Abstract
RNA N^6-methyladenosine (m^6A), the most abundant internal modification
of mRNAs, plays key roles in human development and health.
Post-translational methylation of proteins is often critical for the
dynamic regulation of enzymatic activity. However, the role of
methylation of the core methyltransferase METTL3/METTL14 in m^6A
regulation remains elusive. We find by mass spectrometry that METTL14
arginine 255 (R255) is methylated (R255me). Global mRNA m^6A levels are
greatly decreased in METTL14 R255K mutant mouse embryonic stem cells
(mESCs). We further find that R255me greatly enhances the interaction
of METTL3/METTL14 with WTAP and promotes the binding of the complex to
substrate RNA. We show that protein arginine N-methyltransferases 1
(PRMT1) interacts with and methylates METTL14 at R255, and consistent
with this, loss of PRMT1 reduces mRNA m^6A modification globally.
Lastly, we find that loss of R255me preferentially affects endoderm
differentiation in mESCs. Collectively, our findings show that arginine
methylation of METTL14 stabilizes the binding of the m^6A
methyltransferase complex to its substrate RNA, thereby promoting
global m^6A modification and mESC endoderm differentiation. This work
highlights the crosstalk between protein methylation and RNA
methylation in gene expression.
Subject terms: Epigenomics, Methylation, RNA modification, Stem cells
__________________________________________________________________
The methyltransferase complex of METTL3-METTL14-WTAP is responsible for
m^6A modification on RNA. Here the authors report that METTL14 arginine
255 (R255) is methylated by PRMT1 and this modification increases
interaction of METTL3/METTL14 interaction with WTAP and substrate RNA,
promoting m^6A methylation activity of the complex.
Introduction
N^6-methyladenosine (m^6A) is the most abundant mRNA modification in
mammals, and it has been widely explored following the development of
the methylated RNA immunoprecipitation-sequencing (MeRIP-seq)
method^[52]1,[53]2. mRNA m^6A is mostly found in stop codons,
3´untranslated regions (3´UTRs), and long exons that possess a
consensus motif of RRACH (R means G or A, and H means A, C or
U)^[54]1,[55]3. m^6A is a dynamically reversible modification, which is
synergistically regulated by the methyltransferase complex
METTL3-METTL14-WTAP^[56]4 and demethylases FTO and ALKBH5^[57]5–[58]7.
m^6A plays important roles in RNA stability^[59]8,[60]9,
splicing^[61]10,[62]11, translation^[63]9,[64]12, and other cellular
processes^[65]13–[66]16. Dysregulation of m^6A modification has been
shown to result in impairment of stem cell self-renewal or
differentiation^[67]17–[68]22, abnormal developmental
process^[69]6,[70]23–[71]26, and tumorigenesis^[72]27,[73]28 in
animals.
Protein arginine methylation is a key post-translational modification
(PTM) catalyzed in large part by nine protein arginine
methyltransferases (PRMTs)^[74]29. PRMTs are divided into three
categories: type I PRMTs catalyze mono-methylation and asymmetric
di-methylation; type II PRMTs catalyze mono-methylation and symmetric
di-methylation, and type III PRMTs only catalyze
mono-methylation^[75]30,[76]31. PRMT1 is the predominant type I
arginine methyltransferase and is responsible for 85% of arginine
methyltransferase activity in mammals^[77]32,[78]33. Arginine
methylation of proteins can regulate their activities through
modulating their binding interactions^[79]29 with proteins and nucleic
acids, especially RNAs^[80]34–[81]36. It has also been shown to be
involved in biological processes such as gene
transcription^[82]37–[83]39, RNA splicing^[84]40,[85]41, cell
signaling^[86]42, cell fate decision^[87]43,[88]44, and other cellular
processes^[89]37,[90]45. Although phosphorylation of METTL14^[91]46 and
SUMOylation of METTL3^[92]47 have been detected, arginine methylation
of m^6A methyltransferase complex has not been reported. Moreover, the
role of PTMs on the activity of the methyltransferase complex has not
been fully characterized.
Here, we report arginine methylation at position arginine 255 (R255me)
of METTL14, identified using liquid chromatography tandem mass
spectrometry (LC–MS/MS). Methylation of METTL14 at R255 regulates the
activity of the m^6A methyltransferase complex and enhances global RNA
m^6A modification. We show that PRMT1 contributes to R255 methylation,
and loss of R255me affects the endoderm differentiation of mouse
embryonic stem cells (mESCs). This study elucidates a critical role for
arginine methylation in RNA m^6A regulation and mESC differentiation,
suggesting a direct link between protein methylation and RNA
methylation.
Results
METTL14 is methylated at arginine 255
To investigate the methyl-arginine status of METTL14, we generated a
HeLa cell line stably expressing S-Flag-SBP (SFB)-tagged METTL14, which
we confirmed has a similar expression level as endogenous METTL14
(Supplementary Fig. [93]1a). Western blots showed that
immunoprecipitated SFB-METTL14 protein was arginine methylated
(Fig. [94]1a). This methylation was remarkably decreased by treatment
with an arginine methylation inhibitor, periodate oxidized adenosine
(AdOx) (Fig. [95]1a). Arginine methylation of METTL14 was also detected
in E14Tg2a mouse embryonic stem cells (mESCs) (Supplementary
Fig. [96]1b). To determine the methylation sites, SFB-METTL14 was
purified by tandem affinity purification (TAP) (Supplementary
Fig. [97]1c) and subjected to LC–MS/MS. A reported phosphorylation site
at S399^[98]46 was found, suggesting that our approach captured bona
fide protein modifications. We found the R255 site of METTL14 was
mono-methylated (Fig. [99]1b, Supplementary Fig. [100]1d). To confirm
the methylation at R255, we mutated R255 to lysine (R255K), and found
the mono-methylation of immunoprecipitated METTL14 was greatly reduced
(Fig. [101]1c). Alignment of METTL14 proteins from various species
revealed that R255 is conserved from humans to yeast (Supplementary
Fig. [102]1e). Based on the crystal structure of METTL14^[103]48, R255
sits at the interface between METTL3 and METTL14 and is at the surface
of the substrate RNA-binding site (Fig. [104]1d, Protein Data Bank ID
code 5IL1, [10.2210/pdb5IL1/pdb]), indicating that the R255 methylation
of METTL14 may be functionally important.
Fig. 1. METTL14 is methylated at arginine 255.
[105]Fig. 1
[106]Open in a new tab
a Arginine methylation of immunoprecipitated S-Flag-SBP (SFB) tagged
METTL14 protein detected by western blot in HeLa cells. MMA mono-methyl
arginine, ADMA asymmetric dimethyl arginine. The experiment was
performed once in HeLa cells. b Mass spectrometry showing that METTL14
R255 is methylated. The mass of each b ion and y ion are shown. The
mass error of the peptide identification is 0.26326 ppm. c Arginine
mono-methylation of S-Flag-SBP (SFB) tagged METTL14 and METTL14 R255K
proteins analyzed by western blot. Representative figures of three
independent replicates are shown. Source data for (a) and (c) are
provided as a Source Data file. d Crystal structure ribbon diagram
indicating the position of METTL14 R255 in the METTL3 (cyan) and
METTL14 (pink) heterodimer. RNA is shown as a ball-and-stick model in
the middle.
