Abstract
Mice enter an active hypometabolic state, called daily torpor when they
experience a lowered caloric intake under cold ambient temperature.
During torpor, the oxygen consumption rate in some animals drops to
less than 30% of the normal rate without harming the body. This safe
but severe reduction in metabolism is attractive for various clinical
applications; however, the mechanism and molecules involved are
unclear. Therefore, here we systematically analyzed the gene expression
landscape on the level of the RNA transcription start sites in mouse
skeletal muscles under various metabolic states to identify
torpor-specific transcribed regulatory patterns. We analyzed the soleus
muscles from 38 mice in torpid and non-torpid conditions and identified
287 torpor-specific promoters out of 12,862 detected promoters.
Furthermore, we found that the transcription factor ATF3 is highly
expressed during torpor deprivation and its binding motif is enriched
in torpor-specific promoters. Atf3 was also highly expressed in the
heart and brown adipose tissue during torpor and systemically knocking
out Atf3 affected the torpor phenotype. Our results demonstrate that
mouse torpor combined with powerful genetic tools is useful for
studying active hypometabolism.
Subject terms: Homeostasis, Transcriptomics
__________________________________________________________________
Ruslan Deviatiiarov et al. identify torpor-specific promoters with an
enriched binding motif and the transcription factor ATF3 highly
expressed during torpor deprivation. Knocking out Atf3 affected the
torpor phenotype, giving rise to molecular targets for studying and
translating hypometabolic states.
Introduction
Mammals in hibernation or daily torpor can reduce their metabolic rate
to 1–30% of that of euthermic states and enter a hypothermic condition
without any obvious signs of tissue injury^[38]1,[39]2. How mammals
adapt to such a low metabolic rate and low body temperature without
damage remains one of the central questions in biology. Mammals
maintain their body temperature (T[B]) within a certain range by
producing heat. In the cold, the oxygen requirements for heat
production increases at a rate negatively proportional to the body
size^[40]3. Instead of paying the high heat production cost, some
mammals can lower their metabolism by sacrificing body temperature
homeostasis. This condition, in which the animal reduces its metabolic
rate followed by whole-body hypothermia, is called active
hypometabolism^[41]4. As a result, the homeostatic regulation of body
temperature is modified, and the total energy usage drops. This
hypometabolic condition is called hibernation when it lasts for months
and daily torpor when it occurs daily.
Recently, Sunagawa proposed four conditions to be required in mammalian
active hypometabolism:^[42]4 1) tolerance to low body temperature, 2)
tolerance to low oxygen consumption, 3) suppression of body temperature
homeostasis, and 4) heat production ability under a low metabolic rate.
Of these conditions, 1) and 2) were found to be cell/tissue-specific or
local functions, which prompted researchers to analyze genome-wide
molecular changes in various tissues of hibernators, including the
brain, liver, heart, skeletal muscles, and adipose tissues. With the
development of high-throughput sequencing approaches, such as RNA-seq
and microarrays, a series of transcriptomic investigations were
conducted in well-studied hibernating animals, including ground
squirrels^[43]5–[44]8, bears^[45]9–[46]11, and bats^[47]12,[48]13.
Recent proteomics studies in ground squirrels using two-dimensional gel
electrophoresis^[49]14,[50]15 and shotgun proteomics^[51]16 also
explored the post-transcriptional regulation of hibernation.
Furthermore, several studies demonstrated epigenetic changes during
hibernation^[52]17,[53]18, and a relationship of miRNAs in the
process^[54]19.
Due to the lack of detailed genome information in hibernators, i.e.,
squirrels, bats, and bears, the interpretation of high-throughput
sequencing results is challenging in these animals. Instead, the mouse,
Mus musculus, has rich genetic resources and could overcome this
weakness. Notably, the mouse is well-known to enter torpor by
fasting^[55]20,[56]21, and we have developed an improved method to
initiate and detect fasting-induced torpor (FIT) in mice
reproducibly^[57]4. Furthermore, one group identified neurons
regulating the induction of FIT^[58]22, and our group identified
genetically labeled neurons that can induce a hibernation-like state in
mice^[59]23. Such recent discoveries make the mouse a suitable and
convenient animal model for studying active hypometabolism.
This study aimed to analyze the comprehensive gene expression at the
skeletal muscle by introducing mice as a model for active
hypometabolism, taking advantage of the rich and powerful genetic
technologies available for this animal. To reconstruct genome-wide
changes in gene expression, we performed Cap Analysis of Gene
Expression (CAGE) in soleus muscles taken from 38 animals under various
metabolic conditions. We found that entering torpor and restoring
activity were associated with distinct changes in the transcriptomic
profile, including marked changes in the distribution of transcription
start sites within a promoter (promoter shift). We also present
evidence that the torpor-specific promoters are related to the torpor
phenotype by deleting the gene.
Results
Fasting-induced torpor shows a reversible transcriptome signature
C57BL/6 J mice (B6J mice) enter FIT when deprived of food for
24 h^[60]4. In this study, torpor was defined as having a lower T[B]
and oxygen consumption rate (VO[2]) than the 99.9 % credible interval
of the baseline, which was defined individually for each animal. The
animals return to the normal condition without any damage even after
experiencing hours of extreme hypothermic and hypometabolic conditions.
To analyze the reversibility in peripheral tissue gene expression
during the FIT, we isolated soleus muscles from B6J mice on day 1 (Pre,
n = 4), 2 (Mid, n = 8), and 3 (Post, n = 4) at ZT-22 as experiment #1
(Fig. [61]1a). We chose these time points because B6J mice usually
start to enter torpor at around ZT-14, and at ZT-22, which is two hours
before the light is turned on, the animals are very likely to be
torpid^[62]4. Indeed, the VO[2] was higher in the Pre and Post groups
and was lowest in the Mid group (Fig. [63]1b). Skeletal muscle is a
popular tissue for hibernation research because it shows little atrophy
even during prolonged immobility. Therefore, many transcriptomic and
proteomic studies have been performed with skeletal muscles in the
past^[64]6,[65]11,[66]24–[67]26. Using RNA from the muscle samples, we
analyzed genome-wide transcription profiles using the CAGE
approach^[68]27,[69]28. Based on the transcription start sites (TSS)
distribution, we identified 12,862 total peak clusters, reflecting
genome-wide expression profile on promoters’ level with
single-nucleotide precision. Among all the TSSs, 11,133 were associated
with 10,617 genes, and the remaining was out of ±500-bp regions from
the 5′ ends of annotated genes.
