Abstract

Background

Inflammation is a crucial driver of host damage in patients with Clostridioides difficile colitis. We examined the potential for the intestinal microbiome to modify inflammation in patients with C. difficile colitis via the effects of gut-derived endotoxin on cytokine production.

Methods

Endotoxin from Escherichia coli and Pseudomonas aeruginosa as well as stool-derived endotoxin were tested for their ability to enhance interleukin 1β (IL-1β) and tumor necrosis factor alpha (TNF-α) production by toxin B–stimulated peripheral blood mononuclear cells. Inflammasome and Toll-like receptor 4 (TLR4) blocking studies were done to discern the importance of these pathways, while metagenomic studies were done to characterize predominant organisms from stool samples.

Results

Endotoxin significantly enhanced the ability of C. difficile toxin B to promote IL-1β production but not TNF-α. The magnitude of this effect varied by endotoxin type and was dependent on combined inflammasome and TLR4 activation. Stool-derived endotoxin exhibited a similar synergistic effect on IL-1β production with less synergy observed for stools that contained a high proportion of γ-proteobacteria.

Conclusions

The ability of endotoxin to enhance IL-1β production highlights a manner by which the microbiome can modify inflammation and severity of C. difficile disease. This information may be useful in devising new therapies for severe C. difficile colitis.

Clostridioides difficile colitis is the leading cause of hospital-acquired diarrhea. Affected patients exhibit a range of disease states from asymptomatic colonization to a rapidly progressive condition known as fulminant colitis, which occurs in 1%–10% of patients [1–3]. Pathogen-driven inflammation plays a central role in the clinical manifestations of C. difficile colitis, especially for fulminant disease. The importance of inflammation in this process is highlighted by the elevated levels of inflammatory cytokines and chemokines seen in affected patients, including high levels of interleukin 1β (IL-1β) in the stool and serum [4–7].

The 2 toxins produced by C. difficile (toxins A and B) are essential to the pathogenesis of C. difficile disease (reviewed in [8, 9]). Besides their direct effects on the intestinal epithelium, these toxins stimulate inflammatory cytokine production by host cells [10–13]. Increased toxin production has been hypothesized to result in more severe disease. For example, the NAP1/B1/027 strain, which has a deletion in the negative regulator TcdC gene resulting in increased toxin production, has been linked to outbreaks of severe disease [14, 15].

Changes in the microbiome, including a reduction in biodiversity, play a role in the development of C. difficile disease [16–18]. Less well understood is the contribution of the intestinal microbiome to C. difficile disease severity. Endotoxin (also known as lipopolysaccharide [LPS]) is an important cell membrane constituent of enteric gram negatives. It is present in large quantities in the colon and spontaneously released by organisms. This release can be further augmented by antibiotic therapy [19, 20]. LPS activates Toll-like receptor 4 (TLR4) signaling and promotes inflammation via enhanced cytokine and chemokine production. In this study, we explored the potential for endotoxin to modify the inflammatory response to toxin B by modifying IL-1β and tumor necrosis factor alpha (TNF-α) secretion.

MATERIALS AND METHODS

Cell Culture Studies

Using Ficoll-Paque (GE Healthcare, Uppsala, Sweden), peripheral blood mononuclear cells (PBMCs) were isolated by density centrifugation of leukocyte-enriched blood samples obtained from the New York Blood Bank. Adherent cells were exposed to C. difficile toxin B (List Labs, Campbell, California) with or without commercially obtained LPS (Sigma, St Louis, Missouri). In some experiments, rabbit polyclonal serum against C. difficile toxin B (Biorbyt, Cambridge) or MCC950 (InvivoGen, San Diego, California), a NOD-like receptor pyrin domain-containing protein 3 inflammasome inhibitor, was added to the cell cultures. In other experiments, antibiotics that bind LPS, colistin (Par Pharmaceutical, Chestnut Ridge, New York), or reagents that block the TLR4 pathway, TAK-242 (MilliporeSigma, Burlington, Massachusetts), were used. Supernatants were removed at 16 hours and tested for IL-1β and TNF levels by enzyme-linked immunosorbent assay (R&D Systems, Minneapolis, Minnesota). All in vitro studies were conducted on 2 separate occasions.

Stool Samples

Stool samples from children were collected in sterile containers upon admission to the hospital, sent to the microbiology laboratory, and refrigerated before further processing. Within 24 hours, samples were aliquoted and stored at –80 °C. A convenience sample of 11 stools was chosen for study.

Crude LPS Stool Extracts

Frozen samples were allowed to thaw, weighed, and placed in pyrogen-free test tubes. LPS-free normal saline was added to the tubes to yield a ratio of 1:4 based on weight. Glass beads that were heat baked (250°C for 30 minutes) were added to the mixture, which was then vortexed for 10 minutes and centrifuged at 9500g for 10 minutes. The supernatant was removed, heated to 100°C for 30 minutes, and diluted again before being passed through a nonpyrogenic 0.2-µm syringe filter (Corning Inc, Corning, New York). Before incubation with cells, all samples were diluted 1:400 in LPS-free normal saline.