METTL14 R255K decreases mRNA m^6A modification
To investigate the function of METTL14 R255 methylation, we generated a
METTL14 R255K cell line in mESCs using CRISPR-Cas9 (Supplementary
Fig. [107]2a, b). The protein level of METTL14 was not substantially
affected by this amino acid substitution (Fig.[108]2a). Dot blots
showed hypo-methylation of m^6A in mRNA isolated from the R255K cell
line (Fig. [109]2b), and the m^6A/A ratio of mRNA was significantly
reduced in R255K cells compared to wild-type (WT) cells, as assessed by
LC–MS/MS (Fig. [110]2c, Supplementary Fig. [111]2c). Overexpression of
METTL14 rescued this m^6A decrease (Fig. [112]2c, Supplementary
Fig. [113]2d).
Fig. 2. METTL14 R255K decreases mRNA m^6A modification.
[114]Fig. 2
[115]Open in a new tab
a Western blot showing the protein level of METTL14 in WT and METTL14
R255K knock-in mESCs. Representative figures of three blots are shown.
The band intensity of METTL14 relative to GAPDH is shown in the
right-hand panel, and data are mean ± s.d. from three independent
replicates. b Dot blot showing the m^6A mRNA modification levels from
WT and METTL14 R255K mESCs. Methylene blue (MB) was used as a loading
control. The experiment was performed once. c LC–MS/MS quantification
of m^6A abundance in mRNA from WT, R255K, or R255K with METTL14
overexpressed cells. Data are mean ± s.d. of three independent
experiments. Two-sided Student’s t test. d Distribution of m^6A peaks
from WT and METTL14 R255K cells in transcriptomic regions. e Profile of
m^6A distribution on Nedd4 and Zfp36l1 in WT and R255K cell lines.
Shown is normalized density of IP (green or red) versus input (gray).
Values on the left show the range of IP and input density. f MeRIP-qPCR
verifying decreased m^6A peaks on Nedd4, Zfp36l1, Gas2l3, and Trim71.
Enrichment of MeRIP versus input RNA was normalized against Gapdh. Data
are mean ± s.d. from three independent experiments. Two-sided Student’s
t test. g Abundance of m^6A signals around the m^6A peak center. Solid
line, downregulated m^6A peaks in R255K. Dotted line, constitutive m^6A
peaks. h Box plot showing the expression levels of genes with decreased
m^6A abundance in R255K cells, other m^6A modified genes, and non-m^6A
modified genes. The center line indicates median value, and the box and
whiskers represent the interquartile range (IQR) and 1.5 IQR,
respectively. Two-sided Mann–Whitney U test. Source data for (a), (c),
(f), and (h) are provided as a Source Data file.
We then performed MeRIP-seq from WT and METTL14 R255K cells to explore
the genome-wide effect of R255 methylation. Consistent with previous
reports^[116]1,[117]3, m^6A modifications in both WT and R255K cells
mostly occurred in coding regions and 3´UTRs (Fig. [118]2d,
Supplementary Fig. [119]2e) at the consensus motif GG(m^6A)C
(Supplementary Fig. [120]2f). However, global hypo-methylation of m^6A
was seen in the transcriptome in the R255K mutant (Figs. [121]2d, e).
The number of m^6A peaks on RNA decreased from 17,693 m^6A peaks in the
WT cells to 9437 peaks in R255K cell line. MeRIP-qPCR confirmed the
decreased m^6A levels on individual genes in R255K cells
(Fig. [122]2f). 5008 m^6A regions were significantly decreased in the
R255K mutant. These m^6A regions were enriched for an A(G/A)AC motif,
while the constitutive m^6As were enriched for a GGAC motif
(Supplementary Fig.[123]2g). Previous reports suggest that the A(G/A)AC
motif may not be an ideal substrate for METTL14^[124]48. Not
surprisingly, we found that the R255 dependent m^6As are less abundant
(Fig. [125]2g). Lower abundance m^6A peaks are often observed in highly
expressed transcripts^[126]2. Consistent with this, the expression
levels of genes associated with these R255 regulated m^6A regions were
significantly higher than the other genes in WT cells (Fig. [127]2h).
Together, our results indicate that loss of METTL14 R255 methylation
greatly reduces RNA m^6A modification.
PRMT1 physically interacts with and methylates METTL14
Arginine mono-methylation is catalyzed by PRMTs^[128]29,[129]37. To
identify the PRMT responsible for METTL14 R255 methylation, proteins
that interacted with METTL14 were pulled down by TAP and detected using
LC–MS/MS in HeLa cells (Supplementary Fig. [130]3a). METTL3 and WTAP,
two components of the m^6A methyltransferase complex (Fig. [131]3a)
were captured, indicating the pull down assay captured biologically
relevant interacting partners. PRMT1 was found abundantly in the pulled
down protein pools (Fig. [132]3a). The interaction between PRMT1 and
METTL14 was confirmed by co-immunoprecipitation (Co-IP) (Figs. [133]3b,
[134]c, and Supplementary Fig. [135]3b–e). We next sought to determine
the domain mediating the interaction. Three truncated METTL14 fragments
(Fig. [136]3d) with deletion of RGG repeats (aa 396–456), nuclear
localization signals (NLS, aa 1–146), or the methyltransferase domain
(MTD, aa 147–395) were transfected into HeLa cells with PRMT1, and
Co-IP was carried out (Fig. [137]3d). The METTL14 RGG repeats in the
carboxyl terminal were essential for the interaction between METTL14
and PRMT1 (Fig. [138]3e).
Fig. 3. PRMT1 physically interacts with and methylates METTL14.
[139]Fig. 3
[140]Open in a new tab
a List of the five most abundant proteins identified in the tandem
affinity purification (TAP) pull down assay with METTL14 identified by
LC–MS/MS using Mascot search engine in HeLa cells. b–c Co-IP of
endogenous METTL14 (b) and PRMT1 (c) in HeLa cells. d Schematic of
METTL14 truncations. MTD methyltransferase domain, NLS nuclear
localization signal, RGG RGG repeats. e Western blot showing
interactions of PRMT1 and ectopically expressed full-length or
truncated METTL14 in HeLa cells. Representative figures of three
independent replicates are shown. f In vitro methylation of R255me,
R255, and R255K peptides by PRMT1. Representative figures of two
independent replicates are shown. SAM S-Adenosyl-L-Methionine. Source
data for (b), (c), (e) and (f) are provided as a Source Data file.
To further confirm R255 was methylated by PRMT1, we carried out an in
vitro arginine methylation assay. Three types of peptides, R255
mono-methylated, R255 WT, and R255K mutated peptides, were incubated
with PRMT1 protein and methyl donor S-Adenosyl-L-methionine (SAM) and
then blotted on a membrane and detected with a mono-methylation
antibody. We found that R255 WT peptides were methylated by PRMT1,
while R255K peptides were methylated to a lesser extent (Fig. [141]3f).
