Nanjing 2 2013 Lecture "Nutrigenomics part 2" From healthy to too much: The role of the Small Intestine for metabolic flexibility"
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1. The lecture discusses the role of the small intestine in metabolic flexibility and how its function is affected by dietary factors like saturated and unsaturated fats. Microarray analysis showed high-fat diets significantly impact gene expression in the small intestine, especially related to lipid metabolism. 2. Unsaturated fats are more efficiently taken up in the small intestine by activating nutrient sensing pathways like PPARs, helping prevent early pathology from a high-fat diet. Saturated fats stimulate obesity, hepatic steatosis, and affect the gut microbiota composition. 3. A systems genetics study of mouse strains found a genetically determined set point for obesity. Certain strains showed robust, strain-specific changes in obesity traits from a
Nanjing 2 2013 Lecture "Nutrigenomics part 2" From healthy to too much: The role of the Small Intestine for metabolic flexibility"
- 1. Lecture2 From healthy to too much The role of Small Intestine for metabolic flexibility Michael Müller Nutrition, Metabolism and Genomics Group, Division of Human Nutrition, Wageningen University
- 2. The intestine as a gatekeeper Adipokines: Adiponectin Leptin Resistin ANGPTL4 TNF etc GI hormones: Insulin GIP GLP1 PYY Ghrelin ANGPTL4 FGF15/19 Food intake LPL LPL LPL SFA Glucose Fructose FGF21 ANGPTL4 Satiety
- 3. The Intestine • The small intestine in an adult human = 5 meters with a normal range of 3 - 7 meters (it can measure around 50% longer at autopsy because of loss of smooth muscle tone after death). • It is approximately 2.5-3 cm in diameter. Although the small intestine is much longer than the large intestine (typically around 3 times longer), it gets its name from its comparatively smaller diameter. • Although as a simple tube the length and diameter of the small intestine would have a surface area of only about 0.5m2, the surface complexity of the inner lining of the small intestine increase its surface area by a factor of 500 to approximately 200m2, or roughly the size of a tennis court. • The small intestine is divided into three structural parts: • Duodenum 26 cm in length • Jejunum 2.5 m • Ileum 3.5 m
- 4. Length of the intestine Small intestines: • Human 6-7 m • Mouse 35 cm • Pig 15 m Large intestines: • Human 1.5 m • Mouse 14 cm • Pig 5 m
- 5. Intestine functions related to nutrition • Uptake of nutrients • Chylomicron formation • Nutrient & food bioactives metabolism • Barrier function – Mucosal immunity – Host-microbe interaction • Gland: Satiety signaling (incretines, enterokines)
- 6. Gut: Diseases - Disorders • Gastroenteritis is inflammation of the intestines. It is the most common disease of the intestines. • Colitis is an inflammation of the large intestine. • Celiac disease is a common form of malabsorption, affecting up to 1% of people of northern European descent. Allergy to gluten proteins, found in wheat, barley and rye, causes villous atrophy in the small intestine. Life-long dietary avoidance of these foodstuffs in a gluten-free diet is the only treatment. • Crohn's disease and ulcerative colitis are examples of inflammatory bowel disease (IBD). While Crohn's can affect the entire gastrointestinal tract, ulcerative colitis is limited to the large intestine.
- 7. Simplified view on intestinal nutrient metabolism Thiele lab 2013
- 8. The small intestine as primary organ is response to nutrients & food components
- 9. Gene regulation by dietary lipids in the intestine
- 10. The cellular network in intestinal homeostasis (and inflammation)
- 11. The cellular network in intestinal (homeostasis and) inflammation.
