LC‐MS/MS as an alternative for SDS‐PAGE in blue native analysis of protein complexes

Two‐dimensional blue native/SDS‐PAGE is widely applied to investigate native protein–protein interactions, particularly those within membrane multi‐protein complexes. MS has enabled the application of this approach at the proteome scale, typically by analysis of picked protein spots. Here, we investigated the potential of using LC‐MS/MS as an alternative for SDS‐PAGE in blue native (BN) analysis of protein complexes. By subjecting equal slices from BN gel lanes to label‐free semi‐quantitative LC‐MS/MS, we determined an abundance profile for each protein across the BN gel, and used these profiles to identify potentially interacting proteins by protein correlation profiling. We demonstrate the feasibility of this approach by considering the oxidative phosphorylation complexes I–V in the native human embryonic kidney 293 mitochondrial fraction, showing that the method is capable of detecting both the fully assembled complexes as well as assembly/turnover intermediates of complex I (NADH:ubiquinone oxidoreductase). Using protein correlation profiling with a profile for subunits NDUFS2, 3, 7 and 8 we identified multiple proteins possibly involved in the biogenesis of complex I, including the recently implicated chaperone C6ORF66 and a novel candidate, C3ORF60.     

Stopping the clock on proteomic degradation by heat treatment at the point of tissue excision

The effectiveness of rapid and controlled heating of intact tissue to inactivate native enzymatic activity and prevent proteome degradation has been evaluated. Mouse brains were bisected immediately following excision, with one hemisphere being heat treated followed by snap freezing in liquid nitrogen while the other hemisphere was snap frozen immediately. Sections were cut by cryostatic microtome and analyzed by MALDI‐MS imaging and minimal label 2‐D DIGE, to monitor time‐dependent relative changes in intensities of protein and peptide signals. Analysis by MALDI‐MS imaging demonstrated that the relative intensities of markers varied across a time course (0–5 min) when the tissues were not stabilized by heat treatment. However, the same markers were seen to be stabilized when the tissues were heat treated before snap freezing. Intensity profiles for proteins indicative of both degradation and stabilization were generated when samples of treated and nontreated tissues were analyzed by 2‐D DIGE, with protein extracted before and after a 10‐min warming of samples. Thus, heat treatment of tissues at the time of excision is shown to prevent subsequent uncontrolled degradation of tissues at the proteomic level before any quantitative analysis, and to be compatible with downstream proteomic analysis.     

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

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

Glycomic/glycoproteomic analysis by liquid chromatography/mass spectrometry: analysis of glycan structural alteration in cells

The alteration of glycosyltransferase expression and the subsequent changes in oligosaccharide structures are reported in several diseases. The analysis of glycan structural alteration in glycoproteins is becoming increasingly important in the discovery of therapies and diagnostic markers. In this study, we propose a strategy for glycomic/glycoproteomic analysis based on oligosaccharide profiling by LC/MS followed by proteomic approaches, including 2-DE and 2-D lectin blot. As a model of aberrant cells, we used Chinese hamster ovary cells transfected with N-acetylglucosaminyltransferase III (GnT-III), which catalyzes the addition of a bisecting N-acetylglucosamine (GlcNAc) to beta-mannose of the mannosyl core of N-linked oligosaccharides. LC/MS equipped with a graphitized carbon column (GCC) enabled us to elucidate the structural alteration induced by the GnT-III expression. Using 2-D lectin blot followed by LC/MS/MS, the protein carrying an extra N-acetylhexosamine in cells transfected with GnT-III was successfully identified as integrin alpha3. Thus, oligosaccharide profiling by GCC-LC/MS followed by proteomic methods can be a powerful tool for glycomic/glycoproteomic analysis.     

