Cited by 106Gut microbiota and healthGenetics and Neurodevelopmental DisordersRNA Research and Splicing

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Social interaction-induced activation of RNA splicing in the amygdala of microbiome-deficient mice

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Abstract

Social behaviour is regulated by activity of host-associated microbiota across multiple species. However, the molecular mechanisms mediating this relationship remain elusive. We therefore determined the dynamic, stimulus-dependent transcriptional regulation of germ-free (GF) and GF mice colonised post weaning (exGF) in the amygdala, a brain region critically involved in regulating social interaction. In GF mice the dynamic response seen in controls was attenuated and replaced by a marked increase in expression of splicing factors and alternative exon usage in GF mice upon stimulation, which was even more pronounced in exGF mice. In conclusion, we demonstrate a molecular basis for how the host microbiome is crucial for a normal behavioural response during social interaction. Our data further suggest that social behaviour is correlated with the gene-expression response in the amygdala, established during neurodevelopment as a result of host-microbe interactions. Our findings may help toward understanding neurodevelopmental events leading to social behaviour dysregulation, such as those found in autism spectrum disorders (ASDs).

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Crossref · 10.7554/elife.33070

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Figure 1. Germ-free (GF) mice display reduced social interaction. (A) Experimental design. (B) Time spent in active interaction with either a conspecific or non-social object in the 3-chamber social interaction test (3CSIT). Error bars show range, midlines of boxes show medians. (C) Results of the 2-way ANOVA with Dunnets multiple comparison post-hoc test, n = 11–12/group).
Figure 1. Germ-free (GF) mice display reduced social interaction. (A) Experimental design. (B) Time spent in active interaction with either a conspecific or non-social object in the 3-chamber social interaction test (3CSIT). Error bars show range, midlines of boxes show medians. (C) Results of the 2-way ANOVA with Dunnets multiple comparison post-hoc test, n = 11–12/group).CC BY · PubMed Central
Figure 2. Social interaction induces diverging gene expression patterns in the amygdala. (A) Number of differentially expressed genes (DEGs) including both up- and downregulated genes for all meaningful pairwise comparisons (see Table 1). (B) Presence-absence plot for all DEGs in all groups. Each line represents one gene that is a DEG in at least one pairwise comparison. (C–D) Venn diagram of upregulated (up, red) and downregulated (down, blue) genes in CON-GF and CON-SI or GF-SI comparisons to test for activation of expression patterns in GF mice under naïve conditions that are similar to activation by social interaction at either CON or GF colonisation status. (E) Heatmap to visualize enriched biological functions in social interaction(SI)-induced (upregulated only) genes. FDR-adjusted p-values were calculated for all enriched (padj <0.1) biological-function GO Terms (GObp), log-transformed (-log10) and colour-coded.
Figure 2. Social interaction induces diverging gene expression patterns in the amygdala. (A) Number of differentially expressed genes (DEGs) including both up- and downregulated genes for all meaningful pairwise comparisons (see Table 1). (B) Presence-absence plot for all DEGs in all groups. Each line represents one gene that is a DEG in at least one pairwise comparison. (C–D) Venn diagram of upregulated (up, red) and downregulated (down, blue) genes in CON-GF and CON-SI or GF-SI comparisons to test for activation of expression patterns in GF mice under naïve conditions that are similar to activation by social interaction at either CON or GF colonisation status. (E) Heatmap to visualize enriched biological functions in social interaction(SI)-induced (upregulated only) genes. FDR-adjusted p-values were calculated for all enriched (padj <0.1) biological-function GO Terms (GObp), log-transformed (-log10) and colour-coded.CC BY · PubMed Central
Figure 2—figure supplement 1. Additional data on gene expression analysis. (A) Results of differential gene expression analysis using more stringent filter criteria (padj <0.1 and log2(fold-change) >0.5 or<−0.5) as compared to Figure 1, where filter criteria are padj <0.1. Left panel: Number of differentially expressed genes (DEGs, both directions), right panel: Enrichment of KEGG pathways ‘MAPK sig. pathway’ and ‘Spliceosome’ (expressed as –log10(padj)). (B) Log2(fold-change)-values for all genes associated with the GO-Term ‘RNA processing’ for all comparisons after social interaction (SI). Each line represents one gene, genes significantly up-/downregulated in GF-SI comparison are highlighted in yellow, which are the same genes shown in Figure 3D. (C) Comparison of genes induced by SI in the murine amygdala with genes induced by environmental novelty in the murine hippocampus (see ref. Stilling et al., 2014a), EMBO J). Overlapping upregulated genes are listed and genes with similar function are grouped using different colours.
Figure 2—figure supplement 1. Additional data on gene expression analysis. (A) Results of differential gene expression analysis using more stringent filter criteria (padj <0.1 and log2(fold-change) >0.5 or<−0.5) as compared to Figure 1, where filter criteria are padj <0.1. Left panel: Number of differentially expressed genes (DEGs, both directions), right panel: Enrichment of KEGG pathways ‘MAPK sig. pathway’ and ‘Spliceosome’ (expressed as –log10(padj)). (B) Log2(fold-change)-values for all genes associated with the GO-Term ‘RNA processing’ for all comparisons after social interaction (SI). Each line represents one gene, genes significantly up-/downregulated in GF-SI comparison are highlighted in yellow, which are the same genes shown in Figure 3D. (C) Comparison of genes induced by SI in the murine amygdala with genes induced by environmental novelty in the murine hippocampus (see ref. Stilling et al., 2014a), EMBO J). Overlapping upregulated genes are listed and genes with similar function are grouped using different colours.CC BY · PubMed Central
