Gut microbiome composition and function in experimental colitis during active disease and treatment-induced remission - PubMed (original) (raw)

doi: 10.1038/ismej.2014.3. Epub 2014 Feb 6.

Patrick Veiga 2, Leslie H Wardwell-Scott 3, Timothy Tickle 1, Nicola Segata 1, Monia Michaud 1, Carey Ann Gallini 1, Chloé Beal 4, Johan E T van Hylckama-Vlieg 4, Sonia A Ballal 5, Xochitl C Morgan 1, Jonathan N Glickman 6, Dirk Gevers 7, Curtis Huttenhower 8, Wendy S Garrett 9

Affiliations

Gut microbiome composition and function in experimental colitis during active disease and treatment-induced remission

Michelle G Rooks et al. ISME J. 2014 Jul.

Abstract

Dysregulated immune responses to gut microbes are central to inflammatory bowel disease (IBD), and gut microbial activity can fuel chronic inflammation. Examining how IBD-directed therapies influence gut microbiomes may identify microbial community features integral to mitigating disease and maintaining health. However, IBD patients often receive multiple treatments during disease flares, confounding such analyses. Preclinical models of IBD with well-defined disease courses and opportunities for controlled treatment exposures provide a valuable solution. Here, we surveyed the gut microbiome of the T-bet(-/-) Rag2(-/-) mouse model of colitis during active disease and treatment-induced remission. Microbial features modified among these conditions included altered potential for carbohydrate and energy metabolism and bacterial pathogenesis, specifically cell motility and signal transduction pathways. We also observed an increased capacity for xenobiotics metabolism, including benzoate degradation, a pathway linking host adrenergic stress with enhanced bacterial virulence, and found decreased levels of fecal dopamine in active colitis. When transferred to gnotobiotic mice, gut microbiomes from mice with active disease versus treatment-induced remission elicited varying degrees of colitis. Thus, our study provides insight into specific microbial clades and pathways associated with health, active disease and treatment interventions in a mouse model of colitis.

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Figures

Figure 1

Figure 1

Experimental design and influence of interventions on the gut microbiome. (a) Study experimental schema. (b) Histologic colitis scores. Symbols represent individual mice. Error bars indicate mean±SEM. Colitis scores >2 indicate active colitis and scores ⩽2 remission. Sham, untreated, handling control; Gent, gentamicin; Metro, metronidazole; Vanco, vancomycin; Immunomods, anti-TNF-α or TRegs; MC, non-fermented milk control; FMP, fermented milk product; Diet, dietary intervention with FMP or MC in addition to ad libitum chow. (c) PCoA using unweighted UniFrac distances of gut microbial communities obtained from stool samples collected at baseline (pre-intervention) and upon treatment completion (post-intervention). The first two principal coordinates (PC) from the PCoA are plotted. Symbols represent data from individual mice, color-coded by the indicated metadata. (d) Gut microbiomes were clustered by similarity using the UPGMA clustering algorithm on the unweighted UniFrac distances. Samples from individual mice were clustered by the indicated intervention class (outside ring) or by the specific treatment (inside ring). (e) Phylum-level phylogenetic classification of 16S rRNA gene sequences. Bars represent mean relative abundances for each pre- or post-intervention group.

Figure 2

Figure 2

Antibiotic-driven microbial community shifts may be influenced by early-life exposures and are associated with specific clade responses. (a) Family-level phylogenetic classification of 16S rRNA gene sequences from stool samples collected pre- and post-intervention. Bars represent relative abundances of samples from individual mice. Labels indicate families with average relative abundances ⩾1% in at least one pre- or post-intervention group. Remaining families and reads assigned to higher level taxonomies were binned together in their associated phylum as ‘other' or ‘unclassified' (uncl.), respectively. (b) PCoA plots of the unweighted UniFrac distances of post-intervention stool samples from metronidazole- (_n_=10) and vancomycin (_n_=10)-treated mice. The first two PCs from the PCoA are plotted. Symbols represent data from individual mice, color-coded by the indicated metadata. For caging, M, metronidazole-treated; V, vancomycin-treated. (c) UPGMA clustering algorithm on the unweighted UniFrac distances of samples, color-coded by breeding pair. The letter and number assigned to the sire and dam, respectively, correspond to the PCoA plots in b. (d) Differentially abundant microbial clades in stool from mice with active colitis versus remission. Symbols represent data from individual mice from three independent experiments. Error bars indicate±SEM. Kruskal–Wallis test with Dunn's multiple comparison test: * or +P<0.05; ** or ++P<0.01; and *** or +++P<0.001.

