FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2109331497> ?p ?o ?g. }

• W2109331497 endingPage "533" @default.
• W2109331497 startingPage "519" @default.
• W2109331497 abstract "Defective mobilization of Ca2+ by cardiomyocytes can lead to cardiac insufficiency, but the causative mechanisms leading to congestive heart failure (HF) remain unclear. In the present study we performed exhaustive global proteomics surveys of cardiac ventricle isolated from a mouse model of cardiomyopathy overexpressing a phospholamban mutant, R9C (PLN-R9C), and exhibiting impaired Ca2+ handling and death at 24 weeks and compared them with normal control littermates. The relative expression patterns of 6190 high confidence proteins were monitored by shotgun tandem mass spectrometry at 8, 16, and 24 weeks of disease progression. Significant differential abundance of 593 proteins was detected. These proteins mapped to select biological pathways such as endoplasmic reticulum stress response, cytoskeletal remodeling, and apoptosis and included known biomarkers of HF (e.g. brain natriuretic peptide/atrial natriuretic factor and angiotensin-converting enzyme) and other indicators of presymptomatic functional impairment. These altered proteomic profiles were concordant with cognate mRNA patterns recorded in parallel using high density mRNA microarrays, and top candidates were validated by RT-PCR and Western blotting. Mapping of our highest ranked proteins against a human diseased explant and to available data sets indicated that many of these proteins could serve as markers of disease. Indeed we showed that several of these proteins are detectable in mouse and human plasma and display differential abundance in the plasma of diseased mice and affected patients. These results offer a systems-wide perspective of the dynamic maladaptions associated with impaired Ca2+ homeostasis that perturb myocyte function and ultimately converge to cause HF. Defective mobilization of Ca2+ by cardiomyocytes can lead to cardiac insufficiency, but the causative mechanisms leading to congestive heart failure (HF) remain unclear. In the present study we performed exhaustive global proteomics surveys of cardiac ventricle isolated from a mouse model of cardiomyopathy overexpressing a phospholamban mutant, R9C (PLN-R9C), and exhibiting impaired Ca2+ handling and death at 24 weeks and compared them with normal control littermates. The relative expression patterns of 6190 high confidence proteins were monitored by shotgun tandem mass spectrometry at 8, 16, and 24 weeks of disease progression. Significant differential abundance of 593 proteins was detected. These proteins mapped to select biological pathways such as endoplasmic reticulum stress response, cytoskeletal remodeling, and apoptosis and included known biomarkers of HF (e.g. brain natriuretic peptide/atrial natriuretic factor and angiotensin-converting enzyme) and other indicators of presymptomatic functional impairment. These altered proteomic profiles were concordant with cognate mRNA patterns recorded in parallel using high density mRNA microarrays, and top candidates were validated by RT-PCR and Western blotting. Mapping of our highest ranked proteins against a human diseased explant and to available data sets indicated that many of these proteins could serve as markers of disease. Indeed we showed that several of these proteins are detectable in mouse and human plasma and display differential abundance in the plasma of diseased mice and affected patients. These results offer a systems-wide perspective of the dynamic maladaptions associated with impaired Ca2+ homeostasis that perturb myocyte function and ultimately converge to cause HF. Cardiomyopathies of diverse etiology impair cardiac muscle function and frequently progress to a convergence point where they induce heart dilatation and overt failure. Although HF 1The abbreviations used are: HF, heart failure; PLN, phospholamban; BNP, brain natriuretic peptide; ANF, atrial natriuretic factor; ACE, angiotensin-converting enzyme; FDR, false discovery rate; GO, Gene Ontology; DPY, dihydropyrimidinase; CIA, co-inertia analysis; PDI, protein-disulfide isomerase; DESM, desmin; IQGAP, Ras GTPase-activating-like protein; CHOP, CIEBP homologous