The widespread use of mass spectrometry for protein identification has created a demand for computationally efficient methods of matching mass spectrometry data to protein databases. A search using X!Tandem, a popular and representative program, can require hours or days to complete, particularly when missed cleavages and post-translational modifications are considered. Existing techniques for accelerating X!Tandem by employing parallelism are unsatisfactory for a variety of reasons. The paper describes a parallelization of X!Tandem, called X!!Tandem, that shows excellent speedups on commodity hardware and produces the same results as the original program. Furthermore, the parallelization technique used is unusual and potentially useful for parallelizing other complex programs.
proteomics; protein identification; parallel database search; X!Tandem; tandem mass spectrometry; parallel X!Tandem; MPI
We have developed an integrated web-accessible software system called the Yale Protein Expression Database (YPED) to address the need for storage, retrieval, and integrated analysis of large amounts of data from high throughput proteomic technologies. YPED is an open source system which integrates gel analysis results with protein identifications from DIGE experiments. The system associates the DIGE gel spots and image, analyzed with DeCyder, with mass spectrometric protein identifications from selected gel spots. Following in gel trypsin digestion, proteins in spots of interest are analyzed using MALDI-TOF/TOF on an AB 4700 or, more recently, on an AB 4800 with protein identifications performed by Mascot in conjunction with the AB GPS Explorer system. In addition to DIGE, YPED currently handles protein identifications from MudPIT, iTRAQ, and ICAT experiments. Sample descriptions are compatible with the evolving MIAPE standards. Tandem MS/MS results from MudPIT, and ICAT analyses are validated with the Trans-Proteomic Pipeline and then stored in the database for viewing and linking to the identified proteins. Researchers can view, subset, and download their data through a secure Web interface that includes a table containing proteins identified, a sample summary, the sample description, and a clickable gel image for DIGE samples. Tools are available to facilitate sample comparison and the viewing of phosphoproteins. A summary report with PANTHER Classification System annotations is also available to aid in biological interpretation of the results. The source code is open-source and is available from http://yped.med.yale.edu/yped_dist.
protein expression database; mass spectrometry; MudPIT; DIGE; ICAT; iTRAQ; proteomics
Cardiac voltage-gated Na+ (Nav) channels are key determinants of action potential waveforms, refractoriness and propagation, and Nav1.5 is the main Nav pore-forming (α) subunit in the mammalian heart. Although direct phosphorylation of the Nav1.5 protein has been suggested to modulate various aspects of Nav channel physiology and pathophysiology, native Nav1.5 phosphorylation sites have not been identified. In the experiments here, a mass spectrometry (MS)-based proteomic approach was developed to identify native Nav1.5 phosphorylation sites directly. Using an anti-NavPAN antibody, Nav channel complexes were immunoprecipitated from adult mouse cardiac ventricles. The MS analyses revealed that this antibody immunoprecipitates several Nav α subunits in addition to Nav1.5, as well as several previously identified Nav channel associated/regulatory proteins. Label-free comparative and data-driven phosphoproteomic analyses of purified cardiac Nav1.5 protein identified 11 phosphorylation sites, 8 of which are novel. All the phosphorylation sites identified except one in the N-terminus are in the first intracellular linker loop, suggesting critical roles for this region in phosphorylation-dependent cardiac Nav channel regulation. Interestingly, commonly used prediction algorithms did not reliably predict these newly identified in situ phosphorylation sites. Taken together, the results presented provide the first in situ map of basal phosphorylation sites on the mouse cardiac Nav1.5 α subunit.