Fig. 1. Fasting-induced Torpor Shows a Reversible Transcriptome Signature.
[70]Fig. 1
[71]Open in a new tab
a Protocol for sampling muscles from Pre, Mid, and Post torpor animals
to test the reversibility of the transcriptional profile of muscles
during torpor. b Boxplots for the VO[2] of animals at sampling in the
reversibility experiment #1. Each dot represents one sample from one
animal. During torpor (Mid group), the median VO[2] was lower than
during Pre or Post torpor. The band inside the box, the bottom of the
box, and the top of the box represent the median, the first quartile
(Q[1]), and the third quartile (Q[3]), respectively. The interquartile
range (IQR) is defined as the difference between Q[1] and Q[3]. The end
of the lower whisker is the lowest value still within 1.5 IQR of Q[1],
and the end of the upper whisker is the highest value still within 1.5
IQR of Q[3]. Every other boxplot in this manuscript follows the same
annotation rules. The numbers in the Mid torpor group are
identification numbers of the animals. c MDS plot of the TSS-based
distance in reversibility experiment #1. Each dot represents one sample
from one animal. The Mid group clustered differently from the Pre and
Post groups in the 1st dimension. The two internal groups seen in the
Mid group in d were not evident in this plot, indicating the transient
metabolic change during torpor was not correlated with transcription. d
Hierarchical clustering heatmap based on the TPM of TSS detected in the
reversibility experiment #1. The group colors are denoted in (c). e
Distribution of CAGE clusters according to the fold-change (FC) in the
TPM of Pre to Mid and Mid to Post torpor. The top five up- and
down-regulated reversible promoters that had annotated downstream genes
are shown. f Top ten enriched GO terms in the reversible promoters. g
Top ten enriched KEGG pathways in the reversible promoters. h, i Top
five up- and down-regulated reversible promoters ordered according to
the magnitude of the TPM change. Promoters that had annotated
downstream genes are shown.
The multidimensional scaling (MDS) plot of the promoter-level RNA
expression showed that the Pre and Post groups had distinct expression
profiles from the Mid group (Fig. [72]1c, d). During torpor, the animal
may show both high and low metabolism due to the oscillatory nature of
this condition. Indeed, the animal in the Mid group showed a broad
diversity of metabolic rates (Fig. [73]1b), which indicates animals are
either in torpor or between torpid states. Each number in Fig. [74]1b,
c represents the same animal in the Mid group. Despite the metabolism
during torpor forming two clusters (Fig. [75]1b), the CAGE cluster
profile did not show clustering within the Mid group according to
metabolic state (Fig. [76]1c, d), indicating that the oscillating
metabolic change during torpor does not show a clear difference in
transcription.
To test the reproducibility of this experiment, we performed another
independent set of samplings and CAGE analysis (experiment #2). We
obtained 2, 5, and 3 samples for the Pre, Mid, and Post states,
respectively. In experiment #2, the VO[2] at sampling showed a similar
pattern as in experiment #1 (Supplementary Fig. [77]1a), and the MDS
plot showed that the Pre and Post groups had a distinct transcriptome
profile from the Mid group (Supplementary Fig. [78]1b, c). These
results were consistent with those of experiment #1.
To gain insight into the biological process underlying the reversible
expression during torpor, we analyzed differentially expressed (DE)
genes on the level of promoters in the Pre to Mid and in the Mid to
Postconditions. The promoters were considered differentially expressed
when the false discovery rate (FDR) was smaller than 0.05. Reversibly
up-regulated DE promoters were defined if they show a significant
increase from the Pre to Mid (FDR < 0.05) and decrease from the Mid to
Post (FDR < 0.05). Reversibly down-regulated DE promoters were
similarly defined but in the opposite direction (Fig. [79]1e). We found
589 up-regulated and 277 down-regulated promoters (representing 481 and
221 genes) from the 12,862 total promoters, with enrichment in several
distinct KEGG pathways. The top 10 enriched GO terms and KEGG pathways
related to both the reversibly up- and down-regulated DE genes are
shown in Fig. [80]1f, g. Furthermore, we found enrichment of certain
motifs in the promoters with reversible expression dynamics
(Supplementary Fig. [81]1d, e). Finally, every DE promoter was ranked
in the order of the total fold-change, which was the sum of the
fold-changes in both the Pre to Mid and the Mid to Post (Fig. [82]1h,
i). To note, the reproducibility of this analysis was tested by
comparing experiments #1 to #2, and in Pre to Mid and Mid to Post
comparisons, the DE genes overlapped 80.17% and 76.82%, respectively.
Within the reversible promoters, to exclude the ones resulting from the
direct effect of starvation and not the low metabolism, we further
analyzed the transcriptomic profile of mouse muscles under several
conditions designed to prevent the animal from entering torpor.
Torpor prevention at high ambient temperature revealed
hypometabolism-associated mRNA isoforms formed by alternative promoter usage
Torpor can be induced by removing food for 24 h only when the animal is
placed in a relatively low ambient temperature (T[A]). We have shown
that B6J mice enter torpor at a rate of 100% from the T[A] of
12–24 °C^[83]4 and that confirmed that some animals do not enter torpor
at T[A] of 28 °C (Supplementary Fig. [84]2a). We further tested whether
the animals could enter torpor at T[A] of 32 °C (Supplementary
Fig. [85]2b). In this warm condition, even if the animals were starved
for 24 h, they did not enter torpor, possibly due to the lack of heat
loss compared to animals at lower T[A]s. Taking these two requirements
into account, fasting and low T[A], we designed two torpor-preventive
conditions and compared the expression in the muscles under these
conditions to that under the ideal torpor state (Fig. [86]2a). One is a
high T[A] (HiT) environment, and the other is a non-fasted (Fed)
condition. Both conditions prevented the animals from inducing torpor
because one of the two essential requirements was lacking. We then
compared the tissue from these conditions to the ideal torpid tissue
from fasting animals at a low T[A] and obtained the transcripts that
were differentially expressed from torpor in each non-torpor condition.
