Journals
2009 EN
Anna L. Stevens · John S. Wishnok · Forest M. White
+2 more
The objectives of this study were to perform a quantitative comparison of proteins released from cartilage explants in response to treatment with IL-1beta, TNF-alpha, or mechanical compression injury in vitro and to interpret this release in the context of anabolic-catabolic shifts known to occur in cartilage in response to these insults in vitro and their implications in vivo. Bovine calf cartilage explants from 6-12 animals were subjected to injurious compression, TNF-alpha (100 ng/ml), IL-1beta (10 ng/ml), or no treatment and cultured for 5 days in equal volumes of medium. The pooled medium from each of these four conditions was labeled with one of four iTRAQ labels and subjected to nano-2D-LC/MS/MS on a quadrupole time-of-flight instrument. Data were analysed by ProQuant for peptide identification and quantitation. k-means clustering and biological pathways analysis were used to identify proteins that may correlate with known cartilage phenotypic responses to such treatments. IL-1beta and TNF-alpha treatment caused a decrease in the synthesis of collagen subunits (p < 0.05) as well as increased release of aggrecan G2 and G3 domains to the medium (p < 0.05). MMP-1, MMP-3, MMP-9, and MMP-13 were significantly increased by all treatments compared with untreated samples (p < 0.10). Increased release of proteins involved in innate immunity and immune cell recruitment were noted following IL-1beta and TNF-alpha treatment, whereas increased release of intracellular proteins was seen most dramatically with mechanical compression injury. Proteins involved in insulin-like growth factor and TGF-beta superfamily pathway modulation showed changes in pro-anabolic pathways that may represent early repair signals. At the systems level, two principal components were sufficient to describe 97% of the covariance in the data. A strong correlation was noted between the proteins released in response to IL-1beta and TNF-alpha; in contrast, mechanical injury resulted in both similarities and unique differences in the groups of proteins released compared with cytokine treatment.
Journals
2009 EN
ChienSheng Chen · Sean D. Sullivan · Troy Anderson
+14 more
Specific antimicrobial antibodies present in the sera of patients with inflammatory bowel disease (IBD) have been proven to be valuable serological biomarkers for diagnosis/prognosis of the disease. Herein we describe the use of a whole Escherichia coli proteome microarray as a novel high throughput proteomics approach to screen and identify new serological biomarkers for IBD. Each protein array, which contains 4,256 E. coli K12 proteins, was screened using individual serum from healthy controls (n = 39) and clinically well characterized patients with IBD (66 Crohn disease (CD) and 29 ulcerative colitis (UC)). Proteins that could be recognized by serum antibodies were visualized and quantified using Cy3-labeled goat anti-human antibodies. Surprisingly significance analysis of microarrays identified a total of 417 E. coli proteins that were differentially recognized by serum antibodies between healthy controls and CD or UC. Among those, 169 proteins were identified as highly immunogenic in healthy controls, 186 proteins were identified as highly immunogenic in CD, and only 19 were identified as highly immunogenic in UC. Using a supervised learning algorithm (k-top scoring pairs), we identified two sets of serum antibodies that were novel biomarkers for specifically distinguishing CD from healthy controls (accuracy, 86 +/- 4%; p < 0.01) and CD from UC (accuracy, 80 +/- 2%; p < 0.01), respectively. The Set 1 antibodies recognized three pairs of E. coli proteins: Era versus YbaN, YhgN versus FocA, and GabT versus YcdG, and the Set 2 antibodies recognized YidX versus FrvX. The specificity and sensitivity of Set 1 antibodies were 81 +/- 5 and 89 +/- 3%, respectively, whereas those of Set 2 antibodies were 84 +/- 1 and 70 +/- 6%, respectively. Serum antibodies identified for distinguishing healthy controls versus UC were only marginal because their accuracy, specificity, and sensitivity were 66 +/- 5, 69 +/- 5, and 61 +/- 7%, respectively (p < 0.04). Taken together, we identified novel sets of serological biomarkers for diagnosis of CD versus healthy control and CD versus UC.
