It has been recently demonstrated that an altered microbiota acts “locally” through a damaged gut epithelial barrier, and acts systemically on various target organs and cells via its metabolites.1 This is in accordance with the metabolomic studies, which revealed that gut microbiota-derived metabolites determined in many extra-intestinal tissues influence metabolic and immunologic phenotypes in the hosts.2 In support of such a concept, more and more evidence recently showed that gut microbiota is involved in the development of diabetes mellitus (DM) although there are some findings diverge among studies.3,4
Gut microbiota-derived metabolites are closely associated with DM
In recent years, the role of intestinal flora in diabetes has been paid much attention. It is well-known that human intestinal microorganisms weigh about 1.5–2.0 kg, and their distribution density gradually increases from proximal to distal intestines, including about 100 billion bacteria, mainly composed of five bacteria: bacteroides, sclerenchyma, actinomycetes, proteus, and verrucous microflora. Genetic and environmental risk factors, dietary preferences, and sedentary lifestyle are involved in the development of DM. While the host provides nutrition for intestinal microorganisms, intestinal microorganisms can help the body to digest complex carbohydrates, produce signaling molecules, and participate in maintaining the immune and metabolic functions. Recent studies have found that dysbiosis of gut microbiota mediates host cell immune disorders, chronic inflammation, and the development of DM through abnormal production of its metabolites. The main signaling pathways mediated by intestinal flora through these metabolites are as following (summarized as Figure 1).
Short-chain fatty acids
Intestinal flora fermented dietary fiber in the colon and thus led to the production of the short-chain fatty acids (SCFAs) butyrate, propionate, and acetate. Cumulative data have revealed that SCFAs as metabolites of microbiota, not only provide energy sources for the host cells (accounting for 5%–10% of the energy intake5), but also serve as signal molecules which activate downstream G protein-coupled receptors (GPRs) expressed on the specific cell surface, such as GPR41, GPR43, GPR109a, and Olfactory receptor 78, then participating in the energy metabolism and regulating blood pressure. Immune cells, hepatocytes, adipose cells, and skeletal muscle cells are known to possess cell surface receptors for SCFAs. The SCFAs have been suggested to influence glucose, lipid homeostasis, and insulin sensitivity in DM. Recent studies have found that imbalance of intestinal flora leads to abnormal SCFAs production, impairs the integrity of the intestinal barrier, activates the inflammation signaling cascades and thus promotes the multi-organs damage.6
Acetate is the most abundant microbiota-derived SCFAs. For diabetic individuals, acetate is mainly derived from fiber diet fermented by microbiota, and also from vinegar or alcohol intake and a small amount of endogenous cellular production. There are accumulating discrepant findings of acetate-mediated metabolic regulation. Some studies show that the concentrations of fecal acetate in obese individuals are increased,7 whereas the data cannot provide a causal relationship of microbial energy harvesting and the development of obesity. Perry et al.8 indicated that whole-body acetate turnover is increased in rats with high fat diet-induced obesity, and gut microbial acetate production might be partly responsible for the increase. Moreover, chronic intra-gastric acetate administration for 10 days can cause weight gain and insulin resistance in rats.8 However, several animal and clinical studies have shown that increasing the acetate availability via dietary sources and stimulation of microbial production prevents diet-induced body weight gain, counteracts adiposity, and improves glucose homeostasis and insulin sensitivity. Den Besten et al.9 demonstrated that added 5% sodium acetate to high-fat-fed mice for 12 weeks, the animals showed reduced body weight gain and improved insulin sensitivity without changing food intake or physical activity.
The protective effects of butyrate on intestines and the peripheral tissues have been comprehensively summarized.10 Indeed, butyrate supplementation by dietary intake has been supposed to prevent high fat-diet induced obesity and insulin resistance. Moreover, butyrate suppressed pro-inflammatory cytokines production and decreased the migration and accumulation of monocyte in patients with type 2 DM.11 Collectively, butyrate is widely recognized as a protective metabolite in energy regulation, while additional work is needed to further elucidate the effects in peripheral tissues and potential mechanism of its action.