The expression differences shared in these two experiments would be
those affected by both low T[A] and fasting, and therefore would be the
essential expressions for active hypometabolism, hereafter defined as
hypometabolic promoters. One aspect to note is that either 24-h fasting
or low T[A] is an essential factor in this experiment setup, but in
other environments, such as in lower T[A] or longer fasting, removing
the factors may not prevent torpor. Therefore, the hypometabolic
factors will include the most genes related to torpor, but it still
includes a fraction of genes that are related only to hunger or low
T[A].
Fig. 2. Torpor Prevention at high T[A] Revealed Hypometabolism-associated
Promoters.
[87]Fig. 2
[88]Open in a new tab
a Protocol for detecting the hypometabolic expression by sampling
muscles from two groups in which torpor was prevented (HiT and Fed
groups, n = 4 for each). For the torpid group, the samples collected in
the reversibility test were used (Mid group, n = 8). b Boxplots for the
VO[2] of animals at sampling in the hypometabolic experiment. Each dot
represents one sample from one animal. During torpor prevention by
high-T[A] (HiT group), the VO[2] was lower than in the Mid group, and
when torpor was prevented by food administration (Fed group), VO[2] was
higher than in the Mid group. c MDS plot of the TSS-based distance in
the hypometabolic experiment. Each dot represents one sample from one
animal. The Mid, Fed, and HiT groups were clustered separately. d
Hierarchical clustering heatmap based on TPM of the TSS detected in the
hypometabolic experiment. The group colors are denoted in (c). e
Distribution of CAGE clusters according to the fold-change in TPM of
the HiT to Mid and Fed to Mid groups. The top five up- and
down-regulated hypometabolic promoters that had annotated downstream
genes are shown. f The top ten enriched GO terms in the hypometabolic
promoters. g The top ten enriched KEGG pathways in the hypometabolic
promoters. h, i The top five up- and down-regulated hypometabolic
promoters are ordered according to the magnitude of the TPM change.
Promoters that had annotated downstream genes are shown.
We first compared the VO[2] in the HiT and Fed groups against the Mid
group (Fig. [89]2b). Even though both groups had no animals entering
torpor, the HiT group showed a lower VO[2] while the Fed group showed a
higher metabolism. Due to the food availability, the Fed group showed
high RQ compared to the Mid and HiT groups (Supplementary Fig. [90]2c).
Next, we compared the expression profile acquired from the CAGE
analysis of tissues from both groups. The MDS plot and hierarchical
clustering showed that the Mid, Fed, and HiT groups consisted of
independent clusters (Fig. [91]2c, d). This finding indicated that the
expressions during torpor (Mid group) were distinct from those during
starvation alone (HiT) or at low T[A] alone (Fed).
To extract the hypometabolic state–associated promoters, we performed
the DE analysis (Fig. [92]2e) between the HiT to Mid and the Fed to
Mid. CAGE clusters up-regulated in both the HiT to Mid and the Fed to
Mid were those that were up-regulated during torpor regardless of the
initial condition, i.e., warm T[A] or no fasting (green dots in
Fig. [93]2e). There were 330 of these up-regulated hypometabolic
promoters from a total of 12,862. On the other hand, 137 CAGE clusters
that were down-regulated in both the HiT to Mid and the Fed to Mid,
were promoters that were down-regulated regardless of the initial
condition, and thus were the down-regulated hypometabolic promoters
(red dots in Fig. [94]2e). The enrichment analyses of GO terms and KEGG
pathways were performed (Fig. [95]2f, g), and the motifs enriched in
the hypometabolic promoters were also analyzed (Supplementary
Fig. [96]2d, e). The top five promoters that had annotated genes nearby
are listed as up- and down-regulated hypometabolic promoters in
Fig. [97]2h, i, respectively.
These results showed that considerable numbers of genes are
specifically involved in the active hypometabolic process and
independent from either hunger or cold responses. One of these genes,
Ppargc1a, which was found at the top of the up-regulated hypometabolic
promoters, was also found at the top of up-regulated reversible
promoters (Fig. [98]1h). Such a gene is a good candidate for a
torpor-specific gene because it belongs to both the reversible and the
hypometabolic groups in this study. Therefore, we next merged the
results of the reversible and the hypometabolic promoters to specify
the torpor-specific promoters and elucidate the fundamental
transcriptional network of active hypometabolism in peripheral tissues.
Identification of torpor-specific promoters and their dynamics
Our analyses on two essential torpor characteristics, i.e.,
reversibility and hypometabolism, revealed that the skeletal muscle of
torpid mice has a specific transcriptomic pattern (Figs. [99]1 and
[100]2). Combining these results, we obtained torpor-specific expressed
promoters, defined as the intersection of the reversible and the
hypometabolic promoters. We found 226 up-regulated and 61
down-regulated torpor-specific promoters (Fig. [101]3a). The top five
promoters ordered according to the sum of the fold-change observed in
the two groups (reversible and hypometabolic promoters) are shown in
Fig. [102]3b, c. Remarkably, “protein binding” in the molecular
function category in the GO terms was listed in the top ten enriched GO
terms (Supplementary Fig. [103]3a). This group includes various
protein-binding gene products, including transcription factors. To
highlight the predominant transcriptional pathway related to torpor, we
ran an enrichment study of KEGG pathways with the torpor-specific
promoters. We obtained 13 pathways that showed statistically
significant enrichment (Supplementary Fig. [104]3b). In particular, the
mTOR pathway, which includes various metabolic processes related to
hibernation and starvation, was identified. Furthermore, we analyzed
the enriched motifs in the torpor-specific promoters (Supplementary
Fig. [105]3c, d) and found 131 significantly enriched motifs out of 579
motifs registered in JASPAR 2018^[106]29.
Fig. 3. Identification of Torpor-specific Promoters and their Dynamics.
[107]Fig. 3
[108]Open in a new tab
a Torpor-specific promoters were defined by the intersection of
reversible and hypometabolic promoters. Up-regulated torpor-specific
promoters (n = 226), which were CAGE clusters that were highly
expressed exclusively during torpor, were at the intersection of the
up-regulated reversible (n = 589) and hypometabolic promoters (n =
330). Down-regulated torpor-specific promoters (n = 61), which were
CAGE clusters that were highly suppressed exclusively during torpor,
were at the intersection of down-regulated reversible (n = 277) and
hypometabolic promoters (n = 137). b, c Top five up-regulated (b) and
down-regulated (c) torpor-specific promoters ordered according to the
sum of the TPM change observed in the reversibility and hypometabolism
experiments. Only promoters that had annotated downstream genes are
shown. d Distribution of the SI of all of the mouse muscle promoters.