This residual mono-methylation signal may be due to the presence of
other arginine sites in the peptides. To reduce the background signal
caused by other potential methylated sites, we generated truncated
METTL14 and METTL14 R255K (METTL14-T and R255K-T) and transfected these
constructs into cells to see if PRMT1 could methylate R255. We found
that loss of PRMT1 reduced the mono-methylation of the METTL14-T
construct but had little effect on the R255K-T construct (Supplementary
Fig. [142]3f). Together, these results indicate that PRMT1 interacts
with and methylates METTL14 at R255.
PRMT1 regulates mRNA m^6A modification
Considering that PRMT1 methylated METTL14 R255, we investigated the
relationship between PRMT1 and RNA m^6A modification. We found that
PRMT1 overexpression increased mRNA m^6A in HeLa and mESCs
(Figs. [143]4a, [144]e, and Supplementary Fig. [145]4a), while PRMT1
knockdown decreased m^6A (Fig. [146]4b, Supplementary Fig. [147]4b).
Next, we generated PRMT1 mutant mES cell lines using CRISPR-Cas9
(Supplementary Fig. [148]4c) and confirmed by western blot that the
PRMT1 protein was not detectable in the mutant cells (Supplementary
Fig. [149]4d). LC–MS/MS data showed that the m^6A level of mRNA
decreased in PRMT1 mutant cells (Fig. [150]4c, Supplementary
Fig. [151]4e), an effect that could be rescued by PRMT1 overexpression
(Fig. [152]4c, Supplementary Fig. [153]4f). Accordingly, gene-specific
MeRIP-qPCR showed that the genes whose m^6A level decreased in the
METTL14 R255K cell line also had decreased RNA m^6A levels in PRMT1
mutant cells (Fig. [154]4d). Moreover, overexpression of PRMT1 in R255K
mESCs could not rescue the decreased mRNA m^6A level (Fig. [155]4e).
These results indicate that PRMT1 may regulate RNA m^6A deposition
through METTL14 R255 methylation.
Fig. 4. PRMT1 regulates mRNA m^6A modification.
[156]Fig. 4
[157]Open in a new tab
a m^6A level of mRNA in HeLa cells overexpressing HA-tagged PRMT1 or
GFP control. Data are mean ± s.d. from three independent experiments.
Two-sided Student’s t-test. b m^6A level of mRNA in HeLa cells after
siRNA-mediated knockdown of PRMT1. Data from two independent
experiments are shown. c m^6A level of mRNA in WT, Prmt1^-/-, and PRMT1
overexpressed Prmt1^-/- mESCs. Data are mean ± s.d. from three
independent experiments. Two-sided Student’s t-test. d MeRIP-qPCR
analysis of m^6A peaks on indicated genes in WT and Prmt1^-/- mESCs.
Data are mean ± s.d. from four independent experiments. Two-sided
Student’s t test. e m^6A level of mRNA in WT and METTL14 R255K mESCs
after the over-expression of GFP or PRMT1. Data are mean ± s.d. from
three independent experiments. Two-sided Student’s t-test. Source data
for (a–e) are provided as a Source Data file.
METTL14 R255 methylation stabilizes the methyltransferase complex to its
substrate RNA
The m^6A methyltransferase complex consists of three components: WTAP,
METTL3, and METTL14. METTL3 is the catalytic subunit, METTL14
structurally supports METTL3 and recognizes RNA substrates^[158]48, and
WTAP is required for the recruitment of METTL3-METTL14^[159]49. To
dissect the mechanism giving rise to the decrease in RNA m^6A in the
METTL14 R255K cell line, we looked into the properties of the
methyltransferase complex. The protein level of METTL3 was not changed
in R255K mESCs, whereas the amount of WTAP increased (Fig. [160]5a,
Supplementary Fig. [161]5a). Then we separated the cytoplasmic and
nuclear proteins, and western blots showed that subcellular
localization of these three methyltransferase complex components in the
R255K cell line were comparable to that in WT cells (Fig. [162]5b,
Supplementary Fig. [163]5a). Next, we investigated the stability of the
methyltransferase complex. Compared to WT METTL14, the association
between METTL14 R255K and METTL3 did not change (Figs. [164]5c, [165]d,
Supplementary Fig. [166]5b), but the association between METTL14 R255K
and WTAP greatly decreased (Fig. [167]5d, Supplementary Fig. [168]5b
and c). This suggests the increase of WTAP protein in the R255K cells
may be an attempt to compensate for the decreased interaction between
WTAP with METTL14-METTL3.
Fig. 5. METTL14 R255 methylation stabilizes the methyltransferase complex to
its substrate RNA.
[169]Fig. 5
[170]Open in a new tab
a Western blot of methyltransferase complex components METTL3, METTL14
and WTAP proteins in WT and METTL14 R255K mESCs. Representative figures
of two independent replicates are shown. b Western blot showing the
subcellular location of METTL3, METTL14, and WTAP proteins in WT and
METTL14 R255K mESCs. WCL whole cell lysate, C cytoplasmic fraction, N
nuclear fraction. Representative figures of two independent replicates
are shown. c Co-IP showing the interaction of METTL3 with SFB-tagged
METTL14 or METTL14 R255K in HeLa cells. Representative figures of four
independent replicates are shown. d Co-IP showing the interaction of
MYC-WTAP and METTL3 with SFB tagged METTL14 or METTL14 R255K. The
experiment was performed once in HeLa cells. SFB-GFP served as a
control in (c) and (d). e qPCR showing the binding between METTL14 or
METTL14 R255K and RNA with m^6A downregulated or other m^6A peaks.
Enrichment was normalized against Gapdh. Data are mean ± s.d. from
three independent experiments. Two-sided Student’s t-test. f Western
blot showing METTL14 or METTL14 R255K protein pulled down by ssRNA
probe containing RRACH domains. Representative figures of three
independent replicates are shown. Source data for (a–f) provided as a
Source Data file. g Proposed model showing the mechanism of METTL14
R255 methylation affecting the deposition of m^6A methylation on mRNA.
R255, arginine 255; R255(me), methylated arginine 255.
Given that R255 is positioned near the site of METTL14 RNA binding, we
simulated the binding of METTL14 R255me with RNA substrates using
molecular docking and dynamics simulations. We generated the initial
structure of METTL14 based on the crystal structure of the
METTL3-METTL14 complex (PDB ID 5IL1)^[171]48. The RNA structure of
GGACU was docked onto the RNA binding region of METTL14^[172]48. We
next simulated the molecular dynamics (MD) of RNA with R255
unmethylated or mono-methylated METTL14^[173]50,[174]51. The root mean
square fluctuation (RMSF) of RNA in the R255 methylated complex was
lower than that of the unmethylated complex, suggesting that the
structure of RNA is more stable in the presence of R255me
(Supplementary Fig.[175]6e). We measured the hydrogen bond interaction
and binding energy of RNA with METTL3-METTL14 and found that after R255
mono-methylation, the average number of hydrogen bonds increased from
4.95 to 8.09 (Supplementary Fig. [176]6f), and the binding energy
decreased from −167.478 ± 142.476 kJ/mol to −625.963 ± 169.704 kJ/mol
after 30 ns simulation (Supplementary Fig. [177]6g), indicating the
binding of RNA with METTL3-METTL14 was more stable after R255
mono-methylation. Then we tested if the RNA-binding ability of METTL14
is affected by R255me using RNA
photoactivatable-ribonucleoside-enhanced crosslinking and
immunoprecipitation qPCR. We found that the METTL14 R255K exhibited
reduced RNA-binding ability for transcripts with decreased m^6A
modification in R255K cells (Fig. [178]5e). A pull-down assay was
conducted using a single-stranded RNA probe containing the m^6A motif
RRACH. Less METTL14 R255K protein was pulled down compared with WT
METTL14, suggesting that METTL14 R255K has weaker RNA-binding affinity
(Fig. [179]5f). Moreover, we found that R255me changed the conformation
of the arginine side-chain, leading to a change in the RNA binding
pattern on the protein surface (Supplementary Fig.[180] 6h). The 5′
phosphate group of RNA turned from His401 to R471 after R255
mono-methylation (Supplementary Fig. [181]6i).
