Cargando…

Bioengineering Silicon Quantum Dot Theranostics using a Network Analysis of Metabolomic and Proteomic Data in Cardiac Ischemia

Metabolomic profiling is ideally suited for the analysis of cardiac metabolism in healthy and diseased states. Here, we show that systematic discovery of biomarkers of ischemic preconditioning using metabolomics can be translated to potential nanotheranostics. Thirty-three patients underwent percuta...

Descripción completa

Detalles Bibliográficos
Autores principales: Erogbogbo, Folarin, May, Jasmine, Swihart, Mark, Prasad, Paras N., Smart, Katie, Jack, Seif El, Korcyk, Dariusz, Webster, Mark, Stewart, Ralph, Zeng, Irene, Jullig, Mia, Bakeev, Katherine, Jamieson, Michelle, Kasabov, Nikolas, Gopalan, Banu, Liang, Linda, Hu, Raphael, Schliebs, Stefan, Villas-Boas, Silas, Gladding, Patrick
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Ivyspring International Publisher 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3767118/
https://www.ncbi.nlm.nih.gov/pubmed/24019856
http://dx.doi.org/10.7150/thno.5010
_version_ 1782283627638292480
author Erogbogbo, Folarin
May, Jasmine
Swihart, Mark
Prasad, Paras N.
Smart, Katie
Jack, Seif El
Korcyk, Dariusz
Webster, Mark
Stewart, Ralph
Zeng, Irene
Jullig, Mia
Bakeev, Katherine
Jamieson, Michelle
Kasabov, Nikolas
Gopalan, Banu
Liang, Linda
Hu, Raphael
Schliebs, Stefan
Villas-Boas, Silas
Gladding, Patrick
author_facet Erogbogbo, Folarin
May, Jasmine
Swihart, Mark
Prasad, Paras N.
Smart, Katie
Jack, Seif El
Korcyk, Dariusz
Webster, Mark
Stewart, Ralph
Zeng, Irene
Jullig, Mia
Bakeev, Katherine
Jamieson, Michelle
Kasabov, Nikolas
Gopalan, Banu
Liang, Linda
Hu, Raphael
Schliebs, Stefan
Villas-Boas, Silas
Gladding, Patrick
author_sort Erogbogbo, Folarin
collection PubMed
description Metabolomic profiling is ideally suited for the analysis of cardiac metabolism in healthy and diseased states. Here, we show that systematic discovery of biomarkers of ischemic preconditioning using metabolomics can be translated to potential nanotheranostics. Thirty-three patients underwent percutaneous coronary intervention (PCI) after myocardial infarction. Blood was sampled from catheters in the coronary sinus, aorta and femoral vein before coronary occlusion and 20 minutes after one minute of coronary occlusion. Plasma was analysed using GC-MS metabolomics and iTRAQ LC-MS/MS proteomics. Proteins and metabolites were mapped into the Metacore network database (GeneGo, MI, USA) to establish functional relevance. Expression of 13 proteins was significantly different (p<0.05) as a result of PCI. Included amongst these was CD44, a cell surface marker of reperfusion injury. Thirty-eight metabolites were identified using a targeted approach. Using PCA, 42% of their variance was accounted for by 21 metabolites. Multiple metabolic pathways and potential biomarkers of cardiac ischemia, reperfusion and preconditioning were identified. CD44, a marker of reperfusion injury, and myristic acid, a potential preconditioning agent, were incorporated into a nanotheranostic that may be useful for cardiovascular applications. Integrating biomarker discovery techniques into rationally designed nanoconstructs may lead to improvements in disease-specific diagnosis and treatment.
format Online
Article
Text
id pubmed-3767118
institution National Center for Biotechnology Information
language English
publishDate 2013
publisher Ivyspring International Publisher
record_format MEDLINE/PubMed
spelling pubmed-37671182013-09-09 Bioengineering Silicon Quantum Dot Theranostics using a Network Analysis of Metabolomic and Proteomic Data in Cardiac Ischemia Erogbogbo, Folarin May, Jasmine Swihart, Mark Prasad, Paras N. Smart, Katie Jack, Seif El Korcyk, Dariusz Webster, Mark Stewart, Ralph Zeng, Irene Jullig, Mia Bakeev, Katherine Jamieson, Michelle Kasabov, Nikolas Gopalan, Banu Liang, Linda Hu, Raphael Schliebs, Stefan Villas-Boas, Silas Gladding, Patrick Theranostics Research Paper Metabolomic profiling is ideally suited for the analysis of cardiac metabolism in healthy and diseased states. Here, we show that systematic discovery of biomarkers of ischemic preconditioning using metabolomics can be translated to potential nanotheranostics. Thirty-three patients underwent percutaneous coronary intervention (PCI) after myocardial infarction. Blood was sampled from catheters in the coronary sinus, aorta and femoral vein before coronary occlusion and 20 minutes after one minute of coronary occlusion. Plasma was analysed using GC-MS metabolomics and iTRAQ LC-MS/MS proteomics. Proteins and metabolites were mapped into the Metacore network database (GeneGo, MI, USA) to establish functional relevance. Expression of 13 proteins was significantly different (p<0.05) as a result of PCI. Included amongst these was CD44, a cell surface marker of reperfusion injury. Thirty-eight metabolites were identified using a targeted approach. Using PCA, 42% of their