Journals
2009 EN
Tanya C. Petrossian · Steven Clarke
A new program (Multiple Motif Scanning) was developed to scan the Saccharomyces cerevisiae proteome for Class I S-adenosylmethionine-dependent methyltransferases. Conserved Motifs I, Post I, II, and III were identified and expanded in known methyltransferases by primary sequence and secondary structural analysis through hidden Markov model profiling of both a yeast reference database and a reference database of methyltransferases with solved three-dimensional structures. The roles of the conserved amino acids in the four motifs of the methyltransferase structure and function were then analyzed to expand the previously defined motifs. Fisher-based negative log statistical matrix sets were developed from the prevalence of amino acids in the motifs. Multiple Motif Scanning is able to scan the proteome and score different combinations of the top fitting sequences for each motif. In addition, the program takes into account the conserved number of amino acids between the motifs. The output of the program is a ranked list of proteins that can be used to identify new methyltransferases and to reevaluate the assignment of previously identified putative methyltransferases. The Multiple Motif Scanning program can be used to develop a putative list of enzymes for any type of protein that has one or more motifs conserved at variable spacings and is freely available (www.chem.ucla.edu/files/MotifSetup.Zip). Finally hidden Markov model profile clustering analysis was used to subgroup Class I methyltransferases into groups that reflect their methyl-accepting substrate specificity.
Journals
2009 EN
Hasmik Keshishian · Terri A. Addona · Michael Burgess
+6 more
Verification of candidate biomarkers requires specific assays to selectively detect and quantify target proteins in accessible biofluids. The primary objective of verification is to screen potential biomarkers to ensure that only the highest quality candidates from the discovery phase are taken forward into preclinical validation. Because antibody reagents for a clinical grade immunoassay often exist for a small number of candidates, alternative methodologies are required to credential new and unproven candidates in a statistically viable number of serum or plasma samples. Using multiple reaction monitoring coupled with stable isotope dilution MS, we developed quantitative, multiplexed assays in plasma for six proteins of clinical relevance to cardiac injury. The process described does not require antibodies for immunoaffinity enrichment of either proteins or peptides. Limits of detection and quantitation for each signature peptide used as surrogates for the target proteins were determined by the method of standard addition using synthetic peptides and plasma from a healthy donor. Limits of quantitation ranged from 2 to 15 ng/ml for most of the target proteins. Quantitative measurements were obtained for one to two signature peptides derived from each target protein, including low abundance protein markers of cardiac injury in the nanogram/milliliter range such as the cardiac troponins. Intra- and interassay coefficients of variation were predominantly <10 and 25%, respectively. The configured multiplex assay was then used to measure levels of these proteins across three time points in six patients undergoing alcohol septal ablation for hypertrophic obstructive cardiomyopathy. These results are the first demonstration of a multiplexed, MS-based assay for detection and quantification of changes in concentration of proteins associated with cardiac injury in the low nanogram/milliliter range. Our results also demonstrate that these assays retain the necessary precision, reproducibility, and sensitivity to be applied to novel and uncharacterized candidate biomarkers for verification of proteins in blood.
