Comprehensive Energy Balance Measurements in Mice

Lee Moir1, Liz Bentley1, Roger D. Cox1

1 Harwell Campus, Oxfordshire
Publication Name:  Current Protocols in Mouse Biology
Unit Number:   
DOI:  10.1002/cpmo.13
Online Posting Date:  September, 2016
GO TO THE FULL TEXT: PDF or HTML at Wiley Online Library


In mice with altered body composition, establishing whether it is food intake or energy expenditure, or both, that is the major determinant resulting in changed energy balance is important. In order to ascertain where the imbalance is, the acquisition of reproducible data is critical. Therefore, here we provide detailed descriptions of how to determine energy balance in mice. This encompasses protocols for establishing energy intake from home cage measurement of food intake, determining energy lost in feces using bomb calorimetry, and using equations to calculate parameters such as energy intake (EI), digested energy intake (DEI), and metabolisable energy intake (MEI) to determine overall energy balance. We also discuss considerations that should be taken into account when planning these experiments, including diet and sample sizes. © 2016 by John Wiley & Sons, Inc.

Keywords: bomb calorimetry; energy balance; energy expenditure; energy intake; fecal energy; food intake

PDF or HTML at Wiley Online Library

Table of Contents

  • Introduction
  • Strategic Planning
  • Basic Protocol 1: Home Cage Measurement of Food Intake
  • Basic Protocol 2: Fecal Energy Content Determined by Bomb Calorimetry
  • Basic Protocol 3: Energy Intake Equations
  • Basic Protocol 4: Energy Balance Equations
  • Commentary
  • Literature Cited
  • Figures
PDF or HTML at Wiley Online Library


Basic Protocol 1: Home Cage Measurement of Food Intake

  • Appropriate mouse strain or line, preferably congenic
  • Mouse diet
  • Scale (±0.01 g for mice; ±0.001 g for food)
  • Method of recording weights (see Fig.  )

Basic Protocol 2: Fecal Energy Content Determined by Bomb Calorimetry

  • Appropriate mouse strain or line
  • Mouse diet used for food intake study (see protocol 1)
  • White granulated sugar
  • Benzoic acid tablets
  • Scale (±0.01 g for mice; ±0.001 g for food; ±0.0001 g for bomb calorimeter samples)
  • Method of recording weights and energy output (see Fig.  )
  • Mouse cages with clean bedding
  • Absorbent lint‐free tissue
  • Blunt‐end forceps, for feces collection
  • Tube, for feces collection
  • Biosafety level 2 (BSL‐2) cabinet
  • Desiccator jar
  • Silica gel with moisture indicator
  • 55°C incubator
  • Bomb calorimeter setup (e.g., IKA, Parr Instrument Company, LECO Instruments) including the following components:
  • Stainless steel decomposition vessel
  • Holding surface for crucible
  • Crucible
  • Venting button
  • Cotton thread
  • Ignition wire
  • Combustion bag (optional)
NOTE: Only trained personnel competent in the operation of the bomb calorimeter and working with oxygen should undertake this protocol.

Basic Protocol 3: Energy Intake Equations

  • Indirect calorimetry system (see Meyer et al., )
PDF or HTML at Wiley Online Library



