Rapid transcriptional and metabolic adaptation of intestinal microbes to host immune activation

Abstract

The gut microbiota produces metabolites that regulate host immunity, thereby impacting disease resistance and susceptibility. The extent to which commensal bacteria reciprocally respond to immune activation, however, remains largely unexplored. Herein, we colonized mice with four anaerobic symbionts and show that acute immune responses result in dramatic transcriptional reprogramming of these commensals with minimal changes in their relative abundance. Transcriptomic changes include induction of stress-response mediators and downregulation of carbohydrate-degrading factors such as polysaccharide utilization loci (PULs). Flagellin and anti-CD3 antibody, two distinct immune stimuli, induced similar transcriptional profiles, suggesting that commensal bacteria detect common effectors or activate shared pathways when facing different host responses. Immune activation altered the intestinal metabolome within 6 hours, decreasing luminal short-chain fatty acid and increasing aromatic metabolite concentrations. Thus, intestinal bacteria, prior to detectable shifts in community composition, respond to acute host immune activation by rapidly changing gene transcription and immunomodulatory metabolite production.

Keywords: PUL; SCFA; accute inflammation; immune responses; meta-transcriptome; microbiota; polysaccharide utilization loci; stress; transcriptome.

Figure 1.. Flagellin treatment modulates transcriptional activity of the microbiota without affecting community structure.

A) Mice were treated with ampicillin and reconstituted with the CBBP consortium. 14 days later ceca were harvested and sectioned, and species-specific FISH staining was performed. Shown is 1 representative image with single as well as merged channels (n=3, 2 independent experiments performed). B) RNA was extracted from cecal contents of animals reconstituted as described in A) and sequenced. Shown is the functional annotation performed on the resulting reads using the Rast SEED Subsystem, at the Class level (n=3) (right), as well as on the respective genomes (left). C) CBBP-reconstituted mice were injected i.p. with flagellin (2.5 μg). Quantitative PCR was carried out for the depicted genes on cecal tissue harvested at the indicated times following treatment (n=7 from 2 independent experiments, shown are means ± SEM; multiple Wilcoxon tests vs baseline, *p<0.05, **p<0.01, ***p<0.001). D) Relative proportion of CBBP members in cecal content as quantified by 16s rRNA gene sequencing at the depicted time points following flagellin treatment (n=3, bars represent individual mice; shown is one representative of 2 experiments). E) Volcano plots showing genes significantly up- and down-regulated (in red and blue, respectively) by the depicted CBBP members, 6h post flagellin treatment. Numbers in corners indicate significantly differentially expressed genes (DEG, FDR < 0.05, log 2-fold change > 1) (n=3). F) Heatmaps depicting changes in the top variant DEG for each CBBP member at 0h (untreated), 6h and 24h following flagellin treatment (n=3). Shown are all DEG that could be annotated based on the SEED Subsystem, Class level. G) Gene set enrichment analysis was performed on gene expression data shown in Figure 1 F. Shown are SEED Subsystem Subclasses that were significantly enriched (p<0.05).

Figure 2.. Effects of in vivo anti-CD3 antibody treatment on a stable intestinal microbial consortium.

A) Mice were reconstituted with CBBP for 14 days and then injected i.p. with anti-CD3 (a-CD3) antibody (100 μg). Quantitative PCR was carried out for the depicted genes on cecal tissue harvested at the indicated time points following treatment (n=3, shown are means ± SEM; multiple t-tests vs baseline, *p<0.05, **p<0.01, ***p<0.001; similar results were obtained in at least 4 other experiments using mouse strains with different microbiota). B) Relative proportion of CBBP members in cecal content at the depicted time points following treatment, as quantified via 16s rRNA gene sequencing (n=3, bars represent individual mice; shown is one representative of 4 experiments). C) Volcano plots showing genes significantly up- and down-regulated (in red and blue, respectively) by the depicted CBBP members, 6h post anti-CD3 antibody treatment of the mice. Numbers in corners indicate significantly differentially-expressed genes (DEG) (n=3). D) Heatmaps depicting significant DEG for each CBBP member at 0h (untreated), 6h and 24h following anti-CD3 antibody treatment (n=3). Data shown in this figure derive from the same experiment shown in Figure 1, untreated animals (0h time point) are in common.

Figure 3.. Transcriptional adaptation of commensal microbes to distinct immune stimuli.

A) CBBP-reconstituted mice were treated with either anti-CD3 (a-CD3) antibody or flagellin, and sacrificed 6h or 24h post-treatment to perform RNAseq on luminal RNA. Shown is a Principal Component Analysis on rlog transformed counts of all differentially expressed genes (see also Supplementary Figure 3A for PCA on all genes). Polygons represent different time points (n=3 per time point/treatment. Data shown are from the experiment depicted in Figure 1 D–F and Figure 2 B–D). B) Correlation between differential expression of genes in CBBP members following mouse treatment with anti-CD3 antibody or flagellin. Each dot represents a gene, color code indicates significance of the comparison 6h vs baseline (for each treatment). Pearson’s correlation coefficient and p-value are indicated at the top (n=3 per group). C) Volcano plots highlighting genes encoding for the depicted molecules 6h post treatment. Genes of interest are highlighted and color-coded in yellow if present but not-significantly modulated, and in blue if significantly modulated (n=3 per group).

