Cytolethal distending toxin B inoculation leads to distinct gut microtypes and IBS-D-like microRNA-mediated gene expression changes in a rodent model

Figures & data

Figure 1. (a) Serum levels of anti-CdtB antibodies (delta of post-inoculation levels vs. baseline levels) in controls and CdtB-inoculated rats (CdtB). (b) Stool wet weight (%) in controls and CdtB rats. (c) Serum levels of anti-vinculin antibodies in controls and CdtB rats. The Mann-Whitney test was used to compare groups and a p-value <0.05 was considered significant.

Figure 2. (a) Small intestinal (duodenum and ileum), large intestinal (cecum) and stool microbial alpha diversity (Shannon entropy) of CdtB rats (blue) and controls (orange). (b) Small bowel (duodenum and ileum), large intestine (cecum) and stool microbial beta diversity of CdtB rats (shades of blue) and controls (shades of yellow/orange). (c) Relative abundances of all bacterial genera throughout the small bowel (duodenum and ileum), large intestine (cecum) and stool of CdtB rats and controls.

Figure 3. (a) Principal coordinate analysis (PCA) plot of ileal microbiome beta diversity in CdtB rats (blue) and controls (red). (b) PCA plot of ileal microbiome beta diversity in CdtB rats and controls, colored according to differences in alpha diversity (Shannon index). (c) PCA plot of ileal microbiome beta diversity showing the different clusters of CdtB rats (cluster 0 - green, cluster 1 - blue and cluster 2 - purple) and controls (red), after clustering analysis using the K-Means clustering algorithm.

Figure 4. (a) Common altered host ileal tissue pathways in different microbiome-based clusters of CdtB rats, based on whole transcriptome analysis. C1 – cluster 2 vs. Control; C2 – cluster 1 vs. Control; C3 – cluster 0 vs. Control; C4 – CdtB (all rats) vs. Control. (b) Zinc finger (zfp), integrins (itg) and talin (Tln) mRNA expression profiles in control (orange) and CdtB (blue) rats after meta-analysis of differently expressed genes associated with the global effects of CdtB. Hypergeometric distribution was used to analyze the enrichment of pathways, gene ontology, domain structure, and other ontologies. The topGO R library was used to determine local similarities and dependencies between GO terms in order to perform Elim pruning correction. DEseq2 was used to calculate fold changes and p-values. Differentially expressed mRNAs had absolute fold change (FC) ≥ 1.25 and adj. P-value (FDR P-value) <.05.

Figure 5. (a) Differentially expressed genes in host ileal tissues of cluster 2 CdtB rats as compared to controls. (b) Gene ontology (GO) enriched pathways in ileal tissues of cluster 2 CdtB rats as compared to controls. DEseq2 was used to calculate fold changes and p-values. Differentially expressed mRNAs had absolute fold change (FC) ≥ 1.25 and adj. P-value (FDR P-value) <0.05. Hypergeometric distribution was used to analyze the enrichment of pathways, gene ontology, domain structure, and other ontologies. The topGO R library was used to determine local similarities and dependencies between GO terms in order to perform Elim pruning correction.

Figure 6. Differentially expressed host miRNAs in CdtB-induced dysbiosis. (a) Principal component analysis of miRNA expression in clusters of different microbiomes emerged after CdtB exposure. (b) Venn diagram of the differentially expressed (DE) miRNAs in each microbiome cluster. Cluster 0 did not show any differently expressed miRNAs when compared to controls. (c) DE miRNAs in cluster 1. (d) DE miRNAs in cluster 2. (e). Top 20 DE miRNAs in cluster 1. (f) All DE miRNAs in cluster 2. Differentially expressed miRNAs have absolute fold change (FC)≥1.5 and adj. P-value (FDR P-value)<0.1. FDR p-values were obtained through multi-factorial statistics based on a negative binomial generalized linear model (GLM) using CLC Genomics Workbench v.20 (Wald test). Heatmaps use relative color scheme, where the minimum and maximum values in each row are used to convert values to colors. Euclidean distance and average linkage were used for the creation of heatmaps using morpheus software (https://software.Broadinstitute.org/morpheus).

Figure 7. Enrichment analysis of DE host mRNAs that were the targets of DE miRNAs in clusters 2 and 1. Predicted and validated miRNA targets were uploaded to ShinyGO v.0.76.1 to obtain the gene ontology (GO) terms for cellular components and biological processes that were regulated by miRNAs in each cluster. (a) Top 20 dysregulated cellular components regulated by miRNAs in cluster 2. (b) Top 20 dysregulated biological processes controlled by miRNAs in cluster 2. (c) Top 20 dysregulated cellular components regulated by miRNAs in cluster 1. (d) Top 20 dysregulated biological processes controlled by miRNAs in cluster 1. Enrichment analysis in ShinyGO v.0.76 was calculated based on hypergeometric distribution followed by false discovery rate (FDR) correction (FDR <0.05). No background list was used for enrichment analysis.

Table 1. Relevant miRNAs and targets previously identified in the literature and associated with IBS pathophysiology in clinical and animal studies.

	mRNA		miRNA
Group	Up	Down	Up	Down	Biological role
Cluster 1		Srf		miR-143-3p	GI motility^Citation26
		Slc6a4 (Sert)		miR-200a-3p	Visceral hyperalgesia^Citation27
		Aqp3	miR-29a-3p		Intestinal permeability^Citation28
		Pten		miR-21-5p	Intestinal barrier function^Citation29
		Cdh1		miR-219a-5p	Intestinal barrier function and visceral nociception^Citation30
		Cacna1c	miR-342-3p		Colonic motility, pain signaling, and smooth muscle function^Citation31
				miR-338-3p	Intestinal permeability and visceral nociception^Citation30
	Aqp8		miR-29a-3p		Intestinal permeability^Citation28
		Ocln	miR-122-5p		Intestinal barrier function^Citation32
		Myocd			Regulation of GI smooth muscle cell phenotype^Citation26
		Tjp1 (ZO-1)	miR-29a-3p	miR-219a-5p	Intestinal barrier function^Citation30,Citation33
	Pkib				Visceral sensitivity^Citation34
	Prdx1				LPS-induced inflammatory damage^Citation35
				miR-106b-5p	Mapk signaling pathway^Citation36
				miR-148a-3p	IBS-D symptoms^Citation37
				miR-190a-5p	IBS-D symptoms^Citation37
				miR-194-5p	IBS-D symptoms^Citation37

Figure 8. miRNA-mRNA interactions in mechanisms associated with pain in IBS. DE genes involved in mechanisms that were previously associated with pain in IBS were added to the network along with their DE interacting miRNAs from our dataset. LPS was added to the network for activity pattern prediction. Activation/inhibition predictions were obtained using the MAP prediction tool on IPA. Targets with names in purple and miRnas with names in blue were dysregulated in cluster 1 and 2 in the same direction. Targets and miRNAs with names in black were dysregulated in cluster 1 only.

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Data availability statement

The datasets generated during this study are available in the National Center for Biotechnology Information (NCBI) BioProject Repository https://www.ncbi.nlm.nih.gov/bioproject under BioProject PRJNA858800.