Multiplexed LC‐MS/MS analysis of horse plasma proteins to study doping in sport

The development of protein biomarkers for the indirect detection of doping in horse is a potential solution to doping threats such as gene and protein doping. A method for biomarker candidate discovery in horse plasma is presented using targeted analysis of proteotypic peptides from horse proteins. These peptides were first identified in a novel list of the abundant proteins in horse plasma. To monitor these peptides, an LC‐MS/MS method using multiple reaction monitoring was developed to study the quantity of 49 proteins in horse plasma in a single run. The method was optimised and validated, and then applied to a population of race‐horses to study protein variance within a population. The method was finally applied to longitudinal time courses of horse plasma collected after administration of an anabolic steroid to demonstrate utility for hypothesis‐driven discovery of doping biomarker candidates.     

Immuno‐MALDI‐TOF MS: New perspectives for clinical applications of mass spectrometry

The discovery of novel biomarkers by means of advanced detection tools based on proteomic analysis technologies necessitates the development of improved diagnostic methods for application in clinical routine. On the basis of three different application examples, this review presents the limitations of conventional routine diagnostic assays and illustrates the advantages of immunoaffinity enrichment combined with MALDI‐TOF MS. Applying this approach increases the specificity of the analysis supporting a better diagnostic recognition, sensitivity, and differentiation of certain diseases. The use of MALDI‐TOF MS as detection method facilitates the identification of modified peptides and proteins providing additional information. Further, employing respective internal standard peptides allows for relative and absolute quantitation which is mandatory in the clinical context. Although MALDI‐TOF MS is not yet established for clinical routine diagnostics this technology has a high potential for improvement of clinical diagnostics and monitoring therapeutic efficacy.     

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

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

iTRAQ‐coupled 2‐D LC‐MS/MS analysis of protein profile associated with HBV‐modulated DNA methylation

The development of hepatocellular carcinoma (HCC) is believed to be associated with multiple risk factors, including the infection of hepatitis B virus (HBV). Based on the analysis of individual genes, evidence has indicated the association between HCC and HBV and has also been expanded to epigenetic regulation, with an involvement of HBV in the DNA methylation of the promoter of cellular target genes leading to changes in their expression. Proteomic study has been widely used to map a comprehensive protein profile, which in turn could provide a better understanding of underlying mechanisms of disease onset. In the present study, we performed a proteomic profiling by using iTRAQ‐coupled 2‐D LC/MS‐MS analysis to identify cellular genes down‐regulated in HBV‐producing HepG2.2.15 cells compared with HepG2 cells. A total of 15 proteins including S100A6 and Annexin A2 were identified by our approach. The significance of these cellular proteins as target of HBV‐mediated epigenetic regulation was supported by our validation assays, including their reactivation in cells treated with 5‐aza‐2′‐deoxycytidine (a DNA methyltransferase inhibitor) by real‐time RT‐PCR and Western blot analysis, as well as the DNA methylation status analysis by bisulfite genome sequencing. Our approach provides a comprehensive analysis of cellular target proteins to HBV‐mediated epigenetic regulation and further analysis should facilitate a better understanding of its involvement in HCC development.     

Identification of complement C3a as a candidate biomarker in human chronic hepatitis C and HCV-related hepatocellular carcinoma using a proteomics approach

Although the significant risk factors for hepatocellular carcinoma (HCC) are well known from epidemiological studies, diagnosis of this disease at an early stage is difficult, and HCC remains one of the leading causes of cancer death worldwide. Thus, to identify any useful HCC-related biomarkers is still a need. We performed SELDI-TOF MS to identify differentially expressed proteins in HCC serum using weak cation exchange protein chips. Protein characterization was performed by 2-DE separation and nano flow LC-MS/MS. A total of 55 sera were collected from HCC patients and compared with those from 48 patients with chronic hepatitis and 9 healthy individuals. A candidate marker of about 8900 Da was detected as differentially expressed in patients with chronic hepatitis C and hepatitis C virus (HCV)-related HCC. We identified this differentially expressed protein as complement C3a. The expression of C3a in HCC sera was further validated by PS20 chip immunoassay and Western blotting. Complement C3a was found to be elevated in patients with chronic hepatitis C and HCV-related HCC. The combination of SELDI-TOF MS and 2-DE provides a solution to identify disease-associated serum biomarkers.     

