KEYWORDS:Clostridioides difficile,Clostridium difficile, gut inflammation, host-pathogen interactions, intestinal immunity, mucosal immunity

IL-10 deficiency decreases susceptibility to acuteC. difficile infection.

At steady state, IL-10 maintains intestinal homeostasis by negatively regulating commensal bacterium-driven expression of proinflammatory cytokines. In the context ofC. difficile infection, many of these proinflammatory cytokines correlate with increased disease severity. However, it is unclear whether the inflammatory profile associated with infection emerges followingC. difficile-mediated tissue damage or if it proactively drives pathology and worsens disease (20,21). To address this question, intestinal inflammation was induced independently ofC. difficile infection using the murineIl10^−/− spontaneous colitis model, and the impact of constitutive inflammation onC. difficile disease severity was examined. CohousedIl10^−/− and littermateIl10 heterozygous mice (Il10^HET) were treated with a broad-spectrum antibiotic cocktail in their drinking water to induce susceptibility toC. difficile and mimic the microbiota dysbiosis observed in patients at high risk for contractingC. difficile. Antibiotic-treatedIl10^HET mice exhibited peak disease severity within 48 hours of infection, as measured by a disease score based on weight loss, body temperature, diarrhea, and lethargy (Fig. 1A), and approximately 75% mortality rate (Fig. 1B). In contrast,Il10^−/− mice experienced reduced disease severity at 2 days postinfection (p.i.) (Fig. 1A) and were less likely to succumb to acuteC. difficile infection thanIl10^HET mice (Fig. 1B).

Il10^−/− mice challenged with pathogenicEscherichia coli,Salmonella enterica serovar Typhimurium,Citrobacter rodentium,Toxoplasma gondii, orCandida albicans all display improved pathogen clearance via enhanced phagocytic mechanisms by innate immune cells (29–33). Thus,C. difficile burden was measured at days 1 and 2 p.i. No difference inC. difficile burden was observed in the cecal content ofIl10^HET andIl10^−/− mice at days 1 (Fig. 1C) and 2 p.i. (Fig. 1D). Further,C. difficile toxin activity in the cecal content ofIl10^HET andIl10^−/− mice was similar at day 2 p.i., as measured by anin vitro cell-rounding assay (Fig. 1E). Together, these data indicate that loss of IL-10 augments host immunity followingC. difficile infection but does not alter the establishment of infection or production of toxins, the primary virulence factors ofC. difficile.

Intestinal inflammation and the subsequent onset of spontaneous colitis inIl10^−/− mice vary between vivaria and are dependent on the microbiota (25,26). For example,Helicobacter species are well-known colitogenic triggers inIl10^−/− mice (34,35). Prior to cohousing, we confirmed the presence ofHelicobacter spp. in the feces of ourIl10^−/− mice colony but not vendor-purchased C57BL/6 mice (Fig. S1A). To test the rigor of the observed enhanced survival phenotype inC. difficile-infectedIl10^−/− mice, wild-type C57BL/6 andHelicobacter-positiveIl10^−/− mice were cohoused and infected withC. difficile at an independent animal facility. In agreement with our studies inIl10^HET mice,Il10^−/− mice exhibited improved survival (Fig. S1B) compared to cohoused C57BL/6 mice followingC. difficile infection despite no difference inC. difficile burden (Fig. S1C) or toxin production (Fig. S1D) at days 2 and 4 p.i. These complementary experiments demonstrate the robustness of this phenotype.

Enhanced protection inIl10^−/− mice is not driven by a distinct microbiota composition.

The composition of the microbiota impactsC. difficile pathogenesis through multiple direct and indirect mechanisms (36); therefore, cohoused littermate mice were used to normalize for this variable. To test the null hypothesis that the microbiota composition betweenIl10^HET andIl10^−/− mice was indistinguishable, bacterial 16S rRNA marker gene profiling was conducted on cecal content fromIl10^HET andIl10^−/− mice collected at day 2 afterC. difficile or mock infection. Microbial community alpha diversity was not different between uninfected or infectedIl10^HET andIl10^−/− mice (Fig. 2A). Comparison of 16S rRNA bacterial community profiles betweenIl10^HET andIl10^−/− mice by relative bacterial abundance revealed a bloom of amplicon sequence variants (ASVs) identified asC. difficile in bothIl10^HET andIl10^−/− infected mice compared to uninfected mice; however, the relative abundance composition between infected groups was similar (Fig. 2B). Beta diversity comparisons between samples by unsupervised hierarchical clustering (Fig. 2C), unweighted UniFrac distances (Fig. 2D), or permutational multivariate analysis of variance (PERMANOVA) analysis (Table S1) did not support rejecting the null hypothesis that there was no microbial community level difference betweenIl10^HET andIl10^−/− mice on day 2 following mock infection orC. difficile infection. A linear regression model was used to identify individual ASVs that correlate withIl10^HET andIl10^−/− phenotypes. The linear model readily detectedC. difficile as significantly enriched in infected mice compared to uninfected mice but failed to identify an ASV significantly different between the microbiota of infectedIl10^HET andIl10^−/− mice (Fig. S2A and B).

In a validation cohort, 16S rRNA marker gene profiling was conducted on fecal pellets collected from C57BL/6 andIl10^−/− mice prior to cohousing (day −64 p.i.), throughout cohousing, at the start of antibiotic treatment (day −6 p.i.), and on the day of infection (day 0 p.i.). Prior to cohousing,Il10^−/− mice exhibit a distinct microbiota (Fig. S3A, Table S2). Cohousing shifted the microbiota of C57BL/6 mice to resemble the microbiota ofIl10^−/− mice, as determined by unweighted UniFrac distance analysis (Fig. S3A), relative bacterial genus abundance (Fig. S3B), unsupervised hierarchical clustering (Fig. S3C), and PERMANOVA analysis (Table S2). Antibiotic treatment between day −6 and 0 p.i. significantly reduced the alpha diversity (Fig. S3D) and shifted the microbiota of both C57BL/6 andIl10^−/− mice, but no difference between groups was observed (Table S2). To identify specific ASVs that were differentially abundant between cohoused C57BL/6 andIl10^−/− mice, a linear discriminant analysis effect size (LEfSe) comparison was conducted. Several ASVs were differentially abundant within the microbiota of C57BL/6 andIl10^−/− mice prior to cohousing (Fig. S3E). However, following cohousing and antibiotic treatment, none of these differentially abundant ASVs remained (Fig. S3E). Together, these microbial profiling data support the conclusion that the differential outcome observed in antibiotic-treated IL-10-sufficient and -deficient hosts followingC. difficile infection cannot be explained by community-level differences in the microbiota.

