Katharina Müller-Ott1, Fabian Erdel1, Anna Matveeva2, Jan-Philipp Mallm1, Anne Rademacher1, Matthias Hahn3, Caroline Bauer1, Qin Zhang2, Sabine Kaltofen1, Gunnar Schotta3, Thomas Höfer2, Karsten Rippe4. 1. Deutsches Krebsforschungszentrum (DKFZ) and BioQuant, Research Group Genome Organization & Function, Heidelberg, Germany. 2. Deutsches Krebsforschungszentrum (DKFZ) and BioQuant, Division Theoretical Systems Biology, Heidelberg, Germany. 3. Munich Center for Integrated Protein Science and Adolf Butenandt Institute, Ludwig Maximilians University, Munich, Germany. 4. Deutsches Krebsforschungszentrum (DKFZ) and BioQuant, Research Group Genome Organization & Function, Heidelberg, Germany karsten.rippe@dkfz.de.
Abstract
The cell establishes heritable patterns of active and silenced chromatin via interacting factors that set, remove, and read epigenetic marks. To understand how the underlying networks operate, we have dissected transcriptional silencing in pericentric heterochromatin (PCH) of mouse fibroblasts. We assembled a quantitative map for the abundance and interactions of 16 factors related to PCH in living cells and found that stably bound complexes of the histone methyltransferase SUV39H1/2 demarcate the PCH state. From the experimental data, we developed a predictive mathematical model that explains how chromatin-bound SUV39H1/2 complexes act as nucleation sites and propagate a spatially confined PCH domain with elevated histone H3 lysine 9 trimethylation levels via chromatin dynamics. This "nucleation and looping" mechanism is particularly robust toward transient perturbations and stably maintains the PCH state. These features make it an attractive model for establishing functional epigenetic domains throughout the genome based on the localized immobilization of chromatin-modifying enzymes.
The cell establishes heritable patterns of active and silenced chromatin via interacting factors that set, remove, and read epigenetic marks. To understand how the underlying networks operate, we have dissected transcriptional silencing in pericentric heterochromatin (PCH) of mouse fibroblasts. We assembled a quantitative map for the abundance and interactions of 16 factors related to PCH in living cells and found that stably bound complexes of the histone methyltransferase SUV39H1/2 demarcate the PCH state. From the experimental data, we developed a predictive mathematical model that explains how chromatin-bound SUV39H1/2 complexes act as nucleation sites and propagate a spatially confined PCH domain with elevated histone H3lysine 9 trimethylation levels via chromatin dynamics. This "nucleation and looping" mechanism is particularly robust toward transient perturbations and stably maintains the PCH state. These features make it an attractive model for establishing functional epigenetic domains throughout the genome based on the localized immobilization of chromatin-modifying enzymes.
Epigenetic networks control the accessibility of DNA for transcription, DNA repair, and
replication machineries. They establish and maintain different functional chromatin states through
cell division via protein factors that set or remove specific modifications of histones and DNA in
the absence of alterations of the DNA sequence (Berger et al, 2009). These chromatin signals in turn recruit architectural chromatin components or
chromatin remodeling factors in a highly dynamic manner and regulate genome access (McBryant
et al, 2006; Taverna et al,
2007; Campos & Reinberg, 2009; Clapier & Cairns, 2009; Erdel
et al, 2011a). On a global scale, the
concerted and targeted activity of these networks results in the formation of the denser,
transcriptionally repressed heterochromatin state and the more open and biologically active
euchromatin, which can be distinguished at the resolution of the light microscope (Grewal &
Jia, 2007; Eissenberg & Reuter, 2009). A prototypic example for a constitutive heterochromatin domain is
pericentric heterochromatin (PCH) in mouse cells (Probst & Almouzni, 2008). It is characterized by its high content of repetitive major satellite
repeats and repressive epigenetic marks such as 5-methylcytosine (5meC) the binding of proteins with
a methyl-CpG-binding domain that recognize this modification, trimethylation of histone H3lysine
residue 9 (H3K9me3), and histone H4lysine residue 20 (H4K20me3), as well as hypoacetylation of
histones (Probst & Almouzni, 2008). The H3K9me3
modification is set by the histone methylases SUV39H1 and SUV39H2 (in the following
“SUV39H” refers to both isoforms), while SUV4-20H1 and SUV4-20H2 set H4K20me2 and
promote H4K20me3 (“SUV4-20H” for both isoforms) (Kwon & Workman, 2008; Schotta et al, 2008; Eissenberg & Reuter, 2009;
Byrum et al, 2013).A central protein component of PCH is heterochromatin protein 1 (HP1) that is present in three
very similar isoforms HP1α, HP1β, and HP1γ in mice and humans (Maison &
Almouzni, 2004; Hiragami & Festenstein, 2005; Kwon & Workman, 2008). HP1 contains an N-terminal chromodomain (CD) and a C-terminal chromoshadow-domain
(CSD) connected by a flexible linker region. The CD interacts specifically with H3 histone tails
that carry the K9me3 modification (Jacobs & Khorasanizadeh, 2002; Fischle et al, 2003). HP1 is
able to form homo- and heterodimers (Nielsen et al, 2001; Yamamoto & Sonoda, 2003; Rosnoblet
et al, 2011), interacts with SUV39H1
(Aagaard et al, 1999; Yamamoto &
Sonoda, 2003), SUV4-20H2 (Schotta et al,
2004; Souza et al, 2009), the DNA methylase DNMT1 (Fuks et al, 2003; Lehnertz et al, 2003;
Smallwood et al, 2007) as well as the
methyl-CpG-binding proteins MBD1 and MECP2 (Fujita et al, 2003; Agarwal et al, 2007).
SUV39H1 interacts with the DNA methylation-associated proteins DNMT1, MBD1, and MECP2 (Lunyak
et al, 2002; Fujita et al,
2003; Fuks et al, 2003; Esteve et al, 2006).
Thus, a complex protein–protein interaction network exists in PCH. The interactions
constituting this network in mammalian cells have been studied mostly in vitro or
via immunoprecipitation experiments and have not been probed comprehensively in living cells.Since HP1 interacts with SUV39H via its CSD, a feedback loop of HP1 binding-mediated H3K9
methylation has been proposed as a mechanism for propagating the H3K9me3 mark to adjacent
nucleosomes (Schotta et al, 2002; Grewal
& Jia, 2007; Eissenberg & Reuter, 2009). Theoretical models based on a combination of such feedback
loops have suggested the existence of two discrete chromatin states that can stably co-exist
(“bistability”) for a certain range of conditions (Schreiber & Bernstein, 2002; Dodd et al, 2007; Angel et al, 2011). Hathaway
et al have proposed an alternative, “monostable” model of
heterochromatin propagation through interactions between neighboring nucleosomes (Hathaway
et al, 2012). However, direct evidence on
how such epigenetic networks might operate in living cells is lacking. In particular, three crucial
questions remained unanswered: (i) How is the separation of the genome in active and silenced
chromatin states established and maintained and what are the factors that provide
specificity for distinct euchromatic and heterochromatic states? (ii) How is the
confinement of a given chromatin state to a certain genomic locus achieved? For the
case of a feedback loop between SUV39H, HP1, and H3K9me3 in PCH, it is elusive why the H3K9me3 does
not spread throughout the whole genome. (iii) How is a given chromatin state like that of PCH
transmitted through the cell cycle?Here, we have set out to address these issues by dissecting the mouse pericentric heterochromatin
network centered around the H3K9 and H4K20 methylation. This model system has the advantage that the
corresponding heterochromatin domains can be readily identified on fluorescence microscopy images as
chromatin-dense spots, the chromocenters. Accordingly, we were able to distinguish the features of
PCH from the surrounding bona fide euchromatin. By applying a combination of
fluorescence microscopy-based imaging, bleaching and correlation methods (Müller et
al, 2009; Erdel et al, 2011b) in conjunction with quantitative mechanistic modeling, we
identified distinct complexes of stably bound SUV39H as the component that defines the PCH state. We
further demonstrate that these SUV39H complexes represent “nucleation sites” that are
sufficient to provide specificity, confined propagation of the H3K9me3 mark as well as cellular
memory to transmit the PCH state through the cell cycle.
Results
The repressive PCH state is defined by enrichment of 5meC, MECP2, MBD1, and SUV39H
We quantitated the enrichment of the PCH-associated histone modifications H3K9me3, H4K20me3, the
DNA methylation 5meC and the known proteins that set, remove, or recognize these modifications in
the context of PCH in mouseNIH-3T3 fibroblasts: the histone H3K9 and histone H4K20 specific
methylases SUV39H1, SUV39H2, SUV4-20H1, SUV4-20H2, all three isoforms of the H3K9me3-reader HP1
(HP1α, HP1β, and HP1γ), the histone demethylases JMJD2B and JMJD2C that remove
H3K9me3, the DNA methylase DNMT1 as well as the methyl-CpG binding domain (MBD)-containing proteins
MECP2, MBD1, MBD2, and MBD3 [see (Fodor et al, 2010) for a review of previously identified mammalianPCH components].
Furthermore, we included the transcription factors PAX3, PAX5, PAX7, and PAX9 in our analysis since
a role for PAX3 in PCH assembly has been reported (Bulut-Karslioglu et al, 2012). Although the colocalization of these factors and histone
marks with PCH was studied previously, a comprehensive quantitative analysis of their
PCH-specificity and abundance has been lacking. Thus, we fluorescently labeled the factors of
interest (Supplementary Fig S1) and
determined the enrichment of GFP-tagged proteins in PCH using the workflow shown in Fig 1A: For each factor, the fluorescence intensity was measured in
PCH as defined by foci with intense DAPI (4′,6-diamidino-2-phenylindole) staining and in the
surrounding euchromatin of G1 phase cells. The enrichment of these factors in PCH was calculated,
followed by normalization to the enrichment of core histone H2A and DAPI in PCH. Chromatin binding
states were identified by fluorescence recovery after photobleaching (FRAP) and their enrichment in
PCH was determined. Fluorescence correlation spectroscopy (FCS) was used to measure protein
concentrations and the free diffusion coefficient in the cytoplasm, which served as a reference
value. Protein enrichments, concentrations, chromatin binding states, and protein–protein
interactions were integrated into a quantitative molecular model for PCH.
Figure 1
Quantitative analysis of core components of the pericentric heterochromatin (PCH)
network
Workflow of integrative PCH network analysis. The enrichment of different factors in PCH was
measured based on confocal laser scanning microscopy (CLSM) images. Abundance and chromatin
interactions were determined by fluorescence fluctuation microscopy methods (FRAP, FCS). Additional
information on protein–protein interactions was obtained as described in the text and in Fig
2. Based on the experimental data, a network model was
developed that explains the stable maintenance of PCH.
Enrichment of proteins, DNA methylation, H3K9me3, and H4K20me3 in PCH over euchromatic regions
from fluorescence intensity measurements in G1 phase cells. The red line marks the chromatin
compaction in PCH (1.8-fold enrichment of H2A-RFP). Labeled H2A, SUV39H1, and HP1 isoforms were
stably expressed, the other proteins were transiently expressed, and modifications were
immunostained. Error bars correspond to standard error of the mean (SEM).
Enrichment of transiently bound and immobilized protein fractions in PCH versus euchromatin
determined by FRAP. Red lines indicate 2-fold and 10-fold enrichment levels. Error bars correspond
to standard deviation (SD).
Absolute concentrations of stably bound proteins in the immobile FRAP fraction.
