a guide to analysis of mouse energy metabolism

Nature Methods

A guide to analysis of mouse energy metabolism

Matthias H Tschöp, John R Speakman, Jonathan R S Arch, Johan Auwerx, Jens C Brüning, Lawrence

Chan, Robert Eckel, Robert V Farese Jr, Jose E Galgani, Catherine Hambly, Mark A Herman, Tamas L

Horvath, Barbara B Kahn, Sara C Kozma, Eleftheria Maratos-Flier, Timo D Müller, Heike Muenzberg,

Paul T Pfluger, Leona Plum, Marc Reitman, Kamal Rahmouni, Gerald I Shulman, George Thomas, C

Ronald Kahn & Eric Ravussin

Supplementary Table 1: Metabolic rate in mutant versus wild-type (WT) mice.

Supplementary Note 1: Methods and practical issues for measuring energy expenditure by open circuit

indirect calorimetry.

Supplementary Note 2: Body composition methods.

Supplementary Note 3: Practical considerations for the measurement of food intake in rodents

Supplementary Note 4: How ANCOVA works

Supplementary Note 5: Power analysis

Nature Methods: doi:10.1038/nmeth.1806

Supplementary Material

Supplementary Table 1. Metabolic rate in mutant versus wild-type (WT) mice.

Target gene KO/TG Animals

per group Metabolic rate compared WT

Normalization used

Ref.

Mice without brown adipose tissue 7-10 % O2 increase () n/a 1

3 adrenergic receptor KO 6 ml O2/min () n/a 2 Leptin KO n/a ml O2/kg0.7/h () BW^0.7 3 RII subunit of protein kinase A KO 5 ml O2/kg/h () BW 4 Uncoupling protein KO 7-8 ml O2/min () n/a 5 Dopamine -hydroxylase KO 8-10 ml O2/kg/h () BW 6 Bombesin receptor subtype-3 KO 6 ml O2/min () n/a 7 Melanin concentrating hormone KO 4 ml O2/kg/min () BW 8 Vgf KO 6 ml O2/kg/min () BW 9 Hormone-sensitive lipase KO 6 ml O2/min () n/a 10

Human 2 adrenergic receptor TG 6 % O2 increase () n/a 11 Uncoupling protein 1 TG 4 ml O2/g3/4/h () BW 12 Uncoupling protein 3 KO 5 ml O2/kg2/3/min () BW^2/3 13 Acyl-CoA:diacylglycerol transferase KO 7-9 kcal/g/d () BW 14 Perilipin KO 4-6 ml O2/kg/min () BW 15 Uncoupling protein 3 TG 10-12 ml O2/kg/h () BW 16 Melanocortin-3 receptor KO 10 kcal/h () n/a 17 Protein-tyrosine phosphatase 1B KO 5-8 kcal/g/h () BW 18 Melanocortin-3 receptor KO 8 ml O2/kg3/4/h () BW^3/4 19 Estrogen receptor KO 7 ml O2/min () n/a 20 Aromatase KO 10 kcal/d () n/a 21 M3 muscarinic acetylcholine receptor KO 6 ml O2/g3/4/h () BW^3/4 22 Eukaryotic translation initiation KO 7-9 ml O2/kg/h () BW 23 Melanocortin-4 receptor KO 17-18 ml O2/kg3/4/h () BW^3/4 24 Perilipin KO 6 ml O2/kg3/4/h () BW^3/4 25 Stearoyl-CoA desaturase 1 KO 8 ml O2/g3/4 () BW^3/4 26 adrenergic receptor (3 isoforms) KO 8 ml O2/kg lean/min () LM 27 Human FGF-19 TG 4 L O2/kg3/4/h () BW^3/4 28 SRC-1 KO n/a L O2/kg/h () BW 29 TIF2 KO n/a L O2/kg/h () BW 29 MCH1R KO 10-13 kcal/h () n/a 30 Endothelial nitric oxide synthase KO 4-7 ml O2/kg/min () BW 31 Cidea KO 12 ml O2/kg/min () BW 32 S6K1 KO 6 L O2/kg/h () BW 33 RII subunit of protein kinase A KO 5-9 ml O2/kg/min () BW 34 Agouti-related protein KO 5-8 ml O2/kg/h () BW 35 Interleukin 6 KO 6-7 ml O2/min () n/a 36 Tubby KO 2-4 ml O2/kg/h () BW 37 Uncoupling protein 1 KO 6-10 ml O2/h () n/a 38 Uncoupling protein 1 KO 8 ml O2/h () n/a 39

M3 muscarinic acetylcholine receptor KO 6-9 ml O2/g3/4/h () BW^3/4 40 Protein-tyrosine phosphatase 1B KO n/a ml O2/kg () BW 41

