Qualitative and quantitative analysis of the adult Drosophila melanogaster proteome

Drosophila melanogaster is one of the most widely used model organisms in life sciences. Mapping its proteome is of great significance for understanding the biological characteristics and tissue functions of this species. However, the comprehensive coverage of its proteome remains a challenge. Here, we describe a high‐coverage analysis of whole fly through a 1D gel electrophoresis and LC‐MS/MS approach. By combining the datasets of two types of SDS‐PAGE and two kinds of tagmata, the high‐coverage analysis resulted in the identification of 5262 genes, which correspond to 38.23% of the entire coding genes. Moreover, we found that the fly head and body have different molecular weight distributions of their proteomes when the proteins were resolved with SDS‐PAGE and image analysis of the stained gel. This phenomenon was further confirmed by both label‐free and isobaric tags for relative and absolute quantitation‐based quantitative approaches. The consistent results of the two different quantitation methods also demonstrated the stability and accuracy of the LC‐MS/MS platform. The MS proteomics data have been deposited to the ProteomeXchange with identifiers PXD000454 and PXD000455 ( http://proteomecentral.proteomexchange.org/dataset/PXD000454 ; ( http://proteomecentral.proteomexchange.org/dataset/PXD000455 ).     

Quantitative proteomic analysis of cabernet sauvignon grape cells exposed to thermal stresses reveals alterations in sugar and phenylpropanoid metabolism

Grapes (Vitis vinifera) are a valuable fruit crop and wine production is a major industry. Global warming and expanded range of cultivation will expose grapes to more temperature stresses in future. Our study investigated protein level responses to abiotic stresses, with particular reference to proteomic changes induced by the impact of four different temperature stress regimes, including both hot and cold temperatures, on cultured grape cells. Cabernet Sauvignon cell suspension cultures grown at 26°C were subjected to 14 h of exposure to 34 and 42°C for heat stress, and 18 and 10°C for cold stress. Cells from the five temperatures were harvested in biological triplicates and label‐free quantitative shotgun proteomic analysis was performed. A total of 2042 non‐redundant proteins were identified from the five temperature points. Fifty‐five proteins were only detected in extreme heat stress conditions (42°C) and 53 proteins were only detected at extreme cold stress conditions (10°C). Gene Ontology (GO) annotations of differentially expressed proteins provided insights into the metabolic pathways that are involved in temperature stress in grape cells. Sugar metabolism displayed switching between alternative and classical pathways during temperature stresses. Additionally, nine proteins involved in the phenylpropanoid pathway were greatly increased in abundance at extreme cold stress, and were thus found to be cold‐responsive proteins. All MS data have been deposited in the ProteomeXchange with identifier PXD000977 ( http://proteomecentral.proteomexchange.org/dataset/PXD000977 ).     

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 ).     

Absolute protein quantification allows differentiation of cell‐specific metabolic routes and functions

Total protein approach (TPA) is a proteomic method that allows calculation of concentrations of individual proteins and groups of functionally related proteins in any protein mixture without spike‐in standards. Using the two‐step digestion–filter‐aided sample preparation method and LC‐MS/MS analysis, we generated comprehensive quantitative datasets of mouse intestinal mucosa, liver, red muscle fibers, brain, and of human plasma, erythrocytes, and tumor cells lines. We show that the TPA‐based quantitative data reflect well‐defined and specific physiological functions of different organs and cells, for example nutrient absorption and transport in intestine, amino acid catabolism and bile secretion in liver, and contraction of muscle fibers. Focusing on key metabolic processes, we compared metabolic capacities in different tissues and cells. In addition, we demonstrate quantitative differences in the mitochondrial proteomes. Providing insight into the abundances of mitochondrial metabolite transporters, we demonstrate that their titers are well tuned to cell‐specific metabolic requirements. This study provides for the first time a comprehensive overview of the protein hardware mediating metabolism in different mammalian organs and cells. The presented approach can be applied to any other system to study biological processes. All MS data have been deposited in the ProteomeXchange with identifier PXD001352 ( http://proteomecentral.proteomexchange.org/dataset/PXD001352 ).     

