WO2025165867A1 - Microbiome engineering to treat colitis - Google Patents

Abstract

Provided herein are compositions comprising in vivo succinate-producting microorganisms, e.g., Bacteroides and Prevotella species (preferably Bacteroides thetaiotaomicron (e.g., VPI 5482), Bacteroides vulgatus (e.g., NCTC 11154, Prevotella copri (e.g., DSM 18205)), Parabacteroides (e.g., Parabacteroides distasonis), and Bacilli (e.g. Lactobacillus animalis), and methods of use thereof in treating or reducing risk of developing an intestinal infection, optionally an infection with Campylobacter, Salmonella, E. coli, Shigella, Listeria monocytogenes, Vibrio, Enteropathogenic E. coli, Klebsiella, or Clostridioides difficile, or promoting expansion of colonic tuft cells, in a subject.

Description

MICROBIOME ENGINEERING TO TREAT COLITIS

CLAIM OF PRIORITY

This application claims the benefit of U.S. Provisional Patent Application Serial No. 63/626,305, filed on January 29, 2024. The entire contents of the foregoing are hereby incorporated by reference.

STATEMENT REGARDING FEDERAL FUNDING

This invention was made with government support under Grant No. W81XWH-20-2-0013 awarded by the Congressionally Directed Medical Research Programs (CDRMP), and Grant Nos. AI172987, AGO75283, AI155727, and AI007349 awarded by the National Institutes of Health. The government has certain rights in the invention.

TECHNICAL FIELD

Provided herein are compositions comprising in vivo succinate-producing microorganisms, e.g., Bacteroides and Prevotella species (preferably Bacteroides thetaiotaomicron VPI 5482, Bacteroides vulgatus NCTC 11154, and Prevotella copri DSM 18205), and methods of use thereof in treating or reducing risk of developing a Clostridioides difficile infection, or promoting expansion of colonic tuft cells, in a subject.

BACKGROUND

Microbiota-produced metabolites have a crucial role in modulating local and peripheral immune signatures (Blander et al., 2017; McCarville el al., 2020) with three prominent examples that include short chain fatty acids (SCFAs) (Arpaia et al., 2013; Atarashi et al., 2013; Atarashi et al., 201 1 ; Foley et al., 2021 ; Schulthess et al., 2019; Tanoue et al., 2016), indoles (Aoki et al., 2018; Goettel et al., 2016) and secondary bile acids (Foley Sage et al., 2022; Ridlon et al., 2014).

SUMMARY

Metabolic byproducts from gut bacteria help regulate host immune responses. Succinate plays a dual role: it drives the differentiation of tuft cells (TCs) in the small intestine, leading to type 2 immune protection against parasites, but also enhances the growth of the pathogen Clostridioides difficile in the large intestine. The relationship between succinate, TCs, and C. difficile in the large intestine remains unclear. We have identified a three-way interaction between commensal microbes, C. difficile, and the host centered around succinate. Removing specific gut bacteria leads to increased type 2 cytokines, expanding TCs in the colon. Controlled microbiome supplementation experiments confirmed the microbiome's role in regulating colonic TCs and type 2 cytokines. Additionally, succinate-deficient Bacteroides thetaiotaomicron (Afrd) reduced enhanced type 2 immunity in mice. Prophylactic administration of succinate-producing bacteria reduced C. difficile-induced illness and death in mice. This protection relies on the TCS pathway, as confirmed through experiments with Pou2f3+/- and Pou2f3-/- mice. Succinate, an intermediate metabolite during short-chain fatty acid production, often increases during gut dysbiosis. The intestinal epithelial barrier is the first line of defense against enteric pathogens. Activating TCs in the colon through microbiota-produced succinate seems to be the host's mechanism for countering microbiome-driven cues that facilitate pathogen invasion.

Thus, provided herein are compositions comprising at least two, three, four, or five in vivo succinate-producing microorganisms (i.e., microorganisms that produce succinate in vivo), e.g., Bacteroides and Prevotella species (preferably Bacteroides thetaiotaomicron (e.g., VPI 5482), Bacteroides vulgatus (e.g., NCTC 11154), Prevotella copri (e.g., DSM 18205)), Parabacteroides (e.g., Parabacteroides distasonis), and Bacilli (e.g., Lactobacillus animalis), as described herein.

In some embodiments, the compositions further comprise a buffer or carrier. In some embodiments, the compositions are food compositions, e.g., a liquid or solid food.

In some embodiments, the compositions comprise only one, two, three, four, or five of the succinate-producing microorganisms, and can comprise only those three and no other microorganisms, or can comprise up to one, two, three, four, five, six, seven, eight, nine, ten, 20, 25, 30, 35, 40, 45, or 50 additional species of microorganisms. In some embodiments, the microorganisms in the composition consist of only Bacteroides thetaiotaomicron (e.g., VPI 5482), Bacteroides vulgatus (e.g., NCTC 11154), and Prevotella copri (e.g., DSM 18205), and optionally one or both of a Parabacteroides (e.g., Parabacteroides distasonis), and Bacilli (e.g., Lactobacillus animalis). Also provided herein are methods for treating or reducing risk of developing an intestinal infection in a subject, optionally an infection with Campylobacter. Salmonella, E. coll, Shigella, Listeria monocytogenes. Vibrio, Enteropathogenic E. coli, Klebsiella, or Clostridioides difficile, the method comprising administering a composition as described herein to a subject in need thereof. Further provided are the compositions described herein for use in such methods. In some embodiments, a subject is at risk of developing an intestinal infection is a subject who is in or is about to be in a communal living situation, or who is being treated or about to be treated with an antibiotic that increases the risk of developing the intestinal infection. In some embodiments, the antibiotic is cefoperazone, clindamycin, cefixime, cefdinir, cefuroxime, cefpodoxime, amoxicillin/clavulanate, ciprofloxacin, moxifloxacin, dicloxacillin, or cefaclor.

Additionally, provided herein are methods of promoting expansion of colonic tuft cells in a subject, the method comprising administering a composition as described herein to a subject in need thereof. Further provided are the compositions described herein for use in such methods.

Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. Methods and materials are described herein for use in the present invention; other, suitable methods and materials known in the art can also be used. The materials, methods, and examples are illustrative only and not intended to be limiting. All publications, patent applications, patents, sequences, database entries, and other references mentioned herein are incorporated by reference in their entirety. In case of conflict, the present specification, including definitions, will control.

Other features and advantages of the invention will be apparent from the following detailed description and figures, and from the claims.

DESCRIPTION OF DRAWINGS

FIGs. 1A-G: Vancomycin administration expands tuft cells and IL-25 in the proximal colon and leads to the enrichment of Bacteroides thetaiotaomicron in the microbiome. A. Following the approach from (Buonomo et al., 2016) IL-25 was measured by ELISA in the proximal colon of C57BL/6 wild-type mice treated with various antibiotics via oral gavage. Protein concentration in the lysate (pg/mL) was normalized by total protein in the sample (in mg) as in Buonuomo et al 2016. Data are representative of independent experiments repeated twice, using n=4-6 female mice per treatment group. ANOVA with Tukey post-hoc test was run to determine significant differences. Statistical significance was estimated at FDR of 0.05. B. IL-25 mRNA expression was measured by RT-qPCR in the proximal colon of C57BL/6 wild-type mice treated with different antibiotics. Data are representative of independent experiments repeated twice, using n=4-6 female mice per treatment group. ANOVA with Tukey post-hoc test was run to determine significant differences. Statistical significance was estimated at FDR of 0.05.C. Tuft cell percentages were estimated by quantifying the percentage of DCLK1+ EPCAM+ cells compared to total cells in C57BL/6 wild-type mice treated with the various antibiotics or untreated. Data are representative of independent experiments repeated twice, using n=4-6 female mice per treatment group. ANOVA with Tukey post-hoc test was run to determine significant differences. Statistical significance was estimated at FDR of 0.05. D. Expansion of TCs was confirmed via immunohistochemistry by enumerating the number of DCLK1 -expressing cells in the field of view (FOV). The white bar indicates a scale of 100 mm. Data are representative of independent experiments repeated twice, using n=4-6 female mice per treatment group. ANOVA with Tukey post-hoc test was run to determine significant differences. Statistical significance w as estimated at FDR of 0.05. E. Fecal pellets from vancomycin-treated mice and untreated mice were profiled for microbial composition via 16S rRNA sequencing at day 0, 1 and, 10 post-antibiotic treatment and showed enrichment in B. thetaiotaomicron in the samples after vancomycin treatment. F. Principal coordinate analysis of Bray-Curtis distance demonstrates sample segregation according to antibiotic treatment and (vancomycin vs. PBS) and treatment time (Day 0, 1, 10). The top 4 informative component loadings are shown as arrows, each represented by a corresponding microbiome sequencing variant (SV). G Differential analysis for samples at Day 10 was performed using DESeq2 and indicates a statistically significant enrichment of B. thetaiotaomicron (SVs) and Staphyloccous xylosus in vancomycin-treated mice compared to untreated. Significance was determined based on FDR of 0.05. Note: Animals assigned to different antibiotic treatments w ere first co-housed to homogenize the microbiome and then separated according to treatment. FIGs. 2A-F: Fecal microbiota transplantation experiments demonstrate the causal role of microbiome in the induction of Type 2 cytokines in the proximal colon, which correlates with the enrichment of Bacteroides thetaiotaomicron in the microbiome. A. IL-25, IL-5, and IL-13 concentrations were quantified in the proximal colon or B. in the ileum (for IL-25) of C57BL/6 wild-type mice (see Methods) receiving fecal matter transplants (FMTs) from mice treated with vancomycin or left untreated. Prior to FMT, mice were either untreated or pre-treated with an antibiotic combination of ampicillin, vancomycin, neomycin, and metronidazole (AVNM) to eliminate the resident microbiota (Background). Protein concentration in the lysate (pg/mL) was normalized by the total protein mass generated in the sample (in mg) as in Buonuomo et al 2016. Data are representative of independent experiments repeated twice, using n=4-6 female mice per treatment group. ANOVA with Tukey post-hoc test was run to determine significant differences. Statistical significance was estimated at FDR of 0.05. C. 16S rRNA sequencing was conducted on input FMT and fecal samples collected from mice post-FMT. D. Volcano plots were generated following differential analysis using DeSeq2 on fecal microbiome sequencing samples from mice pre-treated with AVNM and receiving FMT from either vancomycin-treated or untreated mice. Amplicon sequencing variants (SVs) from two succinate-producing species (B. thetaiotaomicron and E. faecalis) were found to be enriched in AVNM pre-treated mice receiving FMT from vancomycin-treated animals. Significance was determined based on FDR of 0.05. E. Permutation importance analysis followed by accumulated local effects calculations was carried out on the results of Random Forest Regression (RFR) modeling, which aimed to predict colonic IL-25 concentrations based on microbiome species abundance. Sequence variants associated with B. thetaiotaomicron and E. faecalis w ere identified as positive predictors of IL-25 concentrations in the colon. F. The significance and directionality inferred by the RFR model were confirmed through Elastic Net Regression modeling and Bayesian Variable Selection Linear Regression. SVs linked to B. thetaiotaomicron and E. faecalis were identified as significant predictors of IL-25 accumulation in the colon. Note: Animals assigned to different FMT treatment were first co-housed based on microbiome background in order to homogenize the microbiome and then separated according to FMT type. FIGs. 3A-I: Consortia of succinate-producing bacteria increase colonic TCs and type 2 cytokines and corresponds to higher colonic concentrations of succinate. A-C. IL-25, IL-13, and IL-5 protein concentrations were measured by ELISA (See Methods) in the colon, D-E. IL-25 protein concentrations were also measured in the cecum and the ileum of C57BL/6 wild-ty pe mice receiving succinate- producing or non-succinate-producing bacterial consortia. Protein concentration in the lysate (pg/mL) was normalized by total protein in the sample (in mg) as in Buonuomo et al 2016. Data are representative of independent experiments repeated twice, using n=4 female mice per treatment group. ANOVA with Tukey post-hoc test was run to determine significant differences. Statistical significance was estimated at FDR of 0.05. F. TC expansion was estimated via flow cy tometry' in the colon and ileum of AVNM-pretreated C57BL/6 wild-type mice that were administered a consortium of three succinate producers, three succinate non-producers, or PBS. TC ratios were assessed by gating on CD45-Epcam+Siglecf+ cells. Data are representative of independent experiments repeated twice, using n=4-5 female mice per treatment group. ANOVA with Tukey post-hoc test was run to determine significant deferences. Statistical significance was estimated at FDR of 0.05. G. Expansion of TCs in the colon was confirmed via immunohistochemistry' by enumerating the number of DCLK1 -expressing cells in the field of view (FOV). The white bar indicates a scale of 100 mm. Data are representative of independent experiments repeated twice, using n=4 female mice per treatment group. ANOVA with Tukey post-hoc test was run to determine significant differences. Statistical significance was estimated at FDR of 0.05. H. To demonstrate that phenoty pe induction corresponded to colonization by the bacterial consortia, we performed shotgun metagenomic sequencing. The relative abundances of the top 10 abundant species plus others are displayed as stacked bar plots and indicate colonic engraftment by the administered treatment consortia in the respective recipient mice. As expected, almost no colonization is observed in the ileum. I. Targeted metabolomics was performed to quantify concentrations of acetic acid, propionic acid, butyric acid, succinic acid, 2-methylbutryic acid, isolaveric acid, valeric acid, and succinic acid in the colon and the ileum of AVNM-pretreated C57BL/6 wild-ty pe mice receiving the succinate- or non-succinate-producing bacterial consortia. Data are representative of independent experiments repeated twice, using n=4 female mice per treatment group. Two-sample t-test was run to determine differentially abundant metabolites. Statistical significance was estimated at FDR of 0.05. Note: Animals assigned to treatment with different consortia were first cohoused to homogenize the microbiome before AVNM treatment and then separated according to type of bacterial consortium administered.

