Diet, genetics and microbes in the global epidemic of modern lifestyle diseases

Transcription

1 Diet, genetics and microbes in the global epidemic of modern lifestyle diseases Charles Perkins Centre Andrew Holmes School of Life and Environmental Sciences

2 Lifestyle diseases are multifactorial: This is a challenge and presents opportunities The effects of diet are not easily predictable without considering interaction with other factors The physiological response to food ingestion varies between individuals. The impact of microbes on physiology varies between individuals. The response of the microbial community to diet pressure varies between individuals Understanding how food and microbes interact with our physiology can lead to better public health diet guidelines and individualised interventions. 2

3 What drives disease development in an individual? Interventions Industrialization has changed our relationship with Microbes: Diet and Immune history What drives disease incidence in a human population? Guidelines

4 Explaining variation in systems: Which dimensions impact the system? How many calories? What types of food? Genetically predisposed physiology? Microbe factors? Which of these factors is most important? Can we predict outcomes best by using diet data, genetic data, microbiome data etc? 4

5 Explaining variation in systems: Predictive power of diet in isolation is modest Diet Microbes Genes Blood glucose after meal Independent effects have limited predictive power. so is the question flawed? Total calories eaten is important, but has limited explanatory power Zeevi et al. (2015) Cell 163,

6 People vary in relationship Figure between 2 food eaten and glycemic response Standard meals show wide variation in glycemic response across a population. (Bread ranged from ca 0 to >80) You can predict how an individual will respond to a standard meal. (Individuals with very different responses to bread were consistent) Cell , DOI: ( /j.cell ) Zeevi et al. (2015) Cell 163,

7 Microbes change relation between calories eaten and adiposity Germ free C57Bl/6J mice Normally colonized Diabesity is impacted by diet x microbiome x genome interaction Fleissner et al. (2010) C3H mice Food eaten (g/day) GF mice eat significantly more But conventional mice put on more weight Body Fat (%) ** Diet 2 (low fat) Diet 3 (high fat) Backhed et al. (2004)

8 Explaining variation in systems: Predictive power of microbiome in isolation is modest Evidence from cross sectional studies The major phyla, Bacteroidetes and Firmicutes show different distribution in obese vs. lean Successful weight loss diets shift both microbiome and obesity Human Microbiome Project Fig 2. Finucane et al. (2014) PLoS ONE e84689 No Bact:Firm associatio n with obesity at population level Ley et al. (2006) Nature 444:1022 8

9 Explaining variation in systems: The importance of interactions Microbes Which of these factors, or their interactions, is most important? 9

10 Predictive models need to measure diet AND microbes AND physiology Zeevi et al. (2015) Cell 163,

11 Gene x Environment interactions influencing performance of our symbiosis are affected by diet Food intake changes with availability and eating habits Co-evolved (host and microbe genes) Microbiome composition and activity changes Our inherited genes + tissue pathophysiology + adaptive & epigenetic state + nutrient environment + microbiome collectively define our body state Health Dysbiosis Barrier function changes with enterocyte health modifies signal interface Expression patterns of pathway components change modifies signal response Ha et al WJ Gastroenterol. (2014)

12 Why is there an obesity epidemic and why are there geographic differences?

13 Industrialization of Food Supply Chain: Results in change in what substrates we supply to microbes (especially in colon)

14 Different nutrients are required in different amounts and we can get them from different sources. Foods vary in their nutrient content: Highly processed foods may effectively contain only one nutrient of one macronutrient class Even whole (unprocessed) foods vary in nutrient complexity and quality: May be fat-rich; protein-rich or carbohydrate-rich Foods also vary in their structural complexity: Foods vary in digestibility as well as nutrient quality. Where, when and how nutrients are absorbed varies. Different intake rates of different types of food impacts our health

15 There is tremendous variation at individual level despite common environmental factors how does this happen? Stochastic factors impact how the microbiome responds to change in either diet or host state: What you get varies Example of microbe signature in diet-induced obesity There are common underlying mechanisms that drive microbial responses to change in either diet or host state: The selective driver is consistent. Example of response guilds observed via nutritional geometry

16 Type of Fat matters for health outcome. Poor health associated with increase in Bilophila Saturated n-6 unsaturated n-3 unsaturated Comparing 3 High Fat diets with standard diet: Very bad Mildly worse Improved Lam et al (2015) Obesity 23:1429

17 Lam et al (2015) Obesity 23:1429 Type of Fat matters for health outcome. Type of microbe involved in outcome varies stochastically Comparing 6 replicates of High Sat d Fat diet with standard diet: Disease reproducible but Microbiome varied

18 Geometric analysis of the impact of density and distribution. 30 supplied foods 100 s of ingestion patterns 10 versions of Nutrient distribution (defined sources of Prot, Carb or Fat) ca 900 mice fed ad libitum 3 Cohorts sampled at 15 months 3 Energy densities (3 rates of cellulose dilution) Intake Pattern monitored by recording food consumption Solon-Biet et al. Cell Metabolism (2014)

19 Different dimensions of diet drive different responses Lifespan Blood pressure Dysbiosis? Testes (mg) Immune markers (spleen CD4: CD8) Body fat % Uterus (mg) Glucose tolerance test

