A big-data approach to understanding metabolic rate and response to obesity in laboratory mice
Authors
Corrigan, June K.Ramachandran, Deepti
He, Yuchen
Palmer, Colin J.
Jurczak, Michael J.
Chen, Rui
Li, Bingshan
Friedline, Randall H.
Kim, Jason K.
Ramsey, Jon J.
Lantier, Louise
McGuinness, Owen P.
Banks, Alexander S.
UMass Chan Affiliations
Division of Endocrinology, Metabolism, and Diabetes, Department of MedicineProgram in Molecular Medicine
Document Type
Journal ArticlePublication Date
2020-05-01Keywords
energy expenditurefood intake
genetics
human biology
medicine
metabolic rate
mouse
neuroscience
obesity
thermogenesis
Biochemical Phenomena, Metabolism, and Nutrition
Bioinformatics
Cellular and Molecular Physiology
Nutritional and Metabolic Diseases
Physiological Processes
Research Methods in Life Sciences
Metadata
Show full item recordAbstract
Maintaining a healthy body weight requires an exquisite balance between energy intake and energy expenditure. To understand the genetic and environmental factors that contribute to the regulation of body weight, an important first step is to establish the normal range of metabolic values and primary sources contributing to variability. Energy metabolism is measured by powerful and sensitive indirect calorimetry devices. Analysis of nearly 10,000 wild-type mice from two large-scale experiments revealed that the largest variation in energy expenditure is due to body composition, ambient temperature, and institutional site of experimentation. We also analyze variation in 2329 knockout strains and establish a reference for the magnitude of metabolic changes. Based on these findings, we provide suggestions for how best to design and conduct energy balance experiments in rodents. These recommendations will move us closer to the goal of a centralized physiological repository to foster transparency, rigor and reproducibility in metabolic physiology experimentation.Source
Corrigan JK, Ramachandran D, He Y, Palmer CJ, Jurczak MJ, Chen R, Li B, Friedline RH, Kim JK, Ramsey JJ, Lantier L, McGuinness OP; Mouse Metabolic Phenotyping Center Energy Balance Working Group, Banks AS. A big-data approach to understanding metabolic rate and response to obesity in laboratory mice. Elife. 2020 May 1;9:e53560. doi: 10.7554/eLife.53560. PMID: 32356724; PMCID: PMC7274785. Link to article on publisher's site
DOI
10.7554/eLife.53560Permanent Link to this Item
http://hdl.handle.net/20.500.14038/41463PubMed ID
32356724Related Resources
Rights
Copyright © 2020, Corrigan et al. This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.Distribution License
http://creativecommons.org/licenses/by/4.0/ae974a485f413a2113503eed53cd6c53
10.7554/eLife.53560
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Except where otherwise noted, this item's license is described as Copyright © 2020, Corrigan et al. This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.