FIGs. 4A-I: Colonic induction of tuft cells and related cytokines is dependent on the presence of succinate-producing Bacteroides thetaiotaomicron and Pou213-dependent tuft cells. AVNM-treated mice were orally gavaged with heat-killed Bacteroides thetaiotaomicron, live wild-type B. thetaiotaomicron, succinate production-deficient B. thetaiotaomicron Afrd or PBS. A. TC hyperplasia in the colon of the mice receiving each treatment was assessed via immunohistochemistry by enumerating the number of DCLK1 -expressing cells in the field of view (FOV). The white bar indicates a scale of 100 mm. Data are representative of independent experiments repeated twice, using n=4 female mice per treatment group. ANOVA with Tukey post-hoc test was run to determine significant differences. Statistical significance was estimated at FDR of 0.05. B. TC percentage in the colon and the ileum of AVNM-treated mice gavaged with heat-killed B. thetaiotaomicron, live B. thetaiotaomicron, or B. thetaiotaomicron Afrd was evaluated via flow cytometry by gating on CD45-Epcam+Siglecf+ cells. Data are representative of independent experiments repeated twice, using n=4 female mice per treatment group. ANOVA with Tukey post-hoc test was run to determine significant differences. Statistical significance was estimated at FDR of 0.05. C. Relative mRNA expression measured by RT-qPCR of IL-25 in the proximal colon of AVNM-pretreated C57BL/6 wild-type mice treated with live B. thetaiotaomicron, or B. thetaiotaomicron Afrd. Data are representative of independent experiments repeated twice, using n=4 female mice per treatment group. Two-sample t-test was run to determine differentially abundant metabolites. Statistical significance was estimated at FDR of 0.05. D. Shotgun metagenomic sequencing was performed from colonic and ileal samples to evaluate colonization by B. thetaiotaomicron and succinate production-deficient B. thetaiotaomicron Afrd. We confirmed engraftment of B. thetaiotaomicron Afrd by mapping metagenomic reads to the B. thetaiotaomicron frd gene using bowtie2 and counting how many reads were mapped to frd in each treatment. E. Targeted metabolomics to estimate concentrations of acetic acid, propionic acid, butyric acid, succinic acid, 2-methylbutryic acid, isolaveric acid, valeric acid, and succinic acid in the colon and the ileum of AVNM-pretreated C57BL/6 wild-type mice administered heat-killed B. thetaiotaomicron, B. thetaiotaomicron wild-type or succinate production-deficient B. thetaiotaomicron Afrd. Data are representative of independent experiments repeated twice, using n=4 female mice per treatment group. ANOVA with Tukey post-hoc test was run to determine metabolites significantly different between treatments. Statistical significance was estimated at FDR of 0.05. F. Type 1, Type 3. and G. Type 2-associated cytokines measured by Luminex Multiplex ELISA in the proximal colon of AVNM-pretreated C57BL/6 wild-type mice treated with B. thetaiotaomicron or B. thetaiotaomicron Afrd. Data are representatives of experiments repeated twice, using n=4-8 female mice per treatment group. ANOVA with Tukey post-hoc test was run to determine metabolites significantly different between treatments. Statistical significance was estimated at FDR of 0.05. H. Estimation of TC percentage the colon and ileum of AVNM-pretreated Pou2f3 ^_. Pou2f3‘ ", and Pou2f3^+/+ mice treated with B. thetaiotaomicron or B. thetaiotaomicron Afrd. TC percentage was estimated via flow cytometry by gating on CD45-Epcam+Siglecf+ cells. We run ANOVA comparing the linear model with interaction, TC ~ Genotype + Treatment + Genotype:Treatment against the model with no interaction TC ~ Genotype + Treatment, to evaluate Pou2f3-dependent expansion of TCs in response to different microbial treatments. Pou2f3^+/’ and Pou2f3’ were littermates. Data are representatives of experiments repeated twice, using n=4 female mice per treatment group. Pou2f3 ', Pou213' ' were littermate, while Pou2f3^+/+ from a different litter. Pou2f3^+/", Pou2l " and Pou2f3^+/+ mice were co-housed for at least two weeks for basal microbiome equilibration before antibiotic pre-treatment and administration of bacteria. I. Relative mRNA expression measured by RT-qPCR of IL-25 in the colon and ileum of AVNM-pretreated Pou2f3' ' and Pou2f3^+/+ mice treated with B. thetaiotaomicron or B. thetaiotaomicron Afrd. Same modeling approach as in H. was applied. Data are representatives of experiments repeated twice, using n=4 female mice per treatment group. Pou2f3‘ ' and Pou2f3^{+ +} mice were co-housed for at least two weeks for basal microbiome equilibration before antibiotic pre-treatment and administration of bacteria.

FIGs. 5A-M: Protection from Clostridoides difficile morbidity and mortality is achieved by prophylactic administration of succinate-producing bacteria and depends on the presence of succinate and Pou213-dependent tuft cells. A. Experimental diagram of the cefoperazone-based C. difficile infection animal model which includes prophylactic administration of bacterial consortia and subsequent infection with Clostridoides difficile. B. Probability of survival and C. change in weight compared to weight pre-infection of C57BL/6 wild-type mice infected with C. difficile following treatment with a succinate-producing bacterial consortium. Representative of two independent experiments, n=5 female mice per treatment. Log-rank test was performed to evaluate difference in survival probability between each two treatments. Benjamini-Hochberg-corrected two-samples t-test at different time points was performed to assess differences in weight loss betw een every two treatments. D. Estimation of C. difficile toxin A (tcdA) titer per 100 mg of cecal content using RT-qPCR in cefoperazone-treated mice administered with succinate-producing bacterial consortium or PBS and infected with C. difficile, two days post-infection; n=10 female mice per treatment. Two-samples t-test w as performed to assess statistical significance. E. Probability of survival and F. change in weight compared to weight pre-infection of Pou2f3‘ ' or Pou2f3^+/’ mice infected with C. difficile following treatment with a succinate-producing bacterial consortium, the consortium after heat killing, or sterile PBS. Representative of tw o independent experiments, n=5 female mice per treatment. Log-rank test was performed to evaluate difference in survival probability between each two treatments. Benjamini-Hochberg- corrected two-samples t-test at different time points was performed to assess differences in weight loss between every two treatments. Pou2f3⁺ ' and Pou2f3’ ' were littermate cohoused after weaning. G. Probability of survival and H. change in w eight from pre infection of Pou2f3'^/_ and Pou2f3 mice infected with C. difficile following treatment with sterile PBS. Representative of two independent experiments, n=5 female mice per treatment. Log-rank test was performed to evaluate difference in survival probability between each two treatments. Benjamini-Hochberg-corrected tw o-samples t-test at different time points was performed to assess differences in weight loss between treatments. I. Comparison of colonic TC numbers in C57BL/6 wild-type mice given cefoperazone in the drinking water vs. PBS. TC percentage was evaluated via flow cytometry by gating on CD45-Epcam+Siglecf+ cells.

Representative of two independent experiments, n=4 female mice per treatment. Tw o- samples t-test w as performed to assess statistical significance. J. Comparison of TC numbers in the colon and ileum of Pou2f3^+/+ and Pou2f3 ^/_ mice administered with succinate producers or PBS immediately prior to C. difficile infection. Representative of two independent experiments. n=4 female mice per treatment. ANOVA with Tukey post-hoc test was run to determine metabolites significantly different between treatments. Statistical significance was estimated at FDR of 0.05. Pou2f3'^/_ and Pou2f3^+/+ mice were co-housed for at least two weeks for basal microbiome equilibration before antibiotic pre-treatment and administration of bacteria. K. Targeted metabolomics to evaluate SCFAs and succinate concentration from colonic and ileal content from the mice of panel J. L. Probability of survival and M. change in weight compared to weight pre-infection of C57BL/6 wild-type mice infected with C. difficile following treatment with B. thetaiotaomicron vs B. thetaiotaomicron Afrd. infection. Data are representative of two independent experiments repeated twice, n=10 female mice per treatment. Log-rank test was performed to evaluate difference in survival probability between each two treatments. Benjamini -Hochberg-corrected two-samples t-test at different time points was performed to assess differences in weight loss between treatments.

FIGs. 6A-C: Antibiotic administration increases the concentration of tuftcell associated cytokines in the (A) proximal colon, but not in the cecum (B) or ileum (C). Cytokines were measured by ELISA in the proximal colon of WT C57BL/6 mice treated with different antibiotics or left untreated. Protein concentration in the tissue lysate (pg/mL) was normalized by the total protein mass generated in the sample (in mg).

FIG. 7: Estimation of the percentage of tuft cells via flow cytometry by quantifying DLKC1+Epcam+ cells in mice treated with vancomycin, metronidazole, or PBS. Flow cytometry was used to estimate the percentage of DCLK1+ EPCAM+ CD45- cells compared to total cells in C57BL/6 wild-type mice treated with various antibiotics or left untreated. Mice treated with vancomycin had a significantly higher percentage of DCLK1+ Epcam+ CD45- tuft cells than mice treated with metronidazole or left untreated.

FIG. 8: Amphotericin B administration does not change the ability of vancomycin administration to upregulate IL-25, IL5, and IL-13 in the proximal colon. (A) IL-25 measured by ELISA in the proximal colon of C57BL/6 wild-type (WT) mice treated with antibiotics in combination with amphotericin B (ampB). (B) IL-13 measured by ELISA in the proximal colon ofWT mice treated with antibiotics in combination with ampB. (C) IL-5 measured by ELISA in the proximal colon of WT mice treated with antibiotics in combination with ampB. Protein concentration in the tissue lysate (pg/mL) was normalized by the total protein mass generated in the sample (in mg).

FIG. 9: Spearman’s correlation analysis results between the relative abundance of microbiota amplicon sequencing variants and colonic IL-25 in AVNM-treated animals receiving FMT from untreated or vancomycin-treated mice.

FIG. 10: Targeted metabolomics for succinate and SCFAs in mice treated with AVNM (baseline), AVNM + vancomycin FMT, AVNM + succinate-producing bacteria, AVNM + non-succinate producing bacteria, or untreated (PBS). ANOVA with Tukey post hoc was run to determine significant differences compared to AVNM (baseline). *** p < 0.0001, ** p < 0.01, * p < 0.05.

DETAILED DESCRIPTION

Previous research demonstrates that succinate produced by parasites in the small intestine (SI) is sensed by the taste-chemosensory epithelial tuft cells (TCs) (Chen et al., 2022; Howitt et al.. 2016; O'Leary et al.. 2019) and initiates a type 2 immune signaling cascade leading to parasite expulsion. (Loke and Cadwell, 2018; Luo et al., 2019; Miller et al., 2018; Nadjsombati et al. , 2018; Schneider et al., 2018a; von Moltke et al., 2016). TCs secrete IL -25, which acts on type 2 innate lymphoid cells (ILC2s) to produce the type 2 cytokines IL-4, IL-5, and IL-13 (Loke and Cadwell, 2018; Luo et al., 2019; Miller et al., 2018; Nadjsombati et al., 2018; Schneider et al. , 2018a; von Moltke et al. , 2016). These type 2 cytokines act synergistically to cause hyperplasia of TCs and mucus -producing goblet cells (Schneider el al., 2018b), increased SI length, increased contractility of the smooth muscle within the intestine, and recruitment of eosinophils to the epithelial barrier (Howitt et al., 2016). The physiological outcome of this process, usually referred to as the "weep and sweep" response (WSR), is the expulsion of the parasites via mucus production (weep) and increased motility' (sweep) (Howitt et al., 2016; von Moltke et al., 2016).