protein; CALU, calumenin; CRTC, calreticulin; POST, periostin; FLN, filamin; ENPL, endoplasmin; PLMN, plasminogen; PLSL, L-plastin; SPTA, spectrin A; SPTB, spectrin B; RTN, reticulocalbin; VIME, vimentin. is a major source of global morbidity and death in the developed world (1Thom T. Haase N. Rosamond W. Howard V.J. Rumsfeld J. Manolio T. Zheng Z.J. Flegal K. O'Donnell C. Kittner S. Lloyd-Jones D. Goff Jr., D.C. Hong Y. Adams R. Friday G. Furie K. Gorelick P. Kissela B. Marler J. Meigs J. Roger V. Sidney S. Sorlie P. Steinberger J. Wasserthiel-Smoller S. Wilson M. Wolf P. Heart disease and stroke statistics—2006 update: a report from the American Heart Association Statistics Committee and Stroke Statistics Subcommittee.Circulation. 2006; 113: e85-e151Crossref PubMed Scopus (2646) Google Scholar 1The abbreviations used are: HF, heart failure; PLN, phospholamban; BNP, brain natriuretic peptide; ANF, atrial natriuretic factor; ACE, angiotensin-converting enzyme; FDR, false discovery rate; GO, Gene Ontology; DPY, dihydropyrimidinase; CIA, co-inertia analysis; PDI, protein-disulfide isomerase; DESM, desmin; IQGAP, Ras GTPase-activating-like protein; CHOP, CIEBP homologous protein; CALU, calumenin; CRTC, calreticulin; POST, periostin; FLN, filamin; ENPL, endoplasmin; PLMN, plasminogen; PLSL, L-plastin; SPTA, spectrin A; SPTB, spectrin B; RTN, reticulocalbin; VIME, vimentin.), afflicted patients are typically diagnosed with end stage disease when few effective avenues for restorative intervention remain and clinical outcomes are poor (1Thom T. Haase N. Rosamond W. Howard V.J. Rumsfeld J. Manolio T. Zheng Z.J. Flegal K. O'Donnell C. Kittner S. Lloyd-Jones D. Goff Jr., D.C. Hong Y. Adams R. Friday G. Furie K. Gorelick P. Kissela B. Marler J. Meigs J. Roger V. Sidney S. Sorlie P. Steinberger J. Wasserthiel-Smoller S. Wilson M. Wolf P. Heart disease and stroke statistics—2006 update: a report from the American Heart Association Statistics Committee and Stroke Statistics Subcommittee.Circulation. 2006; 113: e85-e151Crossref PubMed Scopus (2646) Google Scholar). Therefore, innovative preventive and therapeutic measures are needed urgently for more effective early detection, stratification, and treatment of at-risk patients (1Thom T. Haase N. Rosamond W. Howard V.J. Rumsfeld J. Manolio T. Zheng Z.J. Flegal K. O'Donnell C. Kittner S. Lloyd-Jones D. Goff Jr., D.C. Hong Y. Adams R. Friday G. Furie K. Gorelick P. Kissela B. Marler J. Meigs J. Roger V. Sidney S. Sorlie P. Steinberger J. Wasserthiel-Smoller S. Wilson M. Wolf P. Heart disease and stroke statistics—2006 update: a report from the American Heart Association Statistics Committee and Stroke Statistics Subcommittee.Circulation. 2006; 113: e85-e151Crossref PubMed Scopus (2646) Google Scholar). Although considerable progress has been made in the understanding of the mechanistic basis for certain aspects of cardiac dysfunction (2Molkentin J.D. Lu J.R. Antos C.L. Markham B. Richardson J. Robbins J. Grant S.R. Olson E.N. A calcineurin-dependent transcriptional pathway for cardiac hypertrophy.Cell. 1998; 93: 215-228Abstract Full Text Full Text PDF PubMed Scopus (2182) Google Scholar, 3Huss J.M. Kelly D.P. Mitochondrial energy metabolism in heart failure: a question of balance.J. Clin. Investig. 2005; 115: 547-555Crossref PubMed Scopus (389) Google Scholar, 4Dorn II, G.W. Force T. Protein kinase cascades in the regulation of cardiac hypertrophy.J. Clin. Investig. 2005; 115: 527-537Crossref PubMed Scopus (526) Google Scholar, 5Morita H. Seidman J. Seidman C.E. Genetic causes of human heart failure.J. Clin. Investig. 2005; 115: 518-526Crossref PubMed Scopus (210) Google Scholar, 6Benjamin I.J. Schneider M.D. Learning from failure: congestive heart failure in the postgenomic age.J. Clin. Investig. 2005; 115: 495-499Crossref PubMed Scopus (55) Google Scholar), a more complete understanding is required of the key molecular players and biochemical maladaptations associated with disease progression, particularly at the earliest stages of cardiomyopathy that occur prior to clinical presentation. Previously we reported that an inherited human dilated cardiomyopathy resulted from the conversion of Arg-9 to Cys in the human phospholamban (PLN) gene (PLN-R9C) (7Schmitt J.P. Kamisago M. Asahi M. Li G.H. Ahmad F. Mende U. Kranias E.G. MacLennan D.H. Seidman J.G. Seidman C.E. Dilated cardiomyopathy and heart failure caused by a mutation in phospholamban.Science. 