Quantitative Proteomic Analysis of Brucella abortus under Multiple Environmental Stresses
ABSTRACT: We have used a multiple-environmental-stress strategy to reveal global metabolic adaptations of B. abortus to intravacuolar environmental conditions. These conditions included: (i) a Control condition (growth on TSB, condition #1); (ii) seven single-stress conditions: (condition #2-8) and (iii) a multi-stress condition (#9). The multi-stress was a combination of each single-stress that may better simulated the environments that Brucella may occur during the infection of a host. The proteomic analysis identified and quantified in total 2,272 proteins and 74% of the theoretical proteome, which is providing a wide coverage of B. abortus genome. The identification of proteins necessary for stress resistance is crucial to elucidate the infectious process in order to control brucellosis and may provide valuable clues towards discovery of novel therapeutic targets and effective vaccines.
Project description:Proteomic analysis of gastroduodenal fluid offers an alternative strategy to study diseases, such as peptic ulcer disease and gastric cancer. We use in-gel tryptic digestion followed by LC-MS/MS (GeLC-MS/MS) to profile the proteome of gastroduodenal fluid collected during the endoscopic pancreatic function test (ePFT).Gastroduodenal fluid specimens collected during ePFT from six patients with upper abdominal pain were subjected to proteomic analysis. We extracted proteins using three chemical precipitation reagents (acetone, ethanol, and trichloroacetic acid) and analyzed each sample by SDS-PAGE and GeLC-MS/MS for protein identification. Cellular origin and molecular function of the identified proteins were determined via gene ontology analysis.All three precipitation techniques successfully extracted protein from gastroduodenal fluid, with acetone resulting in excellent resolution and minimal protein degradation compared with the other methods. A total of 134 unique proteins were found in our GeLC-MS/MS analysis of ePFT-collected gastroduodenal fluid samples. Sixty-seven proteins were identified in at least two of the three samples. Gene ontology analysis classified these proteins mainly as being peptidases and localized extracellularly.ePFT, followed by acetone precipitation, and coupled with LC-MS/MS, can be used to safely collect gastroduodenal fluid from the upper gastrointestinal tract for MS-based proteomic analysis.
Project description:Saliva contains numerous proteins and peptides, each of them carries a number of biological functions that are very important in maintaining the oral cavity health and also yields information about both local and systemic diseases. Currently, proteomic analysis is the basis for large-scale identification of these proteins and discovery of new biomarkers for distinct diseases.This study compared methodologies to extract salivary proteins for proteomic analysis.Saliva samples were collected from 10 healthy volunteers. In the first test, the necessity for using an albumin and IgG depletion column was evaluated, employing pooled samples from the 10 volunteers. In the second test, the analysis of the pooled samples was compared with individual analysis of one sample. Salivary proteins were extracted and processed for analysis by LC-ESI-MS/MS.In the first test, we identified only 35 proteins using the albumin and IgG depletion column, while we identified 248 proteins without using the column. In the second test, the pooled sample identified 212 proteins, such as carbonic anhydrase 6, cystatin isoforms, histatins 1 and 3, lysozyme C, mucin 7, protein S100A8 and S100A9, and statherin, while individual analysis identified 239 proteins, among which are carbonic anhydrase 6, cystatin isoforms, histatin 1 and 3, lactotransferrin, lyzozyme C, mucin 7, protein S100A8 and S100A9, serotransferrin, and statherin.The standardization of protocol for salivary proteomic analysis was satisfactory, since the identification detected typical salivary proteins, among others. The results indicate that using the column for depletion of albumin and IgG is not necessary and that performing individual analysis of saliva samples is possible.
Project description:Advances in proteomic analysis of human samples are driving critical aspects of biomarker discovery and the identification of molecular pathways involved in disease etiology. Toward that end, in this report we are the first to use a standardized shotgun proteomic analysis method for in-depth tissue protein profiling of the two major subtypes of nonsmall cell lung cancer and normal lung tissues. We identified 3621 proteins from the analysis of pooled human samples of squamous cell carcinoma, adenocarcinoma, and control specimens. In addition to proteins previously shown to be implicated in lung cancer, we have identified new pathways and multiple new differentially expressed proteins of potential interest as therapeutic targets or diagnostic biomarkers, including some that were not identified by transcriptome profiling. Up-regulation of these proteins was confirmed by multiple reaction monitoring mass spectrometry. A subset of these proteins was found to be detectable and differentially present in the peripheral blood of cases and matched controls. Label-free shotgun proteomic analysis allows definition of lung tumor proteomes, identification of biomarker candidates, and potential targets for therapy.
