Tommaso Leonardi1,2, Nunzio Iraci2, Anton J. Enright1 and Stefano Pluchino2

2 Wellcome Trust - Medical Research Council Cambridge Stem Cell Institute, University of Cambridge, UK

1 EMBL-EBI, Wellcome Trust Genome Campus, Hinxton, UK

Mining the sorting machinery of exosomal miRNAs in neural stem/precursor cells

Conclusions

Summary

Tommaso Leonarditl344@ebi.ac.ukScan the QR code for full Methodsand contact info.http://www.ebi.ac.uk/~tl344/isev2015

Smad2/3 Klf7 Obx2NPCth1−DownEXOagg−DownEVbasS−D ownNPCth1−UpEVth2S−UpEVth2S−D ownEVth1−UpEVth1S−UpEVth1S−D ownEVbasS−UpE Vagg−UpE Vagg−DownEXOth2S−UpEXOth2S−DownEXOth1S−UpEXOth1S−DownEXObasS−UpEXOagg−UpEXObasS−Down

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antisensedust_repeats

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miRNAsNPC

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E Fmmu-miR-103target sequences

Figure 1: (A) Fraction of reads dtermined to originate from miRNA loci versus other genomic regions. (B) Heatmap displaying z-score row-normalised expression levels for miRNAs shown to be differentially expressed in at least one comparison, scaled from down-regulated (white), unchanged (green) and up-regulated (blue). (C) Comparison of normalised count data between NPCs and EXOs. miRNAs called significant (DESeq adjusted p-value <0.01) are in red. (D) Comparison of normalised count data between Th1 and Basal EXOs. (E-F) EXO miRNA-mediated effects on target cells. The reporter luciferase was made responsive to the levels of either miR-103 (highly abundant in exosomes) (E) or miR-365 (absent in exosomes) (F) by cloning their target sequence downstream of the coding region in the 3’UTR. Luciferase activity was monitored in 3T3 NIH cells as a function of EXO treatment compared to untreated cells. Data are expressed as fold change (+/- SEM) from a total of 4 independent experiments.*** p-vlaue<0.001; ** p-value<0.01 (Anova, treated vs Ctrl).

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1. Functional miRNAs are enriched in exosomes 3. Promoters of secreted miRNAs are not enriched in bindingsites of any specific transcription factor

4. Secreted miRNAs are enriched in short motifsmiR1miR2miR3miR4

List ordered byFC EXO vs NPC

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BCRANK looks for motifs enriched at the top of the list starting with random motifs of length 3 and

trying all permutations

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Figure 3: Heatmap showing the adjusted p-value of enrichment of a given transcription factor binding se-quence (columns) in the promoter of miRNAs in each category (rows) vs all other miRNAs. Only TFs with adjusted p-value<0.5 in at least one comparison are shown. miRNAs were diveded in 19 categories ac-cording to their expression profiles in NPC, EV and EXO in Basal and Th1 conditions and the promoters in each category were scanned with Homer to identify enriched TF binding sites. After correction of p-values for multiple tests, we did not identify any TFs motif significantly enriched in the promoters of se-creted miRNAs.

Figure 4: (A, B) Seqlogo of the BCCM (A) and GBGK (B) motifs identified by BCRANK. (C, D) Volcano plots showing the log2 fold change (EXO vs NPC) for each miRNA plotted against the -log10 of the adjusted p-value. miRNAs that contain the BCCM (C) or GBGK (D) motif are indicated in blue.

2. Identification of miRNA promoters in the murine genome

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Figure 2: (A) Example of the genomic region surrounding a miRNA (miR-152) showing the chromating features supporting the presence of the miRNA TSS in this region (H3K4me3 peak, ChromHMM peak, Cpg Island, DHS, host gene TSS and Eponine prediction. (B) Heat-map showing what features support each candidate promoter (best cluster). Each row represents a best cluster while each column repre-sents a feature. Yellow cells indicate that the given feature was used to support the given best cluster. (C) PhastCons conservation score of all promoters, best promoter for each miRNA and random genomic sequences.

Neural stem/precursor cell (NPC) transplantation protects the central nervous system from inflammatory damage via cell-to-cell communication mechanisms. Recent works suggest that the exosome-mediated transfer of molecules such as miRNAs might play an important role in mediating the protective effect of NPCs.Here we aim to identify the machinery that sorts miRNAs to exosomes in murine NPCs. Our hypothesis is that such a mechanism might work 1) at the transcriptional level, with transcription factors (TFs) driving the transcription of exosomal miRNAs; or 2) at the post-transcriptional level, with carrier proteins that recognize specific miRNAs, bind to them and export them to exosomes.We purified exosomes from NPC cultured either in Basal or in Th1 pro-inflammatory conditions and we used RNA-Seq to identify miRNAs significantly more abundant in ex-osomes than parental cells (Panel 1). To address whether specific TFs drive the transcription of secreted miRNAs, we first employed ChIP-Seq data produced by the ENCODE project to identify on a genome-wide scale murine miRNA promoters (Panel 2). We then analysed the miRNA promoter sequences to identify any TF binding site enriched in the promoters of secreted miRNAs vs non-secreted (Panel 3). In parallel, we used a variety of motif enrichment tools available in R/Bioconductor (Cosmo, BCRANK, motifRG) to find short motifs enriched in the mature sequences of secreted miRNAs (Panel 4).

We first identified a set of miRNAs which are consistently more abundant in exosomes compared to parental cells, disregarding Th1 cytokine stimula-tion. We then identified on a genome-wide scale miRNA promoters and found that they are conserved across vertebrates and marked by DNAseI hy-persensitivity. We also found that no specific TF binding site is enriched in the promoters of secreted miRNAs. However, we identified two short motifs over-represented in exosomal miRNAs, one of which matches the binding sequence of hnRNPA2B1, which previous works have shown to be involved in miRNA secretion. By western blot we found that hnRNPA2B1 is not pre-sent within NPC-derived exosomes (data not shown in this poster), suggest-ing that other proteins might be involved in miRNA secretion in NPCs.

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doi: 10.6084/m9.figshare.1383206