A method for assessing mitochondrial bioenergetics in whole white adipose tissues

Obesity is a primary risk factor for numerous metabolic diseases including metabolic syndrome, type II diabetes (T2DM), cardiovascular disease and cancer. Although classically viewed as a storage organ, the field of white adipose tissue biology is expanding to include the consideration of the tissue...

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Bibliographic Details
Published in:Redox biology 2014-01, Vol.2 (C), p.656-660
Main Authors: Dunham-Snary, Kimberly J, Sandel, Michael W, Westbrook, David G, Ballinger, Scott W
Format: Article
Language:English
Subjects:
Adipose Tissue, White - metabolism
Animals
Anti-Bacterial Agents - pharmacology
Bioenergetics
Carbonyl Cyanide p-Trifluoromethoxyphenylhydrazone - pharmacology
Cardiovascular Diseases - metabolism
Cardiovascular Diseases - pathology
Energy Metabolism - drug effects
Male
Metabolic Diseases - metabolism
Metabolic Diseases - pathology
Method
Mice
Mice, Inbred C57BL
Mitochondria - metabolism
Mitochondrion
Rotenone - pharmacology
White adipose tissue
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Summary:Obesity is a primary risk factor for numerous metabolic diseases including metabolic syndrome, type II diabetes (T2DM), cardiovascular disease and cancer. Although classically viewed as a storage organ, the field of white adipose tissue biology is expanding to include the consideration of the tissue as an endocrine organ and major contributor to overall metabolism. Given its role in energy production, the mitochondrion has long been a focus of study in metabolic dysfunction and a link between the organelle and white adipose tissue function is likely. Herein, we present a novel method for assessing mitochondrial bioenergetics from whole white adipose tissue. This method requires minimal manipulation of tissue, and eliminates the need for cell isolation and culture. Additionally, this method overcomes some of the limitations to working with transformed and/or isolated primary cells and allows for results to be obtained more expediently. In addition to the novel method, we present a comprehensive statistical analysis of bioenergetic data as well as guidelines for outlier analysis.
ISSN:2213-2317
2213-2317
DOI:10.1016/j.redox.2014.04.005