Il10^−/− andIl10^HET mice exhibit comparable induction of innate immunity followingC. difficile infection.

No differences inC. difficile colonization, toxin production, or microbiota composition were observed between infectedIl10^HET andIl10^−/− mice to account for enhanced protection inIl10^−/− mice; therefore, potential immune-mediated mechanisms were assessed. Induction of IL-10 is an effective strategy employed by some enteric pathogens to dampen the host immune response to infection (29,30,37–39).C. difficile-derived flagellin, surface layer proteins, and toxin (TcdB) all can induce macrophages, monocytes, and dendritic cells to produce IL-10in vitro (40–42). Indeed, C57BL/6 mice infected withC. difficile have elevated IL-10 protein in the cecal tissue at day 2 p.i. (Fig. 3A). The broad immunosuppressive functions of IL-10 include inhibiting granulocyte infiltration into mucosal tissue and limiting expression of type 1 and type 17 cytokines, components of the immune response that promote protective immunity followingC. difficile infection (43–47).

First, protein levels of lipocalin-2 (LCN-2), an established marker of intestinal inflammation (48), were measured in the cecal content of antibiotic-treated uninfected and day 2 p.i.Il10^−/− andIl10^HET mice (48). LCN-2 levels increased to approximately the same concentration in both groups by day 2 p.i. (Fig. 3B). Next, to thoroughly assess the quality of the innate immune response to acuteC. difficile infection,Il10^−/− andIl10^HET mice were sacrificed at day 2 p.i., and recruitment of innate immune cells and induction of proinflammatory cytokines were assessed. Both infectedIl10^HET andIl10^−/− mice exhibited a robust induction of the innate immune response compared to antibiotic-treated, uninfected, control mice (Fig. 3). No statistically significant differences in the frequency (Fig. S4A to C) or total numbers of infiltrating neutrophils (Fig. 3C), monocytes (Fig. 3D), or eosinophils (Fig. 3E) were observed betweenIl10^−/− andIl10^HET mice at day 2 p.i.Il10^−/− andIl10^HET mice at day 2 p.i. exhibited comparably elevated gene expression ofIfng andIl22 (Fig. 3F) as well as downstream host defense genesNos2 andReg3g in the colon (Fig. 3G). Gamma interferon (IFN-γ) and IL-22 protein concentrations in cecal tissue homogenates were also comparable (Fig. 3H). Type 2 cytokines (IL-5, IL-13, and IL-33), associated with eosinophil activation and protection duringC. difficile infection (15,47,49), were not significantly different in the cecum ofIl10^−/− andIl10^HET mice at day 2 p.i. (Fig. 3I). Finally, no differences in proinflammatory cytokines (IL-1β, IL-6, IL-17a, IL-27, and granulocyte-macrophage colony-stimulating factor) reported to modulateC. difficile pathogenesis (16,50–54) or chemokines (CXCL1, CXCL2, and CCL2) involved in neutrophil and monocyte recruitment were observed in the cecal tissue homogenates ofIl10^−/− andIl10^HET mice at day 2 p.i. (Fig. S4D and E). Collectively, these data indicate the magnitude or quality of the innate immune response inIl10^−/− mice followingC. difficile infection is not driving the attenuated disease phenotype.

Loss of IL-10 signaling prior toC. difficile infection drives immune activation in the intestine and augments protective immunity.

In contrast to the comparable immune responses observed inC. difficile-infectedIl10^−/− andIl10^HET mice, antibiotic-treated, uninfectedIl10^−/− mice at day 2 after mock infection had higher levels of LCN-2 in the cecal content (Fig. 3B) and increased expression of IL-22- and IFN-γ-dependent effector molecules (Fig. 3F) in the large intestine than antibiotic-treated, uninfectedIl10^HET mice. Moreover, antibiotic-treatedIl10^−/− mice at day 0 p.i. displayed elevated immune activation in the large intestine compared toIl10^HET mice, as determined by increased frequency (Fig. 4A) and total numbers (Fig. 4B) of infiltrating neutrophils in the large intestine as well as elevated expression of proinflammatory immune defense genes (Il22,Ifng,Reg3g, andNos2) (Fig. 4C), in agreement with previous reports (55,56). These results support the hypothesis that preexisting immune activation, not the magnitude of the immune response following infection, confers protective immunity inIl10^−/− mice.

To determine whether the loss of IL-10 signaling prior to infection and subsequent immune activation augments protection followingC. difficile infection, IL-10 signaling was selectively blocked in C57BL/6 mice starting either 3 weeks prior to infection or on the day of infection, and survival was assessed. Antibody-mediated blockade of the IL-10-specific receptor IL-10R1 (αIL10R1) administered once a week for at least 3 weeks abrogates IL-10 signaling and replicates the intestinal inflammation observed in germ lineIl10^−/− mice (57). C57BL/6 mice that received weekly αIL10R1 treatment starting 3 weeks prior to infection exhibited survival comparable to that ofIl10^−/− mice and significantly improved survival compared to C57BL/6 mice administered αIL10R1 at day 0 p.i. (Fig. 4D). These data support the hypothesis that IL-10 inhibits basal activation of intestinal immune defense genes prior to infection, thereby rendering the host more susceptible toC. difficile infection.

IL-22 is critical for host defense againstC. difficile infection inIl10^−/− mice.

Inhibition of IL-10 signaling limitsC. difficile pathogenesis only if initiated several weeks prior to infection (Fig. 4D). Further,Il10 deficiency leads to enhanced colonicil22 andifng expression in uninfected mice (Fig. 4C). Both IL-22 and IFN-γ are critical in mounting a protective innate immune response during acuteC. difficile infection (13,14,58). These observations suggest immune activation prior to infection promotes improved survival inIl10^−/− mice. To determine the relative contribution of these cytokine pathways to host protection inIl10^−/− mice,Il22 orTbx21 (the gene that encodes T-bet, a master transcription factor that regulates IFN-γ production) was genetically ablated inIl10^−/− mice. FollowingC. difficile infection,Il10.Tbx21 double knockout (dKO) mice exhibited survival comparable to that ofIl10^−/− mice, suggesting the IFN-γ pathway was dispensable for protection inIl10^−/− mice (Fig. 5A). In contrast,Il10.Il22 dKO mice were acutely susceptible toC. difficile infection (Fig. 5A). To confirm the dependence of IL-22 signaling for host protection in an IL-10-deficient setting, cohoused C57BL/6 orIl10^HET mice andIl10^−/−,Il22^−/−,Il10.Il22 dKO, andIl10r2^−/− mice (IL-10R2 is the shared receptor subunit necessary for both IL-10 and IL-22 signaling) were pretreated with antibiotics and infected withC. difficile. Genetic ablation of IL-22 signaling in an IL-10-deficient setting (Il10.Il22 dKO andIl10r2^−/− mice) led to significantly increased disease morbidity at day 2 p.i. (Fig. 5B) and mortality compared toIl10^−/− mice (Fig. 5C). Collectively, these data support the conclusion that loss of IL-10 signaling leads to activation of IL-22-dependent host defense mechanisms that limitC. difficile pathogenesis.

