Does daily activity level determine muscle phenotype?
1 Brain Research Institute, University of California Los Angeles, Los
Angeles, CA 90095-1761, USA
2 Department of Physiological Science, University of California Los Angeles,
Los Angeles, CA 90095-1761, USA
3 Faculty of Political Science and Economics, Matsusaka University,
Matsusaka, Japan
* Author for correspondence (e-mail: rrr{at}ucla.edu)
Accepted 8 August 2005
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Summary |
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Key words: daily integrated EMG, daily EMG duration, muscle fiber type composition, motor unit recruitment, rat
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Introduction |
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The role of activity in defining muscle properties has also been examined
using chronic electrical stimulation to influence the enzyme expression and
contractile properties of skeletal muscles. These observations have been used
to argue that the level of activation largely defines the properties of the
muscle (Eken and Gundersen,
1988; Pette and Vrbova,
1992
). However, chronic stimulation of a muscle often induces
muscle atrophy (Eisenberg et al.,
1984
; Salmons and Sreter,
1976
), and in many cases the changes in phenotype are minimal or
at best incomplete, even when the muscles are stimulated for as much as 24 h
day-1 (Edgerton et al.,
1996
; Lewis et al.,
1997
; Pette et al.,
2002
).
In the cat soleus, a muscle that usually is composed exclusively of slow
fibers, even the most active motor units were reported to be active for less
than 4 h day-1 (Hensbergen and
Kernell, 1997). For other muscles containing slow fibers, such as
the tibialis anterior (TA) in cats and Rhesus monkeys, even the most recruited
motor units appear to be active for less than 1 h day-1, suggesting
that prolonged periods of activation are not necessary to sustain even the
slow fiber phenotype (Hodgson et al.,
2001
; Hensbergen and Kernell,
1997
; Pierotti et al.,
1991
).
Given the extensive use of the rat model for studying the mechanisms by
which a muscle fiber phenotype is determined as well as muscle mass maintained
or even enlarged (Booth and Baldwin,
1996), it seems important to define quantitatively the normal
daily activity levels of muscles having different fiber type compositions and
functions. While we postulate that only relatively short periods of muscle
fiber activation are sufficient to sustain the normal mass and phenotype of
slow muscle fibers, the absence of a clear understanding of what the normal
activity levels are for flexor and extensor and for slow and fast muscles of
rats housed in standard cages precludes a clear conclusion. Thus, the purposes
of this study were to determine and compare (1) the daily activity levels of a
slow plantarflexor (soleus), a fast plantarflexor (medial gastrocnemius, MG),
a fast dorsiflexor (TA), and a fast knee extensor (vastus lateralis, VL) in
adult female rats housed in typical sedentary cages; and (2) the relationship
between the daily activity level and the reported
(Delp and Duan, 1996
) fiber
type composition (percent slow fibers) of each muscle studied. Preliminary
results have been presented in abstract form (Zhong et al., 2003,
2004
).
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Materials and methods |
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EMG implants
The rats were anesthetized with ketamine hydrochloride (100 mg
kg-1 body mass) and xylazine (8 mg kg-1 body mass)
administered intraperitoneally (i.p.). Supplemental doses (30% of the initial
dose, i.p.) were given as needed. Under aseptic conditions, a skin incision
was made along the sagittal suture of the skull. The scalp musculature and
underlying connective tissues were reflected laterally and the exposed skull
was dried thoroughly. Three screws were anchored firmly to the skull and a
9-pin (gold-plated) amphenol connector was cemented (dental cement) to the
skull and screws. Eight multistranded Teflon®-insulated stainless-steel
wires (AS 632, Cooner Wire Co, Chatsworth, CA, USA) were led
subcutaneously from the connector to the hindlimb (see below). The ninth wire
was embedded in the middle back region and served as a common ground. The
undersurface of the headplug between the pins and the wires was sealed with
epoxy resin to prevent any body fluid seepage into the contact area.