To determine whether PRMT1 affects the binding of METTL14 with METTL3
and WTAP, we knocked down PRMT1 in HeLa cells and found that the
binding between METTL14 and WTAP was weaker, while the binding between
METTL14 and METTL3 was relatively unaffected (Supplementary
Fig. [182]5d). The changes of the binding between METTL14 and
METTL3/WTAP in PRMT1 overexpression cells were not detected
(Supplementary Fig. [183]5e). Altogether, these results show that
METTL14 R255 methylation stabilizes the methyltransferase complex and
enhances the RNA binding ability of METTL14 (Fig. [184]5g).
Methylation of METTL14 at arginine 255 is required for normal mESC endoderm
differentiation
Loss of METTL14 leads to a lack of m^6A modification and impairment of
self-renewal in mESCs^[185]17,[186]19,[187]52. To understand the
biological importance of METTL14 methylation at R255, we first
characterized R255K mESCs. Compared with WT cells, the R255K cell
colonies were flattened and did not exhibit the typical dome shape
(Supplementary Fig. [188]7a). Additionally, the mutant cells displayed
less alkaline phosphatase (AP) positive colonies (Supplementary
Fig. [189]7b), although the proliferation rate of R255K cells resembled
WT cells (Supplementary Fig. [190]7c). The expression of pluripotency
genes was slightly decreased in R255K cells, but the mESCs were still
pluripotent with high expression of pluripotency genes and low
expression of differentiation-specific genes (Supplementary
Fig. [191]7d).
Since the loss of METTL14 methylation at R255 greatly reduced the m^6A
level on RNA, we clustered the genes associated with downregulated m^6A
in R255K cells according to their involvement in various biological
processes and found that they were enriched for signaling pathways
regulating pluripotency of stem cells and TGF-beta signaling pathways
(Fig. [192]6a). We, therefore, checked the differentiation capacity of
R255K mESCs through an in vitro embryoid body (EB) differentiation
assay using a suspension culture system in the absence of leukemia
inhibitory factor (LIF). Unlike the rounded spheres WT mESCs generated,
the EBs of R255K mESCs were irregular at day 6 (Supplementary
Fig. [193]7e). As differentiation progressed, ectoderm and mesoderm
markers showed similar increases in R255K and WT cells. However, there
was substantially less of an increase of endoderm markers in R255K
cells relative to WT cells (Fig. [194]6b). When we directed the mESC to
definitive endoderm fates using activin A and bFGF, the differentiation
of R255K cells was hindered (Fig. [195]6c), indicating that loss of
R255me impacts endoderm differentiation.
Fig. 6. Methylation of METTL14 at arginine 255 is required for normal mESC
endoderm differentiation.
[196]Fig. 6
[197]Open in a new tab
a KEGG pathway enrichment analysis of genes associated with
downregulated m^6A regions in R255K cells. One-sided hypergeometric
test, P value was adjusted by Benjamini and Hochberg method. b
Quantitative RT-PCR analysis of differentiation markers of ectoderm,
mesoderm, and endoderm in WT and R255K mESCs. The expression level was
normalized against Gapdh then to WT at day 0. Data from three
independent experiments are shown. c Quantitative RT-PCR analysis of
markers after directed differentiation to definitive endoderm fate
using FGF2 and activin A in WT or R255K mESCs. The expression of genes
was first normalized to Gapdh then to that in undifferentiated mESCs.
Data are mean ± s.d. from three independent experiments. Two-sided
Student’s t-test. d MeRIP-qPCR of m^6A peaks on Klf4, Smad6, and Smad7.
Enrichment of MeRIP versus input RNA was normalized against Gapdh. Data
are mean ± s.d. from three independent experiments. Two-sided Student’s
t-test. e The stability of Klf4, Smad6, and Smad7 RNAs in WT and R255K
cells after Actinomycin D treatment. The expression level was
normalized against Gapdh then to WT at 0 h. Data from three independent
experiments are shown. Source data for (b–e) are provided as a Source
Data file.
To obtain a full picture of R255 target genes that are important for
mESC self-renewal or differentiation, we first assessed global RNA
expression in WT and R255K mESCs using RNA-seq. We found that the
expression level of most genes with R255 regulated m^6A peaks was not
substantially changed (Supplementary Fig. [198]7f). For those genes
that were differentially expressed, we determined they were not
enriched in self-renewal or differentiation related processes
(Supplementary Table [199]4). Given that m^6A can promote or inhibit
targeted RNA degradation^[200]8,[201]9, we measured mRNA stability
using RNA-seq after transcription inhibition with Actinomycin-D in WT
and R255K mESCs. We found that over 67.8% of R255 targeted genes
degraded slower in R255K cells than they did in WT cells (fold change
of half-life >1.5, Supplementary Fig. [202]7g). Among these genes are
Smad6/7, known antagonists of activin-Nodal-TGFβ signaling^[203]53, and
Klf4, an endoderm differentiation inhibitor^[204]54. We further
confirmed that the m^6A level of these genes was decreased
(Fig. [205]6d, Supplementary Fig. [206]7h), and the transcripts of
these genes were more stable in R255K cells (Fig. [207]6e). We
hypothesized that the prolonged lifetime of these genes and the network
they regulated participated in the differentiation of R255K cells.
These results suggest that loss of METTL14 R255 methylation affects the
normal transition of cell fates in mESCs, especially during endoderm
differentiation, which may underlie the importance of R255 methylation
for normal mESC development.
Discussion
RNA m^6A modification has been widely appreciated as an important
post-transcriptional modification, but its dynamic regulation is
largely unstudied. In this study, we identified a post-translational
modification of the m^6A writer complex component METTL14, namely
methylation by PRMT1 at R255. This modification promotes global m^6A
modification and endoderm differentiation in mESCs.