Comparative proteomic analysis of trophoblast cell models reveals their differential phenotypes,potential uses,and limitations

Trophoblastic cell lines are widely used in in vitro studies of placental function as a surrogate for primary trophoblasts. To date, no reference proteomics dataset exists to directly compare the shared and unique characteristics of these cells. Here, we performed comparative proteomic profiling of the BeWo and HTR8/SVneo cell lines using label‐free quantitative MS. A total of 1557 proteins were identified, which included 338 uniquely attributed to BeWo cells, and a further 304 specifically identified in HTR8/SVneo cells. Raw data are available via ProteomeXchange, identifier PDX005045. Of the 915 proteins expressed by both cell lines, 105 were of higher abundance in BeWo cells, while 199 proteins had a significantly higher expression in HTR8/SVneo cells. Comparative GO of unique and upregulated proteins revealed principal differences in cell junction/adhesion, catenin complex, spindle and microtubule associated complex, as well as cell differentiation. Our data indicate that BeWo cells express an epithelial proteome more characteristic of villous trophoblasts, whereas HTR8/SVneo cells embrace a mesenchymal phenotype, more characteristic of extravillous trophoblasts. This novel comparative proteomic profiling of these trophoblastic cell lines provides a useful platform for future investigations of placental function.     

Analysis of Human Nuclear Protein Complexes by Quantitative Mass Spectrometry Profiling

Analysis of protein complexes provides insights into how the ensemble of expressed proteome is organized into functional units. While there have been advances in techniques for proteome‐wide profiling of cytoplasmic protein complexes, information about human nuclear protein complexes are very limited. To close this gap, we combined native size exclusion chromatography (SEC) with label‐free quantitative MS profiling to characterize hundreds of nuclear protein complexes isolated from human glioblastoma multiforme T98G cells. We identified 1794 proteins that overlapped between two biological replicates of which 1244 proteins were characterized as existing within stably associated putative complexes. co‐IP experiments confirmed the interaction of PARP1 with Ku70/Ku80 proteins and HDAC1 (histone deacetylase complex 1) and CHD4. HDAC1/2 also co‐migrated with various SIN3A and nucleosome remodeling and deacetylase components in SEC fractionation including SIN3A, SAP30, RBBP4, RBBP7, and NCOR1. Co‐elution of HDAC1/2/3 with both the KDM1A and RCOR1 further confirmed that these proteins are integral components of human deacetylase complexes. Our approach also demonstrated the ability to identify potential moonlighting complexes and novel complexes containing uncharacterized proteins. Overall, the results demonstrated the utility of SEC fractionation and LC–MS analysis for system‐wide profiling of proteins to predict the existence of distinct forms of nuclear protein complexes.     

LC‐MS/MS‐based serum proteomics for identification of candidate biomarkers for hepatocellular carcinoma

Associating changes in protein levels with the onset of cancer has been widely investigated to identify clinically relevant diagnostic biomarkers. In the present study, we analyzed sera from 205 patients recruited in the United States and Egypt for biomarker discovery using label‐free proteomic analysis by LC‐MS/MS. We performed untargeted proteomic analysis of sera to identify candidate proteins with statistically significant differences between hepatocellular carcinoma (HCC) and patients with liver cirrhosis. We further evaluated the significance of 101 proteins in sera from the same 205 patients through targeted quantitation by MRM on a triple quadrupole mass spectrometer. This led to the identification of 21 candidate protein biomarkers that were significantly altered in both the United States and Egyptian cohorts. Among the 21 candidates, ten were previously reported as HCC‐associated proteins (eight exhibiting consistent trends with our observation), whereas 11 are new candidates discovered by this study. Pathway analysis based on the significant proteins reveals upregulation of the complement and coagulation cascades pathway and downregulation of the antigen processing and presentation pathway in HCC cases versus patients with liver cirrhosis. The results of this study demonstrate the power of combining untargeted and targeted quantitation methods for a comprehensive serum proteomic analysis, to evaluate changes in protein levels and discover novel diagnostic biomarkers. All MS data have been deposited in the ProteomeXchange with identifier PXD001171 ( http://proteomecentral.proteomexchange.org/dataset/PXD001171 ).     