Mice.

Four- to 6-week-old wild-type C57BL/6J,Il10^−/−,Tbx21^−/−, andIl10rb^−/− mice were purchased from the Jackson Laboratory.Il22^−/− mice were provided by R. Flavell (Yale University). All knockout mouse strains were derived on a C57BL/6 background. All mice were bred and maintained in autoclaved cages under specific pathogen free conditions at the University of Pennsylvania. All experiments with cohoused C57BL/6 andIl10^−/− mice were done at Memorial Sloan Kettering Cancer Center.Il10Il22 dKO andIl10.Tbx21 dKO mice were generated by breedingIl10^−/− mice withIl22^−/− andTbx21^−/− mice, respectively. The presence ofHelicobacter spp., a bacterial genus sufficient to trigger early onset of intestinal inflammation inIl10^−/− mice, was confirmed by PCR in the feces of all breederIl10^−/− mice andIl10^−/−-derived mouse strains (34,35,73). OurHelicobacter species-positiveIl10^−/− mice began to display overt signs of colitis at around 3 to 4 months of age. Therefore, 10- to 14-week-oldIl10^−/− mice were used in our studies. At this age,Il10^−/− mice exhibit increased expression of inflammatory immune genes in the intestine but do not yet display clinical manifestations of spontaneous colitis. Sex- and age-matched control mice were used in all experiments according to institutional guidelines for animal care. All animal procedures were approved by the Institutional Animal Care and Use Committee of the University of Pennsylvania and Memorial Sloan Kettering Cancer Center.

Antibiotic pretreatment,C. difficile infection, and mouse monitoring.

Mice were cohoused for 3 weeks prior to antibiotic treatment and then supplemented with metronidazole (0.25 g/liter), neomycin (Sigma) (0.25 g/liter), and vancomycin (Novaplus) (0.25 g/liter) in drinking water for 3 days. One day following cessation of antibiotic water, mice received 200 mg of clindamycin (Sigma) by intraperitoneal (i.p.) injection. Twenty-four hours later, mice received approximately 400C. difficile spores (VPI 10463 strain, ATCC 43255) via oral gavage. For antibody-mediated blockade experiments, mice received 1 mg of αIL10R1 antibody (clone 1B1.3A; Bio X Cell) or mouse IgG1 isotype control (clone MOPC-21; Bio X Cell) i.p. weekly starting either 3 weeks before infection or on the day of infection. After infection, mice were monitored and scored for disease severity by four parameters: weight loss (>95% of initial weight, 0; 95% to 90% initial weight, 1; 90% to 80% initial weight, 2; <80%, 3), surface body temperature (>32°C, 0; 32°C to 30.5°C, 1; 30.5°C to 29°C, 2; <29°C, 3), diarrhea severity (formed pellets, 0; loose pellets, 1; liquid discharge, 2; no pellets/caked to fur, 3), morbidity (score of 1 for each symptoms with a maximum score of 3; ruffled fur, hunched back, lethargy, and ocular discharge). Mice that exhibited severe disease, defined as a surface body temperature below 29.5°C or weight loss in excess of 30%, were humanely euthanized by CO₂ displacement.

C. difficile quantification.

Fecal pellets or cecal content were resuspended in deoxygenated phosphate-buffered saline (PBS), and 10-fold serial dilutions were plated anaerobically at 37°C on brain heart infusion agar supplemented with yeast extract,l-cysteine,d-cycloserine, cefoxitin, and taurocholic acid (CCBHIS-TA). CFU were enumerated 24 h later. Prior to infection, fecal samples from mice were cultured overnight in CCBHIS-TA liquid broth and then serially diluted and grown for 24 h on CCBHIS-TA plates to ensure that mice did not harbor endogenousC. difficile in their microbiota. Supernatants from the cecal or fecal content were obtained after centrifugation for cytotoxicity assays and LCN-2 enzyme-linked immunosorbent assay (ELISA) (Bethyl Labs).

C. difficile toxin cytotoxicity assay.

Vero cells were seeded in 96-well plates at 1 × 10⁴ cells/well and incubated for 24 h at 37°C in 5% CO₂. Cecal or fecal supernatants were added in 10-fold dilutions to the Vero cells (100 μl/well) and incubated overnight prior to removal, rinsing with PBS, and replacement with fresh media. The presence ofC. difficile toxins A and B was confirmed by neutralization with antitoxin antisera (Techlab, Blacksburg, VA). The data are expressed as the log₁₀ reciprocal value of the last dilution where cell rounding was observed. Cell morphological changes were observed after 18 h using a Nikon inverted microscope. The cytopathic effect was determined as rounded cells compared to the negative-control wells.

16S rRNA sequencing.

Cecal content was collected from uninfected mice and mice infected withC. difficile at 2 days p.i. DNA was extracted using the Qiagen MagAttract power microbiome kit DNA/RNA kit (catalog no. 27500-4-EP; Qiagen) and used for rRNA sequencing andHelicobacter species PCR. Genus-specific PCR was conducted on purified bacterial DNA from feces ofIl10^−/− breeder mice, and the V4-V5 region of the 16S rRNA gene was amplified from each sample using the dual indexing sequencing strategy as described previously (74). Sequencing was done on the Illumina MiSeq platform. The V4-V5 region of the 16S rRNA gene was sequenced and demultiplexed using the fqgrep tool. Data were imported into QIIME2 (v. 2020.2) (75) and denoised using the DADA2 plugin (76). For data in Fig. S3 in the supplemental material, the fqgrep tool (https://github.com/indraniel/fqgrep) was used to demultiplex the sequences, followed by denoising using the DADA2 (v. 1.14.1) (76) implementation in R (v. 3.6.3) (77). Due to quality issues on the reverse reads, only the forward reads were used for denoising. Data sets were taxonomically classified in QIIME2 using the q2-feature-classifier (78) classify-sklearn naive Bayes classifier with a newly generated classifier against Greengenes 13_8 99% operational taxonomic unit (OTU) sequences (79). Phylogenetic trees were generated using mafft (80) and the q2-phylogeny plugin (81). Data were then imported into R for further analyses with phyloseq (v. 1.30.0) (82) and visualization with ggplot2 (v. 3.3.0) (83). Unweighted UniFrac (84) dissimilarity was calculated to generate principal coordinate analysis plots and for creating dendrograms using the hclust function (stats package in R core, v. 3.6.3). Finally, a linear model was built using the lm() and padjust() functions (stats package, v. 3.6.3) as well as the Tidyverse package (v. 1.3.0) (85).