2003; 299: 1410-1413Crossref PubMed Scopus (481) Google Scholar). The onset of dilated cardiomyopathy in affected patients typically commenced during adolescence followed by progressive deterioration in cardiac function leading to crisis and mortality (7Schmitt J.P. Kamisago M. Asahi M. Li G.H. Ahmad F. Mende U. Kranias E.G. MacLennan D.H. Seidman J.G. Seidman C.E. Dilated cardiomyopathy and heart failure caused by a mutation in phospholamban.Science. 2003; 299: 1410-1413Crossref PubMed Scopus (481) Google Scholar). A transgenic mouse model of this mutation showed a remarkably similar cardiac phenotype (7Schmitt J.P. Kamisago M. Asahi M. Li G.H. Ahmad F. Mende U. Kranias E.G. MacLennan D.H. Seidman J.G. Seidman C.E. Dilated cardiomyopathy and heart failure caused by a mutation in phospholamban.Science. 2003; 299: 1410-1413Crossref PubMed Scopus (481) Google Scholar) with the afflicted mice presenting with early onset dilated cardiomyopathy characterized by decreased cardiac contractility and premature death. In the present study, we used exhaustive gel-free protein profiling and parallel microarray-based mRNA screening techniques to examine temporal changes in the global expression patterns during disease progression in the cardiac ventricular muscle of R9C mutant animals as compared with age-matched healthy controls. Using a p value of 0.05, we deduced significant changes in the levels of 593 of 6190 proteins identified with high confidence. We then used mRNA microarray data together with extensive RT-PCR and immunoblotting for further validation of the 40 proteins that were calculated to be below an empirically corrected false discovery rate (FDR). Statistically significant over-representation in select Gene Ontology functional categories (GO terms) was detected among both the up- and down-regulated proteins. These GO terms indicated perturbations in cytoskeletal and calcium-binding proteins, alterations in endoplasmic reticulum (ER) stress and apoptosis pathways, and shifts in energy metabolism. We confirmed the activation of apoptosis, and we explored the potential for establishing informative biomarkers of heart disease among the most markedly altered proteins. Overall we established an insightful time course projection of the dynamically changing molecular landscape associated with early stage myocyte dysfunction, midstage cardiac dilatation, and overt end stage HF. The entire processed data set and supporting annotated spectra evidence are fully accessible via a dedicated Website as a platform to support further basic and clinically driven cardiac investigations. The transgenic phospholamban R9C mutant mice were described previously (7Schmitt J.P. Kamisago M. Asahi M. Li G.H. Ahmad F. Mende U. Kranias E.G. MacLennan D.H. Seidman J.G. Seidman C.E. Dilated cardiomyopathy and heart failure caused by a mutation in phospholamban.Science. 2003; 299: 1410-1413Crossref PubMed Scopus (481) Google Scholar). Male and female mice were analyzed at 8, 16, and 24 weeks by M-mode and Doppler echocardiography for non-invasive assessment of left ventricular function and dimensions using methods described previously (8Zvaritch E. Backx P.H. Jirik F. Kimura Y. de Leon S. Schmidt A.G. Hoit B.D. Lester J.W. Kranias E.G. MacLennan D.H. The transgenic expression of highly inhibitory monomeric forms of phospholamban in mouse heart impairs cardiac contractility.J. Biol. Chem. 2000; 275: 14985-14991Abstract Full Text Full Text PDF PubMed Scopus (72) Google Scholar, 9Crackower M.A. Oudit G.Y. Kozieradzki I. Sarao R. Sun H. Sasaki T. Hirsch E. Suzuki A. Shioi T. Irie-Sasaki J. Sah R. Cheng H.Y. Rybin V.O. Lembo G. Fratta L. Oliveira-dos-Santos A.J. Benovic J.L. Kahn C.R. Izumo S. Steinberg S.F. Wymann M.P. Backx P.H. Penninger J.M. Regulation of myocardial contractility and cell size by distinct PI3K-PTEN signaling pathways.Cell. 2002; 110: 737-749Abstract Full Text Full Text PDF PubMed Scopus (520) Google Scholar, 10Crackower M.A. Sarao R. Oudit G.Y. Yagil C. Kozieradzki I. Scanga S.E. Oliveira-dos-Santos A.J. da Costa J. Zhang L. Pei Y. Scholey J. Ferrario C.M. Manoukian A.S. Chappell M.C. Backx P.H. Yagil Y. Penninger J.M. Angiotensin-converting enzyme 2 is an essential regulator of heart function.Nature. 