(559d) Identification of Gut Microbiota-Derived Metabolites As Liver Inflammation Modulators in Non-Alcoholic Fatty Liver Disease | AIChE

(559d) Identification of Gut Microbiota-Derived Metabolites As Liver Inflammation Modulators in Non-Alcoholic Fatty Liver Disease

Authors 

Krishnan, S. - Presenter, Tufts University
Lee, K. - Presenter, Tufts University
Jayaraman, A. - Presenter, Texas A&M University
Choi, M. - Presenter, Tufts University
Saedi, N. - Presenter, Massachusetts General Hospital
Ding, Y. - Presenter, Texas A&M University
Yarmush, M. L. - Presenter, Center for Engineering in Medicine (CEM) at Massachusetts General Hospital – Harvard Medical School - Shriners Hospital for Children

Identification of Gut Microbiota-derived Metabolites as Liver Inflammation Modulators in Non-alcoholic Fatty Liver Disease

The human gastrointestinal (GI) tract harbors an estimated 10 to 100 trillion microorganisms, encompassing several hundred different species. Collectively referred to as the gut microbiota, the microbes perform a number of essential physiological functions, including the metabolism of complex carbohydrates [1], development of the immune system [2], and defense against pathogens [3]. Beyond the GI tract, gut-brain, gut-lung, and gut-liver associations have also been identified, highlighting the importance of the microbiota in host physiology. Consistent with the view that the microbiota is critical for whole body homeostasis, alterations in the intestinal microbiota composition (i.e. dysbiosis) have been correlated to various diseases, including obesity [4, 5], diabetes [6], and cancer [7].

            Non-alcoholic fatty liver disease (NAFLD) has emerged as the most prevalent chronic liver disease in Western countries, paralleling the rise in obesity and the metabolic syndrome. It is characterized by steatosis, or fat deposition in the liver, which can remain a benign condition. However, in 10-20% of patients, NAFLD progresses from steatosis to non-alcoholic steatohepatitis (NASH), which can lead to cirrhosis and liver cancer. Seminal work by the Gordon laboratory [8, 9] and other groups demonstrated that dysbiosis could be a contributing mechanism for obesity and related diseases, including NAFLD, whose estimated prevalence in obese individuals exceeds 75% [10]. Direct, potentially causal involvement of the microbiota in NASH was highlighted by Le Roy et al. [11], who reported that high fat diet (HFD)-fed germ-free (GF) mice inoculated with bacterial isolates from feces of HFD-fed hyperglycemic mice developed steatohepatitis, whereas HFD-fed GF mice inoculated with bacteria from HFD-fed, but normoglycemic mice only showed mild steatosis. This suggests that the composition of the intestinal microbiota, and hence their metabolic products, could determine whether NAFLD progresses to NASH. While these and other recent studies have begun to build a strong case for potential mechanistic links between dysbiosis and NASH, the identities of microbiota-derived molecular mediators and their target pathways remain to be fully elucidated. The study described in this abstract utilizes both untargeted and targeted metabolomics to identify and characterize microbiota-dependent immunomodulatory metabolites that act on the liver to modulate liver inflammation in steatosis.

            In previous work [13], we identified a panel of aromatic amino acid (AAA)-derived metabolites whose levels in the mouse intestine depended on the presence of the microbiota. Furthermore, several of these metabolites were found to activate the aryl hydrocarbon receptor (AhR), a transcriptional regulator of host-microbiota interactions in the intestine. To investigate a potential role for these metabolites in NAFLD, we compared their profiles in serum and liver samples from 14-week old male C57BL/6J mice raised for 8 weeks either on HFD or low-fat diet (LFD). The diets were sucrose calorie-matched and derived 60% and 10% of calories from fat, respectively. Metabolites were extracted from cold PBS-rinsed liver tissue and serum samples using a solvent-based method. Using an untargeted method, we  identified 73 AAA-derived metabolites, including host- and microbiota-dependent metabolites as well as their methyl and hydroxyl derivatives. Interestingly, a large fraction of metabolites that were significantly elevated or depleted in liver and serum from HFD-fed mice (compared to LFD-fed mice) were the hydroxyl/methyl derivatives. Several of the metabolites that were consistently detected in all four sets of samples (liver and serum, HFD and LFD) were previously found to depend on the microbiota and activate the AHR [13]. We thus selected a pair of representative metabolites from this set, tryptamine (TA) and indole-3-acetate (I3A), for further analysis. 

            Absolute quantification of TA and I3A using targeted analysis confirmed that their levels were significantly elevated (ca. 2- and 3-fold, respectively) in the serum of LFD mice compared to HFD mice. We then investigated the ability of TA and I3A to modulate inflammation in hepatocytes using both human (HepG2) and murine (AML12) cell lines. Cultured HepG2 cells were treated with 1, 10, or 100 mM TA or I3A for 24 h, and then exposed to the pro-inflammatory cytokine TNFα for another 24 h in the presence of the metabolites. The expression of two anti-inflammatory genes (IL-4 and IL-10) and a pro-inflammatory chemokine (MCP1) were determined using qPCR. For all three markers, pretreatment with I3A or TA at the 10 mM dose significantly attenuated the pro-inflammatory responses elicited by TNFα treatment. These trends were in good agreement with the results obtained using the AML12 murine cell line. 

