Hydrogen Sulfide Producers Drive a Diarrhea-Like Phenotype and a Methane Producer Drives a Constipation-Like Phenotype in Animal Models.

BACKGROUND: We recently demonstrated that diarrhea-predominant irritable bowel syndrome (IBS-D) subjects have higher relative abundance (RA) of hydrogen sulfide (H2S)-producing Fusobacterium and Desulfovibrio species, and constipation-predominant IBS (IBS-C) subjects have higher RA of methanogen Methanobrevibacter smithii. AIMS: In this study, we investigate the effects of increased methanogens or H2S producers on stool phenotypes in rat models. METHODS: Adult Sprague-Dawley rats were fed high-fat diet (HFD) for 60 days to increase M. smithii levels, then gavaged for 10 days with water (controls) or methanogenesis inhibitors. To increase H2S producers, rats were gavaged with F. varium or D. piger. Stool consistency (stool wet weight (SWW)) and gas production were measured. 16S rRNA gene sequencing was performed on stool samples. RESULTS: In HFD diet-fed rats (N = 30), stool M. smithii levels were increased (P < 0.001) after 52 days, correlating with significantly decreased SWW (P < 0.0001) at 59 days (R = - 0.38, P = 0.037). Small bowel M. smithii levels decreased significantly in lovastatin lactone-treated rats (P < 0.0006), and SWW increased (normalized) in lovastatin hydroxyacid-treated rats (P = 0.0246), vs. controls (N = 10/group). SWW increased significantly in D. piger-gavaged rats (N = 16) on day 10 (P < 0.0001), and in F. varium-gavaged rats (N = 16) at all timepoints, vs. controls, with increased stool H2S production. 16S sequencing revealed stool microbiota alterations in rats gavaged with H2S producers, with higher relative abundance (RA) of other H2S producers, particularly Lachnospiraceae and Bilophila in F. varium-gavaged rats, and Sutterella in D. piger-gavaged rats. CONCLUSIONS: These findings suggest that increased M. smithii levels result in a constipation-like phenotype in a rat model that is partly reversible with methanogenesis inhibitors, whereas gavage with H2S producers D. piger or F. varium results in increased colonization with other H2S producers and diarrhea-like phenotypes. This supports roles for the increased RA of methanogens and H2S producers identified in IBS-C and IBS-D subjects, respectively, in contributing to stool phenotypes.

Effects of Proton Pump Inhibitors on the Small Bowel and Stool Microbiomes.

BACKGROUND: Proton pump inhibitor (PPI) use is extremely common. PPIs have been suggested to affect the gut microbiome, and increase risks of Clostridium difficile infection and small intestinal bacterial overgrowth (SIBO). However, existing data are based on stool analyses and PPIs act on the foregut. AIMS: To compare the duodenal and stool microbiomes in PPI and non-PPI users. METHODS: Consecutive subjects presenting for upper endoscopy without colonoscopy were recruited. Current antibiotic users were excluded. Subjects taking PPI were age- and gender-matched 1:2 to non-PPI controls. Subjects completed medical history questionnaires, and duodenal aspirates were collected using a validated protected catheter. A subset also provided stool samples. Duodenal and stool microbiomes were analyzed by 16S rRNA sequencing. RESULTS: The duodenal microbiome exhibited no phylum-level differences between PPI (N = 59) and non-PPI subjects (N = 118), but demonstrated significantly higher relative abundances of families Campylobacteraceae (3.13-fold, FDR P value < 0.01) and Bifidobacteriaceae (2.9-fold, FDR P value < 0.01), and lower relative abundance of Clostridiaceae (88.24-fold, FDR P value < 0.0001), in PPI subjects. SIBO rates were not significantly different between groups, whether defined by culture (> 103 CFU/ml) or 16S sequencing, nor between subjects taking different PPIs. The stool microbiome exhibited significantly higher abundance of family Streptococcaceae (2.14-fold, P = 0.003), and lower Clostridiaceae (2.60-fold, FDR P value = 8.61E-13), in PPI (N = 22) versus non-PPI (N = 47) subjects. CONCLUSIONS: These findings suggest that PPI use is not associated with higher rates of SIBO. Relative abundance of Clostridiaceae was reduced in both the duodenal and stool microbiomes, and Streptococcaceae was increased in stool. The clinical implications of these findings are unknown.

Quantitative sequencing clarifies the role of disruptor taxa, oral microbiota, and strict anaerobes in the human small-intestine microbiome.