- 12. The cellular network in intestinal (homeostasis) and inflammation
- 13. A major role for PPARa in intestinal fatty acid sensing Physiol Genomics. 2007 ;30(2):192-204
- 14. Intestinal PPAR target genes are largely regulated by dietary PUFAS/MUFAs 6h after oral gavage with OA 18:1 EPA 20:5 DHA 22:6 WY14643 Genes 508 874 894 1218 Apolipoproteins & related TAG (re)-synthesis Pnliprp2 ,Pnliprp1, Mgll, Lipe,Lipa,Pla2g6, Pnpla2,Pnpla8, Daglb, Ces1,Ces3 Chylomicron assembly & secretion Ketone body synthesis Intestinal lipases & phospholipases Fat/Cd36,Slc27a2, Slc27a4,Acsl1,Acsl3, Acsl5,Fabp2,Fabp1, Scarb2,Scarb1 Gpat1, Mogat2, Dgat1,Dgat2, Gpat3,Agpat3 Mttp, Stx5a,Vti1a, Bet1,Sar1a Apob,Apoa1 ,Apoa2,Angptl4, Apoa4,Apoc2,Vldlr,Apoc3, Apoe,Apol3,Apool Acaa2,Acad10,Acad8,Acad9, Acadl,Acadm,Acads,Acadsb, Acadvl,Acot10,Acot2,Acot9, Aldh9a1,Cpt1a,Cpt2,Crat,Dci, Decr1,Hadha,Hadhb,Hibch, Slc22a5,Slc25a20,Aldh3a2, Cyp4a10,Abcd3,Acaa1a, Acaa1b,Acot3,Acot4,Acot5, Acot8,Acox1,Acox2,Crot, Decr2,Ech1,Ehhadh, Hsd17b4,Peci,Pecr, Ppara Acat1, Hmgcl,Hmgcs2 Mitochondrial, microsomal, peroxisomal fatty acid oxidation Fatty acid transport & binding P P A R α
- 15. Longitudinal distribution of genes involved in dietary lipid metabolism in wild-type mice on PPARα activation by WY14643 Fatty acid transport and binding 1 2 3 4 5 6 7 8 9 10 0 3 6 9 12 1 2 3 4 5 6 7 8 9 10 0 3 6 9 12 1 2 3 4 5 6 7 8 9 10 0 2 4 6 1 2 3 4 5 6 7 8 9 10 0 2 4 6 1 2 3 4 5 6 7 8 9 10 0 1 2 3 4 1 2 3 4 5 6 7 8 9 10 0 4 8 12 16 ACSL1 Microarray FABP2 Rel.expression ACSL3SLC27A2 ACSL5SLC27A4 Rel.expressionRel.expression Rel.expressionRel.expressionRel.expression WTControl WTWY14643 B * * * * * * * * * * * * * * * * * * * * * * ** * * * * * * * * * * * * * * * * * * * * * * * * * * TAG (re-) synthesis 1 2 3 4 5 6 7 8 9 10 0.0 0.5 1.0 1.5 2.0 2.5 3.0 1 2 3 4 5 6 7 8 9 10 0.0 0.5 1.0 1.5 2.0 2.5 3.0 1 2 3 4 5 6 7 8 9 10 0.0 0.5 1.0 1.5 2.0 2.5 3.0 Microarray Microarray MOGAT2 Rel.expression DGAT1 DGAT2 Rel.expressionRel.expression C WTControl WTWY14643 * * * * * * Chylomicron formation 1 2 3 4 5 6 7 8 9 10 0 1 2 3 4 1 2 3 4 5 6 7 8 9 10 0 4 8 12 16 1 2 3 4 5 6 7 8 9 10 0 1 2 3 4 Microarray MTTP Rel.expression BET1 FABP1 Rel.expressionRel.expression D WTControl WTWY14643 * * * * * * * * * * * * * * * * * * * * * * * * * 1 2 3 4 5 6 7 8 9 10 0 1 2 3 4 5 Intestinal lipases and phospholipases 1 2 3 4 5 6 7 8 9 10 0 1 2 3 1 2 3 4 5 6 7 8 9 10 0 1 2 3 1 2 3 4 5 6 7 8 9 10 0 1 2 3 1 2 3 4 5 6 7 8 9 10 0 3 6 9 12 1 2 3 4 5 6 7 8 9 10 0 1 2 3 4 Microarray PNPLA2MGLL Rel.expression PLA2G6LIPA PNPLA8PLCB1 Rel.expressionRel.expression Rel.expressionRel.expressionRel.expression WTControl WTWY14643 A * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * *
- 16. 1. Esophagus 2. Stomach 3. Duodenum 4. Jejunum 5, Ileum 6. Cecum 7. Ascending colon 8. Descending colon 9. Rectum
- 17. Background • Obesity and insulin resistance are two major risk factors underlying the metabolic syndrome. The development of these metabolic disorders is frequently studied, but mainly in liver, skeletal muscle, and adipose tissue. • To gain more insight in the role of the small intestine in development of obesity and insulin resistance, dietary fat-induced differential gene expression was determined along the longitudinal axis of small intestines of C57BL/6J mice.
