Proteome Discoverer Research Articles

Urinary protein biomarkers based on LC-MS/MS analysis to discriminate vascular dementia from Alzheimer's disease in Han Chinese population.

This study aimed to identify the potential urine biomarkers of vascular dementia (VD) and unravel the disease-associated mechanisms by applying Liquid chromatography tandem-mass spectrometry (LC-MS/MS). LC-MS/MS proteomic analysis was applied to urine samples from 3 groups, including 14 patients with VD, 9 patients with AD, and 21 normal controls (NC). By searching the MS data by Proteome Discoverer software, analyzing the protein abundances qualitatively and quantitatively, comparing between groups, combining bioinformatics analysis using Gene Ontology (GO) and pathway crosstalk analysis using Kyoto Encyclopedia of Genes and Genomes (KEGG), and literature searching, the differentially expressed proteins (DEPs) of VD can be comprehensively determined at last and were further quantified by receiver operating characteristic (ROC) curve methods. The proteomic findings showed quantitative changes in patients with VD compared to patients with NC and AD groups; among 4,699 identified urine proteins, 939 and 1,147 proteins displayed quantitative changes unique to VD vs. NC and AD, respectively, including 484 overlapped common DEPs. Then, 10 unique proteins named in KEGG database (including PLOD3, SDCBP, SRC, GPRC5B, TSG101/STP22/VPS23, THY1/CD90, PLCD, CDH16, NARS/asnS, AGRN) were confirmed by a ROC curve method. Our results suggested that urine proteins enable detection of VD from AD and VC, which may provide an opportunity for intervention.

Identification of molecular network of gut-brain axis associated with neuroprotective effects of PPARδ-ligand erucic acid in rotenone-induced Parkinson's disease model in zebrafish.

Disruption of the gut-brain axis in Parkinson's disease (PD) may lead to motor symptoms and PD pathogenesis. Recently, the neuroprotective potential of different PPARδ-agonists has been shown. We aimed to reveal the effects of erucic acid, peroxisome proliferator-activated receptors (PPARs)-ligand in rotenone-induced PD model in zebrafish, focusing on the gut-brain axis. Adult zebrafish were exposed to rotenone and erucic acid for 30 days. Liquid chromatography-mass spectrometry and tandem mass spectrometry (LC-MS/MS) analysis was performed. Raw files were analysed by Proteome Discoverer 2.4 software; peptide lists were searched against Danio rerio proteins. STRING database was used for protein annotations or interactions. Lipid peroxidation (LPO), nitric oxide (No), alkaline phosphatase, superoxide dismutase, glutathione S-transferase (GST), acetylcholinesterase and the expressions of PD-related genes were determined. Immunohistochemical tyrosine hydroxylase (TH) staining was performed. LC-MS/MS analyses allowed identification of over 2000 proteins in each sample. The 2502 and 2707 proteins overlapped for intestine and brain. The 196 and 243 significantly dysregulated proteins in the brain and intestines were found in rotenone groups. Erucic acid treatment corrected the changes in the expression of proteins associated with cytoskeletal organisation, transport and localisation and improved locomotor activity, expressions of TH, PD-related genes (lrrk2, park2, park7, pink1) and oxidant-damage in brain and intestines in the rotenone group as evidenced by decreased LPO, No and increased GST. Our results showed beneficial effects of erucic acid as a PPARδ-ligand in neurotoxin-induced PD model in zebrafish. We believe that our study will shed light on the mechanism of the effects of PPARδ agonists and ω9-fatty acids in the gut-brain axis of PD.

A bottom-up proteomics workflow for a system containing multiple organisms.

Discovery proteomics has been popularized to be essential in the investigator's biological toolbox. Many biological problems involve the interplay of multiple organisms. Herein, a bottom-up proteomics workflow was developed to study a system containing multiple organisms to promote a thorough understanding of how each interacts with the others. A label-free quantification proteomics workflow was developed with nanoscale liquid chromatography coupled to tandem mass spectrometry (nanoLC-MS/MS). This protocol describes a bottom-up proteomics workflow used to study differential protein expression in the context of fleas (Ctenocephalides felis felis) experimentally infected by the bacterium Bartonella henselae, the etiological agent of Cat Scratch Disease (CSD). Step-by-step instructions are provided for protein extraction, protein cleanup, total protein measurement, nanoLC-MS/MS data acquisition, and data analysis using Proteome Discoverer software. Comprehensive and exhaustive details are included to promote the adoption of this proteomics workflow in other laboratories. A proteomics protocol is detailed for a system containing multiple proteomes from different taxonomic lineages using CSD (cats bitten by fleas infected with Bartonella henselae) as a model. The operating protocol can be readily applied to other label-free proteomics work involving multiple proteomes from taxonomically distinct organisms.

Implementing the MSFragger Search Engine as a Node in Proteome Discoverer.