Skin incisions were made in the hindlimb to expose the soleus, MG, TA and
VL muscles. Two wires from the headplug were inserted into each of the
following: the midbelly of the soleus, and a deep region (i.e. close to the
bone) of the midbelly of the TA, MG and VL. These anatomical locations were
chosen to ensure a consistent sampling site across rats and to sample a
predominantly slow fiber type area in the soleus, and an area having the
highest proportion of slow fibers (3035% slow fibers) in the deep
regions of the MG, TA and VL (Delp and
Duan, 1996
). The wires were inserted into each muscle region
(
23 mm apart) by passing them individually through a 23-gauge
hypodermic needle. Recording electrodes were made by removing
0.5 mm of
insulation from each wire. Following back-stimulation of the muscle through
the headplug to ensure the proper placement of the electrodes, each lead was
secured with a suture at its entry and exit from the muscle. This procedure
effectively secured the electrodes in the muscle belly. The bared tips of the
wires were covered by gently pulling the Teflon® coating over the tips to
avoid recording extraneous potentials. All incisions were closed using 4-0
Ethilon® suture. These procedures are used routinely in our laboratories
(Roy et al., 1985
;
Roy et al., 1991b
).
The rats were allowed to fully recover from anesthesia in an incubator (27°C) and were given lactated Ringers solution (5 ml, subcutaneously). PolyFlex®, a general antibiotic, was administered (100 mg kg-1, subcutaneously, twice/day) during the first 3 days of recovery. The rats were housed in polycarbonate cages (26 cm x 48 cm x 20 cm) individually and the room was maintained at 26±1°C, 40% humidity and a reversed 12 h:12 h light:dark cycle (dark from 9:00 h to21:00 h). Rats were supplied with Purina® rat chow and water ad libitum.
EMG recordings and analyses
All electromyogram (EMG) recordings were performed using the same cages in
which the animals were normally housed and were initiated at least 1 week
after the implant surgeries. After this 1 week of recovery, no evidence of
appreciable signal artefacts with the animals at rest or in motion were
observed. The housing conditions were considered to be `normal' for
experimental rats, since they are the usual conditions under which rats are
housed before characterization of the muscle properties of a `control'
population of animals. A nine-conductor swivel (Alice King Chatham Medical
Arts, Inglewood, CA, USA) was mounted on the top of each cage, allowing the
animals to move freely during the recordings. Signals were amplified
(x1000, custom-built portable amplifiers) upon exiting the swivel, and
then recorded digitally at 2 kHz on a desktop computer using custom
acquisition software. Visual inspection of the EMG signals indicated stable
baseline levels with no fibrillation potentials, which remained stable during
passive manipulation of the limb. Raw EMG data were transferred to CD-ROM for
subsequent analysis. Recordings began between 08:00 h and 10:00 h and were
concluded 24 h later.
The EMG data were analyzed using in-house software developed using LabVIEW
(National Instruments, Houston, TX, USA). The methods have been reported in
previous publications (Edgerton et al.,
2001; Hodgson et al.,
2001
). Briefly, all EMG data were first reviewed by displaying the
recorded data on a computer monitor at selected time resolutions ranging from
fractions of a second to several minutes of data on the computer screen.
Segments of data containing interference were identified and excluded from
further analysis. Typically these were sections containing 60 Hz noise or
large amplitude, relatively slow transients across all channels. The remaining
data were digitally high-pass filtered at 10 Hz and rectified. Mean EMG values
of 40 ms time epochs were calculated from these data, effectively smoothing
with a 12.5 Hz low pass filter and decimating the data to 25 samples
s-1. Amplitude histograms were constructed from the processed EMG
signals from each muscle for each hour of the day. Integrated EMG (IEMG)
values were calculated by multiplying each bin count by its corresponding
amplitude, and then summing these values over all bins. The duration of EMG
activity was calculated by summing all bin counts above a threshold level. The
threshold level was determined by generating amplitude histograms of EMG data
when no activity was apparent in any muscle and the animal was assumed to be
inactive. The threshold level was set at the highest bin required to exclude
95% of the baseline data. Mean burst amplitudes of EMG activity were
calculated by dividing the burst integral by the burst duration. Data were
corrected to properly represent each hour of activity in those instances where
interference excluded some data from the analyses. The daily mean EMG
amplitude was calculated by dividing the IEMG by 24 h.
Statistical procedures
Group means and standard deviations (S.D.) are given where
appropriate to show trends and variability in the data. Ranges in the data and
the number of observations are provided in the tables and figures. In many
cases, these ranges did not overlap. The Wilcoxon Signed-Rank test was used to
test for significant differences between pairs of muscles from each animal.