- 18. Methods • Male C57BL/6J mice were fed a low-fat or a high-fat diet that mimicked the fatty acid composition of a Western-style human diet. • After 2, 4 and 8 weeks of diet intervention small intestines were isolated and divided in three equal parts. • Differential gene expression was determined in mucosal scrapings using Mouse genome 430 2.0 arrays.
- 19. Low-fat (LF) diet High-fat (HF) diet gm% kcal% gm% kcal% Protein 19 20 24 20 Carbohydrate 67 70 41 35 Fat 4 10 24 45 Ingredients gm kcal gm kcal Casein, lactic 200 800 200 800 L-Cystine 3 12 3 12 Corn Starch 427.2 1709 72.8 291 Maltodextrin 100 400 100 400 Sucrose 172.8 691 172.8 691 Cellulose, BW200 50 0 50 0 Soybean Oil 25 225 25 225 Palm oil 20 180 177.5 1598 Mineral Mix S10026 10 0 10 0 DiCalcium Phosphate 13 0 13 0 Calcium Carbonate 5.5 0 5.5 0 Potassium Citrate, 1 H2O 16.5 0 16.5 0 Vitamin Mix V10001 10 40 10 40 Choline Bitartrate 2 0 2 0 Total 1055 4057 858.15 4057 Diets used in this study
- 20. Body weight and oral glucose tolerance test • (A) Body weight gain of C57BL/6J mice during a low-fat or high-fat diet intervention of 8 weeks. • (B) An oral glucose tolerance test was performed after 7 weeks of diet intervention. After an oral gavage of 100 mg glucose, blood glucose levels were monitored for 150 minutes. • The changes in blood glucose levels (upper figure) and the area under he curve were calculated (lower figure). In (A) and (B), data are means ± SE. * p < 0.05. • LF = low-fat diet, HF = high-fat diet
- 21. Dietary fat-induced differential gene expression along the longitudinal axis of the small intestine
- 22. Heat map diagrams of differentially expressed genes on a high-fat diet
- 23. Heat map diagrams of differentially expressed genes on a high-fat diet
- 24. Heat map diagrams of differentially expressed genes on a high-fat diet
- 25. Relative mRNA expression of nuclear receptors along the longitudinal axis of the small intestine under basal conditions
- 26. Results • The high-fat diet significantly increased body weight and decreased oral glucose tolerance, indicating insulin resistance. • Microarray analysis showed that dietary fat had the most pronounced effect on differential gene expression in the middle part of the small intestine. • By overrepresentation analysis we found that the most modulated biological processes on a high-fat diet were related to lipid metabolism, cell cycle and inflammation. • Our results further indicated that the nuclear receptors Ppars, Lxrs and Fxr play an important regulatory role in the response of the small intestine to the high-fat diet. • A secretome analysis revealed differential gene expression of secreted proteins, such as Il18, Fgf15, Mif, Igfbp3 and Angptl4. • Finally, we linked the fat-induced molecular changes in the small intestine to development of obesity and insulin resistance.
- 28. Conclusion • During dietary fat-induced development of obesity and insulin resistance, we found substantial changes in gene expression in the small intestine, indicating modulations of biological processes, especially related to lipid metabolism. • Moreover, we found differential expression of potential signaling molecules that can provoke systemic effects in peripheral organs by influencing their metabolic homeostasis. Many of these fat-modulated genes could be linked to obesity and/or insulin resistance. • Together, our data provided various leads for a causal role of the small intestine in the etiology of obesity and/or insulin resistance.
- 29. Immune mechanisms that limit bacteria– epithelial cell interactions
- 30. Microbial community composition at different body locations in a healthy human
- 31. A summary of the functional changes seen in various regions of the gut for different microbiome colonizations
- 32. Assembly and stability of the gut microbiota, and environmental factors affecting the gut microbiome during life
- 33. Major metabolites involved in host-microbe communication, originating from synthesis from microbial conversion of nutrients and host metabolites in the gut lumen
- 36. Factors shaping intestinal microbial composition and effects of dysbiosis on host health
- 37. Microbiota-induced maturation of the gastrointestinal tract
- 38. Challenges for mouse studies: Several genera are significantly different in abundance between mouse strains
- 39. Microbial impact on host physiology
- 41. Saturated fat affects obesity & liver TGs Correlation between body weight gain and epididymal fat pads
- 42. HF-PO diet reduced microbial diversity and increased the Firmicutes-to-Bacteroidetes ratio
- 43. Lipid metabolism-related gene expression in the distal small intestine after 8 weeks of diet intervention
- 44. Conclusions • Saturated fat stimulates obesity and hepatic steatosis and affects gut microbiota composition by an enhanced overflow of dietary fat to the distal intestine. • Unsaturated fat is more effectively taken up by the small intestine, likely by more efficiently activating nutrient sensing systems (PPARs) and thereby contributing to the prevention the development of early pathology (e.g. NASH).