FRAP experiments of transiently expressed MBD1 and MECP2 in PCH and euchromatin (Eu). Data were
fitted to yield chromatin binding parameters.
FRAP of SUV39H1 (stably expressed) and SUV39H2 (transiently expressed).
FRAP of transiently expressed SUV4-20H1 and SUV4-20H2.
FRAP of stably expressed HP1β and HP1γ. For additional data including HP1α,
see Supplementary Table S2.
Quantitative analysis of core components of the pericentric heterochromatin (PCH)
network
Workflow of integrative PCH network analysis. The enrichment of different factors in PCH was
measured based on confocal laser scanning microscopy (CLSM) images. Abundance and chromatin
interactions were determined by fluorescence fluctuation microscopy methods (FRAP, FCS). Additional
information on protein–protein interactions was obtained as described in the text and in Fig
2. Based on the experimental data, a network model was
developed that explains the stable maintenance of PCH.
Figure 2
Protein–protein interaction analysis of HP1 and SUV39H1
Analytical ultracentrifugation (AUC) experiments of HP1β and its isolated domains. The
sedimentation coefficient c(s) distribution obtained from AUC
sedimentation velocity runs in the concentration range from 8–30 μM showed
dimerization of HP1β and the CSD (left panel) (Supplementary Table S3). Larger complexes were not observed. HP1β dimers
dissociated at lower concentrations, which is reflected by two peaks in the
c(s) distribution (right panel). An equilibrium dissociation
constant of 1–2 μM was determined from the relative molar fractions of monomer and
dimer species.
Protein–protein interaction analysis of soluble nucleoplasmic complexes by FCCS in
transiently transfected NIH-3T3 cells. The parameter ratio G(τ) reflects the
amount of complexes containing GFP- and RFP-labeled proteins. Control measurements were conducted
with double-labeled beads in buffer (positive control) and with inert GFP and RFP transiently
expressed in NIH-3T3 cells (negative control). For HP1, homodimers and heterodimers were found.
Additional FCCS measurements for HP1 and SUV39H1 are shown in Supplementary Fig S5A.
F2H interaction analysis of SUV39H1 and other PCH proteins. Human U2OS cells were co-transfected
with GBP-LacI and the indicated GFP and RFP constructs, resulting in tethering of the GFP-tagged
protein to the three lac-operator integration sites. HP1β interacted with SUV39H1 in living
cells with the percentage of colocalizations displayed in the barplot. Self-association of SUV39H1
and HP1α recruitment by MECP2 was also demonstrated. Isolated GFP was used as a negative
control. Scale bars, 10 μm. Error bars correspond to SD. Further F2H interaction measurements
are shown in Supplementary Fig S5B.
Enrichment of proteins, DNA methylation, H3K9me3, and H4K20me3 in PCH over euchromatic regions
from fluorescence intensity measurements in G1 phase cells. The red line marks the chromatin
compaction in PCH (1.8-fold enrichment of H2A-RFP). Labeled H2A, SUV39H1, and HP1 isoforms were
stably expressed, the other proteins were transiently expressed, and modifications were
immunostained. Error bars correspond to standard error of the mean (SEM).Enrichment of transiently bound and immobilized protein fractions in PCH versus euchromatin
determined by FRAP. Red lines indicate 2-fold and 10-fold enrichment levels. Error bars correspond
to standard deviation (SD).Absolute concentrations of stably bound proteins in the immobile FRAP fraction.FRAP experiments of transiently expressed MBD1 and MECP2 in PCH and euchromatin (Eu). Data were
fitted to yield chromatin binding parameters.FRAP of SUV39H1 (stably expressed) and SUV39H2 (transiently expressed).FRAP of transiently expressed SUV4-20H1 and SUV4-20H2.FRAP of stably expressed HP1β and HP1γ. For additional data including HP1α,
see Supplementary Table S2.PCH was about 1.8 ± 0.3-fold denser than euchromatin as determined from the H2A-RFP
intensity, whereas the DNA stain with DAPI yielded a 2.7 ± 0.1-fold enrichment in PCH,
possibly reflecting its binding preference for A/T-rich sequences. We conclude that chromatin is
about 2-fold more compacted in PCH (Fig 1B). In terms of
factors targeted to PCH during G1, we identified three different groups (Fig 1B): (i) Proteins displaying a diffuse distribution throughout the nucleus or a
slight depletion in PCH, which is indicative of little PCH-specific interactions (JMJD2B/C, DNMT1,
MBD3, and the PAX proteins). (ii) Factors whose PCH enrichment (2–3-fold) essentially
followed the increased chromatin density and accordingly displayed only moderate specificity for PCH
(MBD2, HP1, and H3K9me3). When normalized to the H2A-RFP chromatin density, the average enrichment
of H3K9me3 in PCH was only 1.4 ± 0.2-fold. Measured values ranged from 0.8- to 1.6-fold
between different experiments and antibodies used (Millipore and Abcam). (iii) Factors that were
clearly enriched above the 2-fold DNA compaction in PCH and thus represent PCH-specific components
(5meC, MECP2, MBD1, SUV39H, H4K20me3, SUV4-20H: ∼4- to 10-fold). The PCH enrichment of 5meC
measured by immunostaining varied between 2- and 5-fold, depending on antibody and fixation
protocols used. From bisulfite sequencing data of major satellite repeats in NIH-3T3 cells, mouse
embryonic stem cells (ESCs), and primary differentiated cells, we calculated an enrichment of 7
± 1 (Wilson & Jones, 1984; Yamagata et
al, 2007; Meissner et al, 2008; Arand et al, 2012).To validate the functional role of SUV39H and H3K9me3 in PCH of our cellular system, we measured
the abundance of satellite transcripts by quantitative real-time PCR in ESCs, immortalized mouse
embryonic fibroblasts (iMEFs) and iMEFs that had Suv39h1 and
Suv39h2 (iMEF Suv39h dn) deleted (Peters et al,
2001). The transcription levels of pericentric major
satellites were 4.6 ± 0.2-fold higher in ESCs and 14 ± 2-fold higher in iMEF
Suv39h dn cells as compared to fully differentiated iMEF wild-type (wt) cells
(Supplementary Fig S2A). Thus, PCH-specific
H3K9me3 levels in wild-type iMEFs, ESCs, and Suv39h dn iMEFs anti-correlate with
satellite repeat transcription, in agreement with previous measurements (Lehnertz et
al, 2003; Martens et al, 2005; Meshorer & Misteli, 2006). Importantly, the chromatin-dense chromocenters persisted in both
Suv39h and Suv4-20h double null cells, showing that
transcriptional silencing is not due to chromatin compaction per se (Supplementary Fig S2B and C). Decondensation of
the chromocenters was only observed upon inhibition of histone deacetylation (Supplementary Fig S2D) in agreement with previous
reports (Taddei et al, 2001). In summary,
we conclude that the enrichment of 5meC as well as MECP2, MBD1, SUV39H1, and SUV39H2 proteins
represent the hallmarks of PCH.
MECP2, SUV39H, and HP1 are the most abundant stably PCH-associated proteins
The above quantitative analysis of relative steady-state PCH enrichment levels lacks information
on the absolute endogenous protein concentrations and does not resolve differences in binding
kinetics. To address these issues, we integrated FCS and FRAP (Supplementary Fig S3A) (Müller et
al, 2009). By combining quantitative FCS and Western
blot analysis, endogenous SUV39H and SUV4-20H concentrations were determined to be between
0.1–0.4 μM in euchromatin and 0.2–3.0 μM in PCH (Supplementary Fig S3B and C, Table 1, Supplementary Table S1). HP1 displayed the highest concentration of the factors studied of
19 ± 12 μM in euchromatin and 41 ± 25 μM in PCH, with HP1β and
HP1γ being significantly more abundant than HP1α (Table 1, Supplementary Table
S1). The diffusion coefficients measured by FCS in the cytoplasm were in the expected range
and represent a reference value for the intracellular protein mobility of a given factor in the
absence of chromatin interactions (Supplementary
Table S1).
Table 1
Summary of binding interactions within the nucleus
Endogenous protein concentrations are given in terms of monomers. Values were determined from FCS
measurements of GFP-tagged proteins (Supplementary
Table S1) and APD-imaging (Supplementary
Materials and Methods). The ratio of endogenous to exogenous protein concentrations in the
cytoplasm (Cyto), euchromatin (Eu), and heterochromatin (PCH) was determined by quantitative Western
blot analysis. The minimal number of binding classes was determined from FRAP measurements and
subsequent data fitting to either a diffusion or a reaction-diffusion model. From the fit, fractions
of each binding class were determined and residence times were calculated according to
τres = 1/koff.
a Values for endogenous SUV39H2 and MECP2 concentrations were determined from RNA
expression levels measured in iMEF cells relative to SUV39H1 levels.
b For SUV4-20H, concentrations were measured in embryonic stem cells and represent
also values in fibroblasts since concentrations do not change significantly during differentiation
(Efroni et al, 2008).
c Class III binding of MECP2 in euchromatin was estimated by refitting the FRAP curves
with a reaction-diffusion model.
d Class II binding of HP1 was estimated by refitting the FRAP curves with a
reaction-diffusion model including a fixed off-rate, which has been determined for
heterochromatin.
e For unspecific binding of class I, the residence time τres
≤ 0.5 s is given as an estimate of the upper boundary resulting from the time resolution of
the FRAP measurements (not extractable from data fitting).
f The immobile fraction (class IV) is measured from the plateau value of the FRAP
curve after measurements for 4–5 min. It gives the lower boundary of the proteins’
residence time for which an approximate value of 4 min was used in the network model.
Summary of binding interactions within the nucleusEndogenous protein concentrations are given in terms of monomers. Values were determined from FCS
measurements of GFP-tagged proteins (Supplementary
Table S1) and APD-imaging (Supplementary
Materials and Methods). The ratio of endogenous to exogenous protein concentrations in the
cytoplasm (Cyto), euchromatin (Eu), and heterochromatin (PCH) was determined by quantitative Western
blot analysis. The minimal number of binding classes was determined from FRAP measurements and
subsequent data fitting to either a diffusion or a reaction-diffusion model. From the fit, fractions
of each binding class were determined and residence times were calculated according to
τres = 1/koff.a Values for endogenous SUV39H2 and MECP2 concentrations were determined from RNA
expression levels measured in iMEF cells relative to SUV39H1 levels.b For SUV4-20H, concentrations were measured in embryonic stem cells and represent
also values in fibroblasts since concentrations do not change significantly during differentiation
(Efroni et al, 2008).c Class III binding of MECP2 in euchromatin was estimated by refitting the FRAP curves
with a reaction-diffusion model.d Class II binding of HP1 was estimated by refitting the FRAP curves with a
reaction-diffusion model including a fixed off-rate, which has been determined for
heterochromatin.e For unspecific binding of class I, the residence time τres
≤ 0.5 s is given as an estimate of the upper boundary resulting from the time resolution of
the FRAP measurements (not extractable from data fitting).f The immobile fraction (class IV) is measured from the plateau value of the FRAP
curve after measurements for 4–5 min. It gives the lower boundary of the proteins’
residence time for which an approximate value of 4 min was used in the network model.Chromatin binding in the nucleus was evaluated by FRAP (Fig 1E–H) with a reaction-diffusion analysis that yielded the effective diffusion
coefficient Deff (including transient binding interactions), the
dissociation rate constant koff, the pseudo on-rate
k*on (including the free binding site concentration), and the
protein fraction immobilized on the minute time scale (Supplementary Fig S3A). From these data, we calculated average protein residence
times τres to different types of binding sites according to the following
rationale (Table 1, Supplementary Tables S1 and S2): (i) The difference between Dfree and
Deff indicated the presence of a protein pool, which binds transiently
with τres ≤ 0.5 s. These represent the lowest affinity binding sites (class
I) in our analysis. (ii) Kinetic on- and off-rates determined from the reaction-diffusion fit were
used to characterize two additional types of binding sites, class II and class III, with
1/koff = τres in the range of 3–5 s
(class II) and 25–100 s (class III). (iii) The highest affinity class IV binding sites
comprised the protein fraction that was immobile during the measurement corresponding to a lower
limit of τres of approximately 4 min.Accordingly, we interpret transient interactions (class I) as unspecific chromatin binding
interactions. These were present both in PCH and euchromatin and comprised essentially the entire
protein pool of the H3K9me3 demethylases JMJD2B/C and the transcription factor PAX3 (Supplementary Table S2, Supplementary Fig S4A and B). Class II and class
III binding sites were present in both euchromatin and PCH for the other proteins, albeit at
different concentrations. With respect to the immobile protein fractions (class IV), we measured a
particularly strong enrichment for MECP2 (∼80-fold), SUV39H1 (∼50-fold), and SUV39H2
(16-fold) in PCH as compared to euchromatin (Fig 1C).