Here, we describe the implementation of the fast proteomics search engine MSFragger as a processing node in the widely used Proteome Discoverer (PD) software platform. PeptideProphet (via the Philosopher tool kit) is also implemented as an additional PD node to allow validation of MSFragger open (mass-tolerant) search results. These two nodes, along with the existing Percolator validation module, allow users to employ different search strategies and conveniently inspect search results through PD. Our results have demonstrated the improved numbers of PSMs, peptides, and proteins identified by MSFragger coupled with Percolator and significantly faster search speed compared to the conventional SEQUEST/Percolator PD workflows. The MSFragger-PD node is available at https://github.com/nesvilab/PD-Nodes/releases/.

PGlycoQuant with a deep residual network for quantitative glycoproteomics at intact glycopeptide level

Large-scale intact glycopeptide identification has been advanced by software tools. However, tools for quantitative analysis remain lagging behind, which hinders exploring the differential site-specific glycosylation. Here, we report pGlycoQuant, a generic tool for both primary and tandem mass spectrometry-based intact glycopeptide quantitation. pGlycoQuant advances in glycopeptide matching through applying a deep learning model that reduces missing values by 19–89% compared with Byologic, MSFragger-Glyco, Skyline, and Proteome Discoverer, as well as a Match In Run algorithm for more glycopeptide coverage, greatly expanding the quantitative function of several widely used search engines, including pGlyco 2.0, pGlyco3, Byonic and MSFragger-Glyco. Further application of pGlycoQuant to the N-glycoproteomic study in three different metastatic HCC cell lines quantifies 6435 intact N-glycopeptides and, together with in vitro molecular biology experiments, illustrates site 979-core fucosylation of L1CAM as a potential regulator of HCC metastasis. We expected further applications of the freely available pGlycoQuant in glycoproteomic studies.

Broad‐ranging effects of APOE4 on cellular protein expression in neural precursors

AbstractBackgroundIt is increasingly becoming evident that ApoE4 isoform contributes to AD risk over the life course of individuals. Much remains unknown about the biological pathways that connect APOE4 genotype with the development of pathology that eventually leads to AD, nor do we know how early in life these cellular alterations begin. To answer these questions, we derived neural precursor cells (NPCs) from induced pluripotent stem cells (IPSCs) that were CRISPR‐edited at APOE locus (Ramakrishna et al. 2021; Schmid et al. 2019). We intended to characterize the protein expression landscape in the NPCs subsequent to targeted deletion of E4 from a parent IPSC line of APOE3/4 genotype.MethodsProtein isolates from NPCs were analyzed on the Thermo Scientific‐ Orbitrap Fusion instrument and the resulting Mass Spectrometer data was searched against a reference human protein database using Proteome Discoverer 2.2. Differentially expressed proteins (DEP) were determined from the protein abundance fold change values obtained for each protein. Proteins which showed >1.2‐fold difference with FDR adjusted P‐value < 0.05 were considered differentially expressed. DEPs were mapped to STRING database (v11.5) for retrieval of interacting proteins and functional enrichment.ResultsCRISPR‐editing of E4 from the parent line revealed 105 differential expressed proteins. Of these, 62 were upregulated, and 43 were downregulated. Further analysis of the DEPs via STRING database showed that these changes primarily affect pathways linked to RNA processing, plasma membrane repair, and cytoskeleton organization.ConclusionsOur primary motivation was to determine proteomic alterations with targeted deletion of E4. And indeed, we find the effects of E4 extend beyond proteins considered central to AD pathology. Knowing more about the protein interactions regulated by ApoE, in an isoform‐specific manner, has the potential to reveal novel drug targets. In future experiments, we intend to follow the DEPs identified here and the associated pathways through the course of neural differentiation.

Proteomic Characterisation of the Plasma Proteome in Extramedullary Multiple Myeloma Identifies Potential Prognostic Biomarkers

