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Gut microbiome: debugging the obesity and cancer link Overview

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Presentation on theme: "Gut microbiome: debugging the obesity and cancer link Overview"— Presentation transcript:

1 Gut microbiome: debugging the obesity and cancer link Overview
Carrie R. Daniel-MacDougall, PhD, MPH Department of Epidemiology Division of Cancer Prevention and Population Sciences

2 Biological mechanisms linking adiposity and cancer risk
Adapted from Ho et al. Cancer Res 2012

3 Diet, energy balance, and gut microbiome
The composition of bacteria living within the gut can be linked to functional metabolic pathways in the host Figure of healthy gut (fecal) microbiome: NIH-HMP Consortium, Nature 2012 Energy balance regulation Secretion of leptin Hepatic insulin sensitivity and lipid synthesis Modulate intestinal environment and appetite signaling

4 Diet may directly and indirectly modulate association between energy balance (EB) and cancer
Satiety Insulin signaling Prebiotic fibers (e.g., legumes) resist digestion until they reach the colon; undergo bacterial fermentation Obesity or weight-loss Microbial energy harvest from the diet; fat storage by host; energy loss in feces Microbial production of SCFA Regulation of EB SCFA (Propionate, acetate, butyrate) act as signaling molecules on G-protein coupled receptors expressed in colon and adipocytes Secretion of leptin; hepatic insulin sensitivity and lipid synthesis; modulate intestinal environment and appetite signaling Endocrine

5 Diet, gut microbiome, obesity, and cancer
Energy balance Inflammation Insulin Resistance Relevant exposures (e.g., diet, medications)

6 Nadim Ajami, PhD, Baylor College of Medicine
Alkek Center for Metagenomics and Microbiome Research (Director: Joe Petrosino, PhD), Department of Molecular Virology and Microbiology Cross-talk between Akkermansia muciniphila and intestinal epithelium controls diet-induced obesity (Everard 2013) Manasi Shah, MS, MD Anderson & UT-SPH Decreased dietary fiber intake and structural alteration of gut microbiota in patients with advanced colorectal adenoma (Chen 2013)

7 Alkek Center for Metagenomics and Microbiome Research
Nadim J. Ajami, Ph.D. Alkek Center for Metagenomics and Microbiome Research Department of Molecular Virology and Microbiology Baylor College of Medicine Houston, TX

8 Key concepts Akkermansia muciniphila Gram-negative anaerobe
Degrades mucin Resides in the mucus layer of the intestinal epithelium Abundant in nutrient-rich environments Represents 3-5% of the microbial community in healthy subjects Abundance inversely correlates with body weight, severity of appendicitis, and T1D Obesity and Type 2 Diabetes Altered gut microbiota Inflammation Gut barrier disruption Increased gut permeability -> endotoxemia & metabolic inflammation Named after Dutch microbiologist Antoon D.L. Akkermans, pioneer in studying molecular ecology of bacterial communities

9 Objective Hypothesis Experimental design
To define the physiological role of Akkermansia muciniphila in obesity. Hypothesis A. Muciniphila controls gut barrier function Experimental design Administration of live or heat-killed A. muciniphila to mice fed a high-fat diet. Gut barrier Glucose homeostasis Adipose tissue metabolism

10 Findings Akkermansia muciniphila treatment reverses high-fat diet-induced metabolic disorders, including fat-mass gain, metabolic endotoxemia, adipose tissue inflammation, and insulin resistance.

11 Abundance of A. muciniphila is decreased in obese and diabetic mice
Leptin defficient mice Leptin: 16-kDa adipose-derived hormone that plays a key role in regulating energy intake and expenditure, including appetite and hunger, metabolism, and behavior. Mechanism? Prebiotic: Oligofructose 0.3gr/mouse/day

12 Prebiotic treatment restores A
Prebiotic treatment restores A. muciniphila to basal levels and reverses metabolic endotoxemia Mechanism?

13 High fat (HF) diet increases macrophage infiltration and fat mass
CD11c subpopulation of macrophages: primary population of increases adipose tissue macrophages in obesity Muciniphila does not grow in oligofructose media – suggesting complex cross-feeding interactions Oligofructose  goblet cells  mucin production  thicker mucus layer? Evidence in rats. Mucin degrading bug  turnover of mucin…steady production Oligofructose changes more than 100 different taxa in mice

14 Treatment with A. muciniphila does not induce changes in the gut microbiota
HF diet alters the composition of the microbiota irrespective of Akk. MITChip V1/V6 16S rRNA gene

15 A. Muciniphila counteracts metabolic endotoxemia, diet induced obesity, adipose tissue macrophage infiltration, improves glucose homeostasis, and adipose tissue metabolism 1F: 40% reduction in hepatic glucose-6-phosphatase expression, thereby suggesting a reduction in gluconeogenesis. 1G: increased expression of markers of adipocyte differentiation and lipid oxidation without affecting lipogenesis markers (Fasn [fatty acid synthase] and Acc1 [acetyl-CoA carboxylase]) Mechanism? – Role of other bacteria… Verrucomicrobia? High circulating LPS levels inhibit adipose tissue differentiation and lipogenesies, thereby contributing to altered adipose tissue metabolism