Journals
2009 EN
Rebekah L. Gundry · Kimberly Raginski · Yelena S. Tarasova
+6 more
Endogenous regeneration and repair mechanisms are responsible for replacing dead and damaged cells to maintain or enhance tissue and organ function, and one of the best examples of endogenous repair mechanisms involves skeletal muscle. Although the molecular mechanisms that regulate the differentiation of satellite cells and myoblasts toward myofibers are not fully understood, cell surface proteins that sense and respond to their environment play an important role. The cell surface capturing technology was used here to uncover the cell surface N-linked glycoprotein subproteome of myoblasts and to identify potential markers of myoblast differentiation. 128 bona fide cell surface-exposed N-linked glycoproteins, including 117 transmembrane, four glycosylphosphatidylinositol-anchored, five extracellular matrix, and two membrane-associated proteins were identified from mouse C2C12 myoblasts. The data set revealed 36 cluster of differentiation-annotated proteins and confirmed the occupancy for 235 N-linked glycosylation sites. The identification of the N-glycosylation sites on the extracellular domain of the proteins allowed for the determination of the orientation of the identified proteins within the plasma membrane. One glycoprotein transmembrane orientation was found to be inconsistent with Swiss-Prot annotations, whereas ambiguous annotations for 14 other proteins were resolved. Several of the identified N-linked glycoproteins, including aquaporin-1 and beta-sarcoglycan, were found in validation experiments to change in overall abundance as the myoblasts differentiate toward myotubes. Therefore, the strategy and data presented shed new light on the complexity of the myoblast cell surface subproteome and reveal new targets for the clinically important characterization of cell intermediates during myoblast differentiation into myotubes.
Journals
2009 EN
Amanda G. Paulovich · Dean Billheimer · AmyJoan L. Ham
+27 more
Optimal performance of LC-MS/MS platforms is critical to generating high quality proteomics data. Although individual laboratories have developed quality control samples, there is no widely available performance standard of biological complexity (and associated reference data sets) for benchmarking of platform performance for analysis of complex biological proteomes across different laboratories in the community. Individual preparations of the yeast Saccharomyces cerevisiae proteome have been used extensively by laboratories in the proteomics community to characterize LC-MS platform performance. The yeast proteome is uniquely attractive as a performance standard because it is the most extensively characterized complex biological proteome and the only one associated with several large scale studies estimating the abundance of all detectable proteins. In this study, we describe a standard operating protocol for large scale production of the yeast performance standard and offer aliquots to the community through the National Institute of Standards and Technology where the yeast proteome is under development as a certified reference material to meet the long term needs of the community. Using a series of metrics that characterize LC-MS performance, we provide a reference data set demonstrating typical performance of commonly used ion trap instrument platforms in expert laboratories; the results provide a basis for laboratories to benchmark their own performance, to improve upon current methods, and to evaluate new technologies. Additionally, we demonstrate how the yeast reference, spiked with human proteins, can be used to benchmark the power of proteomics platforms for detection of differentially expressed proteins at different levels of concentration in a complex matrix, thereby providing a metric to evaluate and minimize pre-analytical and analytical variation in comparative proteomics experiments.
Journals
2009 EN
Paul A. Rudnick · Karl R. Clauser · Lisa E. Kilpatrick
+31 more
A major unmet need in LC-MS/MS-based proteomics analyses is a set of tools for quantitative assessment of system performance and evaluation of technical variability. Here we describe 46 system performance metrics for monitoring chromatographic performance, electrospray source stability, MS1 and MS2 signals, dynamic sampling of ions for MS/MS, and peptide identification. Applied to data sets from replicate LC-MS/MS analyses, these metrics displayed consistent, reasonable responses to controlled perturbations. The metrics typically displayed variations less than 10% and thus can reveal even subtle differences in performance of system components. Analyses of data from interlaboratory studies conducted under a common standard operating procedure identified outlier data and provided clues to specific causes. Moreover, interlaboratory variation reflected by the metrics indicates which system components vary the most between laboratories. Application of these metrics enables rational, quantitative quality assessment for proteomics and other LC-MS/MS analytical applications.
