Proteomic profiles of human lung adeno and squamous cell carcinoma using super‐SILAC and label‐free quantification approaches

Nonsmall cell lung cancer (NSCLC) accounts for 85% of lung cancers, and is subdivided into two major histological subtypes: adenocarcinoma (ADC) and squamous cell carcinoma (SCC). There is an unmet need to further subdivide NSCLC according to distinctive molecular features that may be associated with responsiveness to therapies. Four primary tumor‐derived xenograft proteomes (two‐each ADC and SCC) were quantitatively compared by using a super‐SILAC labeling approach together with ultrahigh‐resolution MS. Proteins highly differentially expressed in the two subtypes were identified, including 30 that were validated in an independent cohort of 12 NSCLC primary tumor‐derived xenograft tumors whose proteomes were quantified by an alternative, label‐free shotgun MS methodology. The 30‐protein signature contains metabolism enzymes including phosphoglycerate dehydrogenase, which is more highly expressed in SCC, as well as a comprehensive set of cytokeratins and other components of the epithelial barrier, which is therefore distinctly different between ADC and SCC. These results demonstrate the utility of the super‐SILAC method for the characterization of primary tissues, and compatibility with datasets derived from different MS‐based platforms. The validation of proteome signatures of NSCLC subtypes supports the further development and application of MS‐based quantitative proteomics as a basis for precision classifications and treatments of tumors. All MS data have been deposited in the ProteomeXchange with identifier PXD000438 ( http://proteomecentral.proteomexchange.org/dataset/PXD000438 ).     

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 ).     

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 ).     

In‐depth protein profiling of the postsynaptic density from mouse hippocampus using data‐independent acquisition proteomics

Located at neuronal terminals, the postsynaptic density (PSD) is a highly complex network of cytoskeletal scaffolding and signaling proteins responsible for the transduction and modulation of glutamatergic signaling between neurons. Using ion‐mobility enhanced data‐independent label‐free LC‐MS/MS, we established a reference proteome of crude synaptosomes, synaptic junctions, and PSD derived from mouse hippocampus including TOP3‐based absolute quantification values for identified proteins. The final dataset across all fractions comprised 49 491 peptides corresponding to 4558 protein groups. Of these, 2102 protein groups were identified in highly purified PSD in at least two biological replicates. Identified proteins play pivotal roles in neurological and synaptic processes providing a rich resource for studies on hippocampal PSD function as well as on the pathogenesis of neuropsychiatric disorders. All MS data have been deposited in the ProteomeXchange with identifier PXD000590 ( http://proteomecentral.proteomexchange.org/dataset/PXD000590 ).     

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 analysis of livers from fat‐fed mice deficient in either PKCδ or PKCε identifies Htatip2 as a regulator of lipid metabolism

Insulin resistance contributes to the development of Type 2 diabetes, and is associated with lipid oversupply. Deletion of isoforms of the lipid‐activated protein kinase C (PKC) family, PKCδ or PKCε, improves insulin action in fat‐fed mice, but differentially affects hepatic lipid metabolism. To investigate the mechanisms involved, we employed an in vivo adaptation of SILAC to examine the effects of a fat diet together with deletion of PKCδ or PKCε on the expression of liver proteins. We identified a total of 3359 and 3488 proteins from the PKCδ and PKCε knockout study groups, respectively, and showed that several enzymes of lipid metabolism were affected by the fat diet. In fat‐fed mice, 23 proteins showed changes upon PKCδ deletion while 19 proteins were affected by PKCε deletion. Enzymes of retinol metabolism were affected by the absence of either PKC. Pathway analysis indicated that monosaccharide metabolism was affected only upon PKCδ deletion, while isoprenoid biosynthesis was affected in a PKCε‐specific manner. Certain proteins were regulated inversely, including HIV‐1 tat interactive protein 2 (Htatip2). Overexpression or knockdown of Htatip2 in hepatocytes affected fatty acid storage and oxidation, consistent with a novel role in mediating the differential effects of PKC isoforms on lipid metabolism. All MS data have been deposited in the ProteomeXchange with identifier PXD000971 ( http://proteomecentral.proteomexchange.org/dataset/PXD000971 ).     

Reference proteome of highly purified human Th1 cells reveals strong effects on metabolism and protein ubiquitination upon differentiation

The differentiation of human CD4⁺ T cells into T helper cell subtypes and regulatory T cells is crucial to the immune response. Among subtypes, Th1 cells are dominant, representing approximately 50% of all lymphocytes. Thus far, most global proteomic studies have used only partially purified T helper cell subpopulations and/or have employed artificial protocols for inducing specific T helper cell subtypes and/or used gel‐based approaches. These studies have shed light on molecular details of certain aspects of the proteome; nevertheless a global analysis of high purity primary naïve and Th1 cells by LC‐MS/MS is required to provide a reference dataset for proteome‐based T cell subtype characterization. The utilization of highly purified Th1 cells for a global proteome assessment and the bioinformatic comparison to naïve cells reveals changes in cell metabolism and the ubiquitination pathway upon T cell differentiation. All MS data have been deposited in the ProteomeXchange with identifier PXD001066 ( http://proteomecentral.proteomexchange.org/dataset/PXD001066 ).     

