Abstract

A localized transcriptome at the synapse facilitates synapse-, stimulus- and transcript-specific local protein synthesis in response to neuronal activity. While enzyme-mediated mRNA modifications are known to regulate cellular mRNA turnover, the role of these modifications in regulating synaptic RNA has not been studied. We established low-input m6A-sequencing of synaptosomal RNA to determine the chemically modified local transcriptome in healthy adult mouse forebrains and identified 4,469 selectively enriched m6A sites in 2,921 genes as the synaptic m6A epitranscriptome (SME). The SME is functionally enriched in synthesis and modulation of tripartite synapses and in pathways implicated in neurodevelopmental and neuropsychiatric diseases. Interrupting m6A-mediated regulation via knockdown of readers in hippocampal neurons altered expression of SME member Apc, resulting in synaptic dysfunction including immature spine morphology and dampened excitatory synaptic transmission concomitant with decreased clusters of postsynaptic density-95 (PSD-95) and decreased surface expression of AMPA receptor subunit GluA1. Our findings indicate that chemical modifications of synaptic mRNAs critically contribute to synaptic function.

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Change history

  • 10 August 2018

    In the version of this article initially published, a Supplementary Fig. 6f was cited in the last paragraph of the Results. No such panel exists; the citation has been deleted. The error has been corrected in the HTML and PDF versions of the article.

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Acknowledgements

We thank Y. Hayashi for critical reading of this manuscript, CeMI imaging center at iCeMS, and the supporting facility at the medical school of Kyoto University for technical support. This work was supported by grants KAKENHI17H03546, KAKENHI26702038 and KAKENHI26115515, and grants from the Hirose Foundation and Astellas Foundation to D.O.W. I.O and B.J.G are supported by Japan Society for the Promotion of Science fellowships.

Author information

Author notes

  1. These authors contributed equally: Daria Merkurjev, Wan-Ting Hong, Kei Iida.

Affiliations

  1. Statistics Department, University of California at Los Angeles, Los Angeles, CA, USA

    • Daria Merkurjev
  2. Institute for Integrated Cell-Material Sciences (iCeMS), Kyoto University, Kyoto, Japan

    • Wan-Ting Hong
    • , Ikumi Oomoto
    • , Belinda J. Goldie
    • , Hitoshi Yamaguti
    • , Takayuki Ohara
    •  & Dan Ohtan Wang
  3. Medical Research Support Center of Graduate School of Medicine, Kyoto University, Kyoto, Japan

    • Kei Iida
  4. Graduate School of Biostudies, Kyoto University, Kyoto, Japan

    • Ikumi Oomoto
    •  & Takayuki Ohara
  5. Japan Society for the Promotion of Science (JSPS), Tokyo,, Japan

    • Belinda J. Goldie
  6. Undergraduate School of Informatics and Mathematical Science, Kyoto University, Kyoto, Japan

    • Hitoshi Yamaguti
  7. Society-Academia Collaboration for Innovation, Kyoto University, Kyoto, Japan

    • Shin-ya Kawaguchi
  8. Graduate School of Science, Kyoto University, Kyoto, Japan

    • Shin-ya Kawaguchi
    •  & Tomoo Hirano
  9. Department of Psychiatry and Biobehavioral Sciences, University of California at Los Angeles, Los Angeles, CA, USA

    • Kelsey C. Martin
  10. Semel Institute for Neuroscience and Human Behavior, University of California at Los Angeles, Los Angeles, CA, USA

    • Kelsey C. Martin
  11. Department of Biological Chemistry, University of California at Los Angeles, Los Angeles, CA, USA

    • Kelsey C. Martin
  12. Department of Molecular, Cell and Developmental Biology, University of California at Los Angeles, Los Angeles, CA, USA

    • Matteo Pellegrini
  13. The Keihanshin Consortium for Fostering the Next Generation of Global Leaders in Research (K-CONNEX), Kyoto University, Kyoto, Japan

    • Dan Ohtan Wang

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Contributions

D.O.W. conceived and designed the project. W.T.-H. purified synaptosomes and performed RNA extractions, m6A dot-blotting and data mining. D.O.W. and T.O. constructed libraries; D.M., K.I., B.J.G, H.Y. and M.P. performed bioinformatics analysis; T.O. performed immunostaining; I.O. constructed shRNA and performed KD, FISH and spine analysis in cultured hippocampal neurons. S.-y.K. performed electrophysiology. D.O.W and B.J.G. wrote the manuscript. K.C.M. and T.H. supervised parts of the project. All authors participated in data analysis and interpretation and made indispensable contributions.

Competing interests

The authors declare no competing financial interests.

Corresponding author

Correspondence to Dan Ohtan Wang.

