Abstract
Dysregulation of the balance between pro-inflammatory and
anti-inflammatory macrophages has a key function in the pathogenesis of
Duchenne muscular dystrophy (DMD), a fatal genetic disease. We
postulate that an evolutionarily ancient protective mechanism against
infection, known as trained immunity, drives pathological inflammation
in DMD. Here we show that bone marrow-derived macrophages from a murine
model of DMD (mdx) exhibit cardinal features of trained immunity,
consisting of transcriptional hyperresponsiveness associated with
metabolic and epigenetic remodeling. The hyperresponsive phenotype is
transmissible by bone marrow transplantation to previously healthy mice
and persists for up to 11 weeks post-transplant. Mechanistically,
training is induced by muscle extract in vitro. The functional and
epigenetic changes in bone marrow-derived macrophages from dystrophic
mice are TLR4-dependent. Adoptive transfer experiments further support
the TLR4-dependence of trained macrophages homing to damaged muscles
from the bone marrow. Collectively, this suggests that a
TLR4-regulated, memory-like capacity of innate immunity induced at the
level of the bone marrow promotes dysregulated inflammation in DMD.
Subject terms: Monocytes and macrophages, Chronic inflammation, Innate
immunity, Innate immune cells
__________________________________________________________________
The immunopathology of Duchenne Muscular Dystrophy includes a disturbed
balance of pro and anti-inflammatory macrophages. Here the authors
implicate trained innate immunity in a murine model of the disease, and
reveal TLR4 as a key regulator of this process.
Introduction
Duchenne muscular dystrophy (DMD) is one of the most frequent X-linked
lethal disorders, affecting approximately 1 in 5000 males^[42]1.
Despite recent advances in cell- and gene-based therapies, DMD remains
a devastating disease for which treatment options are extremely
limited. The primary cause of the disease is loss of dystrophin^[43]2,
a large protein which helps link the internal cytoskeleton to the
extracellular matrix of muscle cells, thereby providing mechanical
stability to the muscle fiber membrane^[44]3. Evidence from both animal
models and humans indicates that maladaptive inflammatory mechanisms
play an integral role in promoting the disease from its earliest
stages^[45]4,[46]5.
Macrophages are the most abundant leukocyte population in DMD
muscles^[47]6, where their abnormal persistence and dysregulated
production of inflammatory mediators play a key role in driving disease
progression^[48]7–[49]9. In previous work, we generated
dystrophin-deficient mdx mice (model of DMD) lacking the chemokine
receptor CCR2 and demonstrated the importance of bone marrow
(monocyte)-derived macrophages (BMDM) in early pathogenesis of the
disease^[50]10. Genetic abrogation of CCR2, which impairs the ability
of inflammatory monocytes to exit the bone marrow^[51]11, resulted in
reduced numbers of pro-inflammatory macrophages in the dystrophic
muscles, accompanied by reduced fibrosis and improved force
generation^[52]10. Intriguingly, genetic ablation of Toll-like receptor
4 (TLR4) in mdx mice led to similar beneficial effects along with a
skewing of intramuscular macrophages toward a more anti-inflammatory
profile^[53]12. However, the cellular mechanisms underlying these
phenomena are incompletely understood.
It is well established that macrophages have a large capacity to
respond and adapt their function to different environmental cues. This
plasticity is exemplified by the fact that in vitro stimulation with
either interferon-gamma (IFN-γ) or interleukin-4 (IL-4) can polarize
the cells toward opposing phenotypes with pro-inflammatory (also called
classically activated or M1-like) or anti-inflammatory (alternatively
activated or M2-like) profiles, respectively. Moreover, it is well
recognized that the above macrophage polarization model greatly
oversimplifies and underestimates the true diversity of macrophage
phenotypic states^[54]13, particularly during chronic inflammation in
vivo. Macrophage phenotype is also modulated by exposure to various
pathogen-associated molecular patterns (PAMPs) and endogenous molecules
released after tissue injury (damage-associated molecular patterns, or
DAMPs), which can serve as ligands for classical receptors of innate
immunity such as members of the TLR family^[55]14.
Further complexity is added by the recent recognition that macrophages
can undergo epigenetic imprinting to confer a form of innate immune
“memory”, also known as trained immunity^[56]15–[57]17. A cardinal
feature of trained immunity is that it lacks antigen-specificity and
promotes exaggerated cytokine responses to multiple forms of unrelated
pathological stimuli^[58]16. This non-specific hyperresponsiveness of
the innate immune system has been mechanistically linked to histone
modifications^[59]18–[60]20, as well as alterations in cellular
metabolism^[61]21. Although initially described in the context of
infections, there is increasing evidence that trained immunity may also
play a deleterious role in different non-infectious diseases associated
with chronic sterile inflammation^[62]22–[63]25.
Interestingly, trained immunity can be initiated at the level of
myeloid progenitors within the bone marrow^[64]26–[65]29. This suggests
that the process is regulated by systemic factors released from distant
sites of inflammation, which can potentially either induce or inhibit
trained immunity. Pattern recognition receptors such as TLRs and
NOD-like receptors are involved in the regulation of trained immunity
in monocytes/macrophages^[66]18,[67]30. In DMD local immune cell
stimulation by DAMPs within the damaged muscles is thought to be a
major contributor to disease progression, but the question of whether
DAMPs or other factors released from dystrophic muscles might also
induce wider epigenetic and functional changes at the level of myeloid
cells within the bone marrow, has not been explored.
Here, we show major remodeling of the epigenetic, metabolic and
functional inflammatory profiles of monocyte-derived macrophages from
the bone marrow of mdx mice. The fact that these changes are found at a
distance from the pathological muscle microenvironment implies a role
for systemically released mediators such as DAMPs in driving the
altered phenotype of these cells. In support of the latter mechanism,
we find that abnormal epigenetic and functional characteristics of BMDM
from muscular dystrophy mice are TLR4-dependent. Furthermore, the
altered phenotype of mdx BMDM demonstrates the hallmark features of
trained immunity, including being transmissible and long-lasting after
bone marrow transplantation to non-dystrophic mice. Accordingly,
trained immunity may be an important mechanism underlying both the
generation and maintenance of pathological inflammation in DMD.
Results
mdx BMDM exhibit disease stage-specific alterations in basal inflammatory and
metabolic profile
The BMDM from dystrophic mdx mice and age-matched wild-type (WT)
controls were studied following 7 days in culture under basal
conditions. To determine the influence of disease stage on BMDM
phenotype, the cells were harvested at different ages, taking advantage
of the fact that skeletal muscle pathology in mdx mice can be separated
into prenecrotic (2–3 weeks old), necrotic (6–8 weeks old), and
fibrotic (50–60 weeks old) stages of the disease. We first surveyed a
panel of classical pro-inflammatory “M1” (iNOS, TNF, IL6, IL12α) and
anti-inflammatory “M2” (TGFβ, CD206, Ym1, Arg1) macrophage marker genes
in BMDM at the transcriptional level (Fig. [68]1a–c). During the
prenecrotic phase, the expression of these genes was generally
equivalent to WT. In contrast, there was significant basal upregulation
of multiple pro-inflammatory as well as anti-inflammatory genes in mdx
BMDM during the necrotic phase, most of which remained elevated to a
lesser extent at the later fibrotic stage. These data indicate that in
temporal association with the onset of dystrophic skeletal muscle
pathology, the precursor cells in the bone marrow which give rise to
macrophages are functionally modified.
Fig. 1. Disease stage-dependent alterations in the basal inflammatory status
of mdx BMDM.
[69]Fig. 1
[70]Open in a new tab
a–c The basal mRNA transcript levels (expressed relative to the mean
age-matched WT level) of prototypical M1 (iNOS, TNF, IL6, and IL12α)
and M2 (TGFβ, CD206, YM1, and Arg1) marker genes during the: a
prenecrotic (n = 4 for iNOS, TNF, IL12α, Arg1 genes in mdx; rest
n = 5/group), b necrotic (n = 5 for WT, n = 4 for mdx), and c fibrotic
phases (n = 4 for WT, n = 5 for mdx) of disease, are shown. The
relative levels of phospho-STAT1, total STAT1, phospho-STAT3 and total
STAT3 in cell lysates of WT and mdx BMDM from the same disease phases
(d–f, respectively; all experimental replicates are shown) are also
demonstrated; d (n = 5/group), e (n = 5/group), f (n = 4 for WT, n = 5
for mdx). Data represent means ± SEM of biologically independent
samples from different mice. *P < 0.05 vs. WT (unpaired t-test,
two-tailed). See Source Data file for the exact P-values.
To explore potential alterations in inflammatory signaling, we
determined the levels of phosphorylated Signal Transducer and Activator
of Transcription (STAT) proteins (Fig. [71]1d–f), which are known to be
key players in canonical intracellular pathways linked to macrophage
plasticity. Both p-STAT1 and p-STAT3 were unaltered in mdx BMDM during
the prenecrotic phase, consistent with the M1 and M2 marker gene
expression data. However, at the necrotic stage of disease there was
exaggerated phosphorylation of STAT1 and STAT3 in mdx BMDM, which was
mitigated but still present during the fibrotic phase. On the other
hand, p-STAT6 was not detectable in mdx BMDM during either the necrotic
or fibrotic stages (Supplementary Fig. [72]1).