In‐depth characterization of the secretome of mouse CNS cell lines by LC‐MS/MS without prefractionation

Microglia, astrocytes, and neurons, which have important functions in the central nervous system (CNS), communicate mutually to generate a signal through secreted proteins or small molecules, but many of which have not been identified. Because establishing a reference for the secreted proteins from CNS cells could be invaluable in examining cell‐to‐cell communication in the brain, we analyzed the secretome of three murine CNS cell lines without prefractionation by high‐resolution mass spectrometry. In this study, 2795 proteins were identified from conditioned media of the three cell lines, and 2125 proteins were annotated as secreted proteins by bioinformatics analysis. Further, approximately 500 secreted proteins were quantifiable as differentially expressed proteins by label‐free quantitation. As a result, our secretome references are useful datasets for the future study of neuronal diseases. All MS data have been deposited in the ProteomeXchange with identifier PXD001597 ( http://proteomecentral.proteomexchange.org/dataset/PXD001597 ).     

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 ).     

LC-MS/MS based proteomic analysis and functional inference of hypothetical proteins in Desulfovibrio vulgaris

High efficiency capillary liquid chromatography-tandem mass spectrometry (LC-MS/MS) was used to examine the proteins extracted from Desulfovibrio vulgaris cells across six treatment conditions. While our previous study provided a proteomic overview of the cellular metabolism based on proteins with known functions [W. Zhang, M.A. Gritsenko, R.J. Moore, D.E. Culley, L. Nie, K. Petritis, E.F. Strittmatter, D.G. Camp II, R.D. Smith, F.J. Brockman, A proteomic view of the metabolism in Desulfovibrio vulgaris determined by liquid chromatography coupled with tandem mass spectrometry, Proteomics 6 (2006) 4286-4299], this study describes the global detection and functional inference for hypothetical D. vulgaris proteins. Using criteria that a given peptide of a protein is identified from at least two out of three independent LC-MS/MS measurements and that for any protein at least two different peptides are identified among the three measurements, 129 open reading frames (ORFs) originally annotated as hypothetical proteins were found to encode expressed proteins. Functional inference for the conserved hypothetical proteins was performed by a combination of several non-homology based methods: genomic context analysis, phylogenomic profiling, and analysis of a combination of experimental information, including peptide detection in cells grown under specific culture conditions and cellular location of the proteins. Using this approach we were able to assign possible functions to 20 conserved hypothetical proteins. This study demonstrated that a combination of proteomics and bioinformatics methodologies can provide verification of the expression of hypothetical proteins and improve genome annotation.     

Comprehensive Map of the Artemisia annua Proteome and Quantification of Differential Protein Expression in Chemotypes Producing High versus Low Content of Artemisinin

Artemisia annua is well known for biosynthesizing the antimalarial drug artemisinin. Here, a global proteomic profiling of A. annua is conducted with identification of a total of 13 403 proteins based on the genome sequence annotation database. Furthermore, a spectral library is generated to perform quantitative proteomic analysis using data independent acquisition mass spectrometry. Specifically, proteins between two chemotypes that produce high (HAP) and low (LAP) artemisinin content, respectively, are comprehensively quantified and compared. 182 proteins are identified with abundance significantly different between these two chemotypes means after the statistic use the p‐value and fold change it is found 182 proteins can reach the demand conditions which represent the expression are significantly different between the high artemisnin content plants (HAPs) and the low artemisnin content plants (LAPs). Data are available via ProteomeXchange with identifier PXD015547. Overall, this current study globally identifies the proteome of A. annua and quantitatively compares the targeted sub‐proteomes between the two cultivars of HAP and LAP, providing systematic information on metabolic pathways of A. annua.     