BACKGROUND: Upper gastrointestinal (GI) disorders and abdominal pain afflict between 12 and 30% of the worldwide population and research suggests these conditions are linked to the gut microbiome. Although large-intestine microbiota have been linked to several GI diseases, the microbiota of the human small intestine and its relation to human disease has been understudied. The small intestine is the major site for immune surveillance in the gut, and compared with the large intestine, it has greater than 100 times the surface area and a thinner and more permeable mucus layer. RESULTS: Using quantitative sequencing, we evaluated total and taxon-specific absolute microbial loads from 250 duodenal-aspirate samples and 21 paired duodenum-saliva samples from participants in the REIMAGINE study. Log-transformed total microbial loads spanned 5 logs and were normally distributed. Paired saliva-duodenum samples suggested potential transmission of oral microbes to the duodenum, including organisms from the HACEK group. Several taxa, including Klebsiella, Escherichia, Enterococcus, and Clostridium, seemed to displace strict anaerobes common in the duodenum, so we refer to these taxa as disruptors. Disruptor taxa were enriched in samples with high total microbial loads and in individuals with small intestinal bacterial overgrowth (SIBO). Absolute loads of disruptors were associated with more severe GI symptoms, highlighting the value of absolute taxon quantification when studying small-intestine health and function. CONCLUSION: This study provides the largest dataset of the absolute abundance of microbiota from the human duodenum to date. The results reveal a clear relationship between the oral microbiota and the duodenal microbiota and suggest an association between the absolute abundance of disruptor taxa, SIBO, and the prevalence of severe GI symptoms. Video Abstract.

The duodenal microbiome is altered in small intestinal bacterial overgrowth.

Small intestinal bacterial overgrowth (SIBO) is highly prevalent and is associated with numerous gastrointestinal disorders, but the microbes involved remain poorly defined. Moreover, existing studies of microbiome alterations in SIBO have utilized stool samples, which are not representative of the entire gastrointestinal tract. Therefore, we aimed to determine and compare the duodenal microbiome composition in SIBO and non-SIBO subjects, using duodenal aspirates from subjects undergoing standard-of-care esophagogastroduodenoscopy without colon preparation. Using the recently-redefined cutoff for SIBO of >103 colony forming units per milliliter (CFU/mL), 42 SIBO and 98 non-SIBO subjects were identified. Duodenal samples from SIBO subjects had 4x103-fold higher counts than non-SIBO subjects when plated on MacConkey agar (P<0.0001), and 3.8-fold higher counts when plated on blood agar (P<0.0001). Twenty subjects had also undergone lactulose hydrogen breath tests (LHBTs), of whom 7/20 had SIBO. At the 90-minute timepoint, 4/7 SIBO subjects had positive LHBTs (rise in hydrogen (H2) ≥ 20 ppm above baseline), as compared to 2/13 non-SIBO subjects. 16S ribosomal RNA (rRNA) sequencing revealed that SIBO subjects had 4.31-fold higher relative abundance of Proteobacteria (FDR P<0.0001) and 1.64-fold lower Firmicutes (P<0.0003) than non-SIBO subjects. This increased relative abundance of Proteobacteria correlated with decreased α-diversity in SIBO subjects (Spearman R = 0.4866, P<0.0001) Specific increases in class Gammaproteobacteria correlated with the area-under-the-curve for H2 for 0-90 mins during LHBT (R = 0.630, P = 0.002). Increases in Gammaproteobacteria resulted primarily from higher relative abundances of the family Enterobacteriaceae (FDR P<0.0001), which correlated with the symptom of bloating (Spearman R = 0.185, 2-tailed P = 0.028). Increases in family Aeromonadaceae correlated with urgency with bowel movement (Spearman R = 0.186, 2-tailed P = 0.028). These results validate the >103 CFU/mL cutoff for the definition of SIBO, and also reveal specific overgrowth of Proteobacteria in SIBO vs. non-SIBO subjects, coupled with an altered Proteobacterial profile that correlates with symptom severity. Future research may elucidate host-microbiome interactions underlying these symptoms in SIBO patients.

Acute appendicitis is associated with appendiceal microbiome changes including elevated Campylobacter jejuni levels.

OBJECTIVES: To compare the appendiceal microbiomes and examine the prevalence of Campylobacter species in the appendices of adult subjects with confirmed acute non-perforated appendicitis and controls with healthy appendices. DESIGN: Archived samples of formalin-fixed paraffin-embedded appendiceal tissues were obtained from 50 consecutive female subjects who underwent appendectomy for acute, non-perforated appendicitis, and 35 consecutive female controls who underwent incidental appendectomy during gynaecological surgery. RESULTS: 16S rRNA gene sequencing revealed that the relative abundances (RAs) of the major phyla in appendiceal tissues (Firmicutes, Proteobacteria, Bacteroidetes, and Actinobacteria) were similar in both groups. Beta diversity was significantly different due to differences in Bacteroidetes and Proteobacteria (p<0.0001). Within Proteobacteria, RAs of classes Alphaproteobacteria (~21%, fold change (FC)=1.31, false discovery rate (FDR) p value=0.03) and Epsilonproteobacteria (~1%, FC=0.25, FDR p value>0.05) were increased in acute appendicitis samples. RAs of unknown genera from families Burkholderiaceae and Enterobacteriaceae were decreased in appendicitis samples, and 14 genera were increased, including Neisseria, Acinetobacter and Campylobacter. Quantitative PCR revealed that levels of Campylobacter jejuni DNA, but not other Campylobacter species or pathogens tested, were significantly higher in appendicitis samples than in controls (p=0.013). Using a cut-off of 0.31 pg/µL, 40% of appendicitis cases and 6% of controls were positive for C. jejuni, indicating specificity of 93.7% (95% Cl 79.2 to 99.2), sensitivity of 40.9% (95% Cl 24.7 to 54.5), and OR of 10.38 (Fisher's p value=0.0006, 95% Cl 2.3 to 47.4). CONCLUSIONS: Our findings indicate that Campylobacter jejuni may be a significant cause of acute appendicitis. This supports earlier studies and suggests that targeted antibiotic therapies could be an alternative treatment for a subset of non-complicated acute appendicitis cases.