PGC 1 KO 5-6 ml O2/kg/min () BW

42


Uncoupling protein 3 TG 8 kcal/kg/h () BW 43

Adipocyte LDL receptor-related protein 1 KO 16 kcal/kg/96 h () BW 44

AMPK2 in POMC neurons KO 8-11 ml O2/min () ANCOVA 45 Ren1c KO 9 kcal/kg lean/d () LM 46

Pten (ablation in leptin-sensitive neurons) KO 3-4 ml O2/kg/h () BW 47

PNRC2 KO 4 ml O2/kg/min () BW 48 GPR50 KO 11 ml O2/kg/h () BW 49 KRAP KO 5-6 kJ/kg3/4/h () n/a 50 Ate1 KO 6 ml O2/kg/min () BW 51

AMPK 1 KO 6 ml O2/kg/h () BW 52 POMC-Asb4 TG 7 ml O2/kg/h () BW 53 ACC2 KO n’a ml O2/kg/h () BW 54 NF-B p65 TG 8 kcal/kg lean/h () LM 55

NF-B p50 KO 9 kcal/kg lean/h () LM 55

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30. Marsh, D.J., et al. Melanin-concentrating hormone 1 receptor-deficient mice are lean, hyperactive, and hyperphagic and have altered metabolism. Proc Natl Acad Sci U S A 99, 3240-3245 (2002).

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34. Newhall KJ, Cummings DE, Nolan MA & McKnight GS. Deletion of the RIIbeta-subunit of protein kinase A decreases body weight and increases energy expenditure in the obese, leptin-deficient ob/ob mouse. Mol Endocrinol 19:982-91 (2005).

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39. Ukropec, J., Anunciado, R.P., Ravussin, Y., Hulver, M.W. & Kozak, L.P. UCP1-independent thermogenesis in white adipose tissue of cold-acclimated Ucp1-/- mice. J Biol Chem 281, 31894-31908 (2006).


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Supplementary Note 1.

Methods and practical issues for measuring energy expenditure by open circuit indirect

calorimetry.

Open circuit indirect calorimetry for mice has become the standard technique for modern

metabolism laboratories. The optimum indirect calorimetry system would allow for simultaneous

measurements of mice undergoing combined genetic, pharmacological and dietary studies at the

same time. Today, systems of up to 32 and more cages are available and allow such simultaneous

measurements. However, the ideal system would in addition have one O2 and one CO2 sensor

for every cage, to allow a constant measurement of each cage over the desired period of time.

Unfortunately, in most commercially available systems the number of CO2 and O2 sensors is

lower than the number of cages, which is mainly based on the high cost of the analyzers.

Commonly, one sensor pair has to measure CO2 and O2 values for up to 16 cages. These

calorimeters therefore usually measure the O2 and CO2 content of a cage for a given short period

of time, and then switch over to the next cage. The in- and outgoing O2 and CO2 content of the

air in each cage is compared to a reference value taken either from the air in the room, or from a

gas bottle with known concentrations of O2 and CO2. If possible, the reference should be

measured at the same time as the cage of interest. However, in many cases reference air is

measured only once at the beginning of a measurement cycle. In that case, changes in ambient

O2 or CO2concentrations within the room, for instance through the presence of the researchers

(who consume O2 and generate CO2 as well), or through changes in the room climate control

system, could markedly affect the results. Therefore, it is preferable to draw fresh air into the


system from outside the building or from an isolated air plenum. If not, measuring reference air

between measures of each individual cage would help to overcome this issue, albeit to the extent

of prolonging the overall time for one measurement cycle from cage 1 to cage x.

Indirect calorimetry systems usually come in sizes between 4 and 36 cages and offer

measurement of O2 consumption and CO2 production, various aspects of locomotor activity,

plus in many cases automated recording of food intake and fluid intake (and in some cases

telemetry based temperature and heart rate data). These systems usually switch from cage to cage

(usually requiring 1 to 3 min of measurement per cage). Accordingly, depending on the

sophistication of the system and the number of cages, there could be intervals of 30 to 60 min

between measurements. With new fast switching systems and a limited number of cages per

calorimeter, intervals between measurements may come closer to 10 min.

The choice of the ambient temperature for calorimetric measurements is of paramount

importance for studies of energy balance, especially those with a focus on thermogenesis.

Several studies have shown that mouse metabolic rate is lowest at ambient temperatures between

28°C and 34°C, which then constitutes the state of thermoneutrality, where animals perform no

thermogenesis to regulate body temperature1-4. When environmental temperatures decrease

below 28°C mice, animals increase both their metabolism and their energy intake5‐7 to defend a

homeothermic body temperature. However, laboratory mice are usually housed and monitored

under mild to moderate cold exposure conditions, i.e. at ambient temperatures between 20 and

23°C. It has been proposed repeatedly and rightfully that studies of obesity should involve

maintenance of mice at thermoneutrality, a preferred condition for measures of energy balance


and arguably better representing the conditions in which humans live by wearing clothes and

adjusting environmental temperatures. However, acute studies of energy metabolism in rodents

under thermoneutral conditions are of limited interest since they do not reflect the chronic

conditions under which an obese or lean phenotype has developed. Therefore, animal housing

and metabolic phenotype analysis under thermoneutral conditions may represent the optimal

approach, but is unfeasible in most research institutions. One of the major reason for this is that

higher temperatures facilitate disease transmission and breakdown of barrier conditions.

