Focus articles

Several studies have been performed around the world on the gut microbiome-endocannabinoidome axis. The members of CERC-MEND have been busy finding relevant articles and reviewing them for your reading.

Endocannabinoids as an alternative to reduce virulence of pathogens

Commensal bacteria make GPCR ligands that mimic human signaling molecules

-Review by Isabelle Bourdeau-Julien and Prof. Frédéric Raymond.

The gut shelters billions of microorganisms consuming and rejecting different molecules that are absorbed and directed to the bloodstream [1]. The importance of the contribution of the gut microbiota to host metabolism is well recognized, but the mechanisms regulating this interaction is still poorly understood [2]. Indeed, the large variety of bacterial metabolic functions and cross-feeding interactions between bacteria makes the gut microbiota hard to study [3]. Using a mechanistic approach, Cohen and colleagues report that the gut microbiota would affect host metabolism through GPCR activity [4].

G-protein coupled receptors (GPCRs) are the largest family membrane receptors in eukaryote and the most studied drug targets. GPCR ligands include N-acyl amides, a class of molecules with numerous possible combinations of amine head groups and acyl tails. They modulate a large variety of metabolic functions involved in glucose metabolism, inflammation, lipid metabolism, neuronal activity, satiety, appetite, gastrointestinal motility, etc. [5, 6]. Their importance for the metabolism is also demonstrated by their implication in many diseases such as diabetes, obesity, cancer, inflammatory bowel disease and others [7]. Moreover, it was reported that, in 2017, clinical trials for new drugs targeting GPCRs were mostly aimed at obesity and diabetes [8].

Recent evidence suggests that GPCR and bioactive lipid metabolism would be important for the interaction between the gut microbiota and host metabolism. Among GPCR ligands, endocannabinoidome mediators has been strongly associated to the gut microbiota and metabolic diseases [9, 10]. Also, commendamide is a long-chain N-acyl amide produced by gut bacteria that can interact with GPR132 (G2A) [11]. Cohen and colleagues provide further evidence by finding gut microbiota N-acyl amides that interact with eukaryotic G-protein coupled receptors.

First, they used bioinformatic analysis of the human microbiota sequencing data to identify potential GPCR-active N-acyl amides encoded by gut microorganisms. With a BLASTN search of N-acyl synthase (NAS) genes in the Human Microbiome Project, they identified 143 human microbial (hm) NAS genes. Out of the 44 hm-NAS tested in E. Coli cultures, 31 produced N-acyl amides that could be grouped in six families based on the amine head group and the fatty acid tail; (1) N-acyl glycine; (2) N-acyloxyacyl lysine; (3) N-acyloxyacyl glutamine; (4) N-acyl lysine/ornithine; (5) N-acyl alanine; (6) N-acyl serinol.

Looking at their distribution in different body sites, they observed an enrichment of hm-NAS genes in bacteria of the gastrointestinal tract. Even within the gastrointestinal tract, some region harbors different patterns of hm-NAS genes corresponding to specific N-acyl amide families. For example, in stool samples, genes encoding for N-acyl glycine (1) are highly enriched compared to the other N-acyl amide families. Although their expression level differs between individuals, most hm-NAS genes are found in 90% of individuals except for the genes responsible for the production of the N-acyl amides from two families (3 and 5) which are very little or not detected. Thus, NAS-genes are highly prevalent in human gut microbiome.

Then, to validate the potential of the bacterial N-acyl amide to interact with GPCRs, the major metabolites of each gene families were assayed for agonist and antagonist activity against 240 human GPCRs. Strong and specific agonist interactions were observed for N-palmitoyl serinol (6) with GPR119, N-3-hydroxypalmitoyl ornithine (4) with S1PR4 and N-myristoyl alanine (5) with GPR132 (G2A). Specific antagonist interaction was observed for N-acyloxyacyl glutamine (3) with prostaglandin receptor PTGIR and PTGER4 was antagonized by some N-acyl amides including N-acyloxyacyl glutamine (3). Thus, in addition to having hm-NAS genes, the bacterial N-acyl amide produced can interact with GPCRs.

Bacterial N-acyl amides have structural and functional similarities with endogenous human GPCR ligands. The clearest overlap is observed between OEA and 2-OG, ligands for the endocannabinoid receptor GPR119, and N-oleoyl serinol (6). Beyond structural similarities, Cohen and al. show the bacterial ligand N-oleoyl serinol (6) induce a higher activation of GPR119 and GLP-1 secretion by GLUTag cells than the human ligands. In mice, colonization with E.coli producing N-oleoyl serinols (6) decreased blood glucose and increased secretion of the hormones GLP-1 and insulin. Thus, GPR119 bacterial agonist can regulate metabolic hormones and glucose homeostasis as efficiently as human ligands.