            Using HepG2 cells, we next investigated whether the AAA-derived, microbiota-dependent metabolites could modulate the impact of TNFα treatment on cholesterol and bile acid metabolism. Compared to vehicle control, TNFα treatment significantly increased both intra- and extracellular levels of several bile acids, including cholic acid (CA), glycocholic acid (GCA), and taurocholic acid (TCA). This profile was consistent with our findings that both CA and TCA were significantly elevated in livers of HFD-fed mice compared to LFD-fed mice. Pretreatment with either 1 mM TA or I3A significantly attenuated the TNFα–stimulated increases in bile acid levels, similar to the metabolites’ effects on cytokine and chemokine gene expression.

            To confirm activation of the AHR pathway, we utilized a hepatocyte reporter cell line, where binding of an AHR-ligand complex to the dioxin response element (DRE) leads to transcription of the reporter gene (GFP), resulting in fluorescence. Consistent with our previous findings [13], 24 h exposure to TA and I3A dose-dependently increased GFP expression in the reporter cells, indicating ligand activation of the AHR by these metabolites.

            In summary, our results demonstrate that several AAA-derived microbiota metabolites are significantly depleted in a mouse model of diet-induced liver steatosis, and that these metabolites can act directly on hepatocytes to modulate inflammatory pathways. Our results also show that these microbiota metabolites are ligands for the AHR, providing a mechanistic link for the observed anti-inflammatory effects. Taken together, our findings support the hypothesis that dysbiosis of the gut microbiota could predispose the liver to inflammation in diet-induced steatosis through an altered microbiota metabolite profile. Prospectively, insights into the mechanisms underlying the link between microbiota dysbiosis and NAFLD could provide novel strategies to treat or prevent the progression of fatty liver diseases through the use of probiotics or postbiotics.

[1]        T. Arora and R. Sharma, "Fermentation potential of the gut microbiome: implications for energy homeostasis and weight management," Nutrition Reviews, vol. 69, pp. 99-106, 2011.

[2]        L. V. Hooper, D. R. Littman, and A. J. Macpherson, "Interactions Between the Microbiota and the Immune System," Science, vol. 336, pp. 1268-1273, June 8, 2012 2012.

[3]        N. Kamada, G. Y. Chen, N. Inohara, and G. Nunez, "Control of pathogens and pathobionts by the gut microbiota," Nat Immunol, vol. 14, pp. 685-690, 2013.

[4]        J. Shen, M. S. Obin, and L. Zhao, "The gut microbiota, obesity and insulin resistance," Molecular Aspects of Medicine, vol. 34, pp. 39-58, 2013.

[5]        S. Greenblum, P. J. Turnbaugh, and E. Borenstein, "Metagenomic systems biology of the human gut microbiome reveals topological shifts associated with obesity and inflammatory bowel disease," Proceedings of the National Academy of Sciences, vol. 109, pp. 594-599, January 10, 2012 2012.

[6]        J. K. Nicholson, E. Holmes, J. Kinross, R. Burcelin, G. Gibson, W. Jia, et al., "Host-Gut Microbiota Metabolic Interactions," Science, vol. 336, pp. 1262-1267, June 8, 2012 2012.

[7]        J. C. Arthur, E. Perez-Chanona, M. Mühlbauer, S. Tomkovich, J. M. Uronis, T.-J. Fan, et al., "Intestinal Inflammation Targets Cancer-Inducing Activity of the Microbiota," Science, vol. 338, pp. 120-123, October 5, 2012 2012.

[8]        R. E. Ley, F. Backhed, P. Turnbaugh, C. A. Lozupone, R. D. Knight, and J. I. Gordon, "Obesity alters gut microbial ecology," Proc Natl Acad Sci U S A, vol. 102, pp. 11070-5, Aug 2 2005.

[9]        P. J. Turnbaugh, R. E. Ley, M. A. Mahowald, V. Magrini, E. R. Mardis, and J. I. Gordon, "An obesity-associated gut microbiome with increased capacity for energy harvest," Nature, vol. 444, pp. 1027-31, Dec 21 2006.

[10]      S. G. Sheth, F. D. Gordon, and S. Chopra, "Nonalcoholic steatohepatitis," Ann Intern Med, vol. 126, pp. 137-45, Jan 15 1997.

[11]      T. Le Roy, M. Llopis, P. Lepage, A. Bruneau, S. Rabot, C. Bevilacqua, et al., "Intestinal microbiota determines development of non-alcoholic fatty liver disease in mice," Gut, vol. 62, pp. 1787-94, Dec 2013.

[12]      W. R. Wikoff, A. T. Anfora, J. Liu, P. G. Schultz, S. A. Lesley, E. C. Peters, et al., "Metabolomics analysis reveals large effects of gut microflora on mammalian blood metabolites," Proceedings of the National Academy of Sciences of the United States of America, vol. 106, pp. 3698-3703, Mar 2009.

[13]      G. V. Sridharan, K. Choi, C. Klemashevich, C. Wu, D. Prabakaran, L. B. Pan, et al., "Prediction and quantification of bioactive microbiota metabolites in the mouse gut," Nat Commun, vol. 5, p. 5492, 2014.