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Diabetes/Metabolism Research and Reviews 2009-Sep

Acetyl-CoA carboxylases 1 and 2 show distinct expression patterns in rats and humans and alterations in obesity and diabetes.

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Prihlásiť Registrácia
Odkaz sa uloží do schránky
Sebastian Kreuz
Corinna Schoelch
Leo Thomas
Wolfgang Rist
Jörg F Rippmann
Heike Neubauer

Kľúčové slová

Abstrakt

BACKGROUND

Acetyl-CoA carboxylases (ACC) 1 and 2 are central enzymes in lipid metabolism. To further investigate their relevance for the development of obesity and type 2 diabetes, expression of both ACC isoforms was analyzed in obese fa/fa Zucker fatty and Zucker diabetic fatty rats at different ages in comparison to Zucker lean controls.

METHODS

ACC1 and ACC2 transcript levels were measured by quantitative real-time polymerase chain reaction in metabolically relevant tissues of Zucker fatty, Zucker diabetic fatty and Zucker lean control animals. Quantitative real-time polymerase chain reaction was also applied to measure ACC tissue distribution in human tissues. For confirmation on a protein level, quantitative mass spectrometry was used.

RESULTS

Disease-related transcriptional changes of both ACC isoforms were observed in various tissues of Zucker fatty and Zucker diabetic fatty rats including liver, pancreas and muscle. Changes were most prominent in oxidative tissues of diabetic rats, where ACC2 was significantly increased and ACC1 was reduced compared with Zucker lean control animals. A comparison of the overall tissue distribution of both ACC isoforms in humans and rats surprisingly revealed strong differences. While in rats ACC1 was mainly expressed in lipogenic and ACC2 in oxidative tissues, ACC2 was predominant in oxidative and lipogenic tissues in humans.

CONCLUSIONS

Our data support a potential role for both ACC isoforms in the development of obesity and diabetes in rats. However, the finding of fundamental species differences in ACC1 and ACC2 tissue expression might be indicative for different functions of both isoforms in humans and rats and raises the question to which degree these models are predictive for the physiology and pathophysiology of lipid metabolism in humans.

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