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1 Department of Zoology, University of Wisconsin, Madison, Wisconsin 53706-1381; and 2 Departments of Anesthesiology, Physiology, and Biophysics, Mayo Clinic and Mayo Foundation, Rochester, Minnesota 55905
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ABSTRACT |
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Top
Abstract
Introduction
Materials & Methods
Results
Discussion
References
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Swallow, John G., Theodore Garland, Jr., Patrick A. Carter,
Wen-Zhi Zhan, and Gary C. Sieck. Effects of voluntary activity and
genetic selection on aerobic capacity in house mice
(Mus domesticus). J. Appl. Physiol. 84(1): 69-76, 1998.
An animal model was developed to study effects on components of
exercise physiology of both "nature" (10 generations of genetic
selection for high voluntary activity on running wheels) and
"nurture" (7-8 wk of access or no access to running wheels,
beginning at weaning). At the end of the experiment, mice from both
wheel-access groups were significantly lighter in body mass than mice
from sedentary groups. Within the wheel-access group, a statistically
significant, negative relationship existed between activity and final
body mass. In measurements of maximum oxygen consumption during forced
treadmill exercise (
O2 max), mice with
wheel access were significantly more cooperative than sedentary mice;
however, trial quality was not a significant predictor of individual
variation in O2 max.
Nested two-way analysis of covariance demonstrated that both genetic
selection history and access to wheels had significant positive effects on O2 max.
A 12% difference in
O2 max existed
between wheel-access selected mice, which had the highest
mass-corrected
O2 max, and
sedentary control mice, which had the lowest. The respiratory exchange
ratio at O2 max was
also significantly lower in the wheel-access group. Our results suggest
the existence of a possible genetic correlation between voluntary
activity levels (behavior) and aerobic capacity (physiology).
maximum oxygen consumption; wheel running; artificial selection; quantitative genetics; heritability
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INTRODUCTION |
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Top
Abstract
Introduction
Materials & Methods
Results
Discussion
References
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A WORKING MODEL to describe the complex relationship between habitual physical activity and health-related physical fitness was developed at the International Conference on Exercise, Fitness, and Health (4). According to the model, habitual physical activity can improve health-related fitness traits, which, in turn, may exert positive feedback on habitual activity levels. Individual humans with the highest levels of habitual activity tend to maintain the highest levels of health-related fitness. Similarly, as an individual's level of physical fitness increases, so does the propensity to engage in physical activity. Furthermore, all of the major components of the model are affected by genetics. For example, habitual activity levels (27), as well as health-related fitness traits (3) such as aerobic and anaerobic performance (2), appear to be genetically heritable in humans. However, no information concerning possible genetic correlations (8, 9, 12) between habitual physical activity and physical-fitness traits presently exists. An understanding of the underlying genetics of habitual activity will help answer questions concerning the relationship between activity and health. For instance, do individuals with a genetic propensity for high levels of physical activity also tend to have high levels of aerobic fitness?
We propose the use of an animal model to study simultaneously the
effects of both "nature" (genetic endowment for high activity) and "nurture" (access to a running wheel) on physical-fitness traits. Animal models have been widely used to study physiological effects of exercise training. For example, rodents given access to
running wheels will display significant amounts of spontaneous activity. Individual variation in wheel-running behavior is
substantial; some animals will run many kilometers per day, whereas
others engage in almost no activity (e.g., Refs. 11 and 14).
Furthermore, wheel-running activity has been shown to elicit a variety
of physiological adaptations to training [e.g., increased maximum
O2 consumption (O2 max) and running
economy (22); muscle enzyme activity (28); and vascular adaptations
(29)]. In addition, animal models using wheel running have
provided insight into the effects of exercise on health and longevity
(e.g., Ref. 21).
Artificial selection is one of several tools that can be applied with animal models to separate genetic and environmental influences on particular phenotypic traits (12, 17). The goal of selective breeding is often to change the mean phenotype of a defined population compared with a control population. Selective breeding should result in changes in allele frequencies for all genes associated with the phenotype under selection; allele frequencies of genes unrelated to the selected phenotype are expected to remain unchanged, except for possible effects of linkage or random genetic drift. In the present study, we used selective breeding to create four replicate lines of mice with high activity levels, compared with four random-bred control lines (30); 10 generations of selective breeding resulted in an ~75% increase in the activity level of males (the sex used in this study) compared with males from control lines.
