Proteome reference map and regulation network of neonatal rat cardiomyocyte

Li, Zijian; Liu, Ning; Han, Qinghua; Zhang, Youyi

doi:10.1038/aps.2011.86

Cited by 3 publications

(5 citation statements)

References 21 publications

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“…Thus the IPA was a very important tool for filtering our results and identifying possible links for biological systems, thus providing a better understanding of protein interactions between NS4B and cellular proteins such as CypA. IPA can identify both relevant cellular pathways and mechanisms through which proteins are involved, thus enabling attests for hypotheses and validation experiments for complex data. − …”

Section: Results and Discussionmentioning

confidence: 99%

Systems Biology Reveals NS4B-Cyclophilin A Interaction: A New Target to Inhibit YFV Replication

et al. 2017

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Yellow fever virus (YFV) replication is highly dependent on host cell factors. YFV NS4B is reported to be involved in viral replication and immune evasion. Here interactions between NS4B and human proteins were determined using a GST pull-down assay and analyzed using 1-DE and LC-MS/MS. We present a total of 207 proteins confirmed using Scaffold 3 Software. Cyclophilin A (CypA), a protein that has been shown to be necessary for the positive regulation of flavivirus replication, was identified as a possible NS4B partner. 59 proteins were found to be significantly increased when compared with a negative control, and CypA exhibited the greatest difference, with a 22-fold change. Fisher's exact test was significant for 58 proteins, and the p value of CypA was the most significant (0.000000019). The Ingenuity Systems software identified 16 pathways, and this analysis indicated sirolimus, an mTOR pathway inhibitor, as a potential inhibitor of CypA. Immunofluorescence and viral plaque assays showed a significant reduction in YFV replication using sirolimus and cyclosporine A (CsA) as inhibitors. Furthermore, YFV replication was strongly inhibited in cells treated with both inhibitors using reporter BHK-21-rep-YFV17D-LucNeoIres cells. Taken together, these data suggest that CypA-NS4B interaction regulates YFV replication. Finally, we present the first evidence that YFV inhibition may depend on NS4B-CypA interaction.

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Section: Results and Discussionmentioning

confidence: 99%

Systems Biology Reveals NS4B-Cyclophilin A Interaction: A New Target to Inhibit YFV Replication

et al. 2017

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“…In addition, induction of myocardial CTGF mRNA and protein in pigs with heart failure was not a decisive effector in fibrosis 19 . CTGF is a growth factor and has 4 modules, each of which interacts with different proteins and regulates many physiological processes 4 . Therefore, CTGF may also have an unknown function for maintaining cardiac physiological actions other than enhancement of fibrosis.…”

Section: Discussionmentioning

confidence: 99%

“…Analysis (IPA) software to predict cardiac functions by using two-dimensional electrophoresis data of protein extracts from cultured neonatal rat cardiomyocytes 4 and to identify target mRNAs involved in mouse cardiac hypertrophy 5 . IPA uses a database of the scientific literature to predict pathways, upstream regulators, and biological functions relevant to the uploaded data set and to provide biological interpretations and their statistical probabilities.…”

Section: Several Studies Have Utilized Ingenuity Pathwaymentioning

confidence: 99%

Cultured Neonatal Rat Cardiomyocytes Continue Beating Through Upregulation of CTGF Gene Expression

