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The Journal of Neurophysiology Vol. 88 No. 2 August 2002, pp. 839-846
Copyright ©2002 by the American Physiological Society
1Institute of Pharmacology and Toxicology, CH-8057, 2University Hospital, Department of Clinical Immunology, CH-8044, University of Zürich, Zürich, Switzerland; and 3Department of Physiology, 2300RC, Leiden University Medical Center, Leiden, The Netherlands
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 ABSTRACT
 INTRODUCTION
METHODS
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DISCUSSION
REFERENCES
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Deboer, Tom,
Adriano Fontana, and
Irene Tobler.
Tumor Necrosis Factor (TNF) Ligand and TNF Receptor Deficiency
Affects Sleep and the Sleep EEG.
J. Neurophysiol. 88: 839-846, 2002.
Tumor necrosis factor
(TNF) and lymphotoxin-
(LT-) are proinflammatory cytokines
involved in host defense and pathogenesis of various diseases. In
addition, there is evidence that TNF is involved in sleep. TNF and
LT- both bind to the tumor necrosis factor receptors (TNFR).
Recently, it was shown that TNF receptor 1 (TNFR1) knockout mice (R1KO)
sleep less during the light period than controls. We investigated the
effect of a TNF and LT- double deficiency on sleep in mice (Ligand
KO) and compared their sleep with that of R1KO, TNFR2 knockout (R2KO)
mice, and wild-type (WT) controls. All mice were adapted to a 12:12 h
light:dark cycle and their electroencephalographs (EEG) and
electromyographs (EMG) were continuously recorded during a baseline
day, 6-h sleep deprivation (SD), and 18-h recovery. Ligand KO and R2KO
had 15% less rapid eye movement (REM) sleep during the baseline light
period due to a reduction in REM sleep episode frequency. After SD, all
genotypes showed an initial increase in slow-wave activity (SWA) (EEG
power density between 0.75 and 4.0 Hz) in non-REM sleep, which
gradually declined in the following hours. In Ligand KO the increase
was mainly caused by an increase in fast SWA (2.75-4.0 Hz), which was
also increased in R2KO. In contrast, in R1KO mice the increase was
limited to the slow portion of SWA (0.75-2.5 Hz). R2KO and WT mice
showed increases in both frequency ranges. The sub-division into fast
and slow SWA frequencies corresponds to previous electrophysiological data where the two types of slow-waves were induced by either excitatory or inhibitory stimuli. Our data suggest that in Ligand KO
the SWA increase is caused by an increase in excitatory input to the
cortex, whereas in R1KO this input seems to be almost absent.
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INTRODUCTION |
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TOP
ABSTRACT
INTRODUCTION
METHODS
RESULTS
DISCUSSION
REFERENCES
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Tumor necrosis factor (TNF) is
produced by macrophages and circulating monocytes and is a
pro-inflammatory cytokine involved in host defense and pathogenesis of
various diseases (Aggarwal and Vilcek 1992
;
Beutler 1992). In the CNS TNF is produced in astrocytes
(Lieberman et al. 1989) and microglial macrophages (Frei et al. 1987) and influences the peripheral immune
system through the lymphatic pathway (Dickstein et al.
1999). There is an extensive literature suggesting that TNF and
other cytokines may also be involved in sleep regulation. Thus it was
shown in several mammalian species that administration of TNF increases nonrapid eye movement (NREM) sleep (Dickstein et al.
1999; Fang et al. 1997; Kapas et al.
1992; Shoham et al. 1987; Terao et al. 1998). Moreover, inhibition of endogenous TNF after
administration of antibodies or soluble receptors inhibits spontaneous
sleep (Takahashi et al. 1995a,b) and attenuates the
increase in sleep after sleep deprivation (SD) (Takahashi et al.
1996). Hypothalamic levels of TNF mRNA (Bredow et al.
1997) and protein (Floyd and Krueger 1997) are
increased during the light period in rats, i.e., during the main sleep
period of the animals. These and other findings led to the notion that
TNF is involved in sleep regulation (reviewed by Krueger et al.
1999).
Two cell-surface receptors for TNF, TNF receptor 1 and 2 (TNFR1 and
TNFR2) (55 and 75 kDa in size, respectively) have been characterized
(Hohmann et al. 1989, 1990; Schall et al.