Selection for a single trait may also result in correlated changes in
other traits (12, 15, 17). Because high levels of habitual activity may
require high endurance and aerobic capacity, we hypothesized that
selection for high levels of activity would be accompanied by a
concomitant increase in aerobic capacity (see also Refs. 10 and 18).
O2 max during exercise
appears to be genetically heritable (2) and thus capable of responding to selection in either a direct or correlated manner. In a two-way design, we studied the effects of both genetic selection history and
exercise history (access to running wheels) on body mass, O2 max, and respiratory
exchange ratio (RER).
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MATERIALS AND METHODS |
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Top
Abstract
Introduction
Materials & Methods
Results
Discussion
References
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Animal husbandry and breeding design. The mice used in this study were sampled from an artificial selection experiment for increased voluntary activity levels on running wheels, including four replicate selected lines and four randomly bred control lines (30). These mice are the result of 10 generations of within-family selection for total wheel-running activity. Each generation of mice was housed individually with access to running wheels and scored for activity over a 6-day period; selection was based on the total number of revolutions run on days 5 and 6. After 10 generations of selective breeding, males from the selected lines were ~75% more active than males from the control lines. The original progenitors of these lines were outbred HSD:ICR mice (see Refs. 8-11 for strain history) purchased from Harlan Sprague Dawley (Indianapolis, IN) in 1993.
The mice studied herein were from second litters; their siblings (first litters) were part of the routine selection protocol and were measured for wheel-running activity at 6-8 wk of age. The parents had first been mated at 8 wk and were then remated at ~13 wk of age by placing each male with its mate from the first pairing the day after the first litter was weaned. Males were removed 15-18 days after pairing; births began 19 days after pairing. From 19 to 33 days after pairing, pregnant females were checked daily between 1600 and 1800. At 21 days of age, offspring were weaned from the dam, weighed, and toe clipped for individual identification. One male was selected at random from each family for measurement to ensure statistical independence of data points. Only males were studied to eliminate possible sex-related variation both in behavioral (females tend to run more on the wheels) and physiological traits (6, 8-10). Twelve mice were assigned to each of four measurement groups: sedentary control, wheel-access control, sedentary selected, and wheel-access selected. The sedentary mice were housed in groups of four in standard clear plastic cages (27 × 17 × 12.5 cm) with metal tops and wood shavings in a temperature-controlled room (~22°C) with a constant 12:12-h light-dark cycle centered at 1400 (CST). Water and food [Harlan Teklad Laboratory Rodent Diet (W)-8604] were available ad libitum. The wheel-access mice were housed with four siblings until the following day, and then they were housed individually with access to running wheels. As a result of variation in birth date, time of access to wheels (before measurement of mass andO2 max)
ranged between 51 and 61 days.
Voluntary wheel-running behavior. In the wheel-access group, voluntary activity was monitored every day for each mouse from 22 days of age until the day before measurement of peak exercise metabolism (73-83 days of age). Voluntary wheel running was measured on Wahman-type activity wheels [as described (11): 1.12-m-circumference, 10-cm-wide running surface of 10-mm mesh bounded by clear Plexiglas walls; Lafayette Instruments, Lafayette, IN; model 86041 with modifications]. Normal housing cages were attached to the wheels by a 7.7-cm-diameter hole in the cage side so that mice had continuous access to activity wheels. Attached to each wheel was a photocell counter, which was interfaced to an IBM-compatible personal computer. Customized software from San Diego Instruments (San Diego, CA) measured the number of clockwise and counterclockwise revolutions during every 1-min interval for each wheel. Data were downloaded every 24 h.
Peak exercise metabolic rate.
O2 max and maximum
carbon dioxide production
(CO2 max)
were measured on 2 consecutive days via an incremental step protocol on
a motorized treadmill (8, 10, 11, 14, 19). Measurements were made first
in the sedentary group and then in the wheel-access group. All
measurements were done from July 24 to 27 between 0900 and 1900. The
wheel-access group continued to be housed with access to wheels during
this period, but running activity was not recorded.