To investigate whether the changes in mdx BMDM phenotype include signs
of metabolic reprogramming, we first assessed mitochondrial oxygen
consumption rate (OCR) in BMDM. There were no significant differences
in OCR between WT and mdx BMDM during the prenecrotic phase
(Fig. [73]2a). However, significant reductions in both basal and
maximal OCR were observed in mdx BMDM during the necrotic phase in
comparison to the age-matched WT group (Fig. [74]2b). In contrast, mdx
BMDM from the fibrotic phase showed a reversal of this pattern with
increased maximal OCR relative to age-matched WT values (Fig. [75]2c).
Along the same lines, there were no significant differences in culture
media lactate concentrations (index of glycolysis) between WT and mdx
BMDM during the prenecrotic phase, whereas in older mice lactate was
increased during the necrotic phase and decreased during the fibrotic
phase in the mdx groups (Fig. [76]2d). Interestingly, in WT mice the
induction of massive muscle necrosis by bilateral hindlimb muscle
(tibialis anterior) injection of the myotoxic agent cardiotoxin in vivo
did not trigger comparable alterations in either the inflammatory
(Fig. [77]2e) or metabolic (Fig. [78]2f) profiles of BMDM. Repeated
bouts of acute cardiotoxin-induced muscle damage were similarly unable
to recapitulate the BMDM phenotype of mdx mice (Fig. [79]2e). These
results imply that chronic ongoing muscle injury is required to induce
the abnormal immunometabolic phenotype observed in mdx BMDM.
Fig. 2. Metabolic changes in mdx BMDM at different disease stages.
[80]Fig. 2
[81]Open in a new tab
a–c Oxygen consumption rate (OCR) values after sequential treatment of
BMDM with oligomycin (O), FCCP (F) and antimycin + rotenone (A/R) as
measured by the Seahorse XF Analyzer at: a prenecrotic (n = 8/group), b
necrotic (n = 8/group), and c fibrotic (n = 8/group) phases of disease.
OCR values are normalized to cell count. d Lactate levels (normalized
to µg of cell lysate protein) in supernatants from WT and mdx BMDM
after incubating the cells for 48 h in phenol-red-free RPMI culture
media (n = 4/group for prenecrotic, n = 10/group for necrotic, and
n = 5/group for fibrotic). e mRNA transcript levels in BMDM (expressed
relative to the mean uninjured level represented by the dashed line)
obtained from WT mice after acute muscle injury (Injury 1x = injection
of cardiotoxin into both tibialis anterior muscles with euthanasia 3
days later; Injury 2x = injection of cardiotoxin into tibialis anterior
and gastrocnemius muscles on days 0 and 3, respectively, with
euthanasia at day 13) (n = 5/group). f Representative OCR curve from
Injury 1x group in e (n = 5/group). Data represent means ± SEM of
biologically independent samples from different mice. *P < 0.05 vs. WT
(unpaired t-test, two-tailed). See Source Data file for the exact
P-values.
mdx BMDM respond in an exaggerated fashion to heterologous inflammatory
stimuli
We wished to determine whether mdx BMDM exhibit non-specific
amplification of gene transcription responses after exposure to
heterologous stimuli, which is a defining feature of trained immunity.
For this purpose, we employed a variety of unrelated secondary stimuli
(cytokines, PAMPs/DAMPs). Following acute exposure to the classical
M1-polarizing stimulus of LPS + IFN-γ, mdx BMDM from the necrotic phase
showed increased pro-inflammatory gene (iNOS, TNF, IL6, IL12α)
transcript upregulation compared to WT BMDM (Fig. [82]3a). Greater
anti-inflammatory gene expression (TGFβ, CD206, Ym1, Arg1) was
similarly observed in mdx BMDM after exposure to the M2-polarizing
cytokine IL-4 (Fig. [83]3b). Stimulation with fibrinogen, an endogenous
TLR4 ligand DAMP previously implicated in DMD pathogenesis^[84]31, also
triggered greater pro-inflammatory (Fig. [85]3c) as well as
anti-inflammatory (Fig. [86]3d) gene transcript levels in the mdx BMDM
group. Furthermore, we exposed BMDM to the fungal cell wall-derived
PAMP β-glucan, as a non-specific secondary stimulus which is entirely
unrelated to DMD pathogenesis. Once again, significant
hyperresponsiveness was observed in mdx BMDM relative to the WT group
for β-glucan (Fig. [87]3e, f). An analogous but less pronounced pattern
of generalized hyperresponsiveness to these stimuli was also found in
mdx BMDM from the fibrotic phase of the disease (Supplementary
Fig. [88]2). On the other hand, BMDM from prenecrotic mdx mice
(Supplementary Fig. [89]3a–c) as well as cardiotoxin-injured mice
(Supplementary Fig. [90]3d, e) failed to exhibit similarly amplified
responses to secondary stimuli in comparison to WT BMDM. These data
show that following the onset of chronic generalized skeletal muscle
necrosis in mdx mice, BMDM are profoundly altered and demonstrate
significant hyperresponsiveness to multiple forms of unrelated
inflammatory stimuli.
Fig. 3. mdx BMDM exhibit non-specific amplification of M1 and M2 marker gene
expression in response to heterologous stimuli.
[91]Fig. 3
[92]Open in a new tab
a–f BMDM from age-matched WT and mdx mice at the necrotic phase of
disease were exposed to: a LPS + IFNγ (n = 5/group), b IL4
(n = 5/group), c, d fibrinogen (n = 3/group), or e, f β-glucan for 4
and 24 h (n = 5/group); mRNA transcript data for prototypical M1 and M2
marker genes are expressed relative to the mean basal WT (unstimulated)
level determined on the same PCR plate. Data represent means ± SEM of
biologically independent samples from different mice. *P < 0.05 vs.
unstimulated WT and †P < 0.05 vs. stimulated WT at a given time point
(one-way ANOVA followed by Tukey post-hoc test, two-tailed). See Source
Data file for the exact P-values.
Sustained phenotypic reprogramming of mdx BMDM
To account for the altered BMDM phenotype observed in post-necrotic mdx
mice, we postulated that DAMPs released into the systemic circulation
from widespread muscle damage could be at least partly responsible for
these changes. To test this hypothesis, naive WT BMDM were first
exposed to crushed skeletal muscle extract (ME) derived from either WT
or mdx mice to act as a primary training stimulus; the ME was removed
after 24 h, and the BMDM were then exposed 5 days later to fibrinogen
acting as a secondary stimulus (Fig. [93]4a). For the majority of genes
showing enhanced upregulation after the first challenge with ME,
expression had largely returned to baseline levels prior to the
secondary challenge with fibrinogen (Supplementary Fig. [94]4a, b). In
comparison to the control BMDM (PBS group), the BMDM exposed to either
WT-ME or mdx-ME demonstrated greater pro-inflammatory (Fig. [95]4b) as
well as anti-inflammatory (Fig. [96]4c) gene upregulation in response
to fibrinogen. Thus, exposing naive WT BMDM to components of damaged
skeletal muscle induced a phenotype resembling the mdx BMDM. The
magnitude of this effect was dependent on both the concentration
(Supplementary Fig. [97]4c) and duration (Supplementary Fig. [98]4d) of
exposure to ME, which could account for the fact that mdx serum induced
lesser effects than the highest dose of ME (Supplementary Fig. [99]4e).
Overall, these findings support the concept that muscle damage-related
molecules could potentially act as a primary “training stimulus” for
the induction of trained immunity in BMDM of mdx mice.
Fig. 4. BMDM exposed to muscle damage show a trained-like phenotype both in
vitro and in vivo.
[100]Fig. 4
[101]Open in a new tab
a Experimental design for WT- or mdx- muscle extract (ME) exposure to
induce trained immunity in naive WT BMDM. b, c Transcript levels are
shown for BMDM trained with PBS, WT-ME, or mdx-ME and then secondarily
exposed to fibrinogen (Fib) or RPMI for 8 h; the mRNA levels determined
by qPCR are expressed relative to the mean control (PBS-trained and
RPMI-stimulated) value (n = 5/group). d Schematic representation of the
BM transplant chimeric model. At 11 weeks post-transplantation BMDM
were generated from recipient mice previously transplanted with whole
BM from either WT (WT → WT) or mdx (mdx → WT) mice at necrotic phase.
The BMDM were stimulated with fibrinogen or β-glucan for 4 and 24 h
(e–h); e (n = 4 for TNF in 24 h mdx group, rest n = 5/group), f
(n = 5/group), g (n = 4 for TNF in 4 h mdx group, rest n = 5/group), h
(n = 4 for TGFβ and CD206 WT 4 h groups, rest n = 5/group). Data
represent means ± SEM of biologically independent samples from
different mice. b, c *P < 0.05 vs. PBS-trained and †P < 0.05 vs. WT-ME
trained. e–h *P < 0.05 vs. WT-unstimulated and †P < 0.05 vs.