Immobile fractions of MBD1, SUV4-20H, and HP1 were about 8-fold enriched in PCH. When calculating
the immobile fractions in terms of the absolute protein concentrations, the immobile fraction of the
combined HP1 species was the largest (2.7 μM), followed by that of MECP2 (1.6 μM),
SUV39H (1.1 μM), SUV4-20H (0.2 μM), and MBD1 (0.2 μM) (Fig 1D). Thus, the amount of immobilized HP1 provides enough protein molecules for
interactions with MECP2/MBD1, SUV39H, and SUV4-20H at the high-affinity binding sites, although this
HP1 fraction represents only approximately 7% of the total HP1 pool. Accordingly, we conclude
that 1–3 μM of MECP2, SUV39H, HP1, and SUV4-20H are tightly bound
(koff < 0.005 s−1) at PCH-specific sites that
are mostly absent in euchromatin.
PCH proteins form a complex interaction network
Our finding that MECP2/MBD1, HP1, and SUV39H are present at similar concentrations of about
1–3 μM in a stably PCH-attached state (Fig 1D;
Table 1) suggests that they assemble into a complex.
Accordingly, we mapped their protein interactions in vitro and in living cells (Fig
2, Supplementary Fig S5, Supplementary Tables
S3 and S4): First, we used
analytical ultracentrifugation (AUC) to measure the association state of full-length HP1β and
its isolated CD and CSD at physiological ionic strength. Full-length HP1β formed a dimer with
an equilibrium dissociation constant of 1–2 μM (Fig 2A, Supplementary Table S3). No
larger complexes were detectable up to a concentration of 30 μM. Dimerization was mediated by
the CSD of HP1 since the isolated domain was found to be dimeric while the CD was monomeric in
agreement with previous results (Ball et al, 1997; Nielsen et al, 2001). Second,
HP1 association in living cells was studied by fluorescence cross correlation spectroscopy (FCCS)
after transfecting cells stably expressing GFP-HP1α with RFP-HP1α, β or
γ. A soluble nuclear HP1 fraction of 65 ± 34% formed a dimer with either the
same HP1 isoform (homodimer) or another isoform (heterodimer) (Fig 2B, Supplementary Fig S5A).
Self-association of SUV39H1 was shown with a corresponding approach, yielding an approximately
24% fraction of soluble SUV39H1 present in homodimeric complexes (Supplementary Fig S5A). Third, we applied the
fluorescent two-hybrid (F2H) method (Zolghadr et al, 2008; Chung et al, 2011)
to evaluate the SUV39H1-SUV39H1 self-association and interactions of HP1-dimers with stably
chromatin-bound SUV39H in living cells. Tethering of SUV39H1-GFP to the lacO arrays
resulted in the recruitment of RFP-HP1 and SUV39H1-RFP (Fig 2C, Supplementary Fig S5B).
Furthermore, a strong interaction of HP1 with MECP2 and MBD1 was observed. However, we could not
confirm association of SUV39H1 with the MBD-proteins that was reported elsewhere (Supplementary Fig S5B) (Lunyak et
al, 2002; Fujita et al, 2003; Fuks et al, 2003; Esteve et al, 2006). A summary
of all (direct or indirect) protein–protein associations for the factors studied here is
given in Supplementary Table S4. It reveals
that the proteins involved in DNA and histone methylation form a complex interaction network in
living fibroblasts. We conclude that several of the above described protein–protein
interactions cooperate to target SUV39H to PCH and provide the interaction energy for its stable
tethering.
Protein–protein interaction analysis of HP1 and SUV39H1
Analytical ultracentrifugation (AUC) experiments of HP1β and its isolated domains. The
sedimentation coefficient c(s) distribution obtained from AUC
sedimentation velocity runs in the concentration range from 8–30 μM showed
dimerization of HP1β and the CSD (left panel) (Supplementary Table S3). Larger complexes were not observed. HP1β dimers
dissociated at lower concentrations, which is reflected by two peaks in the
c(s) distribution (right panel). An equilibrium dissociation
constant of 1–2 μM was determined from the relative molar fractions of monomer and
dimer species.Protein–protein interaction analysis of soluble nucleoplasmic complexes by FCCS in
transiently transfected NIH-3T3 cells. The parameter ratio G(τ) reflects the
amount of complexes containing GFP- and RFP-labeled proteins. Control measurements were conducted
with double-labeled beads in buffer (positive control) and with inert GFP and RFP transiently
expressed in NIH-3T3 cells (negative control). For HP1, homodimers and heterodimers were found.
Additional FCCS measurements for HP1 and SUV39H1 are shown in Supplementary Fig S5A.F2H interaction analysis of SUV39H1 and other PCH proteins. HumanU2OS cells were co-transfected
with GBP-LacI and the indicated GFP and RFP constructs, resulting in tethering of the GFP-tagged
protein to the three lac-operator integration sites. HP1β interacted with SUV39H1 in living
cells with the percentage of colocalizations displayed in the barplot. Self-association of SUV39H1
and HP1α recruitment by MECP2 was also demonstrated. Isolated GFP was used as a negative
control. Scale bars, 10 μm. Error bars correspond to SD. Further F2H interaction measurements
are shown in Supplementary Fig S5B.
SUV4-20H operates downstream of SUV39H and stabilizes HP1 binding to PCH
SUV39H is required for the enrichment of H3K9me3, H4K20me3, SUV4-20H, and HP1 in PCH, and the
loss of H3K9me3 and SUV39H leads to a strong increase in mobility of HP1 in PCH (Supplementary Figs S2B and S4C, Supplementary Table S5) as reported previously (Peters et al,
2001; Schotta et al, 2004; Müller et al, 2009). Immunostaining of 5meC revealed that this mark was maintained in iMEF
Suv39h dn cells, and also the MBD-proteins MECP2 [as shown previously in
(Brero et al, 2005)] and MBD1 remained
enriched in PCH (Supplementary Fig S2B).
This confirms that DNA methylation and enrichment of its reader proteins do not rely on SUV39H
(Lehnertz et al, 2003; Brero et
al, 2005).To assess the influence of H4K20me3 on PCH, we analyzed heterochromatin proteins and histone
modifications in iMEF Suv4-20h dn cells that lack both H4K20-specific methylases
SUV4-20H1 and SUV4-20H2 (Supplementary Fig
S2C) (Schotta et al, 2008). As
expected, the H3K9me3 mark was unperturbed, and SUV39H as well as HP1 were still enriched at the
chromocenters (Supplementary Fig S2C, Supplementary Table S5) (Schotta et
al, 2004). However, FRAP analyses revealed that HP1
was more mobile in Suv4-20h dn cells as compared to wild-type cells (Supplementary Table S2). In particular, the
immobile HP1 fraction was decreased to about half the wild-type value (Supplementary Fig S4D), the residence time of the
bound fraction was shorter, and the effective diffusion coefficient increased. This suggests that
SUV4-20H can enhance chromatin binding of HP1 although its binding to PCH occurs downstream of
H3K9me3, SUV39H, and HP1.
HP1 stabilizes SUV39H1 binding at PCH and promotes H3K9 trimethylation
We knocked down all three HP1 isoforms with siRNAs to evaluate the effect of HP1 on SUV39H
binding and H3K9me3 levels in chromocenters versus euchromatin on the single-cell level. The
knock-down resulted in a wide range of HP1 expression levels in individual cells (determined by
immunostaining) that correlated with SUV39H1 and H3K9me3 intensity signals (Fig 3A). Global nuclear expression levels of stably integrated SUV39H1-GFP followed
that of HP1, suggesting that HP1 stabilizes the Suv39h1 transcript or protein. In
addition, the PCH enrichment of SUV39H1 was reduced at lower HP1 concentrations. While SUV39H1
expression levels and PCH enrichment were sensitive to HP1 abundance over the complete range of
knockdown concentrations, the H3K9me3 levels remained constant for HP1 levels above 80% of
the wild-type concentration. Thus, cells were able to compensate for variations of HP1 and SUV39H1
concentrations to some extent. Below 80% of HP1, the heterochromatic H3K9me3 levels decayed
gradually with decreasing HP1 expression until euchromatic levels were reached (Fig 3A and B). Thus, HP1 contributes to the enrichment of SUV39H1 in
PCH and is required for maintaining wild-type H3K9me3 levels. Euchromatic H3K9me3 levels decreased
slightly with reduced HP1 concentrations (Fig 3A). This
could be related to interactions of HP1 with the histone methylases G9A and SETDB1 that are
preferentially active in euchromatin (Tachibana et al, 2002; Chin et al, 2007;
Loyola et al, 2009).
Figure 3
Effect of perturbation of HP1 and SUV39H protein expression
Triple knockdown of HP1α/β/γ by siRNA in NIH-3T3 cells stably expressing
SUV39H1-GFP. As apparent from HP1 immunostaining (top) knockdown efficiencies varied largely between
individual cells so that a large range of endogenous HP1 concentration was covered. The effects on
the abundance of SUV39H1-GFP and the H3K9me3 mark were detected by immunostaining (upper plot
panels). Their fold enrichment within PCH is presented in the bottom panels. Light gray bars depict
SEM.
Frequency distribution of methylation levels per PCH focus in wild-type (wt) cells (control,
solid line), Suv39h dn cells (Suv39h dn, dotted line), and HP1
triple-knockdown cells (TKD, dashed line) transfected with HP1 siRNA.
Comparison of H3K9me3 levels in wild-type and Suv39h dn cells determined from
quantitative imaging after immunostaining. H3K9me3 in PCH was largely reduced in
Suv39h dn cells while euchromatic levels were unperturbed (see also Supplementary Fig S2B). Absolute H3K9me3 levels
were calculated based on the global cellular H3K9me3 level reported previously (Waterston et
al, 2002; Fodor et al, 2006). Error bars correspond to SEM.
Average methylation rates were determined based on a simple model assuming an unmethylated and a
methylated state for each nucleosome. From the steady-state levels of H3K9me3 in wild-type and
Suv39h dn cells, the relative rate constants for the transitions are derived.