To ensure our findings were not related to contaminating proteins or nucleic acids, LPS was extracted from 8 stools using the hot phenol-water method with some modifications [21]. For these studies, stool samples weighing 50–100 mg were treated serially with RNase (40 μg/mL) and DNase I (12.5 U/mL) (both Thermo Fisher Scientific, Waltham, Massachusetts) and 1 µL/mL of 20% magnesium sulfate for 1 hour at 37°C. This was followed by incubation with proteinase K (100 μg/mL) (Abcam, Branford, Connecticut) overnight at 37°C. Samples were then treated with tri-saturated phenol (65°C–70°C) (Fisher Scientific, Pittsburgh, Pennsylvania) with intermittent shaking over 15 minutes. Supernatants were harvested and precipitated with 10 volumes of 100% ethanol and 0.5 M sodium acetate. Precipitates were dissolved in endotoxin-free water and dialyzed against endotoxin-free water followed by lyophilization. Specimens were tested for protein contamination using the bicinchoninic acid (BCA) (Thermo Fisher Scientific) and nucleic acid contamination by running samples on 1% agarose gel followed by ethidium bromide staining.

LPS Determinations

LPS levels of crude stool extracts were determined using the Toxin Sensor Chromogenic LAL LPS Assay (GenScript, Piscataway, New Jersey) according to the manufacturer’s instructions. Prior to testing, all samples were diluted in LPS-free normal saline (1:125) and the pH of sample was determined to ensure it ranged between 6 and 8.

Biome Studies

Stool samples stored at –80°C were used for sequencing. Metagenomic DNA was extracted from stool samples using a PowerSoil DNA Isolation Kit [22]. The Weinstock Laboratory at Jackson Laboratories (Farmington, Connecticut) produced sequencing data from the metagenomic DNA. The V1 through V3 hypervariable regions (V1–V3) of 16S ribosomal RNA genes were amplified from the metagenomic DNA using primers 27F and 534R. The uniquely barcoded amplicons from multiple samples were pooled and sequenced on the Illumina MiSeq sequencing platform using a V3 2 × 300 sequencing protocol. Illumina’s software was used for initial processing of all the raw sequencing data. One mismatch in primer and zero mismatch in barcodes were applied to assign read pairs to the appropriate sample within a pool of samples. Barcode and primers were removed from the reads. Reads were further processed by removing primers using Trimmomatic version 0.32 with the commands HEADCROP:20, TRAILING:10, MINLEN:100 [23] joining paired-end sequences using the FLASH algorithm [24]. Chimeric sequences were removed using UChime [25]. The cleaned, assembled amplicons were the input data for analysis. Institutional review board approval from the Albert Einstein College of Medicine was obtained for these studies. Parts of the data presented here have previously been included in a manuscript detailing the intestinal biome of hospitalized children [26].

Metagenomic Analysis

We used the Qiime2 (version 2019.4) [27] software package to calculate the relative abundances of microbes in each patient sample. We used the Qiime2 implementation of DADA22 for sequence quality control and sequence feature table construction. With the resulting sequence feature tables, we performed taxonomic classification using the Qiime [28] maintained 85% clustered version of the Greengenes [29] database. We classified each full-length sequence feature using the “feature-classifier” tool. The resulting classification was plotted using the “barplot” tool.

Statistical Analysis

All statistics were calculated using Graph Pad Prism (GraphPad, San Diego, California). For numerical data, Shapiro–Wilk test was done to test for normality. For normally distributed data, a t test was used for individual comparisons and analysis of variance when >2 groups were being compared. A Tukey multiple comparisons test was done for subsequent comparisons between individual groups. Simple linear regression was used to determine correlations between endotoxin levels in stool samples and cytokine production. For biome and cytokine comparisons, stool samples were classified as low cytokine (IL-1β or TNF-α) producers based on levels that were ≤25th percentile. Comparisons of the predominant bacteria among these groups were performed using a Fisher exact test.

RESULTS

LPS Acts Synergistically With Toxin B to Increase IL-β Production, but Not TNF-α

Incubation of PBMCs with either C. difficile toxin B or Escherichia coli LPS (ELPS) alone resulted in relatively low IL-1β levels. In contrast, the coincubation of ELPS with toxin B resulted in elevated IL-1β levels over a wide range of LPS concentrations (Figure 1A). The magnitude of this synergistic effect increased with increasing toxin B concentrations (Figure 1C). When these experiments were conducted with Pseudomonas aeruginosa LPS, a similar synergistic effect was observed, though overall, IL-1β levels were lower when compared to ELPS (Figures 1B and 1D). In contrast to IL-1β production, incubation of LPS alone (either from E. coli and P. aeruginosa) resulted in significant TNF-α production (Figure 2A–D), and the addition of toxin B did not increase TNF-α production.