O2) was recorded for 1.5-2 min. The treadmill was then started at an initial speed of
1.5 km/h. Mice were induced to run by being prodded with a straightened
paper clip inserted through a hole at the rear of the chamber
and/or by a mild electric current (50-110 V, 3-12 mA)
provided through a horizontal grid of twelve 2-mm bars spaced 5 mm
apart at the end of the moving belt. Treadmill speed was then increased
every 2 min by 0.5 km/h. All mice reached at least 2.5 km/h; the
maximum speed attained by any mouse in this study was 4.0 km/h. Trials
were ended when O2 failed
to increase with increasing speed and/or the mouse failed to
keep pace with the treadmill.
O2 generally decreased
before a trial was ended (i.e., while the mouse was still running).
After the treadmill was stopped, mice were left in the chamber for
1.5-2 min. Mice were then removed from the chamber, and baseline
data were again recorded for 2 min. Body mass of each animal was
recorded on the first day of measurement. Time of day, speed at which
the trial ended, and a subjective assessment of run quality (5 categories from poor to excellent) were recorded at the end of each
trial. All measurements were blind with respect to selection history
and were taken by one individual (J. G. Swallow).
Gas exchange was monitored with an open-circuit respirometry system.
Air was drawn from the running chamber via a series of eight ports
(each 3 mm diameter) in its top, through a column of Drierite for
removal of water vapor, and then passed through a thermal mass-flow
controller (series 840 Side=Trak, Sierra Instruments) set at 2,500 ml/min STPD. This flow rate ensured
rapid chamber washout; time to initial response was <5 s. Excurrent
air was analyzed continuously by an Ametek (Applied Electrochemistry) S-3A/II O2 analyzer and an Ametek
(Applied Electrochemistry) CD-3A CO2 analyzer. Effective volume of
the system was determined separately for
O2 (604 ml) and
CO2 (630 ml), and analysis
software made "instantaneous" corrections for chamber washout (1)
because standard equations assume steady-state (equilibrium)
conditions. Instantaneous corrections are minor with a rapid washout
rate, as in our system (see RESULTS; Refs. 8, 10, and 11).
Our data-acquisition program recorded values for
O2 and
CO2 each second as the average of
20 consecutive readings and wrote the data to disk. The program also
allowed us to put marks in the file (used to indicate baseline, mouse
in chamber without treadmill running, and speed of treadmill). A
data-analysis program corrected for baseline drift by using linear
regression. CO2 production (CO2) values were
calculated by using Eq. 2 in Ref. 16
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O2 values were
calculated by using Eq. 3b in Ref. 33
![<A><AC>V</AC><AC>˙</AC></A><SC>o</SC><SUB>2</SUB> = [(<A><AC>V</AC><AC>˙</AC></A><SC>e</SC>)(F<SC>i</SC><SUB>O<SUB>2</SUB></SUB> − F<SC>e</SC><SUB>O<SUB>2</SUB></SUB>) − (<A><AC>V</AC><AC>˙</AC></A><SC>co</SC><SUB>2</SUB> × F<SC>i</SC><SUB>O<SUB>2</SUB></SUB>)]/(1 − F<SC>i</SC><SUB>O<SUB>2</SUB></SUB>)](/content/vol84/issue1/fulltext/69/img002.gif)
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CO2 is expressed as
milliliters CO2 per hour
(STPD);
O2 is expressed
as milliliters O2 per hour
(STPD);
FI is fractional concentration
of gas in inspired air; FE is
fractional concentration of gas in expired air; and
E is flow
rate (ml/h; STPD).
The highest 1-min period of
O2 and
CO2 was determined
separately (both steady-state and instantaneous) for each treadmill run. The higher of the two measurements was taken as
O2 max and
CO2 max,
respectively. RER and speed at which
O2 max
and
CO2 max
were first attained (determined from marks in the data file) were also
recorded.
Statistical analyses.