WT-stimulated group at a given time point (one-way ANOVA followed by a
Tukey post-hoc test, two-tailed). See Source Data file for the exact
P-values.
To build on the above in vitro evidence for trained immunity, we next
performed in vivo experiments whereby irradiated WT host mice received
bone marrow transplants from either WT (WT→WT) or mdx (mdx→WT) donor
mice (Fig. [102]4d). At 11 weeks after bone marrow reconstitution,
there was no pathological macrophage infiltration in muscles of the WT
host mice that received mdx donor BMDM (Supplementary Fig. [103]4f).
However, the significant functional differences between WT and mdx
origin BMDM remained intact when these cells were studied in vitro.
Hence mdx origin BMDM continued to show greater pro- and
anti-inflammatory gene responses after stimulation with fibrinogen
(Fig. [104]4e, f) or β-glucan (Fig. [105]4g, h) despite being
transplanted into WT mice. This in vivo transmissibility and long-term
maintenance of the hyperresponsive mdx BMDM phenotype within a
non-dystrophic WT host environment is consistent with the presence of
innate immune memory^[106]29.
Phenotypic reprogramming of mdx BMDM is TLR4-dependent
TLR4 has the ability to sense a wide range of DAMPs released after
tissue injury. Therefore, we generated mdx mice with genetic abrogation
of TLR4 (mdxTLR4^-/-) to determine the role of TLR4 in the altered
immunophenotype of mdx BMDM. Under basal conditions mdxTLR4^-/- BMDM
exhibited lower transcript levels of both pro- and anti-inflammatory
genes compared to mdx BMDM, most strikingly during the necrotic stage
of the disease (Fig. [107]5a). In this regard, unsupervised
hierarchical clustering (Fig. [108]5b) clearly separated mdx from WT
and mdxTLR4^-/- BMDM during the necrotic phase; this genotype
clustering was less pronounced during the fibrotic phase and completely
absent at the prenecrotic stage. In addition, mdxTLR4^-/- BMDM from
both the necrotic (Fig. [109]5c) and fibrotic (Fig. [110]5d) stages
exhibited a higher maximal OCR level compared to their age-matched mdx
BMDM counterparts. Exposure to unrelated secondary stimuli
(Fig. [111]5e–h) revealed that the expression of both pro-inflammatory
and anti-inflammatory genes was reduced in mdxTLR4^-/- BMDM in
comparison to necrotic phase mdx BMDM. The changes in mRNA transcript
levels were corroborated at the protein level by western blotting
(Fig. [112]5i) and ELISA (Fig. [113]5j). Furthermore, using the same in
vitro ME stimulation protocol which induced signs of trained immunity
in WT BMDM (Fig. [114]4a), we found that this training response to ME
was prevented in cultured BMDM from TLR4-deficient (non-dystrophic)
mice. This was evinced by absence of the characteristic amplified gene
expression responses to fibrinogen and β-glucan (Fig. [115]5k, l).
Overall, these data indicate that the hyperresponsiveness to unrelated
secondary inflammatory stimuli as well as the altered metabolic
phenotype observed in mdx BMDM are largely abrogated by TLR4
deficiency.
Fig. 5. TLR4 regulates the altered phenotype of mdx BMDM.
[116]Fig. 5
[117]Open in a new tab
a Basal M1 and M2 marker gene transcript levels (expressed relative to
the mean age-matched WT level) in BMDM from WT, mdx, mdxTLR4^–/– mice
at different phases of disease (n = 4 for iNOS in prenecrotic phase and
IL12α in necrotic phase mdx groups, rest n = 5/group). b Heatmap
showing unsupervised hierarchical clustering analysis of samples based
on the gene expression data shown in a. Genes with higher and lower
expression levels are identified as red or blue (variable units
proportional to color intensity), respectively, whereas outlier samples
are black. c, d Oxygen consumption rate (OCR) data for mdx and
mdxTLR4^-/- BMDM at necrotic (n = 5/group) and fibrotic phases
(n = 5/group) of the disease. e–h WT, mdx, and mdxTLR4^–/– BMDM at
necrotic phase were stimulated with LPS + IFNγ (n = 5/group) or IL4
(n = 5/group) or fibrinogen (n = 3/group) to determine mRNA transcript
levels (expressed relative to the mean WT-unstimulated value) of: (e,
g) M1 and (f, h) M2 marker genes. i western blot images and
densitometric analyses of total iNOS and Arginase1 in cell lysates of
fibrinogen-stimulated (24 h) WT, mdx and mdxTLR4^–/– BMDM from necrotic
phase mice (n = 3/group; all experimental replicates are shown). j
ELISA measurements of TNF and IL6 protein levels in culture
supernatants from WT, mdx and mdxTLR4^–/– BMDM after stimulation with
fibrinogen for 24 h (n = 4/group). k, l As shown in Fig. [118]4a, WT
and TLR4^-/- BMDM were trained with mdx-ME and secondarily challenged
with k fibrinogen (8 h; n = 4/group) or l β-glucan (4 h; n = 4/group),
followed by qPCR. The graph shows mRNA transcript levels of genes
relative to the mean control (PBS-trained and RPMI-stimulated) WT
group. Data represent means ± SEM of biologically independent samples
from different mice; a *P < 0.05 WT vs. mdx and †P < 0.05 mdx vs.
mdxTLR4^–/– (one-way ANOVA followed by Tukey post-hoc test,
two-tailed); c, d *P < 0.05 WT vs. mdx (unpaired t-test, two-tailed);
e–j *P < 0.05 vs. WT and †P < 0.05 vs. mdx at a given time point
(one-way ANOVA followed by a Tukey post-hoc test, two-tailed); k
*P < 0.05 PBS vs. ME and †P < 0.05 WT vs. TLR4^–/– group (two-way ANOVA
followed by a Tukey post-hoc test, two-tailed). See Source Data file
for the exact P-values.
mdx BMDM are epigenetically altered in a TLR4-dependent manner
Epigenetic reprogramming is an important mechanism underlying the
development of trained immunity. We performed chromatin
immunoprecipitation (ChIP)-seq to quantify trimethylation of histone 3
lysine 27 (H3K27me3), a histone mark classically associated with gene
silencing^[119]32. Genome-wide analysis revealed a significant
reduction of H3K27me3 signal intensity in mdx BMDM compared to WT BMDM;
in contrast the mdxTLR4^-/- BMDM showed an overall increase in H3K27me3
signal relative to WT (Fig. [120]6a). The three experimental groups
were next analyzed according to their different patterns of relative
H3K27me3 signal intensity in close proximity (−5 kb to +1 kb) to the
gene body across the genome (see Supplementary Data [121]1 table). This
analysis identified four distinct patterns (termed GP1–GP4) showing
dynamic regulation in the mdx group relative to WT (Fig. [122]6b).
Among the mdx-altered H3K27me3 peaks, by far the predominant pattern
was a relative reduction of the signal in mdx compared to WT, with
restoration to WT levels in the mdxTLR4^-/- group (GP1 = 69% of peaks).
This pattern was followed in frequency by a reduction in mdx without
restoration in mdxTLR4^-/- (GP2 = 24% of peaks); increase in mdx
without restoration in mdxTLR4^-/- (GP3 = 5% of peaks); and increase in
mdx with restoration in mdxTLR4^-/- (GP4 = 2% of peaks).
Fig. 6. Dynamic regulation of H3K27me3 is present in mdx BMDM and mediated by
TLR4.
[123]Fig. 6
[124]Open in a new tab
ChIP sequencing was performed in WT, mdx and mdxTLR4^–/– BMDM: a Violin
plots representing normalized intensity fold-change (H3K27me3 vs.
Input) in the –5 kb to +1 kb neighboring genomic region around all
genes across the whole genome; *P < 0.0001 compared to WT BMDM and
†P < 0.0001 compared to mdx group (two-sided Mann–Whitney U-test). b
Heatmaps showing, in order of frequency (indicated by the percentages
in parentheses), the different Gene-based Patterns (GP1-4) of the
normalized H3K27me3 read intensity (variable units proportional to red
color intensity) within the nearby region [–5 kb to +1 kb] of the gene
body for WT, mdx and mdxTLR4^–/– BMDM. c Pathway enrichment analysis
(Reactome database) for genes showing the predominant GP1 configuration
(Supplementary Data [125]2 table shows the extended list for all
Gene-based Patterns). The vertical line indicates the cutoff
P-value = 0.05. d Heatmaps of H3K27me3 intensity for pre-defined genes
representing prototypical pro-inflammatory, anti-inflammatory, and
pro-fibrotic pathways (see Supplementary Data [126]3 table for complete
gene lists). e Representative pro-inflammatory gene loci (iNOS, IL12α)
showing the lower H3K27me3 peak intensity in the mdx group compared to
WT and mdxTLR4^–/–. f, g ChIP-qPCR was performed to detect H3K27me3
occupancy on the promoters of M1 and M2 marker genes in: f WT versus
mdx BMDM (n = 4 for iNOS, IL12α, CD206 and Arg1 gene in mdx group, rest
n = 5/group) and g mdx versus mdxTLR4^-/- BMDM (n = 5/group); IgG was
used as a control for non-specific binding of antibody. Data represent
means ± SEM of biologically independent samples from different mice.