Distinct serum proteome profiles associated with collagen‐induced arthritis and complete Freund's adjuvant‐induced inflammation in CD38−/− mice: The discriminative power of protein species or proteoforms

Collagen‐type‐II‐induced arthritis (CIA) is an autoimmune disease, which involves a complex host systemic response including inflammatory and autoimmune reactions. CIA is milder in CD38^?/? than in wild‐type (WT) mice. ProteoMiner‐equalized serum samples were subjected to 2D‐DiGE and MS‐MALDI‐TOF/TOF analyses to identify proteins that changed in their relative abundances in CD38^?/? versus WT mice either with arthritis (CIA⁺), with no arthritis (CIA^?), or with inflammation (complete Freund's adjuvant (CFA)‐treated mice). Multivariate analyses revealed that a multiprotein signature (n = 28) was able to discriminate CIA⁺ from CIA^? mice, and WT from CD38^?/? mice within each condition. Likewise, a distinct multiprotein signature (n = 16) was identified which differentiated CIA⁺ CD38^?/? mice from CIA⁺ WT mice, and lastly, a third multiprotein signature (n = 18) indicated that CD38^?/? and WT mice could be segregated in response to CFA treatment. Further analyses showed that the discriminative power to distinguish these groups was reached at protein species level and not at the protein level. Hence, the need to identify and quantify proteins at protein species level to better correlate proteome changes with disease processes. It is crucial for plasma proteomics at the low‐abundance protein species level to apply the ProteoMiner enrichment. All MS data have been deposited in the ProteomeXchange with identifiers PXD001788, PXD001799 and PXD002071 ( http://proteomecentral.proteomexchange.org/dataset/PXD001788 , http://proteomecentral.proteomexchange.org/dataset/PXD001799 and http://proteomecentral.proteomexchange.org/dataset/PXD002071 ).     

Differential accumulation of soluble proteins in roots of metallicolous and nonmetallicolous populations of Agrostis capillaris L. exposed to Cu

Differential expression of soluble proteins was explored in roots of metallicolous (M) and non‐M (NM) plants of Agrostis capillaris L. exposed to increasing Cu to partially identify molecular mechanisms underlying higher Cu tolerance in M plants. Plants were cultivated for 2 months on perlite with a CuSO₄ (1–30 μM) spiked‐nutrient solution. Soluble proteins extracted by the trichloroacetic acid/acetone procedure were separated with 2DE (linear 4–7 pH gradient). After Coomassie Blue staining and image analysis, 19 proteins differentially expressed were identified using LC‐MS/MS and Expressed Sequence Tag (ESTs) databases. At supra‐optimal Cu exposure (15–30 μM), glycolysis was likely altered in NM roots with increased production of glycerone‐P and methylglyoxal based on overexpression of triosephosphate isomerase and fructose bisphosphate aldolase. Changes in tubulins and higher expressions of 5‐methyltetrahydropteroyltriglutamatehomocysteine methyltransferase and S‐adenosylmethionine synthase underpinned impacts on the cytoskeleton and stimulation of ethylene metabolism. Increased l ‐methionine and S‐adenosylmethionine amounts may also facilitate production of nicotianamine, which complexes Cu, and of l ‐cysteine, needed for metallothioneins and GSH. In M roots, the increase of [Cu/Zn] superoxide dismutase suggested a better detoxification of superoxide, when Cu exposure rose. Higher Cu‐tolerance of M plants would rather result from simultaneous cooperation of various processes than from a specific mechanism.     

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.     

Quantitative proteomics suggests metabolic reprogramming during ETHE1 deficiency

Deficiency of mitochondrial sulfur dioxygenase (ETHE1) causes the severe metabolic disorder ethylmalonic encephalopathy, which is characterized by early‐onset encephalopathy and defective cytochrome C oxidase because of hydrogen sulfide accumulation. Although the severe systemic consequences of the disorder are becoming clear, the molecular effects are not well defined. Therefore, for further elucidating the effects of ETHE1‐deficiency, we performed a large scale quantitative proteomics study on liver tissue from ETHE1‐deficient mice. Our results demonstrated a clear link between ETHE1‐deficiency and redox active proteins, as reflected by downregulation of several proteins related to oxidation‐reduction, such as different dehydrogenases and cytochrome P450 (CYP450) members. Furthermore, the protein data indicated impact of the ETHE1‐deficiency on metabolic reprogramming through upregulation of glycolytic enzymes and by altering several heterogeneous ribonucleoproteins, indicating novel link between ETHE1 and gene expression regulation. We also found increase in total protein acetylation level, pointing out the link between ETHE1 and acetylation, which is likely controlled by both redox state and cellular metabolites. These findings are relevant for understanding the complexity of the disease and may shed light on important functions influenced by ETHE1 deficiency and by the concomitant increase in the gaseous mediator hydrogen sulfide. All MS data have been deposited in the ProteomeXchange with the dataset identifiers PXD002741 ( http://proteomecentral.proteomexchange.org/dataset/PXD002741 ) and PXD002742 ( http://proteomecentral.proteomexchange.org/dataset/PXD002741 ).     