Proteomic analysis of mouse astrocytes and their secretome by a combination of FASP and StageTip‐based,high pH,reversed‐phase fractionation

Astrocytes are the most abundant cells in the CNS, but their function remains largely unknown. Characterization of the whole‐cell proteome and secretome in astrocytes would facilitate the study of their functions in various neurodegenerative diseases and astrocyte–neuron communication. To build a reference proteome, we established a C8‐D1A astrocyte proteome to a depth of 7265 unique protein groups using a novel strategy that combined two‐step digestion, filter‐aided sample preparation, StageTip‐based high pH fractionation, and high‐resolution MS. Nearly, 6000 unique protein groups were identified from conditioned media of astrocyte cultures, constituting the largest astrocyte secretome that has been reported. High‐confidence whole‐cell proteomes and secretomes are valuable resources in studying astrocyte function by label‐free quantitation and bioinformatics analysis. All MS data have been deposited in the ProteomeXchange with identifier PXD000501 ( http://proteomecentral.proteomexchange.org/dataset/PXD000501 ).     

Proteomic analysis of sera from hepatocellular carcinoma patients after radiofrequency ablation treatment

Comparative proteomic analysis was used to search for characteristic alterations in the sera of hepatocellular carcinoma (HCC) patients who had undergone curative radiofrequency ablation treatment. Serum samples collected from eight patients before and after treatment were subjected to 2-DE. Eighty-eight protein spots differentially expressed with the treatment were selected by clustering analysis, and the proteins were identified by MS based on MALDI-TOF/TOF analysis and public database searches. The statistical analysis suggested that four proteins decreased after treatment (pro-apolipoprotein, alpha2-HS glycoprotein, apolipoprotein A-IV precursor, and PRO1708/PRO2044, which is the carboxy terminal fragment of albumin) and that seven proteins were increased after treatment, including leucine-rich alpha2-glycoprotein and alpha1-antitrypsin. These data facilitate the identification of differentially expressed proteins that are involved in HCC carcinogenesis and provide candidate biomarkers for the development of diagnostic and therapeutic tools.     

Expression changes of proteins associated with the development of preeclampsia in maternal plasma: A case‐control study

Defective deep placentation, involving abnormal transformation of the spiral arteries in the junctional zone of the myometrium, is known to cause significant obstetric complications, such as preeclampsia (PE), fetal growth restriction, and placental infarction leading to fetal death. Serological biomarkers to predict and diagnose PE would help antenatal care and reduce obstetric complications. To discover candidate PE biomarkers, we first performed global proteomic profiling of three pairs of plasma samples obtained from pregnant women in the early second trimester, who subsequently developed PE, and controls to identify candidate proteins that were abundant in the patients. We further evaluated the changes in the expression of PE‐representing proteins in stored plasma samples of a cohort that subsequently developed PE and their matched controls by MRM‐MS analysis. We identified that both complement C1s subcomponent (C1S) and protein AMBP were elevated in the plasma samples of the PE cohort before the manifestation of clinical disease. We propose that these proteins may be involved in the remodeling process of the spiral arteries even before PE manifestation. These proteins can serve as potential plasma biomarkers to predict the pregnant women having an increased risk of developing PE.     

Proteomic analysis of liver tissue from HBx‐transgenic mice at early stages of hepatocarcinogenesis

The hepatitis B virus X‐protein (HBx), a multifunctional viral regulator, participates in the viral life cycle and in the development of hepatocellular carcinoma (HCC). We previously reported a high incidence of HCC in transgenic mice expressing HBx. In this study, proteomic analysis was performed to identify proteins that may be involved in hepatocarcinogenesis and/or that could be utilized as early detection biomarkers for HCC. Proteins from the liver tissue of HBx‐transgenic mice at early stages of carcinogenesis (dysplasia and hepatocellular adenoma) were separated by 2‐DE, and quantitative changes were analyzed. A total of 22 spots displaying significant quantitative changes were identified using LC‐MS/MS. In particular, several proteins involved in glucose and fatty acid metabolism, such as mitochondrial 3‐ketoacyl‐CoA thiolase, intestinal fatty acid‐binding protein 2 and cytoplasmic malate dehydrogenase, were differentially expressed, implying that significant metabolic alterations occurred during the early stages of hepatocarcinogenesis. The results of this proteomic analysis provide insights into the mechanism of HBx‐mediated hepatocarcinogenesis. Additionally, this study identifies possible therapeutic targets for HCC diagnosis and novel drug development for treatment of the disease.     