Project description:Neurons are categorised into many subclasses, and each subclass displays different morphology, expression patterns, connectivity and function. Changes in protein synthesis are critical for neuronal function. Therefore, analysing protein expression patterns in individual neuronal subclass will elucidate molecular mechanisms for memory and other functions. In this study, we used neuronal subclass-selective proteomic analysis with cell-selective bio-orthogonal non-canonical amino acid tagging. We selected Caenorhabditis elegans as a model organism because it shows diverse neuronal functions and simple neural circuitry. We performed proteomic analysis of all neurons or AFD subclass neurons that regulate thermotaxis in C. elegans. Mutant phenylalanyl tRNA synthetase (MuPheRS) was selectively expressed in all neurons or AFD subclass neurons, and azido-phenylalanine was incorporated into proteins in cells of interest. Azide-labelled proteins were enriched and proteomic analysis was performed. We identified 4,412 and 1,834 proteins from strains producing MuPheRS in all neurons and AFD subclass neurons, respectively. F23B2.10 (RING-type domain-containing protein) was identified only in neuronal cell-enriched proteomic analysis. We expressed GFP under the control of the 5' regulatory region of F23B2.10 and found GFP expression in neurons. We expect that more single-neuron specific proteomic data will clarify how protein composition and abundance affect characteristics of neuronal subclasses.
Project description:Protein palmitoylation is a dynamic process that regulates membrane targeting of proteins and protein-protein interactions. We have previously demonstrated a critical role for protein palmitoylation in platelet activation and have identified palmitoylation machinery in platelets. Using a novel proteomic approach, Palmitoyl Protein Identification and Site Characterization, we have begun to characterize the human platelet palmitoylome. Palmitoylated proteins were enriched from membranes isolated from resting platelets using acyl-biotinyl exchange chemistry, followed by identification using liquid chromatography-tandem mass spectrometry. This global analysis identified > 1300 proteins, of which 215 met criteria for significance and represent the platelet palmitoylome. This collection includes 51 known palmitoylated proteins, 61 putative palmitoylated proteins identified in other palmitoylation-specific proteomic studies, and 103 new putative palmitoylated proteins. Of these candidates, we chose to validate the palmitoylation of triggering receptors expressed on myeloid cell (TREM)-like transcript-1 (TLT-1) as its expression is restricted to platelets and megakaryocytes. We determined that TLT-1 is a palmitoylated protein using metabolic labeling with [³H]palmitate and identified the site of TLT-1 palmitoylation as cysteine 196. The discovery of new platelet palmitoyl protein candidates will provide a resource for subsequent investigations to validate the palmitoylation of these proteins and to determine the role palmitoylation plays in their function.
Project description:Nucleolus is the most prominent subnuclear structure, which performs a wide variety of functions in the eukaryotic cellular processes. In order to understand the structural and functional role of the nucleoli in bovine cells, we analyzed the proteomic composition of the bovine nucleoli. The nucleoli were isolated from Madin Darby bovine kidney cells and subjected to proteomic analysis by LC-MS/MS after fractionation by SDS-PAGE and strong cation exchange chromatography. Analysis of the data using the Mascot database search and the GPM database search identified 311 proteins in the bovine nucleoli, which contained 22 proteins previously not identified in the proteomic analysis of human nucleoli. Analysis of the identified proteins using the GoMiner software suggested that the bovine nucleoli contained proteins involved in ribosomal biogenesis, cell cycle control, transcriptional, translational and post-translational regulation, transport, and structural organization.
Project description:BACKGROUND: Follicular fluid accumulates into the antrum of follicle from the early stage of follicle development. Studies on its components may contribute to a better understanding of the mechanisms underlying follicular development and oocyte quality. With this objective, we performed a proteomic analysis of mare follicular fluid. First, we hypothesized that proteins in follicular fluid may differ from those in the serum, and also may change during follicle development. Second, we used four different approaches of Immunodepletion and one enrichment method, in order to overcome the masking effect of high-abundance proteins present in the follicular fluid, and to identify those present in lower abundance. Finally, we compared our results with previous studies performed in mono-ovulant (human) and poly-ovulant (porcine and canine) species in an attempt to identify common and/or species-specific proteins. METHODS: Follicular fluid samples were collected from ovaries at three different stages of follicle development (early dominant, late dominant and preovulatory). Blood samples were also collected at each time. The proteomic analysis was carried out on crude, depleted and enriched follicular fluid by 2D-PAGE, 1D-PAGE and mass spectrometry. RESULTS: Total of 459 protein spots were visualized by 2D-PAGE of crude mare follicular fluid, with no difference among the three physiological stages. Thirty proteins were observed as differentially expressed between serum and follicular fluid. Enrichment method was found to be the most powerful method for detection and identification of low-abundance proteins from follicular fluid. Actually, we were able to identify 18 proteins in the crude follicular fluid, and as many as 113 in the enriched follicular fluid. Inhibins and a few other proteins involved in reproduction could only be identified after enrichment of follicular fluid, demonstrating the power of the method used. The comparison of proteins found in mare follicular fluid with proteins previously identified in human, porcine and canine follicular fluids, led to the identification of 12 common proteins and of several species-specific proteins. CONCLUSIONS: This study provides the first description of mare follicular fluid proteome during the late follicle development stages. We identified several proteins from crude, depleted and enriched follicular fluid. Our results demonstrate that the enrichment method, combined with 2D-PAGE and mass spectrometry, can be successfully used to visualize and further identify the low-abundance proteins in the follicular fluid.