*P < 0.05 by unpaired t-test, two-tailed). See Source Data file for the
exact P-values.
Pathway analysis was next applied to the mdx-altered H3K27me3 signal
patterns using Reactome informatics (Supplementary Data [127]2 table).
For the largely predominant GP1 pattern, extracellular matrix- and
collagen-related processes were among the most significantly enriched
biological pathways (Fig. [128]6c; see Supplementary Fig. [129]5 for
GP2-4 patterns). Individual genes selected a priori to reflect key
pro-inflammatory, anti-inflammatory, and pro-fibrotic processes were
also examined (Supplementary Data [130]3 table). In comparison to the
WT group, there was a widespread decrease of the H3K27me3 mark in mdx
BMDM for all of these gene categories, which was significantly reversed
in the mdxTLR4^-/- group (Fig. [131]6d, e). Dynamically regulated
patterns of the H3K27me3 mark in mdx BMDM were also used to perform
transcription factor-related pathway analysis (Supplementary
Fig. [132]6). The latter analysis indicated that for the most
frequently observed H3K27me3 pattern (termed PP1), transcription factor
enrichment was found for genes linked to the VENTX homeobox protein,
RUNX3/Wnt signaling, and several interleukins (IL-21, IL-35, IL-23,
IL-20, IL-12, IL-2) (Supplementary Fig. [133]6; Supplementary
Data [134]4 and [135]5 tables).
ChIP-qPCR was employed to corroborate these results by quantifying the
H3K27me3 mark within promoter regions of the prototypical pro- and
anti-inflammatory marker genes. In keeping with the ChIP-seq data, the
mdx group showed lower H3K27me3 promoter occupancy than in WT
(Fig. [136]6f), whereas levels of this histone mark were relatively
increased in the mdx BMDM lacking TLR4 (Fig. [137]6g). ChIP-PCR was
additionally utilized to assess promoter occupancy by H3K4me3
(Supplementary Fig. [138]7), a permissive histone mark typically
associated with gene activation. Greater H3K4me3 promoter occupancy was
observed for several genes in the mdx group (Supplementary
Fig. [139]7a), but in contrast to H3K27me3, genetic abrogation of TLR4
in mdx BMDM had no significant impact on H3K4me3 deposition
(Supplementary Fig. [140]7b).
In addition to changes in methylation, increased acetylation (ac) of
H3K27 is linked to greater chromatin accessibility and increased
transcriptional competency. ChIP-seq revealed that in comparison to WT
BMDM, there was an overall reduction of H3K27ac signal intensity in mdx
BMDM, with a further decrease in the mdxTLR4^-/- group (Supplementary
Fig. [141]8a, b; Supplementary Data [142]1 table). Reactome pathway
analysis (Supplementary Data [143]2 table) of this dominant pattern
(GP1 = 73% of peaks) indicated particular enrichment for biological
processes associated with protein metabolism, the cell cycle, and gene
expression (Supplementary Fig. [144]8c). The next most frequent pattern
was increased H3K27ac signal in mdx BMDM compared to WT and a relative
decrease in the mdxTLR4^-/- group (GP2 = 16% of peaks). Interestingly,
this pattern was especially enriched for cellular responses to stress
and external stimuli (Supplementary Fig. [145]8d), which is consistent
with the trained immunity phenotype. Transcription factor-related
pathway analysis was also performed (Supplementary Fig. [146]9;
Supplementary Data [147]4 and [148]5 tables), and the corresponding
peak patterns suggested possible involvement of interleukin, Notch, and
interferon signaling.
Taken together, these data suggest a complex pattern of epigenetic
reprogramming in mdx BMDM, with co-existence of histone mark
modifications that can either augment (decreased H3K27me3 and increased
H3K4me3) or reduce (decreased H3K27ac) the open chromatin state. The
predominant histone mark changes demonstrated in mdxTLR4^-/- BMDM, on
the other hand, would generally be expected to decrease chromatin
accessibility (increased H3K27me3 and decreased H3K27ac). In addition,
among the epigenetic modifications observed in mdx BMDM, it was most
clearly evident for H3K27me3 that the changes were TLR4-dependent and
could promote increased transcriptional activation of genes involved in
inflammation and fibrosis.
Functional differences between WT, mdx, and mdxTLR4^-/- BMDM in vivo
Finally, to determine whether the changes in mdx BMDM phenotype in
vitro are associated with functional differences in vivo, we performed
intravenous (IV) adoptive transfer of bone marrow from necrotic phase
mdx mice or age-matched WT mice (bone marrow donors) into WT recipient
mice (hosts) subjected to acute hindlimb muscle injury via cardiotoxin
injection (Fig. [149]7a). The bone marrow donor mice shared the common
CD45.2 allele and both strains (WT and mdx) demonstrated an equivalent
distribution of bone marrow leukocyte populations prior to adoptive
transfer (Fig. [150]7b–d). The bone marrow recipient WT host mice had
the CD45.1 allele in order to allow donor versus host origin
macrophages to be distinguished by flow cytometry. Muscles were
collected from the WT host mice at 4 days post-injury, which was the
approximate time of maximal macrophage infiltration.
Fig. 7. Adoptive transfer reveals the altered phenotype of mdx and
mdxTLR4^–/– BMDM after muscle injury in vivo.
[151]Fig. 7
[152]Open in a new tab
a Pictorial representation showing adoptive transfer of bone marrow
(BM) from WT or mdx (both CD45.2 allele) mice into non-irradiated
congenic WT (CD45.1 allele) mice at the onset of cardiotoxin-induced
hindlimb muscle injury, followed by flow cytometric analysis of donor
and host BMDM in the injured muscle 4 days later. b–d Comparison of
absolute number of: b Hematopoietic precursor cells (CLP: common
lymphoid progenitors, CMP: common myeloid progenitors, GMP:
granulocyte/macrophage progenitors, MEP: megakaryocyte/erythrocyte
progenitors; n = 5/group), c Innate myeloid cells (EPs: Eosinophils,
NPs: Neutrophils, MCs: Monocytes, MPs: Macrophages) (n = 5/group) and d
Lymphocytes (B: B cells, CD3: CD3 T cells, CD4: CD4 T cells, CD8: CD8 T
cells) (n = 5/group) in the BM of age-matched WT or mdx at necrotic
phase. e, f Quantification of host (CD45.1–WT; e n = 15/group) and
donor (CD45.2-either WT or mdx or mock adoptive transfer with PBS; f
n = 14 for WT, rest n = 15/group) macrophages in the injured muscles
(defined as CD45 + CD11c-CD11b + F4/80 + ). g Percentage of donor
pro-inflammatory (iNOS + TGFβ-CD206-) and h donor anti-inflammatory
(iNOS-TGFβ + CD206 + ) BMDM of either WT or mdx origin in the injured
WT host muscle (n = 10/group). i Schematic showing adoptive transfer of
mdx or mdxTLR4^–/– BM using the same experimental design. j, k
Quantification of host (CD45.1–WT; n = 6 for PBS, rest n = 10/group)
and donor (CD45.2-either mdx or mdxTLR4^–/–; n = 5/group) macrophages
in the injured muscles. l Percentage of donor pro-inflammatory and m
donor anti-inflammatory BMDM of either mdx or mdxTLR4^-/- origin in the
injured WT host muscle (n = 5/group). Data represent means ± SEM of
biologically independent samples from different mice. *P < 0.05
(unpaired t-test, two-tailed). See Source Data file for the exact
P-values.
The majority of macrophages in the injured muscle were of host origin
(CD45.1), and there were no differences in CD45.1 macrophage number
between the WT and mdx donor groups (Fig. [153]7e). However, donor
origin (CD45.2) BMDM in the injured muscles were significantly more
abundant in the mice injected with mdx donor cells as compared to WT
donors (Fig. [154]7f). As muscles of mdx mice from the necrotic phase
of disease contain a higher proportion of pro-inflammatory (iNOS + ,
TGFb-, CD206-) macrophages (Supplementary Fig. [155]10), we also sought
this phenotypic signature in the adoptively transferred BMDM. In the
host mice that received mdx bone marrow donor cells, the injured
muscles contained a greater percentage of CD45.2 macrophages exhibiting
a pro-inflammatory phenotype in comparison to mice which had received
WT donor cells (Fig. [156]7g, h). Importantly, these differences in
inflammatory profile were limited to the CD45.2 (donor) macrophages and
not observed in CD45.1 (host) macrophages (Supplementary Fig. [157]11a,
b) within the same muscles.
