium urate crystals within joints triggers an acute inflammatory reaction that is the root cause of gout. The inflammation induced by the injection of MSU crystals into the murine air pouch for 1, 3, and 5 h was examined by iTRAQ-based proteomic profiling. The iTRAQ-labeled peptides were fractionated by SCX, basic-RP or solution-IEF, followed by LC-MS/MS analysis. A total of 951 proteins were quantified from the total combined fractions. Among them, 317 proteins exhibited a differential expression, compared to that of the controls at one time point or more. The majority of the differentially expressed proteins were found in the sample after a 5-h MSU treatment. Western blot revealed that the expression levels of cathelin-related antimicrobial peptide and S100A9 were positively correlated with the time-course treated with MSU. Further analysis of GeneGO pathway demonstrated that these differentially expressed proteins are primarily related to the immune-related complement system and the tricarboxylic acid cycle. Moreover, seven genes from the TCA cycle were found to be significantly downregulated at the transcriptional level and its correlation with gout and possible therapeutic applications are worth further investigation. Last, we found that pyruvate carboxylation could be potential targets for antigout treatment.

Proteomics characterization of exosome cargo

Characterization of exosomal cargo is of significant interest because this cargo can provide clues to exosome biogenesis, targeting, and cellular effects and may be a source of biomarkers for disease diagnosis, prognosis and response to treatment. With recent improvements in proteomics technologies, both qualitative and quantitative characterization of exosomal proteins is possible. Here we provide a brief review of exosome proteomics studies and provide detailed protocols for global qualitative, global quantitative, and targeted quantitative analysis of exosomal proteins. In addition, we provide an example application of a standard global quantitative analysis followed by validation via a targeted quantitative analysis of urine exosome samples from human patients. Advantages and limitations of each method are discussed as well as future directions for exosome proteomics analysis.

Proteomic profiling of nipple aspirate fluid (NAF): Exploring the complementarity of different peptide fractionation strategies

NAF is a breast fluid that is closely related to the tumor microenvironment and a valuable sample for studying breast cancer. To perform an in-depth proteomic analysis of this sample, aliquots of a single NAF digest were analyzed by the following peptide-centric fractionation strategies: a) 30-cm reversed-phase (RP) column on-line with an LTQ-Orbitrap XL; b) off-line strong cation-exchange (SCX) column; and c) pI-based OFFGEL fractionation. All fractions from approaches (b) and (c) were further analyzed on a 10-cm RP column hyphenated to the same mass spectrometer. The RP-30cm, SCX/RP-10cm, and OFFGEL/RP-10cm approaches identified 1676, 2930, and 3240 peptides, which corresponded to 193, 390 and 528 proteins, respectively. In our cumulative dataset, 4466 distinct NAF peptides corresponded to a total of 557 proteins, of which only 34% were identified by all three approaches. No exclusive protein identification was associated to the RP-30cm approach, while SCX/RP-10cm and OFFGEL/RP-10cm contributed to 28 and 166 exclusive identifications, respectively. Each approach provided additional information related to energy metabolism (fermentation process/carbohydrate biosynthesis). In conclusion, the pre-fractionation platforms used were complementary for the comprehensive characterization of NAF and our work provides methodological information for future quantitative cancer-related NAF sample studies.

BIOLOGICAL SIGNIFICANCE

High-resolution peptide separation is a sine qua non condition for achieving extensive proteome coverage. Various techniques have been employed to improve peptide fractionation prior to LC-MS/MS, thus allowing a comprehensive characterization of complex biological samples. Although fractionation efficiency is very sample-dependent, this issue is commonly overlooked, and a "cookbook" approach is routinely used during this critical step. The present study provides a systematic comparison of analytical information needed for the successful large-scale differential proteomic analysis of NAF samples from breast cancer patients, a precious and volume-limited biological sample. It reinforces the importance of optimizing sample-specific fractionation protocols for information retrieval from mass spectrometric analysis.

IPG strip-based peptide fractionation for shotgun proteomics

Efficient fractionation of peptides is an essential prerequisite for comprehensive analysis of complex protein mixtures by shotgun mass spectrometry. The separation of peptides by isoelectric focusing is particularly attractive due to its orthogonality to reverse-phase HPLC. Here, we present a protocol for in-gel peptide isoelectric focusing using immobilized pH gradient strips. The method shows high resolving power for up to 1 mg of sample and is highly reproducible.

Up-regulation of fatty acid oxidation in the ligament as a contributing factor of ankylosing spondylitis: A comparative proteomic study

OBJECTIVES

The present study first utilized a standardized shotgun proteomic analysis method to determine differences in protein expression of fibroblasts in the ligament between AS patients and healthy controls.

METHODS

Proteins extracted from primarily cultured FLLs from 35 AS patients and 10 normal subjects were analyzed by automated 2D-Nano-LC-ESI-MS/MS. Differentially expressed proteins were screened by 2-sample t-test and fold change. Bioinformatics analysis of differentially expressed proteins was based on the IPA. Fatty acid β-oxidation-related proteins and INSR pathway-related proteins in the ligament were confirmed by real-time PCR and Western blot.