To date, most of the literature that details the function of TCs in the GI tract focuses on the small intestine and how these small intestinal TCs interact with, respond to intestinal parasites and their substrates, and initiate protection against them. Despite the interest in TCs in the GI tract and beyond, there is limited information about colonic TCs. TCs have been previously identified in the colon, and shown to possess the succinate receptor, SCNR1 (Lei et al., 2018). While some literature has demonstrated a potential impact of bacterial members of the microbiota on TCs, these papers have been limited to the small intestine and only relied on systemic antibiotic manipulation of the microbiome (Banerjee et al., 2020). Indeed, despite the fact that the microbiota predominantly occupies the colon compared to the SI by multiple orders of magnitude (Kennedy and Chang. 2020), there have been no reports of communication between TCs and commensal microbes in the colon.

Microbiome-produced metabolites modulate innate and adaptive immune responses in the intestine (Geva-Zatorsky et al. , 2017; Zheng et al. , 2020). Most mechanistic studies on this topic have focused on unveiling the causal role by which microbial-derived metabolic end-products (such as SCFAs and SBAs) preserve immune homeostasis (Atarashi et al., 2013; Atarashi etal., 2011; Foley et al., 2021; Tanoue et al., 2016), and on determining the routes by which gut pathobionts promote inflammation (Atarashi et al., 2017; Britton Graham et al., 2020).

Succinate is an intermediary metabolite that is produced during the degradation of dietary fibers into other fatty acids (Femandez-Veledo and Vendrell, 2019). Succinate accumulation has often been associated with higher incidence of obesity and IBD (Serena et al.. 2018), but it has also been found to promote gluconeogenesis and brain signaling (de Vadder and Mithieux, 2018). While succinate accumulation in the SI during invasion by parasites promotes the expansion of TCs with implications for tissue regeneration and parasite expulsion (Ting and von Moltke, 2019; von Moltke et al., 2016), it also stimulates growth and activates virulence for different enteric pathogens such as C. difficile and Salmonella enterica.

In the colon, succinate accumulation often occurs when the microbiome is perturbed (Tulstrup et al., 2015) and it has been considered a biomarker of inflammation since higher succinate concentrations are observed in the serum and feces of IBD patients compared to healthy controls (Fremder et al., 2021). Succinate is the most prevalent biochemical route to propionate production by primary fermenters including members of the Bacteroides and Prevotella genera (Ikeyama et al., 2020). It is also a major cross-feeding metabolite (Femandez-Veledo and Vendrell, 2019), was shown to enhance the in vivo growth of Clostridioides difficile (Ferreyra et al., 2014), and acts as an environmental signal to regulate Salmonellas ’ virulence as well as host invasion programs (Spiga e/ tz/.. 2017).

Type 2 immunity, a hallmark response to helminths and allergens, also mediates tissue regeneration in many muco-cutaneous barriers including the colon (Akdis et al., 2020; Cox et al., 2021; Gieseck et al., 2018). In mice, intraperitoneal administration of recombinant IL-25 induced eosinophil-mediated barrier protection against Clostridioides difficile morbidity and mortality with no effect on C. difficile intestinal levels (Buonomo et al., 2016). Similar findings were obtained in humans with lower IL-25 concentrations found in colonic biopsies of C. difficile-infected patients compared to healthy controls (Buonomo et al., 2016). Finally, TCs and TC- derived IL-25 were also protective in a mouse model of DSS-induced colitis (Qu et al., 2015), and patients with inflammatory bowel disease (IBD) display fewer IL-25 expressing cells in their intestinal mucosa, with IL-25 levels being lower during active disease compared to remission (Su et al., 2013). Thus, the TC response is critical to maintain homeostasis of the colonic tissue in many inflammatory and auto- inflammatory conditions, suggesting distinct TC functions according to anatomy (e.g., colon vs. the small intestine), possibly imprinted by host and environmental cues.

Here we hypothesize that microbially-produced succinate is a metabolite at the center of a three-way circuit that includes the microbiome, C. difficile, and host epithelial cells in the colon. Specifically, without wishing to be bound by theory, it is believed that expansion of colonic TCs in response to the accumulation of microbiota- produced succinate acts as a protective mechanism by which the host resolves C. difficile -caused intestinal distress.

In support of this hypothesis, we demonstrate that selective colonic microbiome perturbation leading to the enrichment of succinate-producing microbes (through the selective depletion of succinate consumers) induces TCs expansion and consequent production of type 2 immune cytokines. We show the causality⁷ of the phenotype through microbiome reconstitution experiments with stool transplants that are enriched for succinate-producing bacteria, as well as by using defined consortia of know n succinate-producing commensals. We demonstrate the dependency of this phenotype on microbial-produced succinate as knocking out succinate production in B. thetaiotaomicron leads to significantly lower TC number and type 2 cytokines levels in the colon, while not affecting levels of type 1 cytokines. This effect is localized to the colon; no effect is observed in the small intestine or in the cecum. Furthermore, we show that this phenotype requires live succinate-producing bacteria as heat-killed succinate-producing bacteria do not stimulate this colonic TC- dependent circuit.

Following reports that exogenous administration of IL-25 protects from C. difficile induced-colonic damage (Buonomo el al.. 2016), we show that prophylactic administration of succinate-producing live bacteria protects from C. difficile morbidity, and mortality. Importantly, we show that this mechanism is mediated by the presence of succinate and on the presence of succinate-responsive TCs as protection is lost in TC knockout Pou2t mice. This is a significant advancement to studies aimed at exploiting the microbiome to control C. difficile-induced disease; our approach provides access to a novel microbiome-regulated axis for immune-mediated C. difficile control that can be complementarity explored in addition to current microbiome-based efforts at preventing C. difficile disease which are focused on using bacteria intended to directly inhibit this pathogen in the intestine (Bobilev et al., 2019; Buffie et l., 2015).

The present data show that cefoperazone administration significantly decreases TC numbers in both the ileum and the colon and that the increase of TCs following cefoperazone by administration of succinate-producing consortia protects from C. difficile disease in a POU2F3 -dependent manner. Cefoperazone treatment is one of the main models used to induce C. difficile colitis in mice (Theriot et al., 2011; Winston et al., 2016). Cefoperazone-dependent reduction in colonic TCs by directly acting on the epithelial barrier or by (more likely) killing the resident, succinate- producing Bacteroides species (Erb Downward et al., 2013) may be one of the mechanisms by which mice become susceptible to C. difficile. The mechanism by which cefoperazone is decreasing TC number remains to be elucidated, but cefoperazone does not appear to alter the ability⁷ of the administered microbial consortia to expand TCs and protect from C. difficile. Remarkably, the succinate- producing bacterial consortia produced succinate at expected concentrations in wildtype and cefoperazone-treated mice, indicating that cefoperazone does not affect the ability of the orally administered species to engraft in the intestine, produce succinate, and subsequently cause TC hyperplasia similarly to what is observed in solely AVNM-treated mice. The succinate-producing consortia induced a roughly two-fold increase in TCs in mice treated with cefoperazone, which subsequently provided protection against CDI, despite not rescuing TC numbers to the degree observed in AVNM-treated mice administered with producers.

The inability of the succinate producers’ administration post AVNM to increase succinate concentrations in Pou2f3'^/' mice is intriguing as it may suggest that Pou2B-dependent TCs are needed for the establishment of a succinate-producers- dominated microbiome that leads to downstream TC activation. Importantly, this observation is consistent with recent findings not only showing that mice lacking Paneth Cells have a different intestinal microbiome composition in presence and absence of TCs, but also that Poi^fS^' strongly negatively select for abundance of those same Bacteroides species that we found in our study to increase succinate and promote TC expansion in our studies (Coutry et al., 2023). Combined with our findings, this points to a possible, novel feedback between TCs and the microbiome that underpins intestinal response to pathogens, which has yet to be fully elucidated.

At homeostasis, succinate is a metabolic intermediate in the conversion of dietary fibers to health-promoting metabolites including short-chain fatty acids (Femandez-Veledo and Vendrell, 2019). Abnormal accumulation of microbiome- derived succinate in the intestine is a signature of gastrointestinal dysbiosis and is associated with the emergence of different diseases including IBD and obesity (Mills and O'Neill, 2014; Serena et al., 2018). Considering this, and the results of this study, succinate-sensing by colonic TCs may be a sentinel mechanism that evolved to temporarily counteract the loss of succinate-to-SCFA converters during dysbiosis which may have a role in containing damage that is caused by dysbiosis-thriving opportunistic pathogens. Perhaps C. difficile activates virulence factors in the presence of commensal succinate to overcome the increased intestinal protection provided by TCs in the presence of a succinate-enriched microbiome.

Compositions

Provided herein are compositions comprising in vivo succinate-producing microorganisms, e.g., Bacteroides and Prevotella species (preferably Bacteroides thetaiotaomicron (e.g., VPI 5482), Bacteroides vulgatus (e.g., NCTC 11154), Prevotella copri (e.g., DSM 18205)), Parabacteroides (e.g., Parabacteroides distasonis). and Bacilli (e.g.. Lactobacillus animalis). In some embodiments, the compositions comprise only one, two, three, four, or five succinate-producing microorganisms, and can comprise only those two, three, four, or five and no other microorganisms, or can comprise up to one, two, three, four, five, six, seven, eight, nine, ten, 20, 25, 30, 35, 40, 45, or 50 additional species of microorganisms. In some embodiments, the microorganisms in the composition consist of only Bacteroides thetaiotaomicron (e.g., strain VPI 5482), Bacteroides vulgatus (e.g., strain NCTC 11154). and Prevolella copri (e.g., strain DSM 18205). The microorganisms in the compositions should be viable, e.g., should be alive and capable of secreting succinate.

As will be appreciated by one of skill in the art, one or more bacterial strains identified as having succinate-producing activity can be included in the compositions described herein. Aspects of the disclosure relate to bacterial strains with 16S rDNA sequences that have sequence identity to a nucleic acid sequence of any one of the sequences of the bacterial strains or species described herein. The terms “identical,” or percent “identity ,” in the context of two or more nucleic acids or amino acid sequences, refer to two or more sequences or subsequences that are the same. Two sequences are “substantially identical” if two sequences have a specified percentage of amino acid residues or nucleotides that are the same (e.g., at least 80%, 85%, 90%, 95%, 96%, 97%, 98%, 99%, 99.5%, 99.6%, 99.7%, 99.8% or 99.9% sequence identity) over a specified region of a nucleic acid or amino acid sequence or over the entire sequence, when compared and aligned for maximum correspondence over a comparison window, or designated region as measured using one of the following sequence comparison algorithms or by manual alignment and visual inspection. Optionally, the identity exists over a region that is at least about 50 nucleotides in length, or more preferably over a region that is 100 to 500 or 1000 or more nucleotides in length. In some embodiments, the identity exists over the length the 16S rRNA or 16S rDNA sequence. In some embodiments, identification is done using PCR using the universal primers RW01 and DG74, which flank an ~370-bp fragment found in the 16S rRNA gene of all bacterial species. In some embodiments, the bacterial strain has at least 60%, at least 70%, at least 80%, at least 81%, at least 82%, at least 83%, at least 84%, at least 85%, at least 86%, at least 87%, at least 88%, at least 89%, at least 90%, at least 91%, at least 92%, at least 93%, at least 94%, at least 95%, at least 96%, at least 97%, at least 98%, at least 99%, at least 99.5%, at least 99.6%, at least 99.7%, at least 99.8%, at least 99.9%, or up to 100% sequence identity relative to any of the strains or bacterial species described herein over a specified region or over the entire sequence. It would be appreciated by one of skill in the art that the term "sequence identity’’ or ‘'percent sequence identity,” in the context of two or more nucleic acid sequences or amino acid sequences, refers to a measure of similarity⁷ between two or more sequences or portion(s) thereof. In some embodiments, the composition includes two or more (e.g., 2, 3, 4. 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22. 23. 24. 25. 26. 27, 28, 29, 30, 31, 32, 33, 34, 35, 36 or more, e.g., up to 10, 15, 20, 25, 30, 35, 40, 45, or 50) bacterial strains, wherein the two or more bacterial strains contain 16S rDNA sequences having at least 97% sequence identity with 16S nucleic acid sequences that identify the species. Additionally, or alternatively, two or more sequences may be assessed for the alignment between the sequences. The terms “alignment” or percent “alignment” in the context of two or more nucleic acids or amino acid sequences, refer to two or more sequences or subsequences that are the same. Two sequences are “substantially aligned” if two sequences have a specified percentage of amino acid residues or nucleotides that are the same (e.g., at least 80%, 85%, 90%, 95%, 96%, 97%, 98%, 99%, 99.5%, 99.6%, 99.7%, 99.8% or 99.9% identical) over a specified region or over the entire sequence, when compared and aligned for maximum correspondence over a comparison window, or designated region as measured using one of the following sequence comparison algorithms or by manual alignment and visual inspection. Optionally, the alignment exists over a region that is at least about 50 nucleotides in length, or more preferably over a region that is 100 to 500 or 1000 or more nucleotides in length. In some embodiments, the identify exists over the length the 16S rRNA or 16S rDNA sequence. For sequence comparison, typically one sequence acts as a reference sequence, to which test sequences are compared. Methods of alignment of sequences for comparison are known in the art. See, e.g., by⁷ the local homology⁷ algorithm of Smith and Waterman (1970) Adv. Appl. Math.2:482c, by the homology alignment algorithm of Needleman and Wunsch, J. Mol. Biol. (1970) 48:443. by the search for similarity⁷ method of Pearson and Lipman. Proc. Natl. Acad. Sci. USA 85:2444, 1988, by computerized implementations of these algorithms (GAP, BESTFIT, FASTA, and TFASTA in the Wisconsin Genetics Software Package, Genetics Computer Group. Madison. WI), or by manual alignment and visual inspection (see. e.g.. Brent et al., Current Protocols in Molecular Biology⁷, John Wiley H Sons, Inc. (Ringbou ed., 2003)). Two examples of algorithms that are suitable for determining percent sequence identity and sequence similarity are the BLAST and BLAST 2.0 algorithms, which are described in Altschul et al., Nuc. Acids Res.25:3389-3402, 1977; and Altschul et al., J. Mol. Biol.215:403-410, 1990, respectively.