Cohen and colleagues suggest that the relationship between the gut microbiota and host metabolism would be regulated through GPCR-associated signaling. Indeed, the authors provide strong evidence for the potential of the gut microbiota to modulate many physiological processes through the production of GPCR ligands. However, there are some limitations to the study. First, by looking at the gene abundance of hm-NAS genes from the 6 main families in different body sites, the N-acyl serinol (6) family was not detected in stool samples. Yet, the metabolite interacting with GPR119 and regulating metabolic hormones and glucose homeostasis as efficiently as human ligands is part of the N-acyl serinol (6) family. Thus, further studies will be needed to investigate which hm-NAS genes are present in human stool bacteria, their expression level, and the presence of N-acyl amides. Also, as the authors have pointed out, it would be interesting to look at co-localization of GPCR with hm-NAS gene expression in gastrointestinal niches to confirm the potential interactions.

The authors suggest a commensal relationship between gut microbiota and the host where the beneficial bacteria evolved to mimic our signaling molecules. The relationship between the gut microbiota and the host can be seen a mutualism interaction, being beneficial for both the bacteria and the host. Furthermore, organisms from mutualistic relationships tend to co-evolve [12]. In fact, several evidence show that the gut microbiota and the host co-evolved, among others with the immune system [13]. Therefore, we can hypothesize that humans have evolved to express GPCRs interacting with bacterial ligands in tissues where the microbiota is abundant. Also, bacteria use metabolites for communication between microorganisms. Among these, N-acyl-homoserine lactones (AHLs) are used for quorum-sensing and are detected by LuxR family proteins in prokaryote [14]. As bacterial N-acyl amides have structural similarities with AHLs, they could be used for bacterial communication. It would be useful to test the microorganism’s response to bacterial N-acyl amides. It would also be interesting to compare the presence and expression of genes responsible for N-acyl amide production in the bacteria of the microbiota to bacteria from other non-human associated ecosystems. In this regard, Cohen and colleagues point out that the bacterial metabolites N-acyl ornithine, lysine and glutamines are natural produced by soil bacteria [15, 16]. In plants, it has been shown that bacterial quorum-sensing AHLs regulate Arabidopsis root growth through two receptors, whose expression level is dependent on the bacterial metabolites [17]. This way, the interaction of the gut microbiota and human host through GPCR metabolism could be the result of co-evolution. Although, an important research effort would be necessary to test this hypothesis.

Read the full article.


[1]       K. Oliphant and E. Allen-Vercoe, “Macronutrient metabolism by the human gut microbiome: major fermentation by-products and their impact on host health,” (in eng), Microbiome, vol. 7, no. 1, p. 91, 06 2019, doi: 10.1186/s40168-019-0704-8.

[2]       Z. Y. Kho and S. K. Lal, “The Human Gut Microbiome – A Potential Controller of Wellness and Disease,” (in eng), Front Microbiol, vol. 9, p. 1835, 2018, doi: 10.3389/fmicb.2018.01835.

[3]       D. Ríos-Covián, P. Ruas-Madiedo, A. Margolles, M. Gueimonde, C. G. de Los Reyes-Gavilán, and N. Salazar, “Intestinal Short Chain Fatty Acids and their Link with Diet and Human Health,” (in eng), Front Microbiol, vol. 7, p. 185, 2016, doi: 10.3389/fmicb.2016.00185.

[4]       L. J. Cohen et al., “Commensal bacteria make GPCR ligands that mimic human signalling molecules,” (in eng), Nature, vol. 549, no. 7670, pp. 48-53, 09 2017, doi: 10.1038/nature23874.

[5]       S. Lacroix et al., “Rapid and Concomitant Gut Microbiota and Endocannabinoidome Response to Diet-Induced Obesity in Mice,” (in eng), mSystems, vol. 4, no. 6, Dec 2019, doi: 10.1128/mSystems.00407-19.

[6]       A. S. Husted, M. Trauelsen, O. Rudenko, S. A. Hjorth, and T. W. Schwartz, “GPCR-Mediated Signaling of Metabolites,” (in eng), Cell Metab, vol. 25, no. 4, pp. 777-796, Apr 04 2017, doi: 10.1016/j.cmet.2017.03.008.