RESULTS

A total of 556 differential proteins were screened in AS. Of them, 322 proteins were up-regulated and the remaining 234 proteins were down-regulated. GO and pathway analyses showed that six fatty acid β-oxidation-related proteins (HADHB, ECHS1, ACSL4, ACADM, ACSL1 and HADH) were up-regulated in FLL cells, which was consistent with the results obtained from real-time PCR, Western blot and MS, while INSR pathway-related proteins (INSR, IRS1, PI3K and PKC) was low in the ligament of AS as compared with that in healthy controls.

CONCLUSION

The lower body fat level in AS maybe due to up-regulation of fatty acid β-oxidation-related enzymes regulated by INSR/PI3K/PKC pathway.

BIOLOGICAL SIGNIFICANCE

Ankylosing spondylitis (AS), a common spondyloarthropathy, is an inflammatory rheumatic disease with a predilection for the axial skeleton. Clinical hallmarks of AS include sacroiliitis, uveitis, enthesitis and persistent spinal inflammation. The pathogenic mechanism of disease causation and perpetuation remains poorly understood. In this study, we primarily cultured fibroblast cells from ligament biopsies, knowing that fibroblast cells are dominant cells in the diseased ligament. One of the characteristic pathologic changes in AS is inflammation of the attachment points, including the muscle, ligament and bone or joint capsule. Inflammation of the tendon attachment point is usually non-bacterial and can lead to pain and swelling of the tendon ligament. To obtain more information, we used Shotgun proteomic analysis based on multidimensional liquid chromatography tandem mass spectrometry (LC-MS/MS). we firstly mixed the lysates of FLL cells derived from the ligaments of 35 AS patients and 10 normal subjects, identified proteins by automated 2D-Nano-LC-ESI-MS/MS method, GO and pathway analyses showed that six fatty acid β-oxidation-related proteins (HADHB, ECHS1, ACSL4, ACADM, ACSL1 and HADH) were up-regulated in the ligament, which was consistent with the results obtained from real-time PCR, Western blot and MS, while INSR pathway-related proteins (INSR, IRS1, PI3K and PKC) was low in the ligament of AS as compared with that in healthy controls. We also find that AS subjects had significantly lower body mass index (BMI) and BMI Z-scores compared with that in healthy controls. The results remind us that up-regulation of fatty acid β-oxidation-related proteins lower the body fat content, which is a new discovery contributing to the progression of AS. This is the first report on fatty acid oxidation in AS. It was found that the body fat level was low in AS due to high fatty acid oxidation, suggesting that insulin signaling may play an important role in the metabolic switch from predominant to fatty acid metabolism that characterizes the ligament of AS. One mechanism for this transition is increased expression of genes that regulate the rate of fatty acid oxidation. This effect may be mediated by PI3K, a downstream mediator of many receptor tyrosine kinases, including the INSR. This is a newly discovered factor contributing to the progression of AS.

De Novo proteome analysis of genetically modified tumor cells by a metabolic labeling/azide-alkyne cycloaddition approach

Activin receptor type II (ACVR2) is a member of the transforming growth factor type II receptor family and controls cell growth and differentiation, thereby acting as a tumor suppressor. ACVR2 inactivation is known to drive colorectal tumorigenesis. We used an ACVR2-deficient microsatellite unstable colon cancer cell line (HCT116) to set up a novel experimental design for comprehensive analysis of proteomic changes associated with such functional loss of a tumor suppressor. To this end we combined two existing technologies. First, the ACVR2 gene was reconstituted in an ACVR2-deficient colorectal cancer (CRC) cell line by means of recombinase-mediated cassette exchange, resulting in the generation of an inducible expression system that allowed the regulation of ACVR2 gene expression in a doxycycline-dependent manner. Functional expression in the induced cells was explicitly proven. Second, we used the methionine analog azidohomoalanine for metabolic labeling of newly synthesized proteins in our cell line model. Labeled proteins were tagged with biotin via a Click-iT chemistry approach enabling specific extraction of labeled proteins by streptavidin-coated beads. Tryptic on-bead digestion of captured proteins and subsequent ultra-high-performance LC coupled to LTQ Orbitrap XL mass spectrometry identified 513 proteins, with 25 of them differentially expressed between ACVR2-deficient and -proficient cells. Among these, several candidates that had already been linked to colorectal cancer or were known to play a key role in cell growth or apoptosis control were identified, proving the utility of the presented experimental approach. In principle, this strategy can be adapted to analyze any gene of interest and its effect on the cellular de novo proteome.