Isolation of lamina propria cells and flow cytometry.

Single-cell suspensions were obtained from the large intestine lamina propria compartment by longitudinally cutting the large intestine and washing out its contents in PBS. Intestinal tissues were incubated at 37°C under gentle agitation in stripping buffer (PBS, 5 mM EDTA, 1 mM dithiothreitol, 4% fetal calf serum, 10 μg/ml penicillin-streptomycin) for 10 min to remove epithelial cells and then for another 20 min to remove intraepithelial lymphocytes. The tissue was digested with collagenase IV at 1.5 mg/ml (500 U/ml) and DNase (20 μg/ml) in complete medium (DMEM supplemented with 10% fetal bovine serum, 10 μg/ml penicillin-streptomycin, 50 μg/ml gentamicin, 10 mM HEPES, 0.5 mM β-mercaptoethanol, 20 μg/mll-glutamine) for 30 min at 37°C under gentle agitation. Supernatants containing the lamina propria fraction were passed through a 100-μm cell strainer and then a 40-μm cell strainer. After counting, cells were plated at 10⁶ cells per well in 96-well round-bottom plates and washed twice in PBS before incubating with a cell viability dye for 20 min at room temperature (Invitrogen AQUA dye). After Fc blockade (anti-mouse CD16/32 clone 2.4G2; BD Biosciences), cells were stained using a standard flow cytometric staining protocol with fluorescently conjugated antibodies specific to CD3ε, CD5, CD19, CD45, major histocompatibility complex class II, Siglec-F, Ly-6G, Ly6C, CD11b, and CD11c. Stained cells were kept in fluorescence-activated cell sorter (FACS) buffer at 4°C until run. Samples were acquired on an LSR-II flow cytometer (Becton, Dickinson). Data were analyzed using FlowJo version 9.9.6 software. Cell populations were calculated from total cells per colon as a percentage of live CD45⁺ cells.

Cytokine and chemokine quantification.

Cecal tissue was homogenized in tissue extraction buffer with protease inhibitors for 1 min by bead beating with steel beads. Homogenates were centrifuged at 10,000 rpm for 5 min, and supernatants were collected and stored at −80°C. Supernatants containing protein were analyzed by mouse multiplex Luminex assay (Invitrogen) at the Human Immunology Core at University of Pennsylvania. Concentrations are displayed as nanogram of analyte per gram of cecal tissue.

Tissue RNA isolation, cDNA preparation, and qRT-PCR.

RNA was isolated from proximal colon tissue using mechanical homogenization and TRIzol isolation (Invitrogen) according to the manufacturer’s instructions. cDNA was generated using QuantiTect reverse transcriptase (Qiagen). Quantitative reverse transcription-PCR (RT-PCR) was performed on cDNA using either TaqMan primers and probes or QuantiTect primers in combination with TaqMan PCR master mix (ABI) or SYBR green chemistry, and reactions were run on a RT-PCR system (QuantiStudio 6 Flex; Applied Biosystems). Gene expression is displayed as fold increase over antibiotic-pretreated, uninfected control mice and was normalized to theHprt gene.

Statistical analysis.

Results represent means ± standard errors of the means (SEM). Statistical significance was determined by unpairedt test and log-rank test for survival curve. Statistical analyses were performed using Prism GraphPad software v6.0 (*,P < 0.05; **,P < 0.01; ***,P < 0.001).