Proteomic differences in recombinant CHO cells producing two similar antibody fragments

Chinese hamster ovary (CHO) cells are the most commonly used mammalian hosts for the production of biopharmaceuticals. To overcome unfavorable features of CHO cells, a lot of effort is put into cell engineering to improve phenotype. “Omics” studies investigating elevated growth rate and specific productivities as well as extracellular stimulus have already revealed many interesting engineering targets. However, it remains largely unknown how physicochemical properties of the recombinant product itself influence the host cell. In this study, we used quantitative label‐free LC‐MS proteomic analyses to investigate product‐specific proteome differences in CHO cells producing two similar antibody fragments. We established recombinant CHO cells producing the two antibodies, 3D6 and 2F5, both as single‐chain Fv‐Fc homodimeric antibody fragments (scFv‐Fc). We applied three different vector strategies for transgene delivery (i.e., plasmid, bacterial artificial chromosome, recombinase‐mediated cassette exchange), selected two best performing clones from transgene variants and transgene delivery methods and investigated three consecutively passaged cell samples by label‐free proteomic analysis. LC‐MS‐MS profiles were compared in several sample combinations to gain insights into different aspects of proteomic changes caused by overexpression of two different heterologous proteins. This study suggests that not only the levels of specific product secretion but the product itself has a large impact on the proteome of the cell. Biotechnol. Bioeng. 2016;113: 1902–1912. © 2016 The Authors. Biotechnology and Bioengineering Published by Wiley Periodicals, Inc.     

Intact protein profiling in breast cancer biomarker discovery: Protein identification issue and the solutions based on 3D protein separation,bottom‐up and top‐down mass spectrometry

Proteomics profiling of intact proteins based on MALDI‐TOF MS and derived platforms has been used in cancer biomarker discovery studies. This approach suffers from a number of limitations such as low resolution, low sensitivity, and that no knowledge is available on the identity of the respective proteins in the discovery mode. Nevertheless, it remains the most high‐throughput, untargeted mode of clinical proteomics studies to date. Here we compare key protein separation and MS techniques available for protein biomarker identification in this type of studies and define reasons of uncertainty in protein peak identity. As a result of critical data analysis, we consider 3D protein separation and identification workflows as optimal procedures. Subsequently, we present a new protocol based on 3D LC‐MS/MS with top‐down at high resolution that enabled the identification of HNRNP A2/B1 intact peptide as correlating with the estrogen receptor expression in breast cancer tissues. Additional development of this general concept toward next generation, top‐down based protein profiling at high resolution is discussed.     

Adolescent Risperidone treatment alters protein expression associated with protein trafficking and cellular metabolism in the adult rat prefrontal cortex

The prefrontal cortex (PFC) is associated with mental health illnesses including schizophrenia, depression, bipolar disorder, and autism spectrum disorders. It richly expresses neuroreceptors which are the target for antipsychotics. However, as the precise mechanism of action of antipsychotic medications is not known, proteomic studies of the effects of antipsychotic drugs on the brain are warranted. In the current study, we aimed to characterize protein expression in the adult rodent PFC (n = 5 per group) following low‐dose treatment with Risperidone or saline in adolescence (postnatal days 34–47). The PFC was examined by triplicate 1 h runs of label‐free LC‐MS/MS. The raw mass spectral data were analyzed with the MaxQuant^TM software. Statistical analysis was carried out using SAS® Version 9.1. Pathway and functional analysis was performed with IngenuityPathway Analysis and in the Database for Annotation, Visualization and Integrated Discovery (DAVID), respectively, the most implicated pathways were found to be related to mitochondrial function, protein trafficking, and the cytoskeleton. This report adds to the current repertoire of data available concerning the effects of antipsychotic drugs on the brain and sheds light on their biological mechanisms. The MS data have been deposited with the ProteomeXchange Consortium with dataset identifier PXD000480.     