Figure 2—figure supplement 2. RT-qPCR validation of RNA-seq results. (A) RT-qPCR validation results for 18 selected genes. n = 4–12 per group. (B) Overview of correspondence of RNAseq and qPCR results for selected genes. RT-qPCR results were analysed by 2-way ANOVA with multiple-testing correction (Tukey correction for effect of colonisation status; Sidak correction for effect of social interaction stimulation (SI)), significance level: padj <0.05.
Figure 2—figure supplement 2. RT-qPCR validation of RNA-seq results. (A) RT-qPCR validation results for 18 selected genes. n = 4–12 per group. (B) Overview of correspondence of RNAseq and qPCR results for selected genes. RT-qPCR results were analysed by 2-way ANOVA with multiple-testing correction (Tukey correction for effect of colonisation status; Sidak correction for effect of social interaction stimulation (SI)), significance level: padj <0.05.CC BY · PubMed Central
Figure 3. Loss of normal induction of MAP-K pathway is accompanied by upregulation of splicing pathways. (A) Comparison of enrichment of MAP-K pathway-associated genes and spliceosome-related genes among DEGs between groups. Dotted line: significance level (p=0.1) (B) Functional enrichment analysis of overlapping and uniquely regulated subsets of DEGs between CON-SI and GF-SI comparisons showed shared and different processes transcriptionally activated in the amygdala in response to social stimulation (C) Percentage of DEGs falling into the TOP20 enriched KEGG pathways for CON-SI and GF-SI. (D) Log2(fold change) (Log2FC) values plotted for each of the 112 DEGs in the GF-SI comparison that was associated with GO-Term ‘RNA processing’. black line: median, non-parametric Friedman test F = 65.5, p<1.0e-4; ***p<1.0e-4, *p<0.05, Dunn’s multiple comparisons, n = 112/group.
Figure 3. Loss of normal induction of MAP-K pathway is accompanied by upregulation of splicing pathways. (A) Comparison of enrichment of MAP-K pathway-associated genes and spliceosome-related genes among DEGs between groups. Dotted line: significance level (p=0.1) (B) Functional enrichment analysis of overlapping and uniquely regulated subsets of DEGs between CON-SI and GF-SI comparisons showed shared and different processes transcriptionally activated in the amygdala in response to social stimulation (C) Percentage of DEGs falling into the TOP20 enriched KEGG pathways for CON-SI and GF-SI. (D) Log2(fold change) (Log2FC) values plotted for each of the 112 DEGs in the GF-SI comparison that was associated with GO-Term ‘RNA processing’. black line: median, non-parametric Friedman test F = 65.5, p<1.0e-4; ***p<1.0e-4, *p<0.05, Dunn’s multiple comparisons, n = 112/group.CC BY · PubMed Central
Figure 4. Social interaction leads to a strong increase in alternative splicing in GF and exGF animals. (A) Number of differentially spliced genes (DSGs) for all meaningful pairwise comparisons (see Table 1). (B–C) Venn diagrams showing overlapping DSGs for naïve (B) and social interaction (SI, (C) comparisons. After stimulation differences become evident. (D) Heatmap to visualize enriched pathways in SI-induced differentially spliced genes. FDR-adjusted p-values were calculated for all enriched (padj <0.1) KEGG pathways, log-transformed (-log10) and colour-coded.
Figure 4. Social interaction leads to a strong increase in alternative splicing in GF and exGF animals. (A) Number of differentially spliced genes (DSGs) for all meaningful pairwise comparisons (see Table 1). (B–C) Venn diagrams showing overlapping DSGs for naïve (B) and social interaction (SI, (C) comparisons. After stimulation differences become evident. (D) Heatmap to visualize enriched pathways in SI-induced differentially spliced genes. FDR-adjusted p-values were calculated for all enriched (padj <0.1) KEGG pathways, log-transformed (-log10) and colour-coded.CC BY · PubMed Central
Figure 5. Behavioural performance correlates with expression of RNA processing genes in GF mice. (A) Design of analysis. A gene list, ranked by Pearson correlation between expression level of a given gene and behavioural performance for each individual mouse, was used for gene-set enrichment analysis (GSEA). The algorithm assigns one or multiple functions to each gene in the list based on the GO-Term or KEGG Pathway databases, then calculates an enrichment score for each function based on the rank of genes associated with this function (B–C) GSEA-generated enrichment plots for two selected significantly enriched functions (KEGG pathway ‘Spliceosome’, GO-Term ‘RNA splicing’). (D) Normalized GSEA enrichment scores for all significantly enriched functions or pathways found in this analysis. (E) Gene-expression analysis within the GF-SI group (GF-SIhigh vs GF-SIlow, n = 6). Shown are expression values for three significantly differentially regulated genes plotted against the animals time spent in active social interaction. r: Pearson correlation coefficient.
Figure 5. Behavioural performance correlates with expression of RNA processing genes in GF mice. (A) Design of analysis. A gene list, ranked by Pearson correlation between expression level of a given gene and behavioural performance for each individual mouse, was used for gene-set enrichment analysis (GSEA). The algorithm assigns one or multiple functions to each gene in the list based on the GO-Term or KEGG Pathway databases, then calculates an enrichment score for each function based on the rank of genes associated with this function (B–C) GSEA-generated enrichment plots for two selected significantly enriched functions (KEGG pathway ‘Spliceosome’, GO-Term ‘RNA splicing’). (D) Normalized GSEA enrichment scores for all significantly enriched functions or pathways found in this analysis. (E) Gene-expression analysis within the GF-SI group (GF-SIhigh vs GF-SIlow, n = 6). Shown are expression values for three significantly differentially regulated genes plotted against the animals time spent in active social interaction. r: Pearson correlation coefficient.CC BY · PubMed Central