Constant mild thermal stress by housing animals at 20-23oC may influence energy balance. As

an example, the lack of UCP1 in C57BL/6J mice induces obesity only at thermoneutrality30, but

not under ambient conditions between 20-28oC8,9.

For specific questions such as uncovering impaired cold induced thermogenesis, a transient

decrease of environmental temperature can be useful (e.g. 4°C). Animal body core temperature

must be monitored and animals have to be removed before risk of harm occurs. Unless the goal

of a study is to test the reaction to sudden environmental challenges (such as cold exposure),

adequate acclimation (usually at 3-7 days) is required. Acclimation is particularly important to

minimize the impact of stress and the bias introduced by changed behavior in smaller chambers,

with often different food and water presentation in a different environment. Removal of bedding

(e.g. for indirect calorimetry studies to avoid interference with airflow) can introduce another

artifact. When conducting indirect calorimetry studies in larger groups of mice, the number of

metabolic cages might not be sufficient to simultaneously evaluate all mice. Therefore, groups

sometimes have to be split into subpopulations and placed consecutively into the indirect

calorimetry system. In such case, special care must be taken to keep all environmental, technical

and experimental conditions as constant as possible.


Since oscillations of EE or transient decreases in metabolism are sometimes observed10, the use

of only one cage per calorimeter with continuous measurement has advantages. This approach

however also comes with its own set of potential challenges: 1) A single cage being measured

would therefore only allow for the study of one mouse at a time. With acclimation time and at

least 48 hours of data collection per mouse, a one time comparison of 4 groups of 8 mice

(KO/WT/ male/female) would take more than 3 months with continuous use of the system; 2)

Over those three months, there would likely be important variability from changing age and

environmental conditions, thus decreasing the validity of the indirect calorimetry measures; 3) If

large resources are available, 8 or more separate indirect calorimeters could be purchased and

used in parallel, each one measuring one mouse at a time, but continuously. This set up of

course, is not only extremely costly but also carries its own set of pitfalls: Pooling data from 8

separate calorimeters could introduce potential instrument-to-instrument variability requires

substantial quality control measures. A reasonable compromise may be to use a well-calibrated,

multi-cage indirect calorimetry system, where mice are acclimated until a stable dark/light

pattern of credible food intake and energy expenditure data is observed. Alternating

measurements, switching from cage to cage should then be performed for at least 96 hours to

achieve a number of measurements per cage that includes but limits influence of outlier data

points (e.g. measurements every 12 min in a new fast switching 12 cage system would allow for

480 measurements/mouse). These measurements should be done in parallel in sufficient numbers

of KO vs. WT or treated vs. untreated mice, all of which should be set up in alternating cages

within the system.


Minimizing the time for one measurement cycle is critical for indirect calorimetry studies. Based

on the number of O2 and CO2 sensors, one full cycle can last up to 60min. This long time is

based on the number of cages (e.g. 16), the number of measurements of reference air per cycle

(e.g. 4 measurements per cycle), but also the length of measurement for each individual cage.

Preferably, this measurement time should be as short as possible, to shorten the time of one

measurement cycle. Practically, the type of O2 or CO2 sensors will determine the amount of time

needed to get an accurate measurement; typical high temperature zirconium sensors for instance

need up to 3 minutes to get a reliable steady measurement of oxygen concentration. New

generations of (more costly) high-speed sensors however get reliable measurements already in a

fraction of that time, and allow significant shortening of the measurement cycle. Overall, a short

measurement cycle time would increase the number of measurements for each individual cage

and animal over the course of the whole experiment. A high number of measurements per cage is

desirable since it will increase the accuracy, minimize the variability and enhance the statistical

power of detecting differences between groups.

Another important consideration is the choice of the total duration of the measurement. As

already discussed, the animals should be free of stress and fully acclimatized to the

environmental conditions. In this regard it has to be considered that stress sensitive or anxiety

prone mouse strains, e.g. BALB/c or 129S611,12 usually require a longer time for acclimatization

than e.g. less stress/anxiety vulnerable C57/BL6J mice. A minimum acclimatization period of at

least 48hrs for C57/BL6J mice and 72 hrs or more for more stress sensitive strains has been

sufficient on average in our experience to re-establish normal feeding and behavior. At any time

during the measurement, mice should be disturbed as little as possible and investigators should


enter the room not more and no longer than absolutely necessary. To allow for appropriate

diurnal comparison of energy expenditure (e.g. between the light and dark phase) analysis of at

least 72-96h (3-4 full light/dark cycles) post acclimatization is recommended.