2002; 417: 822-828Crossref PubMed Scopus (1338) Google Scholar, 11Oudit G.Y. Trivieri M.G. Khaper N. Husain T. Wilson G.J. Liu P. Sole M.J. Backx P.H. Taurine supplementation reduces oxidative stress and improves cardiovascular function in an iron-overload murine model.Circulation. 2004; 109: 1877-1885Crossref PubMed Scopus (179) Google Scholar, 12Gramolini A.O. Trivieri M.G. Oudit G.Y. Kislinger T. Li W. Patel M.M. Emili A. Kranias E.G. Backx P.H. Maclennan D.H. Cardiac-specific overexpression of sarcolipin in phospholamban null mice impairs myocyte function that is restored by phosphorylation.Proc. Natl. Acad. Sci. U. S. A. 2006; 103: 2446-2451Crossref PubMed Scopus (65) Google Scholar). Immediately prior to the preparation of cardiac tissue samples, at least six mice in each category were CO2-asphyxiated, and the ventricle muscle was collected rapidly and rinsed in ice-cold PBS. For pathology and histological analyses, the hearts were washed extensively in ice-cold PBS and fixed immediately with ice-cold 4% paraformaldehyde in PBS. Cardiomyocytes were isolated, and intracellular Ca2+ measurements were performed as described previously (8Zvaritch E. Backx P.H. Jirik F. Kimura Y. de Leon S. Schmidt A.G. Hoit B.D. Lester J.W. Kranias E.G. MacLennan D.H. The transgenic expression of highly inhibitory monomeric forms of phospholamban in mouse heart impairs cardiac contractility.J. Biol. Chem. 2000; 275: 14985-14991Abstract Full Text Full Text PDF PubMed Scopus (72) Google Scholar, 9Crackower M.A. Oudit G.Y. Kozieradzki I. Sarao R. Sun H. Sasaki T. Hirsch E. Suzuki A. Shioi T. Irie-Sasaki J. Sah R. Cheng H.Y. Rybin V.O. Lembo G. Fratta L. Oliveira-dos-Santos A.J. Benovic J.L. Kahn C.R. Izumo S. Steinberg S.F. Wymann M.P. Backx P.H. Penninger J.M. Regulation of myocardial contractility and cell size by distinct PI3K-PTEN signaling pathways.Cell. 2002; 110: 737-749Abstract Full Text Full Text PDF PubMed Scopus (520) Google Scholar, 10Crackower M.A. Sarao R. Oudit G.Y. Yagil C. Kozieradzki I. Scanga S.E. Oliveira-dos-Santos A.J. da Costa J. Zhang L. Pei Y. Scholey J. Ferrario C.M. Manoukian A.S. Chappell M.C. Backx P.H. Yagil Y. Penninger J.M. Angiotensin-converting enzyme 2 is an essential regulator of heart function.Nature. 2002; 417: 822-828Crossref PubMed Scopus (1338) Google Scholar, 11Oudit G.Y. Trivieri M.G. Khaper N. Husain T. Wilson G.J. Liu P. Sole M.J. Backx P.H. Taurine supplementation reduces oxidative stress and improves cardiovascular function in an iron-overload murine model.Circulation. 2004; 109: 1877-1885Crossref PubMed Scopus (179) Google Scholar, 13Trivieri M.G. Oudit G.Y. Sah R. Kerfant B.G. Sun H. Gramolini A.O. Pan Y. Wickenden A.D. Croteau W. Morreale de Escobar G. Pekhletski R. St Germain D. Maclennan D.H. Backx P.H. Cardiac-specific elevations in thyroid hormone enhance contractility and prevent pressure overload-induced cardiac dysfunction.Proc. Natl. Acad. Sci. U. S. A. 2006; 103: 6043-6048Crossref PubMed Scopus (86) Google Scholar). Organellar protein fractions were extracted from pooled ventricle tissue as described previously (14Kislinger T. Rahman K. Radulovic D. Cox B. Rossant J. Emili A. PRISM, a generic large scale proteomic investigation strategy for mammals.Mol. Cell. Proteomics. 2003; 2: 96-106Abstract Full Text Full Text PDF PubMed Scopus (147) Google Scholar, 15Kislinger T. Gramolini A.O. MacLennan D.H. Emili A. Multidimensional protein identification technology (MudPIT): technical overview of a profiling method optimized for the comprehensive proteomic investigation of normal and diseased heart tissue.J. Am. Soc. Mass. Spectrom. 2005; 16: 1207-1220Crossref PubMed Scopus (119) Google Scholar). Briefly ventricle tissue from four to six mice was combined and homogenized in a Dounce homogenizer in ice-cold lysis buffer (250 mm sucrose, 50 mm Tris-HCl (pH 7.4), 5 mm MgCl2, 1 mm DTT, 1 mm PMSF) using a tight fitting glass pestle. The lysate was cleared of debris by tabletop centrifugation at 800 × g for 15 min. Mitochondrial and microsomal fractions were isolated from the supernatant by further centrifugation at 8000 × g and 100,000 × g, respectively, and the supernatant served as the soluble cytosolic fraction. Protein aliquots (100 μg) were precipitated, reduced, alkylated, and digested sequentially with endoproteinase Lys-C and trypsin as reported previously (15Kislinger T. Gramolini A.O. MacLennan D.H. Emili A. Multidimensional protein identification technology (MudPIT): technical overview of a profiling method optimized for the comprehensive proteomic investigation of normal and diseased heart tissue.J. Am. Soc. Mass. Spectrom. 