Wheel running (over first 2 wk of exposure to wheels and over the last
6 wk of exposure to wheels), body mass at weaning, body mass within the
wheel-access group, and
O2 max within the wheel-access group were analyzed by nested one-way analysis of variance
(ANOVA) with type III sums of squares in the Statistical Analysis
System General Linear Models (SAS GLM) procedure. Line type (selected
vs. control) was used as the grouping variable; replicated line
(n = 8 total) was nested within line
type. Number of toes clipped for identification and an index of wheel
rotational resistance were used as covariates in analyses of wheel
running. Average number of revolutions run per day (rev/day) during the last week of exposure to wheels was used as a covariate in the analysis
of final body mass within the wheel-access group. Average number of
rev/day during the last week of exposure to wheels as well as body mass
and trial quality were used in the analysis of
O2 max within the
wheel-access group.
O2 max,
CO2 max,
RER, running performance (speed at
O2 max, speed at
CO2 max,
maximum speed attained in trial), and trial quality were analyzed by a
nested two-way ANOVA with type III sums of squares in the SAS GLM
procedure. Exercise group (sedentary vs. wheel-access) and line type
(selected vs. control) were the grouping factors; replicate line was
nested within line type. Body mass was included as a covariate in all analyses of exercise metabolism. Models were tried both with and without trial quality as a covariate in analyses of
O2 max and CO2 max;
results from both analyses (with and without trial quality) are
presented. Trial quality, but not body mass, was used in the analyses
of treadmill-running performance. The foregoing are mixed models with
both random (exercise group) and fixed (line type and line) factors.
Therefore, effects of line type were tested over the mean squares of
line-within-line type, and effects of exercise group were tested over
the mean squares of the interaction of exercise group × line-within-line type. Adjusted means were calculated by using the
LSMEANS command in the SAS GLM procedure; all covariates in the model,
regardless of statistical significance, were used to calculate adjusted
means.
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RESULTS |
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Top
Abstract
Introduction
Materials & Methods
Results
Discussion
References
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Wheel running. Figure 1 shows the mean rev/day by mice from the selected and the control lines as a function of age. During the first 2 wk of exposure to the running wheels, when mice were 22-36 days of age, mice from selected lines ran significantly more rev/day than did mice from the control lines [F = 6.83; degrees of freedom (df ) = 1,6; P = 0.0399]. Mice from both selected and control lines exhibited a temporal trend for increased wheel running over the first 6 wk of exposure to wheels, after which activity levels declined. Although mice from selected lines continued to have higher mean values of rev/day from weeks 3 to 8, this difference was no longer statistically significant. Number of toes clipped and wheel resistance were never significant in any of the analyses.
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Metabolic responses.
Between trial days, individual mice displayed repeatable variation in
trial quality (cooperativity) during the treadmill test (r = 0.489;
P = 0.001), and trial quality was
significantly higher on the second trial (paired
T = 2.14; df = 1,43; 2-tailed,
P = 0.038). Because trial quality can
influence whether an animal reaches
O2 max, it has often
been used to assess whether a particular run should be included in
analyses (e.g., Ref. 5). To our knowledge, however, trial quality has
not been used as a covariate in analyses, even though it may influence
metabolism. Therefore, we tried analyses with and without trial quality
as a covariate, both to allow comparability with previous studies and
to correct for possible effects of run quality.
O2 max were
highly correlated (r = 0.980), with
the latter averaging 4% higher. Here, only instantaneous values were
presented; regardless of which values are analyzed, the basic
conclusions remain unchanged.
In a two-way ANCOVA, mice from the selected lines had significantly
higher O2 max than did
mice from control lines (F = 10.13; df = 1,6; P = 0.0190); wheel-access mice
also had higher values of
O2 max than did
sedentary mice, although this difference was only marginally
significant (F = 5.88; df = 1,6;
P = 0.0515). The interaction term
between line type and exercise group was not statistically significant
(F = 1.72; df = 1,6;
P = 0.2378). Figure
3 shows instantaneous
O2 max as a function of
body mass; as expected, body mass was a significant predictor of
O2 max (F = 26.51; df = 1,26;
P = 0.0001). Trial quality was not a
significant predictor of
O2 max
(F = 1.68; df = 1,26;
P = 0.2058).
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O2 max without trial
quality, significance levels for both line type
(F = 10.36; df = 1,6;
P = 0.0185) and exercise group
(F = 7.63; df = 1,6;
P = 0.0328) were similar (Table
3). Again, the interaction term was not
statistically significant (F = 1.26;
df = 1,6; P = 0.3048), and
body mass was a significant predictor
(F = 24.34; df = 1,26;
P = 0.0001).