1990). The two receptors mediate distinct actions
(Schutze et al. 1994; Vilcek and Lee
1991) but cannot be differentiated by pharmacological means. It
is known that lymphotoxin- (LT-) binds to the same receptors as
TNF, and consequently, administration of TNF and LT- leads to
similar biological responses in vivo and in vitro (Beutler and
Van Huffel 1994). This redundancy in receptor binding and their
overlapping expression pattern renders a distinction between the
function of TNF and LT- rather difficult. For this purpose, TNF
receptor-deficient mice were generated, which should enable the
dissection of the immunological function of the receptors (Erickson et al. 1994; Pfeffer et al.
1993; Rothe et al. 1993; Ruby et al.
1997). In addition, it was shown that TNFR1 knockout (R1KO)
mice show less sleep during the light period and do not increase sleep
after application of exogenous TNF (Fang et al. 1997),
indicating that TNF affects sleep via TNFR1.
An alternative approach to investigate the role of the TNF receptors is
by removal of the ligands, TNF and LT-. The consequences of the
combined deficiency of TNF and LT- on the immune system were
investigated recently by generating TNF and LT- double-deficient mice (Amiot et al. 1997; Eugster et al.
1996). Our aim was to investigate the role of TNF receptors in
sleep and sleep regulation in these mice (Ligand KO). On the basis of
the results with R1KO mice, we expected that the Ligand KO mice would
show less sleep during the light period. To enhance physiological sleep
pressure, a sleep deprivation (SD) was performed and sleep and sleep
regulation of the double-deficient mice were compared with that of
wild-type control mice (WT) and R1KO and TNFR2 knockout (R2KO) mice.
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INTRODUCTION
METHODS
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DISCUSSION
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Animals
Adult mice of the four genotypes were used [WT,
n = 12; TNF and lymphotoxin- double deficient
(Ligand KO), n = 9; R1KO, n = 8; R2KO,
n = 8]. The KO mice were generated on 129/SV
background and backcrossed for 6 (Ligand KO) or 10 generations (R1KO
and R2KO) with C57BL/6. Normal C57BL/6 mice were used as WT controls. The animals were maintained on a 12:12 h light:dark schedule (lights on
from 0800-2000 h; daylight-type fluorescent tubes, 18 W, 50-100 lux
at the level of the mice), individually kept in Macrolon cages (36 × 20 × 35 cm), and placed in sound-attenuated chambers. Food and
water were available ad libitum. The animals were adapted for a minimum
of 3 wk to these conditions.
Surgery
The mice were implanted with electroencephalographic (EEG) and electromyographic (EMG) electrodes under deep pentobarbital sodium anesthesia (Nembutal sodium, 80 mg/kg ip, volume approximately 0.5 ml). Two gold-plated miniature screws (Ø0.9 mm), placed over the right occipital cortex (2-3 mm lateral to midline, 2 mm posterior to bregma) and the cerebellum (at midline, 1 mm posterior to lambda), served as epidural EEG electrodes. The EMG was recorded with two gold wires (Ø0.2 mm) inserted into the neck muscles. The electrodes were connected to stainless steel wires that were glued to the skull with dental cement. At least 3 wk were allowed for recovery. Age at recording onset was approximately 16 wk and did not differ between genotypes.
Experimental protocol
A 24-h baseline recording starting at lights on preceded the 6-h SD. Mice were also recorded during the SD and for the following 18 h. SD began at light onset and was performed by introducing objects (e.g., nesting material) into the cage, and later by tapping on the cage whenever the animal appeared drowsy or the EEG exhibited slow-waves. Halfway through the SD, the mice were provided with new cages, which induced additional stimulation and elicited exploratory behavior. To minimize stress, some material from the old cage was transferred to the new one. The mice were never disturbed during feeding and drinking.
The EEG and EMG signals were amplified (amplification factor
~2000), conditioned by analog filters (high-pass filter: 
3 dB at
0.016 Hz; low-pass filter: 3 dB at 40 Hz, less than 35 dB at 128 Hz), sampled with 512 Hz, digitally filtered (EEG: low-pass FIR filter,
25 Hz; EMG: band-pass FIR filter, 20-50 Hz), and stored with a
resolution of 128 Hz. EEG power spectra were computed for consecutive
4-s epochs by a fast Fourier transform (FFT) routine within the
frequency range of 0.25-25.0 Hz. Between 0.25 and 5.0 Hz, the values
were collapsed in 0.5-Hz bins and between 5.25 and 25.0 Hz the values
were collapsed into 1-Hz bins. EMG signals were integrated over 4 s and ambient temperature inside the cage was recorded at 4-s
intervals. All data were recorded simultaneously and stored on optical
disk. The EEG and EMG channels were calibrated by recording a 10-Hz
sine-wave, 300 µVPP signal before each recording.