Toxin B acts synergistically with lipopolysaccharide (LPS) to increase interleukin 1β (IL-1β) production. Supernatant IL-1β levels following incubation of peripheral blood mononuclear cells (PBMCs) with varying concentrations of Escherichia coli (A) or Pseudomonas aeruginosa (B) LPS (range, 0.1–10 ng/mL) in the presence or absence of toxin B (5 ng/mL) are shown. LPS alone, black-filled bars; toxin and LPS, gray-filled bars. IL-1β levels following incubation of PBMCs with varying concentrations of toxin B (5 or 50 ng/mL) in the presence of a fixed concentration of LPS (1 ng/mL) from E. coli (C) or P. aeruginosa (D). *P < .05. For all experiments, comparisons were done relative to no toxin added.
Figure 1.

Toxin B acts synergistically with lipopolysaccharide (LPS) to increase interleukin 1β (IL-1β) production. Supernatant IL-1β levels following incubation of peripheral blood mononuclear cells (PBMCs) with varying concentrations of Escherichia coli (A) or Pseudomonas aeruginosa (B) LPS (range, 0.1–10 ng/mL) in the presence or absence of toxin B (5 ng/mL) are shown. LPS alone, black-filled bars; toxin and LPS, gray-filled bars. IL-1β levels following incubation of PBMCs with varying concentrations of toxin B (5 or 50 ng/mL) in the presence of a fixed concentration of LPS (1 ng/mL) from E. coli (C) or P. aeruginosa (D). *P < .05. For all experiments, comparisons were done relative to no toxin added.

Toxin B does not act synergistically with lipopolysaccharide (LPS) to increase tumor necrosis factor alpha (TNF-α) production. Supernatant TNF-α levels following incubation of PBMCs with varying concentrations of Escherichia coli (A) or Pseudomonas aeruginosa (B) LPS (0–10 ng/mL) in the presence or absence of toxin B (5 ng/mL) are shown. LPS without toxin B, black-filled bars; LPS with toxin B (5 ng/mL), gray-filled bars. TNF-α levels following incubation of PBMCs with varying concentrations of toxin B (0–50 ng/mL) in the presence of a fixed concentration of LPS (1 ng/mL) from E. coli (C) or P. aeruginosa (D). *P < .05. For all experiments, comparisons were done relative to no toxin added.
Figure 2.

Toxin B does not act synergistically with lipopolysaccharide (LPS) to increase tumor necrosis factor alpha (TNF-α) production. Supernatant TNF-α levels following incubation of PBMCs with varying concentrations of Escherichia coli (A) or Pseudomonas aeruginosa (B) LPS (0–10 ng/mL) in the presence or absence of toxin B (5 ng/mL) are shown. LPS without toxin B, black-filled bars; LPS with toxin B (5 ng/mL), gray-filled bars. TNF-α levels following incubation of PBMCs with varying concentrations of toxin B (0–50 ng/mL) in the presence of a fixed concentration of LPS (1 ng/mL) from E. coli (C) or P. aeruginosa (D). *P < .05. For all experiments, comparisons were done relative to no toxin added.

Inhibition of IL-1β Production

To better understand the synergy of LPS and toxin B on IL-1β production, several studies were done in which inhibitors were added to the combination of LPS and toxin B (Figure 3). The addition of the antibiotic colistin, which is known to bind LPS, decreased IL-1β production in a concentration-dependent manner (Figure 3A). Similarly, the TLR4 inhibitor, TAK-242, also inhibited IL-β production, but only at the highest concentration of inhibitor (Figure 3B). Both a polyclonal rabbit serum against toxin B and an NLP3-inflammasome inhibitor also reduced IL-1β production produced by the combination of LPS and toxin B. This effect was lost at the highest toxin B concentrations (Figures 3C and 3D).

Inhibition of lipopolysaccharide (LPS) or toxin B signaling pathway limits the synergistic increase in interleukin 1β (IL-1β) production. IL-1β levels following the incubation of colistin (A) or TAK-242 (B) with the combination of Escherichia coli LPS (1 ng/mL) and toxin B (50 ng/mL). Both compounds interfere with LPS signaling and produced a dose-dependent reduction in IL-1β levels. IL-1β levels following the incubation of polyclonal antitoxin B antibody (C) at a concentration of 5 μg/mL with LPS (1 ng/mL) and different concentrations of toxin B. A similar reduction in IL-1β levels was observed with the NLPR3 inhibitor MCC 950 (D). For these experiments, a concentration of E. coli LPS of 1 ng/mL was used with various concentrations of toxin B. The concentration of MCC 950 was 1 μM for all toxin concentrations (white bars), though at the highest toxin concentration, a higher dose (10 µM, gray bar) was also studied. *P < .05. For all experiments, comparisons were done relative to no inhibitor added.
Figure 3.