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O2 max was repeated
within the wheel-access group with average rev/day as an additional covariate during the last week of wheel exposure. Differences between
mice from the selected and control lines were no longer statistically
significant (F = 1.34; df = 1,6;
P = 0.2918). Amount of wheel running
did not predict individual variation in
O2 max (F = 1.07; df = 1,11;
P = 0.3242), but body mass did
(F = 16.57; df = 1,26;
P = 0.0018).
The treadmill speed at which
O2 max was attained
averaged slightly higher than 2 km/h (Table 3) and did not differ
significantly between either selected and control lines
(F = 0.44; df = 1,6; P = 0.5324) or wheel-access and
sedentary mice (F = 0.01; df = 1,6;
P = 0.9264). Similarly,
maximum speed attained on the treadmill averaged slightly higher than 3 km/h (Table 3) and did not differ between either selected and control
lines (F = 0.62; df = 1,6; P = 0.4619) or wheel-access and
sedentary mice (F = 0.16; df = 1,6;
P = 0.7013). In the foregoing
analyses, the subjective measurement of trial quality was a
significant, positive predictor of the speed at which
O2 max was attained
(F = 7.61; df = 1,27;
P = 0.0103) as well as the maximum
speed attained on the treadmill (F = 27.81; df = 1,27; P = 0.0001). We
repeated the analyses without trial quality as a covariate. Speed at
which O2 max was
attained still did not differ significantly in relation to selection
(F = 0.08; df = 1,6;
P = 0.7874) or exercise group
(F = 1.58; df = 1,6;
P = 0.2549). Maximum speed attained in
a trial did not differ in relation to selection
(F = 0.01; df = 1,6;
P = 0.9247) but was higher in the
wheel-access mice (F = 8.34; df = 1,6;
P = 0.0278).
No significant difference in
CO2 max
was observed between mice from either selected and control lines
(F = 1.02; df = 1,6; P = 0.3514) or wheel-access and
sedentary groups (F = 0.33; df = 1,6;
P = 0.5858). Again, the interaction
term between line type and exercise group was not statistically
significant (F = 2.77; df = 1,6;
P = 0.14). Body mass, but not trial
quality, was a significant predictor of
CO2 max.
Not surprisingly,
CO2 max
was significantly higher than
CO2 at
O2 max (Table 3; paired
T = 7.50; df = 1,43;
P = 0.0001). No group differences
(F < 0.05; df = 1,6;
P > 0.5) existed for the speed at
which
CO2 max
was attained, whether or not trial quality was used as a covariate. In
the reduced model of
CO2 max
without trial quality, effects of neither line type
(F = 1.02; df = 1,6;
P = 0.3519) nor exercise
group (F = 0.34; df = 1,6;
P = 0.5807) were statistically
significant (Table 3). The interaction term also was not statistically
significant (F = 2.77; df = 1,6; P = 0.1470).
In the two-way ANCOVA, access to running wheels significantly reduced
the RER at O2 max
(F = 7.15; df = 1,6;
P = 0.0368); however, genetic
selection history did not affect RER at
O2 max (F = 0.42; df = 1,6;
P = 0.5417), and neither body mass nor
trial quality was a significant predictor of RER. In a reduced model with neither body mass nor trial quality as a covariate, results were
qualitatively similar; access to running wheels significantly reduced
RER (F = 22.42; df = 1,6;
P = 0.0032; Table 3), but
genetic selection had no effect (F = 0.66; df = 1,6; P = 0.4482). As might be expected, RER at
CO2 max
(grand mean = 1.11) was significantly higher than RER at
O2 max (grand mean = 1.02; paired T = 10.28; df = 1,43;
P = 0.0001).
Mice with access to activity wheels had significantly higher subjective
measurements of trial quality than did sedentary mice (2-way ANOVA:
F = 8.19; df = 1,6;
P = 0.0287; Table 3). Thus wheel-access mice were more cooperative on the treadmill. Trial quality
did not differ significantly in relation to selection history
(F = 0.77; df = 1,6;
P = 0.4142).