Nav1.5 Channels; Heart; Native Phosphorylations; Mass Spectrometric Identifications; Label-free Comparative and Data-driven LC-MS/MS Analyses
Immunodepletion of abundant plasma proteins increases the depth of proteome penetration by mass spectrometry. However, the nature and extent of immunodepletion and the effect of off-target depletion on the quantitative comparison of the residual proteins have not been critically addressed. We performed mass spectrometry label-free quantitation to determine which proteins were immunodepleted and by how much. Two immunodepletion resins were compared: Qproteome (Qiagen) which removes albumin+immunoglobulins and Seppro IgY14+SuperMix (Sigma-Aldrich) which removes 14 target proteins plus a number of unidentified proteins. Plasma collected by P100 proteomic plasma collection tubes (BD) from 20 human subjects was individually immunodepleted to minimize potential variability, prior to pooling. The abundant proteins were quantified better when using only albumin+immunoglobulins removal (Qproteome) while lower abundance proteins were evaluated better using exhaustive immunodepletion (Seppro IgY14+SuperMix). The latter resin removed at least 155 proteins, 38% of the plasma proteome in protein number and 94% of plasma protein in mass. The depth of immunodepletion likely accounts for the effectiveness of this resin in revealing low abundance proteins. However, the more profound immunodepletion achieved with the IgY14+SuperMix may lead to false-positive fold-changes between comparison groups if the reproducibility and efficiency of the depletion of a given protein is not considered.
immunodepletion; Seppro; IgY; Qproteome; iTRAQ; EMMOL normalization; off-target
Comprehensive knowledge of proteome complexity is crucial to understanding cell function. Amino termini of yeast proteins were identified through peptide mass spectrometry on glutaraldehyde-treated cell lysates as well as a parallel assessment of publicly-deposited spectra. An unexpectedly large fraction of detected amino-terminal peptides (35%) mapped to translation initiation at AUG codons downstream of the annotated start codon. Many of the implicated genes have suboptimal sequence contexts for translation initiation near their annotated AUG, and their ribosome profiles show elevated tag densities consistent with translation initiation at downstream AUGs as well as their annotated AUGs. These data suggest that a significant fraction of the yeast proteome derives from initiation at downstream AUGs, increasing significantly the repertoire of encoded proteins and their potential functions and cellular localizations.
Protein translation initiation sites
Mutations in cohesin genes have been identified in Cornelia de Lange syndrome (CdLS), but its etiopathogenetic mechanisms are still poorly understood. To define biochemical pathways that are affected in CdLS we analyzed the proteomic profile of CdLS cell lines carrying mutations in the core cohesin genes, SMC1A and SMC3. Dysregulated protein expression was found in CdLS probands compared to controls. The proteomics analysis was able to discriminate between probands harboring mutations in the different domains of the SMC proteins. In particular, proteins involved in the response to oxidative stress were specifically down-regulated in hinge mutated probands. In addition, the finding that CdLS cell lines show an increase in global oxidative stress argues that it could contribute to some CdLS phenotypic features such as premature physiological aging and genome instability. Finally, the c-MYC gene represents a convergent hub lying at the center of dysregulated pathways, and is down-regulated in CdLS. This study allowed us to highlight, for the first time, specific biochemical pathways that are affected in CdLS, providing plausible causal evidence for some of the phenotypic features seen in CdLS.
Cohesin; Cornelia de Lange syndrome; SMC1A; SMC3; 2D-DIGE; proteomic profile; dysregulated protein expression; c-Myc
Parsimony and protein grouping are widely employed to enforce economy in the number of identified proteins, with the goal of increasing the quality and reliability of protein identifications; however, in a counterintuitive manner, parsimony and protein grouping may actually decrease the reproducibility and interpretability of protein identifications. We present a simple illustration demonstrating ways in which parsimony and protein grouping may lower the reproducibility or interpretability of results. We then provide an example of a data set where a probabilistic method increases the reproducibility and interpretability of identifications made on replicate analyses of Human Du145 prostate cancer cell lines.