Provided herein are compositions comprising bacterial strains and combinations of bacterial strains that are identical or have a high percent of identity (e.g., at least 97%, e.g., at least 98%, or 99%) with bacterial strains comprising 16S rDNA sequences as provided in PCT Publication No. W02021030198, or Teng et al., J Clin Microbiol. 2004 Apr; 42(4): 1727-1730 (Bacteroides thetaiotaomicrori). It should be appreciated that the bacterial strains described herein that have a 16S rDNA sequence with a high percent of identity (e.g., at least 97%, e.g., at least 98% or 99%) to the exemplified strains may also be homologous to other strains based on their whole genome sequence, or subset of their whole genome sequence.

In one aspect, the compositions comprise a fraction of a fecal sample, or comprise at least one strain isolated from a fecal sample.

In some embodiments, the compositions described herein comprise spore forming and non-spore forming bacterial strains. In some embodiments, the compositions described herein comprise spore forming bacterial strains. In some embodiments, the compositions described herein comprise only spore forming bacterial strains. In some embodiments, the compositions described herein comprise only non-spore forming bacterial strains. The spore- forming bacteria can be in spore form (i.e., as spores) or in vegetative form (i.e., as vegetative cells). See, e.g., in PCT Publication No. W02021030198. In some embodiments, at least one (e.g., 1, 2, 3, 4, 5, or more) of the bacterial strains in the composition is in spore form. In some embodiments, at least one (e.g., 1, 2, 3, 4, 5, or more) of the bacterial strains in the composition is in vegetative form. The strains of the compositions provided herein are alive and will be alive when they reach the target area (e.g., the intestines). Bacterial spores are considered to be alive in this regard. Viability of spores or bacteria can be determined by plating the spores and growing the spores. For instance, spores can be plated in appropriate media and incubated in the anaerobic chamber for a period of time (e.g., 48-96 hrs.). Viability⁷ can subsequently be determined by quantifying the colony forming units which correspond to spores that germinated. For instance, spores can be plated on TCCFA plates (taurocholate, cycloserine, cefoxintin, fructose agar plates), in which taurocholate helps the spores to germinate. In addition, spores can be quantified using the dipicolinic assay (DPA assay).

The bacterial strains used in the present compositions can be isolated or purified, for example, from a source such as a culture (optionally obtained from a commercial source such as ATCC) or a microbiota sample (e.g., fecal matter). The bacterial strains used in the compositions provided herein generally are isolated from the microbiome of healthy individuals. However, bacterial strains can also be isolated from individuals that are considered not to be healthy. In some embodiments, the compositions include strains originating from multiple individuals. As used herein, the term “isolated” refers to a bacteria or bacterial strain that has been separated from one or more undesired component, such as another bacterium or bacterial strain, one or more component of a growth medium, and/or one or more component of a sample, such as a fecal sample. In some embodiments, the bacteria are substantially isolated from a source such that other components of the source are not detected. As also used herein, the term “purified” refers to a bacterial strain or composition comprising such that has been separated from one or more components, such as contaminants. In some embodiments, the bacterial strain is substantially free of contaminants. In some embodiments, one or more bacterial strains of a composition may be independently purified from one or more other bacteria produced and/or present in a culture or a sample containing the bacterial strain. In some embodiments, a bacterial strain is isolated or purified from a sample and then cultured under the appropriate conditions for bacterial replication, e.g., under anaerobic culture conditions. The bacteria that is grown under appropriate conditions for bacterial replication can subsequently be isolated/ purified from the culture in which it is grown.

The microorganisms can be present in a composition comprising a buffer or other carrier for delivery⁷ to a tissue in a subject. For example, biodegradable polymeric microparticles or nanoparticles such as liposomes, micelles, polymer nanoparticles, and inorganic nanomaterials, which are ty pically in the range of ID- 150 nm in size, can be used as earners. See, e.g., Yu et al., J Control Release. 2016 Oct 28; 240: 24-37. The compositions can include a pharmaceutically acceptable carrier. The term “pharmaceutically acceptable” refers to molecular entities and compositions that do not produce an adverse, allergic or other untoward reaction when administered to a subj ect. The term “phannaceutically acceptable carrier,” as used herein, includes any and all solvents, dispersion media, coatings, antibacterial, isotonic and absorption delaying agents, buffers, excipients, binders, lubricants, gels, surfactants and the like, that may be used as media for a pharmaceutically acceptable substance.

The present disclosure also provides food compositions comprising the microorganisms. Food compositions can include, e.g., liquid or solid food, feed or drinking water. Tn some embodiments, the compositions are food products, such as, for example, beverages including dairy and non -dairy based drinks, plant or animalbased milk products (e g., almond, cashew, soy, or oat milk; or cow, goat, or sheep milk), milk powder, reconstituted milk, cultured milk, smoothies or cultured beverages (resulting from fermentation of the carbohydrate containing media), flavored beverages, yogurt, drinking yogurt, set yogurt, fruit and/or vegetable juices or concentrates thereof, fruit and vegetable juice powders, reconstituted fruit products, powders, or malt or soy or cereal based beverages, and sports supplements including dairy and non-dairy based sports supplements; or solid foods including breakfast cereal such as muesli flakes, spreads, meal replacements, confectionary, chocolate, gels, ice creams, cereal, fruit puree, and/or chocolate bars, energy bars, snack bars, food bars, sauces, gummies, or dips. The compositions can also be additives, e.g., to be mixed into solid food, e.g., by sprinkling onto or mixing into a food; or to be mixed into a beverage, e.g., into water, juice, or milk, and can include flavors. As used herein, a smoothie is a drink made from pureed raw fruit and/or vegetables, typically using a blender. A smoothie typically comprises a liquid base such as water, fruit juice, plant and/or animal-based milk products such as milk, yogurt, ice cream or cottage cheese. Smoothies can comprise additional ingredients, e.g., crushed ice, sweeteners (e.g., natural sweeteners such as agave syrup, maple syrup, honey⁷ or sugar, or artificial sweeteners), vinegar, protein supplements such as whey powder, chocolate, or nutritional supplements,

In some embodiments, the food composition comprises carbohydrates such as, but not limited to, starches such as are contained in rice flour, flour, tapioca flour, tapioca starch, and whole wheat flour, modified starches or mixtures thereof.

In some embodiments, the compositions including the microorganisms are in the form of a liquid, and thus can be used as a beverage. In some embodiments, the beverage composition comprising the microorganisms is naturally sweetened. Suitable natural sweeteners include, but are not limited to, sugars and sugar sources such as sucrose, lactose, glucose, fructose, maltose, galactose, com syrup (including high fructose com syrup), sugar alcohols, maltodextrins, high maltose com syrup, starch, glycerin, brown sugar and mixtures thereof. In some embodiments, fiber, inulin, or prebiotics or probiotics are included.

In some embodiments, the food or beverage compositions include milk or milk-derived product, e g., yogurt. In some embodiments, a stabilizer may be combined with the milk-derived product. Combining a stabilizer with the milk- derived product may thicken the milk-derived product. In some embodiments, a stabilizer can be combined with the milk-derived product following completion of microorganism culture. The stabilizer can be selected from, as examples, gums, salts, emulsifiers, and their mixtures. Gums can be selected from, as examples, locust bean gum, xanthan gum, guar gum, gum arabic, and carageenan. In some embodiments, salts include, but are not limited to, sodium chloride and potassium chloride.

In some embodiments, the microorganisms can be administered to a subject with alkaline phosphatase. These methods involve administering to the subject a composition including the microorganisms and an amount of an alkaline phosphatase effective to increase the number of commensal bacteria in the gastrointestinal tract, wherein alkaline phosphatase decreases the number of pathogenic bacteria in the gastrointestinal tract, or increases the number of commensal bacteria and decreases the number of pathogenic bacteria in the gastrointestinal tract, thereby modulating gastrointestinal tract flora levels in the subject. The alkaline phosphatase composition and the methods of use is described in WO 2010/025267, which is incorporated by reference in its entirety.

Methods of Treating and Reducing Risk of Infection

The compositions and methods as described herein can be used, e g., to treat a Clostridioides difficile infection; the methods include administering the microorganisms as described herein. Other infections that can be treated include pathogens that cause intestinal barrier disruption or distress, e.g., infections with Campylobacter, Salmonella, E. coli, Shigella, Listeria monocytogenes, Vibrio, Enteropathogenic E. coli, and Klebsiella. The methods described in the present disclosure are effective for treating C. difficile infections in a variety of subjects including mammals, e.g., humans and veterinary subjects, such as laboratory animals, e.g., mice, rats, rabbits, or monkeys, or domesticated and farm animals, e.g., cats, dogs, goats, sheep, pigs, cows, horses, and birds, e.g., chickens and turkeys.

Healthcare providers can identify subjects in need of treatment for C. difficile infection using their experience and judgment, which can be based on subjective (e.g., based on the healthcare provider’s opinion or observation of the subject) or objective (e.g., measurable by a test or diagnostic method) information. As used herein, the terms “treat,” treating,” “treatment,” and the like refer to reducing or ameliorating a disorder and/or symptoms associated therewith. It will be appreciated that, although not precluded, treating a disorder or condition does not require that the disorder, condition, or symptoms associated therewith be completely eliminated.

The present disclosure provides methods of inhibiting or reducing the risk of C. difficile infections and for treating C. difficile infections. As used herein, the term “reducing the risk” refers to reducing the probability of developing a disorder or condition in a subject, who does not have, but is at risk of, or susceptible to, developing a disorder or condition, e.g., a subject who is in or about to be in a communal living situation such as a nursing home or hospital.

In some embodiments, the subject is being administered an antibiotic that increases the risk of developing a C. difficile infection, e.g., clindamycin, later- generation cephalosporins (e.g., cefoperazone), and fluoroquinolones, (see, e.g. Miller et al., Open Forum Infectious Diseases, Volume 10, Issue 8, August 2023, ofad413). In some embodiments, the antibiotic is cefoperazone, clindamycin, cefixime, cefdinir, cefuroxime, cefpodoxime, amoxicillin/clavulanate, ciprofloxacin, moxifloxacin, dicloxacillin, or cefaclor.

In some embodiments, the microorganisms can be administered to a subject in combination with some other known treatments for C. difficile infection. For example, the microorganisms can be used in combination with an antibiotic therapy, such as vancomycin and/or fidaxomicin, or with cessation of antibiotic therapy causing the C. difficile infection. In some embodiments, the microorganisms are administered to the subject after the subject have received an antibiotic therapy. In some embodiments, the microorganisms are administered to the subject before the subject has received an antibiotic therapy. In other embodiments, the microorganisms are administered to the subject when the subject is under an antibiotic therapy.