Co-expression network analysis identifies Spleen Tyrosine Kinase (SYK) as a candidate oncogenic driver in a subset of small-cell lung cancer

Background

Oncogenic mechanisms in small-cell lung cancer remain poorly understood leaving this tumor with the worst prognosis among all lung cancers. Unlike other cancer types, sequencing genomic approaches have been of limited success in small-cell lung cancer, i.e., no mutated oncogenes with potential driver characteristics have emerged, as it is the case for activating mutations of epidermal growth factor receptor in non-small-cell lung cancer. Differential gene expression analysis has also produced SCLC signatures with limited application, since they are generally not robust across datasets. Nonetheless, additional genomic approaches are warranted, due to the increasing availability of suitable small-cell lung cancer datasets. Gene co-expression network approaches are a recent and promising avenue, since they have been successful in identifying gene modules that drive phenotypic traits in several biological systems, including other cancer types.

Results

We derived an SCLC-specific classifier from weighted gene co-expression network analysis (WGCNA) of a lung cancer dataset. The classifier, termed SCLC-specific hub network (SSHN), robustly separates SCLC from other lung cancer types across multiple datasets and multiple platforms, including RNA-seq and shotgun proteomics. The classifier was also conserved in SCLC cell lines. SSHN is enriched for co-expressed signaling network hubs strongly associated with the SCLC phenotype. Twenty of these hubs are actionable kinases with oncogenic potential, among which spleen tyrosine kinase (SYK) exhibits one of the highest overall statistical associations to SCLC. In patient tissue microarrays and cell lines, SCLC can be separated into SYK-positive and -negative. SYK siRNA decreases proliferation rate and increases cell death of SYK-positive SCLC cell lines, suggesting a role for SYK as an oncogenic driver in a subset of SCLC.

Conclusions

SCLC treatment has thus far been limited to chemotherapy and radiation. Our WGCNA analysis identifies SYK both as a candidate biomarker to stratify SCLC patients and as a potential therapeutic target. In summary, WGCNA represents an alternative strategy to large scale sequencing for the identification of potential oncogenic drivers, based on a systems view of signaling networks. This strategy is especially useful in cancer types where no actionable mutations have emerged.

Analysis of the proteolysis of bioactive peptides using a peptidomics approach

Identifying the peptidases that inactivate bioactive peptides (e.g., peptide hormones and neuropeptides) in mammals is an important unmet challenge. This protocol describes a recent approach that uses liquid chromatography-mass spectrometry (LC-MS) peptidomics to identify endogenous cleavage sites of a bioactive peptide; it also addresses the subsequent biochemical purification of a candidate peptidase on the basis of these cleavage sites and the validation of the candidate peptidase's role in the physiological regulation of the bioactive peptide by examining a peptidase-knockout mouse. We highlight the successful application of this protocol in the discovery that insulin-degrading enzyme (IDE) regulates physiological calcitonin gene-related peptide (CGRP) levels, and we detail the key stages and steps in this approach. This protocol requires 7 d of work; however, the total time for this protocol is highly variable because of its dependence on the availability of biological reagents such as purified enzymes and knockout mice. The protocol is valuable because it expedites the characterization of mammalian peptidases, such as IDE, which in certain instances can be used to develop novel therapeutics.

Fast photochemical oxidation of proteins for comparing solvent-accessibility changes accompanying protein folding: data processing and application to barstar

Mass spectrometry-based protein footprinting reveals regional and even amino-acid structural changes and fills the gap for many proteins and protein interactions that cannot be studied by X-ray crystallography or NMR spectroscopy. Hydroxyl radical-mediated labeling has proven to be particularly informative in this pursuit because many solvent-accessible residues can be labeled by OH in a protein or protein complex, thus providing more coverage than does specific amino-acid modifications. Finding all the OH-labeling sites requires LC/MS/MS analysis of a proteolyzed sample, but data processing is daunting without the help of automated software. We describe here a systematic means for achieving a comprehensive residue-resolved analysis of footprinting data in an efficient manner, utilizing software common to proteomics core laboratories. To demonstrate the method and the utility of OH-mediated labeling, we show that FPOP easily distinguishes the buried and exposed residues of barstar in its folded and unfolded states. This article is part of a Special Issue entitled: Mass spectrometry in structural biology.

Evaluation and optimization of mass spectrometric settings during data-dependent acquisition mode: focus on LTQ-Orbitrap mass analyzers

Mass-spectrometry-based proteomics has evolved as the preferred method for the analysis of complex proteomes. Undoubtedly, recent advances in mass spectrometry instrumentation have greatly enhanced proteomic analysis. A popular instrument platform in proteomics research is the LTQ-Orbitrap mass analyzer. In this tutorial, we discuss the significance of evaluating and optimizing mass spectrometric settings on the LTQ-Orbitrap during CID data-dependent acquisition (DDA) mode to improve protein and peptide identification rates. We focus on those MS and MS/MS parameters that have been systematically examined and evaluated by several researchers and are commonly used during DDA. More specifically, we discuss the effect of mass resolving power, preview mode for FTMS scan, monoisotopic precursor selection, signal threshold for triggering MS/MS events, number of microscans per MS/MS scan, number of MS/MS events, automatic gain control target value (ion population) for MS and MS/MS, maximum ion injection time for MS/MS, rapid and normal scan rate, and prediction of ion injection time. We furthermore present data from the latest generation LTQ-Orbitrap system, the Orbitrap Elite, along with recommended MS and MS/MS parameters. The Orbitrap Elite outperforms the Orbitrap Classic in terms of scan speed, sensitivity, dynamic range, and resolving power and results in higher identification rates. Several of the optimized MS parameters determined on the LTQ-Orbitrap Classic and XL were easily transferable to the Orbitrap Elite, whereas others needed to be reevaluated. Finally, the Q Exactive and HCD are briefly discussed, as well as sample preparation, LC-optimization, and bioinformatics analysis. We hope this tutorial will serve as guidance for researchers new to the field of proteomics and assist in achieving optimal results.