Three disease phenotypes, Barrett’s esophagus (BE), high-grade dysplasia (HGD), esophageal adenocarcinoma (EAC), and a set of normal control (NC) serum samples are examined using a combination of ion mobility spectrometry (IMS), mass spectrometry (MS) and principal component analysis (PCA) techniques. Samples from a total of 136 individuals were examined, including: 7 characterized as BE, 12 as HGD, 56 as EAC and 61 as NC. In typical datasets it was possible to assign ~20 to 30 glycan ions based on MS measurements. Ion mobility distributions for these ions show multiple features. In some cases, such as the [S1H5N4+3Na]3+ and [S1F1H5N4+3Na]3+ glycan ions, the ratio of intensities of high-mobility features to low-mobility features vary significantly for different groups. The degree to which such variations in mobility profiles can be used to distinguish phenotypes is evaluated for eleven N-linked glycan ions. An outlier analysis on each sample class followed by an unsupervised PCA using a genetic algorithm for pattern recognition reveals that EAC samples are separated from NC samples based on 46 features originating from the 11-glycan composite IMS distribution.
ion mobility; electrospray ionization mass spectrometry; glycans; cancer; genetic algorithm; principal component analysis
Lipid rafts are microdomains in the plasma membrane of eukaryotic cells. Among their many functions, lipid rafts are involved in cell toxicity caused by pore forming bacterial toxins including Bacillus thuringiensis (Bt) Cry toxins. We isolated lipid rafts from brush border membrane vesicles (BBMV) of Aedes aegypti larvae as a detergent resistant membrane (DRM) fraction on density gradients. Cholesterol, aminopeptidase (APN), alkaline phosphatase (ALP) and the raft marker flotillin were preferentially partitioned into the lipid raft fraction. When mosquitocidal Cry4Ba toxin was pre-incubated with BBMV, Cry4Ba localized to lipid rafts. A proteomic approach based on one dimensional gel electrophoresis, in-gel trypsin digestion, followed by liquid chromatography-mass spectrometry (geLC-MS/MS) identified a total of 386 proteins. Of which many are typical lipid raft marker proteins including flotillins and glycosylphosphatidylinositol (GPI)-anchored proteins. Identified raft proteins were annotated in silico for functional and physicochemical characteristics. Parameters such as distribution of isoelectric point, molecular mass, and predicted post-translational modifications relevant to lipid raft proteins (GPI anchorage and myristoylation or palmitoylation) were analyzed for identified proteins in the DRM fraction. From a functional point of view, this study identified proteins implicated in Cry toxin interactions as well as membrane-associated proteins expressed in the mosquito midgut that have potential relevance to mosquito biology and vector management.
Lipid rafts; Detergent resistant membranes; Brush border membrane vesicles; Cry4Ba toxin; Cholesterol; Proteomics; LC-MS/MS
Our increased interest in translational research has created a large demand for blood, tissue and other clinical samples, which find use in a broad variety of research including genomics, proteomics, and metabolomics. Hundreds of millions of dollars have been invested internationally on the collection, storage and distribution of samples. Nevertheless, many researchers complain in frustration about their inability to obtain relevant and/or useful samples for their research. Lack of access to samples, poor condition of samples, and unavailability of appropriate control samples have slowed our progress in the study of diseases and biomarkers. In this editorial, I focus on five major challenges that thwart clinical sample use for translational research and propose near term objectives to address them. They include: (1) defining our biobanking needs; (2) increasing the use of and access to standard operating procedures; (3) mapping inter-observer differences for use in normalizing diagnoses; (4) identifying natural internal protein controls; and (5) redefining the clinical sample paradigm by building partnerships with the public. In each case, I believe that we have the tools at hand required to achieve the objective within 5 years. Potential paths to achieve these objectives are explored. However we solve these problems, the future of proteomics depends on access to high quality clinical samples, collected under standardized conditions, accurately annotated and shared under conditions that promote the research we need to do.