Methods of Administration in Animal Subjects

The therapeutic methods disclosed herein (including prophylactic treatments) generally include administration of a therapeutically effective amount of a composition comprising the microorganisms to a subject in need thereof. Such treatment will be suitably administered to subjects, particularly humans, suffering from, having, susceptible to, or at risk for C. difficile infection. Determination of those subjects who are “at risk” can be made by any objective or subjective determination by a diagnostic test or opinion of a health care provider.

A subject is effectively treated when a clinically beneficial result ensues. This may mean, for example, a resolution of the symptoms associated with C. difficile infection, a decrease in the severity of the symptoms associated with C. difficile infection, or a slowing of the progression of symptoms associated with C. difficile infection. The most common symptom of C. difficile infection is diarrhea; usually watery diarrhea that is sometimes bloody and sometimes accompanied with abdominal pain. Fever, nausea, and vomiting can also occur. Fever and abdominal distension and/or tenderness are signs of more severe C. difficile infection.

Compositions comprising the microorganisms can be administered to a subject through many different routes, e.g., by endoscopy, by enteroscopy, by colonoscopy, by a nasoduodenal catheter, by enema, or by oral administration. In the case of oral administration, the composition can be delivered in a capsule or pill form, e.g., for intestinal delivery. In some embodiments, the composition is in a capsule form, e.g.. packaged in gelatin capsules.

Dosage

The compositions can be formulated in a unit dosage form, each dosage containing, for example, from about 0.005 mg to about 2000 mg of the microorganisms. The dosage scheduling can be approximately once per week, twice per week, three times per week, or four times per week. In some embodiments, the compositions can be administered to a subject every day, every other day, every three days, every four days, every five days, every six days, or once per week. A person skilled in the art can refine the dosage scheduling as needed. The phrase “unit dosage forms” refers to physically discrete units suitable as unitary dosages for human subjects and other mammals, each unit containing a predetermined quantify of active material calculated to produce the desired therapeutic effect, in association with a suitable pharmaceutical excipient. When referring to these pre-formulation compositions as homogeneous, the active ingredient is typically dispersed evenly throughout the composition so that the composition can be readily subdivided into equally effective unit dosage forms.

The compositions can be formulated in a unit dosage form, each dosage containing, for example, from about 0.1 mg to about 50 mg, from about 0. 1 mg to about 40 mg, from about 0. 1 mg to about 20 mg, from about 0. 1 mg to about 10 mg, from about 0.2 mg to about 20 mg, from about 0.3 mg to about 15 mg, from about 0.4 mg to about 10 mg, from about 0.5 mg to about 1 mg; from about 0.5 mg to about 100 mg, from about 0.5 mg to about 50 mg, from about 0.5 mg to about 30 mg, from about 0.5 mg to about 20 mg, from about 0.5 mg to about 10 mg, from about 0.5 mg to about 5 mg; from about 1 mg from to about 50 mg, from about 1 mg to about 30 mg. from about 1 mg to about 20 mg, from about 1 mg to about 10 mg, from about 1 mg to about 5 mg; from about 5 mg to about 50 mg, from about 5 mg to about 20 mg, from about 5 mg to about 10 mg; from about 10 mg to about 100 mg, from about 20 mg to about 200 mg, from about 30 mg to about 150 mg, from about 40 mg to about 100 mg, from about 50 mg to about 100 mg of the microorganisms.

Kits

The present disclosure also provides kits comprising the microorganisms described herein. In some embodiments, the kit includes a sterile container which contains a therapeutic or prophylactic composition comprising the microorganisms. Such containers can be boxes, ampoules, bottles, vials, tubes, bags, pouches, blisterpacks, or other suitable container forms known in the art. Such containers can be made of plastic, glass, laminated paper, metal foil, or other materials suitable for holding medicaments.

The kit can also include instructions, e g., information about the use of the composition for treating a C. difficile infection. The kit can further contain precautions; warnings; indications; counter-indications; overdose information; adverse reactions; animal pharmacology; clinical studies; and/or references. The instructions may be printed directly on the container (when present), or as a label applied to the container, or as a separate sheet, pamphlet, card, or folder supplied in or with the container.

EXAMPLES

The invention is further described in the following examples, which do not limit the scope of the invention described in the claims.

MATERIALS AND METHODS:

The following materials and methods were used in the Examples below.

Experimental animals. All animal studies were approved by the UMass Chan Institutional Animal Care and Use Committee (Protocols A-1993-17 and PROT0202100184) in accordance with National Institutes of Health guidelines. All experiments were performed with mice 8-12-weeks of age. C57BL/6J wild-type Specific Pathogen Free (SPF) mice of both sexes were purchased from The Jackson Laboratory (Bar Harbor, ME). C57BL/6J-Pou2f3emlCbwi/J mice were used to generate Pou2f^!' and Pou2f' animals in-house. For all experiments involving mice purchased by external vendors, animals were acclimatized to housing facilities for at least 4 weeks before their use in experiments. For the experiments in where w e compared the effect of host genotype (i.e., Pou2f) on microbiome dependent TC induction we used littermate animals for Pou2f ' and Pou2f^!’ . while Pou2f ’ ' animals were not littermate. However, in all the experiments involving mice with different genotypes, before antibiotic pre-treatment and administration of bacterial suspensions, animals of different genotypes were first co-housed for at least two weeks to normalize any baseline microbiome effects.

Fecal pellet collection. Mice were placed into separate, autoclaved plastic beakers until 3 fecal pellets w ere produced. Immediately after production, individual fecal pellets were transferred using sterile toothpicks into a microfuge tube and flash- frozen in liquid nitrogen.

Antibiotic administration experiments. The approach follow s previous work published by us and others (Foley et al., 2021). C57BL6/6J 8-10 week old female SPF mice (n = 6-12 per treatment group, depending on the experiment) were treated with metronidazole (1 g I’¹; Sigma), vancomycin (500 mg I’¹; Sigma), or an antibiotic cocktail, AVNM (a combination of ampicilllin (1 g I’¹; Fisher), vancomycin (500 mg I ¹; Sigma), neomycin (1 g I ¹; Sigma), and metronidazole (1 g I ¹; Sigma)) suspended in phosphate-buffered saline (PBS) or PBS as control. Each mouse received lOuL/g body weight of treatment via oral gavage every 12 hours for a total of 7 days. 12 hours after the final antibiotic gavage, mice were sacrificed via carbon dioxide asphyxiation. Tissue samples and intestinal contents were extracted and immediately flash-frozen for immune phenotypes quantification. Feces were collected before, during and at the end of antibiotic treatment. Bacterial DNA was extracted microbiome sequencing analysis as detailed below.

Stool matter transplant experiments. 8-10-week-old C57BL6/6J female SPF mice (n = 5-6 per treatment group) classified as recipients were either pre-treated with AVNM in their drinking water for 7 days to deplete the resident microbiome (Foley et al., 2021) or left on standard acidified drinking water. SPF mice (n=4 per group) classified as donors were pre-treated with vancomycin (500 mg I'¹; Sigma) or standard acidified drinking water. After 7 days of antibiotic pre-treatment, all mice were returned to standard acidified drinking water for the remainder of the experiment. 24 hours were allowed to pass between the removal of the antibiotics and the first fecal transplant to allow for antibiotic washout. Donor mice were placed individually in autoclaved plastic beakers until they produced three fecal pellets. Fecal pellets from donor mice in each group were pooled and collected into a 15mL conical tube containing 5mL PBS and resuspended. The fibrous matter was pelleted at 300x g for 5 minutes and removed from the fecal suspension to facilitate passage through the gavage needle. The fecal suspension from either untreated SPF mice or from mice previously treated with vancomycin was orally introduced to recipient mice at lOul/g bodyweight. This was repeated every day for 5 days, with donor feces collected and suspended fresh each day. 24 hours after the final transplant, all mice were sacrificed by carbon dioxide euthanasia. Tissue samples and intestinal content extracts for immune phenotype quantification were collected and flash-frozen. Fecal samples collected over time, along with samples from input suspensions, were obtained for bacterial DNA extraction and microbiome sequencing. Bacterial growth for live consortia. All bacterial work was performed in a Coy™ anaerobic chamber available in the UMass Chan Center for Microbiome Research. All strains were grown in BD Difco™ Reinforced Clostridial Media (BD 218081). All bacterial species were previously determined to have approximately 1x10⁸ colony forming units/mL at an optical 600nm (OD600) of 1 when grown for 48 hours. Bacterial strains were grown in 20mL of media in sterile, anaerobic media bottles at 37°C at 50 RPMs for 48 hours. OD600 was determined, and individual strains were pelleted at 10,000 x g for 1 minutes. Bacterial pellets were resuspended in the appropriate volume of anaerobic, sterile PBS to produce 3.33mL of the strain at an OD600 of either 1, or 5. Bacteria were then pooled to produce the consortia into either a consortium of bacteria known to produce succinate in vivo, (Baderoides thetaiotaomicron VPI 5482, Bader aides vulgatus NCTC 11154, Prevotella/Segatella copri DSM 18205), or a consortium of bacteria not known to product succinate in vivo, (Eggerthella lenta DMS2243 , Eubacterium redale ATCC 33656, Dorea formicigenerans ATCC2 7755), so that the final volume of each consortium was lOmL. The consortia were transported in anaerobic jars to ensure viability. This process was repeated daily for each administration of the live consortia. This same approach was used for the experiments comparing immune induction by Bacteroides thetaiotaomicron VPI 5482 and the succinate production-deficient B. thetaiotaomicron Dfrd (Spiga al., 2017).

Live consortia administration experiments. 8-10-week-old C57BL/6J female SPF mice (n = 4-8 per treatment group, depending on the experiment) w ere pre-treated with AVNM with 2% sucrose in their drinking water for 7 days to deplete the resident microbiome (see above). Mice were then administered via oral gavage either (1) “succinate-producers” described above, (2) “non-producers” described above, or (3) the “succinate-producers” after heat-killing for 5 minutes at 65°C at an OD600 of 1. Mice were gavaged at lOul/g of body weight. The gavage was repeated every 24 hours for 4 days. 24 hours after the last gavage of the live consortia, mice were euthanized by carbon dioxide asphyxiation. Tissue samples and intestinal extracts w ere collected and flash frozen. Bacterial DNA w as collected from luminal contents of the ileum and proximal colon and sequenced via shotgun metagenomics (see below). Ileal and colonic content was also subjected to targeted metabolomics (see below). The same experimental protocol and assay was used in the assays comparing phenotype induction by Bacteroides thetaiotaomicron VPI 5482 or the succinate production-deficient B. thetaiotaomicron Dfrd (Spiga et al., 2017) in C57BL/6J, Pou2f3^+/" and Pou2f3' \ 8-10-week-old female SPF mice.

Clostridioides difficile infection experiments. We evaluated the response of mice receiving different live bacterial consortia to C. difficile infection by adapting the animal model described in (Theriot et al., 201 1 ; Winston et al., 2016). 8-10-week- old C57BL/6J female SPF mice (n=6 per treatment group) were pre-treated with sterile AVNM with 2% sucrose for one week (days 24 to 17 prior to infection) in their drinking water (see above). Mice were removed from AVNM and returned to standard drinking water 24 hours before microbiota gavage to allow antibiotic washout. Mice were orally gavaged once every 24 hours by the “succinate-producers” (see above) or heat-killed producers at an OD600 of 5 (approximately 5x10⁸ CFUs/mL). or PBS daily for 3 days at 0.2mL/g bodyweight (16, 15, and 14 days prior to infection). Three days after the cessation of AVNM and start of bacterial administration mice were given cefoperazone (0.5 mg/ml; MP Bioworks) in sterile PBS with 2% sucrose for 10 days (days 13 to 3 prior to infection). Mice continued to receive gavage of microbial consortia or controls every other day during the 10 days of cefoperazone treatment (9, 7, 5. and 3 days prior to infection). Cefoperazone was ceased and mice were returned to standard acidified drinking water two days prior to infection and received daily gavage of microbial consortia every day (2 and 1 days prior to infection). On the day of infection, mice were orally gavaged with 10⁵ CFUs of C. difficile strain VPI 10463 (ATCC 43255) (200 ul total volume). Animals were assessed for symptoms such as inappetence (lack of appetite), diarrhea, and hunching at 12-hour intervals. Animals were euthanized if they lost 20% of their initial baseline weight. Similar C. difficile infection experiments were performed where succinate- producing bacteria or PBS were orally gavaged into Pou2f3^+/’ and Pou2f3’ 8-10- week-old female SPF mice (n=5-6 per treatment).