Integrated supplementary information

  1. Supplementary Figure 1 Cross-database comparison and experimental setup for preparation and characterization of m6A synaptic RNA in synaptosomes.

    a. Summary of cross-database comparison of m6A mRNA and localized mRNA lists. b. Synaptosome purification from healthy adult mouse forebrains using percoll-sucrose discontinuous gradients. F3 and F4 fractions were pooled as synaptosomal fraction (SYN). Homogenate lysate without fractionation was used as control for comparison (HOM); c. Relative (de)enrichment of a panel of synaptic and somatic markers probed using western blot (n=3 independent experiments); d. Full scan of blots in c (n=3 independent experiments); e. Separation of RNA populations was confirmed by qRT-PCR examination of nuclear lncRNA Malat1, somatic RNA beta-3 tubulin and known synaptically localized transcript CaMKIIα (mean value ±s.e.m., n=3 independent experiments). f. Bioanalyzer analysis of RNA integrity in prepared fractions. HOM, homogenate; Cyto, cytoplasm, F3 and F4 (SYN), synaptosomes (n=3 independent experiments). g. A biological replicate of m6A dot-blot presented in Fig. 1b shows highly similar results (n=2 independent experiments).

  2. Supplementary Figure 2 Validation of low-input m6A-seq and characterization of HOM and SYN peaks.

    a. Sequencing summary in this study; b. Pairwise comparison of biological replicate sequencing libraries demonstrates strong, linear correlation between replicates (n=2 independent experiments); c. reads sorted and removed from further analysis; d. Mapping statistics for QC reads mapped with STAR to mm9 refseq.GTF. e. hypergeometric tests on peak overlapping to three previously published databases (n=2 independent experiments); f. Frequency plot of motif per 5nt per peak (y axis) against distance from peak summit (x axis) in HOM; g. Enriched human phenotypes among genes with START codon-associated and STOP codon-associated SYN peaks (ToppGene); h. Left, synapse-enriched peak in Ckap5 transcript; Right, synapse-depleted peak in Lysmd4. Red, IP tracks; blue, INPUT tracks; black, peak location track.

  3. Supplementary Figure 3 Negative impact of methylation on synaptic mRNA stability and synaptic localization.

    a. (left) Box plots depicting synaptic concentrations of genes in four groups with increasing methylation level. For each gene, methylation level (ML) was calculated as IP/INPUT reads ratios in each designated RNA region (full length, 5’UTR, CDS, and 3’UTR) and divided into four groups from the least methylated to the most methylated (a; ML < −2, b; −2 <= ML < 0, c; 0 <= ML < 2, d; 2 <= ML). S.TMP: transcripts per million at SYN. (right) Scatter plot and regression model labeled with slope, p-value testing the quality of model fitting, and Pearson’s correlation coefficient r; (n=2 independent experiments showing similar results). b. Analogous plots representing transcript enrichment at synapse compared to whole cell. Y-axis and X-axis represent relative expression values and relative methylation values averaged from two independent experiments. For box plots, genes were classified into one of the four groups as follows: e; rel. ML < −1, f; −1 <= rel. ML < 0, g; 0 <= rel. ML < 1, h; 1 <= rel. ML. Genes with TPM less than 1 were excluded from the analysis. number of data points included in this figure: (a) Total; a: 790, b: 5034, c: 4976, d: 1107, 5’UTR; a: 596, b: 2787, c: 4238, d: 1508, CDS; a: 1540, b: 5129, c: 3550, d: 1192, 3’UTR; a: 1062, b: 3590, c: 4011, d: 1808, (b) Total; e: 133, f: 7861, g: 3126, h: 29, 5’UTR; e: 730, f: 78 3367, g: 3306, h: 691, CDS; e: 216, f: 7311, g: 3193, h: 41. 3’UTR; e: 482, f: 5824, g: 3156, h: 256.

  4. Supplementary Figure 4 m6A regulatory proteins in dendritic processes of dissociated hippocampal neuronal cultures and brain slices.

    a. Confocal images of m6A regulatory proteins (magenta) and counter-stained with phalloidin (green) to label F actin-rich spines. Scale bar, 5 μm. b. m6A reader YTHDF1 in perfused mouse brain slices. Top, cortical cortex; Bottom, hippocampus and CA1 and CA3 regions of hippocampus. Scale bars, 100 μm and 50 μm. (n= 3 independent experiments).