Introduction: Extramedullary multiple myeloma (EMM) is an aggressive manifestation of multiple myeloma (MM) reported to occur in approximately 7% of patients at diagnosis and up to 30% of patients at relapse. EMM is characterised by the spread of malignant plasma cells from the bone marrow microenvironment to distal tissues or organs. It is associated with an adverse prognosis, correlating with a significant reduction in overall survival. Currently there are no validated, established biomarkers to predict EMM. Furthermore, EMM is often treated similarly to high-risk MM with no targeted therapeutic strategies. In-depth proteomic studies on EMM are lacking and the underlying molecular mechanisms that facilitate extramedullary transition are yet to be fully defined. Novel biomarkers and therapeutic targets are urgently required. To enhance our understanding of EMM and to identify novel prognostic biomarkers, we performed a mass spectrometry-based proteomic study on plasma from MM patients with and without extramedullary spread. Methods: Label-free liquid chromatography mass spectrometric analysis of age and gender-matched medullary MM (n=8) and EMM (n=9) blood plasma samples was carried out using a Thermo Q-Exactive mass spectrometer (Thermo Fisher Scientific). Proteome Discoverer 2.2 using Sequest HT (Thermo Fisher Scientific) and a percolator were employed for the identification of peptides and proteins. Several parameters were defined for protein identification: MS/MS mass tolerance was set to 0.02 Da; peptide mass tolerance was set to 10ppm; methionine oxidation was set as a variable modification; carbamido-methylation was set as a fixed modification; and up to two missed cleavages were tolerated. Peptide probability was set to high confidence. Data was imported into Perseus (1.6.14.0) for further analysis. Proteins with less than 70% valid values were removed from the analysis. Proteins of interest were identified based on an FDR-adjusted p-value ≤0.1, fold change >1.5 between experimental groups. Six proteins were selected for further validation using DuoSet enzyme linked immunosorbent assay (ELISA) kits (R&D Systems). We performed receiver operating characteristic (ROC) and area under the curve (AUC) analyses to determine the diagnostic potential of the validated proteins. Results: The median age was 65. Survival analysis revealed a statistically significant change in overall survival (OS) between the two patient cohorts (Log-rank = 3.977, P = 0.046). The median OS of patients with EMM and those without extramedullary spread was 19 months and 83 months, respectively. Our quantitative MS-based proteomic analysis identified 21 proteins of differential abundance between EMM and MM patient plasma (False discovery rate (FDR)-adjusted p-value < 0.1, fold change > 1.5) (Fig. 1A). Antibody-based validation using ELISAs was performed on six proteins (vascular cell adhesion molecule 1 (VCAM1), hepatocyte growth factor activator (HGFA), pigment epithelial-derived factor (PEDF), alpha-2-macroglobulin (A2M), cholinesterase (BCHE), aminopeptidase N (CD13)). VCAM1, HGFA and PEDF were confirmed as being significantly altered between the two cohorts (FDR-adjusted p-value < 0.05). VCAM1, HGFA and PEDF were subject to ROC analyses, demonstrating high discriminatory power for EMM diagnosis (AUC = 0.96, AUC = 0.85, and AUC = 0.97, respectively). The diagnostic efficacy was further enhanced by combining these biomarkers using a logistic regression model (AUC = 1). Conclusion: Our mass spectrometry and antibody-based study identified proteins of differential abundance in the blood plasma of MM patients with and without extramedullary spread. VCAM1, PEDF and HGFA represent promising predictive biomarkers and warrant further investigation in a larger cohort of patients. Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal

Paleoproteomic profiling for identification of animal skin species in ancient Egyptian archaeological leather using liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS)

Ancient protein analysis provides clues to human life and diseases from ancient times. Paleoproteomics has the potential to give a better understanding of the modes of fabrication of ancient materials, their composition, and pathways of degradation, as well as the development of animal fibers through domestication and breeding. Thus, this study aimed at providing guidance for choosing proteomics workflows to analyze leather samples and their capacity to distinguish between unknown archeological species. Here, we performed shotgun proteomics of archeological animal skin for the first time. The raw output data were analyzed using three different software (Proteome Discoverer, Protein Pilot, and Peptide Shaker) with their impeded algorithms. The study found that the best species identification percentage was obtained using protein piolet with protein database. Particularly prevalent and relatively high collagen expression suggests its resistance to degradation, despite the samples’ exposure to environmental and chemical alterations. The success of this case study indicates that further analyses could assist in reworking historical baseline data for putative identification of unknown archeological samples.

Comparative Evaluation of Proteome Discoverer and FragPipe for the TMT-Based Proteome Quantification.

Isobaric labeling-based proteomics is widely applied in deep proteome quantification. Among the platforms for isobaric labeled proteomic data analysis, the commercial software Proteome Discoverer (PD) is widely used, incorporating the search engine CHIMERYS, while FragPipe (FP) is relatively new, free for noncommercial purposes, and integrates the engine MSFragger. Here, we compared PD and FP over three public proteomic data sets labeled using 6plex, 10plex, and 16plex tandem mass tags. Our results showed the protein abundances generated by the two software are highly correlated. PD quantified more proteins (10.02%, 15.44%, 8.19%) than FP with comparable NA ratios (0.00% vs. 0.00%, 0.85% vs. 0.38%, and 11.74% vs. 10.52%) in the three data sets. Using the 16plex data set, PD and FP outputs showed high consistency in quantifying technical replicates, batch effects, and functional enrichment in differentially expressed proteins. However, FP saved 93.93%, 96.65%, and 96.41% of processing time compared to PD for analyzing the three data sets, respectively. In conclusion, while PD is a well-maintained commercial software integrating various additional functions and can quantify more proteins, FP is freely available and achieves similar output with a shorter computational time. Our results will guide users in choosing the most suitable quantification software for their needs.