Pros and cons of peptide isolectric focusing in shotgun proteomics

In shotgun proteomics, protein mixtures are proteolytically digested before tandem mass spectrometry (MS/MS) analysis. Biological samples are generally characterized by a very high complexity, therefore a step of peptides fractionation before the MS analysis is essential. This passage reduces the sample complexity and increases its compatibility with the sampling performance of the instrument. Among all the existing approaches for peptide fractionation, isoelectric focusing has several peculiarities that are theoretically known but practically rarely exploited by the proteomics community. The main aim of this review is to draw the readers' attention to these unique qualities, which are not accessible with other common approaches, and that represent important tools to increase confidence in the identification of proteins and some post-translational modifications. The general characteristics of different methods to perform peptide isoelectric focusing with natural and artificial pH gradients, the existing instrumentation, and the informatics tools available for isoelectric point calculation are also critically described. Finally, we give some general conclusions on this strategy, underlying its principal limitations.

Mass spectrometry of membrane proteins: a focus on aquaporins

Membrane proteins are abundant, critically important biomolecules that conduct essential functions in all cells and are the targets of a significant number of therapeutic drugs. However, the analysis of their expression, modification, protein-protein interactions, and structure by mass spectrometry has lagged behind similar studies of soluble proteins. Here we review the limitations to analysis of integral membrane and membrane-associated proteins and highlight advances in sample preparation and mass spectrometry methods that have led to the successful analysis of this protein class. Advances in the analysis of membrane protein posttranslational modification, protein-protein interaction, protein structure, and tissue distributions by imaging mass spectrometry are discussed. Furthermore, we focus our discussion on the application of mass spectrometry for the analysis of aquaporins as a prototypical integral membrane protein and how advances in analytical methods have revealed new biological insights into the structure and function of this family of proteins.

Comparative evaluation of electrostatic repulsion-hydrophilic interaction chromatography (ERLIC) and high-pH reversed phase (Hp-RP) chromatography in profiling of rat kidney proteome

ERLIC and high-pH RP (Hp-RP) have been reported to be promising alternatives to strong cation exchange (SCX) in proteome fractionation. Here we compared the performance of ERLIC, concatenated ERLIC and concatenated Hp-RP in proteome profiling. The protein identification is comparable in these three strategies, but significantly more unique peptides are identified by the two concatenation methods, resulting in a significant increase of the average protein sequence coverage. The pooling of fractions from spaced intervals results in more uniform distribution of peptides in each fraction compared with the chromatogram-based pooling of adjacent fractions. ERLIC fractionates peptides according to their pI and GRAVY values. These properties remains but becomes less remarkable in concatenated ERLIC. In contrast, the average pI and GRAVY values of the peptides are comparable in each fraction in concatenated Hp-RP. ERLIC performs the best in identifying peptides with pI>9 among the three strategies, while concatenated Hp-RP is good at identifying peptides with pI<4. These advantages are useful when either basic or acidic peptides/proteins are analytical targets. The power of ERLIC in identification of basic peptides seems to be due to their efficient separation from acidic peptides. This study facilitates the choice of proper fractionation strategies based on specific objectives.

BIOLOGICAL SIGNIFICANCE

For in-depth proteomic analysis of a cell, tissue and plasma, multidimensional liquid chromatography (MDLC) is still necessary to reduce sample complexity for improving analytical dynamic range and proteome coverage. This work conducts a direct comparison of three promising first-dimensional proteome fractionation methods. They are comparable in identifying proteins, but concatenated ERLIC and concatenated Hp-RP identify significantly more unique peptides than ERLIC. ERLIC is good at analyzing basic peptides, while concatenated Hp-RP performs the best in analyzing acidic peptides with pI<4. This will facilitate the choice of the proper peptide fractionation strategy based on a specific need. A combination of different fractionation strategies can be used to increase the sequence coverage and number of protein identification due to the complementary effect between different methods.

Quality assessment for clinical proteomics

Proteomics has emerged from the labs of technologists to enter widespread application in clinical contexts. This transition, however, has been hindered by overstated early claims of accuracy, concerns about reproducibility, and the challenges of handling batch effects properly. New efforts have produced sets of performance metrics and measurements of variability that establish sound expectations for experiments in clinical proteomics. As researchers begin incorporating these metrics in a quality by design paradigm, the variability of individual steps in experimental pipelines will be reduced, regularizing overall outcomes. This review discusses the evolution of quality assessment in 2D gel electrophoresis, mass spectrometry-based proteomic profiling, tandem mass spectrometry-based protein inventories, and proteomic quantitation. Taken together, the advances in each of these technologies are establishing databases that will be increasingly useful for decision-making in clinical experimentation.