[7]       P. D. Cani et al., “Endocannabinoids–at the crossroads between the gut microbiota and host metabolism,” (in eng), Nat Rev Endocrinol, vol. 12, no. 3, pp. 133-43, Mar 2016, doi: 10.1038/nrendo.2015.211.

[8]       A. S. Hauser, M. M. Attwood, M. Rask-Andersen, H. B. Schiöth, and D. E. Gloriam, “Trends in GPCR drug discovery: new agents, targets and indications,” (in eng), Nat Rev Drug Discov, vol. 16, no. 12, pp. 829-842, Dec 2017, doi: 10.1038/nrd.2017.178.

[9]       C. Rousseaux et al., “Lactobacillus acidophilus modulates intestinal pain and induces opioid and cannabinoid receptors,” (in eng), Nat Med, vol. 13, no. 1, pp. 35-7, Jan 2007, doi: 10.1038/nm1521.

[10]     V. Di Marzo and C. Silvestri, “Lifestyle and Metabolic Syndrome: Contribution of the Endocannabinoidome,” (in eng), Nutrients, vol. 11, no. 8, Aug 20 2019, doi: 10.3390/nu11081956.

[11]     L. J. Cohen et al., “Functional metagenomic discovery of bacterial effectors in the human microbiome and isolation of commendamide, a GPCR G2A/132 agonist,” (in eng), Proc Natl Acad Sci U S A, vol. 112, no. 35, pp. E4825-34, Sep 01 2015, doi: 10.1073/pnas.1508737112.

[12]     L. P. Medeiros, G. Garcia, J. N. Thompson, and P. R. Guimarães, “The geographic mosaic of coevolution in mutualistic networks,” (in eng), Proc Natl Acad Sci U S A, vol. 115, no. 47, pp. 12017-12022, 11 20 2018, doi: 10.1073/pnas.1809088115.

[13]     H. Y. Cheng, M. X. Ning, D. K. Chen, and W. T. Ma, “Interactions Between the Gut Microbiota and the Host Innate Immune Response Against Pathogens,” (in eng), Front Immunol, vol. 10, p. 607, 2019, doi: 10.3389/fimmu.2019.00607.

[14]     L. Keller and M. G. Surette, “Communication in bacteria: an ecological and evolutionary perspective,” (in eng), Nat Rev Microbiol, vol. 4, no. 4, pp. 249-58, Apr 2006, doi: 10.1038/nrmicro1383.

[15]     X. Zhang, S. M. Ferguson-Miller, and G. E. Reid, “Characterization of ornithine and glutamine lipids extracted from cell membranes of Rhodobacter sphaeroides,” (in eng), J Am Soc Mass Spectrom, vol. 20, no. 2, pp. 198-212, Feb 2009, doi: 10.1016/j.jasms.2008.08.017.

[16]     E. K. Moore et al., “Lysine and novel hydroxylysine lipids in soil bacteria: amino acid membrane lipid response to temperature and pH in Pseudopedobacter saltans,” (in eng), Front Microbiol, vol. 6, p. 637, 2015, doi: 10.3389/fmicb.2015.00637.

[17]     G. Jin et al., “Two G-protein-coupled-receptor candidates, Cand2 and Cand7, are involved in Arabidopsis root growth mediated by the bacterial quorum-sensing signals N-acyl-homoserine lactones,” (in eng), Biochem Biophys Res Commun, vol. 417, no. 3, pp. 991-5, Jan 20 2012, doi: 10.1016/j.bbrc.2011.12.066.

Impact of gut microbiota on plasma oxylipins profile under healthy and obesogenic conditions

-Review by Volatiana Rakotoarivelo, postdoctoral fellow and Prof. Nicolas Flamand

During obesity, the morphological changes induced by adipocyte hypertrophy leads to hypoxia and oxidative stress [1-3]. As a result, stressed adipocytes begin to secrete proinflammatory cytokines and chemokines resulting in chronic and low-grade inflammation [4]. This inflammation is induced by activation of the immune system in tissues such as adipose tissue [5], muscle [6], the liver and pancreas [7]. This chronic inflammation is believed to contribute to the development of obesity-related-diseases, such as type 2 diabetes, hypertension and cardiometabolic diseases[4].