The trimethylamine N-oxide pathway
Trimethylamine (TMA) is derived from dietary choline, L-carnitine, and phosphatidylcholine by fermentation of certain microbiota species. TMA is further oxidized to trimethylamine N-oxide (TMAO) in the liver. The oxidization process is catalytic by the enzyme flavin monooxygenase 3 (FMO3).
The TMAO pathway enhances cholesterol accumulation in macrophages and platelet hyperactivaties.12 Accordingly, elevated plasma TMAO level has been shown to increase the risk of cardiovascular disease,13 non-alcoholic fatty liver disease,14 and DM.7,15 In mice fed with a high-fat diet, dietary TMAO intake (0.2%) exacerbated adipose tissue inflammation and the hepatic insulin resistance, which are driving factors of DM.16 Accordingly, inhibition of FMO3 related to reduced TMAO formation decreases the plasma levels of glucose. Moreover, TMAO supplements were shown to attenuate endoplasmic reticulum stress and blunt diabetes-induced activation of the unfolded protein response in streptozotocin-induced diabetic mice. To sum, the TMA/FMO3/TMAO pathway activation might play a key negative effect of glucose metabolism maintenance. A clinical trial17,18 was designed for 2 years to examine the association between low-calorie diet-induced changes of plasma TMAO levels with diabetes-related parameter changes among 264 overweight and obese individuals. The results revealed that weight loss was significantly related to a decrease in TMAO levels, indicating plasma levels of TMAO might serve as a predictive marker of response to weight-loss treatment. The same study documented a significant improvement of insulin resistance associated with decreases in the TMAO precursors choline and L-carnitine.
The above animal and clinical observation are based on the association of the TMA/FMO3/TMAO pathways with glucose metabolism and target organ dysfunction. Nevertheless, direct molecular targets of TMAO and the potential mechanisms have not yet been elucidated. Recently, the mechanism of epigenetic modifications of TMAO is supposed to be involved in the development of insulin resistance.19
Homeostasis of the gut microbiota is important for maintenance of the host immunity. There has been evidence demonstrating that changes in gut microbiota composition affect gut permeability20 and inflammation21 in DM.22,23 An altered composition and diversity of gut microbiota impaired immune cells and causes intestinal barrier demagnification via microbial products-lipopolysaccharide (LPS).24 The LPS released from the gut into the systemic circulation caused “metabolic endotoxemia”-a state of low-grade systemic inflammation.
The LPS translocates from the gut lumen to enter the blood circulation by paracellular or transcellular manners. The translocation routes depend on lipids in the epithelium of intestinal tract since LPS has a high affinity to lipoproteins and lipoproteins help to increase the translocation of LPS to the blood circulation. Host cells response to LPS exposure promote not only lipogenesis and adipocytes dysfunction, but also the phenotypic change to M1 type of macrophages.25 The LPS is a group of structurally diverse molecules and mainly functions as an agonist to toll-like receptor-4 (TLR-4). The LPS does not directly bind to TLR4, whereas a typical “pattern” of LPS can be recognized and incorporated in an activation complex involving LPS-binding proteins, cluster of differentiation 14, and myeloid differentiation factor 2 (MD-2).26 This (TLR4MD-2LPS)2 complex initiates the myeloid differentiation primary response protein 88 (MyD88)-NF-κB activation and triggers downstream inflammatory pathways and pro-inflammatory cytokine expression cascades.27 The LPS-TLR4 and other inflammatory signaling pathways are mediators of systemic inflammation, insulin resistance, and DM.4
Aromatic amino acids and their related metabolites
The aromatic amino acids family, which all contain an aromatic ring, consists of tryptophan, phenylalanine, and tyrosine. Aromatic amino acids could be generated into indole and p-cresol by the catalytic effect of tyrosine phenollyase in gut microbiota.28 Subsequently, indole and p-cresol are absorbed into blood circulation and ultimately sulfated into indoxyl sulfate and p-cresyl sulfate by hepatic cells, respectively.