Journals
2009 EN
Patricia M. DiBello · Sanjana Dayal · Suma Kaveti
+4 more
Hyperhomocysteinemia has long been associated with atherosclerosis and thrombosis and is an independent risk factor for cardiovascular disease. Its causes include both genetic and environmental factors. Although homocysteine is produced in every cell as an intermediate of the methionine cycle, the liver contributes the major portion found in circulation, and fatty liver is a common finding in homocystinuric patients. To understand the spectrum of proteins and associated pathways affected by hyperhomocysteinemia, we analyzed the mouse liver proteome of gene-induced (cystathionine beta-synthase (CBS)) and diet-induced (high methionine) hyperhomocysteinemic mice using two-dimensional difference gel electrophoresis and Ingenuity Pathway Analysis. Nine proteins were identified whose expression was significantly changed by 2-fold (p < or = 0.05) as a result of genotype, 27 proteins were changed as a result of diet, and 14 proteins were changed in response to genotype and diet. Importantly, three enzymes of the methionine cycle were up-regulated. S-Adenosylhomocysteine hydrolase increased in response to genotype and/or diet, whereas glycine N-methyltransferase and betaine-homocysteine methyltransferase only increased in response to diet. The antioxidant proteins peroxiredoxins 1 and 2 increased in wild-type mice fed the high methionine diet but not in the CBS mutants, suggesting a dysregulation in the antioxidant capacity of those animals. Furthermore, thioredoxin 1 decreased in both wild-type and CBS mutants on the diet but not in the mutants fed a control diet. Several urea cycle proteins increased in both diet groups; however, arginase 1 decreased in the CBS(+/-) mice fed the control diet. Pathway analysis identified the retinoid X receptor signaling pathway as the top ranked network associated with the CBS(+/-) genotype, whereas xenobiotic metabolism and the NRF2-mediated oxidative stress response were associated with the high methionine diet. Our results show that hyperhomocysteinemia, whether caused by a genetic mutation or diet, alters the abundance of several liver proteins involved in homocysteine/methionine metabolism, the urea cycle, and antioxidant defense.
Journals
2009 EN
Alexander Y. Andreyev · Zhouxin Shen · Ziqiang Guan
+6 more
Compartmentalization of biological processes and the associated cellular components is crucial for cell function. Typically, the location of a component is revealed through a co-localization and/or co-purification with an organelle marker. Therefore, the identification of reliable markers is critical for a thorough understanding of cellular function and dysfunction. We fractionated macrophage-like RAW264.7 cells, both in the resting and endotoxin-activated states, into six fractions representing the major organelles/compartments: nuclei, mitochondria, cytoplasm, endoplasmic reticulum, and plasma membrane as well as an additional dense microsomal fraction. The identity of the first five of these fractions was confirmed via the distribution of conventional enzymatic markers. Through a quantitative liquid chromatography/mass spectrometry-based proteomics analysis of the fractions, we identified 50-member ensembles of marker proteins ("marker ensembles") specific for each of the corresponding organelles/compartments. Our analysis attributed 206 of the 250 marker proteins ( approximately 82%) to organelles that are consistent with the location annotations in the public domain (obtained using DAVID 2008, EntrezGene, Swiss-Prot, and references therein). Moreover, we were able to correct locations for a subset of the remaining proteins, thus proving the superior power of analysis using multiple organelles as compared with an analysis using one specific organelle. The marker ensembles were used to calculate the organelle composition of the six above mentioned subcellular fractions. Knowledge of the precise composition of these fractions can be used to calculate the levels of metabolites in the pure organelles. As a proof of principle, we applied these calculations to known mitochondria-specific lipids (cardiolipins and ubiquinones) and demonstrated their exclusive mitochondrial location. We speculate that the organelle-specific protein ensembles may be used to systematically redefine originally morphologically defined organelles as biochemical entities.
Journals
2009 EN
N. Leigh Anderson · Norman G. Anderson · Terry W. Pearson
+6 more
The lack of sensitive, specific, multiplexable assays for most human proteins is the major technical barrier impeding development of candidate biomarkers into clinically useful tests. Recent progress in mass spectrometry-based assays for proteotypic peptides, particularly those with specific affinity peptide enrichment, offers a systematic and economical path to comprehensive quantitative coverage of the human proteome. A complete suite of assays, e.g. two peptides from the protein product of each of the approximately 20,500 human genes (here termed the human Proteome Detection and Quantitation project), would enable rapid and systematic verification of candidate biomarkers and lay a quantitative foundation for subsequent efforts to define the larger universe of splice variants, post-translational modifications, protein-protein interactions, and tissue localization.