Simulated hyperglycemia in rat cardiomyocytes: a proteomics approach for improved analysis of cellular alterations.
Diabetic hyperglycemia can lead to stress-related cellular apoptosis of cardiac tissue. However, the mechanism by which hyperglycemia inflicts this damage on the structure and function of the heart is unclear. In this study, we examined the relationship between proteome alterations, mitochondrial function, and major biochemical and electrophysiological changes affecting cardiac performance during simulated short-term hyperglycemia. Two-dimensional comparative proteomics analysis of rat hearts perfused with glucose at high (30 mM) or control (5.5 mM) levels revealed that glucose loading alters cardiomyocyte proteomes. It increased expression levels of initial enzymes of the tricarboxylic acid cycle, and of enzymes of fatty acid beta-oxidation, with consequent up-regulation of enzymes of mitochondrial electron transport. It also markedly decreased expression of enzymes of glycolysis and the final steps of the tricarboxylic acid cycle. Glucose loading increased the rate of Bax-independent apoptosis. High glucose increased the duration of the action potential and elevated level of intracellular cytoplasmic calcium. Surprisingly, glucose loading did not influence levels of nitric oxide or mitochondrial superoxide in isolated cardiomyocytes. In summary, short-term simulated hyperglycemia attenuated expression of many anti-apoptotic proteins. This effect was apparently mediated via alterations in multiple biochemical pathways that collectively increased apoptotic susceptibility.
Warda
Mohamad
M
Department of Physiology and Biophysics, College of Medicine, Biohealth Products Research Center, Cardiovascular and Metabolic Disease Center, FIRST Mitochondrial Research Group, Inje University, Busan, Korea.
Kim
Hyoung Kyu
HK
Kim
Nari
N
Youm
Jae Boum
JB
Kang
Sung Hyun
SH
Park
Won Sun
WS
Khoa
Tran Min
TM
Kim
Young Hwan
YH
Han
Jin
J
D000200:Action Potentials / Q000187:drug effects; D000818:Animals; D017209:Apoptosis; D002118:Calcium / Q000378:metabolism; D002952:Citric Acid Cycle; D003198:Computer Simulation; D003593:Cytoplasm / Q000378:metabolism; D004305:Dose-Response Relationship, Drug; D004579:Electron Transport; D015180:Electrophoresis, Gel, Two-Dimensional; D005227:Fatty Acids / Q000378:metabolism; D005434:Flow Cytometry; D005562:Formazans / Q000378:metabolism; D005947:Glucose / Q000378:metabolism / Q000494:pharmacology; D006352:Heart Ventricles / Q000166:cytology; D006943:Hyperglycemia / Q000378:metabolism* / Q000503:physiopathology; D050356:Lipid Metabolism; D008297:Male; D008929:Mitochondria, Heart / Q000378:metabolism; D032383:Myocytes, Cardiac / Q000378:metabolism*; D010084:Oxidation-Reduction; D018408:Patch-Clamp Techniques; D010449:Peptide Mapping; D010477:Perfusion; D011506:Proteins / Q000378:metabolism*; D020543:Proteome / Q000032:analysis; D040901:Proteomics / Q000379:methods*; D051381:Rats; D017207:Rats, Sprague-Dawley; D013997:Time Factors
D005227:Fatty Acids; D005562:Formazans; D011506:Proteins; D020543:Proteome; D005947:Glucose; D002118:Calcium