16 A. Muciniphila colonization restores gut barrier function and increases intestinal endocannabinoids in diet-induced obese mice Intestinal acylglycerols previously demonstrated to reduce metabolic endotoxemia and systemic inflammation  gut barrier function Endocannabinoid system: group of neuromodulatory lipids/receptors involved in processes such as appetite, pain sensations, mood, memory, energy storage, nutrient transport, insulin sensitivity, obesity, diabetes, atherosclerosis etc. Link between the gut microbiota and intestinal endocannabinoid system tone. Decrease monoacylglycerol lipase expression with improved gut barrier function and decreased metabolic inflammation 46% thinner mucus layer in HF-fed mice A. Muciniphila treatment counteracts this decrease

17 Heat-killed A. muciniphila does not counteract metabolic endotoxemia, diet induced obesity, oral glucose intolerance, gut barrier dysfunction or poor adipose tissue metabolism Endotoxemia Fat mass Plasma Glucose Markers of adipocyte differentiation Viable A. muciniphila is required

18 Conclusions and future directions
A. muciniphila: Restores the mucus layer of the intestine Restores gut barrier function and thereby contributes to normalize metabolic endotoxemia and adipose tissue metabolism Improves glucose tolerance and decreases endogenous hepatic glucose production Muciniphila increased the expressionof RegIII gamma under the control diet but not under HF diet. Fecal IgA levels were not affected by treatments, which suggeests tht A. muciniphila controsl gut barrier functin by other mechanism of epithelial function Development of a treatment that uses A. muciniphila for the prevention or treatment of obesity and its associated metabolic disorders?

19 Thank you for your attention
Nadim J. Ajami, Ph.D. Alkek Center for Metagenomics and Microbiome Research

20 Gut microbiome: debugging the obesity and cancer link
Manasi Shah, MS Department of Epidemiology Division of Cancer Prevention and Population Sciences

21 Surrogate marker of diet and environmental history?
The Gut Microbiome Gut Microbiome Surrogate marker of diet and environmental history? Emerging technology Multiple sequencing procedures being developed (WGS) Modifiable! Structural and functional constitution related to diet, obesity and inflammation Modern Day surrogate marker

22 Background Diet may influence colon cancer risk via the microbiota and its metabolites Dietary habits may influence early events in the colon carcinogenic process Fiber Short Chain Fatty Acids (SCFA) in colon lower risk of CRC Colon cancer risk influenced by the balance between microbial production of health-promoting metabolites, such as butyrate; and potentially carcinogenic metabolites, such as secondary bile acids SCFA’s in the colonic lumen is linked to a decreased incidence of CRC by promoting the delivery of short-chain fatty acids (SCFAs), such as butyrate (fermented by the gut microbiota) to the distal colon. SCFA’s in the colonic lumen is linked to a decreased incidence of CRC - is influenced by the balance between microbial production of health-promoting metabolites such as butyrate and potentially carcinogenic metabolites such as secondary bile acids

23 Gut Microbiome and Colon Cancer- The Balancing Act
Dysbiosis is an imbalance in the natural flora of the gut- establishment of opportunistic infections Fig: Jobin, Inflamm Bowel Dis 2011

24 Gut Microbiome and Colorectal Neoplasia
Four high resolution maps of colonic dysbiosis have been independently reported: CRC tissue as compared to adjacent non-malignant mucosa: Potential pathogenic bacteria in CRC tissue Coriobacteridae, Roseburia, Fusobacterium and Faecalibacterium (Marchesi, PLoS 2011) Fusobacterium sequences were enriched in carcinomas while the Bacteroidetes and Firmicutes phyla were depleted (Kostic, Genome Res 2012) Overabundance of Fusobacterium sequences in tumor vs matched control tissue ( Castellarin, Genome Res 2012) Significantly lower level of Lachnospiraceace, Ruminococcaceae and Lactobacillaceae in cancerous tissues compared to normal intestinal lumen. Relative abundance of Bacteroidaceae, Streptococcacea, Fusobacteriaceae was also higher in the cancerous tissue (Chen, PLoS One 2012) Neoplasia- is an abnormal mass of tissue as a result of abnormal growth or division of cells Neoplasms may be benign, pre-malignant or malignant Primarily tissue studies Vs fecal samples- commensal bacteria

25 Cross Sectional Study Flow:

26 Subjects and Methods Consecutive patients who had undergone colonoscopy in 5 medical centers in China, ≥ 50 yrs of age NO previous history of colorectal adenoma or carcinoma or IBD, normal bowel movement Pathological confirmation of advanced colorectal adenoma (A-CRA) Patients with no obvious abnormalities allotted in the healthy control (HC) group Data on demographics, colonoscopy results, lifestyle factors and dietary intake were collected via interview-administered questionnaires Fresh stool samples were collected from all the participants. Fecal SCFA content analyzed by gas chromatography Analysis of 16s rRNA sequences done by 454 pyrosequencing of fecal samples

27 Results

28 Multivariate logistic analysis identified four statistically significant factors associated with advanced colorectal adenoma (A-CRA)

29 Significantly lower yields of fecal SCFAs were found in the A-CRA group (n = 47) than in the HC group (n = 47). The major SCFA product was acetate, followed by butyrate and propionate.