The same experimental design was used to compare the in vivo behavior
of mdx versus mdxTLR4^–/– bone marrow origin macrophages
(Fig. [158]7i). Once again there were no differences in the numbers
(Fig. [159]7j) or inflammatory profile (Supplementary Fig. [160]11c, d)
of host origin (CD45.1) macrophages within the injured WT muscles. In
contrast, adoptively transferred (CD45.2) macrophages were reduced in
number (Fig. [161]7k) and also less inflammatory (Fig. [162]7l, m) in
the injured WT muscles of mice that received mdxTLR4^–/– donor cells as
compared to the group injected with mdx donor cells. These in vivo
adoptive transfer studies are in keeping with the earlier in vitro data
and support the presence of an altered macrophage phenotype in mdx mice
that is epigenetically imprinted at the level of the bone marrow and
significantly mediated via TLR4.
Discussion
From an evolutionary standpoint, the immune system is primarily
designed to deal with acute localized muscle damage (e.g., traumatic or
infectious) rather than the ongoing widespread injury found in chronic
muscle diseases such as DMD. After acute muscle injury an initial wave
of bone marrow (monocyte)-derived M1-like macrophages populates the
muscle, which are then replaced by macrophages with a M2-like
phenotype^[163]33. As a general rule, any interference with this
tightly regulated sequence of events impedes normal skeletal muscle
repair^[164]34. Importantly, this normal sequence is lost in the
context of DMD, where repeated injury leads not only to an abnormal
persistence of macrophages, but also to an increased prevalence of
macrophages within the muscle that exhibit simultaneous upregulation of
both M1 and M2 marker genes^[165]7–[166]9. Failed muscle regeneration
and subsequent fibrosis in dystrophin deficiency have been
substantially attributed to dysregulated function of macrophages and
other immune cells. The dystrophin isoform (Dp71) found in myeloid
cells remains intact in the mdx mouse^[167]35,[168]36, and macrophage
dysregulation is thought to be primarily driven by pathological cues
received directly within the local muscle
microenvironment^[169]8,[170]12,[171]37. The results of the present
study add a major new layer of complexity to this scenario by showing
that before their entry into the pathological muscle microenvironment,
BMDM of dystrophic mice undergo extensive epigenetic remodeling which
is accompanied by pronounced alterations in cellular function.
The fact that a primary muscle disease induces such effects within bone
marrow myeloid cells implies a role for systemic signaling molecules
such as DAMPs originating from the damaged muscles. This concept is
supported by the fact that muscle extract derived not only from mdx but
also from healthy WT mice, was able to induce changes consistent with
trained immunity within naive WT BMDM in vitro. However, the
involvement of muscle damage-derived DAMPs as the primary stimulus
generating trained immunity in mdx mice remains a hypothesis, and it is
possible that other factors such as cytokines or exosomes play
significant roles within the in vivo environment^[172]38,[173]39.
Furthermore, it is interesting to note that the induction of acute
necrotic muscle injury in WT mice in vivo, whether in either single or
repeated bouts, did not recapitulate the changes observed in mdx BMDM.
This is perhaps not surprising since the nature of the molecules
released by different mechanisms of muscle damage, as well as the
quantity and duration of exposure to DAMPs and other signals delivered
to the bone marrow, may differ substantially for various forms of acute
versus chronic muscle injury.
Several DAMPs are known to be endogenous ligands for TLR4^[174]14.
Among candidate DAMPs that are chronically increased in the muscles
and/or serum of mdx mice and DMD patients^[175]40,[176]41, some such as
fibrinogen have been directly implicated in DMD
pathogenesis^[177]12,[178]31,[179]42. The levels of such DAMPs can also
vary according to disease stage^[180]40, which may at least partially
explain our observation of disease stage-specific differences in mdx
BMDM characteristics. Genetic deficiency of fibrinogen led to reduced
muscle pathology in mdx mice^[181]31. Along the same lines, we
previously reported that global TLR4 deficiency in mdx mice reduces
pro-inflammatory macrophages within mdx muscles and significantly
mitigates disease progression including in the most severely affected
muscle, the diaphragm^[182]12. This is consistent with the fact that
low concentrations of TLR ligands induce CCR2-dependent monocyte
emigration from the bone marrow^[183]43. In the present study, we found
that the phenotypic changes observed in mdx BMDM in vitro were all
largely prevented in mdx mice lacking TLR4. Although this could be
partially related to less severe muscle pathology in mdxTLR4^–/– mice,
our data indicate that the ability to induce trained immunity is also
severely impaired in non-dystrophic BMDM lacking TLR4. In addition,
adoptive transfer studies in vivo showed that the mdx BMDM recruited to
injured muscles were significantly reduced in number and associated
with a less inflammatory profile when these BMDM lacked TLR4.
In our study, mdx BMDM demonstrated an undifferentiated mixed M1/M2
phenotype in vitro, whereas mdx BMDM that were adoptively transferred
into an inflammatory muscle injury milieu (such as found in early
stages of the disease), exhibited pro-inflammatory M1-like skewing. The
alterations in cellular metabolism observed over time in mdx BMDM,
suggesting a greater reliance on oxidative phosphorylation at later
stages of the disease, are consistent with the macrophage phenotype
evolution from M1- to M2-like previously described within mdx
muscles^[184]7,[185]44. We speculate that the epigenetic and metabolic
reprogramming found in mdx BMDM serves to place the cells in a more
conducive state for assuming different possible macrophage phenotypes
after entering the muscle. According to this model (see Fig. [186]8),
the functional modifications taking place centrally in the bone marrow
favor more efficient adoption of either end (or some combination
thereof) of the M1/M2 polarization spectrum. The ultimate phenotypic
outcome peripherally in the dystrophic muscle tissue is determined by
additional signals received within the local muscle microenvironment.
This scenario is analogous to the epigenetically-mediated “poised”
state of embryonic stem cells, where a mixture of activating and
repressive marks on the same histones helps to maintain pluripotency
until further environmental cues are received to drive differentiation
toward a specific lineage^[187]32.
Fig. 8. Model for cross-talk between dystrophic skeletal muscle and bone
marrow leading to a reprogrammed macrophage phenotype.
[188]Fig. 8
[189]Open in a new tab
According to the model, chronic systemic exposure to damage-associated
molecular patterns (DAMPs) acting as ligands for innate immune
receptors such as TLR4, induces the hallmark features of trained
immunity (cytokine hyperresponsiveness, metabolic alterations,
epigenetic rewiring) in macrophage precursor cells residing in the bone
marrow. A more open chromatin state for both pro-inflammatory and
anti-inflammatory genes enhances the ability of future macrophages to
adopt different phenotypes once the cells home to damaged dystrophic
muscle tissue. The ultimate macrophage functional phenotype and impact
(adaptive or maladaptive) are dependent on the combination of signals
received at the bone marrow level and within the dystrophic muscle
milieu.
Trained immunity is an evolutionarily conserved protective response
against infection that first arose in organisms without an adaptive
immune system such as plants and invertebrates^[190]16. In addition to
epigenetic changes, we found that mdx BMDM demonstrated several other
keystone features of trained immunity. A major hallmark is the ability
to invoke a more intense inflammatory response upon re-challenge not
only with the initial triggering stimulus, but also with other agents
that differ from the initial challenge stimulus^[191]16. This is
thought to result from the fact that a more open chromatin state
induced by the epigenetic alterations permits a relatively broad and
non-specific increase in transcription factor accessibility to the
regulatory elements of innate immune system genes. Along these lines,
mdx BMDM demonstrated increased cytokine responses to a wide range of
heterologous stimuli (cytokines, fibrinogen, β-glucan) despite the
reliance of these diverse stimuli upon different cell surface
receptors. Analysis of classical markers for M1 and M2 macrophages
suggested global activation of the cells rather than simple skewing
toward M1 or M2 subtypes, which is also observed in trained immunity
induced by β-glucan^[192]21,[193]45. The above characteristics were
found in mdx BMDM despite removal of the cells from their in vivo
environment for 1 week, a “rest period” previously used to demonstrate
trained innate immunity in cultured human monocytes^[194]46,[195]47.
Remarkably, long-lasting differences between WT and mdx BMDM were also
transmissible in vivo, being maintained for at least 11 weeks after
removal from the inciting muscular dystrophy environment by
transplanting the mdx bone marrow into healthy WT mice.
Epigenetic changes representing a form of imprinted cellular memory or
education have increasingly been implicated in the pathogenesis of
inflammatory diseases^[196]16,[197]26. In some cases the maintenance of
inflammation at an abnormally high basal level is sustained for a
prolonged period after removal of the activating stimulus, which has
been referred to as priming^[198]17. In other instances, removal of the
inciting stimulus allows innate immune system activity to largely
return to its original low basal state, but upon reintroduction of
either the same or unrelated immunological stimuli there is a more
robust transcriptional response. The latter situation is characteristic
of trained immunity and was found to be the case in mdx BMDM. The most
commonly reported epigenetic changes linked to trained immunity in
prior studies have involved histone modifications such as H3K4
methylation and H3K27 acetylation^[199]48. In addition, it was recently
shown that TLR4 signaling triggered by transient LPS exposure can
induce persistent alterations of myeloid enhancer accessibility within
hematopoietic stem cells, accompanied by improved innate immunity
against infection^[200]29.