Analysis
Vigilance states were determined for 4-s epochs as described
previously (Tobler et al. 1997). In short, waking was
scored when there was a high-EMG and low-EEG amplitude and high-
activity (EEG power density in the -band, 6.25-9.0 Hz), concomitant
with irregular, high EMG values, and NREM sleep when there was a
low-EMG and higher EEG amplitude compared with waking and high SWA,
rapid eye movement (REM) sleep when the EMG and EEG amplitude was low, and high- activity was visible in the EEG. Epochs containing EEG
artifacts were marked and excluded from the spectral analysis (12.0 ± 2.6% of recording time; >85% of all EEG artifacts
occurred in waking), but vigilance states could always be determined.
The duration and frequency of NREM sleep, REM sleep, and waking
episodes were determined according to criteria described previously (Deboer et al. 1994; Deboer and Tobler
1996). The algorithm is based on the frequency and duration of
interruptions of the vigilance state episodes.
Overall effects within a strain were analyzed by two-way analysis of variance (ANOVA) for repeated measures, with factors "time" and "condition," with the exception of spectral data where, due to intervals with low amount of sleep, resulting in missing values, a two-way ANOVA with factor time and condition was used. Differences between the four genotypes were analyzed by two-way ANOVA with factors "genotype" and time. Contrasts between WT and single KO groups were tested by post-hoc two-tailed t-tests when ANOVA reached significance.
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RESULTS |
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TOP
ABSTRACT
INTRODUCTION
METHODS
RESULTS
DISCUSSION
REFERENCES
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Vigilance states
Ligand KO and R2KO mice had 15% less REM sleep during the baseline light period than controls (Table 1). There were no differences in the amount of sleep between R1KO and WT mice. The lower amount of REM sleep in the Ligand KO and R2KO mice was reflected also in less REM sleep/total sleep time (TST) during the light period (Table 1). The reduced amount of REM sleep was mainly caused by a reduction in REM sleep episode frequency, which was not compensated by an increase in REM sleep episode duration (Table 2). Also, NREM sleep episode frequency was reduced in Ligand KO and R2KO and was compensated by an increase in NREM sleep episode duration. During the dark period, REM sleep episode frequency was reduced in all KO mice, compared with WT, and was compensated by an increase in REM sleep episode duration that reached the same duration as in the light period (Table 2).
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The time course of the vigilance states in the course of the entire experiment is illustrated in Fig. 1. During the first 4-6 h of the baseline light period, all KO mice had less REM sleep than WT, which reached significance in the Ligand KO and R2KO mice only (Fig. 1). The time course of waking and NREM sleep was indistinguishable between the four genotypes during baseline, and no differences were obtained in the response to SD. The amount of sleep during SD was negligible and did not differ between the genotypes (WT: 0.7 ± 0.2% of 6 h; Ligand KO: 1.1 ± 0.2; R1KO: 1.0 ± 0.3; R2KO: 1.6 ± 0.5; F = 1.594, P = 0.209 ANOVA factor "group"). REM sleep showed a prolonged increase after SD in all genotypes. NREM sleep was enhanced in the dark period only, except in R2KO mice where NREM sleep was increased immediately. Despite these differences, there was no significant difference in the effects of SD on NREM sleep and waking when the genotypes were compared.
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EEG power spectra
Ligand KO mice had higher absolute EEG power density in NREM sleep within the slow-wave range than the other genotypes. Thus power density between 0.75 and 2.5 Hz was higher in Ligand KO mice than WT and R1KO (Fig. 2) and higher in the 1.5-Hz bin than R2KO. There were no differences between genotypes in the waking and REM sleep EEG spectra (data not shown). After SD, all mice showed a similar increase in SWA (mean EEG power density 0.75-4.0 Hz) in NREM sleep (Fig. 1). However, there were distinct differences between the genotypes within the SWA band (Fig. 3). Thus the increase in Ligand KO and R2KO mice was mainly in the range of 2.75-4.0 Hz, while in WT and R1KO it was most prominent between 0.75 and 2.5 Hz (Fig. 3, top panels). During the recovery light period, this frequency range remained above baseline (BL) in Ligand KO and R2KO and above WT in Ligand KO (Fig. 3, top panels). Moreover, in the dark period power density in this frequency range was above WT levels in Ligand KO and R2KO in most of the 3-h intervals (Fig. 3, bottom panels). WT, R1KO, and R2KO showed a negative rebound in the range between 0.75 and 3.0 Hz in the dark period.