A thorough metabolic mouse phenotype characterization frequently calls for additional

procedures of varying invasiveness (e.g. blood sampling, glucose or insulin tolerance tests,

behavioral tests, surgery, pump implantation etc.). Even under optimal circumstances, such

procedures can affect mouse behavior and impair metabolic balance leading to a recovery period

of several days. Moreover, different treatment groups (e.g. vehicle vs. drug treatment) may vary

in respect to stress sensitivity and time needed to recover. It has to be considered that changes in

metabolic rate can occur even though no change in BW are apparent (e.g. immediately after

blood sampling or behavioral tests).

Age and disease state of the animals can greatly affect the results of indirect calorimetry. Ideally,

the groups of mice should be disease-free, age matched littermates that only differ in the

presence or absence of the gene of interest (or the kind of treatment). The use of age matched

controls is of major importance as aging is well known to be accompanied by loss of muscle

mass13-16, leading to differences in metabolic rate when compared to weight matched younger

controls. Moreover there may be additional changes in metabolism with age that are independent

of muscle mass that need to be controlled for by age-matching samples17,18.

Another conundrum could be the right timing of measurements. While food intake is typically

monitored continuously over weeks and even months, energy expenditure is mostly measured

only a single time, and just for a few days thereby possibly missing a crucial, and sometimes


short, phase where thermogenic alterations may lead to differences in fat mass. If possible,

indirect calorimetry should be performed at more than one time point over the course of

metabolic phenotype development. Useful time points for such measurements could for example

include an early stage where differences in BW or BC have not yet become apparent and after

the metabolic phenotype has been clearly established. It is possible to observe changes in

respiratory quotients (RQ) between treatment groups and genotypes that are not associated with

measured changes in energy expenditure or food intake. The respiratory quotient is calculated by

dividing the volume of CO2produced by the volume of O2 consumed (RQ = VCO2 / VO2). RQ

provides valuable information about metabolic substrate utilization.


Supplementary Note 2 Body composition methods Destructive methods

The standard procedure is first to kill the animal. The gut contents are then removed and the

remaining carcass is dried, either by freeze drying or in a conventional oven at 60 oC for 10-14

days. Higher temperatures reduce the time to dry, but may cause organic volatization, while

lower temperatures minimise any fat loss, but may not kill bacteria on the carcass and therefore

lead to losses by bacterial decomposition19. The difference between the dry and wet carcass is

the body water content. Fats are then extracted by continuous reflux through the carcass of a

combination of polar and non-polar lipid solvents (generally a mix of petroleum ether and diethyl

ether) in a soxhlet device20. Refluxing continues until all fats have been extracted. The remaining

carcass is then re-dried and the difference between the dry mass and the post-soxhlet mass is the

body fat content. The fat-extracted carcass is then burned in a muffle furnace at 500 oC for 5

hours21 to remove any remaining organic matter, leaving behind the ash from the mineral content

which is predominantly bone22. Subtracting the ash weight from the fat extracted weight yields

the ash free dry lean mass, which is 91-94% protein.

Isotope dilution

Fat and lean tissues are differently hydrated. Hence as an animal becomes fatter the contribution

of water to its total BW gets progressively smaller. Isotope dilution and TOBEC methods use

this fact to generate indirect estimates of water content which can then be converted to fat-free

content, either using a theoretical relationship, or by direct validation against the destructive

methods in a separate sample of animals. Isotope dilution involves taking a sample of body water


(normally blood) and injecting the animal with an isotope of either oxygen or hydrogen

(normally oxygen-18 or deuterium/tritium). The isotope is allowed to distribute in the body for a

period time (for mice and rats generally 30-60 min, although some data suggests equilibration in

mice may be complete in as little as 15 min:23 and then a second sample of body fluid is

collected. The difference in isotope enrichment between the two samples, relative to the

enrichment in the original dose, is due to dilution by body water. Knowing the extent of this

dilution allows an estimate of the body water content. Lean mass can be extrapolated from the

water content assuming a fixed lean mass hydration of 73%. It is generally assumed that all the

water resides in ‘lean’ tissue, and hence the difference between the estimated lean mass (water

mass/0.73) and body weight is an estimate of the body fat content. Theoretically, oxygen-18

gives a more accurate estimate of body water than either deuterium or tritium because less

oxygen takes part in exchange reactions with other body components than hydrogen.

Accordingly deuterium or tritium dilution spaces tend to overestimate body water by 2-5%24-26.

Speakman and colleagues27 reviewed the extent of overestimation of body water by using the

dilution space of deuterium/tritium and concluded the average was 4.59% across 26 species of

mammals and 4.73% across 4 species of birds. In contrast the over-estimation of the body water

by oxygen-18 was 1.8% across 5 species of birds and mammals combined. However, oxygen-18

costs about 100x more than either of the hydrogen isotopes. Furthermore, oxygen-18 and

deuterium need to be measured by sophisticated isotope ratio mass spectrometry methods which

are expensive to set up, although analyses of both these stable isotopes can be made

commercially. Tritium by contrast is cheap and easily measured by liquid scintillation counting,

but on the downside is radioactive. Surprisingly the correlation between deuterium dilution and

body fat content was stronger than the relationship between oxygen-18 dilution and body fatness,


making deuterium overall less variable28 . A strength of the isotope dilution method is that it

provides a direct quantification of the body water content without a need for cross calibration.