In the present study, we show that mdx BMDM exhibit a complex
combination of histone mark modifications that can simultaneously favor
or impede the open chromatin state. These findings are similar to a
previous report also showing a simultaneous decrease in repressive and
activating histone marks in trained immunity^[201]49, which could serve
to maintain gene transcription in a poised state. It is also important
to note that epigenetic modifications in mdx BMDM undoubtedly extend
well beyond the changes found in our study. However, at least with
respect to H3K27, it appears that increased chromatin accessibility in
mdx BMDM is primarily mediated through reduced methylation rather than
increased acetylation. Furthermore, the changes in H3K27me3 were
TLR4-dependent and involved genes associated with dystrophic muscle
inflammation and fibrosis.
Current evidence suggests that trained immunity can occur in
humans^[202]18–[203]20, where it may be an important driver of
pathological inflammation in non-infectious diseases such as
atherosclerosis^[204]23, Alzheimer’s disease^[205]22 and chronic
allergy^[206]24,[207]25. To our knowledge the present study provides
the first evidence for trained immunity in DMD or any other form of
skeletal muscle disease. These findings suggest the possibility of a
new paradigm for DMD muscle inflammation in which monocyte-derived
macrophages from the bone marrow undergo a process of extensive
cellular reprogramming before being recruited to the diseased muscles.
This altered myeloid cell phenotype is regulated by TLR4 and displays
the features of: (1) increased constitutive and DAMP-stimulated
cytokine production, (2) changes in cellular metabolism, and (3)
epigenetic remodeling. While these results are consistent with altered
innate immune memory in murine DMD, whether these phenomena also occur
in human DMD or other types of chronic muscle disease remains to be
determined. The mdx model of DMD exhibits a more intense phase of early
necrosis than human patients. In addition, the specific stimuli
involved in the reprogramming of these cells are yet to be elucidated.
Future studies should be directed at determining whether either
preventing or reversing these processes is feasible and able to
favorably modify the course of the disease. It will also be of interest
to ascertain whether trained immunity, through amplification of the
host immune response, represents an impediment to gene therapy and
other dystrophin restoration strategies.
Methods
Experimental animals
All procedures were approved by the Animal Care and Use Committee of
Research Institute of the McGill University Health Centre (RI-MUHC,
protocol #3480), according to the guidelines issued by the Canadian
Council on Animal Care. Wild-type (WT) mice: CD45.2 (stock #000664) and
CD45.1 (stock #002014) alleles, dystrophic mdx^4cv mice (mdx, stock
#002378) and TLR4^-/- mice (stock #029015) were on the C57BL/6 J
background, with all breeding pairs originally purchased from The
Jackson Laboratories (Bar Harbor, ME). The mdx mice lacking TLR4
(mdxTLR4^−/−) were generated as described previously^[208]12. All
experiments were performed on male mice. Both experimental and control
groups were bred separately and co-housed under pathogen-free
conditions at the animal facility of RI-MUHC and kept under a 12-h
light/12-h dark cycle at a temperature 21 ± 1 °C and relative humidity
of 40–60%. Euthanasia was conducted under anesthesia with isoflurane
followed by cervical dislocation.
Culture of bone marrow-derived macrophages (BMDM)
L929 mouse fibroblast cells were purchased from the American Type
Culture Collection and grown at 37 °C with 5% CO[2] for 7 days in
Dulbecco’s Modified Eagle Medium (DMEM) supplemented with 10% fetal
bovine serum (FBS); supernatant containing macrophage
colony-stimulating factor (M-CSF) was then collected and stored at
−80 °C for later use. For BMDM culture, tibia and femur bone were
harvested bilaterally and bone marrow was flushed out using a syringe
filled with Roswell Park Memorial Institute (RPMI) (Wisent) medium
containing 10% FBS. Bone marrow cells were plated in RPMI media
supplemented with 2 mM l-glutamine, 10% FBS, 1% non-essential amino
acids, 1% essential amino acids, 0.14% 5 N NaOH, 2% HEPES,1 mM sodium
pyruvate, 100 U/ml penicillin, 100 mg/ml streptomycin (all from Wisent)
and 30% L929 supernatant for 7 days in order to obtain differentiated
BMDM. For stimulation, BMDM obtained at the end of 7 days were treated
with LPS (100 ng/ml) + IFN-γ (20 ng/ml) (Invitrogen, USA), IL-4
(20 ng/ml) (Invitrogen, USA), fibrinogen (1 mg/ml) (Sigma, USA), or
β-glucan (100 µg/ml, Sigma, USA) for 4 h and 24 h prior to cell
harvesting.
Real-time quantitative PCR (RT–qPCR)
Total RNA was extracted using TRIzol reagent (Invitrogen, USA)
according to the manufacturer’s protocol. After DNase I (Gibco, USA)
treatment, 1 µg of RNA was used for cDNA generation with random primers
and SuperScript II (Invitrogen, USA) reverse transcriptase. RT–qPCR was
performed using 10 ng of cDNA mixed with 5 µl of 2x SYBR Green
(Invitrogen, USA) and 0.5 µl of 10 µM primer mixes. RT–qPCR was carried
out for 40 cycles at a melting temperature of 95 °C for 15 s and an
annealing temperature of 60 °C for 1 min using a StepOne Plus
Thermocycler (Applied Biosystems, USA). Mouse HPRT1 was used as an
internal control. The relative quantification of gene expression was
analyzed by the 2^–△△Ct method, and the results are expressed as n-fold
difference relative to untreated WT control cells. Primer sequences are
shown in the Supplementary Data [209]6 table. Gene expression from qPCR
was used to generate heatmaps and perform unsupervised hierarchical
clustering with a web-based program (Heatmapper^[210]50,
[211]http://www.heatmapper.ca). Average linkage and Euclidean distance
measurement methods were used for clustering the samples.
Western blot
After washing and scraping the cells, total cell lysate was prepared in
radioimmunoprecipitation assay (RIPA) buffer followed by incubation on
ice for 1 h. Following centrifugation at 16,000 × g for 15 min, protein
concentration was detected by Pierce™ BCA Protein Assay Kit (Thermo
Fisher Scientific, USA). Equal amounts (20 µg) of protein lysate were
loaded onto Mini-PROTEAN® Precast Gels (Bio-Rad, Canada) and then
transferred onto polyvinylidene fluoride (PVDF) membrane. After
blocking with 5% BSA in Tris buffered saline (TBS) containing 0.1%
Tween-20, the membranes were incubated overnight at 4 °C with the
following primary antibodies (1:1000 dilution; from Cell Signalling,
USA, unless stated otherwise): p-STAT1 (#9167), total STAT1 (#9172),
p-STAT3 (#9131), total STAT3 (#9139), p-STAT6 (#9361), total STAT6
(#9362), arginase1 (#93668), and iNOS (1:1000 dilution, #610329, BD
Biosciences, USA). After washing with TBS containing 0.1% Tween-20,
blots were incubated with horseradish peroxidase (HRP)-conjugated
anti-mouse (1:5000 dilution, #W4021) and anti–rabbit (1:2500 dilution,
#W4011) secondary antibodies (Promega, Canada). Blots were developed
using the enhanced chemiluminescence (ECL) system (ECL Plus; Thermo
Scientific, USA). As a loading control, membranes were incubated
overnight with actin antibody (1:10,000 dilution, #A2228; Sigma, USA).
The original western blot images are provided in the corresponding
Source Data file sections. The intensity of the bands was quantified
with Image Lab software (Bio-Rad, USA), and the densitometry analysis
is expressed as n-fold-change relative to WT control after actin
normalization.
Cellular bioenergetics (Seahorse) analyses
Measurements of mitochondrial oxygen consumption rate (OCR) were
obtained using the XF96 Extracellular Analyzer (Seahorse Bioscience).
BMDM at a density of 1 × 10^5 in 100 µl of DMEM media were seeded into
XF96 cell culture microplates 24 h before the assay. For the assay, XF
assay media supplemented with 10 mM glucose and 1 mM sodium pyruvate at
pH 7.4 was used. Following the basal respiration measurement, the OCR
was analyzed after three measurements were taken pre- and post-addition
of 1.5 µM oligomycin, 1 µM carbonilcyanide
p-triflouromethoxyphenylhydrazone (FCCP), 2 µM rotenone, and 1 µM
antimycin (all from Sigma, USA). Background from cell-free wells was
subtracted, and basal and maximal OCR values were calculated using
Seahorse Wave software (Seahorse Bioscience). For normalization,
adherent cells were washed twice with phosphate-buffered saline (PBS)
and fixed with 1% paraformaldehyde (PFA) for 20 min at 4 °C and stained
with 0.05% crystal violet for 30 min. After washing away the excess
crystal violet with PBS, the stained cells were solubilized with 1%
sodium dodecyl sulfate (SDS) followed by optical density (OD)
measurements at 595 nm using a Tecan plate reader. Data are expressed
as OCR normalized to the OD value from each individual well.