Two methyltransferases, METTL3 and METTL14, form the core catalytic
complex^[208]48 that is accompanied by additional subunits such as
WTAP^[209]49. Structural studies have shown that METTL14 serves as an
RNA-binding platform but does not catalyze methyl-group
transfer^[210]48. Here, we show that arginine methylation of METTL14
promotes the binding of METTL14 to its RNA substrates. These results
suggest an expanded role for METTL14 as a versatile and flexible
scaffold to regulate interactions between the methyltransferase complex
and substrate RNA. Recent studies showed that METTL14 directly binds to
H3K36me3 to recruit the methyltransferase complex to mRNA 3′
UTRs^[211]16. It will be interesting to explore whether arginine
methylation of METTL14 is also involved in this process.
Arginine methylation functions in gene expression and various
biological processes^[212]29,[213]37. For example, fragile X mental
retardation protein (FMRP) is methylated by PRMT1 to modulate the RNA
binding activity of FMRP^[214]34,[215]55. The arginine methylation of
HuD affected its RNA binding ability and reduces the half-life of bound
RNAs^[216]56. Here, we show that PRMT1 methylates METTL14 at R255 to
stabilize the m^6A methyltransferase/RNA complex. This finding is
consistent with the conventional role of arginine methylation in
regulating nucleic acid interactions^[217]34,[218]36,[219]56.
Considering that PRMT1 knockdown has only a mild effect on global m^6A
methylation levels, we infer that other members of the PRMT family may
be redundantly involved in METTL14 methylation. In the future, it will
be interesting to determine context-dependent PRMT methyltransferases
for METTL14 methylation in development and disease.
In summary, our findings demonstrate how arginine methylation fine
tunes the regulation of m^6A methyltransferase activity and uncover a
specific role for it in mESC endoderm differentiation, suggesting a
crosstalk between protein methylation and RNA methylation in gene
expression.
Methods
Cell cultures
E14Tg2a (National Collection of Authenticated Cell Cultures) and CGR8
(from Dr. Shoujun Huang) murine embryonic stem cells (mESCs) were
cultured in high-glucose DMEM (Invitrogen) supplemented with 15% fetal
bovine serum (FBS, Biological Industries), 1% non-essential amino acid
(Invitrogen), 1 mM glutamine (Invitrogen), 0.15 mM 1-thioglycerol
(Sigma-Aldrich), 100 U/mL Penicillin/Streptomycin (Invitrogen), and
1000 U/mL LIF (Millipore) at 37 °C with 5% CO[2]. Cells were maintained
in plates coated with 0.2% gelatin.
The human HeLa (from Dr. Qinmiao Sun) and HEK293T (National Collection
of Authenticated Cell Cultures) cell lines were grown in DMEM media
supplemented with 10% FBS (Biological Industries), 100 U/mL penicillin,
and 100 U/mL streptomycin (Invitrogen), at 37 °C with an atmosphere of
5% CO2 and 95% humidity.
For EB differentiation, mESCs were cultivated in low-attachment dishes
at a density of 1 × 10^5/mL in the presence of complete medium without
LIF. EBs were collected at the indicated time points for further
experiments.
Definitive endoderm differentiation of mESCs was carried out as
described^[220]57–[221]59. mESCs were hung at a concentration of 1000
cells per 20 μl drop in Dulbecco’s Modified Eagle Medium containing
Nutrient Mixture F-12 (DMEM/F12 1:1), 20% fetal bovine serum for stem
cell, NEAA (Gibco), Glutamine (Gibco), and 100 μM 1-Thioglycerol
(Sigma). 100 drops were plated per dish. After 4 days of growth, the
cells were transferred to a gelatin-coated plate to adhere. 50 ng/ml
activin A (R&D) and 5 ng/ml bFGF (R&D) were then used to induce the
endoderm differentiation for 48 h.
Stable cell line generation
Coding regions of METTL14, METTL14 R255K, PRMT1, or GFP were cloned
into pcDNA4-TRE-SFB vector^[222]60 and transfected into HeLa cells with
pEF-IRES-rtTA plasmids using PEI (Polyscience). 36 h later, 10 μg/mL
puromycin (ThermoFisher) and 100 μg/mL zeocin (ThermoFisher) were added
to the medium and selected for 24–48 h. Resistant cells were plated at
low density, and single colonies were isolated. The protein expression
was confirmed by western blot.
siRNA KD of proteins
siRNAs were synthesized by RiboBio (Guangzhou) and transfected into
HeLa cells using Lipofectamine 2000 Transfection Reagent
(ThermoFisher). 48 h later, cells were collected for RT-qPCR, WB or
LC–MS/MS. The siRNA sequences are listed in supplementary table [223]1.
Virus packaging and infection
pLVX vectors containing GFP and PRMT1 CDS were transfected into 293 T
cells with pIRES-rtTA, pMD2.G and psPAX2. Viruses were collected after
48–72 h, concentrated, and used to infect mESCs along with polybrene
(8 mg/mL, Sigma). 48 h after infection, blasticidin and G418 were added
to the culture medium to select for the infected cells. The surviving
cells were collected for WB and LC–MS/MS.
Generation of knock-in and knockout cell lines
Knock-in cell lines were generated using CRISPR-Cas9
techniques^[224]61,[225]62. sgRNAs recognizing genomic regions near the
arginine 255 site were designed on [226]http://crispr-era.stanford.edu/
and cloned into the pXPR_001 plasmid. Donor vectors were generated by
integrating the PCR product of METTL14 genomic regions around R255
sites into a pUC19 vector, and the AGA at amino acid 255 was mutated to
AAA to generate the R255K mutation (Supplementary Table [227]2). Donor
and pXPR_001 were transfected by electroporation into mES cells using a
Neo kit (Gibco). After 48 h, 2 μg/mL puromycin (ThermoFisher) was
added, and resistent cells were plated for single colony isolation.
Colonies with the desired mutation were identified by restriction
enzyme digest and Sanger sequencing.
For knockout cell line generation, pXPR001-sgRNA (Supplementary
Table [228]3) was transfected and selected as above. Colonies were
identified by Sanger sequencing.
Inhibitor treatment
Adenosine, periodate oxidized (AdOx, Sigma) was dissolved in dimethyl
sulfoxide (DMSO). A HeLa SFB-METTL14 stable cell line was treated with
30 μM AdOx and DMSO for 36 h before pulldown assays with S-protein
agarose beads (Novagen). Arginine methylation was determined by western
blot.
Alkaline Phosphatase staining and quantification
mESC colonies were fixed with 4% paraformaldehyde and processed using
BCIP/NBT Alkaline Phosphatase Color Development Kit following the
manufacturer’s instructions (Beyotime). An Alkaline Phosphatase Assay
Kit (Beyotime) was used to quantify ALP. A Microplate Reader was used
to measure the OD at 405 nm.
Cell proliferation assays
For analysis of ESC self-renewal, mESCs (20,000 per well) were seeded
in 12-well plates, and on days 1–5, cells were collected and counted.
Alkaline phosphatase staining was performed with a BCIP/NBT Alkaline
Phosphatase Color Development Kit (Beyotime) following the
manufacturer’s instructions.