Cefoperazone administration experiment. To evaluate the intestinal epithelial effect of cefoperazone on mice receiving the antibiotic, we performed only the cefoperazone administration detailed in the CDI experiment. Mice were administered cefoperazone (0.5 mg/ml; MP Bioworks) in sterile PBS with 2% sucrose for 10 days. Control mice were administered PBS with 2% sucrose. Mice were removed from cefoperazone 2 days before euthanasia to permit the antibiotic to wash out and mimic prior experimental conditions. On day 13, mice were sacrificed via carbon dioxide asphyxiation. Tissue samples from the colon and ileum were analyzed using flow cytometry.

Tissue preparation and cytokine measurement. Cecal tissue was flushed with sterile PBS and sectioned into 0.5cm sections before flash freezing. Ileal and proximal colon tissue were manually evacuated and sectioned into 0.5cm sections before flash freezing. Protein lysates from intestinal tissue were generated as described in (Foley et al., 2021) (i.e., benchtop homogenization in tubes containing Lysing Matrix D (MP Biomedical) beads and lysis buffer (20 mM Tris pH 7.4, 120 mM NaCl, 1 mM EDTA, 1% Triton-X-100, 0.5% sodium deoxy cholate, l x protease inhibitor cocktail [Roche])). Cytokine protein concentrations were measured by ELISA (1L-17E, IL-5, and IL-13 Duo-Set, R&D Systems). Following (Buonomo et al., 2016), cytokine protein concentration in the lysate (pg/mL) was normalized by the total protein mass generated in the sample quantified using the BioRad DC assay (in mg). RNA from epithelial cells and tissue was isolated by following the TRIzol extraction manufacture protocol. Total RNA was used for RT-qPCR. Complementary DNA was generated using iScript Reverse Transcription Supermix (Invitrogen, catalog no. 18080-044). For RT-qPCR, cDNA was mixed with appropriate primers (Table 1) and SYBR green master mix (BioRad, catalog no. 1708882) and run on a Thermocycler T100 (BioRad). Proximal colon lysates were used to measure concentrations of IL- lb, IL-2, IL-21, IL-22, IL-31, and IL-33 cytokines with multiplexed-ELISA assay with Luminex 200 Multiplex Bio-Plex 200 System (EMD Millipore, Billerica, MA, USA) using a Milliplex Map kit (EMD Millipore).

Immunohistochemistry for TC quantitation. Colon and ileum were fixed overnight in 4% of PFA, followed by 2 hours of washing in phosphate buffer solution and overnight incubation at 4 °C in a solution of 30% sucrose. Tissues were embedded in an optimum cutting temperature compound and cut into 7 mm sections using a Leica Ciyostat Microtome. Then, sections were blocked with specific serum and 5% BSA and stained with anti-DCLKl (Abeam; ab31704), anti-CD326 (BioLegend, clone G8.8), and DAPI. Incubations were performed in Tris-buffered saline containing 5% BSA, 10% normal mouse serum, and 0.1% Triton X-114. Sections were mounted in Fluoromount-G (Southern Biotech, catalog no. 0100-01) and imaged on a Zeiss fluorescent microscope using a *20 objective with a numerical aperture of 0.8.

Succinate and short chain fatty acids measurement. Quantitation of C2 to C6 short-chain fatty⁷ acids (SCFAs) and succinic acid was carried out as previously described in (Han et al., 2015) by the UVic-Genome BC Proteomics Centre. Briefly, serially diluted standard solutions of SCFAs and succinic acid were prepared with the use of their standard substances in 60% acetonitrile. An internal standard (IS) solution of the isotope-labeled version of SCFAs and succinic acid was prepared using 13C6- 3-nitrophenylhydrazine and following the derivatizing procedure described in the publication. The samples were precisely weighed into 2-mL homogenizing tubes. 60% acetonitrile at 10 pL per mg of raw material was added. The samples were homogenized on a MM 400 mill mixer with the aid of two metal beads at 30 Hz for 3 min, followed by centrifugal clarification at 21,000 rpm and 5 °C for 10 min. 20 pL of the clear supernatant of each sample or standard solution was mixed in turn with 80 pL of 200-mM 3 -nitrophenylhydrazine solution and 80 pL of 150-mM EDC-6% pyridine solution. The mixtures were incubated at 40 °C for 30 min. After the reaction, each solution was diluted 10-fold with the IS solution. 10-pL aliquots of the resultant solutions were injected into a C18 (2.1*150 mm, 1.8 pm) column to run LC- MRM/MS on a Waters UPLC system coupled to a Sciex 4000 QTRAP mass spectrometer with negative-ion detection. The mobile phase was 0.01% formic acid in water (A) and 0.01% formic acid in acetonitrile (B) for binary-solvent gradient elution of 15% to 90% B over 15 min, at 40 °C and 0.35 mL/min. Linear-regression calibration curv es were constructed with the data acquired from injections of the standard solutions. Concentrations of the detected analytes in the samples were calculated by interpolating the calibration curves with the peak area ratios measured from injections of the sample solutions. Flow cytometry. Mouse intestines were opened longitudinally and vortexed in a 50-ml conical tube containing Hanks' balanced salt solution supplemented with 5% heat-inactivated FBS and 10 mM HEPES, pH 7.2. Epithelial cells were isolated by rotating the tissues in a pre-digestion medium (RPMI medium, 5% heat-inactivated FBS, 10 mM HEPES, pH 7.2, and 10 mM EDTA) for 30 mm at 37 °. Cells were stained with antibodies for CD326 (BioLegend, clone G8.8), CD45.2 (BioLegend, catalog no. 30-F11), anti-SiglecF (BioLegend, clone 1RNM44N). anti-DCLKl (Abeam; ab31704) and LIVE/DEAD.

C. difficile quantification. Mice were sacrificed by carbon dioxide asphyxiation 48 hours after infection with C. difficile and cecal contents were flash frozen. Genomic DNA was extracted from lOOmg mouse cecal contents using the Qiagen DNEasy PowerSoil Pro Kit. We performed an initial amplification of the region of C. difficile toxin A using the listed primers (Table 1), and the amplification program consisted of one cycle at 98°C for 30s and then 40 cycles at 98°C for 5s, 62°C for 10s, and 72°C for 15s, with a final extension at 72°C for 5 minutes. The RT- qPCR protocol was performed as described in (Kubota et al., 2014). We utilized the TaqMan primer-probe sets targeting ted A (tcdA-F/R/P) as described (Table 1). RT- qPCR was performed in 384-well optical plates on an Applied Biosystems ViiA7Real-Time PCR System (Applied Biosystems). Each reaction mixture of 10 pL was composed of 5uL of 2x SsoAdvanced Universal Probes Supermix (BioRad, cat. no. 1725280), 0.2 pM of each specific primer, 0.2 pM of the fluorescent probe, and 2.5 pL of template DNA. The amplification program consisted of one cycle at 95°C for 30s and then 50 cycles at 95°C for 5s and 56°C for 50s. A standard curve was developed by extracting DNA from a culture of C. difficile VPI 10463 that had been serially plated for CFUs.

Microbiome sequencing and bioinformatics. Bacterial DNA was extracted from frozen fecal pellets and different intestinal compartments (ileum, cecum and colon) with the DNeasy Powersoil Pro Kit by Qiagen (Hilden, Germany) according to the manufacturer’s protocol. For the 16S rRNA sequencing, the bacterial 16S rRNA gene (variable regions V3 to V4) was subjected to PCR amplification using the universal 341F and 806R barcoded primers for Illumina sequencing. Using the SequalPrep Normalization kit, the products were pooled into sequencing libraries in equimolar amounts and sequenced on the Illumina MiSeq platform using v3 chemistry for 2 x 300 bp reads. The forward and reverse amplicon sequencing reads were dereplicated and sequences were inferred using dada2 (Callahan et al., 2016) as in (Wipperman et al., 2021). For shotgun metagenomics, sequencing libraries were prepped using the Nextera XT DNA library prep kit and sequenced on a NovaSeq X Plus 2x150. We trimmed raw reads using Trimmomatic (version 0.39) and performed host decontamination using Bowtie2 (version 2.5.4) via the kneaddata pipeline (ver 0.10.0) (iitips7/github.cojWbiobake?y/kBeaddata). The resulting metagenomic data was profded for microbial abundance using MetaPhlAn (v4) (Beghini et al., 2021).

Statistical analysis of host readouts and metabolites. We conducted several statistical analyses to investigate variations in cytokine protein concentrations, gene expression, TC numbers, metabolite concentrations, mouse survival in response to C. difficile infection, and the effect of microbiome treatment on weight loss. To assess differences in cytokine protein concentrations, mRNA abudance, TC numbers from flow cytometry or IHC as well as microbial metabolites for conditions that included more than two treatment variables we conducted an Analysis of Variance (ANOVA) followed by Tukey post-hoc tests (Hastie and Chambers, 1992). For comparisons that included two treatment variables, we used two-sample t-tests (Chap, 2003b). We determined significant associations at a False Discovery Rate (FDR) value of 0.05. To evaluate genotype-dependent expansion of TCs in response to different microbial treatments (e.g. B. thetaiotaomicron vs. B. thetaiotaomicron Afrd) in different intestinal compartments, we run ANOVA comparing the linear model with interaction, TC ~ Genotype + Treatment + Genotype: Treatment against the model with no interaction TC ~ Genotype + Treatment (Hastie and Chambers, 1992). To evaluate differences in mouse survival following C. difficile infection due to different treatments or mouse genotypes, we employed log-rank tests (Chap, 2003a). To investigate the impact of treatment on weight loss after C. difficile infection, we run Benjamini -Hochberg-corrected two-samples t-test at different time points as in (Dsouza et al., 2022). All statistical analyses were carried out using the “R” statistical software environment. Two sample t-test was run to assess differential C. difficile colonization in the cecum. Statistical analysis and machine learning modeling of microbiome data.

For the 16S rRNA sequencing data, differences in the abundance of DADA2- identified amplicon sequencing variants (SVs) between treatments were evaluated using DESeq2 (Love etal., 2014) in “R”. Briefly SVs were first filtered to select based on a prevalence cutoff of 5% and relative abundance cutoff of le-4. Counts were then normalized by first estimating the size factors using the "median ratio method" with the estimateSizeFactors function (package DESeq2) and by then obtaining dispersion estimates for Negative Binomial Distributed data with the estimateDispersions function (package DESeq2). Finally, a Negative Binomial GLM model fitting returning Wald statistics (DeSeq2 function, from package DESeq2) was performed to assess significance and effect size (as Log2 Fold Change) for contrasts between pairs of treatments. Significant associations were determined at an FDR value of 0.05. Prediction of colonic IL-25 as a function of the abundance of 16S rRNA-determined AS Vs was performed by building and running Random Forest Regression (RFR) models as in (Wipperman et al., 2021). Briefly, SVs were first converted to relative abundances by dividing each SV count by the total read counts in each sample. SVs were then filtered using 5% prevalence and le-4 relative abundance cut-off. Relative abundances of the filtered SVs in each sample were used to predict colonic IL-25 concentrations via Random Forest Regression using the "R” randomForest function (package randomForest), with 10000 trees and default mtry value. To determine significance of the associations between ASVs and IL-25 the resulting random forest model was then input to the Permutated Variable Importance algorithm using the PIMP function in R. Directionality positive/negative of the association was evaluated by performing Accumulated Local Effect calculation analysis via the ALEPlot function (package ALEPlot) in R with default values.

Results from the RFR analysis were confirmed by running Elastic Net and Bayesian Variable Selection linear regression models using in-house code, see (Bucci et al., 2016). Elastic Net models were fit to the data using the glmnet (package glmnet). The lambda parameter for glmnet was first calculated using 10-fold cross-validation for Gaussian functions. The Bayesian Variable Selection algorithm was implemented in the R Baysian modeling environment rjags. We assumed that the zeroth and first order term of the linear model to normally distributed with diffuse priors. We assumed that the selection parameter multiplying the first order tenri of the linear model to follow a Bernoulli distribution. For the data generated using shotgun metagenomic, microbiome profiling of intestinal contents was displayed using stacked bar-plots as before (Dsouza et al., 2022).

Table 1. RT-qPCR primer sequences used in this study.

Example 1. Vancomycin treatment causes an increase in colonic IL-25, IL- 13, IL-5, and TC number.

