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 ).     

A high yield multi-method extraction protocol for protein quantification in activated sludge

A multi-method extraction protocol based on mechanical, ionic and hydrophobic methods was investigated on two types of activated sludge samples. Extraction methods were chosen with regards to optimal protein yield without cell disruption. Sonication, EDTA and Tween extraction methods were selected and combined. The total amount of protein released by the multi-method protocol sums up to 191 and 264 mg equiv. BSA/g VSS for the two different sludge samples. Protocol repetition on the same sample showed that protein yield after each successive protocol fitted an exponential curve model. The total amount of extractable proteins was evaluated by model predictions, 423 and 516 mg equiv. BSA/g VSS for the two sludge samples. The multi-method extraction protocol appears relevant for harvesting a representative quantity of proteins from the original sample (45-49%), moreover the multi-method criterion of the protocol also offers a heterogeneous pool of proteins. Thus, further qualitative studies may not be biased by the extraction protocol.     

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 ).     

Phosphoproteome analysis of Lotus japonicus seeds

In this study, we report the first dataset of phosphoproteins of the seeds of a model plant, Lotus japonicus. This dataset might be useful in studying the regulatory mechanisms of seed germination in legume plants. By proteomic analysis of seeds following water absorption, we identified a total of 721 phosphopeptides derived from 343 phosphoproteins in cotyledons, and 931 phosphopeptides from 473 phosphoproteins in hypocotyls. Kinase‐specific prediction analyses revealed that different kinases were activated in cotyledons and hypocotyls. In particular, many peptides containing ATM‐kinase target motifs, X‐X‐pS/pT‐Q‐X‐X, were detected in cotyledons. Moreover, by real‐time RT‐PCR analysis, we found that expression of a homolog of ATM kinase is upregulated specifically in cotyledons, suggesting that this ATM‐kinase homolog plays a significant role in cell proliferation in the cotyledons of L. japonicus seeds. The data have been deposited to the ProteomeXchange with identifier PXD000053 ( http://proteomecentral.proteomexchange.org/dataset/PXD000053 ).     

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 ).     

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 ).     

Characterization of individual mouse cerebrospinal fluid proteomes

Analysis of cerebrospinal fluid (CSF) offers key insight into the status of the CNS. Characterization of murine CSF proteomes can provide a valuable resource for studying CNS injury and disease in animal models. However, the small volume of CSF in mice has thus far limited individual mouse proteome characterization. Through nonterminal CSF extractions in C57Bl/6 mice and high‐resolution 2D‐LC MS/MS analysis of individual murine samples, we report the most comprehensive proteome characterization of individual murine CSF to date. We identified a total of 566 unique proteins, including 128 proteins from three individual CSF samples that have been previously identified in brain tissue. Our methods and analysis provide a mechanism for individual murine CSF proteome analysis. The data are available in the ProteomeXchange with identifier PXD000248 ( http://proteomecentral.proteomexchange.org/dataset/PXD000248 ).     

Bacterial community analysis of activated sludge: an evaluation of four commonly used DNA extraction methods

The effectiveness of three commercially available direct DNA isolation kits (Mobio, Fast, Qiagen) and one published direct DNA extraction protocol (Bead) for extracting bacterial DNA from different types of activated sludge was investigated and mutually compared. The DNA quantity and purity were determined using real-time PCR targeting the bacterial 16S rDNA gene. Microbial community fingerprints were assessed by automated ribosomal intergenic spacer analysis. The resulting community profiles were analyzed with canonical correspondence analysis. Our results clearly demonstrate that direct DNA extraction methods can significantly influence the DNA quantity, purity, and observed community patterns of microbiota in activated sludge. Fast and Mobio generated high amounts of good quality DNA compared to Bead and Qiagen. Mobio also resulted in the detection of the highest number of species while Fast scored the best in discriminating between the community patterns of different activated sludge types. With respect to the characterization of community profiles, our analyses demonstrated a strong sludge type dependent variability among methods. Taking into account our results, we recommend Fast as the most suitable DNA extraction method for activated sludge samples used for bacterial community studies.     

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 ).     

Comparison of Bacterial Extracellular Polymer Extraction Methods

Five different bacterial extracellular polymer extraction methods and a combination of two of these methods were compared on cultures of activated sludge, synthetic activated sludge, and Klebsiella aerogenes. High-speed centrifugation was the most effective extraction method for the K. aerogenes culture, based on the comparatively small amount of cell disruption and the relatively high extracellular polymer yield. Steaming treatment was the most effective extraction method for the activated sludges, since it released a significant quantity of extracellular polymers from the flocs and caused less cellular disruption than ethylenediaminetetraacetic acid and sodium hydroxide treatments. Sodium hydroxide treatment caused extensive disruption in all cultures. Ultrasonication released low concentrations of extracellular polymers from all cultures. However, it caused no significant cell disruption and therefore may be useful as a preliminary treatment in conjunction with another extraction method.     

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 ).     