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DISCUSSION |
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Top
Abstract
Introduction
Materials & Methods
Results
Discussion
References
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This experiment clearly demonstrates an effect of nature
on O2 max. The average
difference in O2 max
between mice from genetically selected and control lines is 6% (Table
3; adjusted means of whole-animal values). Thus 10 generations of
selection for a single behavioral trait, voluntary activity on running
wheels, resulted not only in a shift in mean activity levels but also in a correlated response in
O2 max. Our results
suggest a mechanistic link between habitual activity levels and aerobic
capacity: some of the genes that influence wheel-running behavior must
also influence O2 max.
Nurture had an effect on
O2 max that was similar
in magnitude to the effect of nature (Table 3; 6% difference in
adjusted means of whole-animal values). Several previous studies of
rodents have also shown that voluntary wheel-running activity results in increased aerobic capacity. MacNeil and Hoffman-Goetz (23) reported
that, after 8 wk of voluntary wheel running, male house mice (C3H/He)
had 21% higher O2 max
values compared with sedentary controls. Overton et al. (25) found a
20% difference between sedentary and wheel-access female rats (SP-SHR)
but only a 9% difference in similarly treated male rats after 4 wk of
voluntary exercise. Lambert and Noakes (22) found a 9% difference in
O2 max between wheel-access and sedentary male rats (Long-Evans) after a
12-wk exposure.
Several protocol differences may explain the smaller training effect
that we observed (6% increase in
O2 max) compared with other studies. First, the animals in this study were neither
prescreened for running ability (e.g., Ref. 25) nor divided into
activity categories before analysis (e.g., Ref. 22); therefore, the
selected group mean (Tables 1-3) includes data from mice that
exhibited low levels of activity. Second, animals in our study were
given access to wheels at a younger age (22 days) and smaller body mass (10 g), which may have limited early activity (see Fig. 1).
Finally, the way O2 data are
reported may affect apparent differences among groups. Among species
of mammals, exercise
O2 max has been
empirically determined to scale approximately as
mass0.8. Alternatively,
O2 max expressed per
unit body mass scales as
mass
0.2 (20, 31). Although
this relationship has not been extensively studied within species of
mammals,
O2 max
expressed per unit body mass clearly shows a significant negative
relationship with body mass within laboratory house mice (Fig.
4); the smallest individuals have the
highest mass-specific rates of
O2. Therefore, expressing the
ratio of O2 to unit body mass
inflates the group difference in comparisons between lighter, trained
and heavier, untrained animals. In the present study, when
O2 max is expressed per
unit body mass (Table 3), the apparent magnitude of the difference between wheel-access and sedentary mice doubles to 12% because wheel-access mice are >4 g lighter than sedentary mice.
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In our analysis, the interaction between line type and exercise group
was not statistically significant (P > 0.2). Lack of interaction implies that the effects of selection and
exercise group are independent and additive, not dependent on genotype. However, ANOVA has relatively low power to detect
genotype-by-environment interaction (32). To explore a possible
genotype-dependent training response in more detail, we analyzed the
sedentary group and the wheel-access group separately with one-way
ANCOVA (body mass and trial quality as covariates). Analysis of the
sedentary group indicated that
O2 max was
significantly higher in mice from selected lines compared with mice
from control lines (F = 11.34; df = 1,6; P = 0.0151). Analysis of the
wheel-access group, however, indicated that
O2 max did not differ
significantly between selected and control lines
(F = 2.21; df = 1,6;
P = 0.1881). Thus trainability may
differ between line types. If this difference is real, then one
possible explanation is that the control mice were running at
a higher relative intensity (i.e., at a higher percentage of O2 max), which, over
the course of the experiment, led to a larger relative increase in
O2 max. In
any case, future studies with larger sample size will be required to
test the hypothesis that sensitivity to training is genotype dependent
in these mice.
Our estimate of O2 max
is similar to others previously reported (Fig. 4). Our empirical
results also closely match those predicted by an equation developed by
Fernando et al. (13) to predict
O2 of mice running on a
treadmill, on the basis of body mass and running velocity
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O2 max), this equation
predicts 295 vs. 317 ml/h found in our study.