Reaching for the deep proteome: recent nano liquid chromatography coupled with tandem mass spectrometry-based studies on the deep proteome

In the last decade, there has been a dramatic progress in separation techniques, mass spectrometry, and bioinformatics, and this progress has significantly improved the techniques on protein analysis. However, the analysis of low-abundance proteins is still challenging because of the limited performance in the method of choice compared to the complexity and the vast dynamic range of biological samples. Since this issue is a big obstacle in most proteomics investigations, great interest has been paid recently to various techniques, such as multi-dimensional analysis, specific peptide selection, high-abundance protein depletion, ligand library treatment, to address this challenge. Therefore, here, the author reviews recent nano liquid chromatography coupled with tandem mass spectrometry-based studies on the deep proteome, mainly focusing on their methods and perspectives.

Proteomic analysis of oropharyngeal carcinomas reveals novel HPV-associated biological pathways

Oropharyngeal carcinoma (OPC) can be classified into two equally prevalent subtypes depending on the presence of human papillomavirus (HPV). Patients with HPV-positive (HPV+) OPC represent a unique cohort with a distinct tumor biology and clinical behavior compared to HPV-negative (HPV-) OPC. Genetic studies have demonstrated chromosomal and gene expression changes associated with distinct subclasses of OPC; however, the proteomic consequences of HPV infection are not known. We analyzed sets of ten HPV+ and ten HPV- OPCs and ten normal adult oral epithelia using a standardized global proteomic analysis platform. This analysis yielded a total of 2,653 confidently identified proteins from which we chose 31 proteins on the basis of expression differences between HPV+, HPV- and normal epithelium for targeted protein quantitation. Analysis of differentially expressed proteins by HPV status revealed enrichment of proteins involved in epithelial cell development, keratinization and extracellular matrix organization in HPV- OPC, whereas enrichment of proteins in DNA initiation and replication and cell cycle control was found for HPV+ OPC. Enrichment analysis for transcription factor targets identified transcription factors E2F1 and E2F4 to be highly expressed in HPV+ OPC. We also found high expression of argininosuccinate synthase 1 in HPV+ OPC, suggesting that HPV+ OPC is more dependent on conditionally essential amino acid, arginine, and this was confirmed on a OPC-specific tissue microarray. These identified proteomic changes reveal novel driving molecular pathways for HPV+ and HPV- OPCs that may be pertinent in therapeutic strategies and outcomes of OPC.

High-pH reversed-phase chromatography with fraction concatenation for 2D proteomic analysis

Orthogonal high-resolution separations are critical for attaining improved analytical dynamic range and protein coverage in proteomic measurements. High-pH reversed-phase liquid chromatography (RPLC), followed by fraction concatenation, affords better peptide analysis than conventional strong cation-exchange chromatography applied for 2D proteomic analysis. For example, concatenated high-pH RPLC increased identification of peptides (by 1.8-fold) and proteins (by 1.6-fold) in shotgun proteomics analyses of a digested human protein sample. Additional advantages of high-pH RPLC with fraction concatenation include improved protein sequence coverage, simplified sample processing and reduced sample losses, making this an attractive alternative to strong cation-exchange chromatography in conjunction with second-dimension low-pH RPLC for 2D proteomics analyses.

Identifying mutated proteins secreted by colon cancer cell lines using mass spectrometry

Secreted proteins encoded by mutated genes (mutant proteins) are a particularly rich source of biomarkers being not only components of the cancer secretome but also actually implicated in tumorigenesis. One of the challenges of proteomics-driven biomarker discovery research is that the bulk of secreted mutant proteins cannot be identified directly and quantified by mass spectrometry due to the lack of mutated peptide information in extant proteomics databases. Here we identify, using an integrated genomics and proteomics strategy (referred to iMASp - identification of Mutated And Secreted proteins), 112 putative mutated tryptic peptides (corresponding to 57 proteins) in the collective secretomes derived from a panel of 18 human colorectal cancer (CRC) cell lines. Central to this iMASp was the creation of Human Protein Mutant Database (HPMD), against which experimentally-derived secretome peptide spectra were searched. Eight of the identified mutated tryptic peptides were confirmed by RT-PCR and cDNA sequencing of RNA extracted from those CRC cells from which the mutation was identified by mass spectrometry. The iMASp technology promises to improve the link between proteomics and genomic mutation data thereby providing an effective tool for targeting tryptic peptides with mutated amino acids as potential cancer biomarker candidates. This article is part of a Special Issue entitled: Integrated omics.