Specimen; biobank; clinical; translational; public partnership; standard operating procedure; sample processing; tissue; blood; standardization; healthcare; disease; reference standard; informed consent; donors; ethics; governance; proteomics; cohort; case/control; database; calibration; diversity; inclusion
The filamentous fungus Magnaporthe oryzae (M. oryzae) is the causative agent of rice blast disease and presents a significant threat to worldwide rice production. To establish the groundwork for future research on the pathogenic development of M. oryzae, a global proteomic study of conidia was performed. The filter aided sample preparation method (FASP) and anion StageTip fractionation combined with long, optimized shallow 210 min nanoLC gradients prior to mass spectrometry analysis on an Orbitrap XL was applied, which resulted in a doubling of protein identifications in comparison to our previous GeLC analysis. Herein, we report the identification of 2912 conidial proteins at a 1% protein false discovery rate (FDR) and we present the most extensive study performed on M. oryzae conidia to date. A similar distribution between identified proteins and the predicted proteome was observed when subcellular localization analysis was performed, suggesting the detected proteins build a representative portion of the predicted proteome. A higher percentage of cytoplasmic proteins (associated with translation, energy and metabolism) were observed in the conidial proteome relative to the whole predicted proteome. Conversely, nuclear and extracellular proteins were less well represented in the conidial proteome. Further analysis by gene ontology revealed biological insights into identified proteins important for central metabolic processes and the physiology of conidia.
proteomics; mass spectrometry; Magnaporthe oryzae; FASP; statistical tests; differential protein expression
Although hepatocellular carcinoma (HCC) has been subjected to continuous investigation and its symptoms are well known, early-stage diagnosis of this disease remains difficult and the survival rate after diagnosis is typically very low (3–5%). Early and accurate detection of metabolic changes in the sera of patients with liver cirrhosis can help improve the prognosis of HCC and lead to a better understanding of its mechanism at the molecular level, thus providing patients with in-time treatment of the disease. In this study, we compared metabolite levels in sera of 40 HCC patients and 49 cirrhosis patients from Egypt by using ultra-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometer (UPLC-QTOF MS). Following data preprocessing, the most relevant ions in distinguishing HCC cases from cirrhotic controls are selected by statistical methods. Putative metabolite identifications for these ions are obtained through mass-based database search. The identities of some of the putative identifications are verified by comparing their MS/MS fragmentation patterns and retention times with those from authentic compounds. Finally, the serum samples are reanalyzed for quantitation of selected metabolites along with other metabolites previously selected as candidate biomarkers of HCC. This quantitation was performed using isotope dilution by selected reaction monitoring (SRM) on a triple quadrupole linear ion trap (QqQLIT) coupled to UPLC. Statistical analysis of the UPLC-QTOF data identified 274 monoisotopic ion masses with statistically significant differences in ion intensities between HCC cases and cirrhotic controls. Putative identifications were obtained for 158 ions by mass based search against databases. We verified the identities of selected putative identifications including glycholic acid (GCA), glycodeoxycholic acid (GDCA), 3beta, 6beta-dihydroxy-5beta-cholan-24-oic acid, oleoyl carnitine, and Phe-Phe. SRM-based quantitation confirmed significant differences between HCC and cirrhotic controls in metabolite levels of bile acid metabolites, long chain carnitines and small peptide. Our study provides useful insight into appropriate experimental design and computational methods for serum biomarker discovery using LC-MS/MS based metabolomics. This study has led to the identification of candidate biomarkers with significant changes in metabolite levels between HCC cases and cirrhotic controls. This is the first MS-based metabolic biomarker discovery study on Egyptian subjects that led to the identification of candidate metabolites that discriminate early stage HCC from patients with liver cirrhosis.