Proteome profiling of human epithelial ovarian cancer cell line TOV-112D

A proteome profiling of the epithelial ovarian cancer cell line TOV-112D was initiated as a protein expression reference in the study of ovarian cancer. Two complementary proteomic approaches were used in order to maximise protein identification: two-dimensional gel electrophoresis (2DE) protein separation coupled to matrix assisted laser desorption/ionisation time-of-flight mass spectrometry (MALDI-TOF MS) and one-dimensional gel electrophoresis (1DE) coupled to liquid-chromatography tandem mass spectrometry (LC MS/MS). One hundred and seventy-two proteins have been identified among 288 spots selected on two-dimensional gels and a total of 579 proteins were identified with the 1DE LC MS/MS approach. This proteome profiling covers a wide range of protein expression and identifies several proteins known for their oncogenic properties. Bioinformatics tools were used to mine databases in order to determine whether the identified proteins have previously been implicated in pathways associated with carcinogenesis or cell proliferation. Indeed, several of the proteins have been reported to be specific ovarian cancer markers while others are common to many tumorigenic tissues or proliferating cells. The diversity of proteins found and their association with known oncogenic pathways validate this proteomic approach. The proteome 2D map of the TOV-112D cell line will provide a valuable resource in studies on differential protein expression of human ovarian carcinomas while the 1DE LC MS/MS approach gives a picture of the actual protein profile of the TOV-112D cell line. This work represents one of the most complete ovarian protein expression analysis reports to date and the first comparative study of gene expression profiling and proteomic patterns in ovarian cancer.     

Platelet Releasate Proteome Profiling Reveals a Core Set of Proteins with Low Variance between Healthy Adults

Upon activation, platelets release a powerful cocktail of soluble and vesicular signals, collectively termed the "platelet releasate" (PR). Although several studies have used qualitative/quantitative proteomic approaches to characterize PR; with debated content and significant inter‐individual variability reported, confident, and reliable insights have been hindered. Using label‐free quantitative (LFQ)‐proteomics analysis, a reproducible, quantifiable investigation of the 1U mL^?1 thrombin‐induced PR from 32 healthy adults was conducted. MS proteomics data are available via ProteomeXchange, identifier PXD009310. Of the 894 proteins identified, 277 proteins were quantified across all donors and form a "core" PR. Bioinformatics and further LFQ‐proteomic analysis revealed that the majority (84%) of "core" PR proteins overlapped with the protein composition of human platelet‐derived exosomes. Vesicles in the exosomal‐size range were confirmed in healthy‐human PR and reduced numbers of similar‐sized vesicles were observed in the PR of a mouse model of gray platelet syndrome, known to be deficient in platelet alpha‐granules. Lastly, the variability of proteins in the PR was assessed, and reproducible secretion levels were found across all 32 healthy donors. Taken together, the PR contains valuable soluble and vesicular cargo and has low‐population variance among healthy adults, rendering it a potentially useful platform for diagnostic fingerprinting of platelet‐related disease.     

Possible target‐related proteins and signal network of bufalin in A549 cells suggested by both iTRAQ‐based and label‐free proteomic analysis

Bufalin (BF) exhibited antiproliferation and antimigration effects on human A549 lung cancer cells. To search its target‐related proteins, protein expression profiles of BF‐treated and control cells were compared using two quantitative proteomic methods, iTRAQ‐based and label‐free proteomic analysis. A total of 5428 proteins were identified in iTRAQ‐based analysis while 6632 proteins were identified in label‐free analysis. The number of common identified proteins of both methods was 4799 proteins. By application of 1.20‐fold for upregulated and 0.83‐fold for downregulated cutoff values, 273 and 802 differentially expressed proteins were found in iTRAQ‐based and label‐free analysis, respectively. The number of common differentially expressed proteins of both methods was 45 proteins. Results of bioinformational analysis using Metacore^TM showed that the two proteomic methods were complementary and both suggested the involvement of oxidative stress and regulation of gene expression in the effects of BF, and fibronectin‐related pathway was suggested to be an important pathway affected by BF. Western blotting assay results confirmed BF‐induced change in levels of fibronectin and other related proteins. Overexpression of fibronectin by plasmid transfection ameliorated antimigration effects of BF. Results of the present study provided information about possible target‐related proteins and signal network of BF.     