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Also, in frequencies above 5 Hz, SD elicited changes in the EEG power spectra in NREM sleep. Ligand KO and R2KO showed an increase in almost all frequency bins between 7 and 25 Hz (Fig. 3, top panels). In contrast, WT and R1KO mice showed only a small increase above BL around 9 Hz in the second 3-h interval of the recovery light period. In this frequency range, the Ligand KO also showed an increase above WT in the first 3-h interval of recovery (Fig. 3, top panels). In the last two 3-h intervals of the dark period, R2KO showed increases above WT in several bins between 15 and 22 Hz (Fig. 3, bottom right panel).
Slow-wave activity
Because of the differences between genotypes in the slow-wave
range of the NREM sleep EEG spectrum after SD (Fig. 3), and previous
results in mice suggesting that there is a difference in the effect of
SD on "slow" slow-waves (0.75-2.0 Hz) and "fast" slow-waves
(2.75-4.0 Hz) (Huber et al. 2000b), SWA was subdivided into these two bands (Fig. 4). During
baseline, both slow and fast slow-wave bands decreased in parallel
during the first part of the light period in all genotypes. At the
beginning of the dark period the fast slow-wave band increased above
the values of the slow band and remained higher during the dark period.
This increase was particularly evident in the Ligand KO, where fast SWA
increased above the WT level already during the last 2-h interval of
the light period (Fig. 4). After SD the relationship between the fast
and slow SWA bands in WT persisted. Both bands showed an increase above
baseline levels in the initial 2 h of recovery in WT and R2KO and
exhibited a subsequent negative rebound in the dark period. However, in
Ligand KO mice only the fast SWA band had increased above the baseline
level and remained high throughout the rest of the recovery period.
During the dark period, fast SWA was above levels reached by WT, and it
was not followed by a negative rebound. In contrast, in R1KO only the
slow SWA increased above baseline levels and showed a negative rebound during the dark period.
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DISCUSSION |
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TOP
ABSTRACT
INTRODUCTION
METHODS
RESULTS
DISCUSSION
REFERENCES
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No difference was found in the amount of sleep between the
genotypes. This is in contrast with previous data where a 20%
reduction in NREM sleep was reported for R1KO mice (Fang et al.
1997). Since this reduction was attributed to the deficiency of
a signal coming from the TNF R1 receptor, we expected that the Ligand
KO and our R1KO mice would sleep less as well. It is unlikely that in
our mice compensation occurs via a different mechanism, since we did not obtain less NREM sleep in any genotype. The present results are in
accordance with the interpretation that the reduction in NREM sleep
reported previously may be a consequence of differences in the genetic
background of the R1KO mice and WT control (Fang et al.
1997).
Since the mice do not sleep less when lacking either the ligand or the
TNFR1 receptor, the data suggest that the role of TNF in the regulation
of spontaneous NREM sleep is not as large as was suggested previously
(Fang et al. 1997; Krueger et al. 1999). Their relation with previous data obtained with TNF antibodies and
soluble TNF receptor fragments needs to be investigated further. These
results were obtained in rats and rabbits (Takahashi et al.
1995a,b) and mice may react differently to this type of
treatment. In mice it was also found that NREM sleep increases after
application of TNF (Fang et al. 1997). However, it is
known that mice often react differently to treatments than rats, e.g.,
mice become hypothermic, instead of producing a fever when infected
with influenza (Klein et al. 1992; Toth et al.
1995). Therefore the effects of TNF antibodies or soluble TNF
receptors still need to be investigated in mice.
The clear reduction in the amount of REM sleep in Ligand KO and R2KO
mice contrasted the lack of difference in NREM sleep. This reduction
was restricted to the light period and was due to a lower amount of
NREM sleep and REM sleep episodes. The reduction in NREM sleep episodes
was compensated by an increase in their duration, whereas the reduction
of REM sleep episode frequency was not compensated. In the dark period
all KO mice showed an increase in REM sleep episode duration to light
period levels, accompanied by a reduction in REM sleep episode
frequency. The absence of TNF receptors or their ligands seems to
reduce the probability of initiating REM sleep, a deficiency that can
only be compensated by increasing the duration of REM sleep episodes. The effects on REM sleep in the KO mice are similar to the effects of
chronic melatonin administration in Djungarian hamsters (Deboer and Tobler 1997) or of small amounts of a serotonin (5-HT) 1A receptor agonist administered into the peribrachial region of the
pedunculo pontine nuclei in cats (Sanford et al. 1994).