Tandem affinity purification (TAP) of S-Flag-SBP-tagged proteins
For identification of METTL14 PTMs, HeLa cells stably expressing
SFB-METTL14 were lysed in buffer (20 mM Tris-Cl at pH 7.4, 150 mM NaCl,
1 mM EDTA, 1 mM EGTA, 1% NP-40, 0.5% sodium deoxycholate, 0.1% SDS, and
protease inhibitor (Sigma)) for 30 min at 4 °C. Crude lysates were
treated for 40 sec with a sonicator (SCIENTZ, 10% power, 5 sec on/
5 sec off), and the debris was removed. The cell lysates were incubated
with streptavidin Sepharose beads (GE Healthcare,) for 2 h at 4 °C, and
bead-bound proteins were eluted with 1 mg/mL biotin (Sigma). Eluates
were further subjected to S protein beads immunoprecipitation
(Novagen), and bound proteins were subjected to SDS-PAGE and visualized
by Coomassie blue staining (Tiangen). Protein bands were excised and
subjected to LC–MS/MS analysis.
For the identification of METTL14 interacting proteins, the TAP
procedure was performed as above, except for the buffer components
(25 mM Tris-Cl pH 7.4, 150 mM NaCl, 0.5% TritonX-100, and 10%
glycerol).
LC–MS/MS analysis of protein
The LC–MS/MS was carried out as described^[229]63 (PTM biolab). Gel
pieces were destained, dehydrated with 100% acetonitrile, and
rehydrated by incubating with dithiothreitol. After a secondary
dehydration, samples were incubated in 55 mM iodoacetamide for 45 min
protected from light. Gel pieces were washed with NH[4]HCO[3],
dehydrated, and then digested with trypsin at 37 °C overnight.
Peptides were extracted, dried, and dissolved in solvent A (0.1% formic
acid, 2% acetonitrile in water), and then loaded onto a reversed-phase
analytical column packed in-house (15-cm length, 75 μm i.d.) and run on
an EASY-nLC 1000 UPLC system at a constant flow rate of 800 nL/min. The
gradient started from 6% to 25% solvent B (0.1% formic acid in 90%
acetonitrile) in 16 min, then by a 6 min gradient from 25% to 40%, and
finally climbing to 80% in 4 min, then holding at 80% for 4 min. The
peptides were then subjected to nanospray ionization (NSI)
(ThermoFisher) and analyzed by tandem mass spectrometry (MS/MS) using
an Orbitrap Q Exactive Plus tandem mass spectrometer (ThermoFisher)
coupled online to the UPLC. For the full MS scan, the range was set to
350–1800 m/z. Intact peptides were detected at a resolution of 70,000
in the Orbitrap. Peptides were selected for MS/MS using normalized
collision energy (NCE) setting of 28. The ion fragments were detected
at a resolution of 17,500 in the Orbitrap. A data-dependent procedure
which alternated between one MS scan and 20 MS/MS scans was applied
with 15.0 s dynamic exclusion. The electrospray voltage applied was
2.0 kV. Automatic gain control (AGC) was set at 5E4. The intensity
threshold was set to 5E3, and the maximum injection time was 200 ms.
The MS/MS data were processed using Proteome Discoverer 1.3. Tandem
mass spectra were searched using Mascot search engines (v2.3.0) in
Proteome Discoverer against METTL14 protein sequence database.
Trypsin/P was set as the cleavage enzyme, and up to two missing
cleavages in phosphorylation and up to four missing cleavages in
methylation detection were allowed. Mass error of precursor ions was
set to 10 ppm and fragment ions were set to 0.02 Da. Carbamidomethyl on
Cys was specified as a fixed modification, and phosphorylation on Ser,
Thr, and Tyr, mono-methylation and di-methylation on Arg, oxidation on
Met, and N-terminal acetylation were specified as variable
modifications. To increase the confidence of identification, peptide
confidence was set as high, and peptide ion score was set to >20.
For the identification of METTL14 interacting proteins, the tryptic
peptides were dissolved in solvent A and loaded onto an Acclaim PepMap
RSLC C18 column (15 cm length, 75 μm i. d.). The gradient was composed
of an increase from 5% to 90% solvent B (0.1% formic acid in 80%
acetonitrile) over 60 min at a constant flow rate of 300 nL/min on an
LC-20AD (Shimadzu) and a Dionex Ultimate 3000 RSLCnano system
(ThermoFisher). The peptides were then subjected to nanospray
ionization (NSI) (ThermoFisher) and analyzed by tandem mass
spectrometry (MS/MS) using an Orbitrap Q Exactive tandem mass
spectrometer (ThermoFisher). Peptides were then selected for MS/MS
using Normalized Collision Energy (NCE) setting of 27. Automatic gain
control (AGC) was set at 1E5. The maximum IT for MS1 and MS2 were set
to 40 ms and 60 ms. The MS/MS data were processed using Proteome
Discoverer 1.3. Tandem mass spectra were searched using Mascot search
engines (v2.3.0) in Proteome Discoverer. Mass error of precursor ions
was set to 20 ppm, and fragment ions was set to 0.6 Da. Carbamidomethyl
on Cys was specified as a fixed modification, and oxidation was
specified as a variable modification. The significance threshold was
set to 0.05.
Western blots
For NIR western blot, the secondary antibodies Dylight 800 Goat
Anti-Rabbit IgG (1:10000, A23920, Abbkine), Dylight 800, and Goat
Anti-Mouse IgG (1:10000, A23910, Abbkine) were used. Membranes were
scanned using an Odyssey Clx Imager (LI-COR) and quantified using Image
Studio 5.2 (LI-COR). The uncropped blots for all western blots were
provided in the Source Data file.
RNA pulldown assays
Flag tagged METTL14 and METTL14 R255K transfected HeLa cells were
collected using a precooled cell scraper and lysis buffer (10 mM
Tris-HCl, pH 7.4, 1 mM EDTA, 0.2% Tween, 150 mM NaCl, protease
inhibitor, and Rnase inhibitor (Promega)) for 30 min at 4 °C. Cells
were briefly sonicated, and the debris was removed at 13,523 g for
10 min at 4 °C. RNA probes containing an m^6A motif
(5´biotin-GGACCRRACHGGUCCCCACGCGUCGRRACHCGA) (Takara) were incubated
with MyOne Streptavidin C1 beads (ThermoFisher) for 15 min at room
temperature, and redundant probes were abandoned. Cell supernatants
were incubated with probe-beads complex for 2 h at 4 °C. Nonspecific
binding was removed by washing with lysis buffer and 10 mM Tris-HCl, pH
7.4, 0.1% NP-40, and 150 mM NaCl. Pulldown proteins were eluted with 2x
protein loading buffer for 10 min at 98 °C and detected by western
blot.
RT-qPCR
Total RNA or immunoprecipitated RNA was reverse transcribed by a
Promega GoScript Reverse Transcription System A500. The resulting cDNA
was used for real-time quantitative polymerase chain reaction (qPCR)
with a Roche LightCycler 96. Primers are listed in Supplementary
Table [230]2. Data were analyzed using the 2^−ΔΔCt method.
Cell fractionation and immunoblotting
In total, 1 × 10^7 cells were collected and suspended in 800 μL
1 × cell lysis buffer (10 mM Tris pH 7.4, 10 mM NaCl, and 0.5% NP-40)
freshly supplemented with protease inhibitor cocktail and PhosSTOP
Tablets (Roche). Cells were incubated for 10 min at 4 °C. Nuclei were
recovered after centrifugation at 376 g for 10 min at 4 °C.