The antibiotic vancomycin targets Gram-positive bacteria, including many succinate-consuming commensal Clostridia (Isaac et al., 2017), and has been shown to increase IL-25 production preferentially and specifically in the colon (Tulstrup et al. 2015, Li et al. 2019). Consequently, we hypothesized that vancomycin would globally promote type 2 cytokine production (IL-25, IL-5, IL-13) in the colon and drive TC hyperplasia. To test this, we compared tissues from mice selectively administered with either vancomycin, metronidazole, an antibiotic cocktail (ampicillin, vancomycin, neomycin, metronidazole; AVNM). or left untreated (sterile phosphate-buffered saline, PBS) for seven days by oral gavage. We assessed the differences in IL-25, IL- 13, and IL-5 concentrations by first using enzyme-linked immunosorbent assays (ELISA) (see Methods). We found higher colonic IL-25 protein concentrations in vancomycin-treated mice compared to untreated (p=0.001). AVNM-treated (p=0.001) and metronidazole-treated (p=0.001) mice (Fig. 1A). Concentrations of IL-5 and IL-13 protein were also significantly elevated in the colon of vancomycin-treated mice compared to untreated, metronidazole-treated, or

AVNM-treated mice (p<0.05) (Fig. 6A). Interestingly, no increase in IL-25, IL-13 or IL-5 was observed in the cecum nor in the ileum (Figs. 6B-C), suggesting an anatomically compartmentalized effect of vancomycin. These initial results drove our interest specifically to the behavior of colonic TCs interacting with the microbiota. Reverse transcription-quantitative polymerase chain reaction (RT-qPCR) performed on a subset of samples recapitulated the IL-25 results. Colonic IL-25 expression was significantly increased in vancomycin-treated mice (p-value ANOVA with Tukey post-hoc = 0.001) compared to mice that received PBS (e.g., untreated), or metronidazole (p = 0.01) (Fig. IB). We then evaluated TC expansion by assessing the ratio of DCLK⁺ expressing epithelial cells relative to the number of epithelial (EPCAM+) cells via flow' cytometry (von Moltke et al., 2016) (Fig. 1C, Fig. 7) (See Methods), and confirmed flow results via immunohistochemistry (IHC) staining of DCLK1 -expressing cells (Fig. ID). Mice treated with vancomycin showed significantly higher proportions of TCs in the colon by flow- cytometry compared to mice receiving PBS (p = 0.005), and a marginally significant increase compared to metronidazole (Fig. 1C). Similarly, IHC showed that vancomycin-treated mice showed higher number of DCLK1 -expressing cells compared to those treated with metronidazole or left untreated (Fig. ID) The observed phenotype was independent of intestinal colonization by fungi, a potential succinate producer (Begum et al., 2022), as confirmed by treatment with the antifungal amphotericin B (See Methods) which resulted in no change to the enhanced IL-25, IL-13, and IL-5 protein concentrations in vancomycin-treated animals (Fig. 8). We performed 16S ribosomal RNA (16S rRNA) sequencing of fecal pellets from vancomycin-treated mice before (Day 0), during (Day 1), and at the end (Day 10) of vancomycin treatment, and of fecal pellets from corresponding time-points in PBS-treated mice (Fig. IE). Principal coordinate analysis revealed distinct sample separation based on treatment (PCI) and the timing of treatment for vancomycin-treated mice (PC2) (Fig. IF). Utilizing DeSeq2 for differential analysis (Love et a , 2014), we identified an enrichment of Amplicon Sequencing Variants (SVs) associated with succinate-producing Bacteroides thetaiotaomicron and Staphylococcus xylosus in vancomycin-treated mice compared to untreated controls (Fig. 1G). Our findings demonstrate that vancomycin administration leads to an elevation in IL-25, IL-13, and IL-5 concentrations and TC hyperplasia in the proximal colon. This correlation coincides with the enrichment of the succinate-producer B. thetaiotaomicron in the microbiome. Example 2. Microbiome reconstitution with FMT enriched in succinate- producing bacteria increases IL-25, IL- 13, and IL-5 in the colon but not in the cecum or ileum.

To demonstrate a causal role for the microbiome in inducing colonic IL-25, IL-13, and IL-5, we performed fecal matter transplant (FMT) experiments as previously described (Ubeda et al., 2013). Mice were either pre-treated with AVNM ad-libitum in drinking water for 7 days or left untreated (sterile PBS). After pretreatment, mice were orally administered a pooled stool fraction obtained from mice subjected to one week of vancomycin treatment; vancomycin treatment was discontinued 24 hours before donor feces collection. An FMT from mice left untreated was used as control. We observed a significant increase in the colonic concentrations of IL-25 and IL-5 (FDR adjusted p-value ANOVA with Tukey post- hoc < 0.05) and a marginally significant increase in IL- 13 (p-value=0.09) in AVNM- pretreated mice receiving vancomycin-treated stool compared to untreated stool (Fig. 2A). No difference was observed in mice that were not AVNM pretreated (Fig. 2A). No significant difference in IL-25 was observed in the cecum or the ileum between mice receiving vancomycin-treated stool or untreated stool irrespective of the pretreatment background (Fig. 2B), suggesting that this microbiome-dependent induction is location dependent. This prompted our subsequent experiments to focus on colonic TCs and compare them to small intestinal TCs previously described in the literature to be responsive to the microbiome.

To determine differences in the microbiome of mice that differentially responded to FMTs, we performed 16S rRNA sequencing of fecal samples from all mice obtained 24 hours after the last FMT. Echoing the findings from the selective microbiome depletion experiment (Fig. 1D-F), the FMT input from vancomycin- treated mice exhibited a dominance (>50%) of B. thetaiotaomicron, which was successfully transferred to AVNM-treated mice receiving vancomycin FMT (Fig. 2C). No significant differentially abundant species were observed post-transplant in mice receiving FMT from vancomycin-treated mice or untreated mice if they did not receive a pre-treatment with AVNM (FDR adjusted p-value >0.05 using DeSeq2, see (Love et al., 2014)). This is expected, as either perturbed or naturally dysbiotic microbiotas are needed to facilitate colonization by FMT-derived bacteria (Suez et al., 2018). For the mice that received AVNM pre-treatment, amplicon sequencing variants (AS Vs) belonging to succinate-producing species of Bacter aides thetaiotaomicron and Enteroccocus faecalis (Catlett et al.. 2020; Kim et al.. 2016) were observed to be significantly increased in relative abundance in mice receiving stool from vancomycin-treated relative to untreated mice (Fig. 2D) (FDR adjusted p-value < 0.05 using DeSeq2, see (Love et al., 2014)). To identify which bacterial species were associated with the observed host induction in the AVNM-pretreated mice, we took advantage of random forest regression (RFR) modeling as we have previously described (Wipperman et al., 2021). Specifically, we used RFR to predict the concentration of IL -25 in every sample as a function of the abundances of all detected SVs in these mice (See Methods). SVs mapping to B. thetaiotaomicron and E. faecalis were found to be the only two bacteria (Fig. 2E) whose increase in abundance predicts a significant increase in colonic IL-25 concentrations. Positive significant associations between the abundance of B. thetaiotaomicron and E. faecalis SVs and colonic IL-25 concentrations were corroborated by running Elastic Net as well as Bayesian Variable Selection linear regression modeling on this data (Fig. 2F, Fig. 9). Taken together, these data show that microbiome reconstitution with stool fractions leading to the enrichment in succinate-producing bacteria such as B. thetaiotaomicron coincides with the elevation of IL-25 and type 2-associated cytokines in the colon.

Example 3. Microbiome reconstitution with defined bacterial consortia of succinate-producing strains increases IL-25, IL-13, and IL-5 in the colon but not in the cecum or ileum.

The data from the FMT experiments provides causal evidence of the microbiome in promoting TC-dependent cytokine production in the colon. To demonstrate that this effect can be recapitulated by administration of a limited consortium of bacteria actively producing succinate, we first performed reconstitution experiments where AVNM-pretreated mice were re-colonized with either a consortium of three known in vivo succinate-producing Bacteroides and Segatella species (Bacteroides thetaiotaomicron, Bacteroides vulgatus, Segatella copri) (Ferreyraet a/., 2014; Iljazovic et al., 2021; Louis and Flint, 2017), a consortium of three common gut bacteria with no known in vivo succinate production (Eggerthella lenta. Eubacterium eligens, Dorea formicigenerans), or with PBS as control (See

Methods). Mice receiving the succinate-producing consortium showed a significantly higher colonic concentration of IL-25, IL-13, and IL-5 (two-sample t-test p < 0.05) compared to those receiving the non-succinate-producers (Fig. 3A-C). As in the stool transplant experiments, we did not observe significant differences between treatments in IL-25 protein concentrations in these animals' cecum or ileum (Fig. 3D,E). This was also associated with a significantly higher percentage of TCs in the colons of succinate producing bacteria-recipient mice compared to those receiving the nonproducing strains, as measured by flow cytometry, with no significant differences observed in the ileum. (Fig. 3F). Colonic TC expansion in succinate producing bacteria-recipient mice mice was validated through quantification of DCLK1- expressing cells, as assessed by IHC (Fig. 3G). Accordingly, we performed shotgun metagenomic analysis of the intestinal compartments and found significantly higher colonization by the succinate producers species B. thetaiotaomicron and B. vulgatus in the colon, but not in the ileum of the mice receiving producers (Fig. 3H). Similarly, we observed colonization of the non-producers species E. lenta and D. formicigenerans in the colon, but not in the ileum of the mice receiving the nonproducers (Fig. 3H). This confirmed that the difference in host phenotype induction observed in the colon of these animals was due to colonization by the inducing bacterial strains.

We then tested whether the administration of succinate-producing bacteria significantly increased succinate concentration in the gut by performing targeted metabolomics for succinate and other microbiota-associated SCFAs from colonic content, ileal contents and fecal samples from Untreated, AVNM-treated, AVNM pretreated receiving FMT from vancomycin-treated mice, AVNM pre-treated receiving succinate-producing bacteria, AVNM pre-treated receiving non-succinate-producing bacteria or AVNM pre-treated given vehicle (PBS) (See Methods). Mice gavaged with the succinate-producing bacteria after AVNM pre-treatment displayed significantly higher concentrations of succinate compared to mice that received nonproducing microbes (two-sample t-test p < 0.05) (Fig. 31, Fig. 10). No difference in succinate concentrations was detected in the ileum (Fig. 31), suggesting that local succinate production underpins type-2 response and TC expansion in the colon. Moreover, although several other SCFAs were enriched in mice receiving the succinate producers compared to the non-succinate producers in the colon, they were similarly enriched in the ileum (Fig. 31) ruling out their association with the TC expansion occurring solely in the colon.

B. thetaiotaomicron emerged as the microbe most strongly associated with phenotype induction in the antibiotic treatment and fecal microbiota reconstitution experiments (Figs. 1A-G, 2A-F). Consequently, we aimed to verify that administering B. thetaiotaomicron would lead to the expansion of colonic TCs. AVNM-treated animals orally gavaged with B. thetaiotaomicron alone showed a higher number of DCLK1 expressing cells compared to AVNM-treated animals mice administered with heat-killed B. thetaiotaomicron or vehicle (PBS) (p-value ANOVA with Tukey post- hoc < 0.05) (Fig. 4A).

We subsequently sought to confirm that succinate drives TC hyperplasia in the colon. To do this, we compared TC expansion in AVNM-pretreated mice that were orally gavaged with either wild-type (WT) B. thetaiotaomicron or the succinate production-deficient B. thetaiotaomicron fumarate reductase knockout (Dfrd) (Spiga et al.. 2017). AVNM-pretreated mice administered with the WT succinate-producing B. thetaiotaomicron displayed a significantly higher number of DLCLK1 -expressing cells to those administered with the B. thetaiotaomicron Dfrd knockout (p-value ANOVA with Tukey post-hoc < 0.05) (Fig. 4A). Similarly, AVNM-pretreated mice administered with the WT succinate-producing B. thetaiotaomicron showed higher percentage of TCs compared to those administered with the B. thetaiotaomicron Dfrd knockout or heat-killed B. thetaiotaomicron (p-value ANOVA with Tukey post-hoc < 0.05) in the colon, but not in the ileum (Fig. 4B). This also corresponded to higher concentrations of IL-25 mRNA expression (Fig. 4C) in the colon.

Shotgun metagenomic analysis of the colonic and ileal contents demonstrated that while both B. thetaiotaomicron and B. thetaiotaomicron Afrd were able to colonize the colonic compartment similarly, less degree of colonization was observed in the ileum by either strain, and particularly by B. thetaiotaomicron Afrd (Fig. 4D). Similarly, metabolomics analysis in the ileum and the colon demonstrated significantly higher (ANOVA Tukey adjusted p-value < 0.05) succinate concentrations in the colon of AVNM-pretreated mice gavaged with wild-type B. thetaiotaomicron compared to those receiving B. thetaiotaomicron Dfrd or heat-killed B. thetaiotaomicron, but not in the ileum (Fig. 4E). Interestingly, we also observed significant differences in the concentrations of other SCFAs among the three treatments (Fig. 4E).

