Correlation between intraluminal oxygen gradient and radial partitioning of intestinal microbiota

Abstract

Background & aims: The gut microbiota is a complex and densely populated community in a dynamic environment determined by host physiology. We investigated how intestinal oxygen levels affect the composition of the fecal and mucosally adherent microbiota.

Methods: We used the phosphorescence quenching method and a specially designed intraluminal oxygen probe to dynamically quantify gut luminal oxygen levels in mice. 16S ribosomal RNA gene sequencing was used to characterize the microbiota in intestines of mice exposed to hyperbaric oxygen, human rectal biopsy and mucosal swab samples, and paired human stool samples.

Results: Average Po2 values in the lumen of the cecum were extremely low (<1 mm Hg). In altering oxygenation of mouse intestines, we observed that oxygen diffused from intestinal tissue and established a radial gradient that extended from the tissue interface into the lumen. Increasing tissue oxygenation with hyperbaric oxygen altered the composition of the gut microbiota in mice. In human beings, 16S ribosomal RNA gene analyses showed an increased proportion of oxygen-tolerant organisms of the Proteobacteria and Actinobacteria phyla associated with rectal mucosa, compared with feces. A consortium of asaccharolytic bacteria of the Firmicute and Bacteroidetes phyla, which primarily metabolize peptones and amino acids, was associated primarily with mucus. This could be owing to the presence of proteinaceous substrates provided by mucus and the shedding of the intestinal epithelium.

Conclusions: In an analysis of intestinal microbiota of mice and human beings, we observed a radial gradient of microbes linked to the distribution of oxygen and nutrients provided by host tissue.

Keywords: Aerobic; Anaerobic; Microbe; Spatial Gradient of Oxygen.

Figure 1

Application of phosphorescence oximetry to intestinal oxygen measurements. A) Intestinal oxygen measurements by phosphorescence quenching (the scheme does not represent correct proportions of physical dimensions). B) Phosphorescence decays typically observed in tissue (Oxyphor G4) and intraluminal (OxyphorMicro) oxygen measurements. C) Structure, optical absorption, and phosphorescence spectra of Pt tetrabenzoporphyrin used as an oxygen sensing element in both Oxyphor G4 and OxyphorMicro. D) Calibration curves for Oxyphor G4 in physiological saline and OxyphorMicro directly in mouse fecal material at 36.5°C. Data for OxyphorMicro are a superposition of several animal samples.

Figure 2

Effect of altering oxygen concentration in the inhaled gas mixture on host tissue and gut luminal oxygen levels. Arrows indicate switching pure O₂ on (↓) and returning to ambient air (↑). A) Changes in intestinal tissue pO₂ in the cecum. Data for the liver tissue are shown for comparison. Changes in intestinal luminal pO₂ using trans-abdominal measurements (B) and in the cecum after laparotomy (C). D) Relative time-dependent changes in tissue and luminal (cecum) pO₂’s: ΔpO₂=pO₂(t)-pO₂(0), where pO₂(t) and pO₂(0) are the pO₂ values measured at time t and in the beginning of the experiment (time zero), respectively.

Figure 3

Differences in oxygen tolerance and community membership between the mucosallyassociated and fecal microbiota. Bacterial communities were profiled using 16S rRNA gene sequencing. A) Separation of murine bacterial communities, analyzed using 16S rRNA gene sequencing of V1V2 tags, after day 6 of Hyperbaric Oxygen Therapy (HBOT). An unweighted UniFrac plot is shown (p=0.008; permanova). B) Number of samples with OTUs annotating as Anaerostipes. The difference achieves p<10e-10 (logistic mixed-effects model). C) Number of bacterial genera classified as obligate anaerobes vs. more oxygen-tolerant “all others” in paired human rectal biopsy and stool samples. D) Number of bacterial genera classified as catalase positive vs. negative in paired human rectal biopsy and stool samples. E) Relationship between mucosally- and stool-associated microbiota using an unweighted Unifrac PCoA ordination (Ellipses represent 95% confidence intervals for a multivariate normal distribution). F) Pairwise distance in microbiota composition between stool, rectal biopsy, and rectal swab samples.

Figure 4

Heatmap of the microbiota in stool, biopsy, and rectal swab samples from 16S rRNA gene sequencing. In the “Mucosally Associated Consortium” 1=Asaccharolytic bacteria and 2=Aerobic or facultative anaerobic bacteria.

Figure 5

Gene content in gut bacteria inferred from 16S rRNA gene data. Gene content was inferred by using 16S rRNA gene tag data to access whole genome sequences of bacterial relatives, and this information was used to infer potential gene content in the bacterial communities studied.