SUV39H methylates PCH with a specificity ratio of 8, whereas SETDB1/G9A methylate preferentially
euchromatic regions but with a lower specificity ranging from 1.5–2.2.
Effect of perturbation of HP1 and SUV39H protein expression
Triple knockdown of HP1α/β/γ by siRNA in NIH-3T3 cells stably expressing
SUV39H1-GFP. As apparent from HP1 immunostaining (top) knockdown efficiencies varied largely between
individual cells so that a large range of endogenous HP1 concentration was covered. The effects on
the abundance of SUV39H1-GFP and the H3K9me3 mark were detected by immunostaining (upper plot
panels). Their fold enrichment within PCH is presented in the bottom panels. Light gray bars depict
SEM.Frequency distribution of methylation levels per PCH focus in wild-type (wt) cells (control,
solid line), Suv39h dn cells (Suv39h dn, dotted line), and HP1
triple-knockdown cells (TKD, dashed line) transfected with HP1 siRNA.Comparison of H3K9me3 levels in wild-type and Suv39h dn cells determined from
quantitative imaging after immunostaining. H3K9me3 in PCH was largely reduced in
Suv39h dn cells while euchromatic levels were unperturbed (see also Supplementary Fig S2B). Absolute H3K9me3 levels
were calculated based on the global cellular H3K9me3 level reported previously (Waterston et
al, 2002; Fodor et al, 2006). Error bars correspond to SEM.Average methylation rates were determined based on a simple model assuming an unmethylated and a
methylated state for each nucleosome. From the steady-state levels of H3K9me3 in wild-type and
Suv39h dn cells, the relative rate constants for the transitions are derived.
SUV39H methylates PCH with a specificity ratio of 8, whereas SETDB1/G9A methylate preferentially
euchromatic regions but with a lower specificity ranging from 1.5–2.2.
SUV39H is responsible for depositing H3K9me3 preferentially in PCH
To quantify the contribution of SUV39H in catalyzing H3K9 trimethylation, we determined the
H3K9me3 levels of euchromatin and PCH in wild-type and Suv39h dn iMEFs based on the
relative H3K9me3 immunofluorescence signal in the same sample preparation (Fig 3C, Supplementary Fig
S2B). In wild-type cells, an average H3K9me3 level of 38 ± 3% in PCH and 28
± 1% in euchromatin was calculated based on a total H3K9me3 level of 28%
reported previously for mouse fibroblasts (Fodor et al, 2006). The corresponding values in the Suv39h dn cells were 13
± 2% (PCH) and 25 ± 4% (euchromatin), from which the relative
methylation rate of SUV39H can be estimated according to a simple quantitative model: Nucleosomes
can carry H3K9me3 (M) or lack this modification (U) (Fig 3D,
Supplementary Materials and Methods). Since
the JMJD2B/C demethylases were homogeneously distributed in the nucleus and displayed similar
mobility in both euchromatin and PCH (Supplementary Fig S4A), the demethylation rate k-m is assumed to
be equal in both chromatin states. The resulting H3K9me3 level in each state is solely determined by
the ratio of methylation rate km to k-m.
This yields an 8-fold preference of SUV39H for methylation of PCH versus euchromatin, while the
euchromatin-specific methylation provided by other methylases like SETDB1 and G9A is roughly 2-fold
higher in euchromatin than in PCH (Fig 3D). Notably, the
SUV39H specificity for PCH correlates well with the enrichment of chromatin-bound SUV39H molecules
in PCH (16- to 50-fold, Fig 1C). Thus, we conclude that the
SUV39H-dependent H3K9me3 modification is directly related to the amount of chromatin-bound
enzyme.
Silenced major satellite repeats are enriched with SUV39H, H3K9me3, HP1, and 5meC
To corroborate that SUV39H binding to chromatin concurs with HP1 and H3K9me3 at sites of DNA
methylation, we conducted an analysis by ChIP-seq (chromatin immunoprecipitation followed by DNA
sequencing). The enrichment of HP1β, SUV39H1, SUV39H2, and H3K9me3 at major satellite repeats
was evaluated in neural progenitor cells (NPCs) using the H3K36me3 modification as a reference
signature for transcriptionally active chromatin. NPCs were generated in vitro from
ESCs and represent a well-established model system for studying epigenetic modifications and
chromatin composition established during differentiation (Teif et al, 2012; Lorthongpanich et al, 2013). SUV39H1, SUV39H2, H3K9me3, and HP1β were enriched at the canonical
major satellite repeat sequence while no enrichment was detected for H3K36me3 (Fig 4A and B). Furthermore, we analyzed the distribution of bound
proteins at 16 uniquely mappable intergenic/intronic major satellite repeats annotated by the
RepeatMasker tool (Fig 4C and D). Of these repeats, 12 were
enriched for SUV39H, H3K9me3, and HP1β while H3K36me3 was depleted. Another two repeats
resided in an inactive state with low H3K36me3 and higher H3K9me3 levels but lacked enrichment of
SUV39H or HP1β. In contrast, the two active repeats carrying H3K36me3 lacked SUV39H, H3K9me3,
and HP1β. Thus, the ChIP-seq analysis corroborates our conclusions that stable chromatin
binding of SUV39H and transcriptional repression of major repeats correlate with the presence of HP1
and H3K9me3. Based on the 5meC distribution reported elsewhere (Lorthongpanich et
al, 2013), we calculated CpG methylation levels of
88 ± 8% at the 12 inactive intergenic/intronic repeats loaded with SUV39H, H3K9me3,
and HP1. The two active repeats had similar CpG densities and similar CpG methylation levels of 86
± 2%. Since the normalized 5meC density was only slightly higher at 1.3 ±
0.1-fold for silenced repeats compared to transcribed ones, we conclude that 5meC is not the
dominant silencing factor for these repeats.
Figure 4
Genome-wide ChIP-seq analysis of HP1, SUV39H, and H3K9me3 enrichment at major satellite
repeats
Fraction of total sequencing reads that mapped to the consensus sequence of major satellite
repeats (gamma satellites, GSAT) after ChIP-seq of HP1β, SUV39H1, or SUV39H2. Mild sonication
conditions were applied in neural progenitor cells (NPCs). The histogram shows the distribution of
the mapped reads along the consensus sequence. Error bars correspond to SD.
Same as panel A but for ChIP-seq of H3K9me3 and H3K36me3 and with stronger sonication
conditions.
Representative sequencing read distributions at interspersed major satellites that can be
uniquely identified in the genome. Two repeats located on chromosomes 2 and 12 (no. 4 and no. 35 in
panel D) are depicted. HP1 and SUV39H were enriched at the transcriptionally inactive repeat (no. 4)
that additionally had a high level of the repressive H3K9me3 mark and a low level of the activating
H3K36 trimethylation. At the actively transcribed repeat (no. 35) marked by H3K36me3, binding of
SUV39H and HP1 was at background levels. The height of the histogram is normalized to total
reads.
Enrichment of all mapped sequencing reads to interspersed GSAT regions over input control. The 16
regions that can be uniquely mapped are shown. Error bars correspond to SD.
Composition of the HP1-SUV39H nucleation complex as inferred from the enrichment of stably bound
protein in PCH, protein–protein interaction measurements and ChIP-seq analysis. The
postulated complex comprises a HP1 dimer binding H3K9me3-modified nucleosomes and interacting with a
SUV39H dimer. Binding of SUV39H is further stabilized by methyl-binding proteins (MBPs) that
recognize 5meC and possibly by other interacting factors.
Genome-wide ChIP-seq analysis of HP1, SUV39H, and H3K9me3 enrichment at major satellite
repeats
Fraction of total sequencing reads that mapped to the consensus sequence of major satellite
repeats (gamma satellites, GSAT) after ChIP-seq of HP1β, SUV39H1, or SUV39H2. Mild sonication
conditions were applied in neural progenitor cells (NPCs). The histogram shows the distribution of
the mapped reads along the consensus sequence. Error bars correspond to SD.Same as panel A but for ChIP-seq of H3K9me3 and H3K36me3 and with stronger sonication
conditions.Representative sequencing read distributions at interspersed major satellites that can be
uniquely identified in the genome. Two repeats located on chromosomes 2 and 12 (no. 4 and no. 35 in
panel D) are depicted. HP1 and SUV39H were enriched at the transcriptionally inactive repeat (no. 4)
that additionally had a high level of the repressive H3K9me3 mark and a low level of the activating
H3K36 trimethylation. At the actively transcribed repeat (no. 35) marked by H3K36me3, binding of
SUV39H and HP1 was at background levels. The height of the histogram is normalized to total
reads.Enrichment of all mapped sequencing reads to interspersed GSAT regions over input control. The 16
regions that can be uniquely mapped are shown. Error bars correspond to SD.Composition of the HP1-SUV39H nucleation complex as inferred from the enrichment of stably bound
protein in PCH, protein–protein interaction measurements and ChIP-seq analysis. The
postulated complex comprises a HP1 dimer binding H3K9me3-modified nucleosomes and interacting with a
SUV39H dimer. Binding of SUV39H is further stabilized by methyl-binding proteins (MBPs) that
recognize 5meC and possibly by other interacting factors.
SUV39H methylases remain attached to chromatin during mitosis
Many proteins remain attached to PCH during mitosis (Lewis et al, 1992; Fujita et al, 1999; Bachman et al, 2001;
Craig et al, 2003; Hayakawa et
al, 2003; Easwaran et al, 2004; Kourmouli et al, 2004; Mateescu et al, 2004;
Brero et al, 2005; Fischle et
al, 2005; Hirota et al, 2005; McManus et al, 2006; Schermelleh et al, 2007; Hahn et al, 2013). Thus, the
PCH state might be transmitted through cell division by stably bound bookmarking factors. Since
SUV39H1 also remains bound to chromosomes in metaphase (Melcher et al, 2000), we analyzed its localization in all mitotic phases (Fig
5A). Notably, SUV39H1 remained attached to chromatin through
mitosis. From FRAP experiments on mitotic cells, we found 5 ± 3% of SUV39H1 stably
bound to chromatin (Fig 5B, Supplementary Table S6). Since euchromatin and
PCH cannot be distinguished on mitotic chromosomes, this should be compared to the weighted average
of bound SUV39H1 in PCH and euchromatin of interphase cells (4 ± 1%). Thus, most
SUV39H remained stably bound, suggesting that it serves a bookmarking function for PCH.
Figure 5
Chromatin bookmarking by SUV39H1 during the complete cell cycle
Nuclear distribution of SUV39H1-GFP in living cells during different cell cycle phases.
SUV39H1-GFP remained stably associated to mitotic chromatin (stained with Hoechst 33342) during all
phases of the cell cycle. Scale bars, 10 μm.
FRAP measurements of SUV39H1-GFP bound to condensed chromosomes in mitotic cells. Since
euchromatin and PCH cannot be distinguished on mitotic chromosomes, the immobilized fraction of 5
± 3% was compared to the weighted average of immobile SUV39H1 in PCH and euchromatin
in interphase cells (Supplementary Tables
S2 and S6). Error bars correspond to
SEM.
Chromatin bookmarking by SUV39H1 during the complete cell cycle
Nuclear distribution of SUV39H1-GFP in living cells during different cell cycle phases.