Inhibition of lipopolysaccharide (LPS) or toxin B signaling pathway limits the synergistic increase in interleukin 1β (IL-1β) production. IL-1β levels following the incubation of colistin (A) or TAK-242 (B) with the combination of Escherichia coli LPS (1 ng/mL) and toxin B (50 ng/mL). Both compounds interfere with LPS signaling and produced a dose-dependent reduction in IL-1β levels. IL-1β levels following the incubation of polyclonal antitoxin B antibody (C) at a concentration of 5 μg/mL with LPS (1 ng/mL) and different concentrations of toxin B. A similar reduction in IL-1β levels was observed with the NLPR3 inhibitor MCC 950 (D). For these experiments, a concentration of E. coli LPS of 1 ng/mL was used with various concentrations of toxin B. The concentration of MCC 950 was 1 μM for all toxin concentrations (white bars), though at the highest toxin concentration, a higher dose (10 µM, gray bar) was also studied. *P < .05. For all experiments, comparisons were done relative to no inhibitor added.

Stool Studies

The average age of patients from whom these stools came was 2.9 ± 4.6 years; 4 patients were <1 year of age. Stools came from 8 females and 3 males. One tested positive for C. difficile toxin by polymerase chain reaction, but this likely represented colonization as he was <1 year of age. Of the patients, 1 of 11 (9.1%) had diarrhea while 9 of 11 (82%) were receiving antibiotics. Several patients had underlying diseases including sickle cell disease, cholangitis, cholestasis, malignancy, and ventriculoperitoneal shunt infection.

Stool Experiments

Eleven crude stool LPS extracts were available for IL-1β experiments; enough sample was left for TNF-α studies in 9 samples. Incubation of PBMCs with these extracts resulted in IL-1β expression for all specimens, though there was significant variation between the specimens (Figure 4A). Co-incubation of stool extracts with toxin B consistently elicited higher IL-1β levels when compared to stool extracts alone. Importantly, the magnitude of this effect varied greatly between stool extracts, with an average increase of 23.6-fold (range, 2.5- to 46.8-fold). This synergistic effect was completely abrogated by the addition of colistin to cell cultures (Figure 4B).

Effects of stool-derived lipopolysaccharide (LPS) combined with toxin B on interleukin 1β (IL-1β) and tumor necrosis factor alpha (TNF-α) production. Crude stool LPS extracts from different individuals were incubated with or without toxin B (50 ng/mL) and the effects on IL-β (A) and TNF-α (C) were measured. Cytokine levels produced by incubation of stool-derived LPS alone or together with toxin are represented by black and gray bars, respectively. Numbers above columns represent the fold increase in cytokine level produced by stool-derived endotoxin combined with toxin B relative to stool-derived endotoxin alone. B, The addition of colistin B (1 mg/mL) prevented the IL-1β produced by the co-incubation of toxin B with 2 representative stool samples. D, Supernatant IL-1β levels following incubation of PBMCs with LPS, which was obtained by phenol extraction, are shown. For A, C, and D, statistical comparisons are between stool-derived endotoxin with or without toxin B. For B, comparisons are between stool and toxin B with or without colistin. Dotted lines represent the 25th percentile and 75th cytokine percentiles for co-incubation of stool and toxin. *P value < .05.
Figure 4.

Effects of stool-derived lipopolysaccharide (LPS) combined with toxin B on interleukin 1β (IL-1β) and tumor necrosis factor alpha (TNF-α) production. Crude stool LPS extracts from different individuals were incubated with or without toxin B (50 ng/mL) and the effects on IL-β (A) and TNF-α (C) were measured. Cytokine levels produced by incubation of stool-derived LPS alone or together with toxin are represented by black and gray bars, respectively. Numbers above columns represent the fold increase in cytokine level produced by stool-derived endotoxin combined with toxin B relative to stool-derived endotoxin alone. B, The addition of colistin B (1 mg/mL) prevented the IL-1β produced by the co-incubation of toxin B with 2 representative stool samples. D, Supernatant IL-1β levels following incubation of PBMCs with LPS, which was obtained by phenol extraction, are shown. For A, C, and D, statistical comparisons are between stool-derived endotoxin with or without toxin B. For B, comparisons are between stool and toxin B with or without colistin. Dotted lines represent the 25th percentile and 75th cytokine percentiles for co-incubation of stool and toxin. *P value < .05.

Incubation of PBMCs with crude stool LPS extracts resulted in TNF-α production by PBMCs for all specimens. Co-incubation of PBMCs with a combination of stool extracts with toxin B resulted in a significant increase in TNF-α levels relative to stool LPS extracts alone, for most samples. However, the magnitude of this increase was lower when compared with changes in IL-1β production, with a mean increase of 2.4-fold (range, 1.1- to 4.2-fold) (Figure 4C).

Endotoxin concentrations of the 11 stool samples varied from 98.4 to 196.2 EU/mL. There was no correlation between the endotoxin concentrations of individual stool sample and the amount of IL-1β produced by the combination of the sample with toxin (r2 = 0.11, P = .32) (not shown).