Mapping the Segmental Microbiomes in the Human Small Bowel in Comparison with Stool: A REIMAGINE Study.

BACKGROUND: Most gut microbiome studies have been performed using stool samples. However, the small intestine is of central importance to digestion, nutrient absorption, and immune function, and characterizing its microbial populations is essential for elucidating their roles in human health and disease. AIMS: To characterize the microbial populations of different small intestinal segments and contrast these to the stool microbiome. METHODS: Male and female subjects undergoing esophagogastroduodenoscopy without colon preparation were prospectively recruited. Luminal aspirates were obtained from the duodenum, jejunum, and farthest distance reached. A subset also provided stool samples. 16S rRNA sequencing was performed and analyses were carried out using CLC Genomics Workbench. RESULTS: 16S rRNA sequencing identified differences in more than 2000 operational taxonomic units between the small intestinal and stool microbiomes. Firmicutes and Proteobacteria were the most abundant phyla in the small intestine, and Bacteroidetes were less abundant. In the small intestine, phylum Firmicutes was primarily represented by lactic acid bacteria, including families Streptococcaceae, Lactobacillaceae, and Carnobacteriaceae, and Proteobacteria was represented by families Neisseriaceae, Pasteurellaceae, and Enterobacteriaceae. The duodenal and FD microbial signatures were markedly different from each other, but there were overlaps between duodenal and jejunal and between jejunal and FD microbial signatures. In stool, Firmicutes were represented by families Ruminococcaceae, Lachnospiraceae, Christensenellaceae, and Proteobacteria by class Deltaproteobacteria. CONCLUSIONS: The small bowel microbiome is markedly different from that in stool and also varies between segments. These findings may be important in determining how compositional changes in small intestinal microbiota contribute to human disease states.

Optimizing microbiome sequencing for small intestinal aspirates: validation of novel techniques through the REIMAGINE study.

BACKGROUND: The human small intestine plays a central role in the processes of digestion and nutrient absorption. However, characterizations of the human gut microbiome have largely relied on stool samples, and the associated methodologies are ill-suited for the viscosity and low microbial biomass of small intestine samples. As part of the REIMAGINE study to examine the specific roles of the small bowel microbiome in human health and disease, this study aimed to develop and validate methodologies to optimize microbial analysis of the small intestine. RESULTS: Subjects undergoing esophagogastroduodenoscopy without colon preparation for standard of care were prospectively recruited, and ~ 2 ml samples of luminal fluid were obtained from the duodenum using a custom sterile aspiration catheter. Samples of duodenal aspirates were either untreated (DA-U, N = 127) or pretreated with dithiothreitol (DA-DTT, N = 101), then cultured on MacConkey agar for quantitation of aerobic gram-negative bacteria, typically from the class Gammaproteobacteria, and on blood agar for quantitation of anaerobic microorganisms. DA-DTT exhibited 2.86-fold greater anaerobic bacterial counts compared to DA-U (P = 0.0101), but were not statistically different on MacConkey agar. DNA isolation from DA-U (N = 112) and DA-DTT (N = 43) samples and library preparation for 16S rRNA gene sequencing were also performed using modified protocols. DA-DTT samples exhibited 3.81-fold higher DNA concentrations (P = 0.0014) and 4.18-fold higher 16S library concentrations (P < 0.0001) then DA-U samples. 16S rRNA gene sequencing revealed increases in the detected relative abundances of obligate and facultative anaerobes in DA-DTT samples, including increases in the genera Clostridium (false discovery rate (FDR) P = 4.38E-6), Enterococcus (FDR P = 2.57E-8), Fusobacterium (FDR P = 0.02) and Bacteroides (FDR P = 5.43E-9). Detected levels of Gram-negative enteropathogens from the phylum Proteobacteria, such as Klebsiella (FDR P = 2.73E-6) and Providencia (FDR P < 0.0001) (family Enterobacteriaceae) and Pseudomonas (family Pseudomonadaceae) (FDR P = 0.04), were also increased in DA-DTT samples. CONCLUSIONS: This study validates novel DTT-based methodology which optimizes microbial culture and 16S rRNA gene sequencing for the study of the small bowel microbiome. The microbial analyses indicate increased isolation of facultative and obligate anaerobes from the mucus layer using these novel techniques.