An SI of 2 indicates a singleton-shaped CAGE TSS signal, and promoters
with SI <−1 have a broad shape. e, f Distribution of the SI (e) or %GC
(f) for torpor-specific promoters compared to all muscle promoters. The
three horizontal lines inside the violin denote the 1st, 2nd, and 3rd
quartile of the distribution from the upmost line.
CAGE analysis can detect TSSs at a single base-pair resolution, and
therefore, it can be used to estimate the architecture of the
promoter^[109]30. The shape index (SI) is one of the major indices used
to evaluate promoter architecture^[110]31. “Narrow” promoters initiate
transcription at specific positions, while “broad” promoters initiate
transcription at more dispersed regions. It is widely accepted that the
promoter shape differs among different tissues or
conditions^[111]32,[112]33. To detect promoter dynamics in the skeletal
muscle under different metabolic conditions, we analyzed the promoter
shape of each of the detected promoters in the reversible,
hypometabolic, and torpor-specific groups (Fig. [113]3d). In the
torpor-specific groups, the down-regulated promoters showed a
significantly different shape when compared to all muscle promoters
(Fig. [114]3e), while the GC richness did not show a difference
(Fig. [115]3f).
The torpor-specific active promoters were identified through the
expression changes in the natural cycle of FIT and two environmental
cues which prevent the animals from entering FIT, namely feeding and
high ambient temperature. To further narrow down causal promoters for
FIT regulation, an adaptive method to prevent the animal entrance to
FIT was introduced.
Atf3 is related to the regulation of FIT
The torpor-specific promoters we found may represent regulators both
upstream and downstream of the torpor transcriptional network. To
further elucidate the early events involved in torpor-specific
metabolism in peripheral tissues, it was necessary to place the animal
in a condition where it had an extreme tendency to enter torpor and
compare the muscle gene expression with regular torpor entry. For this,
we mimicked the classical technique, sleep deprivation, which is
frequently used in basic sleep research^[116]34,[117]35, and performed
torpor deprivation by gently touching the animal. All of the
torpor-deprived animals showed a similar metabolism level to the
metabolically non-torpid animals in the Mid-torpor group
(Fig. [118]4a). Furthermore, the transcriptome profile in the muscles
from torpor-deprived animals did not show a clear difference from
Mid-torpor animals in MDS plots (Fig. [119]4b). When compared to
Mid-torpor muscles, the torpor-deprived muscles had 45 up- and 27
down-regulated promoters (Fig. [120]4c). Among these 72
torpor-deprivation-specific promoters, one promoter starting at the
minus strand of chromosome 1: 191217941, namely the promoter of the
activating transcription factor 3 (Atf3) gene, was also found in the
torpor-specific promoters (Fig. [121]4d). Atf3 has two documented
promoters^[122]36. This study detected the canonical promoter as a
torpor-specific promoter and an up-regulated promoter in a torpor
deprived animal. Transcripts from the other promoter located 34.7 kbp
upstream from the canonical promoter did not change significantly in
this study. Surprisingly, the binding site of ATF3 was one of the
motifs enriched in the torpor-specific promoters (Supplementary
Fig. [123]4a). The ATF3 motif was found in 33 of 289 torpor-specific
promoters, and the peak of the motif probability was 79 bp upstream of
the TSS (Fig. [124]4e).
Fig. 4. Atf3 is related to FIT regulation.
[125]Fig. 4
[126]Open in a new tab
a Boxplots for the VO[2] of animals at sampling in the torpor
deprivation experiment. Each dot represents one sample from one animal.
Torpor-deprived animals (Dep group, n = 4) did not show an apparent
change in VO[2] compared to the Mid group. b MDS plot of the TSS-based
distance in the torpor-deprivation experiment. Each dot represents one
sample from one animal. A clear separation between the Mid and Dep
groups was not found in this analysis. c Distribution of CAGE clusters
according to the mean TPM and the fold-change TPM of the Mid to Dep
group. The top five up- and down-regulated torpor-deprivation-specific
promoters that had annotated downstream genes are shown. d Among the
torpor-specific up-regulated genes, Atf3 was the only DE gene during
torpor deprivation. e The motif probability of ATF3 and TBP in
torpor-specific promoters. f Estimated ΔΔCT of atf3 mRNA for each organ
from normal to torpid condition. The black solid line and the dashed
lines denote the median and the lower and upper 89% HPDI. The red line
is drawn at zero. Heart, BAT, and the soleus muscle have lower CT
during torpor, which indicates higher mRNA. See Supplementary
Fig. [127]4b for raw CT counts. g The FIT phenotype of Atf3-KO mice (n
= 8, pink lines) was compared to wildtypes (n = 4, black lines). The
thick lines denote the average of either T[B] or VO[2] in each group,
while thin lines show individual recordings. Atf3-KO have a tendency of
higher metabolism during torpor compared to wildtypes. h The minimal
T[B] and VO[2] during torpor were compared between Atf3-KO (pink) and
wild-type mice (black). Two animals in the KO group failed to record
body temperature due to equipment trouble. The three-digit numbers by
the dots are the animal ID. Two KO lines, which showed higher
metabolisms than wildtypes, ATF3-025, and ATF3-021, were selected for
further evaluation.
To evaluate the functional universality of ATF3, the gene expression
level was quantified at heart, liver, brown adipose tissue (BAT),
brain, and soleus muscle during normal and FIT (Supplementary
Fig. [128]4b). The heart, BAT and soleus muscle showed a significant
increase in expression, while the liver and brain showed no difference
(Fig. [129]4f). To test the systemic function of ATF3 during
fasting-induced torpor, Atf3 gene was knocked out by
CRISPR/Cas9-mediated gene editing. The guide sequences targeting the 5′
and 3′ regions of the Atf3 gene were designed to delete a 12.2-kb
genomic region spanning three exons of Atf3 on chromosome 1
(Supplementary Fig. [130]4c). The FIT phenotype of eight F0 siblings
confirmed as Atf3 KO mice were tested. All mice entered torpor but
showed higher metabolism during FIT than controls (Fig. [131]4g, h).