Figure 3

Figure 3

Immunomodulatories influence low abundance gut microbial community members and drive distinct microbial responses. (a) Left panel: Venn diagram of exclusive and shared species-level phylotypes (non-singleton OTUs, at ⩾97% sequence identity) in anti-TNF-α injected (_n_=10), TReg infused (_n_=10) or sham (untreated; _n_=12) mice. In total, 4420 OTUs were present across samples. Right panel: number of 16S rRNA gene sequences in each of the indicated segments of the Venn diagram. In total, 265 344 sequences were present across samples. (b) Differentially abundant microbial clades in stool from immunomodulatory-treated (anti-TNF-α or TRegs; _n_=20) versus sham (_n_=12) mice. (c) Differentially abundant microbial clades in stool from anti-TNF-α-(_n_=10) versus TReg (_n_=10)-treated mice. For cladograms, white circles represent non-significant microbial clades.

Figure 4

Figure 4

A FMP influences the microbial communities of the gut and MLNs. (a) Differentially abundant microbial clades in stool collected before and after FMP (_n_=10). (b) Differentially abundant microbial clades in stool after FMP (_n_=10) versus MC (_n_=10). (c) PCoA plots of the unweighted UniFrac distances of post-intervention stool samples (FMP, _n_=10; MC, _n_=10) and MLNs (FMP, _n_=21; MC, _n_=16; 5 MLNs/mouse). The first two PCs from the PCoA are plotted. Symbols represent data from individual mice, color-coded by the indicated metadata. (d) Phylum-level phylogenetic classification of 16S rRNA gene sequences from pre-intervention (_n_=20) and post-intervention stool samples (FMP, _n_=10; MC, _n_=10) and post-intervention MLNs (FMP, _n_=21; MC, _n_=16; 5 MLNs/mouse). Pie charts represent the mean relative abundances of phyla across mice from each group. (e) Differentially abundant microbial clades in post-intervention samples from stool (FMP, _n_=10; MC, _n_=10) versus MLNs (FMP, _n_=21; MC, _n_=16; 5 MLNs/mouse). (f) Differentially abundant microbial clades in post-intervention MLNs of FMP- (_n_=21) versus MC (_n_=16)-fed mice. *, aerotolerant genera;+, genera shared between MLNs and deep colonic crypt communities (Pédron et al., 2012). For cladograms, white circles represent non-significant microbial clades.

Figure 5

Figure 5

Gut microbiome composition in active colitis and treatment-induced remission with in vivo functional validation of pro-inflammatory activity in gnotobiotic TRUC mice. (a) Differentially abundant microbial clades in stool from mice with active colitis (_n_=31) versus remission (_n_=51) upon intervention completion. For cladogram, white circles represent non-significant microbial clades. (b) Experimental schema of 8-week gnotobiotic TRUC association with conventionally raised, SPF TRUC donor stool. SPF donors were treated for 4 weeks prior to stool collection. Stool from the indicated number of donors was pooled and transplanted into gnotobiotic TRUC recipients. (c) Histologic colitis scores of donors and recipients. Symbols represent data from individual mice. Error bars indicate±SEM. Mann–Whitney test: *P<0.05. (d) B. lactis and L. lactis levels quantified by RT-qPCR in stool from fermented milk (FMP)-treated donors (pooled; _n_=4) and their corresponding GF recipients (_n_=5).

Figure 6

Figure 6

Inferred gut microbiome functions associated with active colitis and treatment-induced remission. Relative abundances of KO gene families grouped into BRITE functional hierarchies, as inferred by PICRUSt from 16S rRNA gene sequences. Differentially abundant microbial functions associated with active colitis (_n_=31) versus remission (_n_=51) upon intervention completion organized by KEGG BRITE categories (a) and pathways (b–d). Boxplots denote top quartile, median and bottom quartile. Whiskers and outliers are plotted by the Tukey method. (e) ELISA-based determinations of fecal dopamine levels. Symbols represent data from individual mice from three independent experiments. Mann–Whitney test: *P<0.05; **P<0.01 and ***P<0.001.

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