Significance was set at P<0.05. The Wilcoxon test gave P
values of 0.028 (N=6) or 0.043 (N=5) for the differences
found to be significant. Pearson product correlation coefficients were used to
determine the relationship between fiber type composition and activity
level.
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Results |
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The distributions of EMG amplitudes (based on 40 ms bins) during a 24 h
period for each muscle in a representative rat are shown in
Fig. 4A (thick line). The broad
peak extending from the zero amplitude bin (leftmost portion of curve) shows
that the soleus was active at low levels for prolonged periods, whereas the
other muscles had higher counts at zero amplitude and sharper declines in the
amplitude count, indicating longer periods of inactivity in these muscles.
Another way to represent the duration of activity at different recruitment
levels is to plot the time that the EMG activity exceeded a given amplitude
level (Fig. 4B).
Mathematically, these curves plot the integrals of all data points to the
right of the corresponding EMG amplitudes in
Fig. 4A. Note that the
y-axis is a logarithmic scale in
Fig. 4A, but a linear scale in
Fig. 4B. These plots indicate
that almost all of the activity in all of the muscles was at relatively low
levels when compared to their peak EMG amplitudes. For example, the soleus
muscle had peak amplitudes of 0.2 mV in all of the animals, yet the EMG
amplitudes remained below 0.05 mV (i.e. 25% of the peak) for
21 h of the
day. This observation indicates that some muscle fibers, even in the
relatively highly active soleus muscle, are activated for relatively short
periods of the day (i.e. <3 h). Data from the other muscles indicate much
lower levels of activity for a majority of the day.
|
If we make the conservative assumption that EMG amplitudes greater than 0.1
mV represent full recruitment of the soleus muscle, then we can estimate that
the duration of activity above 0.1 mV represents the total time that all
soleus motor units were active. The soleus muscles in our sample of animals
were active at >0.1 mV for 15 s to 41 min per day. A higher amplitude for
full recruitment would indicate even shorter periods of full recruitment. For
example, if we assumed full recruitment at 0.15 mV, the total duration for
which all fibers were active would drop to between 5 and 32 s
day-1. The daily distribution of EMG amplitudes in the other three
muscles actually reached higher amplitudes than in the soleus
(Fig. 4A). This was confirmed
in all of the rats studied. A threshold of 0.15 mv (50% peak amplitude)
for the other three muscles yields durations for full recruitment between 40 s
and 17 min day-1. A threshold of 0.225 mV (70% peak amplitude)
reduced the durations to 5 s to 3 min day-1.
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Discussion |
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Variation in activity levels across rat hindlimb muscles
The relative levels of EMG activity of hindlimb muscles in the rats in the
present study are consistent with the results of previous EMG studies
(Alford et al., 1987;
Blewett and Elder, 1993
;
Fournier et al., 1983
) and
with the duration of activities reflected in whole body movements
(Block and Zucker, 1976
;
Moore and Bickler, 1976
;
Mouret and Bobillier, 1971
)
over prolonged periods of time during normal cage activity. The present study,
however, provides the most comprehensive analysis of the daily activity of
four rat hindlimb muscles. A majority of the muscle activity occurred during
the dark phase of the circadian cycle and the soleus was the most active
muscle studied. Interestingly, the mean EMG amplitudes during periods of
muscle activity were almost exactly the same during the light and dark
periods, suggesting similar levels of recruitment but for much shorter periods
of time during the light period. In the present experiments, daily IEMG in
soleus across all rats was between 24, 16 and 710 times
the corresponding values for the MG, VL and TA, respectively. These results
are consistent with previous data from rats, e.g. the soleus total daily IEMG
activity has been reported to be between 310 and 20 times higher than
for the MG and TA, respectively (Alford et
al., 1987
; Fournier et al.,
1983
). The daily mean EMG amplitudes for the MG, VL and TA bursts
were generally similar, i.e. at
5% of the peak values recorded, and the
soleus daily mean EMG amplitude was about twice the amplitude for the other
muscles, i.e. at about 10% of its peak value. Since the duration of activity
is closely linked to the overall activity measured as IEMG, this suggests that
the duration of time that a motor pool is activated provides a rough estimate
of the total activity of that motor pool. Some activity was detected in the
soleus for 1115 h per day, similar to the findings in a report by
Blewett and Elder (1993
),
whereas the TA was active for only 23 h per day. The MG was active for
59 h and the VL, which was the most variable of the muscles recorded,
was active for 314 h day-1. Thus, the slow plantarflexor
(soleus) was more active than the fast plantarflexor (MG) and fast knee
extensor (VL) muscles, which in turn were more active than the fast
dorsiflexor (TA) muscle. These activity durations would be expected to
represent only the most readily excitable motor units within each motor pool.