Two strains—ATF3-021 and 025—out of eight F0 Atf3 KO mice were selected
and crossed with wild-type animals to produce heterozygous KO mice. The
four KO alleles segregated from these two lines are shown in
Supplementary Fig. [132]4d. The F1 heterozygous KO mice holding the
identical KO allele were crossed multiple times to obtain wildtype,
heterozygous, and homozygous Atf3 KO mice. Every strain was viable, and
the growth was normal (Supplementary Fig. [133]4e). To evaluate the
gene deletion effect of Atf3 to FIT, both the minimal T[B] and VO[2]
during torpor of the KO mice were compared to those of wild-type
animals (Supplementary Fig. [134]4f). A Bayesian statistical model
including the phenotype differences as parameters was designed, and the
parameters were estimated from the observed data. Both heterozygous and
homozygous ATF-021a KO were estimated to have higher T[B] than
wild-type mice (Supplementary Fig. [135]4g), although VO[2] did not
have any difference. Interestingly, 025b has shown lower T[B] in
heterozygous and homozygous strains with any differences in VO[2].
We found that transcription factor ATF3, one of the torpor-specific
genes at the soleus muscle, is highly expressed during torpor
deprivation. When the gene is deleted systemically, we found two
strains ATF3-021a and ATF3-025b showed shallower and deeper torpor
phenotypes than wild-type animals. Collectively, the results suggest
Atf3 expression is related to the torpor phenotype, and lack of the
gene changes the minimal VO[2] during the FIT.
Discussion
In this study, we identified 287 torpor-specific promoters in B6J mouse
skeletal muscle (Fig. [136]3a). Specificity was assured by including
both reversible and hypometabolic promoters (Figs. [137]1a, [138]2a).
The results enabled us to identify likely metabolic pathways enriched
during torpor (Supplementary Fig. [139]3b). Although skeletal muscle is
not the core tissue in mitochondrial metabolism suppression during
torpor^[140]37, the current study gained insight into transcriptional
changes in muscles during daily torpor in mice.
The circadian rhythm was the most enriched KEGG pathway by
torpor-specific promoters. The circadian clock is important in
organizing metabolism and energy expenditure^[141]38. In our study, the
core circadian clock gene Per1 was up-regulated torpor-specifically,
and Arntl1 was up-regulated during torpor but not included in the
hypometabolism-associated promotors. Because Per1 and Arnlt1 are
normally expressed in reversed circadian phases, our results in which
both components were up-regulated together indicated that the circadian
clock was disrupted in the skeletal muscle during torpor. Several past
studies have focused on the central circadian clock of
hibernation^[142]39,[143]40 or the chronic effect of cold and hunger to
the peripheral clock relative to the central clock^[144]41. However,
little is known about the peripheral circadian clock in acutely fasted
torpid animals. Thus, our results may provide evidence that the
peripheral clock is disrupted at the entrance of active hypometabolism.
Similarities between fasting during hibernation or daily torpor and
calorie restriction in non-hibernating mammals are reported^[145]42.
During long-term torpor, such as in hibernating mammals,
carbohydrate-based metabolism switches to lipid use. Many studies have
suggested that the activation of AMPK is important in torpor
induction^[146]43–[147]45. However, another study demonstrated AMPK
activation only in white adipose tissue, not in the liver, skeletal
muscle, brown adipose tissue, or brain, during hibernation^[148]46. Our
study corroborates the findings of Horman’s research by demonstrating
no significant changes in the AMPK-encoding gene expression during
torpor in skeletal muscle. Although, the enriched AMPK signaling
pathway without AMPK expression bespeaks a complex nature of muscle
transcription in daily torpor.
The PPAR-signaling pathway also regulates lipid metabolism. Numerous
studies have shown increased PPARs in various organs at the mRNA and
protein levels during torpor, in several hibernating
species^[149]42,[150]46. Recently, an over-expression of PPARα protein
in mouse liver, comparable to that in hibernating bats, was reported,
suggesting a potential hibernation capability of mice^[151]47.
According to our data, Ppara is up-regulated in torpid mice muscle
along with several target genes associated with cholesterol metabolism
and fatty acid transport. Remarkably, the Ppargc1a gene, encoding
PGC-1α (peroxisome proliferator-activated receptor-γ coactivator-1),
was also over-expressed in mouse soleus muscle during torpor. Recently,
PGC-1α activation was suggested to be responsible for protecting
skeletal muscle from atrophy during long periods of torpor in
hibernators^[152]48. Our results suggest that a similar pathway may be
activated in mouse torpor as well.
We found that the insulin/Akt and mTOR signaling pathways, which have
roles in skeletal muscle remodeling and metabolic rate depression, were
enriched. Previous studies showed that insulin signaling is inhibited
in the skeletal muscle of torpid gray mouse lemurs^[153]49 and that the
Akt kinase activity is suppressed during torpor in multiple tissues of
ground squirrels^[154]50–[155]52. The suppressed Akt activity is
accompanied by a reduction in mTOR activation, leading to a state of
protein synthesis inhibition during torpor in
hibernators^[156]52–[157]54. Our results demonstrated a down-regulation
of Igf1, which encodes IGF-1, and activation of Mtor, which encodes
mTOR, in torpor, which appears paradoxical to past studies.
The Insulin/Akt pathway also controls the phosphorylation and
activation of the FOXO1 transcription factor, a disuse atrophy
signature that up-regulates the muscle-specific ubiquitin ligases
Trim63 (MuRF1) and Fbxo32 (Atrogin-1). In our study, we found that
FOXO1, MuRF1, and Atrogin-1 were up-regulated, as in the case of disuse
atrophy in mice and rats^[158]55,[159]56.
In summary, we found that the up-regulation of PGC-1α and
down-regulation of IGF-1 in the skeletal muscle of torpid mice are
similar to hibernating animals, in which they contribute to muscle
protection and the suppression of protein synthesis. On the other hand,
muscle atrophy and autophagy signatures such as FOXO1, MuRF1, and
Atrogin-1 were up-regulated during torpor, indicating that atrophic
changes are also progressed. Furthermore, mTOR, a signature of muscle
hypertrophy, activation was found. Thus, we can conclude that mouse
torpor has a unique transcription profile, sharing signatures with
hibernation, starvation-induced atrophy, and muscle hypertrophy.