The sulfation of phenols and indoles is supposed to be associated with thrombosis29,30 and kidney diseases.31 Indoxyl sulfate and p-cresyl sulfate, also known as uremic toxins, could be accumulated in the blood of patients with chronic kidney disease. The recent study clarified the precisely biological or toxic effects of the gut microbiota-derived metabolites. The p-cresyl sulfate elicited multi-toxicities in glomerular cells. Particularly, overproduction and abnormal excessive accumulation of the metabolite p-cresyl sulfate in the plasma-induced mitochondrial dysfunction, podocytes injuries, thickened the glomerular basement membrane, and ultimately led to renal micro-inflammation, and perivascular fibrosis. Collectively, p-cresyl sulfate might lead to exaggerated albuminuria in diabetic nephropathy.32 Determined by untargeted metabolomics, the levels of gut microbiota-derived metabolite p-cresyl sulfate in the kidney were increased in progressive diabetic rats with human uremic toxin transporter SLCO4C1 overexpression. Furthermore, in a diabetic patient cohort, p-cresyl sulfate levels ware significantly correlated with basal and predicted 2-year progression of albuminuria. The p-cresyl sulfate administration induced podocyte damage and albuminuria in diabetic animals whereas inhibition of tyrosine phenol-lyase and p-cresyl sulfate synthesis reduced albuminuria in diabetic mice. These data suggest that reducing dietary intake of aromatic amino acids might decrease p-cresyl sulfate production, thereby reducing albuminuria and being renoprotective for diabetic patients.
Modulation of intestinal flora could be a therapeutic target for DM
Prebiotics and dietary interventions
Prebiotics, as a kind of food ingredients, are indigestible and fermentable, promoting the amplification or biological activity of certain beneficial gut bacteria. Prebiotics are also defined as “A substrate that is selectively utilized by host microorganisms conferring a health benefit.” by the International Scientific Association for Probiotics and Prebiotics.33 Some food ingredients are recognized as prebiotics, such as indigestible polysaccharides, including inulin, lactulose, oligosaccharides, galactooligosaccharides, fructooligosaccharides, and resistant starch.34 Prebiotics elicited beneficial effects by promoting the growth of healthy microbiota and modulating microbiota-derived metabolites levels of LPS35 and SCFAs, which reduced inflammation, improved the integrity of intestinal epithelium, and nutrient absorption. Recently, a systematic review included 27 published studies were carried out to provide evidence-based beneficial effects of prebiotics on the metabolic modulation and anti-inflammatory properties of individuals with DM compared with placebo intervention.36
Compared to fecal microbiota transplantation (FMT), probiotic treatment provides an attempt to targeted modulation of the gut microbiota. Probiotics are specific live microorganisms which confer beneficial effects on the host by adding adequate probiotic to the microbiota community.33 Probiotics have been proved to be clinically efficient treatment options in some indications.37 The effects of probiotics on glycemic control of diabetic patients displayed controversy results. It was reported that both live and dead probiotic-treated streptozotocin-induced diabetic mice exhibited enhanced insulin sensitivity, decreased serum levels of glycated hemoglobin and leptin compared to the mice in diabetic group.38 There also have been some randomized controlled trials to provide clinical evidence of efficacious beneficial effects of probiotics on glycemic control and insulin resistance among patients with type 2 DM.39
Due to the confounding factors, such as dietary reference and drugs usage that may also affect the gut microbiota, the evaluation of probiotic efficacy is far more complicated in the human population. Thus, future research should be rigorously designed to rule out the confounding factors for better understanding the effects and the potential mechanisms of probiotics on the metabolic regulation in diabetes.