However, it does not provide an estimate of bone mineral content, and therefore the resultant

estimate of ‘non-lean’ tissue includes the bone mass. This is often estimated by assuming bone as

a fixed proportion of total mass and therefore fat mass can be calculated. The absolute average

error in estimated fat content (relative to soxhlet extraction) using deuterium dilution in a sample

of 38 small rodents was 0.6g in males (n = 19) and 1.1g in females (n = 19) for deuterium

dilution and 0.8g in males and 1.1g in females for oxygen-18 dilution28.

Total body electrical conductivity (TOBEC)

TOBEC has been widely employed since the mid 1980s29 because of the cheap availability of

commercial devices that are primarily designed to evaluate the fat content of meat samples. In a

TOBEC device the animal is restrained in a holder and placed into chamber surrounded by a coil.

Because the lean tissues of an organism contain most of the electrolytes there is a large

difference in the electrical conductivity of lean and fat tissues, with the latter being only about

5% of the former. A varying electromagnetic field induces a current which flows in a conductor

in direct relation to its conductivity. This is measured as dissipation of the field. The TOBEC

machine therefore, like isotope dilution, directly measures the lean compartment from which the

fat mass is then calculated by subtraction from the total mass, making an assumption of the

contribution of bone. Unlike isotope dilution however TOBEC does not provide a direct

quantification of the water or lean content and validation of the method to derive a predictive

equation relative to the destructive methods is always required30. If the animal urinates while in

the machine (which is surprisingly common) the run needs to be aborted and the machine


cleaned out since the highly conductive urine has a big effect on the estimates. A second problem

is that the estimate is very sensitive to temperature31. On the plus side TOBEC equipment is

relatively inexpensive. Of note, significant improvement in the accuracy of TOBEC

measurements have been reported if the animal is anesthetised28. The resultant errors were

approximately equivalent to those for isotope dilution. On average the absolute error in fat

content using TOBEC (relative to soxhlet) was 0.8g in males (n = 19) and 1.1g in females (n =

19).

Dual-energy x-ray absorptiometry (DXA)

DXA was developed in the late 1980s32 and used for animal studies during the 1990s and early

2000s e.g.33. The method requires the animal to be anaesthetised. It is then placed in a beam of x-

rays that are emitted at two different energies. Molecules in the pathway of these beams

differentially absorb the two beams hence different tissues also absorb the two different energy

beams differently according to their composition34,35. The machine scans the animal and

generates an image reflecting the extent of x-ray absorption. The analysis of this image involves

comparing the strength of the two x-ray beams at each pixel on the image. Because there are only

2 different energies, the machine can only resolve at each pixel two different components. Hence

in a pixel containing bone the machine can only resolve the relative contributions of bone and

soft-tissue, while in a pixel containing no bone the machine can resolve the difference between

fat and lean tissue36,37. Sophisticated algorithms are used to evaluate the fat and lean contribution

of the soft tissue in pixels where there is bone by comparison to adjacent pixels. Different

software packages use different algorithms and so generate slightly different answers. The main

advantage of DXA is that it resolves the composition into three separate compartments: bone,


lean and fat, and because it generates an image it is possible to perform regional analyses.

Although, as the image is only 2D, these regional analyses can only be performed at a rather

superficial level. It is not possible to distinguish for example subcutaneous from visceral fat in

the abdominal region. Nevertheless it is the cheapest available method allowing this level of

resolution. The major downside of this approach is the animal needs to be completely stationary

and so anaesthesia is necessary for the 3 min scan. Radiation exposure of the animal is

negligible, but operators of the machines may need protection if they do many scans. A second

problem is that machines need individual calibration against destructive methods before they can

generate reliable data38,39. Once calibrated however, the errors are much lower than using either

isotope dilution or TOBEC. On average the absolute error in fat content in small rodents using

DXA was 0.5g in males (n = 19) and 0.3g in females (n = 19)28.