Figure 4.. Impact of community composition on transcriptional adaptation of commensals to immune response.

A) Germ-Free (GF) mice were reconstituted with CBBP (4mix) or a consortium lacking BS (3mix) for 14 days, then administered anti-CD3 antibody (a-CD3) and sacrificed 6h post-treatment. Shown is fecal microbiota composition as assessed by 16s rRNA gene sequencing, prior to treatment (0h) and 6h after treatment. Shown is also composition of the input (n=3 per group, 1 pellet not obtained for untreated mouse #10). B) Venn diagrams depicting the numbers of differentially regulated genes (padj<0.05, absolute log2 fold-change>1) by CB, BP and PD 6h post anti-CD3 antibody treatment, in the absence or presence of BS (3-mix and 4-mix, respectively). Gray circles represent genes differentially expressed only in 3-mix, blue circles represent genes differentially expressed only in 4-mix, and purple intersections represent genes modulated in both contexts. C) Principal Component Analysis of rlog-transformed counts for all genes that were significantly differentially expressed in at least one comparison. Polygons represent different groups (consortium~time point) and colors represent time point (n=3 per group). D) Expression levels of manganese catalase genes in CB, BP and PD, 6h post anti-CD3 treatment in the presence or absence of BS (4mix vs 3mix). Shown are the adjusted pvalue and log2 fold change in expression of the genes (6h vs 0h) across the two mixes (n=3). E) Correlation plots showing log2 fold change values for significantly DEG between 6h post anti-CD3 antibody administration and baseline in the depicted consortia. Each dot corresponds to a gene, color code is: blue = DE only in 4-mix; black = DE only in 3-mix; purple = DE in both. Pearson’s correlation coefficient and p-value are shown on top (n=3 per group). F) Representative volcano plot DEG for BP in the context of 3mix or 4mix, 6h post anti-CD3 antibody treatment. Genes DE in both consortia are shown in purple, genes that are DE in only one consortium are shown in blue. Upper panels: DEG in common are in front; lower panels: unique DEG are in front. Some of the most up-/down-regulated genes are highlighted by colored filling; top panels: common 3-mix/4-mix DEG are highlighted; bottom panels: common 3-mix/4-mix DEG are highlighted.

Figure 5.. Operon structure in CBBP genomes and adaptation modules.

A) RNA sequencing reads from experiment shown in Figure 4 (GF mice, 4-mix) were used to identify operons in the CBBP genomes using a previously published approach (McClure et al., 2013). Bar graphs depict percentage of genes organized into operons for each CBBP member; numbers indicate absolute number of operons. B) Boxplot depicting operon size in CBBP members. Middle line indicates median, box ranges indicate 25 and 75 percentile, whiskers indicate extremes. Dots represent mean values. C) Distribution of operon sizes in CBBP members. Dots indicate presence of an operon with the corresponding size. D) Percentage of operons containing no, all or some unclassified genes, annotated as hypothetical protein by PATRIC. E) Operon organization of top up and down-regulated genes in BS, following anti-CD3 treatment. Bars represent the mean log2-fold change ± SD for genes significantly modulated across 2 independent experiments (n=3 for each). Alternating colors (red, gray) delimitate distinct operons, i.e. color switch corresponds to end of an operon (see Supplementary Figure 5 for a complete depiction of all operons fulfilling the above selection criteria in CBBP members).

Figure 6.. Host immune activation promotes rapid metabolic shifts in the gut lumen.

A) A) Metabolic profile of CBBP members cultured for 48h in BHI+. Heatmap shows fold-enrichment/depletion of the respective metabolite with reference to the plain medium (shown are average values from 2 independent experiments). B) Antibiotic-treated mice were reconstituted with CBBP (4mix) for 14 days and then treated with anti-CD3 antibody (a-CD3). Cecal contents were collected 6h and 24h post-treatment (or in untreated mice, 0h) and subject to metabolomics analysis for the depicted compounds. Shown are the results for a selection of relevant metabolites) (data are cumulative from 5 independent experiments for the 0h and 6h time points, 2 independent experiments for the 24h time point, for a total of 14, 15 and 6 mice, respectively). C) Naïve SPF mice were treated with anti-CD3 antibody. Cecal contents were collected 6h and 24h post-treatment and subjected to metabolomics analysis for the depicted compounds. Shown are the results for the metabolites also shown in (B) (n=5 per group; Wilcoxon test using 0h as a reference test, *p<0.05, **p<0.01, ***p<0.001, ****p<0.0001)