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Metadata

Authors
Stilling, R. M., Moloney, G. M., Ryan, F. J., Hoban, A. E., Bastiaanssen, T. F., Shanahan, F., Clarke, G., Claesson, M. J., Dinan, T. G., & Cryan, J. F.
Affiliations
University College Cork (IE)
Corresponding author
  • Stilling, Roman M
  • Cryan, John F
Venue
eLife
Published
2018-05-29
Volume
7
ISSN
2050-084X (ISSN-L)
OpenAlex
W2805802451
Cited by
106
References
90
Citations by year
2026: 3 · 2025: 5 · 2024: 8 · 2023: 10 · 2022: 13 · 2021: 21 · 2020: 26 · 2019: 15 · 2018: 3
FWCI
5.78
Type
journal article
Language
en
Open access
Locations
  • eLife (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • Arrow@dit (Dublin Institute of Technology) (acceptedVersion)
  • Cork Open Research Archive (University College Cork, Ireland) (submittedVersion, cc-by)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
  • GoeScholar The Publication Server of the Georg-August-Universität Göttingen (Georg-August-Universität Göttingen) (submittedVersion, cc-by)
Funders
  • Science Foundation Ireland (12/RC/2273)
  • Irish Research Council (GOIPD/2014/355)
  • Irish Health Board
  • National Alliance for Research on Schizophrenia and Depression (20771)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gut microbiota and health
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetics and Neurodevelopmental Disorders
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA Research and Splicing
Keywords
host microbiome, germ-free mice, amygdala, RNA splicing, social interaction, social behavior, splicing factors, alternative exon usage, host-microbe interactions, brain development, autism spectrum disorder, gene expression regulation
MeSH terms
Autism Spectrum Disorder, Gastrointestinal Microbiome, RNA Splicing Factors, Amygdala, Animals, Animal Communication, Disease Models, Animal, Germ-Free Life, Male, Nerve Tissue Proteins, RNA Splicing, Weaning, Mice, Neurogenesis

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