- 45. • Obesity is a highly heritable disease driven by complex interactions between genetic and environmental factors. Human genome-wide association studies (GWAS) have identified a number of loci contributing to obesity; however, a major limitation of these studies is the inability to assess environmental interactions common to obesity. Using a systems genetics approach, we measured obesity traits, global gene expression, and gut microbiota composition in response to a high-fat/high-sucrose (HF/HS) diet of more than 100 inbred strains of mice. Here we show that HF/HS feeding promotes robust, strain-specific changes in obesity that are not accounted for by food intake and provide evidence for a genetically determined set point for obesity. GWAS analysis identified 11 genome-wide significant loci associated with obesity traits, several of which overlap with loci identified in human studies. We also show strong relationships between genotype and gut microbiota plasticity during HF/HS feeding and identify gut microbial phylotypes associated with obesity.
- 46. Highlights of the study ► Detailed analysis of diet-induced obesity in more than 100 inbred mouse strains ► Identification of 11 genetic loci associated with obesity and dietary responsiveness ► Significant overlap between mouse loci with human GWAS loci for obesity ► Strain-specific shifts in gut microbiota composition in response to dietary intervention
- 47. Natural Variation in Gene-by-Diet Interactions
- 50. Robust Shifts in Gut Microbiota Composition after HF/HS Feeding
- 51. Plasticity of Gut Microbiota Is Strain Specific
- 52. Conclusions • The intestine plays a crucial role as barrier & gatekeeper • Responsible for the efficient uptake of nutrients & food bioactives • Symbiosis with large sets of microbiota that have a significant impact on the health status of the host (human) • Interaction between host (phenotype/genotype), microbiota, foods/diet, environmental factors • Likely plays a key role in development of many recently emerging diseases. Link to immunity & inflammation • Careful with animal models (strong genotype effects)!
- 53. The effects of heme on the colonic mucosa and the microbiota in mice INCON, 1-4 Oct 2012, San Jose
- 54. Heme as a nutritional stressor Nutritional stressor: heme • Heme is the color pigment of red meat • Known that heme and/or heme-metabolite(s): - are luminal irritants in the colon - catalyse the production of reactive oxygen species (ROS) - are cytotoxic for epithelial cells and induces necrosis - increase proliferation of epithelial cells hyperplasia of the epithelium de Vogel et al., 2008, Carcinogenesis 29:398
- 55. Aim of this study • To identify molecules that signal from the surface to the proliferative colonic crypt to increase cell proliferation upon stress induced by heme Exfoliation or necrotic cell death Cell division Apoptosis or differentiation Exfoliation or necrotic cell death Cell division Apoptosis or differentiation
- 56. -7 0 7 14 days chow diet n=16 HF heme diet n=8 HF control diet n=8 Collection of: Colon -scrapings for gene expression -part of the tissue for IHC and LCM Colonic contents Feces Study 1. Effects of heme on the colonic mucosa High-risk western purified diet male C57Bl6J mice (8 per group) high fat 40% *heme 0.5 μmol/g
- 57. Dietary heme increases fecal water cytotoxicity 0 20 40 60 80 100 120 control heme * %celllysis
- 58. control heme 200x Stainings with an antibody against Ki67, showing more proliferating (brown) cells on the heme diet, and deeper crypts. 200x Dietary heme increases cell proliferation
- 59. Effect of heme on gene expression • Around 3,700 genes differentially expressed (q<0.01 and signal intensity > 20), determined with microarray • Processes in which these genes were involved: • Can we determine more precisely where these changes take place, in surface cells or in crypt cells?