Influence of dietary carbohydrate profile on the dairy cow rumen meta-proteome.

Diet starch and fiber contents influence the rumen microbial profile and its fermentation products, yet no information exists about the effects of these dietary carbohydrate fractions on the metabolic activity of these microbes. The objective of this experiment was to evaluate the effects of dietary carbohydrate profile changes on the rumen meta-proteome profile. Eight cannulated Holstein cows were assigned to the study as part of a 4 × 4 Latin square design with a 2 × 2 factorial treatment arrangement including four 28-d periods. Cows received 1 of 4 dietary treatments on a dry matter (DM) basis. Diets included different concentrations of rumen fermentable starch (RFS) and physically effective undigested NDF (peuNDF240) content in the diet: (1) low peuNDF240, low RFS (LNLS); (2) high peuNDF240, low RFS (HNLS); (3) low peuNDF240, high RFS (LNHS); and (4) high peuNDF240, high RFS (HNHS). Rumen fluid samples were collected from each cow on the last 2 d of each period at 3 time points (0600, 1000, and 1400 h). The microbial protein fraction was isolated, isobarically labeled, and analyzed using liquid chromatography combined with tandem mass spectrometry techniques. Product ion spectra were searched using the SEQUEST search on Proteome Discoverer 2.4 (Thermo Scientific) against 71 curated microbe-specific databases. Data were analyzed using PROC MIXED procedure in SAS 9.4 (SAS Institute Inc.). A total of 138 proteins were characterized across 26 of the searched microbial species. In total, 46 proteins were affected by treatments across 17 of the searched microbial species. Of these 46 proteins, 28 were affected by RFS content across 13 microbial species, with 20 proteins having higher abundance with higher dietary RFS and 8 proteins having higher abundance with lower dietary RFS. The majority of these proteins have roles in energetics, carbon metabolism, and protein synthesis. Examples include pyruvate, phosphate dikinase (Ruminococcus albus SY3), 30S ribosomal protein S11 (Clostridium aminophilum), and methyl-coenzyme M reductase subunit α (Methanobrevibacter ruminantium strain 35063), which had higher abundances with higher dietary RFS. Conversely, glutamate dehydrogenase (Butyrivibrio fibrisolvens) and 50S ribosomal protein L5 (Pseudobutyrivibrio ruminis) and L15 (Ruminococcus bromii) had lower abundances with higher dietary RFS content. Among the remaining 18 proteins unaffected by RFS content alone, 5 proteins were affected by peuNDF240 content, and 13 were affected by peuNDF240 × RFS interactions. Our results suggest that the RFS content of the diet may have a greater influence on rumen microbial protein abundances than dietary peuNDF240 content or peuNDF240 × RFS interactions. This research highlights that dietary carbohydrate profile changes can influence rumen microbial protein abundances. Further research is needed to fully characterize the effects of diet on the rumen meta-proteome and manipulate the various roles of rumen microbes. This will aid in designing the strategies to maximize the efficiency of nutrient use in the rumen.

226 Proteomic and Metabolomic Profiles are Associated with Fresh Pork Loin Quality Phenotypes

Abstract The objective was to define proteomic and metabolomic profiles associated with premium and poor-quality pork. Fresh pork loins (n=100) were aged 12 to 14 d postmortem before quality evaluation. Chops with a star probe values less than 4.5 kg, and a Hunter L score less than 47 were categorized as Premium (n=10). Chops with star probe values greater than 5.7 kg and Hunter L greater than 49.7 were categorized as Poor (n=10). Proteins soluble in low ionic strength buffer (50 mM Tris-HCl pH 8.5 and 1 mM EDTA) were extracted, digested with trypsin, and labeled with 11-plex isobaric TMT labels. Peptides were introduced to the Q-Exactive Hybrid Quadrupole-Orbitrap Mass Spectrometer and identified and quantified with Proteome Discoverer. Data were normalized to the total ion count from each run, Log2 transformed, and median normalization was performed. Only proteins identified in at least one-half of the samples containing at least two unique peptides were included in the analysis. Non-targeted metabolomic analyses were conducted on extracts (80% methanol) of each sample. Separation was conducted with a TG-5MS column (Thermo Scientific, 30m x 0.25mm x 0.25mm). Masses between 50-620 m/z were scanned at four scans/sec after electron impact ionization operating at 70eV. All data were analyzed in R 4.1.1 using the limma package with a false discovery rate of 0.05. Poor chops contained more sugars, including glucose, glucose-6-phosphate, fructose, and galactose. Premium chops had more amino acids, including leucine, isoleucine, serine, and methionine. Proteins/peptides in greater abundance in the soluble fraction in the Premium chops (n=24 proteins) included titin, filamin, phosphoglycerate mutase, AMP deaminase, heat shock protein 27, and calcium transporting ATPase. Proteins/peptides in greater proportion in the Poor chops (n=12 proteins) included annexin, adenylate kinase, and Maillard deglycase. The results demonstrate that distinct molecular phenotypes are associated with variation in fresh pork quality.