2005; 16: 1207-1220Crossref PubMed Scopus (119) Google Scholar, 16Kislinger T. Cox B. Kannan A. Chung C. Hu P. Ignatchenko A. Scott M.S. Gramolini A.O. Morris Q. Hallett M.T. Rossant J. Hughes T.R. Frey B. Emili A. Global survey of organ and organelle protein expression in mouse: combined proteomic and transcriptomic profiling.Cell. 2006; 125: 173-186Abstract Full Text Full Text PDF PubMed Scopus (398) Google Scholar) Comprehensive gel-free shotgun sequencing of reduced, alkylated, and enzymatically digested protein fractions was performed essentially as described previously (15Kislinger T. Gramolini A.O. MacLennan D.H. Emili A. Multidimensional protein identification technology (MudPIT): technical overview of a profiling method optimized for the comprehensive proteomic investigation of normal and diseased heart tissue.J. Am. Soc. Mass. Spectrom. 2005; 16: 1207-1220Crossref PubMed Scopus (119) Google Scholar, 16Kislinger T. Cox B. Kannan A. Chung C. Hu P. Ignatchenko A. Scott M.S. Gramolini A.O. Morris Q. Hallett M.T. Rossant J. Hughes T.R. Frey B. Emili A. Global survey of organ and organelle protein expression in mouse: combined proteomic and transcriptomic profiling.Cell. 2006; 125: 173-186Abstract Full Text Full Text PDF PubMed Scopus (398) Google Scholar, 17Gramolini A.O. Kislinger T. Liu P. MacLennan D.H. Emili A. Analyzing the cardiac muscle proteome by liquid chromatography mass spectrometry-based expression proteomics.Methods Mol. Biol. 2006; 357: 15-31Google Scholar). Briefly the peptide mixtures were solid phase-extracted, acidified with formic acid, and loaded manually onto biphasic 100-μm-inner diameter microcapillary fused silica columns packed sequentially with strong cation exchange beads (Partisphere, Whatman, Clifton, NJ) and reverse phase resin (Zorbax Eclipse XDB-C18, Agilent Technologies, Mississauga, Ontario, Canada). The columns were placed in line with a quaternary HPLC pump interfaced using electrospray ionization to an LTQ linear ion trap mass spectrometer (Thermo Finnigan, San Jose, CA). The bound peptides were eluted using a 12-step × 100-min salt/water/acetonitrile gradient (15Kislinger T. Gramolini A.O. MacLennan D.H. Emili A. Multidimensional protein identification technology (MudPIT): technical overview of a profiling method optimized for the comprehensive proteomic investigation of normal and diseased heart tissue.J. Am. Soc. Mass. Spectrom. 2005; 16: 1207-1220Crossref PubMed Scopus (119) Google Scholar, 16Kislinger T. Cox B. Kannan A. Chung C. Hu P. Ignatchenko A. Scott M.S. Gramolini A.O. Morris Q. Hallett M.T. Rossant J. Hughes T.R. Frey B. Emili A. Global survey of organ and organelle protein expression in mouse: combined proteomic and transcriptomic profiling.Cell. 2006; 125: 173-186Abstract Full Text Full Text PDF PubMed Scopus (398) Google Scholar). Precursor ions (400–2000 m/z) were subjected to data-dependent, collision-induced dissociation with dynamic exclusion enabled. The resultant ∼12.5 million acquired MS/MS spectra were cross-matched against a compilation of 29,051 annotated UniProt mouse (Mus musculus) protein sequences downloaded from the European Bioinformatics Institute on March 11, 2004 using a distributed version of the SEQUEST search algorithm (SEQUEST-PVM version 27 (revision 9) (1993); peak lists were automatically generated using the embedded ExtractMS script with default parameter settings) (18Eng J.K. McCormack A.L. Yates J.R. An approach to correlate tandem mass spectral data of peptides with amino acid sequences in a protein database.J. Am. Soc. Mass Spectrom. 1994; 5: 976-989Crossref PubMed Scopus (5315) Google Scholar). Precursor mass tolerance was set to 3 Da (with daughter mass ion tolerance set to the default of 0), enabling fully tryptic enzyme status, single site missed cleavages, and a static chemical modification of +57 amu on cysteine (carboxyamidomethylation). The statistical probability of each primary match was assessed using the STATQUEST algorithm (15Kislinger T. Gramolini A.O. MacLennan D.H. Emili A. Multidimensional protein identification technology (MudPIT): technical overview of a profiling method optimized for the comprehensive proteomic investigation of normal and diseased heart tissue.J. Am. Soc. Mass. Spectrom. 