Literature Cited

Literature Cited
  Arch, J.R., Hislop, D., Wang, S.J., and Speakman, J.R. 2006. Some mathematical and technical issues in the measurement and interpretation of open‐circuit indirect calorimetry in small animals. Int. J. Obes. 30:1322‐1331. doi: 10.1038/sj.ijo.0803280.
  Arndt, S.S., Laarakker, M.C., van Lith, H.A., van der Staay, F.J., Gieling, E., Salomons, A.R., van't Klooster, J., and Ohl, F. 2009. Individual housing of mice–impact on behaviour and stress responses. Physiol. Behav. 97:385‐393. doi: 10.1016/j.physbeh.2009.03.008.
  Brown, S.D. and Moore, M.W. 2012. Towards an encyclopaedia of mammalian gene function: The international mouse phenotyping consortium. Dis. Model. Mech. 5:289‐292. doi: 10.1242/dmm.009878.
  Butler, A.A. and Kozak, L.P. 2010. A recurring problem with the analysis of energy expenditure in genetic models expressing lean and obese phenotypes. Diabetes 59:323‐329. doi: 10.2337/db09‐1471.
  Dhurandhar, N.V., Schoeller, D., Brown, A.W., Heymsfield, S.B., Thomas, D., Sorensen, T.I., Speakman, J.R., Jeansonne, M., and Allison, D.B. 2015. Energy balance measurement: When something is not better than nothing. Int. J. Obes. 39:1109‐1113. doi: 10.1038/ijo.2014.199.
  Drozdz, A. 1975. Food habits and food assimilation in mammals. In Methods for Ecological Bioenergetics (W. Grodzinski, R.Z. Klekowski, and A. Duncan, eds.). Blackwell Scientific Publications, Oxford, United Kingdom.
  Hall, K.D., Heymsfield, S.B., Kemnitz, J.W., Klein, S., Schoeller, D.A., and Speakman, J.R. 2012. Energy balance and its components: Implications for body weight regulation. Am. J. Clin. Nutr. 95:989‐994. doi: 10.3945/ajcn.112.036350.
  Hunt, C. and Hambly, C. 2006. Faecal corticosterone concentrations indicate that separately housed male mice are not more stressed than group housed males. Physiol. Behav. 87:519‐526. doi: 10.1016/j.physbeh.2005.11.013.
  Kaiyala, K.J., Morton, G.J., Leroux, B.G., Ogimoto, K., Wisse, B., and Schwartz, M.W. 2010. Identification of body fat mass as a major determinant of metabolic rate in mice. Diabetes 59:1657‐1666. doi: 10.2337/db09‐1582.
  Martin, A.L. and Brown, R.E. 2010. The lonely mouse: Verification of a separation‐induced model of depression in female mice. Behav. Brain Res. 207:196‐207. doi: 10.1016/j.bbr.2009.10.006.
  McMurray, F., Church, C.D., Larder, R., Nicholson, G., Wells, S., Teboul, L., Tung, Y.C., Rimmington, D., Bosch, F., Jimenez, V., Yeo, G.S., O'Rahilly, S., Ashcroft, F.M., Coll, A.P., and Cox, R.D. 2013. Adult onset global loss of the fto gene alters body composition and metabolism in the mouse. PLoS Genet. 9:e1003166. doi: 10.1371/journal.pgen.1003166.
  Meyer, C.W., Reitmeir, P., and Tschop, M.H. 2015. Exploration of energy metabolism in the mouse using indirect calorimetry: Measurement of daily energy expenditure (DEE) and basal metabolic rate (BMR). Curr. Protoc. Mouse Biol. 5:205‐222. doi: 10.1002/9780470942390.mo140216.
  Ng, M., Fleming, T., Robinson, M., Thomson, B., Graetz, N., Margono, C., Mullany, E.C., Biryukov, S., Abbafati, C., Abera, S.F., Abraham, J.P., Abu‐Rmeileh, N.M., Achoki, T., AlBuhairan, F.S., Alemu, Z.A., Alfonso, R., Ali, M.K., Ali, R., Guzman, N.A., Ammar, W., Anwari, P., Banerjee, A., Barquera, S., Basu, S., Bennett, D.A., Bhutta, Z., Blore, J., Cabral, N., Nonato, I.C., Chang, J.C., Chowdhury, R., Courville, K.J., Criqui, M.H., Cundiff, D.K., Dabhadkar, K.C., Dandona, L., Davis, A., Dayama, A., Dharmaratne, S.D., Ding, E.L., Durrani