However, each of these muscles contains a population of slow type motor units,
which must be maintained by the short durations of activity observed in these
muscles.
We also attempted to evaluate the contribution of locomotion to the daily activity observed in our subjects. Superimposed on the distribution of daily activity in Fig. 4 are distributions of EMG amplitudes predicted from the locomotor-like bursting patterns of activity as shown in Fig. 1. The shape of these distributions is quite characteristic for locomotion. The shaded plot has been scaled to represent the distribution of amplitudes predicted for 10 min and the dark thin line above it for 20 min of locomotor-like activity, i.e. the time of each bin has been divided by the duration of the original data and then multiplied by either 10 or 20 min. Any activity that appears above the curve representing the total daily activity (thick line) exceeds the measured daily activity and, therefore, is an overestimate of the activity occurring within a 24 h period. Note that portions of the curve representing 20 min of locomotor-like activity lie outside the total daily curve for the soleus, indicating that the maximum time that the rats could have spent in locomotor-like activity was between 10 and 20 min day-1. The first peak on the ordinate of the soleus EMG distribution during locomotor-like activity corresponds to the near zero amplitude in this muscle during the swing phase of locomotion and the second peak represents the predominant EMG amplitude during stance (see Fig. 1). The majority of soleus EMG amplitudes in the daily distribution seem to occur at amplitudes slightly below the highest burst amplitudes observed during the stance phase of the locomotor-like activity, suggesting that a majority of the soleus activity occurs during prolonged periods of posture (compare the EMG amplitudes during posture vs locomotor-like activity in Fig. 1).
|
There is a poor correlation between the percentage of slow fibers in a
muscle and the daily duration of activation (r=0.08)
(Fig. 5C) and IEMG
(r=0.06, data not shown). These weak relationships are apparent for
the muscles within a species and across the four species for which data are
shown. For example, there is a threefold range in the duration of activity for
the rat MG, TA and VL muscles, but the percentages of slow fibers are about
the same in each muscle. Also, the percentage of slow fibers ranges from
0 to 80% for muscles that are active for less than 200 min
day-1 across species. We noted a strong negative correlation
(r=0.95) between the percent slow phenotype composition and
the duration of EMG activity in the human muscles surveyed
(Fig. 5C). Similar comparisons
from other investigators have revealed mixed results
(Kern et al., 2001
;
Monster et al., 1978
). Our
conclusion differs from that drawn by Kernell and Hensbergen
(Kernell and Hensbergen, 1998
)
who demonstrated a positive correlation (r=0.76) between duty time,
i.e. the ratio between total on-time and total sampling time, and fiber type
composition for three predominantly fast muscles in cats, i.e. the TA,
extensor digitorum longus and peroneus longus. If these authors had added the
data for the soleus muscle to that plot, however, the soleus data point would
fall at a much lower value of duration than predicted from the regression line
through the other three muscles. Our general conclusion is that although the
level of activity can play some role in the modulation of fiber type, it does
not play a predominant role.
Hypothetical muscle fiber recruitment model
An ideal examination of the relationship between fiber type and activity
levels would be based on actual recruitment patterns of individual motor units
relative to the phenotype of that unit, but such direct observations have not
been reported. There have been some reports of the activity patterns of single
motor units over prolonged periods from muscles of a predominant phenotype
(Fishbach and Robbins, 1969;
Hennig and Lomo, 1987
). In
these cases, however, there was a high probability that the recordings were
from the most excitable (smaller) motor units.
Our data suggest a wide range of durations of activity even within an
individual fiber phenotype. Fig.