variance was accounted for by 21 metabolites. Multiple metabolic pathways and potential biomarkers of cardiac ischemia, reperfusion and preconditioning were identified. CD44, a marker of reperfusion injury, and myristic acid, a potential preconditioning agent, were incorporated into a nanotheranostic that may be useful for cardiovascular applications. Integrating biomarker discovery techniques into rationally designed nanoconstructs may lead to improvements in disease-specific diagnosis and treatment. Ivyspring International Publisher 2013-09-04 /pmc/articles/PMC3767118/ /pubmed/24019856 http://dx.doi.org/10.7150/thno.5010 Text en © Ivyspring International Publisher. This is an open-access article distributed under the terms of the Creative Commons License (http://creativecommons.org/licenses/by-nc-nd/3.0/). Reproduction is permitted for personal, noncommercial use, provided that the article is in whole, unmodified, and properly cited.
spellingShingle Research Paper
Erogbogbo, Folarin
May, Jasmine
Swihart, Mark
Prasad, Paras N.
Smart, Katie
Jack, Seif El
Korcyk, Dariusz
Webster, Mark
Stewart, Ralph
Zeng, Irene
Jullig, Mia
Bakeev, Katherine
Jamieson, Michelle
Kasabov, Nikolas
Gopalan, Banu
Liang, Linda
Hu, Raphael
Schliebs, Stefan
Villas-Boas, Silas
Gladding, Patrick
Bioengineering Silicon Quantum Dot Theranostics using a Network Analysis of Metabolomic and Proteomic Data in Cardiac Ischemia
title Bioengineering Silicon Quantum Dot Theranostics using a Network Analysis of Metabolomic and Proteomic Data in Cardiac Ischemia
title_full Bioengineering Silicon Quantum Dot Theranostics using a Network Analysis of Metabolomic and Proteomic Data in Cardiac Ischemia
title_fullStr Bioengineering Silicon Quantum Dot Theranostics using a Network Analysis of Metabolomic and Proteomic Data in Cardiac Ischemia
title_full_unstemmed Bioengineering Silicon Quantum Dot Theranostics using a Network Analysis of Metabolomic and Proteomic Data in Cardiac Ischemia
title_short Bioengineering Silicon Quantum Dot Theranostics using a Network Analysis of Metabolomic and Proteomic Data in Cardiac Ischemia
title_sort bioengineering silicon quantum dot theranostics using a network analysis of metabolomic and proteomic data in cardiac ischemia
topic Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3767118/
https://www.ncbi.nlm.nih.gov/pubmed/24019856
http://dx.doi.org/10.7150/thno.5010
work_keys_str_mv AT erogbogbofolarin bioengineeringsiliconquantumdottheranosticsusinganetworkanalysisofmetabolomicandproteomicdataincardiacischemia
AT mayjasmine bioengineeringsiliconquantumdottheranosticsusinganetworkanalysisofmetabolomicandproteomicdataincardiacischemia
AT swihartmark bioengineeringsiliconquantumdottheranosticsusinganetworkanalysisofmetabolomicandproteomicdataincardiacischemia
AT prasadparasn bioengineeringsiliconquantumdottheranosticsusinganetworkanalysisofmetabolomicandproteomicdataincardiacischemia
AT smartkatie bioengineeringsiliconquantumdottheranosticsusinganetworkanalysisofmetabolomicandproteomicdataincardiacischemia
AT jackseifel bioengineeringsiliconquantumdottheranosticsusinganetworkanalysisofmetabolomicandproteomicdataincardiacischemia
AT korcykdariusz bioengineeringsiliconquantumdottheranosticsusinganetworkanalysisofmetabolomicandproteomicdataincardiacischemia
AT webstermark bioengineeringsiliconquantumdottheranosticsusinganetworkanalysisofmetabolomicandproteomicdataincardiacischemia
AT stewartralph bioengineeringsiliconquantumdottheranosticsusinganetworkanalysisofmetabolomicandproteomicdataincardiacischemia
AT zengirene bioengineeringsiliconquantumdottheranosticsusinganetworkanalysisofmetabolomicandproteomicdataincardiacischemia
AT julligmia bioengineeringsiliconquantumdottheranosticsusinganetworkanalysisofmetabolomicandproteomicdataincardiacischemia
AT bakeevkatherine bioengineeringsiliconquantumdottheranosticsusinganetworkanalysisofmetabolomicandproteomicdataincardiacischemia
AT jamiesonmichelle bioengineeringsiliconquantumdottheranosticsusinganetworkanalysisofmetabolomicandproteomicdataincardiacischemia
AT kasabovnikolas bioengineeringsiliconquantumdottheranosticsusinganetworkanalysisofmetabolomicandproteomicdataincardiacischemia
AT gopalanbanu bioengineeringsiliconquantumdottheranosticsusinganetworkanalysisofmetabolomicandproteomicdataincardiacischemia
AT lianglinda bioengineeringsiliconquantumdottheranosticsusinganetworkanalysisofmetabolomicandproteomicdataincardiacischemia
AT huraphael bioengineeringsiliconquantumdottheranosticsusinganetworkanalysisofmetabolomicandproteomicdataincardiacischemia
AT schliebsstefan bioengineeringsiliconquantumdottheranosticsusinganetworkanalysisofmetabolomicandproteomicdataincardiacischemia
AT villasboassilas bioengineeringsiliconquantumdottheranosticsusinganetworkanalysisofmetabolomicandproteomicdataincardiacischemia
AT gladdingpatrick bioengineeringsiliconquantumdottheranosticsusinganetworkanalysisofmetabolomicandproteomicdataincardiacischemia