Exclusive enteral nutrition initiates individual protective microbiome changes to induce remission in pediatric Crohn's disease

Abstract

Exclusive enteral nutrition (EEN) is a first-line therapy for pediatric Crohn's disease (CD), but protective mechanisms remain unknown. We established a prospective pediatric cohort to characterize the function of fecal microbiota and metabolite changes of treatment-naive CD patients in response to EEN (German Clinical Trials DRKS00013306). Integrated multi-omics analysis identified network clusters from individually variable microbiome profiles, with Lachnospiraceae and medium-chain fatty acids as protective features. Bioorthogonal non-canonical amino acid tagging selectively identified bacterial species in response to medium-chain fatty acids. Metagenomic analysis identified high strain-level dynamics in response to EEN. Functional changes in diet-exposed fecal microbiota were further validated using gut chemostat cultures and microbiota transfer into germ-free Il10-deficient mice. Dietary model conditions induced individual patient-specific strain signatures to prevent or cause inflammatory bowel disease (IBD)-like inflammation in gnotobiotic mice. Hence, we provide evidence that EEN therapy operates through explicit functional changes of temporally and individually variable microbiome profiles.

Keywords: EEN; FMT; bacterial strain dynamics; exclusive enteral nutrition; ex vivo gut chemostat model; fiber; medium-chain fatty acids; metagenomics; microbiome; multi-omics data integration; pediatric Crohn’s disease.

Figure 1.. Fecal microbial and metabolic changes in response to EEN

Patients of the pediatric IBD cohort, with the focus on 20 newly diagnosed and treatment-naive CD patients, receiving EEN induction therapy. Longitudinal collected samples (n = samples, N = patients) that were used for 16S rRNA amplicon and metagenomic sequencing as well as metabolome analysis are shown. Paired samples (n = 60) were used for data integration of 16S rRNA and metabolome data (samples highlighted in blue = taken under EEN, orange = taken PostEEN). (B) Weighted pediatric Crohn’s disease activity index (wPCDAI) over time (EEN shaded blue), remission achieved below 12.5 points (dashed line). pE, PreEEN, EE, EEN, PE, PostEEN. (C) Beta-diversity analysis of the fecal microbiota samples. The circular dendrogram shows differences in beta-diversities from the longitudinal microbial profiling based on generalized UniFrac distances between the 291 stool samples of the 20 patients. Indicated in color code are the patients and samples collected during EEN. Taxonomic composition of fecal samples at the phylum level is shown as color-coded stacked bar blots around the dendrogram. Branch color indicates results of unsupervised clustering. Patient color code found in (B). (D) Visualization of untargeted metabolome samples from 18 newly diagnosed pediatric CD patients receiving EEN therapy: complete clustering with Euclidean distance of longitudinal samples from 18 CD-EEN patients (n = 145), patient color code found in (B). (E) Beta-diversity MDS plot samples during EEN (n = 89, active: 55, inactive: 34) vs. PostEEN (n = 188, active: 41, inactive: 147). (F) Analyses of untargeted metabolomics with representative PCA plot comparing samples during EEN (n = 35, active: 21, inactive: 14) and PostEEN (n = 106 active: 21, inactive: 85). Axes indicate principal components (PC), with PC1 representing the most variation (%) and PC2 representing the second most variation (%). (E and F) Coefficients were tested with a t test, reported p values are Bonferroni-corrected; D, diet; A, activity; D:A, interaction term between diet and activity. (G and H) Heatmaps depicting the abundances of the top selected feature from the correlation network Figure S2. Selected sPLS-DA features were subsetted by their mean importance (see STAR Methods: data integration of 16S rRNA amplicon data with metabolomics and metagenomics for details). All values shown are feature-wise Z scores. Information on association with EEN (blue), PostEEN (orange), sample collection under which diet (EEN blue), PostEEN (orange), community association (1–5) are indicated; (G) zOTUs,*BONCAT responders Figure 2, (H) metabolites.

Figure 2.. MCFA-induced activation of translationally active gut bacteria

(A) Experimental design. MP1, MP2, and MP3 stool samples, previously stored in glycerol, were incubated under anaerobic conditions and in the presence of medium-chain fatty acids (MCFAs) (lauric acid [LA], decanoic acid [DA], and octanoic acid [OA]) and of the cellular activity marker (L-azidohomoalanine [AHA]). Translationally active bacterial cells labeled with alkyne-modified dye were sorted with BONCAT-FACS. The taxonomic profiles of sorted and unsorted cells were identified by 16S rRNA genes with amplicon sequencing. (B) Representative confocal microscopic images of one stool sample (MP2) stimulated with OA. Pink: active cells (BONCAT-Cy5); blue: all cells (DAPI). Scale bar is 10 μm. (C) Translationally active bacterial cells quantified in MP1, MP2, and MP3 patients. p values were calculated by Kruskal-Wallis test and Dunn test for multiple comparisons. *p < 0.05, **p < 0.01. ***p < 0.001, ****p < 0.0001. Error bars represent standard deviation of the mean. (D) Beta-diversity MDS plots show clustering of samples based on model patients and sorted-unsorted groups (perMANOVA p = 0.001 for both comparisons). MP1 = orange, MP2 = green, MP3 = turquoise, sorted cells = square, and unsorted cells = circle. (E) Relative abundances of significantly enriched and depleted zOTUs in MP1, MP2, and MP3. *zOUTs identified in network analyses Figures 1G and S2. p values were calculated by ANOVA and Tukey’s test for multiple comparisons. *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001. Boxplot: boxplot medians (center lines), interquartile ranges (box ranges), whisker ranges.