- 60. Laser Capture Microdissection Technology (LCM) LCM was used to isolate colonic surface and crypt cells LCM system and procedure
- 61. LCM separates surface and crypt gene expression Hmox1 0 5 10 15 20 25 30 35 40 45 LCM total surface crypt foldchange Ki67 0 2 4 6 8 10 12 14 LCM total surface crypt control heme foldchange heme control heme control Heme oxygenase is highly induced in the surface Ki67 is highly induced in the crypt * *
- 62. Conclusions from LCM • Heme-related genes and stress-related genes upregulated specifically at the surface epithelium (Hmox1, Creb3l3) • Cell proliferation upregulated in the crypt (Ki67 and cyclins) • Apoptosis is downregulated (Birc5, Xiap, Casp3) • Heme exerts its effect on the surface, and does not directly act on the proliferating cells in the crypt • Therefore signaling molecules from surface to crypt have to start the proliferation
- 63. Downregulated mitogenic surface-to-crypt signals are also decreased at protein level Gene level Protein level Other signals with a similar pattern: Bmp2, Wif1, Ihh
- 64. Gene level Protein level Upregulated mitogenic surface-to-crypt signals are not translated into protein • Amphiregulin (Areg) and Epiregulin (Ereg): epithelial growth factors which play a role in human carcinogenesis
- 65. Protein Translation is controlled by 4E-BP1 • Protein translation is inhibited by 4E-BP1, which is surface specifically upregulated by heme.
- 66. Conclusions • Signaling from the injured surface epithelium occurs via downregulation of feedback inhibitors of proliferation, e.g. Wif1, Ihh, Bmp2 and IL-15 • Upregulated molecules are not translated into proteins, because of the surface specific upregulation of the translation inhibitor 4E-BP1. • If validated in humans, Wif1, Ihh, Bmp2 and IL-15 may be used as early biomarkers of diet- modulated colon cancer risk. IJssennagger et al., Gut (2012)
- 67. Background: • Colon densely populated by bacteria • Cytotox is caused by a covalently modified heme metabolite Aim: • To determine the changes in microbiota upon heme consumption • Do microbiota play a role in the heme induced surface to crypt signaling? Results: • Heme induced hyperproliferation Study 2. Effects of heme on the microbiota
- 68. Heme changed the composition of microbiota 0% 20% 40% 60% 80% 100% Control Heme Relativecontribution TM7 Firmicutes Cyanobacteria Actinobacteria Verrucomicrobia Fusobacteria Fibrobacteres Deferribacteres Proteobacteria Bacteroidetes Verrucomicrobia, proteobacteria and bacteroidetes were more abundant on the heme diet Ratio Control Heme Gram-negative to Gram- positive bacteria 0.72 ± 0.09 2.16 ± 0.27 * Bacteroidetes to Firmicutes 0.63 ± 0.09 1.87 ± 0.30* Heme increased the ratio of gram-negative to gram- positive bacteria.
- 69. • Selective susceptibility of Gram-positives for heme fecal water • Allowed expansion of Gram-negative bacteria → ↑ LPS exposure • No functional change in the sensing of the bacteria by the mucosa, as changes in inflammation pathways and Toll- like receptor signaling were not detected. Conclusion: • Changes in microbiota does not cause the observed hyperproliferation and hyperplasia via inflammation pathways Heme alters microbiota and mucosa, but without functional changes in host-microbe cross-talk
- 70. Study 3. Role of microbiota in heme-induced hyperproliferation Background: • Heme diet changes microbiota Aim: • Investigate whether there is a causal role for microbiota in the heme induced cytotoxicity and hyperproliferation.
- 71. Design of antibiotics (Abx) experiment Broad spectrum antibiotics Ampicillin:1 g/L Neomycin:1 g/L Metronidazole: 0.5 g/L Collection of colon contents and mucosa -7 0 7 14 days chow diet n=36 HF heme diet HF control diet N=9 N=9 N=9 N=9 Control + Abx Control Heme Heme + Abx High-risk western purified diet male C57Bl6J mice (9 per group) high fat 40% *heme 0.5 μmol/g
- 72. Results: • heme induced cytotoxicity and ROS • Abx changes bile acid composition from unconjugated to conjugated BA • Heme increases proliferation, but not when Abx given simultaneously No hyperproliferation on heme + Abx
- 73. No induction of oncogenes on heme + Abx
- 74. • Several cytotoxicity sensors not induced by heme + Abx Heme induced cytotox not seen by mucosa on Abx
- 75. • Still luminal cytotoxicity but not sensed by the mucosa. • Thus an increased mucus barrier with Abx. Conclusion: • Microbiota facilitate the heme induced hyperproliferation by breaking the mucus barrier Possible Mechanism: • Several mucin degrading bacteria (e.g. Akkermansia Muciniphila) decreased by Abx, and this decrease might contribute to the increased mucus barrier. Microbiota facilitate heme induced hyperproliferation