  5. Supplementary Figure 5 Knocking down METTL3 in dissociated hippocampal neuronal cultures causes cell death and knocking down YTHDF1 causes synapse malfunction.

    a. Group quantification of METTL3 protein expression measured by immunofluorescence staining at Day2 after transfection; b. Immunofluorescence images of hippocampal neuronal cultures transfected with shMETTL3 vectors. DAPI (blue), GFP (green), METTL3 (red), (n=3 independent experiments); c. Confocal images of DIV19 dissociated hippocampal neurons expressing shScramble-GFP (left panel) or shYTHDF1-GFP (right panel). DAPI (blue), GFP (green), YTHDF1 (red). Arrowheads point to GFP(+) shScram or shYTHDF1 transfected neurons. Scale bar, 10 μm (n=3 independent experiments); d. Normalized YTHDF1 mRNA expression in shScramble, shYTHDF1-1, and shYTHDF1-2 cells (normalized to beta actin mRNA, n=3 independent experiments); e. Western-blots of YTHDF1 proteins in shScramble, YTHDF1-sh1, and shYTHDF1-2 cells lysates. β-actin was blotted on the same membrane as loading control (n=3 independent experiments). f. Confocal images of dendritic processes of DIV19 dissociated hippocampal neurons expressing shYTHDF1-2-GFP. Top, GFP labels morphology of dendritic shaft and spines; Bottom, PSD-95 staining in the same samples to label post-synaptic density (n=3 independent experiments). g. Group quantification of spine head width in DIV19 dissociated hippocampal neurons expressing shScramble-GFP or shYTHDF1-GFP (n=3 independent experiments). h. Group quantification of PSD-95 intensity in DIV19 dissociated hippocampal neurons expressing shScramble-GFP or shYTHDF1-GFP. i. GFP fluorescence images of control cells (expressing pCAG-EGFP and pX330) and YTHDF1-KD cells (expressing pCAG-EGFP and pX330-guide RNA sequences g1 or g2). Scale bar, 5 μm; j. Group quantifications of spine neck length showed similar phenotypes to YTHDF1-KD using shRNA vectors. k. Group quantification of spine head width showed similar phenotypes to YTHDF1-KD using shRNA vectors (n=2 independent experiments. ***p<1x10-3; Kruskal-Wallis’s multiple comparison test).

  6. Supplementary Figure 6 Reducing YTHDF3 expression in hippocampal neurons causes excessive dendritic filopodia, in place of mature spines, and APC protein expression in YTHDF1-knockdown neurons is reduced.

    a. Confocal images of DIV17 dissociated hippocampal neurons expressing shScram-GFP (top) or shYTHDF3-GFP (bottom). DAPI (blue), GFP (green), YTHDF3 (red). Arrowheads point to GFP(+) shScram or shYTHDF3 transfected neurons. Scale bar, 10 μm (n=3 independent experiments). b. Confocal images on dendritic shaft of GFP (green) and YTHDF3 (red). Scale bar, 10 μm (n=3 independent experiments); c. Quantification of YTHDF3 protein expression by immuno-staining in shScram and shYTHDF3 cells (Scram, sh1, and sh2). YTHDF3 protein in sh1 and sh2 samples decreased over a 4-day time course after transfection (n=3 independent experiments). d. Confocal images of dendritic shaft and spines of shScram and shYTHDF3-2 cells (n=3 independent experiments). Left, GFP labels morphology of dendritic shaft and spines; Right, PSD-95 staining in the same sample (magenta). Contour of affected dendrites was traced as the white lines through GFP expression. Fluorescence signals outside of the contour were masked to restrict quantification to the affected neurons. Scale bar, 5 μm (n=3 independent experiments). e. Confocal images of APC immunostaining using APC N-terminus antibody (top) or APC C-terminus antibody (bottom). GFP labels neurons expressing the shRNAs (shScram or shYTHDF1). Both antibodies consistently detected decreased APC protein expression in YTHDF1-KD neurons; Arrowheads point to GFP-positive neurons. DAPI (blue), GFP (green), APC protein (magenta). Scale bar, 10 μm (n=3 independent experiments).

  7. Supplementary Figure 7 Mapping of synaptic cleft proteins and other synaptic proteins encoded by SYN-methylated mRNA and by mRNAs carrying the most abundant methylation sites in SME.

    Proteins mapped to excitatory and inhibitory synapses. Dark brown: proteins encoded by top SME genes; light brown: synaptic cleft proteins encoded by synaptically methylated transcripts.

Supplementary information

  1. Supplementary Text and Figures

    Supplementary Figures 1–7 and Supplementary Tables 7 and 8

  2. Reporting Summary

  3. Supplementary Table 1

    Synaptic transcriptome

  4. Supplementary Table 2

    HOM peaks and SYN peaks

  5. Supplementary Table 3

    Genes associated with peaks around start or stop codon

  6. Supplementary Table 4

    GO analysis using expressed genes as background

  7. Supplementary Table 5

    Synaptic m6A epitranscriptome (SME)

  8. Supplementary Table 6

    qRT-PCR primers

  9. Supplementary Table 9

    GO analysis of synaptically hypo- and hypermethylated genes

  10. Supplementary Table 10

    Overlap with astrocytic perisynaptic and soma-enriched gene lists

  11. Supplementary Table 11

    Values associated with all box plots

About this article

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DOI

https://doi.org/10.1038/s41593-018-0173-6

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