A large‐scale proteogenomics study of apicomplexan pathogens—Toxoplasma gondii and Neospora caninum

Proteomics data can supplement genome annotation efforts, for example being used to confirm gene models or correct gene annotation errors. Here, we present a large‐scale proteogenomics study of two important apicomplexan pathogens: Toxoplasma gondii and Neospora caninum. We queried proteomics data against a panel of official and alternate gene models generated directly from RNASeq data, using several newly generated and some previously published MS datasets for this meta‐analysis. We identified a total of 201 996 and 39 953 peptide‐spectrum matches for T. gondii and N. caninum, respectively, at a 1% peptide FDR threshold. This equated to the identification of 30 494 distinct peptide sequences and 2921 proteins (matches to official gene models) for T. gondii, and 8911 peptides/1273 proteins for N. caninum following stringent protein‐level thresholding. We have also identified 289 and 140 loci for T. gondii and N. caninum, respectively, which mapped to RNA‐Seq‐derived gene models used in our analysis and apparently absent from the official annotation (release 10 from EuPathDB) of these species. We present several examples in our study where the RNA‐Seq evidence can help in correction of the current gene model and can help in discovery of potential new genes. The findings of this study have been integrated into the EuPathDB. The data have been deposited to the ProteomeXchange with identifiers PXD000297and PXD000298.     

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.     

Proteogenomics and systems biology: quest for the ultimate missing parts

This review describes how intimately proteogenomics and system biology are imbricated. Quantitative cell-wide monitoring of cellular processes and the analysis of this information is the basis for systems biology. Establishing the most comprehensive protein-parts list is an essential prerequisite prior to analysis of the cell-wide dynamics of proteins, their post-translational modifications, their complex network interactions and interpretation of these data as a whole. High-quality genome annotation is, thus, a crucial basis. Proteogenomics consists of high-throughput identification and characterization of proteins by extra-large shotgun MS/MS approaches and the integration of these data with genomic data. Discovery of the remaining unannotated genes, defining translational start sites, listing signal peptide processing events and post-translational modifications, are tasks that can currently be carried out at a full-genomic scale as soon as the genomic sequence is available. Proteomics is increasingly being used at the primary stage of genome annotation and such an approach may become standard in the near future for genome projects. Advantageously, the same experimental proteomic datasets may be used to characterize the specific metabolic traits of the organism under study. Undoubtedly, comparative genomics will experience a renaissance taking into account this new dimension. Synthetic biology aimed at re-engineering living systems will also benefit from these significant progresses.     

Analysis of the proteins associated with platelet detergent resistant membranes

Proteomic studies have facilitated the identification of proteins associated with the detergent‐resistant membrane (DRM) fraction in a variety of cell types. Here, we have undertaken label‐free quantitative (LFQ) proteomic profiling of the proteins associated with detergent‐resistant plasma and internal membranes from resting and activated platelets. One hundred forty‐one proteins were identified and raw data is available via ProteomeXchange with identifier PXD002554. The proteins identified include a myriad of important platelet signaling and trafficking proteins including Rap1b, Src, SNAP‐23, syntaxin‐11, and members of the previously unattributed Ragulator complex. Mean LFQ intensities calculated across three technical replicates for the three biological donors revealed that several important platelet signaling proteins altered their detergent solubility upon activation, including GPIbα, GPIbβ, Src, and 14‐3‐3ζ. Altered detergent solubility for GPIbα, following activation using a variety of platelet agonists, was confirmed by immunoblotting and further coimmunoprecipitation experiments revealed that GPIbα forms a complex with 14‐3‐3ζ that shifts into DRMs following activation. Taken together, proteomic profiling of platelet DRMs allowed greater insight in the complex biology of both DRMs and platelets and will be a useful subproteome to study platelet‐related disease. All MS data have been deposited in the ProteomeXchange with identifier PXD002554 ( http://proteomecentral.proteomexchange.org/dataset/PXD002554 ).     

Proteomic profiling of the mitochondrial inner membrane of rat renal proximal convoluted tubules

The proximal convoluted tubule is the primary site of renal fluid, electrolyte, and nutrient reabsorption, processes that consume large amounts of adenosine‐5′‐triphosphate. Previous proteomic studies have profiled the adaptions that occur in this segment of the nephron in response to the onset of metabolic acidosis. To extend this analysis, a proteomic workflow was developed to characterize the proteome of the mitochondrial inner membrane of the rat renal proximal convoluted tubule. Separation by LC coupled with analysis by MS/MS (LC‐MS/MS) confidently identified 206 proteins in the combined samples. Further proteomic analysis identified 14 peptides that contain an N‐?‐acetyl‐lysine, seven of which are novel sites. This study provides the first proteomic profile of the mitochondrial inner membrane proteome of this segment of the rat renal nephron. The MS data have been deposited in the ProteomeXchange with the identifier PXD000121.     