LPS was obtained by phenol extraction in 8 stool samples. No protein was detected in these samples by BCA assay (limit of detection 50 μg/mL) and no bands were visualized by ethidium bromide staining. Similar to crude extracts, significant synergy for IL-1β production was observed following toxin B coincubation, with an average 41.3-fold increase compared with stool-derived endotoxin alone (range, 8.8- to 132.0-fold increase) (Figure 4D). Levels of IL-1β were similar to those observed following incubation with commercially obtained LPS, but lower than levels observed with crude extract studies (for both stool alone and stool combined with toxin B).

Biome Correlations

The biome and corresponding IL-1β levels produced by the co-incubation of crude stool LPS extracts and toxin B are shown in Figure 5. The bacterial population of specimens, which produced relatively low IL-1β levels, were comprised of a disproportionately high percentage of γ-Proteobacteria and more specifically bacteria from the Aeromonadales order. In this low IL-1β group, 75% (3/4) of samples had Aeromonadales bacteria as the predominant (81%, 72%, 62%) component. A similar pattern was present with for LPS preparations prepared by enzymatic digestion and phenol extraction.

Biome classification for stools with respect to interleukin 1β (IL-1β) production. The microbial composition of various stool samples at the level of order is shown with each column representing an individual sample. Overlying graph (dotted line) represents IL-1β levels produced by incubation of corresponding crude stool lipopolysaccharide extracts with toxin B. White dotted lines represent 25th and 75th percentiles for IL-1β levels.
Figure 5.

Biome classification for stools with respect to interleukin 1β (IL-1β) production. The microbial composition of various stool samples at the level of order is shown with each column representing an individual sample. Overlying graph (dotted line) represents IL-1β levels produced by incubation of corresponding crude stool lipopolysaccharide extracts with toxin B. White dotted lines represent 25th and 75th percentiles for IL-1β levels.

For the 7 remaining samples, the predominant bacterial order was either Bacteroidales (n = 4) or Clostridiales (n = 3) (P = .024). Two of 3 stool specimens, which produced relatively low TNF-α levels when combined with toxin B, contained a majority of bacteria from the Clostridiales order (Figure 6). None of the 6 stool samples from the non–low TNF-α group contained a majority of bacteria from the Clostridiales order; however, this difference was not significant when compared by Fisher exact test (P = .83).

Biome classification for stools with respect to tumor necrosis factor alpha (TNF-α) production. The microbial composition of various stool samples at the level of order is shown with each column representing an individual sample. Overlying graph (dotted line) represents TNF-α levels produced by incubation of corresponding crude stool lipopolysaccharide extracts with toxin B. White dotted lines represent 25th and 75th percentiles for TNF-α levels.
Figure 6.

Biome classification for stools with respect to tumor necrosis factor alpha (TNF-α) production. The microbial composition of various stool samples at the level of order is shown with each column representing an individual sample. Overlying graph (dotted line) represents TNF-α levels produced by incubation of corresponding crude stool lipopolysaccharide extracts with toxin B. White dotted lines represent 25th and 75th percentiles for TNF-α levels.

DISCUSSION

Inflammation plays a central role in severe C. difficile colitis. In support of this hypothesis, several studies have shown increased levels of a variety of chemokines and cytokines in association with severe C. difficile disease [5, 7, 30]. Both serum and stool IL-1β levels are elevated in patients with C. difficile colitis [6, 7, 31]. In mice, decreased IL-1β activity as a result of administration of an IL-1 blocking agent or the use of genetically deficient mice was associated with decreased intestinal pathology [32]. Besides its direct proinflammatory activity, increased IL-1β levels in C. difficile disease may exacerbate inflammation through its ability to augment Th17 inflammation [31, 33]. Nonetheless, a protective mechanism for IL-1β in C. difficile colitis has also been proposed, specifically as it relates to preventing translocation of commensal gut bacteria [34].

Findings from our study demonstrate a previously unrecognized mechanism by which the intestinal microbiome can modify the inflammatory response to C. difficile toxin and thereby affect disease severity. We show that endotoxin acts synergistically with toxin B to augment IL-1β secretion, but not TNF-α. This phenomenon resulted in more than a log10 increase in IL-1β levels, with the effect being dependent on the type of endotoxin, and less so on its concentration. Our findings are consistent with a previously reported synergy between C. difficile toxins (A and B) with Salmonella endotoxin on IL-1β production [13].

We hypothesize that this synergy results from the ability of LPS to increase pro–IL-1β production via TLR4 signaling, and of toxin B to activate the inflammasome, thereby promoting pro–IL-1β processing to mature IL-1β. This hypothesis is consistent with previous studies that demonstrate the ability of toxin B to activate the inflammasome [32, 35, 36]. Our hypothesis is further supported by our inhibition studies, which indicate that both TLR and inflammasome activation are necessary for maximum IL-1β production.