The CAGE technology enabled us to evaluate the dynamics of the
torpor-specific gene expression on the level of promoters. We found
that down-regulated torpor-specific promoters were narrower than other
muscle promoters; that probably, reflects the general impact of
hypometabolism on RNA transcription (Fig. [160]3e). To gain insight
into the upstream network of torpor, we evaluated a torpor-deprived
condition. Note that this dynamic state, the torpor-deprived condition,
is challenging to induce in hibernators because very little stimulation
can cause them to halt torpor induction. Taking advantage of this
torpor-deprivation state in mice, we identified transcription factor
ATF3 as a candidate factor correlated with the need to enter torpor
(Fig. [161]4d). The altered torpor phenotype of Atf3-KO mice supports
the torpor-related function of ATF3 (Fig. [162]4h and Supplementary
Fig. [163]4e).
ATF3 is a well-known stress-inducible transcription factor, and its
expression is induced by cellular stresses such as DNA damage,
oxidative stress, and cell injury^[164]57. In addition to the stress
responding aspect, numerous investigations suggest its regulatory
function to cellular metabolism^[165]58. Both aspects of Atf3, namely
the stress response and the metabolism regulation, may explain the role
of this gene in fasting-induced torpor.
As one of the significant responses as a stress-inducible molecule,
recent cumulative evidence suggests the induction of ATF3 in
ischemia/reperfusion (I/R) injuries in various organs^[166]59–[167]62.
In the current study, ATF3 was identified as a torpor-drive correlated
factor. Torpor is an active hypometabolic condition, which shows a
drastic reduction in oxygen consumption. To stay healthy under low
oxygen consumption, tissues would benefit from becoming tolerant to
ischemia during torpor. Therefore, we propose the hypothesis that Atf3
is mediating the initiation of hypometabolism, and because of that, it
is expressed to protect the organs under stressful conditions such as
ischemia.
Another potential role of Atf3 in the chain of torpor reaction is its
metabolism pathway modifying ability. Systemic deletion of Atf3 results
in no obvious phenotypes^[168]63. However, series of studies suggest
the ATF3 involvement in glucose metabolism in various organs and
tissues. In the pancreas, Atf3 up-regulates the expression levels of
proglucagon^[169]64 and deleting Atf3 from the pancreas specifically
results in low serum glucose^[170]65. In addition, pancreas- and
hypothalamus-specific Atf3 knockout shows a leaner phenotype due to
decreased food intake and increased energy expenditure^[171]61.
Collectively, Atf3 can be assumed as a counter-reaction to systemic
glucose depletion or nutrition deficiency. Therefore, the increased
Atf3 expression in the muscle, exaggerated by torpor deprivation,
denotes the potential Atf3 function for hypometabolism tolerance. One
thing to note is the dissimilar phenotype of two Atf3 knockout strains,
ATF3-21a and ATF3-25b. These results indicate a clear yet complicated
relationship of Atf3 to torpor regulation, and further studies are
mandatory for clarification.
In this study, torpid mouse exhibits increased Atf3 expression in the
skeletal muscle, heart, and BAT but not in the brain and liver. One
possibility is that, for the brain and liver, FIT is not as stressful
as to induce Atf3 expression. This hypothesis could be tested by
expression evaluation in mice facing a much severe hypometabolic
condition. Another possibility is that Atf3 may have an organ-specific
function during torpor, as it has in metabolic homeostasis and
cancer^[172]58. Understanding the organ-dependent function of Atf3
during the FIT, a tissue-specific loss- or gain-of-function approach is
required. Furthermore, the Atf3 promoter detected in this study is one
of the two documented promoters of Atf3^[173]36. Even the same proteins
are produced from the transcripts, deleting the shared protein-coding
region may affect the endogenous function of the Atf3 transcript from
the other promoter. To clarify this, tweaking the promoter region to
evaluate the two distinct transcripts would be necessary independently.
There is a report that torpor phenotype can be affected by epigenetic
changes such as the nutritional experiences during the fetal
period^[174]66. Therefore, in future studies, epigenetic influences
must be taken into consideration along with the SNP analysis.
One limitation of this study is that Atf3 was identified through the
torpor precluding study by tactile stimulation. A sleep deprivation
study inspired this method. To our knowledge, this is the first time to
report torpor deprivation in mice. Even we have frequently observed
animals trying to lower their metabolism unless we touch them during
the experiment, we do not have a quantitative test whether the torpor
propensity will increase by this procedure. Therefore, the higher
expression of Atf3 in torpor-deprived animals could be explained simply
by the nature of this gene as a stress-inducible gene. Moreover, little
effect to torpor-debt may explain the lack of robust effect to the
torpor of Atf3 knockout animals.
The overall results of this study indicate that the mouse is an
excellent animal for studying the as-yet-unknown mechanisms of active
hypometabolism. Understanding the core engine of the hypometabolism in
torpid tissues will be the key to enabling non-hibernating animals,
including humans, to hibernate. Inducing active hypometabolism in
humans would be an important breakthrough for many medical
applications^[175]1. The benefits of using mice are not limited to
technological advances in genetics but extend to the enormous potential
for in vitro studies using cell or tissue culture. In stem cell
biology, patient-derived stem cells represent a valuable resource for
understanding diseases and developing treatments because the cells
reflect the phenotype of the patient^[176]67. We believe, similarly,
that mouse-derived stem cells or tissues will provide a unique platform
for investigating strain-specific hypometabolic phenotypes in animals.
Moreover, because in vitro studies can be easily extended to
experiments using human cells/tissue derived from human induced
pluripotent stem cells, active hypometabolism research in mouse
cells/tissues is an important step toward the realization of human
hypometabolism.
Methods
Animals
All animal experiments were approved by the Institutional Animal Care
and Use Committee of RIKEN Kobe Branch and performed according to RIKEN
Regulations for the Animal Experiments. C57BL/6 J mice were purchased
from Oriental Yeast Co., Ltd., Tokyo, Japan. Until the mice were used
in torpor experiments, they were given food and water ad libitum and
maintained at a T[A] of 21 °C, relative humidity of 50%, and a 12 h
light/12 h dark cycle.
For the C57BL/6 J, 42 male mice were used, and the age at experiment
was 8.22 ± 0.39 weeks old (mean ± SD) and the weight was 23.0 ± 1.2 g
(mean ± SD).