• 1.Lessa FC, Mu Y, Bamberg WM, Beldavs ZG, Dumyati GK, Dunn JR, Farley MM, Holzbauer SM, Meek JI, Phipps EC, Wilson LE, Winston LG, Cohen JA, Limbago BM, Fridkin SK, Gerding DN, McDonald LC. 2015. Burden ofClostridium difficile infection in the United States. N Engl J Med372:825–834. 10.1056/NEJMoa1408913. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 2.Ofori E, Ramai D, Dhawan M, Mustafa F, Gasperino J, Reddy M. 2018. Community-acquired Clostridium difficile: epidemiology, ribotype, risk factors, hospital and intensive care unit outcomes, and current and emerging therapies. J Hosp Infect99:436–442. 10.1016/j.jhin.2018.01.015. [DOI] [PubMed] [Google Scholar]
• 3.CDC. 2019. Clostridioides difficile. CDC’s 2019 antibiotic resistant threats report. CDC, Atlanta, GA. [Google Scholar]
• 4.Guh AY, Mu Y, Winston LG, Johnston H, Olson D, Farley MM, Wilson LE, Holzbauer SM, Phipps EC, Dumyati GK, Beldavs ZG, Kainer MA, Karlsson M, Gerding DN, McDonald LC, Emerging Infections Program Clostridioides difficile Infection Working Group. 2020. Trends in U.S. burden ofClostridioides difficile infection and outcomes. N Engl J Med382:1320–1330. 10.1056/NEJMoa1910215. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 5.Collins J, Robinson C, Danhof H, Knetsch CW, Van Leeuwen HC, Lawley TD, Auchtung JM, Britton RA. 2018. Dietary trehalose enhances virulence of epidemicClostridium difficile. Nature553:291–294. 10.1038/nature25178. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 6.Brown AWW, Wilson RB. 2018.Clostridium difficile colitis and zoonotic origins—a narrative review. Gastroenterol Rep6:157–166. 10.1093/gastro/goy016. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 7.Khanafer N, Barbut F, Eckert C, Perraud M, Demont C, Luxemburger C, Vanhems P. 2016. Factors predictive of severeClostridium difficile infection depend on the definition used. Anaerobe37:43–48. 10.1016/j.anaerobe.2015.08.002. [DOI] [PubMed] [Google Scholar]
• 8.Ananthakrishnan AN, McGinley EL, Binion DG. 2008. Excess hospitalisation burden associated withClostridium difficile in patients with inflammatory bowel disease. Gut57:205–210. 10.1136/gut.2007.128231. [DOI] [PubMed] [Google Scholar]
• 9.Sun X, Hirota SA. 2015. The roles of host and pathogen factors and the innate immune response in the pathogenesis ofClostridium difficile infection. Mol Immunol63:193–202. 10.1016/j.molimm.2014.09.005. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 10.Buonomo EL, Petri WA. 2016. The microbiota and immune response duringClostridium difficile infection. Anaerobe41:79–84. 10.1016/j.anaerobe.2016.05.009. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 11.Péchiné S, Collignon A. 2016. Immune responses induced byClostridium difficile. Anaerobe41:68–78. 10.1016/j.anaerobe.2016.04.014. [DOI] [PubMed] [Google Scholar]
• 12.Hasegawa M, Yamazaki T, Kamada N, Tawaratsumida K, Kim Y-G, Nunez G, Inohara N. 2011. Nucleotide-binding oligomerization domain 1 mediates recognition ofClostridium difficile and induces neutrophil recruitment and protection against the pathogen. J Immunol186:4872–4880. 10.4049/jimmunol.1003761. [DOI] [PubMed] [Google Scholar]
• 13.Hasegawa M, Yada S, Liu MZ, Kamada N, Muñoz-Planillo R, Do N, Núñez G, Inohara N. 2014. Interleukin-22 regulates the complement system to promote resistance against pathobionts after pathogen-induced intestinal damage. Immunity41:620–632. 10.1016/j.immuni.2014.09.010. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 14.Abt MC, Lewis BB, Caballero S, Xiong H, Carter RA, Susac B, Ling L, Leiner I, Pamer EG. 2015. Innate immune defenses mediated by two ILC subsets are critical for protection against acuteClostridium difficile infection. Cell Host Microbe18:27–37. 10.1016/j.chom.2015.06.011. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 15.Frisbee AL, Saleh MM, Young MK, Leslie JL, Simpson ME, Abhyankar MM, Cowardin CA, Ma JZ, Pramoonjago P, Turner SD, Liou AP, Buonomo EL, Petri WA. 2019. IL-33 drives group 2 innate lymphoid cell-mediated protection duringClostridium difficile infection. Nat Commun10:2712. 10.1038/s41467-019-10733-9. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 16.Saleh MM, Frisbee AL, Leslie JL, Scully KW, Abhyankar MM, Petri WA, Saleh MM, Frisbee AL, Leslie JL, Buonomo EL, Cowardin CA, Ma JZ. 2019. Colitis-induced Th17 cells increase the risk for severe subsequentClostridium difficile infection. Cell Host Microbe2019:1–10. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 17.Buonomo EL, Madan R, Pramoonjago P, Li L, Okusa MD, Petri WA. 2013. Role of interleukin 23 signaling inClostridium difficile colitis. J Infect Dis208:917–920. 10.1093/infdis/jit277. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 18.Jose S, Mukherjee A, Abhyankar MM, Leng L, Bucala R, Sharma D, Madan R. 2018. Neutralization of macrophage migration inhibitory factor improves host survival afterClostridium difficile infection. Anaerobe53:56–63. 10.1016/j.anaerobe.2018.06.014. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 19.Steiner TS, Flores CA, Pizarro TT, Guerrant RL. 1997. Fecal lactoferrin, interleukin-1β, and interleukin-8 are elevated in patients with severeClostridium difficile colitis. Clin Diagn Lab Immunol4:719–722. 10.1128/CDLI.4.6.719-722.1997. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 20.Yu H, Chen K, Sun Y, Carter M, Garey KW, Savidge TC, Devaraj S, Tessier ME. 2017. Cytokines are markers of theClostridium difficile-induced inflammatory response and predict disease severity. Clin Vaccine Immunol24:e00037-17. 10.1128/CVI.00037-17. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 21.El Feghaly RE, Stauber JL, Deych E, Gonzalez C, Tarr PI, Haslam DB. 2013. Markers of intestinal inflammation, not bacterial burden, correlate with clinical outcomes inClostridium difficile infection. Clin Infect Dis56:1713–1721. 10.1093/cid/cit147. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 22.Ouyang W, Rutz S, Crellin NK, Valdez PA, Hymowitz SG. 2011. Regulation and functions of the IL-10 family of cytokines in inflammation and disease. Annu Rev Immunol29:71–109. 10.1146/annurev-immunol-031210-101312. [DOI] [PubMed] [Google Scholar]
• 23.Fillatreau S, O’Garra A. 2014. Interleukin-10 in health and disease. Curr Top Microbiol Immunol380:i–viii. 10.1007/978-3-662-43492-5. [DOI] [PubMed] [Google Scholar]