In-depth proteomic analysis of nonsmall cell lung cancer to discover molecular targets and candidate biomarkers

Advances in proteomic analysis of human samples are driving critical aspects of biomarker discovery and the identification of molecular pathways involved in disease etiology. Toward that end, in this report we are the first to use a standardized shotgun proteomic analysis method for in-depth tissue protein profiling of the two major subtypes of nonsmall cell lung cancer and normal lung tissues. We identified 3621 proteins from the analysis of pooled human samples of squamous cell carcinoma, adenocarcinoma, and control specimens. In addition to proteins previously shown to be implicated in lung cancer, we have identified new pathways and multiple new differentially expressed proteins of potential interest as therapeutic targets or diagnostic biomarkers, including some that were not identified by transcriptome profiling. Up-regulation of these proteins was confirmed by multiple reaction monitoring mass spectrometry. A subset of these proteins was found to be detectable and differentially present in the peripheral blood of cases and matched controls. Label-free shotgun proteomic analysis allows definition of lung tumor proteomes, identification of biomarker candidates, and potential targets for therapy.

High confidence and sensitivity four-dimensional fractionation for human plasma proteome analysis

Reducing the complexity of plasma proteome through complex multidimensional fractionation protocols is critical for the detection of low abundance proteins that have the potential to be the most specific disease biomarkers. Therefore, we examined a four dimension profiling method, which includes low abundance protein enrichment, tryptic digestion and peptide fractionation by IEF, SCX and RP-LC. The application of peptide pI filtering as an additional criterion for the validation of the identifications allows to minimize the false discovery rate and to optimize the best settings of the protein identification database search engine. This sequential approach allows for the identification of low abundance proteins, such as angiogenin (10(-9) g/L), pigment epithelium growth factor (10(-8) g/L), hepatocyte growth factor activator (10(-7) g/L) and thrombospondin-1 (10(-6) g/L), having concentrations similar to those of many other growth factors and cytokines involved in disease pathophysiology.

Proteomic consequences of a single gene mutation in a colorectal cancer model

The proteomic effects of specific cancer-related mutations have not been well characterized. In colorectal cancer (CRC), a relatively small number of mutations in key signaling pathways appear to drive tumorigenesis. Mutations in adenomatous polyposis coli (APC), a negative regulator of Wnt signaling, occur in up to 60% of CRC tumors. Here we examine the proteomic consequences of a single gene mutation by using an isogenic CRC cell culture model in which wildtype APC expression has been ectopically restored. Using LC-MS/MS label free shotgun proteomics, over 5000 proteins were identified in SW480Null (mutant APC) and SW480APC (APC restored). We observed 155 significantly differentially expressed proteins between the two cell lines, with 26 proteins showing opposite expression trends relative to gene expression measurements. Protein changes corresponded to previously characterized features of the APCNull phenotype: loss of cell adhesion proteins, increase in cell cycle regulators, alteration in Wnt signaling related proteins, and redistribution of β-catenin. Increased expression of RNA processing and isoprenoid biosynthetic proteins occurred in SW480Null cells. Therefore, shotgun proteomics reveals proteomic differences associated with a single gene change, including many novel differences that fall outside known target pathways.

Protein expression signatures for inhibition of epidermal growth factor receptor-mediated signaling

Analysis of cellular signaling networks typically involves targeted measurements of phosphorylated protein intermediates. However, phosphoproteomic analyses usually require affinity enrichment of phosphopeptides and can be complicated by artifactual changes in phosphorylation caused by uncontrolled preanalytical variables, particularly in the analysis of tissue specimens. We asked whether changes in protein expression, which are more stable and easily analyzed, could reflect network stimulation and inhibition. We employed this approach to analyze stimulation and inhibition of the epidermal growth factor receptor (EGFR) by EGF and selective EGFR inhibitors. Shotgun analysis of proteomes from proliferating A431 cells, EGF-stimulated cells, and cells co-treated with the EGFR inhibitors cetuximab or gefitinib identified groups of differentially expressed proteins. Comparisons of these protein groups identified 13 proteins whose EGF-induced expression changes were reversed by both EGFR inhibitors. Targeted multiple reaction monitoring analysis verified differential expression of 12 of these proteins, which comprise a candidate EGFR inhibition signature. We then tested these 12 proteins by multiple reaction monitoring analysis in three other models: 1) a comparison of DiFi (EGFR inhibitor-sensitive) and HCT116 (EGFR-insensitive) cell lines, 2) in formalin-fixed, paraffin-embedded mouse xenograft DiFi and HCT116 tumors, and 3) in tissue biopsies from a patient with the gastric hyperproliferative disorder Ménétrier's disease who was treated with cetuximab. Of the proteins in the candidate signature, a core group, including c-Jun, Jagged-1, and Claudin 4, were decreased by EGFR inhibitors in all three models. Although the goal of these studies was not to validate a clinically useful EGFR inhibition signature, the results confirm the hypothesis that clinically used EGFR inhibitors generate characteristic protein expression changes. This work further outlines a prototypical approach to derive and test protein expression signatures for drug action on signaling networks.

Chemoresistant colorectal cancer cells and cancer stem cells mediate growth and survival of bystander cells

BACKGROUND

Recent studies suggest that cancer stem cells (CSCs) mediate chemoresistance, but interestingly, only a small percentage of cells in a resistant tumour are CSCs; this suggests that non-CSCs survive by other means. We hypothesised that chemoresistant colorectal cancer (CRC) cells generate soluble factors that enhance survival of chemonaive tumour cells.