SUV39H1-GFP remained stably associated to mitotic chromatin (stained with Hoechst 33342) during all
phases of the cell cycle. Scale bars, 10 μm.FRAP measurements of SUV39H1-GFP bound to condensed chromosomes in mitotic cells. Since
euchromatin and PCH cannot be distinguished on mitotic chromosomes, the immobilized fraction of 5
± 3% was compared to the weighted average of immobile SUV39H1 in PCH and euchromatin
in interphase cells (Supplementary Tables
S2 and S6). Error bars correspond to
SEM.The cell cycle-dependent chromatin interactions of HP1 and SUV39H1 were further analyzed by FRAP
(Supplementary Table S6). Co-transfection
of RFP-tagged proliferating cell nuclear antigen (PCNA) served as a marker for G1 and S phase and
delocalized HP1 as an indicator for G2 phase. SUV39H1 showed relatively similar chromatin
interaction throughout interphase (Supplementary
Fig S1C, Supplementary Table S6).
All HP1 isoforms had comparable cell cycle-dependent mobility, and HP1α is shown as an
example (Supplementary Table S6). While HP1
exhibited considerable chromatin binding in G1 and S phase consistent with previous findings
(Cheutin et al, 2003; Festenstein et
al, 2003; Schmiedeberg et al, 2004; Dialynas et al, 2007), HP1 mobility could best be described by a diffusion model for both
euchromatin and PCH in G2, indicating significantly reduced chromatin interactions. The immobile
fraction in PCH was reduced to euchromatin values of 3 ± 2%. The remaining fraction of
approximately 3% stably tethered HP1 corresponds to a concentration of 1.2 μM, which
is similar to the amount of immobile SUV39H and SUV4-20H in PCH. In summary, our combined imaging-
and FRAP-based analyses provide evidence that a considerable fraction of SUV39H remains stably bound
to chromatin throughout the cell cycle including all phases of mitosis. Likewise, H3K9me3, HP1,
5meC, MECP2, and MBD1 remained available to enhance SUV39H chromatin interactions. This is
consistent with an inheritance mechanism in which the PCH state is transmitted via chromatin-bound
bookmarking factors.
Stable SUV39H-containing complexes in PCH arise from multiple protein–protein
interactions
Our protein–chromatin and protein–protein interaction data can be rationalized with
a model in which SUV39H and HP1 can bind either separately to weaker affinity binding sites with
ΔGSUV39H and ΔGHP1,
respectively, or to high-affinity sites where both proteins interact with chromatin and are
additionally linked by protein–protein interactions. This interaction could be further
stabilized by MECP2 or MBD1, which themselves display high-affinity PCH binding, or by other
additional factors. The binding free energy ΔGHP1-SUV39H of an
HP1-SUV39H complex to these high-affinity sites can be approximated as
ΔGHP1 + ΔGSUV39H. Based
on our FRAP data (Supplementary Table S2),
dissociation constants and residence times for the individual binding reactions to H3K9
trimethylated nucleosomes are Kd = 19 μM and
τres = 3 s for HP1, and Kd = 4 μM
and τres = 13 s for SUV39H1. Together, these contributions lead to a highly
stable chromatin-bound HP1-SUV39H complex with Kd ≈ 0.07 nM and a
corresponding residence time of several minutes, which is consistent with the immobile fraction in
our FRAP experiments. Based on the limiting concentration measured for immobilized SUV39H (Table
1, Supplementary Table S7), this complex can only be sparsely distributed throughout PCH, that
is the stoichiometry equals one complex per 170 nucleosomes.
Immobilized SUV39H1 is sufficient to form a de novo H3K9me3 domain
The correlation between the highly enriched stably chromatin-bound SUV39H fraction (Fig 1C) and the steady-state H3K9me3 levels (Fig 3C) in PCH prompted us to ask whether these stably bound complexes are
responsible for the deposition of H3K9me3 in PCH. To test if immobilized SUV39H1 is sufficient to
establish a methylated chromatin domain, GFP-SUV39H1 was tethered to the nuclear lamina via a
GFP-binding protein that was fused to Lamin B1 (Rothbauer et al, 2008) in living iMEF Suv39h dn cells.
Subsequently, the localization of H3K9me3 was monitored with an RFP-tagged chromodomain (CD) of HP1
(Fig 6A and B). A quantitative analysis of the averaged
H3K9me3 profile across the lamina revealed de novo H3K9me3 modifications at the
nuclear lamina for wild-type SUV39H1 but not for the inactive SUV39H1-H324L-mutant (Fig 6A and C). Thus, immobilized SUV39H methylates nucleosomes that
are brought into spatial proximity. The slightly increased width of the profile at half maximum for
H3K9me3 (0.47 ± 0.03 μm) versus that of GFP-SUV39H1 (0.40 ± 0.02 μm)
indicated that the newly formed H3K9me3 regions extended for < 0.1 μm into the nuclear
interior. Thus, the trimethylation mark did not spread beyond those chromatin loci that could
transiently interact with tethered SUV39H1 via chromatin dynamics, although free GFP-SUV39H1 was
present in the nucleoplasm as detected by FCS.
Figure 6
Propagation of H3K9me3 by stably tethered SUV39H1 to nucleosomes in its spatial
proximity
Establishment of H3K9me3 domains by GFP-SUV39H1 recruited to the nuclear lamina via GBP-Lamin B1
in iMEF Suv39h dn cells. H3K9me3 was detected via CD-RFP and appeared in a confined
region adjacent to the nuclear lamina (see inset). When the inactive mutant SUV39H1-H324L-GFP was
recruited, no enrichment of CD-RFP was observed. Scale bar, 10 μm.
Cartoon model depicting the experimental setup in panel A.
Averaged radial fluorescence intensity profiles from the lamina to the center of the nucleus
measured for the experiments described in panel A. The profile of CD-RFP reflects the H3K9me3 levels
and was measured in cells transfected with GFP-SUV39H1 (red) or the inactive SUV39H1-H324L-GFP
mutant (blue, control). The recruitment of GFP-SUV39H1 (green) resulted in a lamina-confined
enrichment with a width of 0.40 ± 0.02 μm as determined by fitting the data to an
exponential decay curve. While wild-type SUV39H1 methylated the surrounding chromatin within a
confined area of 0.47 ± 0.03 μm width (red), SUV39H1-H324L (blue) did not increase the
methylation (blue) in this region. Error bars correspond to SEM.
Propagation of H3K9me3 by stably tethered SUV39H1 to nucleosomes in its spatial
proximity
Establishment of H3K9me3 domains by GFP-SUV39H1 recruited to the nuclear lamina via GBP-Lamin B1
in iMEF Suv39h dn cells. H3K9me3 was detected via CD-RFP and appeared in a confined
region adjacent to the nuclear lamina (see inset). When the inactive mutant SUV39H1-H324L-GFP was
recruited, no enrichment of CD-RFP was observed. Scale bar, 10 μm.Cartoon model depicting the experimental setup in panel A.Averaged radial fluorescence intensity profiles from the lamina to the center of the nucleus
measured for the experiments described in panel A. The profile of CD-RFP reflects the H3K9me3 levels
and was measured in cells transfected with GFP-SUV39H1 (red) or the inactive SUV39H1-H324L-GFP
mutant (blue, control). The recruitment of GFP-SUV39H1 (green) resulted in a lamina-confined
enrichment with a width of 0.40 ± 0.02 μm as determined by fitting the data to an
exponential decay curve. While wild-type SUV39H1 methylated the surrounding chromatin within a
confined area of 0.47 ± 0.03 μm width (red), SUV39H1-H324L (blue) did not increase the
methylation (blue) in this region. Error bars correspond to SEM.We conclude that the endogenous propagation of H3K9me3 in PCH can originate from relatively
sparsely distributed immobilized SUV39H complexes that locally extend H3K9me3 to spatially adjacent
sites. The underlying molecular spreading mechanism might be chromatin looping that can efficiently
promote interactions within limited genomic distances of several kilobases or < 100 nm
(Rippe, 2001; Erdel et al, 2013).
The dynamics of protein binding and histone modifications in PCH can be integrated into a
quantitative network model
Based on our experimental observations and data analysis, we developed a quantitative model for
the epigenetic network centered around H3K9me3 in PCH with all parameters compiled in Supplementary Table S7. It is based on stably
bound SUV39H complexes that are specifically tethered to PCH via multiple interactions (Fig 4E). These SUV39H complexes represent nucleation sites that
mediate confined propagation of H3K9me3 via chromatin looping (Rippe, 2001; Erdel et al, 2013)
(Fig 7A). In particular, such a mechanism rationalizes the
experimental findings on the limited extension of H3K9me3 from SUV39H1 bound to the nuclear lamina
(Fig 6) as well as the size of histone methylation domains
that have been found around chromatin-tethered proteins (Erdel et al, 2013).
Figure 7
Quantitative model for H3K9 trimethylation in PCH
Probability of interactions between two nucleosomes due to chromatin looping as expressed by
their local molar concentration jM. Based on the data for chromatin
interactions during recombination in living cells (Ringrose et al, 1999), the dependence of jM on the
separation distance from a SUV39H-bound nucleosome was calculated as described previously (Rippe,
2001; Erdel et al, 2013).
PCH network model scheme. The model includes transitions between the following states according
to the indicated rate constants: “n”, nucleosome without H3K9me3;
“m”, H3K9me3 modified; “o”, origin
that represents a high-affinity binding site for SUV39H. HP1 and SUV39H bound to these sites are
represented by H and S, respectively, to form the states
“Hm”, “Sm”,
“SHm”, “Ho”,
“So”, and “SHo”. All SUV39H-bound
states (red) enhance methylation of adjacent unmodified nucleosomes through chromatin looping. See
text and Supplementary Table S7 for further
details.
Steady-state distribution of methylation levels for a chromatin segment in PCH or euchromatin.
The deterministic and stochastic distributions are depicted in black and red, respectively.
Stochastic solutions were averaged over 5,000 min. The nucleation origins (both occupied and
unoccupied) are marked in gray.
Stochastic simulation for a region of 40 nucleosomes. Same color code for nucleosome states and
origins as in panel B.
Quantitative model for H3K9 trimethylation in PCH
Probability of interactions between two nucleosomes due to chromatin looping as expressed by
their local molar concentration jM. Based on the data for chromatin
interactions during recombination in living cells (Ringrose et al, 1999), the dependence of jM on the
separation distance from a SUV39H-bound nucleosome was calculated as described previously (Rippe,
2001; Erdel et al, 2013).PCH network model scheme. The model includes transitions between the following states according
to the indicated rate constants: “n”, nucleosome without H3K9me3;
“m”, H3K9me3 modified; “o”, origin
that represents a high-affinity binding site for SUV39H. HP1 and SUV39H bound to these sites are
represented by H and S, respectively, to form the states
“Hm”, “Sm”,
“SHm”, “Ho”,
“So”, and “SHo”. All SUV39H-bound
states (red) enhance methylation of adjacent unmodified nucleosomes through chromatin looping. See
text and Supplementary Table S7 for further
details.Steady-state distribution of methylation levels for a chromatin segment in PCH or euchromatin.
The deterministic and stochastic distributions are depicted in black and red, respectively.
Stochastic solutions were averaged over 5,000 min. The nucleation origins (both occupied and
unoccupied) are marked in gray.Stochastic simulation for a region of 40 nucleosomes. Same color code for nucleosome states and
origins as in panel B.Our quantitative model focuses on the signature heterochromatin mark H3K9me3 and its interacting
proteins, HP1 and SUV39H, in an extended chromatin segment (300 nucleosomes or ∼60 kb DNA).