• 24.Shouval DS, Ouahed J, Biswas A, Goettel JA, Horwitz BH, Klein C, Muise AM, Snapper SB. 2014. Interleukin 10 receptor signaling: master regulator of intestinal mucosal homeostasis in mice and humans. Adv Immunol122:177–210. 10.1016/B978-0-12-800267-4.00005-5. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 25.Kühn R, Löhler J, Rennick D, Rajewsky K, Müller W. 1993. Interleukin-10-deficient mice develop chronic enterocolitis. Cell75:263–274. 10.1016/0092-8674(93)80068-P. [DOI] [PubMed] [Google Scholar]
• 26.Sellon RK, Tonkonogy S, Schultz M, Dieleman LA, Grenther W, Balish ED, Rennick DM, Sartor RB. 1998. Resident enteric bacteria are necessary for development of spontaneous colitis and immune system activation in interleukin-10-deficient mice. Infect Immun66:5224–5231. 10.1128/IAI.66.11.5224-5231.1998. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 27.Kullberg MC, Jankovic D, Feng CG, Hue S, Gorelick PL, McKenzie BS, Cua DJ, Powrie F, Cheever AW, Maloy KJ, Sher A. 2006. IL-23 plays a key role inHelicobacter hepaticus-induced T cell–dependent colitis. J Exp Med203:2485–2494. 10.1084/jem.20061082. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 28.Keubler LM, Buettner M, Häger C, Bleich A. 2015. A multihit model: colitis lessons from the interleukin-10-deficient mouse. Inflamm Bowel Dis21:1967–1975. 10.1097/MIB.0000000000000468. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 29.Vazquez-Torres A, Jones-Carson J, Wagner RD, Warner T, Balish E. 1999. Early resistance of interleukin-10 knockout mice to acute systemic candidiasis. Infect Immun67:670–674. 10.1128/IAI.67.2.670-674.1999. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 30.Sewnath ME, Olszyna DP, Birjmohun R, ten Kate FJW, Gouma DJ, van der Poll T. 2001. Il-10-deficient mice demonstrate multiple organ failure and increased mortality duringEscherichia coli peritonitis despite an accelerated bacterial clearance. J Immunol166:6323–6331. 10.4049/jimmunol.166.10.6323. [DOI] [PubMed] [Google Scholar]
• 31.Arai T, Hiromatsu K, Nishimura H, Kimura Y, Kobayashi N, Ishida H, Nimura Y, Yoshikai Y. 1995. Effects of in vivo administration of anti-IL-10 monoclonal antibody on the host defence mechanism against murineSalmonella infection. Immunology85:381–388. [PMC free article] [PubMed] [Google Scholar]
• 32.Villegas EN, Wille U, Craig L, Linsley PS, Rennick DM, Peach R, Hunter CA. 2000. Blockade of costimulation prevents infection-induced immunopathology in interleukin-10-deficient mice. Infect Immun68:2837–2844. 10.1128/iai.68.5.2837-2844.2000. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 33.Dann SM, Le C, Choudhury BK, Liu H, Saldarriaga O, Hanson EM, Cong Y, Eckmann L. 2014. Attenuation of intestinal inflammation in interleukin-10-deficient mice infected withCitrobacter rodentium. Infect Immun82:1949–1958. 10.1128/IAI.00066-14. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 34.Kullberg MC, Ward JM, Gorelick PL, Caspar P, Hieny S, Cheever A, Jankovic D, Sher A. 1998.Helicobacter hepaticus triggers colitis in specific-pathogen-free interleukin-10 (IL-10)-deficient mice through an IL-12-and gamma interferon-dependent mechanism. Infect Immun66:5157–5166. 10.1128/IAI.66.11.5157-5166.1998. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 35.Nagalingam NA, Robinson CJ, Bergin IL, Eaton KA, Huffnagle GB, Young VB. 2013. The effects of intestinal microbial community structure on disease manifestation in Il-10^−/− mice infected withHelicobacter hepaticus. Microbiome1:15–15. 10.1186/2049-2618-1-15. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 36.Leber A, Viladomiu M, Hontecillas R, Abedi V, Philipson C, Hoops S, Howard B, Bassaganya-Riera J. 2015. Systems modeling of interactions between mucosal immunity and the gut microbiome duringClostridium difficile infection. PLoS One10:e0134849-19. 10.1371/journal.pone.0134849. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 37.Peñaloza HF, Schultz BM, Nieto PA, Salazar GA, Suazo I, Gonzalez PA, Riedel CA, Alvarez-Lobos MM, Kalergis AM, Bueno SM. 2016. Opposing roles of IL-10 in acute bacterial infection. Cytokine Growth Factor Rev32:17–30. 10.1016/j.cytogfr.2016.07.003. [DOI] [PubMed] [Google Scholar]
• 38.Grainger JR, Wohlfert EA, Fuss IJ, Bouladoux N, Askenase MH, Legrand F, Koo LY, Brenchley JM, Fraser IDC, Belkaid Y. 2013. Inflammatory monocytes regulate pathologic responses to commensals during acute gastrointestinal infection. Nat Med19:713–721. 10.1038/nm.3189. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 39.Brooks DG, Trifilo MJ, Edelmann KH, Teyton L, Mcgavern DB, Oldstone MBA. 2006. Interleukin-10 determines viral clearance or persistencein vivo. Nat Med12:1301–1309. 10.1038/nm1492. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 40.Ryan A, Lynch M, Smith SM, Amu S, Nel HJ, McCoy CE, Dowling JK, Draper E, O'Reilly V, McCarthy C, O'Brien J, Ní Eidhin D, O'Connell MJ, Keogh B, Morton CO, Rogers TR, Fallon PG, O'Neill LA, Kelleher D, Loscher CE. 2011. A role for TLR4 inClostridium difficile infection and the recognition of surface layer proteins. PLoS Pathog7:e1002076. 10.1371/journal.ppat.1002076. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 41.Jafari NV, Kuehne SA, Bryant CE, Elawad M, Wren BW, Minton NP, Allan E, Bajaj-Elliott M. 2013.Clostridium difficile modulates host innate immunity via toxin-independent and dependent mechanism(s). PLoS One8:e69846-10. 10.1371/journal.pone.0069846. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 42.Lynch M, Walsh TA, Marszalowska I, Webb AE, Mac Aogain M, Rogers TR, Windle H, Kelleher D, O'Connell MJ, Loscher CE. 2017. Surface layer proteins from virulentClostridium difficile ribotypes exhibit signatures of positive selection with consequences for innate immune response. BMC Evol Biol17:90. 10.1186/s12862-017-0937-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 43.Rutz S, Ouyang W, Rutz S, Ouyang W. 2016. Regulation of cytokine gene expression in immunity and diseases.Springer-Verlag, Berlin, Germany. [Google Scholar]
