The microbiome regulates amygdala-dependent fear recall

Abstract

The amygdala is a key brain region that is critically involved in the processing and expression of anxiety and fear-related signals. In parallel, a growing number of preclinical and human studies have implicated the microbiome-gut-brain in regulating anxiety and stress-related responses. However, the role of the microbiome in fear-related behaviours is unclear. To this end we investigated the importance of the host microbiome on amygdala-dependent behavioural readouts using the cued fear conditioning paradigm. We also assessed changes in neuronal transcription and post-transcriptional regulation in the amygdala of naive and stimulated germ-free (GF) mice, using a genome-wide transcriptome profiling approach. Our results reveal that GF mice display reduced freezing during the cued memory retention test. Moreover, we demonstrate that under baseline conditions, GF mice display altered transcriptional profile with a marked increase in immediate-early genes (for example, Fos, Egr2, Fosb, Arc) as well as genes implicated in neural activity, synaptic transmission and nervous system development. We also found a predicted interaction between mRNA and specific microRNAs that are differentially regulated in GF mice. Interestingly, colonized GF mice (ex-GF) were behaviourally comparable to conventionally raised (CON) mice. Together, our data demonstrates a unique transcriptional response in GF animals, likely because of already elevated levels of immediate-early gene expression and the potentially underlying neuronal hyperactivity that in turn primes the amygdala for a different transcriptional response. Thus, we demonstrate for what is to our knowledge the first time that the presence of the host microbiome is crucial for the appropriate behavioural response during amygdala-dependent memory retention.

Figure 1

Behavioural assessment to cued fear conditioning in germ-free (GF) mice. (a) Schematic representation of 1-day fear conditioning protocol. (b) Percentage freezing during training to tone (context A). (c) Total percentage freezing for the first trial block (initial 5 tones) used to demonstrate cued memory retention (context B). (d) Cued fear extinction percentage freezing during all 8 trial blocks (40 conditioned stimulus (CS) tone presentations, context B). (e) Total percentage freezing during context recall (context A) (5 min no stimulus trial). CON, conventionally raised mice. *P<0.05, **P<0.01, ***P<0.001. *Represents comparison between CON and GF; ^&represents comparison between CON and ex-GF.

Figure 2

Experimental approach and RNA pooling for investigating mRNA change in the amygdala. (a) Schematic depiction of experimental design including stimulated and naive mice. Schematic indicates number of mice per group. Red indicates the number of mice used to create one pool (equal volumes of RNA were used). The final number of animals per group after pooling was 4 pools per group (except CON-n, pooled to make n=3) for RNA sequencing. GF-n mice were not pooled as only 5 animals were in this group. CON, conventionally raised mice; CON-n, CON naive; GF, germ free; GF-n, GF naive.

Figure 3

Altered gene expression in the amygdala of GF naive mice when compared with naive CON. (a) Number of differentially regulated genes (DEGs) between all pairwise comparisons (including fear conditioned mice). (b) Volcano plot representing the number of differentially regulated genes between CON-n and GF-n mice. Each gene is graphed with fold change (Log2) against q-value (P-value adjusted (P_adj) for multiple comparisons). (c) Gene Ontology analysis for a selection of significant biological processes from the up-regulated gene between CON-n and GF-n mice. (d) Enriched terms for cellular compartment from differentially up-regulated gene between CON-n and GF-n mice. (e) Venn diagrams showing overlaps between CON-n and GF-n and CON-n and CON-fc up- and down-regulated and the gene symbols that contribute to the enrichment in biological process in orange. In grey are immediate-early response genes that are up-regulated in naive GF mice and stimulated CON mice. CON, conventionally raised mice; CON-fc, CON after fear retention; CON-n, CON naive; GF, germ free; GF-n, GF naive.

Figure 4

Transcriptional response to fear retention in CON and GF mice. (a, b) Volcano plot of all the differentially regulated genes between CON-n and CON-fc and GF and GF-fc. (c) Venn diagram showing the overlap between up- and down-regulated genes after comparison of naive and fear conditioned CON and GF mice. (d) Enrichment among unique up-regulated genes in CON-fc mice that are not differentially regulated in GF-fc mice. (e) Enrichment of down-regulated genes that are unique to GF-fc mice. Venn diagram represents the overlap between down-regulated genes in CON-n vs CON-fc and GF-n vs GF-fc. Genes highlighted in orange directly contribute to the Gene Ontology (GO) terms enriched for biological processes in GF-fc mice. CON, conventionally raised mice; CON-fc, CON after fear retention; CON-n, CON naive; GF, germ free; GF-fc, GF after fear retention; GF-n, GF naive.

Figure 5

Altered miRNAs in GF-n mice and their relevant Gene Ontology (GO) terms. (a) Number of dysregulated miRNAs based on raw P-value for each experimental comparison. (b) Number of predicted mRNA for individual down-regulated miRNAs in GF-n mice when compared with CON-n that occur in more than 3 prediction algorithms. (c, d) Venn diagram of the number of significant (P_adj) GO terms for biological processes for each miRNA overlapped with significant GO terms from mRNA sequencing. Bar graphs represent a selection of significant terms that were common between mRNA sequencing and enriched from individual mRNAs. (e) Venn diagram showing the number of overlapping miRNAs between groups after fear retention test (CON-fc and GF-fc). CON, conventionally raised mice; CON-fc, CON after fear retention; CON-n, CON naive; GF, germ free; GF-fc, GF after fear retention; GF-n, GF naive.