The intestinal biome appears to modulate susceptibility to C. difficile infection by several mechanisms including modifications in bile acid metabolism and the production of bacteriocins [17, 37–39]. We found that endotoxin from P. aeruginosa was significantly less effective than endotoxin from E. coli in enhancing IL-1β production when incubated with toxin B. This observation is consistent with the known structural variations in lipid A among different gram-negative organisms and the effects of these differences on TLR4 binding and subsequent inflammatory cytokine secretion (reviewed in [40]). Similarly, we found that stool-derived endotoxin from different individuals demonstrated significant variation in the ability to promote IL-1β production. This effect was present for both crude stool LPS extracts and those prepared by phenol extraction. An overrepresentation of bacterium from the γ-Proteobacteria class, and more specifically from the Aeromonadales order, was found in the samples that produced low IL-1β levels. The high prevalence of Aeromonadales in these samples is unusual but may be accounted for by the high rates of antibiotic usage, underlying diseases, and the relatively young age of this cohort. Additional study is clearly needed to further define the effects of LPS from different bacteria on toxin B–mediated inflammatory responses and its contribution to disease. The extent of synergy is likely to be a dynamic and competitive process, depending on both the predominant bacterial species and the extent of LPS shedding within the colon. We further note that within a given genus, significant variation in the TLR signaling can occur, with some species unable to activate TLR4 signaling (reviewed in [41]) so that distinction at a species level will be important for future studies.

Our findings have important additional potential clinical implications, including the potential utility of endotoxin-binding antibiotics or endotoxin binding resins to help limit IL-1β production and decrease inflammation during C. difficile colitis. This approach might be complicated by the fact that antibiotics like colistin and polymyxin are themselves risk factors for C. difficile disease. Interestingly, successful treatment of severe difficile colitis using hemoperfusion with polymyxin B immobilized fiber has been described [42, 43]. Current recommendations for the treatment of fulminant C. difficile colitis (where surgical intervention is necessary) include the placement of a diverting loop ileostomy with colonic lavage, using vancomycin [44, 45]. For these patients, the use of an endotoxin-binding agent in addition to medical therapy may prove particularly useful, though additional study is clearly indicated.

Antibiotic usage is a known risk factor for the development of C. difficile colitis. Findings from our study imply that antibiotics could also exacerbate colitis by increasing endotoxin release from enteric organisms, thereby increasing inflammation. In this regard, both in vitro and in vivo experiments have demonstrated that antibiotics promote endotoxin release by gram-negative organisms (reviewed in [46]). This effect varies with the type of antibiotic and its mechanism of action.

In summary, our studies highlight a previously unrecognized mechanism by which the intestinal microbiome can alter the inflammatory response to C. difficile disease. The contribution of this mechanism to disease severity remains to be fully demonstrated. We note that our findings are limited by the relatively small number of stool samples we studied as well as the relatively young age of patients who were included. Additional studies examining the biome of patients with differing severity of C. difficile are underway. However, the observed effect is consistent with the known signaling pathways for C. difficile toxin and endotoxin. Furthermore, the high levels of endotoxin in stool, at the site of toxin B activity, highlight the potential biologic relevance of our findings. If confirmed, these findings could have important implications for the treatment of severe C. difficile disease.

Notes

Acknowledgments. We would like to thank Dr George M. Weinstock and his laboratory for the help in DNA sequencing studies.

Potential conflicts of interest. All authors: No reported conflicts of interest.

All authors have submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest. Conflicts that the editors consider relevant to the content of the manuscript have been disclosed.

References

1.

Muto
CA
,
Pokrywka
M
,
Shutt
K
, et al.
A large outbreak of Clostridium difficile-associated disease with an unexpected proportion of deaths and colectomies at a teaching hospital following increased fluoroquinolone use
.
Infect Control Hosp Epidemiol
2005
;
26
:
273
80
.

2.

Sailhamer
EA
,
Carson
K
,
Chang
Y
, et al.
Fulminant Clostridium difficile colitis: patterns of care and predictors of mortality
.
Arch Surg
2009
;
144
:
433
9
.

3.

Dallal
RM
,
Harbrecht
BG
,
Boujoukas
AJ
, et al.
Fulminant Clostridium difficile: an underappreciated and increasing cause of death and complications
.
Ann Surg
2002
;
235
:
363
72
.

4.

Rao
K
,
Erb-Downward
JR
,
Walk
ST
, et al.
The systemic inflammatory response to Clostridium difficile infection
.
PLoS One
2014
;
9
:
e92578
.

5.

El Feghaly
RE
,
Stauber
JL
,
Tarr
PI
,
Haslam
DB
.
Intestinal inflammatory biomarkers and outcome in pediatric Clostridium difficile infections
.
J Pediatr
2013
;
163
:
1697
704.e2
.

6.

Steiner
TS
,
Flores
CA
,
Pizarro
TT
,
Guerrant
RL
.
Fecal lactoferrin, interleukin-1beta, and interleukin-8 are elevated in patients with severe Clostridium difficile colitis
.
Clin Diagn Lab Immunol
1997
;
4
:
719
22
.

7.

Yu
H
,
Chen
K
,
Sun
Y
, et al.
Cytokines are markers of the Clostridium difficile-induced inflammatory response and predict disease severity
.
Clin Vaccine Immunol
2017
;
24
:
e00037-17
.