2005; 16: 1207-1220Crossref PubMed Scopus (119) Google Scholar, 16Kislinger T. Cox B. Kannan A. Chung C. Hu P. Ignatchenko A. Scott M.S. Gramolini A.O. Morris Q. Hallett M.T. Rossant J. Hughes T.R. Frey B. Emili A. Global survey of organ and organelle protein expression in mouse: combined proteomic and transcriptomic profiling.Cell. 2006; 125: 173-186Abstract Full Text Full Text PDF PubMed Scopus (398) Google Scholar). To minimize false positives, protein identifications were accepted if the candidates had a minimum of three high confidence (99%+ probability) supporting spectra that matched to at least two unique (unambiguous) peptides. To determine the FDR, we performed an empirical confidence test by searching approximately half of the spectra against a decoy database consisting of fully inverted protein sequences appended to the original native database entries. Applying the same filter criteria, the proportion of decoy (reverse) matches was found to be 0.0146% at the peptide level (50 reverse and 342,740 native peptide matches) and 0.49% at the protein level (eight reverse and 1611 native protein matches). Hence we estimated the FDR rate across the entire data set at less than 1%, which is comparable to our FDR reported previously in Kislinger et al. (16Kislinger T. Cox B. Kannan A. Chung C. Hu P. Ignatchenko A. Scott M.S. Gramolini A.O. Morris Q. Hallett M.T. Rossant J. Hughes T.R. Frey B. Emili A. Global survey of organ and organelle protein expression in mouse: combined proteomic and transcriptomic profiling.Cell. 2006; 125: 173-186Abstract Full Text Full Text PDF PubMed Scopus (398) Google Scholar). The total combined number of high confidence spectral counts per protein was summed across subcellular fractions as an estimate of relative protein abundance and possible differential expression between the R9C- and control-derived samples (16Kislinger T. Cox B. Kannan A. Chung C. Hu P. Ignatchenko A. Scott M.S. Gramolini A.O. Morris Q. Hallett M.T. Rossant J. Hughes T.R. Frey B. Emili A. Global survey of organ and organelle protein expression in mouse: combined proteomic and transcriptomic profiling.Cell. 2006; 125: 173-186Abstract Full Text Full Text PDF PubMed Scopus (398) Google Scholar, 19Liu H. Sadygov R.G. Yates III, J.R. A model for random sampling and estimation of relative protein abundance in shotgun proteomics.Anal. Chem. 2004; 76: 4193-4201Crossref PubMed Scopus (2043) Google Scholar). Differences in protein levels between diseased and wild-type samples recorded between the 137 different experimental runs can represent biologically relevant differences in protein expression but can also contain bias and noise. To account for spurious variance, the data were normalized. The data generated within each experiment were first separated into an equivalent number (100) of bins based on the observed spectral count value distribution. Each bin, for all the runs, was then normalized by local polynomial regression fitting (Lowess) (20Cleveland W.S. Grosse E. Shyu W.M. Local regression models.in: Chambers J.M. Hastie T.J. Statistical Models in S. Wadsworth & Brooks/Cole, Pacific Grove, CA1992: 309-376Google Scholar) to adjust for differences in the spectral counts obtained for each individual protein in relation to the total number of overall spectra obtained for a given individual sample. The aim of this normalization technique was to reduce the inherent variability that exists between different experiments, different spectral count abundances, and different sample complexities. After normalizing the data, to detect proteins exhibiting differential levels between the control and diseased state, we constructed two linear models. The first modeled both the control and disease states as well as the time (8, 16, and 24 weeks) and localization (cytosol, microsome, mitochondria I, and mitochondria II) as separable parameters, whereas the second model examined only time (8, 16, and 24 weeks) and localization (cytosol, microsome, mitochondria I, and mitochondria II) as discriminate factors. The output of the two models was compared using analysis of variance with