Figure 3.. Species and strain turnover during the transition off of EEN

(A and B) Turnover of taxonomic composition during the transition from EEN to a PostEEN diet of both (A) zOTU and (B) strain compositions. The three lines reflect cubic spline regression of Bray-Curtis dissimilarities against time, averaged across subjects, and offset by an independent intercept for each pair type. (C) Volcano plots showing COGs with significant changes in normalized abundance at the transition off of EEN (Wilcoxon test at false discovery rate [FDR] < 0.1). Here, 54 COGs were at significantly greater relative depth during PostEEN (orange points) and 529 during EEN (blue). (D–F) Composition over time of strains within (D) E. bolteae (red box), (E) E. clostridioformis (blue box), and (F) E. coli (black box), with all three abundant in the CD-EEN patients and all three species having notable strain dynamics during and after EEN. Strain genotypes and fractions were estimated from shotgun metagenomic data. Fractions of abundant strains (colored bars) are shown across samples from individual subjects (P01, P02…), before EEN (‘‘pE’’ labels on x axis), during (‘‘EE’’), and after (‘‘PE’’). *Samples used as donor samples in other experiments. Strain fractions for the species sum to 1; minor strains are summed together and shown in gray. An analogous plot for B. uniformis is in Figure S4D.

Figure 4.. Functional validation of gut-microbiota-dependent EEN efficacy using ex vivo fermentation and gnotobiotic humanized mice

(A) Experimental scheme: FMT 1, patient sample is transferred into GF mice at the age of 8 weeks for 4 weeks. Same patient sample is also transferred (FMT 2) in an ex vivo gut chemostat model and treated with medium simulating EEN (EEN-like, devoid of fibers) or a regular diet (fiber-rich diet, FRD). Fermented sample is transferred (post ex vivo) into GF mice (age of 8 weeks) for 4 weeks (FMT 3—EEN-like medium conditioned, FMT 4—FR medium conditioned). (B and C) Transfer of patient sample: patient’s disease state with wPCDAI and fecal calprotectin levels, and therapy response over time with maintenance therapy (MTX, anti-TNF) and sampling time point. (B) Model patient (MP) 1, sample (red arrow) collected PreEEN in active disease. (C) MP2, sample (blue arrow) collected in EEN-induced remission. (D) Mouse histopathology scoring of colon Swiss rolls of FMT 1, 3, and 4 from MP1. (E) Mouse histopathology scoring of colon Swiss rolls of FMT 1, 3, and 4 from MP2. (F and G) Mouse transfer experiments from FMT 3 and 4: representative (mean of group) H&E-stained sections of colonic Swiss rolls and corresponding higher magnifications for Il10^−/− mice (scale bars, 500 μM; HS, histopathology score; respective controls in extended data, Figure 3) with Tnf gene expression levels (fold of control) in distal colon. (F) MP1. (G) MP2. (H) Experimental scheme: patient sample from MP3 is transferred into GF mice (FMT 1) at the age of 8 weeks, for 4 weeks. Same patient sample is also transferred in an ex vivo gut chemostat model and treated with EEN-like medium. Fermented sample is transplanted (post ex vivo) into GF mice at the age of 8 weeks, for 4 weeks, getting either chow diet (FMT 3) or EEN-like purified diet (EEN-like) 1 week prior to FMT (FMT 4). (I) MP3 sample for transfer (EEN): patients’ disease state with wPCDAI and fecal calprotectin, therapy response over time, maintenance therapy (MTX, anti-TNF), and sampling time point of transferred fecal sample (blue arrow); gray arrow indicates endoscopy performed in the patient PostEEN and the picture taken during endoscopy shows active ileitis. J Mouse histopathology scoring of colon Swiss rolls of FMT 1, 3, and 4 from MP3. (K) Mouse transfer experiments from FMT 3 and 4 from MP3: representative (mean of group) H&E-stained sections of colonic Swiss rolls and corresponding higher magnifications for Il10^−/− mice (scale bars, 500 μM; HS, histopathology score; respective controls in extended data Figure 3) with Tnf gene expression levels (fold of control) in distal colon. (A and H) Created with BioRender.com. Data are represented by (D)–(G), (J), and (K) mean ± SD of six biological replicates. p values were calculated by Mann-Whitney test (F, G, and K) or two-way ANOVA with Tukey multiple pairwise comparisons test (D, E, and J). *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001.

Figure 5.. Strains associated with active or inactive disease in Il10^−/− mice

(A–C) Transfer overview of donor sample (gray) from FMT 1 (black), FMT 3 (EEN-conditioned, blue), and FMT 4 (FR-conditioned, brown) into Il10^−/− mice. Mouse inflammation endpoints are shown (triangles: red = active, green = inactive). Venn diagrams tally strains detected in inflamed (red) and non-inflamed (green) Il10^−/− mice or found in both conditions (yellow) for (A) MP1, (B) MP2, and (C) MP3 for each FMT and combined FMT 1, 3, and 4. (D–F) LEfSe (linear discriminant analysis effect size) analysis of differentially abundant bacteria at species level based on metagenomic data in the recipient inflamed (active, red) or non-inflamed (inactive, green) Il10^−/− mice with abundance of strains in each condition. Different strains are labeled with different numbers. (D) MP1. (E) MP2. (F) MP3. (G) Venn diagrams shows shared or individual species (left) or strains (right) detected in MP1, MP2, and MP3. *zOTUs found in network analyses Figures 1G and S2.