Magnetic resonance spectroscopy (MRS)

All odd numbered isotopes have a net nuclear magnetic spin. MRS utilizes this phenomenon by

measuring the ‘relaxation’ of protons that have had their spins temporarily aligned by application

of a static magnetic field and then excited by application of a resonant frequency field. Because

the relaxation time depends on the environment in which the protons exist, it is possible to

distinguish different compounds by their different relaxation characteristics. Therefore MRS

machines measure directly the numbers of protons that are located in lipids, proteins, bone and

water. Conversion of numbers of protons to actual amounts of lipid and lean tissue depend on

assumptions about the exact tissue compositions. These are built into the machine software. A

major advantage of this approach is that it is quick (scans normally in under 2 minutes) and the

subject animal does not need to be restrained or anaesthetized during the measurement. The main


disadvantages are the necessary assumptions about fat and protein composition. The method

does not allow for regional analysis, unless the animal is killed and dissected, and the component

parts are analyzed separately. MRS estimates of live conscious mice are significantly less

variable than measurements made by DXA40,41 The coefficient of variation in the fat estimate for

mice (0.3 to 0.7%) was about an order of magnitude lower than the CV for DXA measures in the

same animals (3.1 to 12.6%). Accuracy relative to destructive analysis is uncertain.

Magnetic resonance imaging (MRI)

If the animal in the measuring chamber can be kept stationary, and the field orientation is varied

over time it is possible using MRS to locate the protons that are being detected in space.

Sequential measurements can then be used to generate a 3D image of the object detailing the

location of the different soft tissues. This approach is called magnetic resonance imaging. MRI

images generally consist of slices made at given intervals through the body. The resolution of

these images depends on the magnet strength and their interval depends on how long the animal

is immobilized. MRI can provide the sizes of individual fat stores and the sizes of individual

organs and the bone tissue sizes and is hence extremely powerful. However, MRI machines with

sufficient resolution to perform these tasks are very expensive. Moreover the time the animals

need to remain under anesthesia for such a measurement is also quite long, depending on the

slice interval. As might be expected the closer together the slices are, the better the estimate, but

the longer the animal needs to be kept down. The animal is exposed to a magnetic field, but there

is no exposure to ionising radiation.

Computed tomography (CT)


The main alternative to MRI is CT scanning. Like MRI, CT scanning generates a sliced image

but it does this by bombarding the animal with radiation and examining the absorption patterns.

The result is a cheaper machine that yields a similarly detailed 3D model of the tissue

distribution. Comparisons of the weights of different fat stores dissected ex vivo and measured by

CT scanning in 90 C57BL/6mice were very good (r2 = 0.91- 0.94 for different fat pads)42. The

key downside of CT is the radiation dose the animal receives is often not trivial. This dose

depends on the resolution, and repeated measurements at high resolution may involve so much

radiation that effects of radiation poisoning on energy balance are very likely. Modern machines

may involve lower radiation doses43.


Supplementary Note 3 Practical considerations for the measurement of food intake in rodents

For quantification of caloric intake the choice of diet is a key factor. The use of standard “chow”

labeled diets as the standard control diet may often be a source of artifacts, since the exact

dietary content of such diets can vary significantly from batch to batch. Commercial standardized

purified ‘open label’ low-fat diets are more reliable control diets. When using energy-dense

diets, the main source of calories and type of macronutrients (carbohydrates: sucrose, glucose,

fructose, etc; lipids: corn oil, butter fat, etc.) is of importance and should be chosen consciously

and reported in detail. Naturally, the diet should be of high quality, and particular attention

should be paid to keeping the diet fresh. One frequent and important source of artifacts is the fact

that high fat diets typically used for metabolic phenotyping studies in mice can turn bad within

less than a week at room temperature, thereby loosing palatability and introducing a major

interference factor. Laboratory diets, especially those high in fat, should be stored properly, e.g.

in a fridge or freezer, but sufficient defrost time needs to be accounted for before presenting the

diet to the animals. Finally, presentation of the diet (in food hoppers, on the cage floor, pelleted

or non-pelleted) may influence the outcome of any feeding diet study44 and switching from one

presentation mode (home cage) to another (metabolic cage) usually requires several 24-hour

periods of acclimation before a reliable feeding pattern is reestablished45. Different diets are

prone to different degrees of grinding by mice which can influence the accuracy of the reported

intake, as discussed below46.


Food intake (EI for energy intake) can be measured efficiently and accurately manually by an

experienced investigator (regular weighing of food, control for spillage and calculation of

disappearance of grams and calories). Automated food intake monitoring systems allow

measurements of diurnal changes in caloric intake and in addition also enable meal pattern

analyses. When compared to manual measurements of food intake, these systems have the

advantage that the cage does not have to be opened and food pellets do not have to be touched by

the investigator for several 24-hour periods, which further minimizes potentially stressful

disturbances of the animals’ environment.

A number of practical aspects are essential for a thorough determination of calorie intake. Small

laboratory animals might spill their food, especially when fed a powdered diet or a diet with a

soft texture, such as common high fat diets46. To avoid falsely high calorie intake values, the

cages should therefore always be monitored for spilled food. Adding a laminated sheet in a

bright color on the bottom of the cages for example can facilitate such an effort. Alternatively

animals can be housed on grid floors, rather than in sawdust or paper bedding, which facilitates

identification of grinding, but on the other hand this can induce stress47. If necessary, spilled food

has to be included into the weighing, or, if this is not possible, the animal has to be excluded

from further analysis. In addition, the food needs to be replaced in regular intervals to be kept

fresh and palatable. Environmental aspects, such as changes of the light/dark cycle, noise and

stress due to the presence of investigators can considerably influence food intake in mice48.