P343 Novel hydrophobic binding surface proteins are instrumental for phagocytosis of Lichtheimia corymbifera by macrophages

Poster session 3, September 23, 2022, 12:30 PM - 1:30 PMObjectivesPerform proteomic analysis of the spore surface alongside secretome analysis of two strains of Lichtheimia corymbifera.Evaluate interaction, recognition, and phagocytosis of Lichtheimia spores by murine alveolar macrophages.MethodsTwo strains of L. corymbifera (JMRC: FSU: 09682 and JMRC: FSU: 10164) were used in this study. For phagocytosis assay, the spores were labeled with 0.1 mg/ml Fluorescein isothiocyanate (FITC) (Sigma Aldrich Chemie) in 0.1 M Na2CO3 for 30 min 146 at 30°C. Murine alveolar macrophages MH-S (ATCC:CRL-2019) were cultivated in RPMI-1640 (Sigma, 30-2001) supplemented.Identification of the surface proteins of L. corymbifera was carried out as described before with minor modification.1 The supernatants were stored at −80°C for liquid chromatography-mass spectrometry (LC-MS/MS) analysis. Secreted proteins of L. corymbifera were determined as described in a previous study with minor modification2.The raw files generated by the LC-MS/MS were further processed by the software Proteome Discoverer v1.4.0.288 (Thermo). Tandem mass spectra were searched against the NCBI L. corymbifera protein database.3 Approximately 10 000 MH-S cells were cultivated onto 96-well microplates (NUNC 163320) in 100 μL RPMI-1640 medium (Sigma, 30-2001). Images were acquired by the Zeiss Axio Observer 7 Spinning Disk Confocal Microscope (ZEISS, Jena, Germany) and processed with ZEN 2.1 Software (ZEISS) by 63x objective lens.ResultsAbundant surface proteins were found which serve as Candidates for secretome analysis. A total of 113 proteins were identified. Thirty proteins were confirmed to be on the spore surface based on the presence of signal peptides3. The following proteins were predominantly identified: Spore coat protein (CotH), hydrophobic surface binding protein A (HsbA), aconitase, ricin-like lectin, two transition elongation factors, multi-copper oxidase, heat shock protein 70 family (Hsp70), malate synthase, putative allergen Candidates, etc.These proteins were heterologsly overexpressed in yeast. Successful overexpression was confirmed by LC-MS/MS. The yeast mutants were subjected to phagocytosis assays (Fig. 1). The role of surface proteins in macrophages is discussed.ConclusionThe surface proteins are instrumental for recognition of L. corymbifera by macrophages and for intracellular survival in macrophages. The role of surface proteins is discussed in the light of evolution from environmental to human pathogenic fungus.Sources:Voltersen V, Blango MG, Herrmann S, et al. Proteome Analysis Reveals the Conidial Surface Protein CcpA Essential for Virulence of the Pathogenic Fungus Aspergillus fumigatus. mBio. 2018;9(5). doi:10.1128/MBIO.01557-18Thürich J, Meichsner D, Furch ACU, et al. Arabidopsis thaliana responds to colonisation of Piriformospora indica by secretion of symbiosis-specific proteins. PLOS ONE. 2018;13(12):e0209658. doi:10.1371/JOURNAL. PONE.0209658.Schwartze VU, Winter S, Shelest E, et al. Gene Expansion Shapes Genome Architecture in the Human Pathogen Lichtheimia corymbifera: An Evolutionary Genomics Analysis in the Ancient Terrestrial Mucorales (Mucoromycotina). PLOS Genetics. 2014;10(8):e1004496. doi:10.1371/JOURNAL.PGEN.1004496.

Determination of the species origin and thrombin-like enzyme content of Bothrops atrox venom by ultra-high performance liquid chromatography-tandem mass spectrometry based on marker peptide