Hepatocellular carcinoma; liver cirrhosis; metabolic biomarker; cancer biomarker discovery; selected reaction monitoring; isotope dilution; mass spectrometry
Despite decreasing incidence and mortality, gastric cancer remains the second leading cause of cancer-related deaths in the world. Successful management of gastric cancer is hampered by lack of highly sensitive and specific biomarkers especially for early cancer detection. Cell surface proteins that are aberrantly expressed between normal and cancer cells are potentially useful for cancer imaging and therapy due to easy accessibility of these targets. Combining two-phase partition and isobaric tags for relative and absolute quantification methods, we compared the relative expression levels of membrane proteins between noncancer and gastric cancer cells. About 33% of the data set was found to be plasma membrane and associated proteins using this approach (compared to only 11% in whole cell analysis), several of which have never been previously implicated in gastric cancer. Upregulation of SLC3A2 in gastric cancer cells was validated by immunoblotting of a panel of 13 gastric cancer cell lines and immunohistochemistry on tissue microarrays comprising 85 matched pairs of normal and tumor tissues. Immunofluorescence and immunohistochemistry both confirmed the plasma membrane localization of SLC3A2 in gastric cancer cells. The data supported the notion that SLC3A2 is a potential biomarker that could be exploited for molecular imaging-based detection of gastric cancer.
iTRAQ; gastric cancer; plasma membrane; SLC3A2; biomarker
IgA is the most abundantly produced antibody and plays an important role in the mucosal immune system. Human IgA is represented by two isotypes, IgA1 and IgA2. The major structural difference between these two subclasses is the presence of nine potential sites of O-glycosylation in the hinge region between the first and second constant region domains of the heavy chain. Thr225, Thr228, Ser230, Ser232 and Thr236 have been identified as the predominant sites of O-glycan attachment. The range and distribution of O-glycan chains at each site within the context of adjacent sites in this clustered region create a complex heterogeneity of surface epitopes that is incompletely defined. We previously described the analysis of IgA1 O-glycan heterogeneity by use of high resolution LC/MS and electron capture dissociation tandem MS to unambiguously localize all amino acid attachment sites in IgA1 (Ale) myeloma protein. Here, we report the identification and elucidation of IgA1 O-glycopeptide structural isomers that occur based on amino acid position of the attached glycans (positional isomers) and the structure of the O-glycan chains at individual sites (glycan isomers). These isomers are present in a model IgA1 (Mce1) myeloma protein and occur naturally in normal human serum IgA1. Variable O-glycan chains attached to Ser230, Thr233 or Thr236 produce the predominant positional isomers, including O-glycans composed of a single GalNAc residue. These findings represent the first definitive identification of structural isomeric IgA1 O-glycoforms, define the single-site heterogeneity for all O-glycan sites in a single sample, and have implications for defining epitopes based on clustered O-glycan variability.
O-glycosylation; IgA1 immunoglobulin; ECD; electron capture dissociation; FT-ICR MS; glycopeptide isomers
Discovery and validation of plasma biomarkers are quite challenging due to the high complexity and wide dynamic range of the plasma proteome. Current plasma protein profiling strategies usually use major protein immunodepletion and nanoLC-MS/MS as the first and final analytical steps, respectively, but additional fractionation is needed to detect and quantify low-abundant disease biomarkers. In this study, the performance of 1-D SDS-PAGE, peptide isoelectrofocusing, and peptide high pH reverse-phase chromatography for fractionation of immunodepleted human plasma were systematically compared by evaluating protein coverage, peptide resolution, and capacity to detect known low-abundant proteins. Trade-offs between increasing the number of fractions to improve proteome coverage and resulting decreases in throughput also were assessed. High pH reverse-phase HPLC exhibited the highest peptide resolution and yielded the best depth of analysis with detection of the largest number of known low-abundant proteins for a given level of fractionation. Another advantage of using high pH reverse-phase fractionation rather than 1-D SDS gels is that all fractionation steps except for abundant protein depletion occur at the peptide level, making this strategy more compatible with quantitative biomarker validation methods such as stable isotope dilution multiple reaction monitoring.