Accordingly, when exposed to new environmental conditions, mice should always be allowed to

acclimate to those new conditions before food intake is recorded.


Changes in food intake are closely connected to other physiological processes such as energy

expenditure. For example even short-term caloric restriction in mice entails a reduction of

metabolic rate49,50, body core temperature49,51,52, blood pressure50-52 as well as sympathetic

activity53,54. Notably, even under standard laboratory housing conditions, a single overnight fast

is able to induce torpor in mice55-57, reflected by decreased metabolic rates58 Vice versa, cold

exposure or physical activity can increase food intake, while increased environmental

temperature (exposure to an organism’s thermoneutral zone) decreases food intake due to

reduced caloric requirements for thermogenesis59.

The ingested amount of calories is not identical to the number of calories available for

metabolism. Once ingested, a high, but variable percentage of ingested calories is absorbed by

the gastro-intestinal system. This process is highly compartmentalized, and involves a multitude

of passive and active transport systems and digestive enzymes. Gastrointestinal motility,

nutritional status, drugs or gut microbiota all play important roles for nutrient absorption,

systemic or localized bowel inflammation. A defect in any of the absorption mechanisms60, or

changes in microbial flora61-64 can have a significant impact on assimilation efficiency, i.e. the

total energy intake minus the fecal energy output divided by the total energy intake. Therefore,

differences in assimilated calories can account for energy balance differences despite no apparent

differences in food intake65

The assimilation efficiency can be measured by using a bomb calorimetry system. This

technique will requires the collection of all feces, over the course of several days, in combination

with parallel monitoring of food intake. Subsequently, the caloric content of the feces sample and

of the appropriate amount of ingested food is determined by bomb calorimetry. The difference


between the ingested calories and the energy in the feces is called the digestible energy intake.

One disadvantage of bomb calorimetry is that no difference is made between non-digestable/non-

metabolizable energy, and energy that can be utilized by the organism. To address this problem,

several specialized nutrient absorption assays have been developed. For instance, radioactive

tracers of various nutrients can be monitored for proper uptake over time. In addition, non-

radioactive methods such as the sucrose polybehenate method66 allow to specifically measure fat

absorption in a noninvasive manner. However, these approaches do not allow the calculation of

the total number of calories used for metabolism. A combination of food intake measurements,

bomb calorimetry of feces and specific absorption assays for carbohydrates and lipids probably

represents the optimum approach. Some of the digested energy is also unavailable for

metabolism and is excreted in the urine. The total ingested energy minus that in feces and urine

is called the metabolizable energy intake.

Simultaneous analysis of EI and BW gain over the course of several weeks allows an indirect

evaluation of the metabolic rate if food intake happens to be identical, or is artificially matched

by a procedure called “pair-feeding”: If adiposity changes occur in spite of identical caloric

intake (and energy assimilation), then metabolic rates are driving the fat mass phenotype. Pair-

feeding studies require that the group of mice (WT or KO), which ingests (and assimilates) more

calories is limited to the amount of calories ingested (and assimilated) by the other group. This is

most commonly achieved by giving every 24 hour period the restricted mice the amount of food

that the other group ingested the 24 hours before. While offering a powerful tool, one key issue

with pair-feeding studies is that commonly the food is given to the pair-fed animals only once or

maximally twice a day. Since the restricted mice are becoming increasingly hungrier over the


course of such a pair-feeding study, they typically ingest all available food within a few hours

and then starve for the rest of the 24 hour period. This imbalance leads to a bias for metabolic

studies as entrains animals to an artificial meal-feeding paradigm67,68. Ideally, pair-feeding

studies should be performed by providing matched amounts of calories hourly, if not by the

minute, without causing a stressful environment for the animals. This can be achieved by

automated pair-feeding instruments with master/servant cage pairing under computerized

control. Repeated food deprivation periods can lead to increased thermogenesis, chronic

hyperactivation of CNS centers providing orexigenic drive, changes in metabolic circadian

patterns or increased gastrointetinal assimilation of calories. Differences in assimilation

efficiency can remain unnoticed, while still greatly affecting BW phenotypes. For instance, a 3%

difference in assimilation between two groups of mice would be within the statistical error

margin of almost any food assimilation measurement independent of the methodology used.

However, one group would effectively be under- or overfeed by 3%, which might be enough to

generate a body weight phenotype if continued chronically. As mentioned above, advanced food

intake monitoring systems also allow a time- and weight-controlled access to food, and thus

achieve sophisticated pair- or meal- feeding strategies.

Automated, continuous, measurement of food intake can also generate helpful data on meal

patterns such as caloric ingestion speed, meal size and meal number. Such measurements can for

example reveal adaptations to interventions as observed for example after certain types of

bariatric surgery where rodent meal pattern has been described to changed toward more, but

smaller, feeding bouts69.