The Atf3 KO mice were generated with CRISPR/Cas9-mediated gene
targeting by zygote electroporation. For electroporation, C57BL/6 J
pronuclear stage embryos were transferred into Opti-MEM I medium
containing 25 ng/µl each of crRNA1, crRNA2, crRNA3, and crRNA4,
200 ng/µl tracrRNA (FASMAC), and 250 ng/µl Cas9 protein (ThermoFisher).
CUY21EDITII and LF501PT1-10 platinum plate electrodes (BEX Co. Ltd.)
were used with repeated 30 V pulses (3 ms ON + 97 ms OFF) 7 times.
After electroporation, the zygotes were transferred into the oviduct of
pseudopregnant ICR female mice. A total of 64 F0 mice were obtained
from 201 zygotes, and 8 of them were confirmed to be Atf3 KO mice in
which the Atf3 gene locus was deleted. Four F1 heterozygous mice
segregated from two Atf3 KO founder mice, ATF3-021 and ATF3-025, were
used to establish independent mutant mouse lines (021a, 021b, 025a, and
025b; Accession. No. CDB0065E-021a, 021b, 025a and 025b, respectively:
[177]http://www2.clst.riken.jp/arg/mutant%20mice%20list.html). The
genotype of mice was determined by PCR with the following primers;
Fwd08: TCC CGG TAT CGA GCT AAA TG, Rev01: GGG TCG AAG CAG GGA ATC AA,
Rev15: CAG CAA AGG CAC GTG TCA CTA G (Supplementary Fig. [178]4c). PCR
product sizes of wildtype and KO alleles were 747 bp (wildtype),
1255 bp (021a), 1172 bp (021b), 310 bp (025a), and 1250 bp (025b),
respectively. Guide RNA sequences were designed by CRISPRdirect
([179]https://crispr.dbcls.jp)^[180]68. The crRNA and tracrRNA
sequences used for genome editing were synthesized as follows (FASMAC).
crRNA1; GCA AGU CAC AAC AGC GAG UGg uuu uag agc uau gcu guu uug,
crRNA2; AGC GAA GGA AUC GGA UCA AGg uuu uag agc uau gcu guu uug,
crRNA3; GUG CCA CAC UAA CGU UUA CCg uuu uag agc uau gcu guu uug,
crRNA4; tracrRNA: AAA CAG CAU AGC AAG UUA AAA UAA GGC UAG UCC GUU AUC
AAC UUG AAA AAG UGG CAC CGA GUC GGU GCU.
During the experiments, each animal was housed in a
temperature-controlled chamber (HC-100, Shin Factory). To record T[B]
continuously, a telemetry temperature sensor (TA11TA-F10, DSI, New
Brighton, MN) was implanted in the animal’s abdominal cavity under
general inhalation anesthesia at least seven days before recording. The
metabolism of the animal was continuously analyzed by respiratory gas
analysis (ARCO-2000 mass spectrometer, ARCO system, Kashiwa, Japan).
The animal was monitored through a networked video camera (TS-WPTCAM,
I-O DATA, Inc.). This video camera can detect infrared signals, which
made it possible to monitor the animal’s health during the dark phase
without opening the chamber.
Daily torpor induction experiment
Each daily torpor induction experiment was designed to record the
animal’s metabolism for three days unless the tissues were sampled on
day 2. The animals were introduced to the chamber the day before
recording started (day 0). Food and water were freely accessible. The
T[A] was set as indicated on day 0 and kept constant throughout the
experiment. A telemetry temperature sensor implanted in the mouse was
turned on before placing the mouse in the chamber. The standard
experimental design was as follows: on day 2, ZT-0, the food was
removed to induce torpor. After 24 h, on day 3, ZT-0, the food was
returned to each animal. In the torpor-prevention experiment with food
administration (Fig. [181]2a), the food was not removed on day 2. In
the torpor-deprivation experiment, one experimenter monitored the VO[2]
and touched the mouse gently when the VO[2] started to drop. The
metabolism monitoring for torpor deprivation was started at ZT-17 on
day 2 and maintained until the mouse tissue was sampled at ZT-22.
Body temperature and oxygen consumption modeling for daily torpor detection
To model the temporal variation of T[B] and VO[2], we constructed the
models in a Bayesian framework. From the first 24-h recordings of T[B]
and VO[2] for each animal, we estimated the parameters using Markov
Chain Monte Carlo (MCMC) sampling by Stan^[182]69 with the RStan
library^[183]70 in R^[184]71. The method was described
previously^[185]4 and modified with software updates. For each animal,
T[B] and VO[2] were evaluated every six minutes for three days. From
the recordings of day 1, the baseline metabolism was estimated with a
certain credible interval (CI). In this study, we used the 99.9% CI of
the posterior distribution of the estimated metabolism to detect
outliers. When the value is lower than the CI, that time point is
defined as torpor due to an abnormally low metabolic status. When both
T[B] and VO[2] met the criteria in the second half of the day, the time
point was labeled as torpor. When T[B] or VO[2] was unable to record
from equipment troubles, either one successfully recorded was used for
torpor detection.
Parameter estimation of Atf3-KO phenotypes
The effect of Atf3 deletion to the FIT phenotype was evaluated by the
difference of minimal T[B] and VO[2] of Atf3-KO mice from the wild-type
mice. A Bayesian statistical model including the strain and deletion
allele information was produced, and the parameters were estimated from
the observed data. Model fitting was performed using Hamiltonian Monte
Carlo with its adaptive variant, the no-U-turn sampler, as implemented
in version 2.12.2 of Stan with the RStan library in version 4.0.5 of
R^[186]71. We assessed convergence by inspecting the trace plots,
Gelman-Rubin
[MATH: R^
:MATH]
, and an estimate of the effective number of samples. The model priors
were defined as weakly informative and conservative, which are
specified in the following sections. The fundamental principles and
techniques for designing the statistical models were based on the book
Statistical Rethinking^[187]72.