plasma proteome; proteome fractionation; protein profiling; biomarkers; human plasma; biomarker discovery; biomarker validation
Antibody-overlay lectin microarray (ALM) has been used for targeted glycan profiling to identify disease-related protein glycoforms. In this context, high sensitivity is desired because it allows for the identification of disease-related glycoforms that are often present at low concentration. We describe a new Tyramide Signal Amplification (TSA) for Antibody-overlay Lectin Microarray procedure for sensitive profiling of glycosylation patterns. We demonstrated that TSA increased the sensitivity of the microarray over 100 times for glycan profiling using the model protein Prostate Specific Antigen (PSA). The glycan profile of PSA enriched from LNCAP cells, obtained at a sub-nanogram level with the aid of TSA, was consistent with the previous reports. We also established the glycan profile of Prostate Specific Membrane Antigen (PSMA) using the TSA and ALM. Thus, the Tyramide Signal Amplification for Antibody-overlay Lectin Microarray is a sensitive, rapid, comprehensive, and high-throughput method for targeted glycan profiling and can potentially be used for the identification of disease-related protein glycoforms.
Cyclosporine (CsA) is a highly effective immunosuppressant used in patients after transplantation; however its use is limited by nephrotoxicity. Salt depletion is known to enhance CsA-induced nephrotoxicity in the rat, but the underlying molecular mechanisms are not completely understood.
The goal of our study was to identify the molecular effects of salt depletion alone and in combination with CsA on the kidney using a proteo metabolomic strategy. Rats (n=6) were assigned to four study groups: 1) normal controls, 2) low-salt fed controls, 3) 10 mg/kg/d CsA for 28 days on a normal diet, 4) 10 mg/kg/d CsA for 28 days on low-salt diet.
Low-salt diet redirected kidney energy metabolism towards mitochondria as indicated by a higher energy charge than in normal-fed controls. Low-salt diet alone reduced phospho-AKT and phospho-STAT3 levels, and changed the expression of ion transporters PDZK1 and CLIC1.
CsA induced macro- and microvesicular tubular epithelial vacuolization and reduced energy charge; changes that were more significant in low-salt fed animal, probably because of their more pronounced dependence on mitochondria. Here, CsA increased phospho-JAK2 and phospho-STAT3 levels and reduced the phospho-IKKγ and p65 proteins, thus activating NF-κB signaling. Decreased expression of lactate transport regulator CD147 and phospho-AKT was also observed after CsA exposure in low-salt rats, indicating a decrease in glycolysis.
In summary, our study suggests a key role for PDZK1, CD147, JAK/STAT and AKT signaling in CsA-induced nephrotoxicity and proposes mechanistic explanations on why rats fed a low-salt diet have higher sensitivity to CsA.
CsA-induced nephrotoxicity; proteomics; metabolomics; salt depletion
Quantitative proteomics analysis of cortical samples of ten Alzheimer’s disease (AD) brains versus ten normally aged brains was performed by following the accurate mass and time tag (AMT) approach with the high resolution LTQ Orbitrap mass spectrometer. More than 1400 proteins were identified and quantitated. A conservative approach of selecting only the consensus results of four normalization methods was suggested and used. A total of 197 proteins were shown to be significantly differentially abundant (p-values<0.05, corrected for multiplicity of testing) in AD versus control brain samples. Thirty seven of these proteins were reported as differentially abundant or modified in AD in the previous proteomics and transcriptomics publications. The rest to the best of our knowledge are new. Mapping of the discovered proteins with bioinformatic tools revealed significant enrichment with differentially abundant proteins of pathways and processes known to be important in AD, including signal transduction, regulation of protein phosphorylation, immune response, cytoskeleton organization, lipid metabolism, energy production, and cell death.
Alzheimer’s disease; brain; cortical samples; proteomics; bioinformatics; normalization
Cancer is currently considered as the end point of numerous genomic and epigenomic mutations and as the result of the interaction of transformed cells within the stromal microenvironment. The present work focuses on breast cancer, one of the most common malignancies affecting the female population in industrialized countries. In this study we perform a proteomic analysis of bioptic samples from human breast cancer, namely interstitial fluids and primary cells, normal vs disease tissues, using Tandem mass Tags (TmT) quantitative mass spectrometry combined with the MudPIT technique. To the best of our knowledge this work, with over 1700 proteins identified, represents the most comprehensive characterization of the breast cancer interstitial fluid proteome to date. Network analysis was used to identify functionally active networks in the breast cancer associated samples. From the list of differentially expressed genes we have retrieved the associated functional interaction networks. Many different signaling pathways were found activated, strongly linked to invasion, metastasis development, proliferation and with a significant cross-talking rate. This pilot study presents evidence that the proposed quantitative proteomic approach can be applied to discriminate between normal and tumoral samples and for the discovery of yet unknown carcinogenesis mechanisms and therapeutic strategies.