6 illustrates this notion using a hypothetical model of the
activation of a muscle by relating the recruitment of motor units and muscle
fibers to EMG amplitude. The broken red line in
Fig. 6 is a plot of the data
presented in Fig. 4B and shows
the duration of soleus EMG activity at the EMG amplitude indicated on the
abscissa. The black line illustrates the hypothetical recruitment of motor
units, measured as a percentage of the total pool for the EMG amplitudes
displayed on the abscissa. This example shows a motor pool that is 100%
recruited at 70% of the maximum EMG amplitude of the muscle. The
remaining muscle output would be achieved by increasing the discharge
frequency of the already recruited motoneurons. The blue line represents the
number of muscle fibers recruited at the EMG amplitudes displayed on the
abscissa. A linear relationship between the number of muscle fibers recruited
and the EMG amplitude is assumed until all muscle fibers are recruited. The
vertical dotted line at 25% of the maximum EMG amplitude illustrates our
finding that the slow soleus muscle is active at
25% of its maximum for
4 h day-1 (Fig.
4). Thus, all of the muscle fibers recruited above this EMG
amplitude (threshold) would be active for less than 4 h day-1. When
the EMG is at 25% maximum,
35% of the muscle fibers (dotted blue line)
and
70% of the motor units (black line) would be recruited. Although the
precise relationships among EMG amplitude, number of motor units and the
number of muscle fibers cannot be determined directly, the model serves to
illustrate the high probability that some slow muscle fibers in the rat soleus
muscle may be recruited for relatively short periods of time each day,
suggesting that prolonged periods of activation may not be a requisite for the
maintenance of fiber mass or phenotype. The model may be further explored
using the down-loadable excel file supplied as supplementary material.
|
Several assumptions were necessary to construct the model shown in Fig. 6:
This simple model illustrates a key finding of this study: muscle fiber phenotype is maintained even in those fibers that are inactive for substantial periods of time. Assumptions 1 and 2 are conservative assumptions regarding the relationship between EMG and the number of active motor units. Because the estimates chosen for maximum EMG are likely to be lower than actually occurs, our predictions of the duration of activation during normal activity are most likely high.
These observations are inconsistent with the hypothesis that prolonged
daily activity is the major determinant of the contractile and biochemical
properties of skeletal muscles. In the TA, for example, the low-threshold,
presumably slow, muscle fiber population must be maintained by activity that
lasts for only 23 h day-1 whereas some high-threshold,
presumably fast, muscle fibers may be maintained by as little as 12 min
of activity per day. If activity or activity patterns were the sole
determinant of muscle properties, these limitations might be expected to apply
to all muscle fibers of the same phenotype, regardless of the muscle in which
they are found. Based on this logic, conversion to a slow fiber phenotype
should be accomplished by less than 3 h ofactivation per day. Typically, the
patterns of daily stimulation used to demonstrate activity-related changes in
muscle properties are applied for much longer periods of time, as noted above,
and the phenotype conversion is consistently incomplete
(Edgerton et al., 1996).
Furthermore, chronic electrical stimulation paradigms often result in fiber
atrophy in muscles of control rats
(Eisenberg et al., 1984) and
are ineffective in maintaining the size of inactivated or unloaded muscles
(Al Amood et al., 1991
;
Canon et al., 1998
;
Hennig and Lomo, 1987
;
Leterme and Falempin, 1994
).
In contrast, short bouts of load-bearing activity attenuate the loss of muscle
mass associated with chronic periods of decreased neuromuscular activity
(Roy et al., 1991c
;
Edgerton and Roy, 1996
). For
example, extensive attempts to reverse muscle atrophy as a result of
spaceflight or hindlimb unloading suggest that skeletal muscles may require
specific and finely tuned patterns of activity that integrate several
consequences of neural activation, particularly the development of force, to
maintain mass and phenotypic properties that would be considered `normal'
(Alkner and Tesch, 2004
;
Dudley et al., 1999
;
Edgerton and Roy, 1996
;
Roy et al., 2002
). Therefore,
some factors such as muscle loading may be a consequence of activation under
specific conditions, but it seems clear that electrical activation alone does
not adequately define the conditions that lead to the expression of normal
muscle properties.
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Acknowledgments |
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Footnotes |
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References |
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