Supernatants had cytoplasmic components. Nuclei were washed three times
with PBS. Nuclear and cytoplasmic proteins were denatured by 5X protein
loading buffer (1 M Tris-Cl pH 6.8, 10% SDS, 50% glycerol, 10 mM DTT,
and 0.5% bromophenol blue) for 10 min at 98 °C, and then subjected to
western blot analysis. Primary antibodies used were as follows: mouse
anti-WTAP (1:1000, Proteintech, 60188-1-Ig), rabbit anti-WTAP (1:1000,
Abcam, ab195380 ([231]EPR18744)), rabbit anti-METTL3 (1:3000, Bethyl,
A301-567A), rabbit anti-METTL14 (1:1000, Sigma, HPA038002), rabbit
anti-PRMT1 (1:1000, CST, 2449 (A33)), mouse anti-mono and dimethyl
arginine (1:1000, Abcam, ab412), rabbit anti-mono-methyl arginine
(1:1000, CST, 8015 S), rabbit anti-GAPDH (1:10000, Proteintech,
60004-1-Ig), mouse anti-flag (1:3000, MBL, M185-3L), mouse anti-MYC
(1:1000, MBL, M192-3), and mouse anti-HA (1:3000, MBL, M180-3).
Secondary antibodies used were as follows: anti-mouse (1:5000, KPL,
5220-0341), anti-rabbit (1:5000, KPL, 5220-0336), and VeriBlot for IP
Detection Reagent (HRP) (1:200, Abcam, ab131366).
Co-immunoprecipitation
HeLa cells were collected by cell scraping and 211 g centrifugation for
2 min. Supernatants were discarded, and sediment was lysed in IP buffer
(25 mM Tris, 150 mM NaCl, 1 mM EDTA, 5% glycerol, 1% Triton X-100, 1 mM
PMSF, 1 mM DTT, protease inhibitor cocktail, and PhosSTOP Tablets) at
4 °C for 30 min to 1 h. Debris was removed at 18,407 g for 10 min, and
supernatants were supplemented with equal amounts IP buffer without
TritonX-100. Appropriate amounts of METTL14 (1:50, Sigma, HPA038002)
antibody, PRMT1 (1:50, CST, 2449 (A33)) antibody, and control rabbit
IgG (1:100, Santa, SC-2027) were incubated with supernatants and
enriched with Dynabeads Protein G (A1) (Invitrogen, 10004D) for 3 h at
4 °C. Nonspecific binding was removed by washing with IP buffer three
times, and bead-bound proteins were eluted with 5× protein loading
buffer for 10 min at 98 °C for SDS-PAGE for target protein detection.
Co-IP in HeLa SFB-tagged METTL14/PRMT1 stable cell line was conducted
using S-protein beads.
In vitro arginine methylation assays
In total, 0.5 µg peptides (R255 mono-methylated (RVCLRKWGYRR(Met)CED),
R255 WT (RVCLRKWGYRRCED), and R255K mutation (RVCLRKWGYRKCED)) were
incubated with 0 µg (−) or 0.1 µg (+) PRMT1 in 20µL reaction systems
containing 50 mM Tris-HCl pH 8.6, 2 mM MgCl2, 1 mM TCEP (ThermoFisher,
20490), 0.02% Triton X-100, and 25 µM SAM for 3 h at room temperature.
Dot blots were conducted in metal baths at 37 °C, and crosslinking was
performed for 1 h at 37 °C. Arginine methylation signals of products
were detected by WB using anti-mono-methyl arginine (CST, 8015 S)
antibody.
m^6A dot blots
Total RNA was extracted with TRNZOL (TIANGEN), and mRNA was purified
twice with Dynabeads mRNA purification kits (ThermoFisher, cat#61006).
Purified polyadenylated RNAs were denatured and spotted onto Amersham
Hybond-N+ membranes (GE Healthcare) several times. After UV
crosslinking at 2000 mJ/cm^2, unbound RNA was washed away with PBST
buffer (0.05% Tween-20). After blocking with PBSTA buffer (0.05%
Tween-20, 3% BSA) for 1 h, membranes were incubated with m^6A antibody
(1:3000, Synaptic Systems, 202003) overnight at 4 °C. After incubating
with anti-rabbit IgG-HRP (1:5000, KPL, 5220-0336) in PBSTA (0.05%
Tween-20, 3% BSA) for 2 h at room temperature, m^6A signals were
captured by Sage SmartChemi610. Membranes were immersed in methylene
blue (MB) for normalization of spotted RNAs.
Quantification of RNA m^6A by LC–MS/MS
Purified mRNA (200 ng–1 μg) was digested to nucleosides with 0.5 U
nuclease P1 (Sigma, N8630) in 20 μL buffer containing 10 mM ammonium
acetate, pH 5.3 for 6 h at 42 °C followed by addition of 2.5 μL 0.5 M
MES buffer, pH 6.5, and 0.5 U CIAP (Takara, 2250 A) for 6 h at 37 °C.
Mixtures were diluted to 60 μL, filtered and injected to An Agilent
Poroshell 120 column coupled online to AB SCIEX Triple Quad 5500 LC
mass spectrometer (Applied Biosystems) in positive electrospray
ionization mode for LC–MS/MS analysis^[232]64. Concentrations of m^6A
were determined based on standard curves from pure nucleoside
standards, and m^6A/A ratios were calculated by concentration.
Photoactivatable-ribonucleoside-enhanced crosslinking and immunoprecipitation
qPCR
Photoactivatable-ribonucleoside-enhanced crosslinking and
immunoprecipitation was carried out as reported^[233]10,[234]65.
Briefly, mESCs stably transfected with SFB-METTL14 or SFB-METTL14 R255K
were cultured with 100 µM 4SU (Aladdin) and 6 µg/ml doxycycline for
16 h. Cells were washed with PBS twice and crosslinked for 400 mJ/cm^2
under 365 nm UV light on ice. Cells were then collected, lysed with
50 mM Tris-HCl pH7.5, 100 mM NaCl, 2 mM EDTA, and 0.5% NP-40
supplemented with RNase Inhibitor and Protease Inhibitor Cocktail for
30 min and briefly sonicated. Then the lysates were centrifuged and the
supernatants were collected. 1 U/μL RNaseT1 (ThermoFisher) was used to
fragment RNA at room temperature for 8 min. In total, 20 µL flag beads
(Genscript) was then used to bind SFB tagged proteins for 2 h at 4 °C.
Beads were washed with high salt buffer once and low salt buffer twice.
Finally, beads were incubated in 200 μl buffer containing 0.2 mg/ml
Proteinase K at 56 °C for 15 min. The supernatant was collected, and
the RNA was extracted by the TRNZOL Reagent (Tiangen). Then RT qPCR was
performed.