30 Separation between the microbiota genus in the HC (n = 47) and A-CRA (n = 47) groups was significant
Principal component analysis showed altered fecal gut microbiota communities in patients with A-CRA (n = 47) compared with the HCs (separated from principal component 1 at 15.22% and principal component 2 at 10.34% of the explained variance, respectively). On the x axis PC1 direction, the intestinal microbiota of the HC group (n = 47) was relatively consistent and was distinct from that in the A-CRA group (n = 47). A similar tendency was seen on the y axis adenoma–principal component 2 direction, with each sample in the A-CRA group (n = 47) showing bacterial communities similar to each other, together with the appearance of distinct bacterial communities in the ACRA group (n = 47) compared with the HC group (n = 47) PC analysis plots based on the unweighted UniFrac. p = 0.001, t test of permutation

31 Differences in butyrate and butyrate-producing bacteria:
In the HC group (n = 47), both butyrate and butyrate-producing bacteria (Clostridium and Roseburia spp.) were more abundant in subjects with a high fiber intake than in those with a low fiber intake. These differences were also apparent in the A-CRA subgroups. In the low-fiber subgroups, no differences in butyrate and the butyrateproducing bacteria (Clostridium, Roseburia, and Eubacterium spp.) were found between the HC and A-CRA groups; however, in the high-fiber subgroup, both butyrate and butyrate-producing bacteria were more enriched in the HC group than in the A-CRA Group

32 Summary and Discussion
Main Findings: Structural imbalance in the fecal gut microbiota and difference in SCFA concentrations was defined in the A-CRA, as compared to HC Butyrate and other SCFA’s associated with reduced risk of CRC: 3 genera of butyrate-producing bacteria (Clostridium, Roseburia, and Eubacterium) were lower in the A-CRA group than in the HC group Significant higher levels of opportunistic pathogens: Enterococcus and Streptococcus in A-CRA Implications: Microbial community may play an important role in pathogenesis of the progression from A-CRA to CRC via dietary SCFA products Persistent deficiency in substrate dietary fiber may result in a deficiency in butyrate-producing bacteria  fermentation of SCFAs  increased risk of A-CRA

33 Limitations Cross-sectional design: no cause-effect
Prospective human studies are required to determine whether an altered gut microbiome increases risk of colorectal cancer/adenoma or is an artifact of pre-existing disease 454 pyrosequencing identifies bacteria at genus, but not species level. Higher depth genomic techniques may be required to fully differentiate the colonizing groups and their subsequent functions Fecal SCFA concentrations correlate with both formation and uptake throughout the gut, but do not necessarily reflect SCFA production

34 ‘Food’ for Thought: Future Directions
Transmissible and modifiable interactions between diet and microbiota influence host biology and cancer development in mice: Intact uncultured and culturable bacterial component of Obese co-twin’s fecal microbiota caused significantly greater increases in body mass and adiposity than those of lean communities (Ridaura, Science 2013) Diet- or gene-induced obesity alters gut microbiota, thereby increasing the levels of metabolites that secrete inflammatory and tumor-promoting factors in the liver facilitating development of liver cancer (Yoshimoto, Nature 2013) Potential for translation to humans… Gut Microbiome Obesity Colorectal Cancer Inflammation Diet deoxycholic acid (DCA) which provoke Senescence-associated secretory phenotype (SASP) . SASP secretes inflammatory and tumor-promoting factors in the liver facilitating HCC development (Yoshimoto, Nature 2013)

35 Thank You!

36 In Conclusion Microbe-dependent effects
Gene Induced Obesity Mutation or polymorphism Increased Energy Harvest Altered Metabolic Signaling Altered Inflammation Microbe-dependent effects Diet-Induced Obesity High fat/high calorie diet Microbiome Induced Obesity Disrupted microbial community Fiber slows digestion and the postprandial glucose response by slowing the entry of glucose into the bloodstream, thereby reducing insulin stimulation (43). Because a fiber-rich meal is processed more slowly and nutrient absorption occurs over a greater period of time, fiber is linked to a number of positive effects on obesity- and insulin-related factors, including satiety, weight management, adiponectin levels, and diabetes risk Microbe involvement in SCFA Metabolism & GPCR recognition High Fiber diet- reduces insulin stimulation, increases gastric transit time Increased Adipose Tissue Figure adapted from Blaser et al, Cell Press (2013)

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