Characterization of the Proteome of Theobroma cacao Beans by Nano‐UHPLC‐ESI MS/MS

Cocoa seed storage proteins play an important role in flavour development as aroma precursors are formed from their degradation during fermentation. Major proteins in the beans of Theobroma cacao are the storage proteins belonging to the vicilin and albumin classes. Although both these classes of proteins have been extensively characterized, there is still limited information on the expression and abundance of other proteins present in cocoa beans. This work is the first attempt to characterize the whole cocoa bean proteome by nano‐UHPLC‐ESI MS/MS analysis using tryptic digests of cocoa bean protein extracts. The results of this analysis show that >1000 proteins could be identified using a species‐specific Theobroma cacao database. The majority of the identified proteins were involved with metabolism and energy. Additionally, a significant number of the identified proteins were linked to protein synthesis and processing. Several proteins were also involved with plant response to stress conditions and defence. Albumin and vicilin storage proteins showed the highest intensity values among all detected proteins, although only seven entries were identified as storage proteins. A comparison of MS/MS data searches carried out against larger non‐specific databases confirmed that using a species‐specific database can increase the number of identified proteins, and at the same time reduce the number of false positives. The results of this work will be useful in developing tools that can allow the comparison of the proteomic profile of cocoa beans from different genotypes and geographic origins. Data are available via ProteomeXchange with identifier PXD005586.     

Quantitative Analysis of the Global Proteome in Peripheral Blood Mononuclear Cells from Patients with New‐Onset Psoriasis

Psoriasis is a common chronic autoimmune skin disease involving the activation of T cells. To explore the proteomic signature of peripheral blood mononuclear cells, a quantitative analysis of their global proteome was conducted in samples from Chinese patients with new‐onset psoriasis (n = 31) and healthy controls (n = 32) using an integrated quantitative approach with tandem mass tag labeling and LC–MS/MS. Protein annotation, unsupervised hierarchical clustering, functional classification, functional enrichment and cluster, and protein–protein interaction analyses were performed. A total of 5178 proteins were identified, of which 4404 proteins were quantified. The fold‐change cutoff was set at 1.2 (patients vs controls); 335 proteins were upregulated, and 107 proteins were downregulated. The bioinformatics analysis indicated that the differentially expressed proteins were involved in processes related to the activation of immune cells including the nuclear factor kappa‐light‐chain‐enhancer of activated B cells (NF‐κB) pathway, cellular energy metabolism, and proliferation. Three upregulated proteins and two phosphorylated proteins in the NF‐κB pathway were verified or identified by Western blotting. These results confirm that the NF‐κB pathway is critical to psoriasis. In addition, many differentially expressed proteins identified in this study have never before been associated with psoriasis, and further studies on these proteins are necessary.     

Updating the proteome of the uncultivable hemotrophic Mycoplasma suis in experimentally infected pigs

Mycoplasma suis belongs to the hemotrophic mycoplasmas that are associated with acute and chronic anemia in a wide range of livestock and wild animals. The inability to culture M. suis in vitro has hindered its characterization at the molecular level. Since the publication of M. suis genome sequences in 2011 only one proteome study has been published. Aim of the presented study was to significantly extend the proteome coverage of M. suis strain KI_3806 during acute infection by applying three different protein extraction methods followed by 1D SDS‐PAGE and LC‐MS/MS. A total of 404 of 795 M. suis KI_3806 proteins (50.8%) were identified. Data analysis revealed the expression of 83.7% of the predicted ORFs with assigned functions but also highlights the expression of 179 of 523 (34.2%) hypothetical proteins with unknown functions. Computational analyses identified expressed membrane‐associated hypothetical proteins that might be involved in adhesion or host–pathogen interaction. Furthermore, analyses of the expressed proteins indicated the existence of a hexose‐6‐phosphate‐transporter and an ECF transporter. In conclusion, our proteome study provides a further step toward the elucidation of the unique life cycle of M. suis and the establishment of an in vitro culture. All MS data have been deposited in the ProteomeXchange with identifier PXD002294 ( http://proteomecentral.proteomexchange.org/dataset/PXD002294 ).