Connections between the microbiome and health are rapidly emerging in a wide range of diseases. However, a detailed mechanistic understanding of how different microbial communities are influencing their hosts is often lacking. One method researchers have used to understand these effects are germ-free (GF) mouse models. Differences found within the organ systems of these model organisms may highlight generalizable mechanisms that microbiome dysbioses have throughout the host. Here, we applied multiplexed, quantitative proteomics on the brains, spleens, hearts, small intestines, and colons of conventionally raised and GF mice, identifying associations to colonization state in over 7000 proteins. Highly ranked associations were constructed into protein-protein interaction networks and visualized onto an interactive 3D mouse model for user-guided exploration. These results act as a resource for microbiome researchers hoping to identify host effects of microbiome colonization on a given organ of interest. Our results include validation of previously reported effects in xenobiotic metabolism, the innate immune system, and glutamate-associated proteins while simultaneously providing organism-wide context. We highlight organism-wide differences in mitochondrial proteins including consistent increases in NNT, a mitochondrial protein with essential roles in influencing levels of NADH and NADPH, in all analyzed organs of conventional mice. Our networks also reveal new associations for further exploration, including protease responses in the spleen, high-density lipoproteins in the heart, and glutamatergic signaling in the brain. In total, our study provides a resource for microbiome researchers through detailed tables and visualization of the protein-level effects of microbial colonization on several organ systems.

Consumption of refined high-fat, low-fiber diets promotes development of obesity and its associated consequences. Although genetics play an important role in dictating susceptibility to such obesogenic diets, mice with nearly uniform genetics exhibit marked heterogeneity in their extent of obesity in response to such diets. This suggests non-genetic determinants play a role in diet-induced obesity. Hence, we sought to identify parameters that predict, and/or correlate with, development of obesity in response to an obesogenic diet. We assayed behavior, metabolic parameters, inflammatory markers/cytokines, microbiota composition, and the fecal metaproteome, in a cohort of mice (n = 50) prior to, and the 8 weeks following, administration of an obesogenic high-fat low-fiber diet. Neither behavioral testing nor quantitation of inflammatory markers broadly predicted severity of diet-induced obesity. Although, the small subset of mice that exhibited basal elevations in serum IL-6 (n = 5) were among the more obese mice in the cohort. While fecal microbiota composition changed markedly in response to the obesogenic diet, it lacked the ability to predict which mice were relative prone or resistant to obesity. In contrast, fecal metaproteome analysis revealed functional and taxonomic differences among the proteins associated with proneness to obesity. Targeted interrogation of microbiota composition data successfully validated the taxonomic differences seen in the metaproteome. Although future work will be needed to determine the breadth of applicability of these associations to other cohorts of animals and humans, this study nonetheless highlights the potential power of gut microbial proteins to predict and perhaps impact development of obesity.

The gut microbiota plays a key role in host metabolism. Toll-like receptor 5 (TLR5), a flagellin receptor, is required for gut microbiota homeostasis. Accordingly, TLR5-deficient (T5KO) mice are prone to develop microbiota-dependent metabolic syndrome. Here we observed that T5KO mice display elevated neutral lipids with a compositional increase of oleate [C18:1 (n9)] relative to wild-type littermates. Increased oleate contribution to hepatic lipids and liver SCD1 expression were both microbiota dependent. Analysis of short-chain fatty acids (SCFAs) and (13)C-acetate label incorporation revealed elevated SCFA in ceca and hepatic portal blood and increased liver de novo lipogenesis in T5KO mice. Dietary SCFAs further aggravated metabolic syndrome in T5KO mice. Deletion of hepatic SCD1 not only prevented hepatic neutral lipid oleate enrichment but also ameliorated metabolic syndrome in T5KO mice. Collectively, these results underscore the key role of the gut microbiota-liver axis in the pathogenesis of metabolic diseases.

Ulcerative colitis (UC) is driven by disruptions in host-microbiota homoeostasis, but current treatments exclusively target host inflammatory pathways. To understand how host-microbiota interactions become disrupted in UC, we collected and analysed six faecal- or serum-based omic datasets (metaproteomic, metabolomic, metagenomic, metapeptidomic and amplicon sequencing profiles of faecal samples and proteomic profiles of serum samples) from 40 UC patients at a single inflammatory bowel disease centre, as well as various clinical, endoscopic and histologic measures of disease activity. A validation cohort of 210 samples (73 UC, 117 Crohn's disease, 20 healthy controls) was collected and analysed separately and independently. Data integration across both cohorts showed that a subset of the clinically active UC patients had an overabundance of proteases that originated from the bacterium Bacteroides vulgatus. To test whether B. vulgatus proteases contribute to UC disease activity, we first profiled B. vulgatus proteases found in patients and bacterial cultures. Use of a broad-spectrum protease inhibitor improved B. vulgatus-induced barrier dysfunction in vitro, and prevented colitis in B. vulgatus monocolonized, IL10-deficient mice. Furthermore, transplantation of faeces from UC patients with a high abundance of B. vulgatus proteases into germfree mice induced colitis dependent on protease activity. These results, stemming from a multi-omics approach, improve understanding of functional microbiota alterations that drive UC and provide a resource for identifying other pathways that could be inhibited as a strategy to treat this disease.

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.