Melatonin is known to increase 5-HT levels throughout the brain
(reviewed in Sandyk 1995), and both melatonin and 5-HT
treatments reduced REM sleep episode frequency without changing its
duration. TNF is known to increase 5-HT uptake in the brain by
modulating 5-HT transporter function (Mössner et al.
1998). Therefore the removal of TNF or its receptor may
increase the level of 5-HT in the brain. Indeed, it was shown that in
mice deficient of the TNF- gene 5-HT metabolism is increased with
enhanced 5-HT levels in several brain areas, including the medulla
oblongata/pons, a brain area involved in REM sleep regulation
(Yamada et al. 2000). The present data suggest that TNF
influences REM sleep by changing 5-HT levels through both R1 and R2 receptors.
Previously it was shown that mice strains differ in the composition of
fast and slow SWA (Franken et al. 1998; Huber et
al. 2000a). After SD, both fast and slow SWA increased above
baseline levels but the slow SWA increase persisted longer
(Huber et al. 2000b). The present results in the WT
confirmed this finding. Here we show that different frequencies within
SWA were enhanced after SD between the different genotypes. The slow
portion of SWA, which increased in WT, R1KO, and R2KO, corresponds to
the frequency of slow cortical oscillations (<1 Hz) and thalamic
clock-like oscillations (1-4 Hz) typical for sleep (Amzica and
Steriade 1998). In contrast, the fast SWA band, which was
increased in WT, R2KO, and the Ligand KO, corresponds to the intrinsic
delta activity of cortical neurons (3-4 Hz). The latter is the only
slow-wave oscillation that is induced by depolarization of the cell
membrane (Amzica and Steriade 1998). Differences were
also found in the higher frequency range (above 7-8 Hz), but the
differences to WT were not systematic and most of the time no
differences were found in this frequency range between any of the
genotypes. No differences were obtained between WT and R1KO, whereas
Ligand KO and R2KO showed a similar pattern in their differences to WT (Fig. 3). The results suggest that the increase in SWA after SD in the
Ligand KO is mainly caused by an excitatory input to the cortex, which
is enhanced above the normal input occurring during the dark period,
when fast SWA is increased as well. In contrast, in R1KO this
excitatory input seems to be almost absent.
The present results indicate that a similar increase in the traditional
SWA band after SD does not necessarily indicate a similar reaction in
the slow-wave range of the EEG spectrum. Detailed analysis of the EEG
power density spectrum within SWA reveals clear differences in how this
increase is achieved. Moreover, within the slow-wave range there seem
to be differences in recovery speed between fast and slow SWA
(Huber et al. 2000b). It has previously been shown in
rats that application of interleukin-1
in some cases not only
increased power density in the slow-wave range, but also in frequencies
above 10 Hz and between 16 and 25 Hz (Lancel et al.
1996). Here we show that depending on genotype, either the fast
or slow portions or the SWA band increases after SD. This may reflect
differences in the influence of TNF receptors on distinct groups of
neurons and stresses the importance of obtaining detailed spectral data.
In conclusion, the deficiency of one of two TNF receptors or the ligand to that receptor does not affect the amount of NREM sleep in mice. However, it does reduce the amount of REM sleep in a similar way as after administration of 5-HT into the brain. The increase in SWA after SD is changed in Ligand KO and R2KO mice where the increase shifted in the direction of fast slow-waves. Since these fast slow-waves are induced by an excitatory input to the cortex, the data suggest that, in Ligand KO and R2KO mice, SD causes an exaggerated excitatory input above the level normally found during the dark period.
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ACKNOWLEDGMENTS |
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We thank Dr. H. P. Eugster for providing the TNF ligand double-deficient mice, Dr. H. Bluethmann for providing the TNF R1 and TNF R2 KO mice, and M. Lueber for help with scoring.
This research was supported by Swiss National Science Foundation Grant 3100-053005.97.
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FOOTNOTES |
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Present address and address for reprint requests: T. de Boer, Dept. of Physiology, Leiden University Medical Centre, Postbus 9604, 2300 RC Leiden, The Netherlands (E-mail: Tom.de_Boer{at}lumc.nl).
Received 19 July 2001; accepted in final form 18 April 2002.
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REFERENCES |
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TOP
ABSTRACT
INTRODUCTION
METHODS
RESULTS
DISCUSSION
REFERENCES
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