METHODS

Chemoresistant CRC cells were generated by serial passage in oxaliplatin (Ox cells). Conditioned media (CM) was collected from parental and oxaliplatin-resistant (OxR) cells. CRC cells were treated with CM and growth and survival were assessed. Tumour growth rates were determined in nude mice after cells were treated with CM. Mass spectrometry (MS) identified proteins in CM. Reverse phase protein microarray assays determined signalling effects of CM in parental cells.

RESULTS

Oxaliplatin-resistant CM increased survival of chemo-naive cells. CSC CM also increased growth of parental cells. Parental and OxR mixed tumours grew larger than tumours composed of parental or OxR cells alone. Mass spectrometry detected unique survival-promoting factors in OxR CM compared with parental CM. Cells treated with OxR CM demonstrated early phosphorylation of EGFR and MEK1, with later upregulation of total Akt .We identified progranulin as a potential mediator of chemoresistance.

CONCLUSION

Chemoresistant tumour cells and CSCs may promote resistance through soluble factors that mediate survival in otherwise chemosensitive tumour cells.

Electrostatic repulsion-hydrophilic interaction chromatography (ERLIC) versus strong cation exchange (SCX) for fractionation of iTRAQ-labeled peptides

The iTRAQ technique is popular for the comparative analysis of proteins in different complex samples. To increase the dynamic range and sensitivity of peptide identification in shotgun proteomics, SCX chromatography is generally used for the fractionation of iTRAQ-labeled peptides before LC-MS/MS analysis. However, SCX suffers from clustering of similarly charged peptides and the need to desalt fractions. In this report, SCX is compared with the alternative ERLIC method for fractionating iTRAQ-labeled peptides. The simultaneous effect of electrostatic repulsion and hydrophilic interaction in ERLIC results in peptide elution in order of decreasing pI and GRAVY values (increasing polarity). Volatile solvents can be used. We applied ERLIC to iTRAQ-labeled peptides from rat liver tissue, and 2745 proteins and 30,016 unique peptides were identified with high confidence from three technical replicates. This was 12.9 and 49.4% higher, respectively, than was obtained using SCX. In addition, ERLIC is appreciably better at the identification of highly hydrophobic peptides. The results indicate that ERLIC is a more convenient and more effective alternative to SCX for the fractionation of iTRAQ-labeled peptides. Quantification data show that both SCX and ERLIC fractionation have no significant effect on protein quantification by iTRAQ.

Online nanoflow multidimensional fractionation for high efficiency phosphopeptide analysis

Despite intense, continued interest in global analyses of signaling cascades through mass spectrometry-based studies, the large-scale, systematic production of phosphoproteomics data has been hampered in-part by inefficient fractionation strategies subsequent to phosphopeptide enrichment. Here we explore two novel multidimensional fractionation strategies for analysis of phosphopeptides. In the first technique we utilize aliphatic ion pairing agents to improve retention of phosphopeptides at high pH in the first dimension of a two-dimensional RP-RP. The second approach is based on the addition of strong anion exchange as the second dimension in a three-dimensional reversed phase (RP)-strong anion exchange (SAX)-RP configuration. Both techniques provide for automated, online data acquisition, with the 3-D platform providing the highest performance both in terms of separation peak capacity and the number of unique phosphopeptide sequences identified per μg of cell lysate consumed. Our integrated RP-SAX-RP platform provides several analytical figures of merit, including: (1) orthogonal separation mechanisms in each dimension; (2) high separation peak capacity (3) efficient retention of singly- and multiply-phosphorylated peptides; (4) compatibility with automated, online LC-MS analysis. We demonstrate the reproducibility of RP-SAX-RP and apply it to the analysis of phosphopeptides derived from multiple biological contexts, including an in vitro model of acute myeloid leukemia in addition to primary polyclonal CD8(+) T-cells activated in vivo through bacterial infection and then purified from a single mouse.

Integrated proteomic profiling of cell line conditioned media and pancreatic juice for the identification of pancreatic cancer biomarkers