Each nucleosome can either reside in the unmodified state “n” or in
the H3K9 trimethylated state “m” (Fig 7B). Depending on the presence of HP1 (“H”) and
SUV39H (“S”), the chromatin-bound complexes
“Hm”, “Sm”, and
“SHm” can assemble. The PCH-specific high-affinity binding sites for
SUV39H and HP1 are referred to as origins “o”, which can either be
free, occupied by SUV39H (“So”) or HP1
(“Ho”) alone, or by the HP1-SUV39H complex
(“SHo”). According to our experimental data, every 8th
nucleosome in PCH and every 71st nucleosome in euchromatin is an origin (see Supplementary Materials and Methods, Mathematical
modeling of PCH network). Based on the experimentally measured immobile SUV39H fractions and
concentrations, every 21st origin, that is every 170th nucleosome, is in the
SHo state at a given point of time. All parameters used in the modeling and their
sources are given in Supplementary Table
S7.The model quantitatively accounts for the different experimentally observed types of binding
sites for SUV39H1 and HP1 and their occupancy. For the H3K9 trimethylation reaction, we distinguish
different pathways. Freely mobile SUV39H at a concentration cs
methylates nucleosomes with a basal rate km·cs. H3K9
trimethylation by other histone methylases like G9A/SETDB1 is accounted for as an additional
reaction with rate constant ku in PCH and
ke+ku in euchromatin. Finally,
chromatin-bound SUV39H catalyzes H3K9 trimethylation via chromatin looping. The efficiency for
trimethylating H3K9 in a nucleosome at distance b from the SUV39H-bound site
corresponds to
km·jM(b). Here,
jM(b) is the local concentration of the respective
complex in proximity of the target nucleosome (Erdel et al, 2013) (Fig 7A). Importantly, we do not
assume that chromatin-bound SUV39H is intrinsically more active than free SUV39H but that the
decisive factor is the enhanced local concentration of the former.For our model, the association and dissociation rates and the concentrations of free proteins
were taken as determined from the FRAP and FCS experiments (Supplementary Materials and Methods, Supplementary Table S7). To simplify the model, we combined the parameters for
SUV39H1 and SUV39H2 weighted according to their concentrations into a unified SUV39H enzyme (Supplementary Table S7). The rate constant for
H3K9me3 demethylation was fixed to k-m = 0.0013
min−1 according to mass spectrometry experiments in HeLa cells (Zee et
al, 2010). The unspecific methylation rate
ku, the euchromatin-specific rate ke, and
the SUV39H-dependent methylation rate km were fitted to yield the
measured steady-state levels of H3K9me3 in PCH (38%) and euchromatin (28%) of
wild-type cells (Fig 3C). The system was formulated as a set
of deterministic ordinary differential equations (ODEs) to calculate the steady-state probabilities
of each nucleosome to be in a particular state for a given set of conditions and, in parallel,
simulated stochastically (Fig 7C and D; Supplementary Model Code). The model simulations
show that the relatively sparse binding events of SUV39H at the origin sites are sufficient to
account for the increased H3K9me3 levels in PCH compared to euchromatin (Fig 7C and D). At any given nucleosome, the methylation state fluctuates over time
(Fig 7D). However, the time average is consistently
described by the stochastic and deterministic models and yields the observed enrichment of H3K9me3
in PCH over euchromatin as well as the measured occupancies of HP1 and SUV39H. Thus, we conclude
that PCH-specific high-affinity SUV39H/HP1 binding sites can robustly maintain the PCH-specific
H3K9me3 levels via a DNA looping mechanism.
Stochastic simulations reveal that PCH-specific features are robustly maintained for the
experimentally determined parameter range
Several experimental and theoretical studies showed that the epigenetic silencing mechanisms can
be sensitive to stochastic effects either due to the presence of positive feedback loops in
nucleosome modification (Sneppen et al, 2008), long-range nucleosomal interactions (Dodd et al, 2007), the cooperativity in recruitment of histone modifiers
(Sedighi & Sengupta, 2007) or simply due to low
protein concentrations. Accordingly, we evaluated our model with respect to the degree of intrinsic
noise that can cause stochastic focusing effects by conducting Monte Carlo simulations according to
the Gillespie stochastic simulation algorithm. An example for the resulting fluctuations of the
states in which individual nucleosomes are present in PCH or in euchromatin is depicted in Fig 7D. Relatively sparse binding events of SUV39H at the
“o” sites are sufficient to increase H3K9me3 levels compared to
euchromatin. For both the PCH and euchromatin state, we simulated 100 individual time traces up to
5,000 min starting from an initially naive non-modified fiber (Fig 7D). The low variability of H3K9me3 in steady state revealed that the level of intrinsic
noise in our model is very low when averaged over the entire nucleosome chain, with a standard
deviation of approximately 3% from the population-mean for PCH. As expected, the spatial
steady-state distribution of H3K9me3 modifications over the entire chain agreed well with the
deterministic solutions for all conditions (Fig 7C). Thus,
we conclude that the system robustly maintains the PCH-specific H3K9me3 levels.
The cellular response to perturbations of the H3K9me3 state is accurately predicted by the
network model
We systematically investigated the predictions of our model with respect to the response of the
system to perturbations induced by (i) lowering the HP1 concentration, (ii) increasing the H3K9me3
demethylation activity or (iii) changing the concentration of origin sites. First, we evaluated the
distribution of H3K9me3 levels in model simulations for different HP1 concentrations. SUV39H binding
and H3K9me3 levels gradually decreased when lowering the HP1 concentrations, consistent with the
behavior observed in the HP1 knockdown experiments (Fig 8A
and B). Second, we mimicked the increase of H3K9me3 demethylation activity by raising the
corresponding parameter k-m. This resulted in a gradual decrease of
H3K9me3 in PCH, which contradicts the notion of bistable states. To test this behavior of the system
experimentally, we overexpressed JMJD2C, an H3K9me3-specific histone demethylase, to reduce H3K9
trimethylation (Fig 8C). H3K9me3 levels were evaluated in
PCH of single cells on fluorescence microscopy images, normalized to the DAPI signal, and correlated
with the JMJD2C-GFP expression levels. The relation of demethylation rate and H3K9me3 levels
predicted from our model was in good agreement with the experimental data and showed a gradual
decrease of H3K9me3 in PCH with increasing demethylation activity (Fig 8C). Third, we evaluated the dependence of H3K9me3 in PCH on the concentration of
origin sites (Fig 8D). We found an approximately linear
response of the H3K9me3 levels up to the wild-type “o” site
concentration range of approximately 30 μM.
Figure 8
Prediction of PCH features from network model
Dependence of SUV39H enrichment on HP1 concentration in PCH (red) and euchromatin (gray). Model
predictions (black lines) were compared to the experimental values determined in the
triple-knockdown experiments shown in Fig 3.
Same as panel A but for H3K9me3 instead of SUV39H.
Dependence of H3K9me3 levels on the concentration of the H3K9me3 demethylase JMJD2C. Error bars
correspond to SD. The model prediction (solid line) agreed very well with the experimental data
(points) derived from over-expression of JMJD2C-GFP.
Predicted average H3K9me3 levels in PCH versus concentration of the origins.
Stochastic time evolution of H3K9 trimethylation in PCH and euchromatin from a completely
H3K9me3-deficient state. Red and dark gray traces are averages of 100 single stochastic trajectories
with the standard deviation shown in light gray.
Dependence of H3K9me3 in PCH on SUV39H concentration. This parameter varies between different
mouse cell types. For example, in ESCs the combined SUV39H1/2 concentration is 2-fold reduced
compared to NIH-3T3 fibroblasts as estimated from their normalized RNA expression levels.
”Nucleation and looping” model for the propagation of H3K9me3 in PCH. The
high-affinity binding sites with immobilized HP1 and SUV39H represent the SUV39H nucleation complex
(Fig 4E; “SHo” in Fig 7B), which is highly specific for PCH. In contrast, the low-affinity binding
sites composed of single protein factors were found throughout the whole nucleus, that is in both
PCH and euchromatin. While soluble SUV39H proteins can methylate unmodified nucleosomes, the SUV39H
nucleation complex provides a high local concentration of the enzyme and is responsible for the
majority of catalytically productive collisions in PCH. Due to chromatin looping, the
chromatin-bound SUV39H complexes can either methylate adjacent nucleosomes on the same chain or in
3D at other loci that reside in spatial proximity. The persistence of stably chromatin-bound SUV39H
throughout the cell cycle (Fig 5) sustains the H3K9me3
modification.
Prediction of PCH features from network model
Dependence of SUV39H enrichment on HP1 concentration in PCH (red) and euchromatin (gray). Model
predictions (black lines) were compared to the experimental values determined in the
triple-knockdown experiments shown in Fig 3.Same as panel A but for H3K9me3 instead of SUV39H.Dependence of H3K9me3 levels on the concentration of the H3K9me3 demethylase JMJD2C. Error bars
correspond to SD. The model prediction (solid line) agreed very well with the experimental data
(points) derived from over-expression of JMJD2C-GFP.Predicted average H3K9me3 levels in PCH versus concentration of the origins.Stochastic time evolution of H3K9 trimethylation in PCH and euchromatin from a completely
H3K9me3-deficient state. Red and dark gray traces are averages of 100 single stochastic trajectories
with the standard deviation shown in light gray.Dependence of H3K9me3 in PCH on SUV39H concentration. This parameter varies between different
mouse cell types. For example, in ESCs the combined SUV39H1/2 concentration is 2-fold reduced
compared to NIH-3T3 fibroblasts as estimated from their normalized RNA expression levels.”Nucleation and looping” model for the propagation of H3K9me3 in PCH. The
high-affinity binding sites with immobilized HP1 and SUV39H represent the SUV39H nucleation complex
(Fig 4E; “SHo” in Fig 7B), which is highly specific for PCH. In contrast, the low-affinity binding
sites composed of single protein factors were found throughout the whole nucleus, that is in both
PCH and euchromatin. While soluble SUV39H proteins can methylate unmodified nucleosomes, the SUV39H
nucleation complex provides a high local concentration of the enzyme and is responsible for the
majority of catalytically productive collisions in PCH. Due to chromatin looping, the
chromatin-bound SUV39H complexes can either methylate adjacent nucleosomes on the same chain or in
3D at other loci that reside in spatial proximity. The persistence of stably chromatin-bound SUV39H
throughout the cell cycle (Fig 5) sustains the H3K9me3
modification.From simulations of the kinetics of methyl mark propagation in virtual H3K9me3 induction
experiments, we conclude that all transient perturbations on the minute time scale will not affect
the overall PCH H3K9me3 levels due to the slow response of the system (Fig 8E). The simulations were started from the completely unmodified PCH state (e.g.
all nucleosomes in state “n” and “o”
sites at every 8th nucleosome), and the H3K9me3 level was followed over time. The
steady-state PCH level of 38% was reached after approximately 33 h, corresponding to a
propagation rate of 0.35 nucleosomes per hour from a given nucleation site. Notably, these kinetics
are comparable to the value of 0.18 nucleosomes per hour measured experimentally for H3K9me3
propagation at the POU5F1 promoter in mouse fibroblasts when inducing H3K9
trimethylation by tethering HP1α (Hathaway et al, 2012). One key parameter to modulate H3K9me3 levels in PCH is the SUV39H
concentration (Fig 8F), which might vary between cell types.