Interstitial fluid; breast cancer; Tandem mass Tags; MudPIT; LC-MS/MS; pathway analysis; Cytoscape
The cerebrospinal fluid (CSF) is produced in the brain by cells in the choroid plexus at a rate of 500mL/day. It is the only body fluid in direct contact with the brain. Thus, any changes in the CSF composition will reflect pathological processes and make CSF a potential source of biomarkers for different disease states. Proteomics offers a comprehensive view of the proteins found in CSF. In this study, we use a recently developed non-gel based method of sample preparation of CSF followed by liquid chromatography high accuracy mass spectrometry (LC-MS) for MS and MS/MS analyses, allowing unambiguous identification of peptides/proteins. Gel-eluted liquid fraction entrapment electrophoresis (Gelfree) is used to separate a CSF complex protein mixture in 12 user-selectable liquid-phase molecular weight fractions. Using this high throughput workflow we have been able to separate CSF intact proteins over a broad mass range 3.5 kDa-100 kDa with high resolution between 15 kDa and 100 kDa in 2 hours and 40 min. We have completely eliminated albumin and were able to interrogate the low abundance CSF proteins in a highly reproducible manner from different CSF samples in the same time. Using LC-MS as a downstream analysis, we identified 368 proteins using MidiTrap G-10 desalting columns and 166 proteins (including 57 unique proteins) using Zeba spin columns with 5% false discovery rate (FDR). Prostaglandin D2 synthase, Chromogranin A, Apolipoprotein E, Chromogranin B, Secretogranin III, Cystatin C, VGF nerve growth factor, Cadherin 2 are a few of the proteins that were characterized. The Gelfree-LC-MS is a robust method for the analysis of the human proteome that we will use to develop biomarkers for several neurodegenerative diseases and to quantitate these markers using multiple reaction monitoring.
Wounding of the oral mucosa occurs frequently in a highly septic environment. Remarkably, these wounds heal quickly and the oral cavity, for the most part, remains healthy. Deciphering the normal human oral epithelial cell (NHOEC) proteome is critical for understanding the mechanism(s) of protection elicited when the mucosal barrier is intact, as well as when it is breached. Combining 2D gel electrophoresis with shotgun proteomics resulted in identification of 1662 NHOEC proteins. Proteome annotations were performed based on protein classes, molecular functions, disease association and membership in canonical and metabolic signaling pathways. Comparing the NHOEC proteome with a database of innate immunity-relevant interactions (InnateDB) identified 64 common proteins associated with innate immunity. Comparison with published salivary proteomes revealed that 738/1662 NHOEC proteins were common, suggesting that significant numbers of salivary proteins are of epithelial origin. Gene ontology analysis showed similarities in the distributions of NHOEC and saliva proteomes with regard to biological processes, and molecular functions. We also assessed the inter-individual variability of the NHOEC proteome and observed it to be comparable with other primary cells. The baseline proteome described in this study should serve as a resource for proteome studies of the oral mucosa, especially in relation to disease processes.