Lactate release assay and ELISA
BMDM were cultured in 6-well plates in phenol-red-free RPMI media for
48 h for lactate assays. Supernatants were collected and centrifuged at
16,000 × g for 15 min to remove cellular debris before storing at
−80 °C for later use. Supernatant lactate levels were measured with a
commercial kit following the manufacturer’s instructions (Lactate Assay
Kit, Eton Bioscience Inc, USA). Lactate concentrations were normalized
to the cellular content of each well as reflected by total protein
levels after removal of supernatant and washing of the cells with PBS.
For ELISA, BMDM were cultured in RPMI media containing fibrinogen
(1 mg/ml) for 24 h before collecting the supernatant. Levels of TNF and
IL6 in supernatant were measured by ELISA kit according to the
manufacturer’s instructions (R&D Systems, USA).
BMDM training with muscle extract and serum
Muscle extract and serum were used as primary training agents for WT
BMDM. Muscle extracts were prepared fresh from WT and mdx muscle by
homogenizing the muscle in PBS. Following centrifugation at 13,000 × g
for 15 min, extracts were collected and passed through 0.2 µm filter
before measuring the protein concentration. Similarly, serum from 4 to
6 weeks old WT and mdx mice was collected and filter-sterilized prior
to use. At day 3 of cell culture, the cells were incubated in RPMI
media containing muscle extract (1 mg/ml) or 5% serum or PBS for 24 h.
Cells were washed twice with RPMI media before allowing them to rest
for 5 days undisturbed except the addition of fresh RPMI media. BMDM
were then secondarily restimulated with fibrinogen (1 mg/ml) for 8 h or
β-glucan (100 µg/ml) for 4 h, followed by collection of the cells for
RNA extraction.
Generation of bone marrow chimeric mice
C57BL/6 CD45.1 (Jackson Laboratory, USA) recipient mice (6 weeks of
age) were lethally irradiated with total 12 Gy (delivered with two
doses of 6 Gy at 4 h apart) (X-RAD smart, Precision X-ray, North
Branford, CT). At 24 h after the second dose of radiation, 4 × 10^6
bone marrow cells isolated from either WT or mdx (donor, CD45.2 mice)
were injected intravenously to recipient mice. Mice were given
antibiotic treatment (50 mg/ml enrofloxacin, Bayer, USA) in drinking
water for three days before and 2 weeks after irradiation. Bone marrow
chimerism was determined by flow cytometry at 11 weeks after
transplantation.
Bone marrow adoptive transfer and acute muscle injury
For adoptive transfer experiments, bone marrow of CD45.2 allele donor
mice (WT, mdx or mdxTLR4^-/-) was isolated and 6 × 10^7 cells in PBS
were injected intravenously into CD45.1 allele host recipient mice
immediately prior to induction of muscle injury. To induce acute
skeletal muscle injury, both hindlimbs (tibialis anterior (TA) muscle)
were injected with 25 µl of 10 µM cardiotoxin as previously
described^[212]51. Four days later the recipient mice were euthanized
and injured muscles were processed to separately identify the host and
donor-derived macrophages according to their CD45 allelic status by
flow cytometry as described below.
Flow cytometry
Single cell suspensions were obtained by incubating minced muscles in
0.2% collagenase (Roche) at 37 °C for 45 min followed by filtering with
a 70-μm cell strainer. Bone marrow was flushed out using a syringe
filled with PBS and passed through 70-μm cell strainer. For flow
cytometry, 10^6 cells were resuspended in PBS containing 0.5% BSA (FACS
buffer). To distinguish between live and dead cells, cells were stained
with AF700 viability dye (Thermo Fisher Scientific, USA) for 30 min at
4 °C. The cells were then blocked with Fc blocking solution
(anti-CD16/CD32, BD Biosciences) for 10 min followed by
fluorescent-labeled antibody staining for 30 min at 4 °C.
Antibodies for flow cytometry were used at 1:100 dilution (BD
Biosciences, USA) unless stated otherwise. For cell surface markers,
the cells were stained at 4 °C in the dark with primary antibodies:
PE-labeled anti-CD45.1 (clone A20), V500 labeled anti-CD45.2 (clone
104), BUV395 labeled anti-CD45.2 (clone 104), BUV737 labeled anti-CD11c
(1:50 dilution, clone HL3), APC-Cy7 labeled anti-CD11b (clone M1/70,
BioLegend), PE-Cy7 labeled anti-F4/80 (clone BM8, BioLegend), biotin
conjugated: CD5 (clone 53-7.3, BioLegend), anti-Ly6G/C (clone RB6-8C5,
BioLegend), anti-CD11b (clone M1/70), anti-CD4 (clone RM4-5), anti-CD8a
(clone 53-6.7), anti-CD45R (clone RA3-6B2), Streptavidin conjugated
APC-Cy7, BV785 labeled anti-CD127 (clone A7R34), PE-Cy7 labeled
anti-Sca-1 (clone D7, BioLegend), APC labeled anti-c-Kit (clone 2B8),
FITC labeled anti-CD34 – FITC (clone RAM34), PerCp-Cy5.5 labeled
anti-CD16/32 (clone 93), PerCP-Cy5.5 labeled anti-CD3 (clone 145-2C11),
PE-Cy7 labeled anti-CD4 (clone 53-6.7, BioLegend), APC labeled CD8
(clone 53-6.7), BUV395 labeled anti-CD19 (clone 1D3), FITC labeled
anti-Ly6G (Clone 1A8, BioLegend), APC labeled anti-Ly6C (Clone HK1.4,
BioLegend), and PE-CF594 labeled anti Siglec-F (Clone E50-2440).
After staining, cells were washed three times with FACS buffer followed
by fixation with 4% PFA. For the staining of intracellular markers,
cells were permeabilized with 1X eBioscience™ permeabilization buffer
(Invitrogen, USA) and stained with antibodies in the permeabilization
buffer at 4 °C in the dark: FITC labeled anti-iNOS (clone 6/ iNOS/NOS
Type II), BV421 labeled anti-TGFβ (clone TW7-16B4). After washing three
times cells were resuspended in 300 µl of FACS buffer and 200,000
events were acquired on a BD LSRFortessa X-20 machine using BD
FACSDiva™ Software. Finally, the data were analyzed using FlowJo
software (Treestar Inc., Ashland, USA). Gating strategies
(Supplementary Fig. [213]12) were based on the FMO (Fluorescence Minus
One), which includes all antibodies but the one for which gating is
intended.
Chromatin immunoprecipitation (ChIP)-qPCR
Native chip assay was performed as described previously^[214]52.
Cultured BMDM were washed twice with cold PBS and cells were
non-enzymatically detached from the plate using Corning™ CellStripper
Dissociation Reagent (Corning, USA). Cells were washed three times with
cold PBS and 5 × 10^6 cells were then resuspended in douncing buffer
(10 mM Tris-HCl, pH 7.5, 4 mM MgCl2, 1 mM CaCl[2] and 1x protease
inhibitor cocktail (PIC)) and homogenized through a syringe. Chromatin
was digested in Micrococcal nuclease (New England Biolabs, Canada) at
37 °C for 7 min, and the reaction was inactivated by 0.5 M EDTA.
Chromatin was resuspended in hypotonic buffer (0.2 mM EDTA, pH 8.0,
0.1 mM benzamidine, 0.1 mM phenylmethylsulfonyl fluoride, 1.5 mM
dithiothreitol and 1x PIC) and incubated for 1 h on ice. After spinning
down the cell debris the supernatant was recovered. Chromatin was
pre-cleared with 100 μl of protein A Dynabeads (Invitrogen, USA) and
immunoprecipitation was carried out by incubating with a complex of
beads and H3K4me3 antibody (1:50 dilution, #ab8580; Abcam, UK) or
H3K27me3 antibody (1:50 dilution, #9733; Cell Signalling, USA) or
H3K27Ac antibody (1:50 dilution, #39133; Active Motif, USA,) or control
IgG antibody (1:50 dilution, #3900; Cell Signalling, USA) overnight at
4 °C. The complexes were washed twice with ChIP wash buffer I (20 mM
Tris-HCl, pH 8.0, 0.1% SDS, 1% Triton X-100, 2 mM EDTA and 150 mM NaCl)
and once with 400 μl of ChIP wash buffer II (20 mM Tris-HCl (pH 8.0),
0.1% SDS, 1% Triton X-100, 2 mM EDTA and 500 mM NaCl). Finally,
protein–DNA crosslinks were reversed in 200 μl of elution buffer
(100 mM NaHCO[3] and 1% SDS) for 2 h at 68 °C and the isolated DNA was
purified using phenol chloroform. ChIP DNA was analyzed by qPCR using
primers specific to promoter regions of interest, and the data were
normalized by input DNA. The primers used for ChIP-qPCR are listed in
the Supplementary Data [215]6 table.