A 2-fold increase or decrease of the wild-type SUV39H concentration as observed between ESCs and
MEFs would raise or lower H3K9me3 levels in PCH from an average value of 38% to about
51% or 28%, respectively.In summary, we found that the predictions made by our model were in very good agreement with
experiments. We conclude that it introduces an appropriate representation of the available data
reported here and elsewhere that are relevant for the epigenetic network centered on H3K9me3 in
mouse fibroblasts. The model quantitatively describes the properties of euchromatin and PCH
determined here under different conditions and explains how a cell can robustly maintain the PCH
state without the requirement to invoke additional components such as boundary proteins that bind to
chromatin and block linear PCH spreading.
Discussion
Here, we present a comprehensive analysis of the epigenetic network that silences the
transcription of major satellite repeats in mouse fibroblasts. Based on data from advanced
fluorescence microscopy methods and ChIP-seq, we explain how chromatin and protein interactions of
MECP2, MBD1, DNMT1, SUV39H1, SUV39H2, JMJD2B/C, HP1α, HP1β, HP1γ, SUV4-20H1,
and SUV4-20H2 are linked to 5meC, H3K9me3, and H4K20me3 modifications in PCH. From our quantitative
analysis, we derive a predictive mathematical model that provides insight on how the silenced PCH
state in fibroblasts is stably maintained and how it could be transmitted through the cell cycle. As
mentioned above, H3K9me3 levels and transcriptional silencing in PCH vary between cell types (Supplementary Fig S2). The underlying mechanisms
are only partly understood and beyond the scope of the present study. Nevertheless, our modeling
framework provides an approach to evaluate the effect of key parameters. For example, differential
regulation could rely on changing the composition of the nucleation complex (Fig 8B) or SUV39H abundance (Fig 8F). In addition, it is noted that SUV39H activity itself is controlled by posttranslational
modifications like acetylation (Vaquero et al, 2007), methylation (Wang et al, 2013), or phosphorylation (Park et al, 2014), which links it to additional cellular pathways.
Stably bound PCH complexes of SUV39H require the simultaneous presence of DNA methylation,
MECP2, H3K9me3, and HP1
To rationalize our results, we propose that a network of interactions between 5meC, MECP2, MBD1,
SUV39H, H3K9me3, and HP1 is responsible for the stably PCH-bound SUV39H complexes that are immobile
on the time scale of minutes (Fig 4E, Table 1). Additional factors might further stabilize SUV39H as
discussed below. Based on our AUC, FCCS, and F2H experiments, we conclude that most HP1 is present
as a homo- or heterodimer in the cell and interacts with SUV39H1 that is in a monomer–dimer
equilibrium (Fig 2, Supplementary Fig S5). This interaction is needed for stable SUV39H binding and
H3K9 trimethylation in PCH as demonstrated in the triple knockdown of all HP1 isoforms (Fig 3A and B). The link between immobilized HP1 and SUV39H as well as
the H3K9 trimethylation mark was further corroborated by FRAP measurements of HP1 in
Suv39h dn cells, where H3K9me3 reduction and the loss of the binding partner SUV39H
led to a strong increase in HP1 mobility and the loss of immobile HP1 (Supplementary Fig S4C) (Müller et
al, 2009).By quantifying parameters needed for PCH network modeling, our study provides an important
extension of previously published FRAP studies of HP1 (Cheutin et al, 2003; Festenstein et al, 2003; Schmiedeberg et al, 2004; Dialynas et al, 2007). The
concentration of immobilized HP1α/β/γ (1–3 μM, depending on cell
cycle phase) and immobile SUV39H (∼1.4 μM) in PCH measured here is compatible with an
HP1 dimer interacting with a SUV39H dimer. The presence of PCH-bound SUV39H-HP1 complexes is
consistent with our ChIP-seq analysis of SUV39H1, SUV39H2, HP1β, and H3K9me3, which were
enriched at silenced but not at active intergenic/intronic major satellite repeats (Fig 4). These findings are in very good agreement with previous
studies: (i) A SUV39H1 mutant lacking its N-terminal chromodomain (SUV39H1-ΔN89) and thus
being unable to interact with HP1 showed a homogeneous distribution throughout the nucleus and
strongly reduced chromatin interactions in mammalian cell lines (Krouwels et al,
2005). (ii) HP1 dimerization was found to be important for
maintaining H3K9me3 in yeast (Haldar et al, 2011). (iii) In vitro experiments showed that SUV39H1 interacts with HP1 by
binding the molecular surface formed by dimerization of the chromoshadow-domain (Aagaard et
al, 1999; Yamamoto & Sonoda, 2003; Nozawa et al, 2010).Both HP1 and SUV39H1 are able to recognize H3K9me3 (Lachner et al, 2001; Jacobs & Khorasanizadeh, 2002; Jacobs et al, 2004),
and the modification may confer some specificity for PCH binding via local H3K9me3 clusters, since
each of the two chromodomains in an HP1 dimer may bind to one H3K9me2/3 residue (Thiru et
al, 2004). Nevertheless, it is apparent from our
quantification that H3K9me3 alone is not sufficient to stably and specifically tether the HP1-SUV39H
complex to PCH. While high-affinity SUV39H binding was hardly present in euchromatin and the stably
tethered SUV39H pool was enriched approximately 16- to 50-fold in PCH with respect to euchromatin,
H3K9me3 levels were only moderately higher in PCH than in euchromatin (∼1.4-fold). Rather,
our quantitative chromatin interaction analysis suggests that SUV39H is tethered to PCH via
interactions with multiple factors including MECP2, MBD1, and HP1 (Figs 1B, C and 2C, Supplementary Fig S5B). Since MECP2 binding is
linked to 5meC (Nan et al, 1996), 5meC
contributes to SUV39H immobilization. Further, H3K9me3 and 5meC are interrelated as iMEF
Suv39h dn cells showed reduced DNA methylation at major satellite repeats (Lehnertz
et al, 2003; Fuks, 2005) although MECP2 and 5meC colocalized with PCH also in the absence of SUV39H
(Supplementary Fig S2B). Notably, 5meC
enrichment is not sufficient for PCH formation since a subset of intergenic major satellite repeats
displays high 5meC levels but was devoid of SUV39H and transcriptionally active (Fig 4C and D). The above conclusions are supported by a number of
previous findings: (i) Interactions of SUV39H1 with MECP2 have been demonstrated (Lunyak et
al, 2002; Fujita et al, 2003). (ii) Krouwels et al showed that DNA
demethylation increases SUV39H1 mobility and reduces the fraction of immobile SUV39H1, whereas HP1
mobility remained unchanged (Krouwels et al, 2005). This is compatible with our model since only 1–2% of total HP1 were
present in the immobilized HP1-SUV39H complex. (iii) The loss of a DNMT1 complex reduced pericentric
H3K9 methylation levels in humanHeLa cells (Xin et al, 2004). (iv) The knockout of MECP2 in neuronal cells resulted in aberrantly low
levels of H3K9me3 in PCH but not in euchromatin (Thatcher & LaSalle, 2006).We conclude that the stability and specificity of the SUV39H-HP1-MECP2/MBD1 complex in PCH
involves protein–protein interactions between these factors and some contribution from an
increased 5meC level. Nevertheless, it is likely to be enhanced by additional protein factors. Since
the PAX3 and PAX9 transcription factors were not stably bound at PCH (Supplementary Fig S1B and S4B), they are unlikely to play a direct role in
stabilizing the HP1-SUV39H nucleation complex. Rather, PAX proteins might regulate the abundance of
transcripts in PCH that potentially act as a binding platform for downstream factors (Maison
et al, 2011). A number of other factors have
been linked to PCH. For example, it was shown that the Mi-2/NuRD complex, which contains several
interaction partners of SUV39H and HP1, is necessary to maintain the H3K9me3 mark in PCH (Sims
& Wade, 2011). The contribution of such additional
factors that enhance SUV39H binding in addition to MECP2 and/or MBD1 is implicitly considered in our
quantitative model via the use of the experimentally determined enrichment of the SUV39H
high-affinity binding sites in PCH that is independent of their exact molecular composition.
Relatively sparse stably bound SUV39H nucleation complexes are sufficient to propagate
H3K9me3 via chromatin looping
The stably bound SUV39H-HP1-MECP2/MBD1 complex in PCH was present at a concentration of
approximately 1 μM as inferred from the concentrations of its constituting components of 1.4
μM (dimeric HP1 isoforms), 0.7 μM (dimeric SUV39H1 and SUV39H2), 1.4 μM
(MECP2), and 0.2 μM (MBD1), while the nucleosome concentration in PCH was approximately 230
μM (Supplementary Table S7). Thus,
bound SUV39H is sparsely distributed. We propose that the H3K9me3 modification is propagated via
looping of the nucleosome chain to nucleosomes in spatial proximity from these complexes (Figs 6B and 8G). By ectopically
tethering SUV39H1 to the nuclear lamina, we demonstrated experimentally that SUV39H immobilization
indeed leads to the locally confined enrichment of H3K9me3 (Fig 6). Thus, chromatin-bound SUV39H might interact with substrate nucleosomes on the same chain
or from another chromosome in spatial proximity. Our results are fully consistent with the
experimental results from the DamID approach developed by van Steensel et al that
uses adenine methylation by DNA adenine methyltransferase (Dam) as readout for interaction. Both the
extension of adenine methylation from chromatin-tethered Dam (van Steensel & Henikoff, 2000) as well as the extension of this DNA methylation from Dam
tethered to the nuclear lamina (Kind et al, 2013) are in excellent agreement with our mechanism for setting H3K9me3 from SUV39H-bound
sites on chromatin or the nuclear lamina.We would like to emphasize that the propagation of H3K9me3 via the assembly of additional
SUV39H-HP1-MECP2/MBD1 nucleation complexes is inherently limited in 3D without the requirement for
additional insulator proteins: (i) Only sites that also have pre-existing DNA methylation and bound
MECP2/MBD1 in addition to H3K9me3 could lead to nucleation complex assembly. A newly formed H3K9me3
site alone would not be sufficient. (ii) The formation of productive nucleation sites is limited by
the available amount of SUV39H. (iii) The H3K9 trimethylation activity originating from the
nucleation complexes occurs only within the looping distance of chromatin around these complexes.
Typical spreading distances for H3K9me3 limited by the diffusive motion of the chromatin fiber are
5–10 kb, in agreement with other experimental studies discussed elsewhere (Erdel et
al, 2013). (iv) There is no preferred direction for
diffusive motion of chromatin-bound SUV39H molecules and collisions rather occur in three dimensions
with all nucleosomes in spatial proximity that could also be located on a different chromosome. This
provides a straightforward explanation for the spherical shape of chromocenters, which may contain
pericentromeric repeats from more than one chromosome (Probst & Almouzni, 2008).