20 Dimensions of diet-microbiome interaction. Intestinal environment: The major drivers of change in microbiome are Protein and carbohydrate intake Bacteroidetes Carb intake Fat intake Protein intake Protein intake Simpsons diversity index Firmicutes Carb intake Protein intake Fat intake Protein intake Carb intake Protein intake Fat intake Fat Protein intake Although high fat and energy dense foods are associated with big changes, this reflects different responses to P+C intake by major groups

21 A view of the ecological niche in nutrient intake dimensions: Protein and Carbohydrate intake: select for different microbial strategies ERYSIPELOTRICHI (Allobaculum) FIRMICUTES (Lachnospiraceae) Genomes enriched for broad utilization of amino acids. Distinct carbohydrate utilization. VERRUCOMICROBIA (Akkermansia) Carb intake Fat intake Protein intake Protein intake Genomes enriched for utilization of mucin-derived nutrients. Biosynthesis of amino acids enriched. Distinct carb utilization.

22 Nutritional cooperation underpins many diet strategies. Diet-fed microbes compete with us and increase risk of dysbiosis. Huge complexity of diet dimensions can be simplified: 2 Response guilds Secretion-fed microbes are cooperating with us. Endogenous N users favoured Carbohydrate Mouse Low Nutrient intake (3-restrict, 4-intermittent) Secreted N (mucin) N N N Host & microbes co-operate higher diversity beneficial host-microbe association N N Protein Diet impact on Nitrogen source availability in gut drives dichotomy in microbial strategy N Mouse High Nutrient intake (1-Simple Carbs, 2-Protein excess) 2 N N N Diet-derived N (protein) N Dietary N users favoured Host & microbes independent lower diversity poor host-microbe association N Holmes et al. (2016) Cell Metabolism 22

23 Meta-analysis of ethnogeographic variation in nutrient environment, genetics, and microbiome.

24 Ethnic Balinese are intermediate in obesity epidemic timeline, lifestyle & microbiome Asha Febinia

25 Everything is everywhere but the environment selects But the environment is more complex than where you are Multiple factors drive community structure Obesity is overrepresented in the Prevotella Enterotype. Driven by consequences of metabolic network? There are two types of Balinese microbiome Enterotypes Driven by biological network interactions? Asha Febinia

26 Recognize microbes as part of us: This is a challenge and presents opportunities Understanding how food and microbes interact can lead to better diet advice. Every person will respond a little differently to diet: Microbe differences are part of this. Some diet strategies are likely to be more generalizable than others caloric intake pattern; protein:carbohydrate ratio; carbohydrate digestibility. We are approaching an era of personalized diet interventions. Incorporating diet, microbial and metabolic information into diagnostic tests may help diet design for individuals. 26

27 The microbiome node of the Charles Perkins Centre at University of Sydney Gut Microbiology group Andrew Holmes Eline Klaassens Yi Vee Chew Chau Le Connie Ha Feyza Colakoglu Asha Febinia Mark Read Charles Perkins Centre Steve Simpson (CPC) David Raubenheimer David James Len Storlien Ian Caterson Yan Lam Nick Fuller David LeCouteur Aisling McMahon Sam Solon-Biet Laurence Macia Indonesia Herawati Sudoyo Safarina Malik Ketut Suastika The Udayana team Funding NHMRC ARC AusAid University of Sydney Australian Microscopy & Microanalysis Facility

28 What are Bacteria (cell structure) & what do they do? Nutrients organic and inorganic Internal structures: Chromosome, Ribosome, storage bodies. DNA, RNA, Proteins, Lipids, Polysaccharides. Growth and metabolism. Secreted and excreted factors Metabolites: CO 2, CH 4, H 2 S, NH 3, fatty acids, vitamins Effectors: Enzymes, Toxins, Signals METABOLITES Surface structures: Cell wall, pili, flagella, capsule. Proteins, Lipids, Polysaccharides. Protection, motility, adhesion. MAMPS

29 MAMPS Lipid A Peptidoglycan Flagellin Cell Surface Polysaccharide Bacteroidetes Proteobacteria Firmicutes yes low +/- varies yes low +/- varies no high +/- varies Metabolism Monosaccharide utilization Polysaccharide utilization Fermentation end-product Bacteroidetes Proteobacteria Firmicutes varies common SCFA varies rare SCFA varies common SCFA

30 How does the environment select? Sources of C, N, P, S or energy as limiting points Substrate Proteins Fats Carbohydrates Chemical accessibility (e.g. glycosidic linkage) Spatial accessibility (e.g. reaches colon) Nutritional value Basic building blocks (CNS, CP or C) Prefab building blocks (amino acids, vitamins) Bacterial fitness depends on what we eat and Our intestinal responses Electron acceptor (e.g. O 2 ) Intracellular (Fermentative) Extracellular (Respiratory) Innate antimicrobials Stress Adaptive Ig mediated Ha et al. WJ Gastroenterol (2014)

31 Bacterial activity under high protein and acrbohydrate intake differs from that under low intake Protein intake Drives immune state spleen CD4: CD8 cells Dietary only Dietary only Host cooperation Host cooperation Protein and Carbohydrate intake level fundamentally shifts ecological strategy of gut bacteria and their interaction with our immune system At the system level N availability is dictated by protein intake