To evaluate the effect that succinate production by B. thetaiotaomicron has on other colonic cytokines, we examined samples of inflammatory cytokines in colonic tissues by multiplexed ELISA from mice orally administered with wild-type B. thetaiotaomicron or with B. thetaiotaomicron Dfrd. We found no differences in colonic concentrations of type 1 (IL- lb, IL-2, IL-21) and type 3 cytokines (IL-22) (Student t-Test p > 0.05) (Fig. 4F). We found a significant reduction in type 2- associated cytokines such as IL-31 and IL-33 in mice gavaged with B. thetaiotaomicron Dfrd compared to mice gavaged with WT B. thetaiotaomicron (Fig. 4G), confinning the dependency of type 2-related cytokines on B. thetaiotaomicron- produced succinate.

To determine if the increase of TC in response to B. thetaiotaomicron- produced succinate is intrinsic to TCs, we compared the frequency of TCs in ANVM- treated mice that were then orally gavaged with wild-type B. thetaiotaomicron or B. thetaiotaomicron Dfrd in C57BL/6 wild-type (Pou2f3^+,+ Pou2f3⁺'\ and Pou2f3 " mice. POU2F3 is a transcription factor essential for the differentiation of DCLK1+ TCs throughout the body, including in the gastrointestinal (GI) tract, and is implicated in the regulation of mucosal type 2 responses to helminth infection (Gerbe et al., 2016). AVNM pre-treated C57BL/6 wild-type mice administered with wild-type B. thetaiotaomicron displayed a significantly higher percentage of TCs compared to those gavaged with B. thetaiotaomicron Dfrd (two-samples t-test p-value < 0.05) in the proximal colon (Fig. 4H). In the colon, TCs were also marginally elevated (p- value=0.104) in AVNM pre-treated heterozygous mice (Pou2f3⁺') receiving B. thetaiotaomicron compared to B. thetaiotaomicron Dfrd, but no difference was observed in the knockout mice (Pou2f3'^/') (Fig. 4H). Despite a genotype-dependent TC abundance, with C57BL/6 wild-type mice displaying more TCs compared to Pou2f3 ~ and Pou2f3~^/' in both the colon and the ileum (Fig. 4H), no difference in TC percentages was observed between B. thetaiotaomicron and B. thetaiotaomicron Dfrd in the ileum. The significance of genotype-dependent TC hyperplasia in response to B. thetaiotaomicron versus B. thetaiotaomicron Afrd treatment was confirmed by fitting a linear model with interaction to the TC percentages and examining the significance of the interaction coefficient (p = 0.037 from the ANOVA Table, See Methods). Notably, this effect was not observed in the ileum (p > 0.05 from the ANOVA Table, See Methods), further emphasizing the importance of colonic colonization by this bacterium for inducing this response. Similar trends were observed when measuring IL-25 gene expression. A statistically significant elevation in IL-25 transcript was observed in the colon of C57BL/6 wild-ty pe mice when administered with B. thetaiotaomicron compared to B. thetaiotaomicron Dfrd in the colon (adjusted p < 0.05 ANOVA with Tukey post-hoc test) but not in the ileum (Fig. 41). An almost total absence of expression was seen in all Pou2f3'" mice irrespective of the B. thetaiotaomicron strain administered (Fig. 41).

Taken together these data provide evidence that precise microbiome supplementation with succinate-producing bacteria increases succinate concentration, TCs and type 2 cytokines in the colon, with no effect on type 1 and 3 cytokines. Additionally, the data suggest that succinate production by the microbiome is a primary driver of TC expansion in the colon, where the supplemented bacteria engraft. Finally, these data highlight the importance of POU2F3 for IL-25 production in response to succinate-producing bacteria.

Example 4. Prophylactic administration of succinate producing bacteria promotes TCs-mediated protection against C. difficile-induced morbidity and mortality.

Although succinate accumulation in the lumen can promote C. difficile expansion in the intestine (Ferreyra et al., 2014), it is unknown how this translates into host susceptibility to C. difficile-induced disease. Oral administration of recombinant IL-25 protects mice against C. difficile morbidity’ and mortality with no significant differences in C. difficile luminal CFUs (Buonomo et al., 2016). Therefore, we hypothesized that microbiome reconstitution with succinate-producing bacteria might promote colonic TC expansion and initiate a succinate- and TC-dependent immune response that could culminate in protection against C. difficile-cnused morbidity’ and mortality.

To test this hypothesis, we utilized the cefoperazone-induced C. difficile infection (CDI) model (Theriot et al., 2011), which we combined with our previously published approach for the adoptive transfer of C. difficile disease-ameliorating consortia (Buffie et al.. 2015; Dsouza et al., 2022) (See Methods) (Fig. 5A).

Following AVNM treatment and concurrently with cefoperazone treatment, we first administered a suspension of either the succinate-producing bacteria consortium (B. thetaiotaomicron, B. vulgatus, P. copri ). a heat-killed control of the consortium, or PBS to animals prior to infection with C. difficile VPI 10463. Adoptive transfer of the consortium alone significantly ameliorated CDI by increasing survival (log-rank survival test p-values = 0.051 and 0.014; producers vs. PBS and producers vs. heat- killed, respectively) (Fig. 5B) and resulted in reduced weight loss compared to both controls (two-samples t-test Benjamini -Hochberg adjusted p-value < 0.05 comparing weight loss in producers versus PBS and producers versus heat-killed independently at different time points) (Fig. 5C). We measured C. difficile burden in the animals by quantifying the copies of the C. difficile toxin A (icdA) gene from 100 mg of cecal content as in (Kubota et al., 2014) two days post-infection of mice gavaged with the succinate-producing consortium vs. PBS. No significant difference was found between treatments (two-samples t-test p-value > 0.05) (Fig. 5D), suggesting that the protection conferred by the succinate-producers is not due to the consortium directly impacting C. difficile colonization in the intestine.

To determine if the observed protection against CDI was mediated by the presence of TCs, we compared survival and weight loss in Pou2f3⁺'~ and Pou2f3' ' mice that were gavaged with the consortium of succinate-producing bacteria. As hypothesized, Pou2f3⁺ ' and Pou2f3'^/' animals displayed increased death and weight loss compared to WT mice despite being gavaged with the succinate producers (Fig. 5E,F). However, heterozygous Pou2f3⁺ ' mice had significantly higher survival (p- value = 0.008 log-rank survival test) (Fig. 5E) and reduced weight loss compared to the homozy gous Pou2f3'^/' (Fig. 5F) (two-samples t-test p-value < 0.05 comparing weight loss between the two genotypes). In contrast, no statistical difference in survival or weight loss due to CDI was observed between C57BL/6 wild-type and homozygous Pou2f3'^!' mice (Fig. 5G,H) receiving vehicle (PBS) suggesting that the observed protection is not due to baseline genofypic differences or to other effects that are independent of the administration of the succinate-producing bacteria. Although TC percentage is decreased in mice receiving cefoperazone compared to untreated controls (Fig. 51), we confirmed that C57BL/6 wild-type mice demonstrated a significantly higher percentage of TCs when administered with succinate-producing bacteria compared to controls immediately before C. difficile inoculation, a phenomenon not observed in the Pou2f3~^!~ background (Fig. 5 J). Interestingly, the indicated TC expansion is sufficient to provide protection even though it does not return TCs to or elevate them above baseline levels. Consistent with previous experiments, treatment with succinate producers just before C. difficile inoculation corresponded to significantly higher succinate concentrations in the colon of C57BL/6 wild-ty pe mice, but not in Pou2f3' ~ mice (Fig. 5K). To demonstrate that protection was due to the succinate produced by these bacteria we performed a cefoperazone- induced C. difficile infection experiment in where C57BL/6 wild-type mice were orally gavaged daily for three days with either B. thetaiotaomicron or the succinate production-deficient B. thetaiotaomicron Dfrd. B. thetaiotaomicron recipient mice demonstrated significantly higher survival (Fig. 5L) (log-rank survival test p-values = 0.0044) and reduced weight loss (Fig. 5M) compared to the mice receiving B. thetaiotaomicron Dfrd. Based on our indication that B. thetaiotaomicron and B. thetaiotaomicron Dfrd achieve a similar abundance in the colon post-antibiotic treatment in our animal model (Fig. 4D), these data shows that the observed difference in morbidity and mortality’ is due to differential succinate production by these two strains.

Altogether our data provide causal evidence that the administration of succinate-producing bacteria promotes TC expansion to protect against C. difficile- induced morbidity and mortality. This protection is dependent on the ability’ of the administered bacteria to produce succinate and on the presence of Pou2f3-dependent TCs in the colon. The observed protection does not appear to be due to a reduced C. difficile titer in the intestine.

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OTHER EMBODIMENTS

It is to be understood that while the invention has been described in conjunction with the detailed description thereof, the foregoing description is intended to illustrate and not limit the scope of the invention, which is defined by the scope of the appended claims. Other aspects, advantages, and modifications are within the scope of the following claims.

Claims

WHAT IS CLAIMED IS:

1 . A composition comprising at least two, three, four, or five in vivo succinate- producing microorganisms, preferably Bacteroides and Prevotella species (preferably Bacteroides thetaiotaomicron (optionally VPI 5482), Bacteroides vulgatus (optionally NCTC 11154), and/or Pre votella copri (optionally DSM 18205)), Parabacteroides (optionally Parabacteroides distasonis). and Bacilli (e.g., Lactobacillus animalis).

2. The composition of claim 1, further comprising a buffer or carrier.

3. The composition of claim 1, which is a food composition, optionally a liquid or solid food.

4. The composition of claims 1-3, comprising only one, two, or three of the succinate-producing microorganisms, which comprises only those three and no other microorganisms, or comprises up to one, two, three, four, five, six, seven, eight, nine, ten. 20, 25, 30, 35, 40, 45, or 50 additional species of microorganisms.

5. The composition of claims 1-3, wherein the microorganisms in the composition consist of only Bacteroides thetaiotaomicron (optionally VPI 5482), Bacteroides vulgatus (optionally NCTC 11154), and Prevotella copri (optionally DSM 18205), and optionally one or both of a Parabacteroides (optionally Parabacteroides distasonis), and Bacilli (optionally Lactobacillus animalis').

6. A method of treating or reducing risk of developing an intestinal infection in a subject, optionally an infection with Clostridioides difficile, Campylobacter, Salmonella, E. coli, Shigella, Listeria monocytogenes. Vibrio, Enteropathogenic E. coli, or Klebsiella, the method comprising administering the composition of claims 1-5 to a subject in need thereof.

7. The method of claim 6, wherein a subject is at risk of developing an intestinal infection is a subject who is in or is about to be in a communal living situation, or who is being treated or about to be treated with an antibiotic that increases the risk of developing the intestinal infection.

8. The method of claims 6 or 7, wherein the intestinal infection is an infection with Clostridioides difficile.

9. A method of promoting expansion of colonic tuft cells in a subject, the method comprising administering the composition of claims 1-5 to a subject in need thereof.

10. The composition of claims 1-5 for use in a method of treating or reducing risk of developing an intestinal infection in a subject, optionally an infection with Clostridioides difficile, Campylobacter, Salmonella. E. coli. Shigella, Listeria monocytogenes, Vibrio, Enteropathogenic E. coli, o Klebsiella, the method comprising administering the composition to a subject in need thereof.

11. The composition for the use of claim 10. wherein a subject who is at risk of developing an intestinal infection is a subject who is in or is about to be in a communal living situation.

12. The composition for the use of claim 10. wherein a subject who is at risk of developing an intestinal infection is being treated or about to be treated with an antibiotic that increases the risk of developing the intestinal infection.

13. The composition for the use of claim 12, wherein the antibiotic is cefoperazone, clindamycin, cefixime. cefdinir, cefuroxime. cefpodoxime, amoxicillin/clavulanate, ciprofloxacin, moxifloxacin, dicloxacillin, or cefaclor.

14. The composition for the use of claims 10 to 13, wherein the intestinal infection is an infection with Clostridioides difficile.

15. The composition of claims 1-5, for use in a method of promoting expansion of colonic tuft cells in a subject, the method comprising administering the composition to a subject in need thereof.

16. The composition for the use of claims 10 to 15, wherein the composition is formulated to be administered orally.

17. The method of any of claims 6-9, wherein the composition is administered orally.