Using metabolomic analysis to understand inflammatory bowel diseases

Lin, Hui-Ming; Helsby, Nuala A.; Rowan, Daryl D.; Ferguson, Lynnette R.

doi:10.1002/ibd.21426

Cited by 55 publications

(44 citation statements)

References 88 publications

(105 reference statements)

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“…Concerning the metabolome, until now several metabolomics studies have been performed to unravel the microbial metabolism following different biological questions. Many of these studies investigated the particular role of metabolites in inflammatory bowel diseases by using primarily NMR studies (Lin et al, 2011). Non-targeted metabolomics approaches in gut microbial sample matrices and liver, analysing changes occurring in metabolic diseases like obesity, are rarely given, but many studies addressed obesity-related metabolome characterization (Dumas et al, 2006;Williams et al, 2006;Fearnside et al, 2008;Li et al, 2008Li et al, , 2010aShearer et al, 2008;Newgard et al, 2009;Waldram et al, 2009;Kim et al, 2009Kim et al, , 2010Kim et al, , 2011Calvani et al, 2010;Xie et al, 2010Xie et al, , 2012Zhao et al, 2010;Oberbach et al, 2011;Duggan et al, 2011a,b;Jung et al, 2012;Hanhineva et al, 2013;Schäfer et al, 2014;Seyfried et al, 2013;Won et al, 2013;Xu et al, 2013;Daniel et al, 2014;Eisinger et al, 2014).…”

Section: Discussionmentioning

confidence: 99%

Distinct signatures of host–microbial meta-metabolome and gut microbiome in two C57BL/6 strains under high-fat diet

et al. 2014

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A combinatory approach using metabolomics and gut microbiome analysis techniques was performed to unravel the nature and specificity of metabolic profiles related to gut ecology in obesity. This study focused on gut and liver metabolomics of two different mouse strains, the C57BL/6J (C57J) and the C57BL/6N (C57N) fed with high-fat diet (HFD) for 3 weeks, causing dietinduced obesity in C57N, but not in C57J mice. Furthermore, a 16S-ribosomal RNA comparative sequence analysis using 454 pyrosequencing detected significant differences between the microbiome of the two strains on phylum level for Firmicutes, Deferribacteres and Proteobacteria that propose an essential role of the microbiome in obesity susceptibility. Gut microbial and liver metabolomics were followed by a combinatory approach using Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR-MS) and ultra performance liquid chromatography time of tlight MS/MS with subsequent multivariate statistical analysis, revealing distinctive host and microbial metabolome patterns between the C57J and the C57N strain. Many taurine-conjugated bile acids (TBAs) were significantly elevated in the cecum and decreased in liver samples from the C57J phenotype likely displaying different energy utilization behavior by the bacterial community and the host. Furthermore, several metabolite groups could specifically be associated with the C57N phenotype involving fatty acids, eicosanoids and urobilinoids. The mass differences based metabolite network approach enabled to extend the range of known metabolites to important bile acids (BAs) and novel taurine conjugates specific for both strains. In summary, our study showed clear alterations of the metabolome in the gastrointestinal tract and liver within a HFD-induced obesity mouse model in relation to the host-microbial nutritional adaptation.

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Section: Discussionmentioning

confidence: 99%

Distinct signatures of host–microbial meta-metabolome and gut microbiome in two C57BL/6 strains under high-fat diet

et al. 2014

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“…These approaches involve the unbiased quantitative and qualitative analysis of the complete set of small molecules (molecular weight <1,000 Da) present in cells, organisms, body fluids or tissues 20 . Thousands of small molecules derived from microorganisms present in the gut or from food and drug intake are expected to be present in humans 21,22 .…”

Section: The Human Gut Microbiotamentioning

confidence: 99%

How the microbiota shapes rheumatic diseases

et al. 2016

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The human gut harbours a tremendously diverse and abundant microbial community that correlates with, and even modulates, many health-related processes. The mucosal interfaces are particularly active sites of microorganism-host interplay. Growing insight into the characteristic composition and functionality of the mucosal microbiota has revealed that the microbiota is involved in mucosal barrier integrity and immune function. This involvement affects proinflammatory and anti-inflammatory processes not only at the epithelial level, but also at remote sites such as the joints. Here, we review the role of the gut microbiota in shaping local and systemic immune responses and how disturbances in the host-microorganism interplay can potentially affect the development and progression of rheumatic diseases. Increasing our understanding of how to promote host-microorganism homeostasis could therefore reveal novel strategies for the prevention or alleviation of rheumatic disease.

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“…12,13 Metabolomics studies have been reported in human patients with IBD as well as animal models of IBD, and provided new insights into disease pathogenesis. 14,15 Using mass spectrometry platforms, an untargeted metabolomics approach can identify hundreds of metabolites in biological samples simultaneously, and therefore provides a comprehensive functional overview of biochemical pathways that are being up-or downregulated during different physiologic or pathophysiologic state. 16 In veterinary medicine, only few studies have utilized this approach in clinical patients, 17,18 and to our knowledge, no studies using an untargeted metabolomics approach have been reported in dogs with IBD.…”

Section: Introductionmentioning

confidence: 99%

Alteration of the fecal microbiota and serum metabolite profiles in dogs with idiopathic inflammatory bowel disease

et al. 2015

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Idiopathic inflammatory bowel disease (IBD) is a common cause of chronic gastrointestinal (GI) disease in dogs. The combination of an underlying host genetic susceptibility, an intestinal dysbiosis, and dietary/environmental factors are suspected as main contributing factors in the pathogenesis of canine IBD. However, actual mechanisms of the hostmicrobe interactions remain elusive. The aim of this study was to compare the fecal microbiota and serum metabolite profiles between healthy dogs (n D 10) and dogs with IBD before and after 3 weeks of medical therapy (n D 12). Fecal microbiota and metabolite profiles were characterized by 454-pyrosequencing of 16 S rRNA genes and by an untargeted metabolomics approach, respectively. Significantly lower bacterial diversity and distinct microbial communities were observed in dogs with IBD compared to the healthy control dogs. While Gammaproteobacteria were overrepresented, Erysipelotrichia, Clostridia, and Bacteroidia were underrepresented in dogs with IBD. The functional gene content was predicted from the 16 S rRNA gene data using PICRUSt, and revealed overrepresented bacterial secretion system and transcription factors, and underrepresented amino acid metabolism in dogs with IBD. The serum metabolites 3-hydroxybutyrate, hexuronic acid, ribose, and gluconic acid lactone were significantly more abundant in dogs with IBD. Although a clinical improvement was observed after medical therapy in all dogs with IBD, this was not accompanied by significant changes in the fecal microbiota or in serum metabolite profiles. These results suggest the presence of oxidative stress and a functional alteration of the GI microbiota in dogs with IBD, which persisted even in the face of a clinical response to medical therapy.

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Using metabolomic analysis to understand inflammatory bowel diseases

Cited by 55 publications

References 88 publications

Distinct signatures of host–microbial meta-metabolome and gut microbiome in two C57BL/6 strains under high-fat diet

Distinct signatures of host–microbial meta-metabolome and gut microbiome in two C57BL/6 strains under high-fat diet

How the microbiota shapes rheumatic diseases

Alteration of the fecal microbiota and serum metabolite profiles in dogs with idiopathic inflammatory bowel disease

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