Mashimo

Ohno

2020

J Nippon Med Sch

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Background: Some cultured neonatal rat cardiomyocytes continue spontaneous beating even in serumfree medium. The present study explored the cause and genes responsible for this phenomenon.Methods: Ingenuity Pathway Analysis (IPA) software was used to analyze fold changes in gene expression in beating neonatal rat cardiomyocytes, as compared with non-beating cardiomyocytes, which were obtained from DNA microarray data of total RNA extracts of cardiomyocytes. To confirm the involvement of the 8 genes selected by IPA prediction, cellular protein abundances were determined by Western blot. The gene expression of connective tissue growth factor (CTGF) was substantially higher in beating cardiomyocytes than in non-beating cardiomyocytes; thus, CTGF protein content released from cardiomyocytes into the culture medium was examined.Results: IPA showed that the "Apelin Cardiac Fibroblast Signaling Pathway" was significantly inhibited and that microtubule dynamics and cytoskeleton organization were significantly activated. Each fluctuation in the cellular abundances of the 8 proteins in beating cardiomyocytes, as compared with nonbeating cardiomyocytes, was primarily in the same direction as that of gene expression. However, the cellular CTGF protein abundance as well as CTGF content released into the medium did not substantially differ between beating and non-beating cardiomyocytes. Conclusions:The present results suggest that the large increase in CTGF gene expression in beating cardiomyocytes is not a cause but a result of beating, which may provide a putative pathway for controlling beating. Beating is sustained by developed cardiomyofibrils and directly upregulates CTGF gene expression, which is not followed by CTGF protein synthesis.

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“…Large-scale protein-protein interaction maps provide new insights into protein functions, pathways, molecular machines and functional protein modules. 17 Moreover, studies have indicated that protein-protein interaction networks are vital to understanding disease specificity. 18 Recent advances in highthroughput methods for taking global measurements of protein levels from biological samples have driven the field of systems biology.…”

Section: Discussionmentioning

confidence: 99%

“…24 Recent studies have also shown that house-keeping proteins and tissue-specific proteins have different topological properties in the human protein-protein interaction network. [25][26][27][28] Several studies of protein interaction networks have focused on detecting highly connected protein modules which generally correspond to meaningful biological units such as protein complexes and functional modules. 29 However, biological networks including protein-protein interaction networks are generally very sparse.…”

Section: Discussionmentioning

confidence: 99%

Network generation enhances interpretation of proteomics data sets by a combination of two-dimensional polyacrylamide gel electrophoresis and matrix-assisted laser desorption/ionization-time of flight mass spectrometry

Wang

Zhang

Sun

et al. 2012

Analyst

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Recent advances in proteomic technologies have enabled us to create detailed protein-protein interaction maps in diseases. As the size of the interaction dataset increases, powerful computational methods are required in order to effectively interpret network models from large scale interactome data. In this study, we carried out comparative proteomics to construct and identify the proteins networks associated with hepatic injury (HI) which are largely unknown, as a case study. All proteins expressed were separated and identified by two-dimensional gel electrophoresis (2-DE) and matrix-assisted laser desorption/ionization time-of-flight-time-of-flight mass spectrometry (MALDI-TOF/TOF MS). Protein-interacting networks and pathways were mapped using STRING analysis program. We have performed for the first time a comprehensive profiling of changes in protein expression of HI rats, to uncover the networks altered by treated with CCl(4). Identification of fifteen spots (seven over-expressed and eight under-expressed) were established by MALDI-TOF/TOF MS. These proteins were subjected to functional pathway analysis using STRING software for better understanding of the biological context of the identified proteins. It suggested that modulation of multiple vital physiological pathways including DNA repair process, cell apoptosis, oxidation reduction, signal transduction, metabolic process, intracellular signaling cascade, regulation of biological processes, cell communication, regulation of cellular process, and molecular transport. In summary, the present study provides the first protein-interacting network maps and novel insights into the biological responses and potential pathways of HI. The generation of protein interaction networks clearly enhances the interpretation of proteomic data, particularly in respect of understanding molecular mechanisms of panel protein biomarkers.

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Proteome reference map and regulation network of neonatal rat cardiomyocyte

Cited by 3 publications

References 21 publications

Systems Biology Reveals NS4B-Cyclophilin A Interaction: A New Target to Inhibit YFV Replication

Systems Biology Reveals NS4B-Cyclophilin A Interaction: A New Target to Inhibit YFV Replication

Cultured Neonatal Rat Cardiomyocytes Continue Beating Through Upregulation of CTGF Gene Expression

Network generation enhances interpretation of proteomics data sets by a combination of two-dimensional polyacrylamide gel electrophoresis and matrix-assisted laser desorption/ionization-time of flight mass spectrometry

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