The Host-Microbiome Response to Hyperbaric Oxygen Therapy in Ulcerative Colitis Patients - PubMed (original) (raw)

doi: 10.1016/j.jcmgh.2022.03.008. Epub 2022 Apr 1.

Robert H Mills 1, Melissa C Kordahi [ 2](#full-view-affiliation-2 "INSERM U1016, team "Mucosal microbiota in chronic inflammatory diseases", CNRS UMR 8104, Université de Paris, Paris, France."), Marvic Carrillo-Terrazas 3, Henry Secaira-Morocho 4, Christella E Widjaja 5, Matthew S Tsai 5, Yash Mittal 5, Brian A Yee 6, Fernando Vargas 7, Kelly Weldon 8, Julia M Gauglitz 9, Clara Delaroque [ 2](#full-view-affiliation-2 "INSERM U1016, team "Mucosal microbiota in chronic inflammatory diseases", CNRS UMR 8104, Université de Paris, Paris, France."), Consuelo Sauceda 10, Leigh-Ana Rossitto 10, Gail Ackermann 9, Gregory Humphrey 9, Austin D Swafford 11, Corey A Siegel 12, Jay C Buckey Jr 13, Laura E Raffals 14, Charlotte Sadler 15, Peter Lindholm 15, Kathleen M Fisch 16, Mark Valaseck 17, Arief Suriawinata 12, Gene W Yeo 6, Pradipta Ghosh 18, John T Chang 5, Hiutung Chu 19, Pieter Dorrestein 20, Qiyun Zhu 4, Benoit Chassaing [ 2](#full-view-affiliation-2 "INSERM U1016, team "Mucosal microbiota in chronic inflammatory diseases", CNRS UMR 8104, Université de Paris, Paris, France."), Rob Knight 21, David J Gonzalez 22, Parambir S Dulai 23

Affiliations

The Host-Microbiome Response to Hyperbaric Oxygen Therapy in Ulcerative Colitis Patients

Carlos G Gonzalez et al. Cell Mol Gastroenterol Hepatol. 2022.

Abstract

Background & aims: Hyperbaric oxygen therapy (HBOT) is a promising treatment for moderate-to-severe ulcerative colitis. However, our current understanding of the host and microbial response to HBOT remains unclear. This study examined the molecular mechanisms underpinning HBOT using a multi-omic strategy.

Methods: Pre- and post-intervention mucosal biopsies, tissue, and fecal samples were collected from HBOT phase 2 clinical trials. Biopsies and fecal samples were subjected to shotgun metaproteomics, metabolomics, 16s rRNA sequencing, and metagenomics. Tissue was subjected to bulk RNA sequencing and digital spatial profiling (DSP) for single-cell RNA and protein analysis, and immunohistochemistry was performed. Fecal samples were also used for colonization experiments in IL10-/- germ-free UC mouse models.

Results: Proteomics identified negative associations between HBOT response and neutrophil azurophilic granule abundance. DSP identified an HBOT-specific reduction of neutrophil STAT3, which was confirmed by immunohistochemistry. HBOT decreased microbial diversity with a proportional increase in Firmicutes and a secondary bile acid lithocholic acid. A major source of the reduction in diversity was the loss of mucus-adherent taxa, resulting in increased MUC2 levels post-HBOT. Targeted database searching revealed strain-level associations between Akkermansia muciniphila and HBOT response status. Colonization of IL10-/- with stool obtained from HBOT responders resulted in lower colitis activity compared with non-responders, with no differences in STAT3 expression, suggesting complementary but independent host and microbial responses.

Conclusions: HBOT reduces host neutrophil STAT3 and azurophilic granule activity in UC patients and changes in microbial composition and metabolism in ways that improve colitis activity. Intestinal microbiota, especially strain level variations in A muciniphila, may contribute to HBOT non-response.

Copyright © 2022 The Authors. Published by Elsevier Inc. All rights reserved.