Oxylipins (OXLs) are bioactive lipid metabolites derived from polyunsaturated fatty acids (PUFAs) that are implicated in the inflammatory response as well as in the resolution process and play an important role in the establishment of chronic inflammation. The OXLs derived from arachidonic acid (ARA) such as prostaglandins, leukotrienes and thromboxanes may act as proinflammatory mediators whereas lipoxins derived from ARA can be implicated in the resolution of inflammation [10]. OXLs may act as signaling molecules involved in inflammatory processes associated with obesity [8, 9].

At the same time, the gut microbiota plays an important role in obesity and associated diseases. Dysbiosis of the gut microbiota contributes to proinflammatory signalling through pattern recognition receptor (PRR) activation to induce an inflammatory response [11], and other processes.

Recently, Avila-Roman and colleagues described how the composition of the gut microbiota influences plasma OXLs in a manuscript in Clinical Nutrition [12]. In this study, Wistars rats were fed either a standard chow diet (STD) or a hypercaloric cafeteria diet (CAF), which results in the development of metabolic syndrome, for 5 weeks. Two additional groups of rats fed with the STD diet and the CAF diet were treated with a cocktail of antibiotics (ABX) administered in drinking water for the last two weeks.

First, the authors observed that the CAF diet induced obesity and glucose intolerance compared to STD diet. In addition, ABX administration reduced gut microbiota diversity but not CAF-induced obesity/weight gain. ABX administration to either STD or CAF-fed rats resulted in a significant increase of the relative abundance of Proteobacteria, which are associated with inflammation, and a significant decrease in that of Bacteroidetes. In contrast, ABX specifically decreased Actinobacteria, Deferribacteraceae and Verrucomicrobia, which are associated with inflammation in STD-fed rats, while it decreased Spirochaetes in CAF-fed rats.

In addition, the authors observed drastically different profiles of plasma OXLs between the CAF- and STD-fed rats, which could be explained by the nutritional composition of the CAF diet, which was enriched in fat with higher levels of PUFAs. The authors then based their analysis on the diet type; principal coordinate analysis revealed that ABX treatment did not affect the overall profile of OXLs in STD-fed rats but did in CAF-fed rats. However, ABX-dependent changes in specific OXLs in STD-fed rats: an increase in 4-HDHA and 8-HEPE levels and a decrease in 15(R)-Lipoxin A4/A5 levels. In CAF-fed rats, a significant increase in proinflammatory OXLs, (11(12)-DiHETE, 9-HETE, LTB4 and PG D2), as well as in anti-inflammatory OXLs (11-HEPE, 15(S)-HEPE, 10-HDHA and 13-HDHA) were observed in response to ABX.

Finally, the authors correlated the relative abundance of gut bacteria with OXLs levels. Proteobacteria and Bacteroidetes were the major phyla altered by the ABX treatment. Bacteroidetes, showed negative correlations with most of the plasma OXLs (16- HDHA, 8-HEPE, LTB4 and PGD2). It is noteworthy that 16-HDHA and 8-HEPE, which are derived from the w3-PUFAs DHA and EPA respectively, are associated with anti-inflammatory effects. LTB4 and PGD2 are derived from ARA, an omega 6-PUFA linked to proinflammatory effects. Both negative and positive correlations were observed with Proteobacteria and a significant positive correlation with LTB4 was particularly notable.

Based on these observations, Avila-Roman and colleagues propose that dysbiosis of the gut alters plasma OXLs levels in obesity as well as in healthy conditions. They suggested that the gut microbiota may regulate lipid metabolism and affect the inflammatory process mediated by OXLs.  This is the first demonstrated link between microbiota dysbiosis and plasma levels of OXLs. They also propose OXLs and gut microbiota as new biomarkers for chronic low-grade inflammation as well as metabolic profiling.

However, readers should also consider the limitations of the current study. First, it is important remember that the study only found associations, and does not provide evidence for direct causality.  Further studies will be required to elucidate the specific mechanisms involved in the reported apparent alteration in lipid metabolism. In addition, it is important to consider that dysbiosis of the gut microbiota [13], as well as intestinal bioactive lipids [14], regulate intestinal permeability, which is an important parameter in the establishment of inflammation associated with obesity.  Indeed the authors did not assess the inflammatory state of the animals within this study beyond assessing changes in OXL levels.