Microbiome depletion has been used frequently to investigate the role of the gut microbiome in pathological conditions by the administration of several broad-spectrum antibiotics through drinking water or gavage. Some animal studies have been carried out to clarify the effects of different antibiotics related microbiome depletion on the host. Treatment with norfloxacin and ampicillin for 2 weeks lowered blood glucose levels and improved insulin resistance of two obese mice models (leptin-deficient and diet-induced).40 The antibiotic ciprofloxacin exerted profound and rapid shift on the distal gut microbiota community composition and a decrease of diversity within 3–4 days of antibiotics intervention.41 Consistently, the application of antibiotics decreased the diversity of the microbiome and dramatically decreased the levels of microbiota related metabolites SCFAs and bile acids. Thus, the enterocytes in colon tended to prefer glucose as the main metabolic energy source since the deprivation of butyrate. This metabolic shift lowered serum glucose, improved insulin sensitivity, and increased hepatic gluconeogenesis.42 Collectively, the data summarized here further suggest that gut dysbiosis, characterized by decrease diversity and abnormal composition of the microbiota, could contribute to type 2 diabetes and metabolic diseases through alteration of multiple metabolites mediated signaling.43 Whereas the metabolic benefits of this acute microbiome depletion strategy are still unclear: is derived from the depletion of the microbiome, or due to the direct effects of antibiotics on the host or the combination?
Fecal microbiota transplantation
The FMT is a prime example of untargeted microbiome regulation performed by transferring stools from a “healthy” donor to the gastrointestinal tract of an “unhealthy” recipient, for the purpose of improving the spectrum and diversity of the microbiome. FMT is served as a treatment option in metabolic diseases for its beneficial modulation on the production of signaling molecules SCFAs production,44 inhibition of bile acid/ nuclear receptor farnesoid X receptor pathway,45 and amelioration of inflammation and insulin resistance.46 In a placebo-controlled clinical trial on metabolic syndrome, FMT originating from lean healthy donors significantly ameliorated peripheral insulin resistance for obese individuals.47 Consistently, the beneficial effects of FMT were confirmed in another three-fold larger follow-up study which also observed a significant reduction in glycated hemoglobin at 6 weeks after FMT.48 Indeed, these studies provide powerful evidence in the causal interaction between gut microbiota and metabolic syndrome. Extensive research is needed to unravel the potential mechanisms by which gut microbiota interact with host energy metabolism.
There are some logistical challenges of clinical FMT application for FMT related risks (eg, infection) and undesirable side effects (eg, microbiota-associated diseases).49 The safety and efficacy of FMT need further consideration. Optimization of individualized FMT treatment enables this promising new field as novel therapeutic possibilities.
The limitations of the methodological strategies in microbiome analysis
The DNA sequencing analyses provide sequence information of microbial communities from different sample sources and enable quantification and comparison of the associated microbiota profiles. Nevertheless, there are some technical variations and biases for these analytical approaches. The gene region and microbial biomass for analysis of 16S ribosomal ribonucleic acid (rRNA) sequencing can differ among different studies, which influences the scope of the sequencing of microbiota types. Moreover, less microbial DNA queried for analysis, more contamination sequences derived primarily from dust, reagents, and crossover samples, etc. Other variations are derived from the detailed procedures of sample storage, microbial sharing during FMT and longitudinal microbial instability in the host.
Lack of in-depth taxonomic analysis and functional annotation
So far, most microbiome analyses are dependent on the 16S rRNA gene amplification sequencing. This method is relatively low cost and enables large-scale cohort study to be possible. However, the current analysis depth of amplicon sequencing of the 16S rRNA gene is usually limited to the genus level.50 While some of the recent analysis suggests that many taxonomic associations may occur in the subordinate level of species (subspecies or strain).51 Moreover, amplicon sequencing often limits the scope of classification for bacteria and archaea, thus missing information about viruses and eukaryotic members of the intestinal flora. As the whole-genome shotgun method of metagenomic sequencing becomes more economically feasible, the resolution and the limitation of the scope of the taxonomy will soon be overcome. Indeed, metagenomic sequencing also provides microbial genes information and the function of gene library, but this valuable information is usually not in-depth study, part of the reason is the lack of functional annotation, and gut microbial genes, especially the isolated bacteria, are not clear so far.
