Lee, Shin-Haw, Hadipour-Lakmehsari, Sina, Kim, Da Hye, Di Paola, Michelle, Kuzmanov, Uros, Shah, Saumya, Lee, Joseph Jong-Hwan, Kislinger, Thomas, Sharma, Parveen 
ORCID: 0000-0002-5534-2417, Oudit, Gavin Y et al (show 1 more authors)
(2020)
Bioinformatic analysis of membrane and associated proteins in murine cardiomyocytes and human myocardium.
SCIENTIFIC DATA, 7 (1).
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Bioinformatic analysis of membrane and associated proteins in murine cardiomyocytes and human myocardium.pdf - Published version Download (5MB) | Preview |
Abstract
In the current study we examined several proteomic- and RNA-Seq-based datasets of cardiac-enriched, cell-surface and membrane-associated proteins in human fetal and mouse neonatal ventricular cardiomyocytes. By integrating available microarray and tissue expression profiles with MGI phenotypic analysis, we identified 173 membrane-associated proteins that are cardiac-enriched, conserved amongst eukaryotic species, and have not yet been linked to a 'cardiac' Phenotype-Ontology. To highlight the utility of this dataset, we selected several proteins to investigate more carefully, including FAM162A, MCT1, and COX20, to show cardiac enrichment, subcellular distribution and expression patterns in disease. We performed three-dimensional confocal imaging analysis to validate subcellular localization and expression in adult mouse ventricular cardiomyocytes. FAM162A, MCT1, and COX20 were expressed differentially at the transcriptomic and proteomic levels in multiple models of mouse and human heart diseases and may represent potential diagnostic and therapeutic targets for human dilated and ischemic cardiomyopathies. Altogether, we believe this comprehensive cardiomyocyte membrane proteome dataset will prove instrumental to future investigations aimed at characterizing heart disease markers and/or therapeutic targets for heart failure.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | Myocardium, Myocytes, Cardiac, Animals, Mice, Membrane Proteins, Proteome, Computational Biology, Transcriptome, Datasets as Topic, RNA-Seq |
| Depositing User: | Symplectic Admin |
| Date Deposited: | 08 Jan 2021 14:57 |
| Last Modified: | 18 Jan 2023 23:05 |
| DOI: | 10.1038/s41597-020-00762-1 |
| Related URLs: | |
| URI: | https://livrepository.liverpool.ac.uk/id/eprint/3112056 |
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