Molecular simulation
To study the binding between METTL14 R255me and RNA substrates,
molecular docking and molecular dynamics (MD) simulations were carried
out (Modekeji). The initial structure of METTL14 was generated based on
the reported crystal structure of METTL3-METTL14 complex (PDB ID
5IL1)^[235]48. To optimize the initial RNA structure, the RNA structure
of GGACU was equilibrated in a box of water and ions and run to 20 ns
for simulation^[236]50. RNA was docked into the RNA binding region of
the METTL3-METTL14 complex^[237]48 using HDOCK for semi-flexible
docking^[238]66. The structure with top docking score (−210.90) was
selected for further analysis.
MD simulation of the METTL14-RNA complex was carried out using
YASARA^[239]51,[240]67. The hydrogen-bonding network was optimized, and
pKa prediction within YASARA based on the electrostatic potential,
hydrogen bonds, and accessible surface area^[241]68 was conducted to
fine-tune the residues’ protonation states at pH 7.4. 0.1538 mol/L NaCl
ions were added. The unmethylated and methylated simulated system
contains a total of 55599 and 55601 atoms, respectively. To remove
clashes, steepest descent and simulated annealing minimizations were
carried out. Simulations were run at a temperature of 298 K and a
pressure of 1 atm (NPT ensemble), adopting TIP3P model for the water
and AMBER14 force field for the protein and RNA^[242]69, and the force
field parameters of methylated R255 were automatically generated by the
YASARA AutoSMILES algorithm^[243]70–[244]73. The simulation of
RNA-METTL14 was equilibrated for 10 nanoseconds (ns), during which
coordinates of the backbone chain atoms of protein and RNA were
restrained, and the amino acid side-chain atoms were sufficiently
released. The simulation was then run for 50 ns for production. The
cutoff of Van der Waals forces was set to 1.0 nm. Particle mesh Ewald
method was used for long-range electrostatics calculation with a
cut-off of 1.0 nm^[245]74. Bonded interactions were set to 1.25 fs, and
non-bonded interactions were set to 2.5 fs as described^[246]67. Root
mean square deviation, radius of gyration, and solvent accessible
surface area were adopted to ensure the equilibrium of the RNA-protein
complex (Supplementary Fig. [247]6a–d). The root mean square
fluctuation (RMSF) of RNA was measured over the 50 ns production time.
The binding energy E[bind] was calculated by the YASARA software using
the following equation:
[MATH:
Ebind<
/mi>=Epot_complex+
Esol_complex−Epot
_METTL14
−Esol_METTL14−Epot_RN
A−Esol_<
/msub>RNA :MATH]
1
where E[pot_complex,] E[pot_METTL14], and E[pot_RNA] are the potential
energy of the complex, METTL14, and RNA, respectively. The solvent
energy component E[sol] was defined by:
[MATH:
Esol=Esolcoulomb+E<
mi>solvdw+molsurf×surfc
ost :MATH]
2
where E[solcoulomb] and E[solvdw] are the coulomb and Van der Waals
components of solvation energy, molsurf is molecular solvent accessible
surface areas, and surfcost is a guesstimate of the entropic cost of
exposing an area in the surface to the solvent in kJ/mol and 0.65 was
utilized ([248]http://www.yasara.org). Three simulation replicates were
carried out.
MeRIP-seq and qPCR
MeRIP-seq was as conducted as described^[249]75. Briefly, total RNA was
extracted and fragmented into ~100-nucleotide fragments with zinc
acetate, and 300 μg fragmented RNA was prepared for immunoprecipitation
with m^6A antibodies (10 µg, Abcam, ab151230). Nonspecific binding was
washed away with a stringent workflow: high-salt buffer (400 mM NaCl,
0.05% NP-40, 10 mM Tris-HCl), competitive buffer (150 mM NaCl, 0.05%
NP-40, 10 mM Tris-HCl, 0.25 mg/mL adenosine, uridine, guanosine and
cytidine mix), high-detergent buffer (150 mM NaCl, 0.5% NP-40, 10 mM
Tris-HCl), and immunoprecipitation buffer (150 mM NaCl, 0.05% NP-40,
10 mM Tris-HCl). Bound m^6A RNA was eluted by competition with 1 mg/mL
N^6-methyladenosine (Selleckchem). For input RNA, ribosomal RNA was
removed with Epicentre Ribo-zero rRNA removal kits (Epicentre). Library
construction of immunoprecipitated RNAs and input RNAs was conducted
using NEBNext Ultra RNA Library Prep Kits for Illumina (New England
Biolabs) on an Illumina Hiseq Xten platform.
For MeRIP-qPCR, about 30 μg fragmented RNA and 1.5 μg m^6A antibodies
were utilized. Immunoprecipitated RNAs were reverse transcribed using a
GoScript Reverse Transcription System (Promega, A500) and analyzed
using real-time qPCR. Ratios of immunoprecipitated versus input for
peaks were calculated and normalized to GAPDH. Primers are listed in
Supplementary table [250]2.
mRNA lifetime analysis
mESCs were treated with 5 μg/ml Actinomycin D (JK chemical) for the
indicated time and then harvested using TRNZOL. RNA was extracted and
subjected to qPCR analysis or mRNA library construction using a NEBNext
Ultra RNA Library Prep Kit (NEB). Sequencing was carried out on the
Illumina Hiseq Nova platform.
RNA-seq analysis
Reads that mapped to rRNA fasta sequences from the UCSC gene annotation
(mm10) using bowtie2 (v.2.2.6)^[251]76 were discarded, and the
remaining reads were aligned to mm10 using hisat2-align-s
(v.2.0.5)^[252]77. Unique reads with high mapping quality were retained
using Picard ([253]http://broadinstitute.github.io/picard, v.2.16.0)
and SAMtools (v.0.1.09)^[254]78. Differential gene expression between
WT and METTL14 R255K was analyzed by DESeq2 using default
parameters^[255]79.
For mRNA lifetime RNA-seq data analysis, FPKM of genes were calculated,
and the lifetime was calculated as reported^[256]8.
Peak and differential peak identification
Regions of significant MeRIP enrichment relative to input control
(“peaks”) were identified using MACS2^[257]80. The parameter
‘--nomodel’ was used for macs2 peak calling. Macs2 bdgdiff was used to
identify differential peaks. The enrichment of biological process was
conducted using Kobas^[258]81.
Statistical analysis and reproducibility
The number of replicated times of western blots, micrographs, LC–MS/MS
or qPCR experiments is indicated in the figure legends. Key experiments
were repeated in another cell line or another knockout or knock-in
clone. Triplicates were performed for key experiments. Similar results
were obtained in each case, and a representative figure is shown. The
statistical comparisons between two groups were performed using an
unpaired two-tailed Student’s t-test or Mann–Whitney U-test. Graphpad
Prism software (8.3.0) was used for Student’s t-test analysis. The
exact P values, t value, and degrees of freedom were provided in the
source data file. *P < 0.05; **P < 0.01; ***P < 0.001; ****P < 0.0001;
NS not significant.
Reporting Summary
Further information on research design is available in the [259]Nature
Research Reporting Summary linked to this article.
Supplementary information
[260]Supplementary Information^ (8.8MB, pdf)
[261]Peer Review File^ (1.1MB, pdf)
[262]Reporting Summary^ (5.3MB, pdf)
Acknowledgements