蛇毒血凝酶类药物是以蝮蛇蛇毒为原料制备的止血药,主要活性成分为蛇毒类凝血酶(svTLEs)。不同蛇种来源的svTLEs结构不同,止血机制不同,药理作用也存在差异,因此准确鉴别蛇毒种属来源和svTLEs含量对于保障该类产品的质量至关重要。研究基于蛋白质组学技术,筛选出了具有种属特异性的矛头蝮蛇svTLE特征肽,并建立了基于特征肽的超高效液相色谱-串联质谱(UHPLC-MS/MS)检测矛头蝮蛇蛇毒种属来源及类凝血酶含量的方法。采用胰蛋白酶对纯化的矛头蝮蛇svTLE进行酶解,利用纳升液相色谱-四极杆/静电场轨道阱高分辨质谱(Nano LC-Q-Exactive-MS)和Proteome Discoverer 2.2软件分别进行多肽的检测和鉴定,通过BLAST搜索与Uniprot数据库对比分析,筛选出具有种属特异性的矛头蝮蛇svTLEs特征肽“EAYNGLPAK”。针对该特征肽对酶解温度、酶解时间和酶用量等样品前处理方法进行了优化,利用超高效液相色谱-串联质谱,以m/z 481.9>315.2和481.9>485.2作为检测离子对,采用ESI+模式进行了多反应监测(MRM)定性定量分析。结果显示,特征肽在2.5~30 ng/mL范围内线性关系良好,相关系数(r)大于0.9996,多水平加标回收率范围为95.5%~101.9%,各水平平行测定结果的相对标准偏差(RSD)为1.1%~3.2%,完全能够满足实际样品检测需求。方法简便快捷,灵敏度高,专属性强,可用于矛头蝮蛇蛇毒种属鉴别及svTLE含量测定,从源头保证血凝酶类产品的质量,并可为其他蛇毒类产品的质量控制提供参考。

O-028 Small extracellular vesicles (sEV) in peritoneal fluid and peripheral blood as biomarkers of endometriosis

Abstract Study question Can we identify lesion-derived endometriosis-specific sEV cargo in peritoneal fluid of women with endometriosis, and detect the same endometriosis-specific cargo in sEV from peripheral blood? Summary answer Endometriosis-specific sEV are present in PF. Identification in peripheral blood is challenging due to low abundance in comparison to blood-borne sEV. What is known already Endometriosis is characterised by intraperitoneal lesions of endometrial tissue. Although ultrasound detection of severe endometriosis is possible, the final diagnosis currently relies on invasive laparoscopy as the gold standard, which leads to a delay of 8-10 years after women first present to their GPs with symptoms. We have previously shown that the peritoneal fluid (PF) of women with endometriosis contains endometriosis-specific sEV. If these can be traced in blood samples, endometriosis-specific sEV could serve as biomarkers of endometriosis, particularly for stages I and II, which are difficult to detect by ultrasound. Study design, size, duration This is an observational pilot study of 29 patients in total. From March 2021 until August 2021, we collected PF samples from 11 controls and 16 endometriosis cases and blood samples from 12 controls and 11 endometriosis cases. Of these, 19 were paired samples (blood and PF from the same participant). Participants/materials, setting, methods Women &amp;gt;18 years of age undergoing laparoscopic surgery for endometriosis or unrelated conditions were invited to participate (HREC 08078B/HREC 10148B). Exclusion criteria were pregnancy, malignancy, and menopause. Purified, validated sEV were analysed by label based quantitative proteomics Tandem Mass Tag (TMT). Data analysis was performed using Proteome Discoverer v2.4 (Thermo Fisher), statistical analysis using the R (LIMMA), with a protein false discovery rate of 1% and a quantitative threshold of an adjusted p-value &amp;lt;0.05. Main results and the role of chance We ascertained the identity of sEV by TEM and NTA (mode size 121.8 ± 18.0 nm (blood, n = 5) and 155.9 ± 37.2 (PF, n = 6)), and signals for syntenin and ALIX in immunoblots as well as expression of CD9, CD63 and CD81 in capture bead-flow cytometry. Proteomics analysis identified 9145 proteins groups across all sample groups, of these proteins 5,429 are consistently quantifiable, with 602 significantly different between comparisons (adjusted P-value &amp;lt;0.05). PCA showed separation of samples by type rather than batch. Fractionated analysis by SPS-MS3 methodology identified 7064 protein groups, with 3408 proteins consistently quantified across sample groups. Of these, 602 were found to differ significantly across all comparisons. In PF, 533 proteins changed significantly in abundance (245 up and 288 down), while in blood, four proteins changed in abundance. Limitations, reasons for caution The main limitation of the study is in its small sample size, which meant that we could not stratify data according to endometriosis stage. Due to limited amount of protein within sEV samples, not all assays could be done on all samples. Wider implications of the findings Our findings suggest that our methodology makes it feasible to define a protein signature of endometriosis based on sEV cargoes drawn from blood samples. This would represent a non-invasive biomarker of endometriosis and could help diagnose the condition, or rule out endometriosis as the origin of symptoms in the future. Trial registration number not applicable

Protein Markers Related to Non-halal Slaughtering Process of Rat as Mammal Animal’s Model Detected Using Mass Spectrometry Proteome Analysis