Primary human oral epithelial cells; proteomics; inter-individual variability; innate immunity; saliva
Retinal ganglion cells (RGCs) transmit visual information topographically from the eye to the brain, creating a map of visual space in retino-recipient nuclei (retinotopy). This process is affected by retinal activity and by activity-independent molecular cues. Phr1, which encodes a presumed E3 ubiquitin ligase (PHR1), is required presynaptically for proper placement of RGC axons in the lateral geniculate nucleus and the superior colliculus, suggesting that increased levels of PHR1 target proteins may be instructive for retinotopic mapping of retinofugal projections. To identify potential target proteins, we conducted a proteomic analysis of optic nerve to identify differentially abundant proteins in the presence or absence of Phr1 in RGCs. 1D gel electrophoresis identified a specific band in controls that was absent in mutants. Targeted proteomic analysis of this band demonstrated the presence of PHR1. Additionally, we conducted an unbiased proteomic analysis that identified 30 proteins as being significantly different between the two genotypes. One of these, heterogeneous nuclear ribonucleoprotein M (hnRNP-M), regulates antero-posterior patterning in invertebrates and can function as a cell surface adhesion receptor in vertebrates. Thus we have demonstrated that network analysis of quantitative proteomic data is a useful approach for hypothesis generation and for identifying biologically relevant targets in genetically altered biological models.
Phr1; Mycbp2; retinal ganglion cell; proteomics; hnRNP-M; retinotopy; ubiquitin ligase; label-free quantitative proteomics; LC-MS; network analysis
In order to complement the recent genomic sequencing of Chinese hamster ovary (CHO) cells, proteomic analysis was performed on CHO including the cellular proteome, secretome, and glycoproteome using tandem mass spectrometry (MS/MS) of multiple fractions obtained from gel electrophoresis, multi-dimensional 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 a 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 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. 504 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.
Myocardial ischemia-reperfusion induces mitochondrial dysfunction and, depending upon the degree of injury, may lead to cardiac cell death. However, our ability to understand mitochondrial dysfunction has been hindered by an absence of molecular markers defining the various degrees of injury. To address this paucity of knowledge, we sought to characterize the impact of ischemic damage on mitochondrial proteome biology. We hypothesized that ischemic injury induces differential alterations in various mitochondrial sub-compartments, that these proteomic changes are specific to the severity of injury, and that they are important to subsequent cellular adaptations to myocardial ischemic injury. Accordingly, an in vitro model of cardiac mitochondria injury in mice was established to examine two stress conditions: reversible injury (induced by mild calcium overload) and irreversible injury (induced by hypotonic stimuli). Both forms of injury had a drastic impact on the proteome biology of cardiac mitochondria. Altered mitochondrial function was concomitant with significant protein loss/shedding from the injured organelles. In the setting of mild calcium overload, mitochondria retained functionality despite the release of numerous proteins, and the majority of mitochondria remained intact. In contrast, hypotonic stimuli caused severe damage to mitochondrial structure and function, induced increased oxidative modification of mitochondrial proteins, and brought about detrimental changes to the sub proteomes of the inner mitochondrial membrane and matrix. Using an established in vivo murine model of regional myocardial ischemic injury, we validated key observations made by the in vitro model. This pre-clinical investigation provides function and sub-organelle location information on a repertoire of cardiac mitochondrial proteins sensitive to ischemia reperfusion stress and highlights protein clusters potentially involved in mitochondrial dysfunction in the setting of ischemic injury.
proteome biology; ischemia injury; cardiac mitochondria; reversible injury; irreversible injury
During acute Lyme disease, bacteria can disseminate to the central nervous system (CNS) leading to the development of meningitis and other neurologic symptoms. Here we have analyzed pooled cerebrospinal fluid (CSF) allowing a deep view into the proteome for patients diagnosed with early-disseminated Lyme disease and CSF inflammation. Additionally, we analyzed individual patient samples and quantified differences in protein abundance employing label-free quantitative mass spectrometry based methods. We identified 108 proteins that differ significantly in abundance in patients with acute Lyme disease from controls. Comparison between infected patients and control subjects revealed differences in proteins in the CSF associated with cell death localized to brain synapses and others that likely originate from brain parenchyma.
Proteomics; mass spectrometry; Lyme disease; cerebrospinal fluid; Lyme neuroborreliosis