, A.M., Esteghamati, A., Farzadfar, F., Fay, D.F., Feigin, V.L., Flaxman, A., Forouzanfar, M.H., Goto, A., Green, M.A., Gupta, R., Hafezi‐Nejad, N., Hankey, G.J., Harewood, H.C., Havmoeller, R., Hay, S., Hernandez, L., Husseini, A., Idrisov, B.T., Ikeda, N., Islami, F., Jahangir, E., Jassal, S.K., Jee, S.H., Jeffreys, M., Jonas, J.B., Kabagambe, E.K., Khalifa, S.E., Kengne, A.P., Khader, Y.S., Khang, Y.H., Kim, D., Kimokoti, R.W., Kinge, J.M., Kokubo, Y., Kosen, S., Kwan, G., Lai, T., Leinsalu, M., Li, Y., Liang, X., Liu, S., Logroscino, G., Lotufo, P.A., Lu, Y., Ma, J., Mainoo, N.K., Mensah, G.A., Merriman, T.R., Mokdad, A.H., Moschandreas, J., Naghavi, M., Naheed, A., Nand, D., Narayan, K.M., Nelson, E.L., Neuhouser, M.L., Nisar, M.I., Ohkubo, T., Oti, S.O., Pedroza, A., Prabhakaran, D., Roy, N., Sampson, U., Seo, H., Sepanlou, S.G., Shibuya, K., Shiri, R., Shiue, I., Singh, G.M., Singh, J.A., Skirbekk, V., Stapelberg, N.J., Sturua, L., Sykes, B.L., Tobias, M., Tran, B.X., Trasande, L., Toyoshima, H., van de Vijver, S., Vasankari, T.J., Veerman, J.L., Velasquez‐Melendez, G., Vlassov, V.V., Vollset, S.E., Vos, T., Wang, C., Wang, X., Weiderpass, E., Werdecker, A., Wright, J.L., Yang, Y.C., Yatsuya, H., Yoon, J., Yoon, S.J., Zhao, Y., Zhou, M., Zhu, S., Lopez, A.D., Murray, C.J., and Gakidou, E. 2014. Global, regional, and national prevalence of overweight and obesity in children and adults during 1980‐2013: A systematic analysis for the Global Burden of Disease Study 2013. Lancet 384:766‐781. doi: 10.1016/S0140‐6736(14)60460‐8.
  Ravussin, Y., Gutman, R., LeDuc, C.A., and Leibel, R.L. 2013. Estimating energy expenditure in mice using an energy balance technique. Int. J. Obes. 37:399‐403. doi: 10.1038/ijo.2012.105.
  Rozman, J., Klingenspor, M., and Hrabe de Angelis, M. 2014. A review of standardized metabolic phenotyping of animal models. Mamm. Genome 25:497‐507. doi: 10.1007/s00335‐014‐9532‐0.
  Spani, D., Arras, M., Konig, B., and Rulicke, T. 2003. Higher heart rate of laboratory mice housed individually vs in pairs. Lab. Anim. 37:54‐62. doi: 10.1258/002367703762226692.
  Speakman, J.R. 2001. Body Composition Analysis of Animals: A Handbook of Non‐Destructive Methods. Cambridge University Press, Cambridge, United Kingdom.
  Speakman, J.R. 2013. Measuring energy metabolism in the mouse ‐ theoretical, practical, and analytical considerations. Front. Physiol. 4:34. doi: 10.3389/fphys.2013.00034.
  Speakman, J.R., Fletcher, Q., and Vaanholt, L. 2013. The '39 steps': An algorithm for performing statistical analysis of data on energy intake and expenditure. Dis. Model Mech. 6:293‐301. doi: 10.1242/dmm.009860.
  Stechman, M.J., Ahmad, B.N., Loh, N.Y., Reed, A.A.C., Stewart, M., Wells, S., Hough, T., Bentley, L., Cox, R.D., Brown, S.D.M., and Thakker, R.V., 2010. Establishing normal plasma and 24‐hour urinary biochemistry ranges in C3H, BALB/c and C57BL/6J mice following acclimatization in metabolic cages. Lab. Anim. 44:218–225. doi: 10.1258/la.2010.009128.
  Tschop, M.H., Speakman, J.R., Arch, J.R., Auwerx, J., Bruning, J.C., Chan, L., Eckel, R.H., Farese, R.V. Jr., Galgani, J.E., Hambly, C., Herman, M.A., Horvath, T.L., Kahn, B.B., Kozma, S.C., Maratos‐Flier, E., Muller, T.D., Munzberg, H., Pfluger, P.T., Plum, L., Reitman, M.L., Rahmouni, K., Shulman, G.I., Thomas, G., Kahn, C.R., and Ravussin, E. 2012. A guide to analysis of mouse energy metabolism. Nat. Methods 9:57‐63. doi: 10.1038/nmeth.1806.
PDF or HTML at Wiley Online Library