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Figures

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Graphical abstract

Figure 1

Figure 1

Translational sequencing studies identify effect for hyperbaric oxygen on hypoxia response pathways and neutrophil degranulation. (A and B) Boxplots of immunohistochemistry score for epithelial HIF-1α and HO-1 activity for sham (n = 8) and HBOT (n = 10) treated UC patients. Upper and lower limits represent sample score range (A, P < .001, unpaired t_ test; B, not significant). (C) Post-treatment bulk RNA sequencing results of mucosal biopsies for sham (n = 8) and HBOT (n = 5) treated UC patients enrolled in the phase 2A clinical trial. Metallothioneins are a family of highly conserved stress-induced proteins that, by control of cellular zinc homeostasis, protect against oxidative stress. (D) Boxplot of prostaglandin E2 synthase proteome abundance in mucosal biopsies is demonstrated to be significantly lower in UC patients compared with healthy controls using a publicly available proteomics dataset (left bar graph, n = 20; P = .03, unpaired t test), and prostaglandin E2 synthase expression in mucosal biopsies is demonstrated to be significantly increased with HBOT exposure in the phase 2 trials (right bar graph, n = 20; P < .0001, paired _t_ test). Ranges shown represent minimum and maximum. Sample measurement range. (_E_) TMT-multiplexed proteomics-derived enrichments in proteins reduced by HBOT treatment were strongly associated in proteins associated with azurophilic granule membranes, granules, and granule lumen. Enrichment strength (plotted) is derived from the odds ratio and adjusted _P_ value, output from Enrichr algorithm. (_F_) Day 10 pre- and post-HBOT mucosal proteome demonstrated a significant decrease in azurocidin-1 protein abundance in HBOT responders (n = 5) compared with pre-HBOT (analysis of variance–adjusted group-wise comparison, _P_ = .04) and non-responders (_P_ = .01), whereas non-responders were not significantly different from pre-HBOT condition (n = 5, _P_ > .99). (G) Fecal proteome dataset-based neutrophil-associated protein network generated by protein-protein interaction engine STRING (reformatted in CytoScape), segregated by subnetworks of granule type-specific proteins. ∗_P < .05; ∗∗P < .01; ∗∗∗P < .001, analysis of variance adjusted. Range represents minimum and maximum sample measurements.

Figure 2

Figure 2

HBOT reduces STAT3. (A) Representative image for defining ROI from mucosal tissue in patients with UC receiving HBOT, used for DSP (blue = DNA, green = Pan-Cytokeratin, red = CD45, yellow = Neutrophil Elastase). (B) Single-cell gene expression changes of STAT3 (left), STAT1 (center), and HIF-1α (right) in neutrophil-specific ROI (CD45+elastase+) in HBOT-treated vs matched control patients with UC not treated with HBOT. Each dot represents a unique ROI within a single sample, and on average 6 neutrophil-specific ROIs were available per sample per patient. Ranges represent maximum and minimum calculated values. (C) Boxplot of immunohistochemistry scores and staining for STAT3 and phosphorylated STAT3 done for mucosal biopsies. Measurements were taken before and after exposure to sham (n = 8) or HBOT (n = 22) in the phase 2 trials. Ranges represent absolute minimum and maximum. Sample values. Statistical significance derived using analysis of variance–adjusted P value calculations.

Figure 3

Figure 3

Multi-omic characterization of fecal samples identifies HBOT response status associated increases in Firmicutes and bile acid production. (A) Top 8 taxonomic families most affected by HBOT treatment calculated ratiometrically by comparing the percentage of families with species negatively altered by HBOT treatment with their overall species-level percentage representation in metagenomic features. (B) Group-wise comparison of changes in partial Mayo score as a function of post-HBOT loss in the genus Akkermansia (Welch t test, P = .014). Patients showing a decrease (<50 counts compared with their pre-HBOT condition) or no measurable levels were in decreased group, whereas no change or increase was included in the increased group. Range represents maximum calculated values. (C) Left: Group-wise comparison (paired t test, error bars plotted using ± standard error of the mean) of mucosal proteomics abundance changes in MUC2 comparing pre-HBOT (day 0, n = 10) and post-HBOT (day 10, n = 10). Right: Group-wise comparison of post-HBOT mucosal biopsy levels of MUC2 by response group. Results were not significant (unpaired t test, P = .57). (D) A muciniphila strains significantly (P < .05, uncorrected) higher post-exposure in HBOT non-responders compared with HBOT responders. (E) Heatmap generated using mean percentage scores of Average Nucleotide Identity (ANI) between BIOML A9 compared with several canonical phylogroups, with accompanying histograms of ANI scores comparing BIOML A9 and several phylogroups (left) and their boxplot distributions (bottom).

Figure 4

Figure 4

Fecal colonization of IL10-/- mice with stool from responders and non-responders to HBOT demonstrates differential modulation of colitis. Group-wise comparison (Welch unpaired t test, ± standard error of the mean) of (A) colon length (P = .0004) and (B) histology scores between IL10-/- germ-free mice colonized with post-HBOT stool from 2 non-responder donors (n = 10 mice) and 2 responder donors (n = 8 mice) measuring overall (eg, summed) histologic inflammation (P < .0001), mucosa (P = .0004), and submucosa (P < .0001). (C) Representative colon histology images from mice colonized with stool from HBOT non-responders or HBOT responders. (D) Bar plot of expression differences between mouse colonized with responder or non-responder stool (n = 8 replicates, non-responders = 10 replicates) of SOCS3 (not significant), STAT3 (not significant), HIF-1 (Welch unpaired t test, P = .017), and interferon-γ (Welch t test, P = .043) as measured by quantitative polymerase chain reaction on colon tissue.

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