Library preparation for ChIP sequencing
For library preparation, ChIP DNA ends were first repaired at 20 °C for
30 min with repair buffer (2.9 μl of H[2]O, 0.5 μl 1% Tween-20, 1 μl
dNTP mix 10 mM (#77119, Affymetrix, USA), 5 μl 10x T4 ligase buffer
(#L6030-HC-L Enzymatics, Qiagen, USA), 0.3 μl T4 DNA pol (#P7080L
Enzymatics), 0.3 μl T4 PNK (#Y9040 Enzymatics) and 0.06 μl Klenow
(#P7060L Enzymatics). Next, a mixture of 1 μl of Seradyn 3 EDAC
SpeedBeads (#6515-2105-050250, Thermo Fisher Scientific) and 93 μl of
20% PEG8000/2.5 M NaCl (13% final) was added and incubated for 10 min.
Magnetic beads were washed twice with 80% ethanol and air-dried for
10 min before elution in 15 μl ddH[2]O. dA-Tailing was performed by
incubating DNA at 37 °C for 30 min in the mixture of solution with
10.8 μl ddH2O, 0.3 μl 1% Tween-20, 3 μl Blue Buffer (#B0110L
Enzymatics), 0.6 μl dATP 10 mM (#10216-018, Thermo Fisher Scientific),
0.3 μl Klenow 3-5 Exo (#P7010-LC-L Enzymatics). Furthermore, 20%
PEG8000/2.5 M NaCl (13% final) was added and incubated for 10 min.
Beads were eluted in 14 μl of elution buffer (Zymo Research, USA). For
adapter ligation, sample was mixed with 0.5 μl of a BIOO barcode
adapter (#514104 BIOO Scientific, USA) with 15 μl Rapid Ligation Buffer
(#L603-LC-L Enzymatics), 0.33 μl 1% Tween-20 and 0.5 μl T4 DNA ligase
HC (#L6030-HC-L Enzymatics) and incubated for 15 min at room
temperature. Beads were further cleaned with 7 μl of 20% PEG8000/2.5 M
NaCl. Lastly, beads were eluted in 21 μl of elution buffer. From the
eluted volume, 10 μl was further used for PCR amplification (16 cycles)
with IGA primers (AATGATACGGCGACCACCGA) and IGB primers
(CAAGCAGAAGACGGCATACGA) in 1:1 ratio.
ChIP-sequencing data analysis
All H3K27me3 reads for the three libraries (WT, mdx, mdxTLR4^-/-) were
first mapped to the mm10 genome using Bowtie2^[216]53 under the default
parameters. There were four samples for each of the libraries (H3K27me3
replicate 1, H3K27me3 replicate 2, Input replicate 1, Input replicate
2). The reads from replicates were merged for the downstream analyses.
With the mapped reads, we quantified the read intensity for both the
H3K27me3 and Input sample of each library using deepTools^[217]54. The
methylation peaks were also called from the mapped reads using Spacial
Clustering for Identification of ChIP-Enriched Regions
(SICER)-2^[218]55 with the default parameters (window size = 200, gap
size = 600). All peaks with FDR < 0.01 were kept as the final
significant peaks. The overlapped genes were merged and finally 35,918
significant peaks for WT, mdx, and mdxTLR4^-/- were identified.
After all the peaks and genome-wide read intensities for the three
libraries were acquired, different methylation patterns for these peaks
were assigned. We first determined whether there was a significant
methylation difference (H3K27me3 vs. Input) associated with the peak
region for each of the libraries. The significance was calculated based
on the read intensity difference between the H3K27me3 and Input data
using a one-sided Mann–Whitney U-test. If the H3K27me3 read intensity
was significantly higher (defined as P-value < 0.05 and intensity
fold-change >1.5) than its corresponding input, the peak was designated
as Increased (I); otherwise, the peak was considered as Unchanged (U).
Using these designations, all the obtained peaks were assigned to 8 (
[MATH: 23
:MATH]
) different patterns for WT, mdx, mdxTLR4^-/- libraries included in
this study. After inferring the pattern for a specific peak relative to
the input, we also required that the methylation intensity fold-change
of the peak in any “Increased (I)” library be statistically greater
than that in any “Unchanged (U)” library (Mann–Whitney U-test
P-value < 0.05). The associated genes were identified for these
significant peaks if located within –5 kb to +1 kb of the gene.
Besides the above analysis strategy, the patterns for all genes across
the genome were also directly evaluated as follows. If the methylation
read intensity in the nearby region (–5 kb to +1 kb relative to the
gene body^[219]56) was significantly greater in the H3K27me3 sample
than its corresponding Input, this gene was designated as Increased
(I); otherwise, it was considered as unchanged (U). Using this
approach, defined as the Gene-based Pattern (GP) analysis, we
identified 3299 genes with 4 distinct patterns (designated GP1 to
GP4 = IUI, IUU, UII, and UIU, respectively) of dynamic regulation in
the mdx group relative to WT (GP1: 2293 genes, GP2: 786 genes, GP3: 154
genes, GP4: 66 genes). This analysis allowed the application of
biological pathway enrichment analysis (see below) for any given list
of genes (e.g., genes from a particular pathway).
To assess whether a given list of genes was statistically enriched with
a particular pattern, we used the binomial test as follows. First, we
calculated a background probability
[MATH:
pbpt :MATH]
for each pattern
[MATH: pt :MATH]
, which is learned as the percentage of genes (out of all genes) that
follow that particular pattern
[MATH: pt :MATH]
. The enrichment P-value can be calculated using the following
Eq. [220]1:
[MATH: Pvaluept=1−<
/mo>∑i=0Kinpbpti1−p<
mi>bptn−i, :MATH]
1
where
[MATH: n :MATH]
is the total number of genes in the gene list of interest, and
[MATH: k :MATH]
is the number of genes that follow the pattern
[MATH: pt :MATH]
(the null hypothesis H0: more than
[MATH: k :MATH]
out of
[MATH: n :MATH]
genes follow the
[MATH: pt :MATH]
pattern randomly). The biological pathways enriched with the above
patterns were determined using the Reactome pathway database^[221]57,
with a particular focus on those four patterns showing dynamic
regulation in WT vs. mdx groups (GP1–GP4). Using the approach described
above, a list of enriched Reactome pathways (sorted by the binomial
test P-value) associated with each of these patterns (both peak-based
and gene-based) was obtained.
In addition, Hypergeometric Optimization of Motif EnRichment (HOMER)-2
software^[222]58 was employed to identify potential transcription
factor enrichment within the peak regions exhibiting dynamic
differences between the WT and mdx groups. Using an analogous approach
to the Gene-based Pattern analysis outlined earlier, this was
designated as a Peak-based Pattern (PP) analysis (PP1 to PP4 = IUI,
IUU, UII, and UIU patterns, respectively). This information then
allowed further exploration of the biological functions linked to genes
in proximity (–5 kb to +1 kb of the gene) to the peaks using
complementary Reactome pathway analysis.
The H3K27ac ChIP-seq data analysis followed the same general procedure
as the H3K27me3 analysis described above. However, since H3K27ac
primarily marks the promoters and enhancers located in the upstream
region of the gene, only the upstream region (–5 kb) was targeted for
the Gene-based Pattern analysis. In addition, known enhancer
annotations^[223]59 were considered when mapping peaks to nearby genes.
Statistics and reproducibility
Unless stated otherwise, statistical analyses were performed using
GraphPad Prism Version 6.01 (San Diego, CA, USA). A P-value < 0.05 was
considered to be statistically significant (two-tailed for all data).
Comparisons between two groups were determined by unpaired t-test, and
between more than two groups by one- or two-way ANOVA followed by a
Tukey post-hoc test to adjust for multiple comparisons. Outliers
identified by the software were excluded from the analysis. Error bars
represent standard error of the mean (SEM) for the indicated number of
observations. The “n” for each bar graph represents the number of
independent biological replicates. For each figure, the statistical
test used and number of observations are shown in the graph and
respective figure legend. Exact P-values for each individual group
comparison are provided in the Source Data file.
Reporting summary
Further information on experimental design is available in
the [224]Nature Research Reporting Summary linked to this paper.
Supplementary information
[225]Supplementary Information^ (2.9MB, pdf)
[226]Peer Review File^ (424.5KB, pdf)
[227]41467_2022_28531_MOESM3_ESM.pdf^ (5.1KB, pdf)
Description of Additional Supplementary Files
[228]Supplementary Data 1^ (485.9KB, xlsx)
[229]Supplementary Data 2^ (78.3KB, xlsx)
[230]Supplementary Data 3^ (33KB, xlsx)
[231]Supplementary Data 4^ (2.1MB, xlsx)
[232]Supplementary Data 5^ (16.4KB, xlsx)
[233]Supplementary Data 6^ (10.3KB, xlsx)
[234]Reporting summary^ (318.3KB, pdf)
Acknowledgements