8.

Carter
GP
,
Chakravorty
A
,
Pham Nguyen
TA
, et al.
Defining the roles of TcdA and TcdB in localized gastrointestinal disease, systemic organ damage, and the host response during Clostridium difficile infections
.
mBio
2015
;
6
:
e00551
.

9.

Chandrasekaran
R
,
Lacy
DB
.
The role of toxins in Clostridium difficile infection
.
FEMS Microbiol Rev
2017
;
41
:
723
50
.

10.

Mahida
YR
,
Makh
S
,
Hyde
S
,
Gray
T
,
Borriello
SP
.
Effect of Clostridium difficile toxin A on human intestinal epithelial cells: induction of interleukin 8 production and apoptosis after cell detachment
.
Gut
1996
;
38
:
337
47
.

11.

Branka
JE
,
Vallette
G
,
Jarry
A
, et al.
Early functional effects of Clostridium difficile toxin A on human colonocytes
.
Gastroenterology
1997
;
112
:
1887
94
.

12.

Linevsky
JK
,
Pothoulakis
C
,
Keates
S
, et al.
IL-8 release and neutrophil activation by Clostridium difficile toxin-exposed human monocytes
.
Am J Physiol
1997
;
273
:
G1333
40
.

13.

Flegel
WA
,
Müller
F
,
Däubener
W
,
Fischer
HG
,
Hadding
U
,
Northoff
H
.
Cytokine response by human monocytes to Clostridium difficile toxin A and toxin B
.
Infect Immun
1991
;
59
:
3659
66
.

14.

Warny
M
,
Pepin
J
,
Fang
A
, et al.
Toxin production by an emerging strain of Clostridium difficile associated with outbreaks of severe disease in North America and Europe
.
Lancet
2005
;
366
:
1079
84
.

15.

See
I
,
Mu
Y
,
Cohen
J
, et al.
NAP1 strain type predicts outcomes from Clostridium difficile infection
.
Clin Infect Dis
2014
;
58
:
1394
400
.

16.

Schäffler
H
,
Breitrück
A
.
Clostridium difficile—from colonization to infection
.
Front Microbiol
2018
;
9
:
646
.

17.

Sorg
JA
,
Sonenshein
AL
.
Bile salts and glycine as cogerminants for Clostridium difficile spores
.
J Bacteriol
2008
;
190
:
2505
12
.

18.

Giel
JL
,
Sorg
JA
,
Sonenshein
AL
,
Zhu
J
.
Metabolism of bile salts in mice influences spore germination in Clostridium difficile
.
PLoS One
2010
;
5
:
e8740
.

19.

Crosby
HA
,
Bion
JF
,
Penn
CW
,
Elliott
TS
.
Antibiotic-induced release of endotoxin from bacteria in vitro
.
J Med Microbiol
1994
;
40
:
23
30
.

20.

Bucklin
SE
,
Fujihara
Y
,
Leeson
MC
,
Morrison
DC
.
Differential antibiotic-induced release of endotoxin from gram-negative bacteria
.
Eur J Clin Microbiol Infect Dis
1994
;
13(Suppl 1)
:
S43
51
.

21.

Davis
MR
, Jr,
Goldberg
JB
.
Purification and visualization of lipopolysaccharide from gram-negative bacteria by hot aqueous-phenol extraction
.
J Vis Exp
2012
;
63
.

22.

Human Microbiome Project Consortium.
Structure, function and diversity of the healthy human microbiome
.
Nature
2012
;
486
:
207
14
.

23.

Bolger
AM
,
Lohse
M
,
Usadel
B
.
Trimmomatic: a flexible trimmer for Illumina sequence data
.
Bioinformatics
2014
;
30
:
2114
20
.

24.

Magoč
T
,
Salzberg
SL
.
FLASH: fast length adjustment of short reads to improve genome assemblies
.
Bioinformatics
2011
;
27
:
2957
63
.

25.

Edgar
RC
,
Haas
BJ
,
Clemente
JC
,
Quince
C
,
Knight
R
.
UCHIME improves sensitivity and speed of chimera detection
.
Bioinformatics
2011
;
27
:
2194
200
.

26.

Mohandas
S
,
Soma
VL
,
Tran
TDB
, et al.
Differences in gut microbiome in hospitalized immunocompetent vs. immunocompromised children, including those with sickle cell disease
.
Front Pediatr
2020
;
8
:
583446
.

27.

Bolyen
E
,
Rideout
JR
,
Dillon
MR
, et al.
Author correction: reproducible, interactive, scalable and extensible microbiome data science using QIIME 2
.
Nat Biotechnol
2019
;
37
:
1091
.

28.

Callahan
BJ
,
McMurdie
PJ
,
Rosen
MJ
,
Han
AW
,
Johnson
AJ
,
Holmes
SP
.
DADA2: high-resolution sample inference from Illumina amplicon data
.
Nat Methods
2016
;
13
:
581
3
.

29.