SUV39H bookmarks PCH during all cell cycle stages
According to our model, the reestablishment of H3K9me3 in PCH at newly assembled and unmodified
histones after replication is mediated by SUV39H that remains bound throughout the cell cycle (Figs
5 and 8G, Supplementary Fig S1C). This process is likely to
involve the SUV39H interaction partners MECP2 and MBD1 that show the same persistent binding
enhanced by 5meC. This link between H3K9me3 and 5meC is in line with the previous report that the
epigenetic inheritance of H3K9me3 involves DNA methylation (Hathaway et al, 2012). Furthermore, a relatively small fraction of HP1 was still
immobilized at PCH during G2 phase in the FRAP experiments, which amounts to a significant
concentration of approximately 1 μM due to the high level of total HP1. This is consistent
with the detection of HP1α/β/γ in a quantitative proteomics analysis of mitotic
chromosomes (Ohta et al, 2010), and the
presence of HP1α and HP1γ at (peri-)centromeric chromatin on metaphase spreads (Nozawa
et al, 2010; Hahn et al,
2013). In addition, SUV39H and HP1 were detected at nascent
chromatin following DNA replication (Alabert et al, 2014). Thus, we conclude that the SUV39H nucleation sites persist during all phases of the
cell cycle. The constitutive presence of the SUV39H enzymes at PCH together with the finding that
SUV39H1 is sufficient to establish de novo H3K9me3 domains when immobilized at the
nuclear lamina (Fig 6) has important mechanistic
implications: It strongly suggests that the PCH-associated SUV39H molecules are responsible for
locally reestablishing the H3K9me3 modification after its dilution during replication (Fig 8G). Thus, immobilized SUV39H molecules might act as bookmarking
factors that stably transmit the PCH state through the cell cycle.
H3K9me3 can robustly be maintained in PCH via the nucleation and looping mechanism
Linking modifications of histone residues to their readout by specific protein domains is an
important aspect of current theoretical models that describe how epigenetic networks establish and
maintain specific chromatin states based on dynamic nucleosome modifications (Dodd et
al, 2007; Angel et al, 2011; Hathaway et al, 2012; Hodges & Crabtree, 2012). These
include positive feedback loops where modified histones (directly or indirectly) recruit enzymes
that catalyze a similar modification on nearby nucleosomes. One class of these models is
characterized by relatively robust bistable chromatin states that can stably co-exist for a certain
set of conditions (Dodd et al, 2007; Angel
et al, 2011). This originates from the
presence of multiple positive feedback loops as well as “long-range” interactions
along the nucleosome chain. To limit the spreading of a distinct modification to chromatin outside
the domain under consideration, the existence of boundary factors is invoked. If H3K9me3 was able to
spread within PCH via such a mechanism, one would have to explain how spreading is confined in 3D
for the 28 ± 1 chromocenters per nucleus with an average volume of 2.69 ± 0.04
μm3 or approximately 6 Mbp of DNA (Cantaloube et al, 2012). Accordingly, the cell would have to maintain a rather
elaborate spherical boundary structure for the 3D confinement of H3K9me3 to PCH, for which there is
no evidence. It is also noted that for H3K27me3, the view that boundary factors like CTCF are
required to limit domain spreading along the nucleosome chain has been challenged by two recent
studies (Schwartz et al, 2012; Van Bortle
et al, 2012). Nevertheless, the
“nucleation and looping” mechanism proposed here would be fully compatible with the
function of insulators as architectural factors that confine the 3D organization of chromatin by
establishing interactions between distant sites that would promote or inhibit long-range contacts
between nucleosomes and chromatin-bound epigenetic modifiers (Ong & Corces, 2014). Furthermore, we measured that H3K9me3 was less than 2-fold
reduced in euchromatin, which suggests that H3K9me3-dependent feedback loops are rather weak. For
strong feedback, it would be difficult to explain why the mark would not spread throughout the rest
of the genome via the same mechanism as in PCH. Finally, we did not find evidence for bistable
H3K9me3 states when perturbing the balance between H3K9me3 methylation and demethylation (Figs 3A, B and 8A–C).
Rather, the H3K9me3 distribution obtained from measurements of single cells in dependence of the HP1
concentration showed a gradual transition from wild-type levels to those measured in
Suv39h dn cells (Fig 3B).Recently, an alternative model derived from experiments in which HP1α was recruited to the
POU5F1 promoter to induce heterochromatin formation and gene repression was
introduced (Hathaway et al, 2012; Hodges
& Crabtree, 2012). The experimentally determined
H3K9me3 domain with smoothly decreasing borders was modeled with a 1D-lattice model for a chain of
257 nucleosomes, in which the modification is propagated by nearest-neighbor interactions from the
nucleation site along the chain. Here, we detected the endogenous equivalent of these ectopic
nucleation sites for high-affinity binding of SUV39H complexes in PCH. However, the constraints on
protein–chromatin interactions and protein concentrations imposed from our experiments were
not compatible with forming stable H3K9me3 domains via linear nearest-neighbor spreading.
Furthermore, it provided insufficient specificity with respect to the presence/absence of the
high-affinity nucleation sites found in PCH versus euchromatin. In contrast, our nucleation and
looping model schematically depicted in Fig 8G was found to
be robust with respect to maintaining the experimentally measured PCH features: (i) It provides an
intrinsic limit for the SUV39H-dependent extension of H3K9me3 within the system. (ii) Stochastic
number fluctuations of cellular factors have little effect (Fig 7C and D). (iii) Perturbations of SUV39H1 binding (Fig 8A), histone demethylation activity (Fig 8C), or the
concentrations of SUV39H high-affinity sites (Fig 8D) change
the H3K9me3 level only gradually and in a reversible manner. (iv) Transient perturbations of the
system in the range of minutes were insignificant, since the H3K9me3 propagation rate is slow with
only 0.35 nucleosomes per hour (Fig 8E).Furthermore, the response of the quantitative model (Fig 7B) toward perturbations was tested experimentally by HP1 knockdown and overexpression of
the histone demethylase JMJD2C. In these experiments, a gradual change of the H3K9me3 level
depending on HP1 (Figs 3A and 8A, B) or JMJD2C (Fig 8C) concentration
was measured, which was reproduced by the model. Likewise, the steady-state methylation level was
not bistable since the looping-mediated propagation rate of H3K9me3 decreases approximately linearly
with the SUV39H occupancy at the nucleation site. This is consistent with the gradual reduction of
GFP expression from the activated POU5F1 promoter observed in MEFs after triggering
HP1 recruitment (Hathaway et al, 2012).
Concluding Remarks
Our findings lead us to propose that in mousefibroblast cells the PCH state is maintained by a
nucleation and looping mechanism, in which the H3K9me3 modifications originate from relatively
sparsely distributed nucleation sites of stably bound SUV39H complexes (Fig 4E). The local extension of the H3K9me3 modification occurs via looping of the
nucleosome chain to mediate methylation of nucleosomes by a chromatin-bound HP1-SUV39H complex in
spatial proximity against an unspecific demethylation activity provided by JMJD2 enzymes (Fig 8G). This mechanism is site-specific and robust toward number
fluctuations of its components. SUV39H–chromatin complexes persisted through the cell cycle
and could act as bookmarking factors for memorizing PCH silencing of transcription (Fig 5). Our model lacks bistable states and it does neither involve
nearest-neighbor feedback loops for linear spreading of H3K9me3 nor the presence of locus-specific
boundary factors to limit such a process. The predicted behavior of the system according to the
nucleation and looping model in response to perturbations was in excellent agreement with the
experimental findings. Additionally, it is well suited to rationalize general features of cellular
systems that establish, maintain, or modulate epigenetic patterns of characteristic domain size
(Erdel et al, 2013). The proposed mechanism
is fully consistent with results of studies on the distribution of H3K9 methylation along the
nucleosome chain upon chromatin-tethering of HP1 (Hathaway et al, 2012) or the yeast homologue of SUV39H (Kagansky et
al, 2009), as well as with the shape of the H3K27me3
domain observed in Arabidopsis that is involved in silencing the floral repressor
FLC (Angel et al, 2011). Thus, its conceptual
features might be relevant for heritable functional chromatin states at other genomic loci.
Materials and Methods
Cell lines
Experiments were conducted with GFP and RFP constructs in the murineNIH-3T3fibroblast cell line
or in immortalized mouse embryonic fibroblasts (iMEF) wild-type and mutant cell lines (Peters
et al, 2001; Schotta et al,
2008; Müller et al, 2009). Autofluorescent proteins were either expressed as stable
(inducible) cell lines or introduced via transient transfection as described in the Supplementary Materials and Methods.
Fluorescence microscopy imaging, FRAP, and FCS
Confocal imaging, FRAP and FCS experiments, and associated data analysis were conducted with a
Leica TCS SP5 or Zeiss LSM 710 confocal laser scanning microscope as described previously
(Müller et al, 2009; Erdel et
al, 2010) and in the Supplementary Materials and Methods.
Immunofluorescence was conducted with primary anti-H3K9me3 (Millipore, Abcam ab8898),
anti-HP1α (Euromedex, 2HP-1H5-AS), anti-HP1β (Euromedex, 1MOD-1A9-AS),
anti-HP1γ (Euromedex, 2MOD-1G6-AS) or anti-H4K20me3 (Abcam, ab9053) antibodies and a
secondary goat anti-rabbit/mouse Alexa 568 antibody or anti-rabbit/mouse Alexa 633 antibody
(Invitrogen, Molecular Probes).Protein enrichments and H3K9 trimethylation levels were measured from high-resolution microscopy
images using the ImageJ software as described in the Supplementary Materials and Methods. FRAP measurements were fitted either to a
diffusion model, a binding model or a reaction-diffusion model that incorporates both diffusion and
binding processes. The data from the model that yielded the best fit was used for further analysis
and modeling (Müller et al, 2009).
Protein interaction analysis by FCCS, F2H, ChIP-seq and AUC
Protein–protein interaction analysis of the soluble nuclear fraction in living cells was
done by FCCS (Erdel et al, 2010), and
interactions of chromatin-bound proteins were measured via a fluorescent two-hybrid assay (F2H) in
the cell nucleus as reported before (Chung et al, 2011). ChIP-seq experiments were conducted as described previously (Teif et
al, 2012); the data produced have been deposited to
the GEO database (accession number GSE58555). Measurements of HP1 association states with
recombinant proteins were performed by analytical ultracentrifugation according to the workflow
given in our previous work (Kepert et al, 2003; Fejes Tóth et al, 2005). Details on all methods and associated data analysis are given in the Supplementary Materials and Methods section.
Network modeling
The model of the epigenetic network was calculated for a chromatin fiber of 300 nucleosomes. Each
nucleosome on the fiber was able to collide with others via chromatin looping following the
collision probability determined by the local concentration of one nucleosome in the proximity of
the others as described previously (Rippe et al, 1995; Rippe, 2001; Erdel et al,
2013). The resulting values for an increased local
concentration of nucleosomes in the proximity of the first nucleosome at the 0-position due to
chromatin looping is shown in Fig 7A with the concentration
of high-affinity binding sites (“origins”) measured as described in the text. The
model consists of a system of ordinary differential equations (ODEs). The core variables
constituting the network (Fig 7B) are the local probability
of methylation and the local probabilities of occupation by HP1, SUV39H, and HP1-SUV39H complex that
depend on time and the position of nucleosomes and nucleation origins on DNA. The model variables,
parameters, and reference values are summarized in Supplementary Table S7. For the euchromatin fiber system, the ODEs lack the nucleation
origins. Stochastic kinetic traces and stochastic steady-state distributions were simulated with the
Gillespie stochastic simulation algorithm (Gillespie, 2007)
implemented in C++. The state of each nucleosome was derived numerically based on the
deterministic formalism implemented in Mathematica 9.0 (Wolfram Research). See Supplementary Materials and Methods for details
on model implementation and fitting.
Authors: Chanchao Lorthongpanich; Lih Feng Cheow; Sathish Balu; Stephen R Quake; Barbara B Knowles; William F Burkholder; Davor Solter; Daniel M Messerschmidt Journal: Science Date: 2013-09-06 Impact factor: 47.728