Finally, the literature remains unclear regarding the use of inflammatory mediators as biomarkers of metabolic diseases. Whereas Hotamisligil et al. proposed TNFa as well as other pro-inflammatory cytokines as being strongly linked to obesity and the development of diabetes [15-18], later this assertion has been repeatedly challenged [19]. Indeed, the comparison between tissue and circulating concentrations of inflammatory mediators remains debated since the chronic inflammation associated with obesity is initiated by the activation of innate immune cells present in tissues, such as resident macrophages in adipose tissue [20]. It is therefore important to assess the importance of bioactive lipids in the activity of metabolic tissues such as adipose tissue, liver or muscle.

Read the full article.


  1. Kawasaki, N., et al., Obesity-induced endoplasmic reticulum stress causes chronic inflammation in adipose tissue. Scientific Reports, 2012. 2(1): p. 799.
  2. Rausch, M.E., et al., Obesity in C57BL/6J mice is characterized by adipose tissue hypoxia and cytotoxic T-cell infiltration. International Journal Of Obesity, 2007. 32: p. 451.
  3. Ye, J., Emerging role of adipose tissue hypoxia in obesity and insulin resistance. International Journal Of Obesity, 2008. 33: p. 54.
  4. Xu, H., et al., Chronic inflammation in fat plays a crucial role in the development of obesity-related insulin resistance. The Journal of Clinical Investigation, 2003. 112(12): p. 1821-1830.
  5. Braune, J., et al., IL-6 Regulates M2 Polarization and Local Proliferation of Adipose Tissue Macrophages in Obesity. The Journal of Immunology, 2017. 198(7): p. 2927.
  6. Febbraio, M.A., et al., Skeletal muscle interleukin-6 and tumor necrosis factor-α release in healthy subjects and patients with type 2 diabetes at rest and during exercise. Metabolism, 2003. 52(7): p. 939-944.
  7. Targher, G., et al., Pancreatic fat accumulation and its relationship with liver fat content and other fat depots in obese individuals. Journal of endocrinological investigation, 2012. 35(8): p. 748.
  8. Strassburg, K., et al., Postprandial fatty acid specific changes in circulating oxylipins in lean and obese men after high‐fat challenge tests. Molecular nutrition & food research, 2014. 58(3): p. 591-600.
  9. Nayeem, M.A., Role of oxylipins in cardiovascular diseases. Acta Pharmacologica Sinica, 2018. 39(7): p. 1142-1154.
  10. Pauls, S.D., et al., Anti-inflammatory effects of α-linolenic acid in M1-like macrophages are associated with enhanced production of oxylipins from α-linolenic and linoleic acid. The Journal of nutritional biochemistry, 2018. 57: p. 121-129.
  11. Belkaid, Y. and Timothy W. Hand, Role of the Microbiota in Immunity and Inflammation. Cell, 2014. 157(1): p. 121-141.
  12. Ávila-Román, J., et al., Impact of gut microbiota on plasma oxylipins profile under healthy and obesogenic conditions. Clinical Nutrition, 2021. 40(4): p. 1475-1486.
  13. Murphy, E.A., K.T. Velazquez, and K.M. Herbert, Influence of High-Fat-Diet on Gut Microbiota: A Driving Force for Chronic Disease Risk. Current opinion in clinical nutrition and metabolic care, 2015. 18(5): p. 515-520.
  14. Marton, L.T., et al., Omega fatty acids and inflammatory bowel diseases: an Overview. International journal of molecular sciences, 2019. 20(19): p. 4851.
  15. Hotamisligil, G.S., The role of TNFα and TNF receptors in obesity and insulin resistance. Journal of Internal Medicine, 2001. 245(6): p. 621-625.
  16. Hotamisligil, G.S., Inflammation and endoplasmic reticulum stress in obesity and diabetes. International journal of obesity (2005), 2008. 32(Suppl 7): p. S52-S54.
  17. Steinberg, G.R., et al., Tumor necrosis factor α-induced skeletal muscle insulin resistance involves suppression of AMP-kinase signaling. Cell Metabolism, 2006. 4(6): p. 465-474.
  18. Tuncman, G., et al., Functional in vivo interactions between JNK1 and JNK2 isoforms in obesity and insulin resistance. Proceedings of the National Academy of Sciences of the United States of America, 2006. 103(28): p. 10741-10746.
  19. Rakotoarivelo, V., et al., Inflammation in human adipose tissues–Shades of gray, rather than white and brown. Cytokine & growth factor reviews, 2018. 44: p. 28-37.
  20. Amano, Shinya U., et al., Local Proliferation of Macrophages Contributes to Obesity-Associated Adipose Tissue Inflammation. Cell Metabolism, 2014. 19(1): p. 162-171.