In this experiment, animals that had access to running wheels had a
significantly lower RER at
O2 max compared with
sedentary animals (Table 3). Selection history did not affect RER, even though animals from selected lines had higher aerobic capacity. It is
tempting to ascribe the lowered RER in the wheel-access animals to a
training adaptation involving increased fat metabolism. At this
workload, however, hyperventilation, causing increased CO2, confounds interpretation
of RER with respect to fat oxidation, particularly because run quality
differed significantly between sedentary and wheel-access mice. To our
knowledge, no other estimate of RER at
O2 max is available for
house mice. Our estimates of RER (Table 3) are somewhat low but within
the range of values reported for rats (e.g., Refs. 5, 7, 24).
As noted by others working with rats (22), we found that mice with
access to activity wheels were significantly more cooperative during
treadmill trials than were sedentary mice. The subjective measurement
of trial quality was not significantly correlated with
O2 max (see
also Ref. 6 on serum corticosterone levels during treadmill exercise),
but it was positively correlated with both speed at which
O2 max was attained and
the maximum speed attained before termination of the
O2 max trial.
Mice that received higher subjective scores for trial quality were
those that were able to run without much external stimulation (i.e.,
without much electrical stimulation or manual prodding). Fernando et
al. (13) noted that volitional running was easily maintained in mice
without the use of electrical stimulation at speeds below 1.2 km/h (see also Ref. 6). In our study, the starting speed, 1.5 km/h, was above the
speed for volitional running; thus all mice in our study required some
external stimulation.
As reported by others (e.g., Refs. 11, 14, 22, 28, 29), the present study revealed large individual variation in average daily running distance (Fig. 2). As expected, mice from lines that had been subjected to 10 generations of selection for high activity levels (30) ran significantly more total rev/day than did mice from unselected control lines. The significant difference in total activity during the first 2 wk between selected and control lines is caused mainly by the mice from the selected lines running faster, not by their running during a greater fraction of the day. Over the course of the experiment, total rev/day increased as a result of increases in both the number of 1-min intervals of activity and average rpm (Fig. 1; Table 1).
Previous studies of both house mice (23) and rats (22, 28) show that male animals with access to wheels gain less weight than do sedentary controls, even with similar or higher rates of food intake (however, see Ref. 26). We observed a similar pattern in body mass changes. Body masses of the different groups were not different at the beginning of the experiment, but after 7-8 wk of access to the wheels the wheel-access mice were significantly lighter than sedentary mice (Table 1). Furthermore, within the wheel-access group, total daily wheel running averaged over the last week of exposure to wheels was negatively correlated with final body mass (Fig. 2). The mechanism underlying the difference in mass gain is unknown.
In summary, we developed and tested an animal model to study the
effects on aerobic exercise metabolism of both nature and nurture.
Consistent with previous studies (22, 25, 28, 29), we found that access
to wheels significantly reduced body mass, reduced RER at
O2 max, and increased
O2 max. Our results are unique in that we demonstrated a significant effect of genetic selection history on
O2 max. These results
suggest that habitual activity levels and
O2 max are positively
genetically correlated in house mice. Evidence for genotype-sensitive
training effects, however, was equivocal.
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ACKNOWLEDGEMENTS |
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We thank S. J. Davis, S. S. Newton, and K. F. Klomberg for assistance with mouse husbandry and data entry; R. R. Peterson, J. A. Gundlach, and staff for excellent animal care; and K. E. Bonine, G. D. Cartee, P. Koteja, and M. Nepokroeff for helpful discussions and comments on early versions of the manuscript. We also thank Lafayette Instruments and San Diego Instruments for equipment donations.
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FOOTNOTES |
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This project was supported by National Science Foundation Grants IBN-9111185 and IBN-9157268 (T. Garland), the University of Wisconsin Graduate School (T. Garland), and National Heart, Lung, and Blood Institute Grants HL-34817 and HL-37680 (G. C. Sieck).
Present address of P. A. Carter: Dept. of Zoology, Washington State Univ., Pullman, WA 99164.
Address for reprint requests: T. Garland, Dept. of Zoology, 430 Lincoln Dr., Univ. of Wisconsin, Madison, WI 53706-1381 (E-mail: tgarland{at}macc.wisc.edu).
Received 26 March 1997; accepted in final form 25 August 1997.
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REFERENCES |
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Top
Abstract
Introduction
Materials & Methods
Results
Discussion
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