the null hypothesis being that there is no difference, and a low p value indicated substantive discrepancy between the results of the two models, implying that the disease state was a significant determinant of the observed protein levels. To identify those proteins exhibiting a significant change in relative protein abundance as a function of disease progression, we ranked the complete set of detectable proteins based on their computed p values, a subset (593) of which exhibited nominal p values <0.05. To account for multiple hypothesis testing from the above model, the p values were then subjected to FDR correction using the Benjamini-Hochberg calculation (21Benjamin I.J. Hochberg Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing.J. R. Stat. Soc. 1995; 57: 289-300Google Scholar, 22Hochberg Y. Benjamini Y. More powerful procedures for multiple significance testing.Stat. Med. 1990; 9: 811-818Crossref PubMed Scopus (1935) Google Scholar). This generated a final subset of 40 proteins with corrected p values <0.05 for the R9C mouse model that are reported in supplemental Table 4. The proteomics data are reported as peptides identified, whether these peptides are unique to the protein, the raw total number of matched spectra, the normalized number of matched spectra, p values, and corrected p values and are sorted according to the corrected p values. Microarray-based global mRNA profiling experiments were performed using the Affymetrix Mouse 430 2.0 full-genome array chips. Protein accessions were cross-mapped to the corresponding Affymetrix probe sets. Co-inertia analysis is a multivariate method that identifies trends or co-relationships in multiple data sets and was performed to explore the covariance between the proteomics and microarray data sets essentially as described previously (23Culhane A.C. Perriere G. Higgins D.G. Cross-platform comparison and visualisation of gene expression data using co-inertia analysis.BMC Bioinformatics. 2003; 4: 59Crossref PubMed Scopus (109) Google Scholar). The Bayesian probabilistic assessment was performed as described previously (16Kislinger T. Cox B. Kannan A. Chung C. Hu P. Ignatchenko A. Scott M.S. Gramolini A.O. Morris Q. Hallett M.T. Rossant J. Hughes T.R. Frey B. Emili A. Global survey of organ and organelle protein expression in mouse: combined proteomic and transcriptomic profiling.Cell. 2006; 125: 173-186Abstract Full Text Full Text PDF PubMed Scopus (398) Google Scholar, 24Cox B. Kislinger T. Wigle D.A. Kannan A. Brown K. Okubo T. Hogan B. Jurisica I. Frey B. Rossant J. Emili A. Integrated proteomic and transcriptomic profiling of mouse lung development and Nmyc target genes.Mol. Syst. Biol. 2007; 3: 109Crossref PubMed Scopus (62) Google Scholar). Total RNA was extracted from isolated ventricular tissue using TRIzol and subjected to RT-PCR essentially as described previously (25Gramolini A.O. Burton E.A. Tinsley J.M. Ferns M.J. Cartaud A. Cartaud J. Davies K.E. Lunde J.A. Jasmin B.J. Muscle and neural isoforms of agrin increase utrophin expression in cultured myotubes via a transcriptional regulatory mechanism.J. Biol. Chem. 1998; 273: 736-743Abstract Full Text Full Text PDF PubMed Scopus (81) Google Scholar, 26Gramolini A.O. Jasmin B.J. Expression of the utrophin gene during myogenic differentiation.Nucleic Acids Res. 1999; 27: 3603-3609Crossref PubMed Scopus (39) Google Scholar). Primer sets were designed using WebPrimer 2.0 and purchased from AGTC Corp. (Toronto, Ontario, Canada). A complete set of primer sequences is provided in supplemental Table 4. Immunoblot analyses were performed using standard SDS-PAGE chemiluminescent procedures. Blots were processed using commercially available antibodies: mouse monoclonal to HSP47 (13510, Abcam, Cambridge, MA), mouse monoclonal to periostin (14041, Abcam), rabbit polyclonal to protein-disulfide isomerase (539229, Calbiochem), mouse monoclonal to protein-disulfide isomerase (MA3-019, Affinity Bioreagents, Golden, CO), rabbit polyclonal to Filamin A (4762, Cell Signaling Technologies, Danvers, MA)," @default.
• W2109331497 created "2016-06-24" @default.
• W2109331497 creator A5003361977 @default.
• W2109331497 creator A5005593143 @default.
• W2109331497 creator A5010447401 @default.
• W2109331497 creator A5015881464 @default.
• W2109331497 creator A5016151180 @default.