Advances in gut microbial research
Indeed, 16S rRNA amplicon sequencing has boosted the research field of microbiome and continues to be widely carried out. Kim et al. summarized optimizing approaches and dodging pitfalls in microbiome research. They also made several effective feasible and recommendations for the research design of microbiome studies.52 It is encouraging that there have been several novel research techniques such as multi-omic microbiome research sequencing, quantitative microbiome profiling, microfluidics-based chip systems, and extensive taxonomic resolution. Microbiome features and linkages to the host have been far more overlooked and waiting for further precise microbiome modulation as powerful disease intervention.53
To summarize, recent evidence has emphasized a significant role for gut microbiota in metabolic and immune regulation in DM. The pathways and regulatory mechanisms underlying this role, including the metabolites derived from gut microbiota described here (Figure 2), may provide attractive points to further explore pharmacological options for the therapeutic induction of gut microbiota. Although there have been some limitations of gut microbial research, and the current research on the role of gut microbiota in DM is still at an early stage, more and more large-scale longitudinal and interventional studies would be implemented by updating the methodological toolbox, the improvement of gut microbiota dysbiosis could be one of the effective intervention targets for the treatment of DM in the future.
1. Barko PC, McMichael MA, Swanson KS, Williams DA. The gastrointestinal microbiome: a review. J Vet Intern Med
2018; 32 (1):9–25.
2. Blumberg R, Powrie F. Microbiota, disease, and back to health: a metastable journey. Sci Transl Med
2012; 4 (137):137rv7.
3. Cho I, Blaser MJ. The human microbiome: at the interface of health and disease. Nat Rev Genet
2012; 13 (4):260–270.
4. Wen L, Duffy A. Factors influencing the gut microbiota, inflammation, and type 2 diabetes. J Nutr
2017; 147 (7):1468S–1475S.
5. den Besten G, van Eunen K, Groen AK, Venema K, Reijngoud DJ, Bakker BM. The role of short-chain fatty acids in the interplay between diet, gut microbiota, and host energy metabolism. J Lipid Res
2013; 54 (9):2325–2340.
6. Schippa S, Conte MP. Dysbiotic events in gut microbiota: impact on human health. Nutrients
2014; 6 (12):5786–5805.
7. Fernandes J, Su W, Rahat-Rozenbloom S, Wolever TM, Comelli EM. Adiposity, gut microbiota and faecal short chain fatty acids are linked in adult humans. Nutr Diabetes
8. Perry RJ, Peng L, Barry NA, et al. Acetate mediates a microbiome-brain-beta-cell axis to promote metabolic syndrome. Nature
2016; 534 (7606):213–217.
9. den Besten G, Bleeker A, Gerding A, et al. Short-chain fatty acids protect against high-fat diet-induced obesity via a PPARgamma-dependent switch from lipogenesis to fat oxidation. Diabetes
2015; 64 (7):2398–2408.
10. McNabney SM, Henagan TM. Short chain fatty acids in the colon and peripheral tissues: a focus on butyrate, colon cancer, obesity and insulin resistance. Nutrients
2017; 9 (12):E1348.
11. Larasati RA, Harbuwono DS, Rahajeng E, et al. The role of butyrate on monocyte migration and inflammation response in patient with type 2 diabetes mellitus. Biomedicines
2019; 7 (4):E74.
12. Zhu W, Gregory JC, Org E, et al. Gut microbial metabolite TMAO enhances platelet hyperreactivity and thrombosis risk. Cell
2016; 165 (1):111–124.
13. Senthong V, Li XS, Hudec T, et al. Plasma trimethylamine N-oxide, a gut microbe-generated phosphatidylcholine metabolite, is associated with atherosclerotic burden. J Am Coll Cardiol
2016; 67 (22):2620–2628.
14. Chen YM, Liu Y, Zhou RF, et al. Associations of gut-flora-dependent metabolite trimethylamine-N-oxide, betaine and choline with non-alcoholic fatty liver disease in adults. Sci Rep
15. Shan Z, Sun T, Huang H, et al. Association between microbiota-dependent metabolite trimethylamine-N-oxide and type 2 diabetes. Am J Clin Nutr
2017; 106 (3):888–894.
16. Gao X, Liu X, Xu J, Xue C, Xue Y, Wang Y. Dietary trimethylamine N-oxide exacerbates impaired glucose tolerance in mice fed a high fat diet. J Biosci Bioeng
2014; 118 (4):476–481.