Copper stress‐induced changes in leaf soluble proteome of Cu‐sensitive and tolerant Agrostis capillaris L. populations

Changes in leaf soluble proteome were explored in 3‐month‐old plants of metallicolous (M) and nonmetallicolous (NM) Agrostis capillaris L. populations exposed to increasing Cu concentrations (1–50 μM) to investigate molecular mechanisms underlying plant responses to Cu excess and tolerance of M plants. Plants were cultivated on perlite (CuSO₄ spiked‐nutrient solution). Soluble proteins, extracted by the trichloroacetic acid/acetone procedure, were separated with 2‐DE (linear 4–7 pH gradient). Analysis of CCB‐stained gels (PDQuest) reproducibly detected 214 spots, and 64 proteins differentially expressed were identified using LC‐MS/MS. In both populations, Cu excess impacted both light‐dependent (OEE, cytochrome b6‐f complex, and chlorophyll a‐b binding protein), and ‐independent (RuBisCO) photosynthesis reactions, more intensively in NM leaves (ferredoxin‐NADP reductase and metalloprotease FTSH2). In both populations, upregulation of isocitrate dehydrogenase and cysteine/methionine synthases respectively suggested increased isocitrate oxidation and enhanced need for S‐containing amino‐acids, likely for chelation and detoxification. In NM leaves, an increasing need for energetic compounds was indicated by the stimulation of ATPases, glycolysis, pentose phosphate pathway, and Calvin cycle enzymes; impacts on protein metabolism and oxidative stress increase were respectively suggested by the rise of chaperones and redox enzymes. Overexpression of a HSP70 may be pivotal for M Cu tolerance by protecting protein metabolism. All MS data have been deposited in the ProteomeXchange with the dataset identifier PXD001930 ( http//proteomecentral.proteomexchange.org/dataset/PXD001930 ).     

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 ).     

EBprot: Statistical analysis of labeling‐based quantitative proteomics data

Labeling‐based proteomics is a powerful method for detection of differentially expressed proteins (DEPs). The current data analysis platform typically relies on protein‐level ratios, which is obtained by summarizing peptide‐level ratios for each protein. In shotgun proteomics, however, some proteins are quantified with more peptides than others, and this reproducibility information is not incorporated into the differential expression (DE) analysis. Here, we propose a novel probabilistic framework EBprot that directly models the peptide‐protein hierarchy and rewards the proteins with reproducible evidence of DE over multiple peptides. To evaluate its performance with known DE states, we conducted a simulation study to show that the peptide‐level analysis of EBprot provides better receiver‐operating characteristic and more accurate estimation of the false discovery rates than the methods based on protein‐level ratios. We also demonstrate superior classification performance of peptide‐level EBprot analysis in a spike‐in dataset. To illustrate the wide applicability of EBprot in different experimental designs, we applied EBprot to a dataset for lung cancer subtype analysis with biological replicates and another dataset for time course phosphoproteome analysis of EGF‐stimulated HeLa cells with multiplexed labeling. Through these examples, we show that the peptide‐level analysis of EBprot is a robust alternative to the existing statistical methods for the DE analysis of labeling‐based quantitative datasets. The software suite is freely available on the Sourceforge website http://ebprot.sourceforge.net/ . All MS data have been deposited in the ProteomeXchange with identifier PXD001426 ( http://proteomecentral.proteomexchange.org/dataset/PXD001426/ ).     

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 ).     

Protein identification and quantification from riverbank grape,Vitis riparia: Comparing SDS‐PAGE and FASP‐GPF techniques for shotgun proteomic analysis

Protein sample preparation optimisation is critical for establishing reproducible high throughput proteomic analysis. In this study, two different fractionation sample preparation techniques (in‐gel digestion and in‐solution digestion) for shotgun proteomics were used to quantitatively compare proteins identified in Vitis riparia leaf samples. The total number of proteins and peptides identified were compared between filter aided sample preparation (FASP) coupled with gas phase fractionation (GPF) and SDS‐PAGE methods. There was a 24% increase in the total number of reproducibly identified proteins when FASP‐GPF was used. FASP‐GPF is more reproducible, less expensive and a better method than SDS‐PAGE for shotgun proteomics of grapevine samples as it significantly increases protein identification across biological replicates. Total peptide and protein information from the two fractionation techniques is available in PRIDE with the identifier PXD001399 ( http://proteomecentral.proteomexchange.org/dataset/PXD001399 ).     

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 ).     

DNA Extraction from Activated Sludges

To optimize the cell lysis step for DNA extraction from activated sludge samples, two floc dispersion methods (sonication versus stirring with a cation exchange resin), and three cell lysis treatments (lysozyme + SDS, sonication in a water bath, and thermal shock) were tested. For dispersion, stirring with cation exchange resin was more efficient than sonication. The cell lysis procedures were applied in two sequences, and DNA was quantified after each cell lysis treatment. Lysozyme + SDS was the most effective step in the cell lysis procedures. The cell lysis treatment sequences giving the highest DNA yields were not the same for all the sludges. The differences in sludge microbial compositions and floc structures required specifically adapted cell lysis protocols. The proposed protocols were highly efficient for DNA extraction, yielding about 50 mg DNA g⁻¹ volatile suspended solids, and allowed PCR amplification of 16S rDNA. Received: 26 September 1998 / Accepted: 13 February 1999     

Compartment resolved reference proteome map from highly purified naïve,activated, effector,and memory CD8+ murine immune cells

Differentiation of CD8⁺ T lymphocytes into effector and memory cells is key for an adequate immune response and relies on complex interplay of pathways that convey signals from the cell surface to the nucleus. In this study, we investigated the proteome of four cytotoxic T‐cell subtypes; naïve, recently activated effector, effector, and memory cells. Cells were fractionated into membrane, cytosol, soluble nuclear, chromatin‐bound, and cytoskeletal compartments. Following LC‐MS/MS analysis, identified peptides were analyzed via MaxQuant. Compartment fractionation and gel‐LC‐MS separation resulted in 2399 proteins identified in total. Comparison between the different subsets resulted in 146 significantly regulated proteins for naïve and effector cells, followed by 116 for activated, and 55 for memory cells. Besides Granzyme B signaling (for activated and/ or effector cells vs. naïve cells), the most prominent changes occurred in the TCA cycle and aspartate degradation. These changes suggest that correct balancing of metabolism is key for differentiation processes. All MS data have been deposited in the ProteomeXchange with identifier PXD001065 ( http://proteomecentral.proteomexchange.org/dataset/PXD001065 ).