• 44.Snapper SB, McInnis CM, Conaway EA, de Oliveira DC, Horwitz BH. 2017. Inhibition of inflammatory gene transcription by IL-10 is associated with rapid suppression of lipopolysaccharide-induced enhancer activation. J Immunol198:2906–2915. 10.4049/jimmunol.1601781. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 45.Abt MC, McKenney PT, Pamer EG. 2016.Clostridium difficile colitis: pathogenesis and host defence. Nat Rev Microbiol14:609–620. 10.1038/nrmicro.2016.108. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 46.Jarchum I, Liu M, Shi C, Equinda M, Pamer EG. 2012. Critical role for MyD88-mediated neutrophil recruitment duringClostridium difficile colitis. Infect Immun80:2989–2996. 10.1128/IAI.00448-12. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 47.Buonomo EL, Cowardin CA, Wilson MG, Saleh MM, Pramoonjago P, Petri WA. 2016. Microbiota-regulated IL-25 increases eosinophil number to provide protection duringClostridium difficile infection. Cell Rep16:432–443. 10.1016/j.celrep.2016.06.007. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 48.Chassaing B, Srinivasan G, Delgado MA, Young AN, Gewirtz AT, Vijay-Kumar M. 2012. Fecal lipocalin 2, a sensitive and broadly dynamic non-invasive biomarker for intestinal inflammation. PLoS One7:e44328-10. 10.1371/journal.pone.0044328. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 49.Donlan AN, Simpson ME, Petri WA. 2020. Type 2 cytokines IL-4 and IL-5 reduce severe outcomes fromClostridiodes difficile infection. Anaerobe66:102275–102299. 10.1016/j.anaerobe.2020.102275. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 50.Hasegawa M, Kamada N, Jiao Y, Liu MZ, Núñez G, Inohara N. 2012. Protective role of commensals againstClostridium difficile infection via an IL-1β–mediated positive-feedback loop. J Immunol189:3085–3091. 10.4049/jimmunol.1200821. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 51.Nakagawa T, Mori N, Kajiwara C, Kimura S, Akasaka Y, Ishii Y, Saji T, Tateda K. 2016. Endogenous IL-17 as a factor determining the severity ofClostridium difficile infection in mice. J Med Microbiol65:821–827. 10.1099/jmm.0.000273. [DOI] [PubMed] [Google Scholar]
• 52.Wang L, Cao J, Li C, Zhang L. 2018. IL-27/IL-27 receptor signaling provides protection inClostridium difficile-induced colitis. J Infect Dis217:198–207. 10.1093/infdis/jix581. [DOI] [PubMed] [Google Scholar]
• 53.McDermott AJ, Frank CR, Falkowski NR, McDonald RA, Young VB, Huffnagle GB. 2014. Role of GM-CSF in the inflammatory cytokine network that regulates neutrophil influx into the colonic mucosa duringClostridium difficile infection in mice. Gut Microbes5:476–484. 10.4161/gmic.29964. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 54.Chen YS, Chen IB, Pham G, Shao TY, Bangar H, Way SS, Haslam DB. 2020. IL-17-producing γδ T cells protect againstClostridium difficile infection. J Clin Investig130:2377–2390. 10.1172/JCI127242. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 55.Gunasekera DC, Ma J, Vacharathit V, Shah P, Ramakrishnan A, Uprety P, Shen Z, Sheh A, Brayton CF, Whary MT, Fox JG, Bream JH. 2020. The development of colitis in Il10^−/− mice is dependent on IL-22. Mucosal Immunol13:493–506. 10.1038/s41385-019-0252-3. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 56.Jarry A, Bossard C, Bou-Hanna C, Masson D, Espaze E, Denis MG, Laboisse CL. 2008. Mucosal IL-10 and TGF-β play crucial roles in preventing LPS-driven, IFN-γ-mediated epithelial damage in human colon explants. J Clin Investig118:1132–1142. 10.1172/JCI32140. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 57.Bain CC, Oliphant CJ, Thomson CA, Kullberg MC, Mowat AM. 2018. Proinflammatory role of monocyte-derived CX3CR1^int macrophages inHelicobacter hepaticus-induced colitis. Infect Immun86:e00579-17. 10.1128/IAI.00579-17. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 58.Young VB, Lutter R, Grasberger H, Huffnagle GB, Chang Y-M, El-Zaatari M, Franz M, Shreiner A, Zhang M, McDermott AJ, van der Sluijs KF, Kao JY, Kamada N. 2014. Tryptophan catabolism restricts IFN-γ–expressing neutrophils andClostridium difficile immunopathology. J Immunol193:807–816. 10.4049/jimmunol.1302913. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 59.Kim MN, Koh SJ, Kim JM, Im JP, Jung HC, Kim JS. 2014.Clostridium difficile infection aggravates colitis in interleukin 10-deficient mice. World J Gastroenterol20:17084–17091. 10.3748/wjg.v20.i45.17084. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 60.Vonberg R-P, Kuijper EJ, Wilcox MH, Barbut F, Tüll P, Gastmeier P, van den Broek PJ, Colville A, Coignard B, Daha T, Debast S, Duerden BI, van den Hof S, van der Kooi T, Maarleveld HJH, Nagy E, Notermans DW, O'Driscoll J, Patel B, Stone S, Wiuff C. 2008. Infection control measures to limit the spread ofClostridium difficile. Clin Microbiol Infect14:2–20. 10.1111/j.1469-0691.2008.01992.x. [DOI] [PubMed] [Google Scholar]
• 61.Theriot CM, Koumpouras CC, Carlson PE, Bergin II, Aronoff DM, Young VB. 2011. Cefoperazone-treated mice as an experimental platform to assess differential virulence ofClostridium difficile strains. Gut Microbes2:326–334. 10.4161/gmic.19142. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 62.Zhang T, Lin QY, Fei JX, Zhang Y, Lin MY, Jiang SH, Wang P, Chen Y. 2016.Clostridium difficile infection worsen outcome of hospitalized patients with inflammatory bowel disease. Sci Rep6:29791. 10.1038/srep29791. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 63.Zhou F, Hamza T, Fleur AS, Zhang Y, Yu H, Chen K, Heath JE, Chen Y, Huang H, Feng H. 2018. Mice with inflammatory bowel disease are susceptible toClostridium difficile infection with severe disease outcomes. Inflamm Bowel Dis24:573–582. 10.1093/ibd/izx059. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 64.Bernshtein B, Curato C, Ioannou M, Thaiss CA, Gross-Vered M, Kolesnikov M, Wang Q, David E, Chappell-Maor L, Harmelin A, Elinav E, Thakker P, Papayannopoulos V, Jung S. 2019. IL-23-producing IL-10Rα-deficient gut macrophages elicit an IL-22-driven proinflammatory epithelial cell response. Sci Immunol4:eaau6571-15. 10.1126/sciimmunol.aau6571. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 65.Nagao-Kitamoto H, Leslie JL, Kitamoto S, Jin C, Thomsson KA, Gillilland MG, Kuffa P, Goto Y, Jenq RR, Ishii C, Hirayama A, Seekatz AM, Martens EC, Eaton KA, Kao JY, Fukuda S, Higgins PDR, Karlsson NG, Young VB, Kamada N. 2020. Interleukin-22-mediated host glycosylation preventsClostridioides difficile infection by modulating the metabolic activity of the gut microbiota. Nat Med26:608–617. 10.1038/s41591-020-0764-0. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 66.Zheng Y, Valdez PA, Danilenko DM, Hu Y, Sa SM, Gong Q, Abbas AR, Modrusan Z, Ghilardi N, De Sauvage FJ, Ouyang W. 2008. Interleukin-22 mediates early host defense against attaching and effacing bacterial pathogens. Nat Med14:282–289. 10.1038/nm1720. [DOI] [PubMed] [Google Scholar]