Protein recovery and identification from the gulf killifish, Fundulus grandis: comparing snap-frozen and RNAlater® preserved tissues

Reliable proteomic analysis of biological tissues requires sampling approaches that preserve proteins as close to their in vivo state as possible. In the current study, the patterns of protein abundance in one‐dimensional (1‐D) gels were assessed for five tissues of the gulf killifish, Fundulus grandis, following snap‐freezing tissues in liquid nitrogen or immersion of fresh tissues in RNAlater^®. In liver and heart, the protein profiles in 1‐D gels were better preserved by snap‐freezing, while in gill, the 1‐D protein profile was better preserved by immersion in RNAlater^®. In skeletal muscle and brain, the two approaches yielded similar patterns of protein abundance. LC‐MS/MS analyses and database searching resulted in the identification of 17 proteins in liver and 12 proteins in gill. Identified proteins include enzymes of energy metabolism, structural proteins, and proteins serving other biological functions. These protein identifications for a species without a sequenced genome demonstrate the utility of F. grandis as a model organism for environmental proteomic studies in vertebrates.     

ICPLQuant – A software for non‐isobaric isotopic labeling proteomics

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

Identification of Plasma Membrane Glycoproteins Specific to Human Glioblastoma Multiforme Cells Using Lectin Arrays and LC‐MS/MS

Glioblastoma, also known as glioblastoma multiforme (GBM), is the most malignant type of brain cancer and has poor prognosis with a median survival of less than one year. While the structural changes of tumor cell surface carbohydrates are known to be associated with invasive behavior of tumor cells, the cell surface glycoproteins to differentiate the low‐ and high‐grade glioma cells can be potential diagnostic markers and therapeutic targets for GBMs. In the present study, lectin arrays consisting of eight lectins were employed to explore cell surface carbohydrate expression patterns on low‐grade oligodendroglioma cells (Hs683) and GBM cells (T98G). Griffonia simplicifolia I (GS I) was found to selectively bind to T98G cells and not to Hs683 cells. For identification of the glioblastoma‐specific cell surface markers, the glycoproteins from each cell type were captured by a GS I lectin column and analyzed by LC‐MS/MS. The identified proteins from the two cell types were quantified using label‐free quantitative analysis based on spectral counting. Of cell surface glycoproteins showing significant increases in T98G cells, five proteins were selected for verification of both protein and glycosylation level changes using Western blot and GS I lectin‐based immunosorbent assay.     

A label‐free internal standard method for the differential analysis of bioactive lupin proteins using nano HPLC‐Chip coupled with Ion Trap mass spectrometry

Quantitative proteomics based on MS is useful for pointing out the differences in some food proteomes relevant to human nutrition. Stable isotope label‐free (SIF) techniques are suitable for comparing an unlimited number of samples by the use of relatively simple experimental workflows. We have developed an internal standard label‐free method based on the intensities of peptide precursor ions from MS/MS spectra, collected in data dependent runs, for the simultaneous qualitative characterization and relative quantification of storage proteins of Lupinus albus seeds in protein extracts of four lupin cultivars (cv Adam, Arés, Lucky, Multitalia). The use of an innovative microfluidic system, the HPLC‐Chip, coupled with a classical IT mass spectrometer, has allowed a complete qualitative characterization of all proteins. In particular, the homology search mode has permitted to identify single amino acid substitutions in the sequences of vicilins (β‐conglutin precursor and vicilin‐like protein). The MS/MS sequencing of substituted peptides confirms the high heterogeneity of vicilins according to the peculiar characteristics of the vicilin‐encoding gene family. Two suitable bioinformatics parameters were optimized for the differential analyses of the main bioactive proteins: the “normalized protein average of common reproducible peptides” (N‐ACRP) for γ‐conglutin, which is a homogeneous protein, and the “normalized protein mean peptide spectral intensity” (N‐MEAN) for the highly heterogenous class of the vicilins.