Meat produced from non-halal slaughter is forbidden for Moslems. The slaughter methods contribute to the physiological response of animals expressed as different proteome profile. Proteome of two meat obtained from the halal and non-halal slaughter of Wistar rats (Rattus norvegicus) as an animal model was used to search for protein markers related to the slaughter method. The analysis employed Sodium Dodecyl Sulhate Polyacrylamide Gel Electrophoresis (SDS-PAGE), and High-Resolution Mass Spectrometer (HRMS) assisted with Label-Free Quantification (LFQ) Proteome Discoverer software. The non-halal slaughter contributed to the changes in protein expression in animal meat where thirteen proteins were up-regulated and three proteins were specifically identified in the non-halal slaughter, these three proteins are NSFL1 cofactor p47, transketolase, and Von Willebrand. There are three stable peptides identified of those three proteins, SYQDPSNAQFLESIR (m/z = 1755, z = +1) part of NSFL1 cofactor p47, LGQSDPAPLQHQVDVYQK (m/z = 2023, z = +1) part of transketolase, VPLLCTNGSVVHHEVINAMQCR (m/z = 2550, z = +1) part of Von Willebrand. Two of peptides can be targeted as markers in MRM mode LC-MS/MS routine analysis to authentication-halal slaughtering meat. The proposed MRM pair ions are 1755 to 1376, 1262, 1164, and 963, 2033 to 1355, 1016, and 762.

The Role of Testosterone in Spermatogenesis: Lessons From Proteome Profiling of Human Spermatozoa in Testosterone Deficiency.

Testosterone is essential to maintain qualitative spermatogenesis. Nonetheless, no studies have been yet performed in humans to analyze the testosterone-mediated expression of sperm proteins and their importance in reproduction. Thus, this study aimed to identify sperm protein alterations in male hypogonadism using proteomic profiling. We have performed a comparative proteomic analysis comparing sperm from fertile controls (a pool of 5 normogonadic normozoospermic fertile men) versus sperm from patients with secondary hypogonadism (a pool of 5 oligozoospermic hypogonadic patients due to isolated LH deficiency). Sperm protein composition was analyzed, after peptide labelling with Isobaric Tags, via liquid chromatography followed by tandem mass spectrometry (LC-MS/MS) on an LTQ Velos-Orbitrap mass spectrometer. LC-MS/MS data were analyzed using Proteome Discoverer. Criteria used to accept protein identification included a false discovery rate (FDR) of 1% and at least 1 peptide match per protein. Up to 986 proteins were identified and, of those, 43 proteins were differentially expressed: 32 proteins were under-expressed and 11 were over-expressed in the pool of hypogonadic patients compared to the controls. Bioinformatic analyses were performed using UniProt Knowledgebase, and the Gene Ontology Consortium database based on PANTHER. Notably, 13 of these 43 differentially expressed proteins have been previously reported to be related to sperm function and spermatogenesis. Western blot analyses for A-Kinase Anchoring Protein 3 (AKAP3) and the Prolactin Inducible Protein (PIP) were used to confirm the proteomics data. In summary, a high-resolution mass spectrometry-based proteomic approach was used for the first time to describe alterations of the sperm proteome in secondary male hypogonadism. Some of the differential sperm proteins described in this study, which include Prosaposin, SMOC-1, SERPINA5, SPANXB1, GSG1, ELSPBP1, fibronectin, 5-oxoprolinase, AKAP3, AKAP4, HYDIN, ROPN1B, ß-Microseminoprotein and Protein S100-A8, could represent new targets for the design of infertility treatments due to androgen deficiency.

Tear Proteomics of Children and Young Adult Soft Contact Lens, Orthokeratology and Spectacle Wearers – A Pilot Study

Purpose Contact lens complications occur more often in older teenagers and young adults compared to children. This study explored differences in tear proteomics between children and young adults wearing soft contact lens (SCL), orthokeratology or spectacles for >3 years. Methods Twelve children and 12 sex- and correction-matched young adults were enrolled. Tears were collected via Schirmer strips for tear proteomic analysis using mass spectrometry. Proteome Discoverer was used for protein identification. Label-Free Quantitation was generated using Scaffold software; Fisher’s Exact tests were used to compare proteins by age and correction groups. Generalized linear models were used to assess differences in overall protein levels by age and correction groups. A secondary analysis of proteins presented in >50% of samples of each group was conducted using the R/Bioconductor limma package. Results There were 385 proteins present only in young adults while 183 were unique in children. There were 528 unique proteins to SCL, 96 to orthokeratology and 149 to spectacle wearers. Based on Fisher’s Exact analyses, 126 proteins were higher in young adults than children (all P < 0.048). Forty-seven protein levels were higher in SCL compared to orthokeratology (all P < 0.01), 33 protein levels were higher in SCL compared to spectacles (all P < 0.01), 15 protein levels were higher in orthokeratology compared to spectacle wearers (all P < 0.01). Based on generalized linear models, young adults had higher overall protein levels than children (P = 0.001), SCL had higher protein levels than spectacle wearers (P < 0.001) but no differences were found between orthokeratology and spectacle wearers (P = 0.79). Based on the secondary analysis, only Antileukoproteinase was higher in the young adult orthokeratology group compared to other groups (P < 0.01). Conclusions Tear protein type and abundance differ by age and correction. Further research is needed to understand the effects of contact lens correction in children and young adults on the tear proteome.