The advantage of laser‐capture microdissection over whole tissue analysis in proteomic profiling studies

Laser‐capture microdissection (LCM) offers a reliable cell population enrichment tool and has been successfully coupled to MS analysis. Despite this, most proteomic studies employ whole tissue lysate (WTL) analysis in the discovery of disease biomarkers and in profiling analyses. Furthermore, the influence of tissue heterogeneity in WTL analysis, nor its impact in biomarker discovery studies have been completely elucidated. In order to address this, we compared previously obtained high resolution MS data from a cohort of 38 breast cancer tissues, of which both LCM enriched tumor epithelial cells and WTL samples were analyzed. Label‐free quantification (LFQ) analysis through MaxQuant software showed a significantly higher number of identified and quantified proteins in LCM enriched samples (3404) compared to WTLs (2837). Furthermore, WTL samples displayed a higher amount of missing data compared to LCM both at peptide and protein levels (p‐value < 0.001). 2D analysis on co‐expressed proteins revealed discrepant expression of immune system and lipid metabolisms related proteins between LCM and WTL samples. We hereby show that LCM better dissected the biology of breast tumor epithelial cells, possibly due to lower interference from surrounding tissues and highly abundant proteins. All data have been deposited in the ProteomeXchange with the dataset identifier PXD002381 ( http://proteomecentral.proteomexchange.org/dataset/PXD002381 ).     

Identification of novel biomarker candidates for immunohistochemical diagnosis to distinguish low‐grade chondrosarcoma from enchondroma

Chondrosarcoma is the third most common primary bone cancer, requiring surgical resection. However, differentiation of low‐grade chondrosarcoma (grade 1) from enchondroma that is benign and only requires regular follow‐up is one of the most frequent diagnostic dilemmas facing orthopedic oncologists in clinical management. Although multiple techniques are applied to make the distinction, immunohistochemistry is an important ancillary technique, especially when a histopathological stain of specimen must be obtained in order to guarantee an accurate confirmation. Currently, no adequate immunohistochemical diagnostic protein biomarkers are available to distinguish low‐grade chondrosarcoma from enchondroma. To discover novel protein biomarker candidates, an LC‐MS/MS approach was applied to directly compare formalin‐fixed, paraffin‐embedded low‐grade chondrosarcoma with enchondroma tissue samples. The proteomics analysis revealed 17 protein biomarker candidates. A principle was developed to prioritize the candidates using category and ranking. An algorithm, prioritization index of biomarker candidates for immunohistochemistry on tissue specimens, was developed to rank the candidates inside each category. Using the proteomics data and bioinformatics results, the prioritization index of biomarker candidates for immunohistochemistry on tissue revealed periostin as a top candidate. Immunohistochemical staining of periostin in 23 low‐grade chondrosarcoma and 31 enchondroma tissue specimens disclosed 87% specificity and 70% sensitivity.     

Proteomic identification of rainbow trout seminal plasma proteins

In the study, the combination of protein fractionation by 1DE and HPLC‐ESI‐MS/MS was used to characterize the rainbow trout seminal plasma proteome. Our results led to the creation of a catalogue of rainbow trout seminal plasma proteins (152 proteins) and significantly contributed to the current knowledge regarding the protein composition of fish seminal plasma. The major proteins of rainbow trout seminal plasma, such as transferrin, apolipoproteins, complement C3, serum albumin, and hemopexin‐, alpha‐1‐antiproteinase‐, and precerebellin‐like protein, were recognized as acute‐phase proteins (proteins that plasma concentration changes in response to inflammation). This study provides the basis for further functional studies of fish seminal plasma proteins, as well as for the identification of novel biomarkers for sperm quality. The MS data have been deposited in the ProteomeXchange with identifier PXD000306 ( http://proteomecentral.proteomexchange.org/dataset/PXD000306 ).     