17. Heianza Y, Sun D, Smith SR, Bray GA, Sacks FM, Qi L. Changes in gut microbiota-related metabolites
and long-term successful weight loss in response to weight-loss diets: the POUNDS lost trial. Diabetes Care
2018; 41 (3):413–419.
18. Heianza Y, Sun D, Li X, et al. Gut microbiota metabolites
, amino acid metabolites
and improvements in insulin sensitivity and glucose metabolism: the POUNDS lost trial. Gut
2019; 68 (2):263–270.
19. Oellgaard J, Winther SA, Hansen TS, Rossing P, von Scholten BJ. Trimethylamine N-oxide (TMAO) as a new potential therapeutic target for insulin resistance and cancer. Curr Pharm Des
2017; 23 (25):3699–3712.
20. Cani PD, Possemiers S, Van de Wiele T, et al. Changes in gut microbiota control inflammation in obese mice through a mechanism involving GLP-2-driven improvement of gut permeability. Gut
2009; 58 (8):1091–1103.
21. Boutagy NE, McMillan RP, Frisard MI, Hulver MW. Metabolic endotoxemia with obesity: is it real and is it relevant? Biochimie
22. Everard A, Belzer C, Geurts L, et al. Cross-talk between Akkermansia muciniphila and intestinal epithelium controls diet-induced obesity. Proc Natl Acad Sci U S A
2013; 110 (22):9066–9071.
23. Clemente-Postigo M, Queipo-Ortuno MI, Murri M, et al. Endotoxin increase after fat overload is related to postprandial hypertriglyceridemia in morbidly obese patients. J Lipid Res
2012; 53 (5):973–978.
24. Brar PC, Kohn B. Use of the microbiome in the management of children with type 2 diabetes mellitus. Curr Opin Pediatr
2019; 31 (4):524–530.
25. Vishnyakova TG, Bocharov AV, Baranova IN, et al. Binding and internalization of lipopolysaccharide by Cla-1, a human orthologue of rodent scavenger receptor B1. J Biol Chem
2003; 278 (25):22771–22780.
26. Park BS, Song DH, Kim HM, Choi BS, Lee H, Lee JO. The structural basis of lipopolysaccharide recognition by the TLR4-MD-2 complex. Nature
2009; 458 (7242):1191–1195.
27. Zanoni I, Ostuni R, Marek LR, et al. CD14 controls the LPS-induced endocytosis of Toll-like receptor 4. Cell
2011; 147 (4):868–880.
28. Agus A, Planchais J, Sokol H. Gut microbiota regulation of tryptophan metabolism in health and disease. Cell Host Microbe
2018; 23 (6):716–724.
29. Yang K, Du C, Wang X, et al. Indoxyl sulfate induces platelet hyperactivity and contributes to chronic kidney disease-associated thrombosis in mice. Blood
2017; 129 (19):2667–2679.
30. Gao H, Liu S. Role of uremic toxin indoxyl sulfate in the progression of cardiovascular disease. Life Sci
31. Hsiao EY, McBride SW, Hsien S, et al. Microbiota modulate behavioral and physiological abnormalities associated with neurodevelopmental disorders. Cell
2013; 155 (7):1451–1463.
32. Kikuchi K, Saigusa D, Kanemitsu Y, et al. Gut microbiome-derived phenyl sulfate contributes to albuminuria in diabetic kidney disease. Nat Commun
2019; 10 (1):1835.
33. Gibson GR, Hutkins R, Sanders ME, et al. Expert consensus document: the international scientific association for probiotics and prebiotics (ISAPP) consensus statement on the definition and scope of prebiotics. Nat Rev Gastroenterol Hepatol
2017; 14 (8):491–502.
34. Nakamura YK, Omaye ST. Metabolic diseases and pro- and prebiotics: mechanistic insights. Nutr Metab (Lond)
2012; 9 (1):60.
35. Wang X, Bao W, Liu J, et al. Inflammatory markers and risk of type 2 diabetes: a systematic review and meta-analysis. Diabetes Care
2013; 36 (1):166–175.