Determination of Tropomyosin in Shrimp and Crab by Liquid Chromatography-Tandem Mass Spectrometry Based on Immunoaffinity Purification.

A UPLC-MS/MS method was developed for the detection of tropomyosin (TM) in shrimp and crab. After simple extraction, the samples were purified by immunoaffinity column and then digested by trypsin. The obtained sample was separated by Easy-nLC 1000-Q Exactive. The obtained spectrums were analyzed by Thermo Proteome Discoverer 1.4 software and then ANIQLVEK with high sensitivity was selected as the quantitative signature peptide. Isotope-labeled internal standard was used in the quantitative analysis. The method showed good linearity in the range of 5–5,000 μg/L with a limit of quantification (LOQ) of 0.1 mg/kg. The average recoveries were 77.22–95.66% with RSDs ≤ 9.97%, and the matrix effects were between 88.53 and 112.60%. This method could be used for rapid screening and quantitative analysis of TM in shrimp and crab. Thus, it could provide technical support for self-testing of TM by food manufacturers and promote further improvement of allergen labeling in China.

Label-free plasma proteomics for the identification of the putative biomarkers of oral squamous cell carcinoma

Mass spectrometry-based label-free proteomics is becoming the analytical tool of interest to identify and quantitate the biomarkers for cancer. The oral squamous cell carcinoma (OSCC) which is one of the leading cancers worldwide, lacks biomarkers for the early prognosis and diagnosis. The present study profiled plasma proteome of the Indian OSCC human patients using a label-free mass spectrometry proteomics approach. The study first time utilized the three most widely used data analysis software MaxQuant (MQ), Proteome discoverer (PD), and Trans proteomic pipeline (TPP) together for label-free quantitation of the proteins. The study identified 16 proteins which can be used as a signature protein panel for OSCC. The pathway analysis showed predominant involvement of the immune system, hemostasis as the major pathways that are indicative of the disease progression. The network analysis showed maximum interaction for the Fibronectin and C-reactive protein. The study demonstrates that plasma proteins contain signatures that can be used as putative biomarkers for OSCC. Based on the label-free quantitation and the mechanistic analysis C-reactive protein, Carbonic anhydrase-1, and Fibronectin are identified as putative biomarkers of OSCC. Once these findings are validated in the large cohorts these protein signatures can be used as a biomarker for OSCC. SignificanceThe oral squamous cell carcinoma (OSCC) is the eighteenth most prevalent malignancy in the world and ranks second in India. There are no biomarkers that could be indicative of the diseased state. Various studies have been carried out on saliva and tumors of OSCC patients in India, but none of the studies have profiled the plasma. We utilized the label-free approach for the first time on the Indian population in generating the panel of plasma proteins which could be indicative of the diseased state. The study identified Carbonic anhydrase 1, C-reactive protein, and Fibronectin proteins as putative biomarkers for the OSCC. The study obtained the signature panel by utilizing the 3 most widely used software for the label-free quanatitation (LFQ) namely MaxQuant, Proteome Discoverer, and Trans proteomic pipeline. The utilization of 3 software for the LFQ reduced the bias and provided a comprehensive list of proteins. All the differential proteins were mechanistically studied for their biological relevance and the pathway and network analysis were carried out. The study helps us in increasing the understanding of the proteins which are involved in the progression of the diseases. Studying the panel of proteins from all biofluids along with plasma in large cohorts of the population will help in understanding the disease in greater depth and help in identifying the relevant biomarkers for the OSCC.

Amelioration of rotenone-induced alterations in energy/redox system, stress response and cytoskeleton proteins by octanoic acid in zebrafish: A proteomic study.

Rotenone is used to generate Parkinson's disease (PD)-like symptoms in experimental animals. Octanoic acid (C8), is the principal fatty acid of medium-chain triglycerides in ketogenic diets. Beneficial effects of ketogenic diets were shown in PD. We applied proteomic methods to reveal the effects of octanoic acid in rotenone toxicity in zebrafish to gain information on the use of ketogenic diets in PD. Zebrafish were exposed to 5 μg/ml rotenone and octanoic acid (20and 60 mg/ml) for 30 days. LC-MS/MS analysis was performed. Raw files were analyzed by Proteome Discoverer 2.4 software, peptide lists were searched against Danio rerio proteins. STRING database was used for protein annotations or interactions. 2317 unique proteins were quantified, 302 proteins were differentially expressed. Proteins involved in cell organization, biogenesis, transport, response to stimulus were most frequently expressed. Our study is first to report that the alterations in the expressions of proteins related to energy and redox system, stress response, and cytoskeleton proteins caused by rotenone exposure were normalized by octanoic acid treatment in zebrafish.