In‐depth characterization of the tomato fruit pericarp proteome

Since the genome of Solanum lycopersicum L. was published in 2012, some studies have explored its proteome although with a limited depth. In this work, we present an extended characterization of the proteome of the tomato pericarp at its ripe red stage. Fractionation of tryptic peptides generated from pericarp proteins by off‐line high‐pH reverse‐phase phase chromatography in combination with LC‐MS/MS analysis on a Fisher Scientific Q Exactive and a Sciex Triple‐TOF 6600 resulted in the identification of 8588 proteins with a 1% FDR both at the peptide and protein levels. Proteins were mapped through GO and KEGG databases and a large number of the identified proteins were associated with cytoplasmic organelles and metabolic pathways categories. These results constitute one of the most extensive proteome datasets of tomato so far and provide an experimental confirmation of the existence of a high number of theoretically predicted proteins. All MS data are available in the ProteomeXchange repository with the dataset identifiers PXD004947 and PXD004932.     

2‐D PAGE and MS analysis of proteins from formalin‐fixed,paraffin‐embedded tissues

In the past decade, encouraging results have been obtained in extraction and analysis of proteins from formalin‐fixed, paraffin‐embedded (FFPE) tissues. However, 2‐D PAGE protein maps with satisfactory proteomic information and comparability to fresh tissues have never been described to date. In the present study, we report 2‐D PAGE separation and MS identification of full‐length proteins extracted from FFPE skeletal muscle tissue. The 2‐D protein profiles obtained from FFPE tissues could be matched to those achieved from frozen tissues replicates. Up to 250 spots were clearly detected in 2‐D maps of proteins from FFPE tissue following standard mass‐compatible silver staining. Protein spots from both FFPE and frozen tissue 2‐D gels were excised, subjected to in situ hydrolysis, and identified by MS analysis. Matched spots produced matched protein identifications. Moreover, 2‐D protein maps from FFPE tissues were successfully subjected to Western immunoblotting, producing comparable results to fresh‐frozen tissues. In conclusion, this study provides evidence that, when adequately extracted, full‐length proteins from FFPE tissues might be suitable to 2‐D PAGE‐MS analysis, allowing differential proteomic studies on the vast existing archives of healthy and pathological‐fixed tissues.     

Comparison of sialylated N‐glycopeptide levels in serum of pancreatic cancer patients,acute pancreatitis patients,and healthy controls

Serum protein glycosylation is known to be affected by pathological conditions, including cancer and inflammatory diseases. Pancreatic cancer patients would benefit from early diagnosis, as the disease is often detected in an advanced stage and has poor prognosis. Searching for changes in serum protein site‐specific glycosylation could reveal novel glycoprotein biomarkers. We used Sambucus nigra lectin affinity chromatography to enrich α‐2,6 sialylated tryptic N‐glycopeptides from albumin‐depleted sera of pancreatic cancer patients, acute pancreatitis patients, and healthy individuals, and compared their relative abundance using ultra performance LC‐MS. Relative quantitation was done using the spectrum processing software MZmine. Identification was performed on the web‐based tool GlycopeptideID, developed for in silico analysis of intact N‐glycopeptides. Seventeen high‐abundance serum proteins, mainly acute‐phase proteins, and immunoglobulins, with total 27 N‐glycosylation sites, and 62 glycoforms, were identified. Pancreatitis patient sera contained 38, and pancreatic cancer patients sera contained 13 glycoform changes with statistical significance (p < 0.05). In pancreatitis, up to tenfold changes were found in some glycoforms, and in pancreatic cancer, threefold. Analysis showed that the changes often concerned one or two, but not all, N‐glycosylation sites in a specific glycoprotein. In conclusion, the analysis shows that pancreatic cancer, and acute pancreatitis are associated with changes in concentrations of intact sialylated N‐glycopeptides derived from acute‐phase proteins, and immunoglobulins, and that changes are site specific.     

A lectin-coupled, targeted proteomic mass spectrometry (MRM MS) platform for identification of multiple liver cancer biomarkers in human plasma

Aberrantly glycosylated proteins related to liver cancer progression were captured with specific lectin and identified from human plasma by multiple reaction monitoring (MRM) mass spectrometry as multiple biomarkers for hepatocellular carcinoma (HCC). The lectin fractionation for fucosylated protein glycoforms in human plasma was conducted with a fucose-specific aleuria aurantia lectin (AAL). Following tryptic digestion of the lectin-captured fraction, plasma samples from 30 control cases (including 10 healthy, 10 hepatitis B virus [HBV], and 10 cirrhosis cases) and 10 HCC cases were quantitatively analyzed by MRM to identify which glycoproteins are viable HCC biomarkers. A1AG1, AACT, A1AT, and CERU were found to be potent biomarkers to differentiate HCC plasma from control plasmas. The AUROC generated independently from these four biomarker candidates ranged from 0.73 to 0.92. However, the lectin-coupled MRM assay with multiple combinations of biomarker candidates is superior statistically to those generated from the individual candidates with AUROC more than 0.95, which can be an alternative to the immunoassay inevitably requiring tedious development of multiple antibodies against biomarker candidates to be verified. Eventually the lectin-coupled, targeted proteomic mass spectrometry (MRM MS) platform was found to be efficient to identify multiple biomarkers from human plasma according to cancer progression.     