• 67.Behnsen J, Jellbauer S, Wong CP, Edwards RA, George MD, Ouyang W, Raffatellu M. 2014. The cytokine IL-22 promotes pathogen colonization by suppressing related commensal bacteria. Immunity40:262–273. 10.1016/j.immuni.2014.01.003. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 68.Couturier-Maillard A, Froux N, Piotet-Morin J, Michaudel C, Brault L, Le Bérichel J, Sénéchal A, Robinet P, Chenuet P, Jejou S, Dumoutier L, Renauld JC, Iovanna J, Huber S, Chamaillard M, Quesniaux V, Sokol H, Chamaillard M, Ryffel B. 2018. Interleukin-22-deficiency and microbiota contribute to the exacerbation ofToxoplasma gondii-induced intestinal inflammation article. Mucosal Immunol11:1181–1190. 10.1038/s41385-018-0005-8. [DOI] [PubMed] [Google Scholar]
• 69.Zackular JP, Moore JL, Jordan AT, Juttukonda LJ, Noto MJ, Nicholson MR, Crews JD, Semler MW, Zhang Y, Ware LB, Washington MK, Chazin WJ, Caprioli RM, Skaar EP. 2016. Dietary zinc alters the microbiota and decreases resistance toClostridium difficile infection. Nat Med22:1330–1334. 10.1038/nm.4174. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 70.Steed AL, Christophi GP, Kaiko GE, Sun L, Goodwin VM, Jain U, Esaulova E, Artyomov MN, Morales DJ, Holtzman MJ, Boon ACM, Lenschow DJ, Stappenbeck TS. 2017. The microbial metabolite desaminotyrosine protects from influenza through type I interferon. Science357:498–502. 10.1126/science.aam5336. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 71.Ganal SC, Sanos SL, Kallfass C, Oberle K, Johner C, Kirschning C, Lienenklaus S, Weiss S, Staeheli P, Aichele P, Diefenbach A. 2012. Priming of natural killer cells by nonmucosal mononuclear phagocytes requires instructive signals from commensal microbiota. Immunity37:171–186. 10.1016/j.immuni.2012.05.020. [DOI] [PubMed] [Google Scholar]
• 72.Abt MC, Osborne LC, Monticelli LA, Doering TA, Alenghat T, Sonnenberg GF, Paley MA, Antenus M, Williams KL, Erikson J, Wherry EJ, Artis D. 2012. Commensal bacteria calibrate the activation threshold of innate antiviral immunity. Immunity37:158–170. 10.1016/j.immuni.2012.04.011. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 73.Fox JG, Dewhirst FE, Shen Z, Feng Y, Taylor NS, Paster BJ, Ericson RL, Lau CN, Correa P, Araya JC, Roa I. 1998. HepaticHelicobacter species identified in bile and gallbladder tissue from Chileans with chronic cholecystitis. Gastroenterology114:755–763. 10.1016/S0016-5085(98)70589-X. [DOI] [PubMed] [Google Scholar]
• 74.Kozich JJ, Westcott SL, Baxter NT, Highlander SK, Schloss PD. 2013. Development of a dual-index sequencing strategy and curation pipeline for analyzing amplicon sequence data on the miseq illumina sequencing platform. Appl Environ Microbiol79:5112–5120. 10.1128/AEM.01043-13. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 75.Bolyen E, Rideout JR, Dillon MR, Bokulich NA, Abnet CC, Al-Ghalith GA, Alexander H, Alm EJ, Arumugam M, Asnicar F, Bai Y, Bisanz JE, Bittinger K, Brejnrod A, Brislawn CJ, Brown CT, Callahan BJ, Caraballo-Rodríguez AM, Chase J, Cope EK, Da Silva R, Diener C, Dorrestein PC, Douglas GM, Durall DM, Duvallet C, Edwardson CF, Ernst M, Estaki M, Fouquier J, Gauglitz JM, Gibbons SM, Gibson DL, Gonzalez A, Gorlick K, Guo J, Hillmann B, Holmes S, Holste H, Huttenhower C, Huttley GA, Janssen S, Jarmusch AK, Jiang L, Kaehler BD, Kang KB, Keefe CR, Keim P, Kelley ST, Knights D, et al. 2019. Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2. Nat Biotechnol37:852–857. 10.1038/s41587-019-0209-9. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 76.Callahan BJ, McMurdie PJ, Rosen MJ, Han AW, Johnson AJA, Holmes SP. 2016. DADA2: high-resolution sample inference from Illumina amplicon data. Nat Methods13:581–583. 10.1038/nmeth.3869. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 77.R Core Team. 2018. R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna.http://www.R-project.org. [Google Scholar]
• 78.Bokulich NA, Dillon MR, Bolyen E, Kaehler BD, Huttley GA, Caporaso JG. 2018. Q2-sample-classifier: machine-learning tools for microbiome classification and regression. JOSS3:934. 10.21105/joss.00934. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 79.McDonald D, Price MN, Goodrich J, Nawrocki EP, Desantis TZ, Probst A, Andersen GL, Knight R, Hugenholtz P. 2012. An improved Greengenes taxonomy with explicit ranks for ecological and evolutionary analyses of bacteria and archaea. ISME J6:610–618. 10.1038/ismej.2011.139. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 80.Katoh K, Misawa K, Kuma KI, Miyata T. 2002. MAFFT: a novel method for rapid multiple sequence alignment based on fast Fourier transform. Nucleic Acids Res30:3059–3066. 10.1093/nar/gkf436. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 81.Price MN, Dehal PS, Arkin AP. 2010. FastTree 2–approximately maximum-likelihood trees for large alignments. PLoS One5:e9490. 10.1371/journal.pone.0009490. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 82.McMurdie PJ, Holmes S. 2013. Phyloseq: an R package for reproducible interactive analysis and graphics of microbiome census data. PLoS One8:e6217. 10.1371/journal.pone.0061217. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 83.Wickham H. 2016. ggplot2–Elegant Graphics for Data Analysis.Springer-Verlag, Berlin, Germany. [Google Scholar]
• 84.Lozupone C, Knight R. 2005. UniFrac: a new phylogenetic method for comparing microbial communities. Appl Environ Microbiol71:8228–8235. 10.1128/AEM.71.12.8228-8235.2005. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 85.Wickham H, Averick M, Bryan J, Chang W, McGowan L, François R, Grolemund G, Hayes A, Henry L, Hester J, Kuhn M, Pedersen T, Miller E, Bache S, Müller K, Ooms J, Robinson D, Seidel D, Spinu V, Takahashi K, Vaughan D, Wilke C, Woo K, Yutani H. 2019. Welcome to the Tidyverse. J Open Source Sci4:1686. 10.21105/joss.01686. [DOI] [Google Scholar]

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