36. Colantonio AG, Werner SL, Brown M. The effects of prebiotics and substances with prebiotic properties on metabolic and inflammatory biomarkers in individuals with type 2 diabetes mellitus: a systematic review. J Acad Nutr Diet
2019; pii: S2212-2672(18)31341-8.
37. Ford AC, Quigley EM, Lacy BE, et al. Efficacy of prebiotics, probiotics, and synbiotics in irritable bowel syndrome and chronic idiopathic constipation: systematic review and meta-analysis. Am J Gastroenterol
2014; 109 (10):1547–1561.
38. Li X, Xu Q, Jiang T, et al. A comparative study of the antidiabetic effects exerted by live and dead multi-strain probiotics in the type 2 diabetes model of mice. Food Funct
2016; 7 (12):4851–4860.
39. Tiderencel KA, Hutcheon DA, Ziegler J. Probiotics for the treatment of type 2 diabetes: a review of randomized controlled trials. Diabetes Metab Res Rev
40. Chou CJ, Membrez M, Blancher F. Gut decontamination with norfloxacin and ampicillin enhances insulin sensitivity in mice. Nestle Nutr Workshop Ser Pediatr Program
41. Dethlefsen L, Relman DA. Incomplete recovery and individualized responses of the human distal gut microbiota to repeated antibiotic perturbation. Proc Natl Acad Sci U S A
2011; 108: (Suppl 1): 4554–4561.
42. Mahana D, Trent CM, Kurtz ZD, et al. Antibiotic perturbation of the murine gut microbiome enhances the adiposity, insulin resistance, and liver disease associated with high-fat diet. Genome Med
2016; 8 (1):48.
43. Mikkelsen KH, Allin KH, Knop FK. Effect of antibiotics on gut microbiota, glucose metabolism and body weight regulation: a review of the literature. Diabetes Obes Metab
2016; 18 (5):444–453.
44. de Groot P, Scheithauer T, Bakker GJ, et al. Donor metabolic characteristics drive effects of faecal microbiota transplantation on recipient insulin sensitivity, energy expenditure and intestinal transit time. Gut
2019; pii: gutjnl-2019-318320.
45. Wahlstrom A, Sayin SI, Marschall HU, Backhed F. Intestinal crosstalk between bile acids and microbiota and its impact on host metabolism. Cell Metab
2016; 24 (1):41–50.
46. de Groot PF, Frissen MN, de Clercq NC, Nieuwdorp M. Fecal microbiota transplantation in metabolic syndrome: history, present and future. Gut Microbes
2017; 8 (3):253–267.
47. Vrieze A, Van Nood E, Holleman F, et al. Transfer of intestinal microbiota from lean donors increases insulin sensitivity in individuals with metabolic syndrome. Gastroenterology
2012; 143 (4):913–916.e7.
48. Kootte RS, Levin E, Salojarvi J, et al. Improvement of insulin sensitivity after lean donor feces in metabolic syndrome is driven by baseline intestinal microbiota composition. Cell Metab
2017; 26 (4):611–619.e6.
49. Kahn SA, Gorawara-Bhat R, Rubin DT. Fecal bacteriotherapy for ulcerative colitis: patients are ready, are we? Inflamm Bowel Dis
2012; 18 (4):676–684.
50. Matias Rodrigues JF, Schmidt TSB, Tackmann J, von Mering C. MAPseq: highly efficient k-mer search with confidence estimates, for rRNA sequence analysis. Bioinformatics
2017; 33 (23):3808–3810.
51. Costea PI, Coelho LP, Sunagawa S, et al. Subspecies in the global human gut microbiome. Mol Syst Biol
2017; 13 (12):960.
52. Kim D, Hofstaedter CE, Zhao C, et al. Optimizing methods and dodging pitfalls in microbiome research. Microbiome
2017; 5 (1):52.
53. Schmidt TSB, Raes J, Bork P. The human gut microbiome: from association to modulation. Cell
2018; 172 (6):1198–1215.