The minimal T[B] and VO[2] of the animals were modeled on the
assumption that each genotype has a unique phenotype. Four types of
Atf3-KOs were tested in this experiment. Each knockout has three
combinations of alleles, namely the wildtype, heterozygous, and
homozygous KOs. When N is the total number of the animals, and
Y[NORMAL]is the minimal T[B] or VO[2] during the normal state,
Y[NORMAL]of mouse i can be described as the sum of the global mean
parameter α and the group parameter β, with the noise modelled in a
Normal distribution of a scale parameter σ[NORMAL] as:
[MATH: YNO
RMAL[
i]~Normal(α<
/mi>+βgene[i],allele[i],σNOR
MAL)i=1⋯N
:MATH]
1
When another group parameter γ is given as the difference of T[B] or
VO[2] during torpor from the normal state, Y[TORPOR] can be described
as:
[MATH: YTO
RPOR[
i]~Normal(α<
/mi>+βgene[i],allele[i]+γgen
e[i]
,allele<
mrow>[i],σTORPOR)<
/mtd>i=1⋯N
:MATH]
2
Both group parameters were sampled as
[MATH: β~Normal0,σ<
mi>β :MATH]
3
[MATH: γ~Normal0,σ<
mi>γ :MATH]
4
where σ[β] and σ[γ] were sampled from a Half-Cauchy distribution with a
location parameter 0, and scale parameter 2.5. All other σs were
sampled from standard half-normal distributions with scale parameter
10. The phenotype difference of KO strains was evaluated by the
posterior distribution of the difference in γ between homozygous and
wildtype, or heterozygous and wildtype (Supplementary Fig. [188]4g).
Tissue sampling and RNA isolation
Dissected soleus muscles were rapidly frozen in liquid nitrogen. The
RNA was isolated using an RNeasy Fibrous tissue kit (Qiagen) according
to the manufacturer’s instructions. The quality of the total RNA was
evaluated using a Bioanalyzer 2100 (Agilent). The quantity and purity
of the RNA were estimated using a NanoDrop Spectrophotometer. The
lateral or both soleus muscles were used according to the total amount
of RNA needed.
Genotyping of knockout mice by sequencing
The genomic DNA of Atf3 KO mice was prepared from their tail using
Maxwell 16 Tissue DNA Purification Kit (Promega). Each target gene
sequence was amplified by PCR with GoTaq (Promega) by the primers Fwd08
and Rev15, and sequenced. For ATF3-21a, two additional primers were
used to confirm the sequence; Fwd11: CTG GAA CTG GAG TTT CAG AG and
Rev18: ATG GGT CAG CAG TTT ACA A.
Quantification of mRNA levels
cDNA was synthesized from isolated RNA using a High-Capacity cDNA
Reverse Transcription Kit (4368814, Applied Biosystems) according to
the manufacturer’s instructions. qPCR was performed by TaqMan Fast
Universal PCR Master Mix (2X), no AmpErase UNG (4352042, Applied
Biosystems) with gene-specific TaqMan probes using the StepOne
Real-Time PCR Systems (Applied Biosystems). The following TaqMan probes
were used: Atf3 Mm00476033_m1, Gapdh Mm99999915_g1.
Non-amplified non-tagging Illumina cap analysis of gene expression
(nAnT-iCAGE) library preparation and sequencing
Transcriptomics libraries were prepared according to a standard
protocol for the CAGE method using 5 μg of extracted total RNA from
mouse muscles^[189]73. The RNA was used as a template for the
first-strand cDNA synthesis, which was then biotinylated at the 5′-end
to allow streptavidin capture. Linkers were then attached at the 5′ and
3′ ends, and the second strand cDNA was synthesized. The quality of the
libraries was verified using a Bioanalyzer 2100 (Agilent), and the
yield was validated by qPCR. The single-end libraries were then
sequenced on a NextSeq platform (Illumina) or a HiSeq 250 platform
using Rapid Run mode (Illumina) in experiments #1 and #2.
Mapping, peaks calling, and annotation
Sequenced reads were trimmed and mapped on the mouse mm10 genome
assembly using bwa and hisat2^[190]74,[191]75. For each sample, we
obtained CAGE-defined TSSs (CTSSs) according to the reads abundance and
then clustered them using PromoterPipeline^[192]76, the highest peaks
were annotated as TSSs. These CAGE clusters were then associated with
their closest genes using the Ensembl and Refseq transcripts annotation
available for mm10.
Data processing
Data were processed in R^[193]71 unless otherwise noted. The expression
level of the 12,862 defined CAGE clusters was normalized by a sample in
TPM (tags per million) and then analyzed with the edgeR package^[194]77
with TMM (trimmed mean of M-value) normalization. For MDS
(multidimensional scaling) plots, DE (differential expression), and GO
and KEGG pathway enrichment analysis, several R packages were applied,
including edgeR, clusterProfiler^[195]78, and pathview^[196]79. Muscle
enhancers were predicted de novo by applying the FANTOM5
protocol^[197]80 to our mouse CAGE data and masked with ±500-bp regions
from the 5′ ends of annotated genes. The DE results (reversible,
hypometabolic, and torpor-deprivation-specific promoters) along with
torpor-specific promoters are listed in Supplementary file [198]1.
Basic promoter features analysis
Promoter region features were analyzed in terms of GC content and
SI^[199]31. The SI and %GC were calculated for ±50 bp regions around
the TSS position. CpG island muscle promoters were defined by searching
for overlaps with the UCSC annotation using bedtools v2.25.
Motif analysis
Transcription factor binding sites (TFBS) were predicted in
−300/+100 bp regions around the TSS position using MEME Suite 4.11.2
and the JASPAR CORE motif library for vertebrates 2016. The
position-dependent enrichment of these motifs was performed by the
CentriMo tool.
Statistics and reproducibility
Statistical analyses were performed using R. In the CAGE analysis,
genewise negative binomial generalized linear models were used for
differential expression analysis in edgeR. Multiple comparison
adjustment was performed using Benjamini - Hochberg correction. Motif
enrichment P-values were defined by using Fisher’s exact test with
Bonferroni correction in CentriMo. To test the reproducibility of the
CAGE analysis, we created CAGE libraries from two independent batches
of mice. For animal phenotyping, Bayesian statistical models including
the parameters of interest were designed, and the parameters were
estimated from the observed data.
Reporting summary
Further information on research design is available in the [200]Nature
Research Reporting Summary linked to this article.
Supplementary information
[201]Supplementary Information^ (1MB, pdf)
[202]Supplementary Data 1^ (5.5MB, xlsx)
[203]Reporting Summary^ (1.3MB, pdf)
[204]42003_2021_2819_MOESM4_ESM.pdf^ (174.5KB, pdf)
Description of Additional Supplementary Files
[205]Transparent Peer Review File^ (3.9MB, pdf)
Acknowledgements