DeSantis
TZ
,
Hugenholtz
P
,
Larsen
N
, et al.
Greengenes, a chimera-checked 16S rRNA gene database and workbench compatible with ARB
.
Appl Environ Microbiol
2006
;
72
:
5069
72
.

30.

Czepiel
J
,
Biesiada
G
,
Dróżdż
M
, et al.
The presence of IL-8 + 781 T/C polymorphism is associated with the parameters of severe Clostridium difficile infection
.
Microb Pathog
2018
;
114
:
281
5
.

31.

Cowardin
CA
,
Kuehne
SA
,
Buonomo
EL
,
Marie
CS
,
Minton
NP
,
Petri
WA
, Jr.
Inflammasome activation contributes to interleukin-23 production in response to Clostridium difficile
.
mBio
2015
;
6
:
e02386-14
.

32.

Ng
J
,
Hirota
SA
,
Gross
O
, et al.
Clostridium difficile toxin-induced inflammation and intestinal injury are mediated by the inflammasome
.
Gastroenterology
2010
;
139
:
542
52
, 552.e1–3.

33.

Saleh
MM
,
Frisbee
AL
,
Leslie
JL
, et al.
Colitis-induced Th17 cells increase the risk for severe subsequent Clostridium difficile infection
.
Cell Host Microbe
2019
;
25
:
756
65
.e5.

34.

Hasegawa
M
,
Kamada
N
,
Jiao
Y
,
Liu
MZ
,
Núñez
G
,
Inohara
N
.
Protective role of commensals against Clostridium difficile infection via an IL-1β-mediated positive-feedback loop
.
J Immunol
2012
;
189
:
3085
91
.

35.

Wewers
MD
,
Winnard
AV
,
Dare
HA
.
Endotoxin-stimulated monocytes release multiple forms of IL-1 beta, including a proIL-1 beta form whose detection is affected by export
.
J Immunol
1999
;
162
:
4858
63
.

36.

Xu
H
,
Yang
J
,
Gao
W
, et al.
Innate immune sensing of bacterial modifications of Rho GTPases by the Pyrin inflammasome
.
Nature
2014
;
513
:
237
41
.

37.

Bartoloni
A
,
Mantella
A
,
Goldstein
BP
, et al.
In-vitro activity of nisin against clinical isolates of Clostridium difficile
.
J Chemother
2004
;
16
:
119
21
.

38.

Robinson
JI
,
Weir
WH
,
Crowley
JR
, et al.
Metabolomic networks connect host-microbiome processes to human Clostridioides difficile infections
.
J Clin Invest
2019
;
129
:
3792
806
.

39.

Seekatz
AM
,
Theriot
CM
,
Rao
K
, et al.
Restoration of short chain fatty acid and bile acid metabolism following fecal microbiota transplantation in patients with recurrent Clostridium difficile infection
.
Anaerobe
2018
;
53
:
64
73
.

40.

Chilton
PM
,
Embry
CA
,
Mitchell
TC
.
Effects of differences in lipid A structure on TLR4 pro-inflammatory signaling and inflammasome activation
.
Front Immunol
2012
;
3
:
154
.

41.

d’Hennezel
E
,
Abubucker
S
,
Murphy
LO
,
Cullen
TW
.
Total lipopolysaccharide from the human gut microbiome silences Toll-like receptor signaling
.
mSystems
2017
;
2
:
e00046-17
.

42.

Kimura
Y
,
Sato
K
,
Tokuda
H
, et al.
Effects of combination therapy with direct hemoperfusion using polymyxin B-immobilized fiber and oral vancomycin on fulminant pseudomembranous colitis with septic shock
.
Dig Dis Sci
2007
;
52
:
675
8
.

43.

Minami
K
,
Sakaguchi
Y
,
Yoshida
D
, et al.
Successful treatments with polymyxin B hemoperfusion and recombinant human thrombomodulin for fulminant Clostridium difficile-associated colitis with septic shock and disseminated intravascular coagulation: a case report
.
Surg Case Rep
2016
;
2
:
76
.

44.

Neal
MD
,
Alverdy
JC
,
Hall
DE
,
Simmons
RL
,
Zuckerbraun
BS
.
Diverting loop ileostomy and colonic lavage: an alternative to total abdominal colectomy for the treatment of severe, complicated Clostridium difficile associated disease
.
Ann Surg
2011
;
254
:
423
7
; discussion 427–9.

45.

McDonald
LC
,
Gerding
DN
,
Johnson
S
, et al.
Clinical practice guidelines for Clostridium difficile infection in adults and children: 2017 update by the Infectious Diseases Society of America (IDSA) and Society for Healthcare Epidemiology of America (SHEA)
.
Clin Infect Dis
2018
;
66
:
987
94
.

46.

Prins
JM
,
van Deventer
SJ
,
Kuijper
EJ
,
Speelman
P
.
Clinical relevance of antibiotic-induced endotoxin release
.
Antimicrob Agents Chemother
1994
;
38
:
1211
8
.

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