Pancreatic cancer is one of the leading causes of cancer-related deaths, for which serological biomarkers are urgently needed. Most discovery-phase studies focus on the use of one biological source for analysis. The present study details the combined mining of pancreatic cancer-related cell line conditioned media and pancreatic juice for identification of putative diagnostic leads. Using strong cation exchange chromatography, followed by LC-MS/MS on an LTQ-Orbitrap mass spectrometer, we extensively characterized the proteomes of conditioned media from six pancreatic cancer cell lines (BxPc3, MIA-PaCa2, PANC1, CAPAN1, CFPAC1, and SU.86.86), the normal human pancreatic ductal epithelial cell line HPDE, and two pools of six pancreatic juice samples from ductal adenocarcinoma patients. All samples were analyzed in triplicate. Between 1261 and 2171 proteins were identified with two or more peptides in each of the cell lines, and an average of 521 proteins were identified in the pancreatic juice pools. In total, 3479 nonredundant proteins were identified with high confidence, of which ∼ 40% were extracellular or cell membrane-bound based on Genome Ontology classifications. Three strategies were employed for identification of candidate biomarkers: (1) examination of differential protein expression between the cancer and normal cell lines using label-free protein quantification, (2) integrative analysis, focusing on the overlap of proteins among the multiple biological fluids, and (3) tissue specificity analysis through mining of publically available databases. Preliminary verification of anterior gradient homolog 2, syncollin, olfactomedin-4, polymeric immunoglobulin receptor, and collagen alpha-1(VI) chain in plasma samples from pancreatic cancer patients and healthy controls using ELISA, showed a significant increase (p < 0.01) of these proteins in plasma from pancreatic cancer patients. The combination of these five proteins showed an improved area under the receiver operating characteristic curve to CA19.9 alone. Further validation of these proteins is warranted, as is the investigation of the remaining group of candidates.

Online nanoflow reversed phase-strong anion exchange-reversed phase liquid chromatography-tandem mass spectrometry platform for efficient and in-depth proteome sequence analysis of complex organisms

The dynamic range of protein expression in complex organisms coupled with the stochastic nature of discovery-driven tandem mass spectrometry (MS/MS) analysis continues to impede comprehensive sequence analysis and often provides only limited information for low-abundance proteins. High-performance fractionation of proteins or peptides prior to mass spectrometry analysis can mitigate these effects, though achieving an optimal combination of automation, reproducibility, separation peak capacity, and sample yield remains a significant challenge. Here we demonstrate an automated nanoflow 3-D liquid chromatography (LC)-MS/MS platform based on high-pH reversed phase (RP), strong anion exchange (SAX), and low-pH reversed phase (RP) separation stages for analysis of complex proteomes. We observed that RP-SAX-RP outperformed RP-RP for analysis of tryptic peptides derived from Escherichia coli and enabled identification of proteins present at a level of 50 copies per cell in Saccharomyces cerevisiae, corresponding to an estimated detection limit of 500 amol, from 40 μg of total lysate on a low-resolution 3-D ion trap mass spectrometer. A similar study performed on a LTQ-Orbitrap yielded over 4000 unique proteins from 5 μg of total yeast lysate analyzed in a single, 101 fraction RP-SAX-RP LC-MS/MS acquisition, providing an estimated detection limit of 65 amol for proteins expressed at 50 copies per cell.

Proteomic reactors and their applications in biology

Proteomic analysis requires the combination of an extensive suite of technologies including protein processing and separation, micro-flow HPLC, MS and bioinformatics. Although proteomic technologies are still in flux, approaches that bypass gel electrophoresis (gel-free approaches) are dominating the field of proteomics. Along with the development of gel-free proteomics, came the development of devices for the processing of proteomic samples termed proteomic reactors. These microfluidic devices provide rapid, robust and efficient pre-MS sample procession by performing protein sample preparation/concentration, digestion and peptide fractionation. The proteomic reactor has advanced in two major directions: immobilized enzyme reactor and ion exchange-based proteomic reactor. This review summarizes the technical developments and biological applications of the proteomic reactor over the last decade.

Reversed-phase chromatography with multiple fraction concatenation strategy for proteome profiling of human MCF10A cells

In this study, we evaluated a concatenated low pH (pH 3) and high pH (pH 10) reversed-phase liquid chromatography strategy as a first dimension for two-dimensional liquid chromatography tandem mass spectrometry ("shotgun") proteomic analysis of trypsin-digested human MCF10A cell sample. Compared with the more traditional strong cation exchange method, the use of concatenated high pH reversed-phase liquid chromatography as a first-dimension fractionation strategy resulted in 1.8- and 1.6-fold increases in the number of peptide and protein identifications (with two or more unique peptides), respectively. In addition to broader identifications, advantages of the concatenated high pH fractionation approach include improved protein sequence coverage, simplified sample processing, and reduced sample losses. The results demonstrate that the concatenated high pH reversed-phased strategy is an attractive alternative to strong cation exchange for two-dimensional shotgun proteomic analysis.

ScanRanker: Quality assessment of tandem mass spectra via sequence tagging

In shotgun proteomics, protein identification by tandem mass spectrometry relies on bioinformatics tools. Despite recent improvements in identification algorithms, a significant number of high quality spectra remain unidentified for various reasons. Here we present ScanRanker, an open-source tool that evaluates the quality of tandem mass spectra via sequence tagging with reliable performance in data from different instruments. The superior performance of ScanRanker enables it not only to find unassigned high quality spectra that evade identification through database search but also to select spectra for de novo sequencing and cross-linking analysis. In addition, we demonstrate that the distribution of ScanRanker scores predicts the richness of identifiable spectra among multiple LC-MS/MS runs in an experiment, and ScanRanker scores assist the process of peptide assignment validation to increase confident spectrum identifications. The source code and executable versions of ScanRanker are available from http://fenchurch.mc.vanderbilt.edu.