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 ).     

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 ).     

Comparative proteome profiling of bovine and human Staphylococcus epidermidis strains for screening specifically expressed virulence and adaptation proteins

The present study reports a comparative proteome cataloging of a bovine mastitis and a human‐associated Staphylococcus epidermidis strain with a specific focus on surfome (cell‐wall bound and extracellular) proteins. Protein identification by 1DE coupled with LC‐MS/MS analyses resulted in 1400 and 1287 proteins from the bovine (PM221) and human (ATCC12228) strains, respectively, covering over 50% of all predicted and more than 30% of all predicted surfome proteins in both strains. Comparison of the identification results suggests elevated levels of proteins involved in adherence, biofilm formation, signal transduction, house‐keeping functions, and immune evasion in PM221, whereas ATCC12228 was more effective in expressing host defense evasion proteases, skin adaptation lipases, hemagglutination, and heavy‐metal resistance proteins. Phenotypic analyses showed that only PM221 displays protein‐ and DNA‐mediated adherent growth, and that PM221 was more efficient in cleaving tributyrin, a natural compound of milk fat under low CO₂ conditions. These findings are in line with the identification data and suggest that distinct expression of lipases and adhesive surfome proteins could lead to the observed phenotypes. This study is the first extensive survey of S. epidermidis proteomes to date, providing several protein candidates to be examined for their roles in adaptation and virulence in vivo. All MS data have been deposited in the ProteomeXchange with identifier PXD000404 ( http://proteomecentral.proteomexchange.org/dataset/PXD000404 ).     

An iTRAQ characterisation of the role of TolC during electron transfer from Shewanella oneidensis MR‐1

Anodophilic bacteria have the ability to generate electricity in microbial fuel cells (MFCs) by extracellular electron transfer to the anode. We investigated the anode‐specific responses of Shewanella oneidensis MR‐1, an exoelectroactive Gammaproteobacterium, using for the first time iTRAQ and 2D‐LC MS/MS driven membrane proteomics to compare protein abundances in S. oneidensis when generating power in MFCs, and growing in a continuous culture. The regulated dataset produced was enriched in membrane proteins. Proteins shown to be more abundant in anaerobic electroactive anodic cells included efflux pump TolC and an uncharacterised tetratricopeptide repeat (TPR) protein, whilst the TonB2 system and associated uncharacterised proteins such as TtpC2 and DUF3450 were more abundant in microaerobic planktonic cells. In order to validate the iTRAQ data, the functional role for TolC was examined using a δTolC knockout mutant of S. oneidensis. Possible roles for the uncharacterised proteins were identified using comparative bioinformatics. We demonstrate that employing an insoluble extracellular electron acceptor requires multiple proteins involved in cell surface properties. All MS and processed data are available via ProteomeXchange with identifier PXD004090.     

Proteomics analysis of rough endoplasmic reticulum in pancreatic beta cells

Pancreatic beta cells have well‐developed ER to accommodate for the massive production and secretion of insulin. ER homeostasis is vital for normal beta cell function. Perturbation of ER homeostasis contributes to beta cell dysfunction in both type 1 and type 2 diabetes. To systematically identify the molecular machinery responsible for proinsulin biogenesis and maintenance of beta cell ER homeostasis, a widely used mouse pancreatic beta cell line, MIN6 cell was used to purify rough ER. Two different purification schemes were utilized. In each experiment, the ER pellets were solubilized and analyzed by 1D SDS‐PAGE coupled with HPLC‐MS/MS. A total of 1467 proteins were identified in three experiments with ≥95% confidence, among which 1117 proteins were found in at least two separate experiments and 737 proteins found in all three experiments. GO analysis revealed a comprehensive profile of known and novel players responsible for proinsulin biogenesis and ER homeostasis. Further bioinformatics analysis also identified potential beta cell specific ER proteins as well as ER proteins present in the risk genetic loci of type 2 diabetes. This dataset defines a molecular environment in the ER for proinsulin synthesis, folding and export and laid a solid foundation for further characterizations of altered ER homeostasis under diabetes‐causing conditions. All MS data have been deposited in the ProteomeXchange with identifier PXD001081 ( http://proteomecentral.proteomexchange.org/dataset/PXD001081 ).