Discovery and identification of serum potential biomarkers for pulmonary tuberculosis using iTRAQ‐coupled two‐dimensional LC‐MS/MS

Pulmonary tuberculosis (TB) caused by Mycobacterium tuberculosis is a chronic disease. Currently, there are no sufficiently validated biomarkers for early diagnosis of TB infection. In this study, a panel of potential serum biomarkers was identified between patients with pulmonary TB and healthy controls by using iTRAQ‐coupled 2D LC‐MS/MS technique. Among 100 differentially expressed proteins screened, 45 proteins were upregulated (>1.25‐fold at p < 0.05) and 55 proteins were downregulated (<0.8‐fold at p < 0.05) in the TB serum. Bioinformatics analysis revealed that the differentially expressed proteins were related to the response to stimulus, the metabolic and immune system processes. The significantly differential expression of apolipoprotein CII (APOCII), CD5 antigen‐like (CD5L), hyaluronan‐binding protein 2 (HABP2), and retinol‐binding protein 4 (RBP4) was further confirmed using immunoblotting and ELISA analysis. By forward stepwise multivariate regression analysis, a panel of serum biomarkers including APOCII, CD5L, and RBP4 was obtained to form the disease diagnostic model. The receiver operation characteristic curve of the diagnostic model was 0.98 (sensitivity = 93.42%, specificity = 92.86%). In conclusion, APOCII, CD5L, HABP2, and RBP4 may be potential protein biomarkers of pulmonary TB. Our research provides useful data for early diagnosis of TB.     

Coupling proteomics and transcriptomics in the quest of subtype‐specific proteins in breast cancer

Breast‐cancer subtypes present with distinct clinical characteristics. Therefore, characterization of subtype‐specific proteins may augment the development of targeted therapies and prognostic biomarkers. To address this issue, MS‐based secretome analysis of eight breast cancer cell lines, corresponding to the three main breast cancer subtypes was performed. More than 5200 non‐redundant proteins were identified with 23, four, and four proteins identified uniquely in basal, HER2‐neu‐amplified, and luminal breast cancer cells, respectively. An in silico mRNA analysis using publicly available breast cancer tissue microarray data was carried out as a preliminary verification step. In particular, the expression profiles of 15 out of 28 proteins included in the microarray (from a total of 31 in our subtype‐specific signature) showed significant correlation with estrogen receptor (ER) expression. A MS‐based analysis of breast cancer tissues was undertaken to verify the results at the proteome level. Eighteen out of 31 proteins were quantified in the proteomes of ER‐positive and ER‐negative breast cancer tissues. Survival analysis using microarray data was performed to examine the prognostic potential of these selected candidates. Three proteins correlated with ER status at both mRNA and protein levels: ABAT, PDZK1, and PTX3, with the former showing significant prognostic potential.     

Identification of inositol 1,4,5‐trisphosphate‐binding proteins by heparin‐agarose affinity purification and LTQ ORBITRAP MS in Oryza sativa

Inositol 1,4,5‐trisphosohate (IP₃) and its receptors play a pivotal role in calcium signal transduction in mammals. However, no homologs of mammalian IP₃ receptors have been found in plants. In this study, we isolated the microsomal fractions from rice cells in suspension culture and further obtained putative IP₃‐binding proteins by heparin‐agarose affinity purification. The IP₃‐binding activities of these protein fractions were determined by [³H] IP₃‐binding assay. SDS‐PAGE and MS analysis were then performed to characterize these proteins. We have identified 297 proteins from the eluates of heparin‐agarose column chromatography, which will provide insight into the IP₃ signaling pathways in plants. All MS data have been deposited in the ProteomeXchange with identifier PXD000763 ( http://proteomecentral.proteomexchange.org/dataset/PXD000763 ).