Supplementary Note 4

How ANCOVA works

Illustration of how analysis of covariance works to analyze the data from Figure 1 in the main text.

ANCOVA works by effectively fitting a gradient to the data and then sliding all the individual data points

along imaginary parallel lines until they all group together at the average lean BW. This creates two

distributions that can then be tested to see if they differ from each other. This approach is illustrated

below, with the wildtype genotype (black) on the left of the overall mean and the experimental genotype

(white) on the right. As can be seen there is no significant difference. If we repeat this process for study B

sliding the data down the imaginary gradients yields a different result in that the two distributions are now

separated. This process reveals how ANCOVA yields a result that matches our intuitive feel for what is

happening in the data based on visual inspection of Figure 1 in the main text. Thus, we recommend that

ANCOVA should be the method of choice for normalization of the effects of BW on energy expenditure

and food intake data. It is further suggested that data should not be presented as histograms of mean

energy expenditure for each group, but rather individual data should be plotted in relation to BW (or lean

body mass), since this enables a much clearer understanding of what is happening in the data (compare

for example the upper two plots in figure 1 in the main text with the lower two histograms)


STUDY A

STUDYＢ


S P

T

upplementary note 5

ower analysis

he sufficiency of sample size to avoid a type 2 error is known as the power of the test (or β). In

an energy balance study one can work out how many individual animals are needed in an

experiment to avoid a type 2 error by performing an a priori power calculation. A careful a-priori

power and sample size analysis can predetermine success or failure of an experimental setting.

For example, imagine two treatment groups (genotype A and genotype B) fed on a standard diet.

To detect if there is a significant difference in food intake between these genotypes one needs to

decide how much of a difference in intake would be biologically significant. This is called the

effect size. Imagine we decide that a difference in energy intake of 2.5% would be important. For

a typical C57BL/6 type mouse eating 3g of food a day this is a difference between groups of

0.075g. One also needs to know the variation (standard deviation) in food intake between

individuals. In C57BL/6 mice this is approximately 0.3g. If we set the required power of the test

at 95% or β=0.95 (ie the equivalent chance of avoiding a type 2 error to the p value of 0.05 (or α)

which is the probability of avoiding a type 1 error) then the required sample size for the test in a

standard 2 sample t-test is 417 animals per group! Commonly, sample size estimations are based

on power calculations achieving a power of 80-90%, although the rationale for this asymmetry in

statistical requirements to avoid type 1 and type 2 errors has been questioned. Even so with a

power of 80% the required sample size is 350. This reveals a stark fact that virtually every study

of energy balance yet performed, including all those by our own groups, have probably been

underpowered to detect subtle effects of the treatments on energy balance. Studies of energy


metabolism are not unique in this respect. Moher et al.70 reported that from 383 published

controlled trials only 36% had an 80% power to detect a relative difference of 50% between

groups (and only 16% had an 80% power to detect a 25% difference). We should regard with

extreme caution therefore claims that there is no significant difference between treatment groups

(particularly in food intake and expenditure). Another way to look at this is to work out post-hoc

the power analysis in the opposite direction to ask how much power studies actually have to

detect a given difference, or how small a difference they can actually detect. Across a wide range

of energy balance studies the average sample size seems to be around 10 per group. At this

sample size the power to detect a difference of 2.5% in intake between 2 groups using a standard

t-test is only 8.3%. Put another way the smallest difference in mean food intake that could be

reliably detected at this sample size is 0.51g/day (17% of the daily intake). Therefore when

studies using this type of sample size state that there is no significant treatment effect on food

intake (or expenditure) there could still be profound differences in intake and expenditure that

have serious impacts on energy balance that have been missed by the analysis because it is

nderpowered. There are many potential examples in the recent literature71. u

Although power analysis indicates the desirable numbers of animals to be studied the number of

animals to be investigated profoundly affects the costs, duration, and feasibility of a study, which

is often limited by available mouse mutants and experimental conditions (e.g. the number of

calorimetry cages). Measuring over 300 animals per group is going to be logistically impossible

in most situations. It is important, however, that researchers are clear about the power that

particular analyses have when claiming that there is no significant effect of a given treatment,

and tailor the strength of their conclusions according to the power they have to make the


particular claim. We recommend that all claims that food intake, energy expenditure and body

composition ‘are not significantly different’ should include a ‘health warning’ which includes the

power of the analysis and preferably also the effect size that could be detected at the sample size

used. Several excellent free-access online tools are available for power calculations (e.g.

http://www.stat.uiowa.edu/~rlenth/Power/index.html). In parallel with this declaration however

e note that referees and editors also need to be realistic in reviewing papers not to insist onw

ompletely unrealistic power for this type of analysis. Otherwise nothing will be published. c


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a guide to analysis of mouse energy metabolism

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