Project description:BACKGROUND:The complexity of the human plasma proteome represents a substantial challenge for biomarker discovery. Proteomic analysis of genetically engineered mouse models of cancer and isolated cancer cells and cell lines provide alternative methods for identification of potential cancer markers that would be detectable in human blood using sensitive assays. The goal of this work is to evaluate the utility of an integrative strategy using these two approaches for biomarker discovery. METHODOLOGY/PRINCIPAL FINDINGS:We investigated a strategy that combined quantitative plasma proteomics of an ovarian cancer mouse model with analysis of proteins secreted or shed by human ovarian cancer cells. Of 106 plasma proteins identified with increased levels in tumor bearing mice, 58 were also secreted or shed from ovarian cancer cells. The remainder consisted primarily of host-response proteins. Of 25 proteins identified in the study that were assayed, 8 mostly secreted proteins common to mouse plasma and human cancer cells were significantly upregulated in a set of plasmas from ovarian cancer patients. Five of the eight proteins were confirmed to be upregulated in a second independent set of ovarian cancer plasmas, including in early stage disease. CONCLUSIONS/SIGNIFICANCE:Integrated proteomic analysis of cancer mouse models and human cancer cell populations provides an effective approach to identify potential circulating protein biomarkers.
Project description:To complement the recent genomic sequencing of Chinese hamster ovary (CHO) cells, proteomic analysis was performed on CHO cells including the cellular proteome, secretome, and glycoproteome using tandem mass spectrometry (MS/MS) of multiple fractions obtained from gel electrophoresis, multidimensional liquid chromatography, and solid phase extraction of glycopeptides (SPEG). From the 120 different mass spectrometry analyses generating 682,097 MS/MS spectra, 93,548 unique peptide sequences were identified with at most 0.02 false discovery rate (FDR). A total of 6164 grouped proteins were identified from both glycoproteome and proteome analysis, representing an 8-fold increase in the number of proteins currently identified in the CHO proteome. Furthermore, this is the first proteomic study done using the CHO genome exclusively, which provides for more accurate identification of proteins. From this analysis, the CHO codon frequency was determined and found to be distinct from humans, which will facilitate expression of human proteins in CHO cells. Analysis of the combined proteomic and mRNA data sets indicated the enrichment of a number of pathways including protein processing and apoptosis but depletion of proteins involved in steroid hormone and glycosphingolipid metabolism. Five-hundred four of the detected proteins included N-acetylation modifications, and 1292 different proteins were observed to be N-glycosylated. This first large-scale proteomic analysis will enhance the knowledge base about CHO capabilities for recombinant expression and provide information useful in cell engineering efforts aimed at modifying CHO cellular functions.
Project description:Ventilator-associated pneumonia (VAP) is a common complication in patients with acute lung injury (ALI) and can lead to increased morbidity and mortality. Identifying protein profiles specific to VAP in bronchoalveolar lavage fluid (BALF) may aid in earlier diagnosis, elucidate mechanisms of disease, and identify putative targets for therapeutic intervention.BALF was obtained from 5 normal subjects and 30 ALI patients: 14 with VAP (VAP(+)) and 16 without VAP (VAP(-)). Each sample underwent shotgun proteomic analysis based on tandem mass spectrometry. Differentially expressed proteins between the groups were identified using statistical methods based on spectral counting. Mechanisms of disease were explored using functional annotation and protein interaction network analysis. Supervised classification algorithms were implemented to discover a proteomic classifier for identifying critically ill patients with VAP.ALI patients had distinct BALF proteomic profiles compared to normal controls. Within the ALI group, we identified 76 differentially expressed proteins between VAP(+) and VAP(-). Functional analysis of these proteins suggested activation of pro-inflammatory pathways during VAP. We identified and validated a limited proteomic signature that discriminated VAP(+) from VAP(-) patients comprised of three proteins: S100A8, lactotransferrin (LTF), and actinin 1 (ACTN1).Combining proteomic with computational analyses is a powerful approach to study the BALF proteome during lung injury and development of VAP. This integrative methodology is a promising strategy to differentiate clinically relevant subsets of ALI patients, including those suffering from VAP.