• W2109331497 creator A5021544196 @default.
• W2109331497 creator A5024656783 @default.
• W2109331497 creator A5026138153 @default.
• W2109331497 creator A5029478687 @default.
• W2109331497 creator A5041682013 @default.
• W2109331497 creator A5043796863 @default.
• W2109331497 creator A5045991393 @default.
• W2109331497 creator A5060081041 @default.
• W2109331497 creator A5060705328 @default.
• W2109331497 creator A5068839871 @default.
• W2109331497 creator A5072817001 @default.
• W2109331497 creator A5075504588 @default.
• W2109331497 creator A5076978787 @default.
• W2109331497 creator A5084723784 @default.
• W2109331497 creator A5085059825 @default.
• W2109331497 creator A5090607558 @default.
• W2109331497 creator A5091170051 @default.
• W2109331497 date "2008-03-01" @default.
• W2109331497 modified "2023-10-18" @default.
• W2109331497 title "Comparative Proteomics Profiling of a Phospholamban Mutant Mouse Model of Dilated Cardiomyopathy Reveals Progressive Intracellular Stress Responses" @default.
• W2109331497 cites W1485297825 @default.
• W2109331497 cites W1591652640 @default.
• W2109331497 cites W1597678601 @default.
• W2109331497 cites W1966976216 @default.
• W2109331497 cites W1969782660 @default.
• W2109331497 cites W1976824216 @default.
• W2109331497 cites W1977184198 @default.
• W2109331497 cites W1992217162 @default.
• W2109331497 cites W1997504014 @default.
• W2109331497 cites W1998990808 @default.
• W2109331497 cites W2002806885 @default.
• W2109331497 cites W2005818888 @default.
• W2109331497 cites W2006211612 @default.
• W2109331497 cites W2018183883 @default.
• W2109331497 cites W2022525198 @default.
• W2109331497 cites W2025672718 @default.
• W2109331497 cites W2026465178 @default.
• W2109331497 cites W2027418897 @default.
• W2109331497 cites W2031301713 @default.
• W2109331497 cites W2031884895 @default.
• W2109331497 cites W2034931158 @default.
• W2109331497 cites W2041582877 @default.
• W2109331497 cites W2043113652 @default.
• W2109331497 cites W2045143786 @default.
• W2109331497 cites W2045234988 @default.
• W2109331497 cites W2047757567 @default.
• W2109331497 cites W2051304606 @default.
• W2109331497 cites W2051893563 @default.
• W2109331497 cites W2053249961 @default.
• W2109331497 cites W2055224057 @default.
• W2109331497 cites W2058125715 @default.
• W2109331497 cites W2065417808 @default.
• W2109331497 cites W2065719234 @default.
• W2109331497 cites W2068273299 @default.
• W2109331497 cites W2068459121 @default.
• W2109331497 cites W2068671266 @default.
• W2109331497 cites W2073101333 @default.
• W2109331497 cites W2079634451 @default.
• W2109331497 cites W2082516237 @default.
• W2109331497 cites W2089279418 @default.
• W2109331497 cites W2096087960 @default.
• W2109331497 cites W2097553067 @default.
• W2109331497 cites W2120604708 @default.
• W2109331497 cites W2123106337 @default.
• W2109331497 cites W2123119225 @default.
• W2109331497 cites W2123830992 @default.
• W2109331497 cites W2126795450 @default.
• W2109331497 cites W2128822255 @default.
• W2109331497 cites W2129777487 @default.
• W2109331497 cites W2130326770 @default.
• W2109331497 cites W2133812508 @default.
• W2109331497 cites W2134774224 @default.
• W2109331497 cites W2136954841 @default.
• W2109331497 cites W2140453892 @default.
• W2109331497 cites W2140487984 @default.
• W2109331497 cites W2149199989 @default.
• W2109331497 cites W2153340607 @default.
• W2109331497 cites W2153904259 @default.
• W2109331497 cites W2156355974 @default.
• W2109331497 cites W2156433522 @default.
• W2109331497 cites W2159505514 @default.
• W2109331497 cites W2165064047 @default.
• W2109331497 cites W2171215275 @default.
• W2109331497 cites W2171247775 @default.
• W2109331497 cites W2328950147 @default.
• W2109331497 cites W4248136323 @default.
• W2109331497 doi "https://doi.org/10.1074/mcp.m700245-mcp200" @default.
• W2109331497 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/18056057" @default.
• W2109331497 hasPublicationYear "2008" @default.
• W2109331497 type Work @default.
• W2109331497 sameAs 2109331497 @default.

• next