Preventative Health National Research Flagship Protective Foods Stream, CRC-3 Project

1. Preventative Health National Research Flagship Protective Foods Stream, CRC-3 Project Gut Bacterial Population Profiles and Relationships To Diet and Health Dr. Michael Conlon CSIRO Human Nutrition Adelaide, Australia

2. Broad Focus Human studies examining the impact of dietary Resistant Starch (RS) and Fibre on changes in the population dynamics of colonic bacteria and short chain fatty acid (SCFA) production

3. Diet and Colorectal Cancer • Based on recent human epidemiological studies red meat and processed meat intake is associated with colorectal cancer risk whereas fibre intake reduces risk • 500,000 people, followed over 4.8 years • Positive association between colorectal cancer incidents and red and processed meat (but not poultry) • Fibre intake was protective(Norat et al. 2005) • 150,000 mature adults, followed over 20 years • Prolonged high intakes of red or processed meat were associated with elevated risk of colorectal cancer (Chao et al. 2005) • 60,000 Swedish women, followed over 13.9 years • Positive association between red meat consumption and development of colon cancer (Larsson et al. 2005)

4. Protein Protein catabolites Food Bacterial Proliferation Starch Short-chain fatty acids Butyrate pH Prebiosis Large Intestine Small Intestine

5. Interaction of Complex Systems Influencing Bowel Health • Food • Complex cocktail • of substances • -Combinatorial effects • of components on • physiology and biochemistry Gut Microflora -The majority of bacteria in the colon are poorly characterised due to lack of culturability, sheer numbers and variety. -The colonic bacteria carry out a massive range of reactions relating to metabolism of dietary and host components. Bowel Health • Host • Individuals have distinct • genotypes and phenotypes • and may respond differently • to diet and harbour different • bacteria.

6. SCFA • SCFA (especially butyrate): • - Increased through colonic fermentation • - Reduces colonic pH (Topping et al. 1996) • - Inhibits cell proliferation (Lupton et al. 1995) • - Promotes cell differentiation and apoptosis • (Godard et al. 1999) • Butyrate is the primary fuel of cells lining the colon and appears to • help maintain a normal colonic phenotype.

7. Fibre Classified broadly as: Non-Starch Polysaccharides (NSP) (eg. Cellulose) and Resistant Starch (RS) (eg Amylose from grains) All natural polysaccharides except starch resist digestion by small intestine enzymic activity, reaching the large bowel where they provide faecal bulking and promote laxation. Starch is found primarily as amylose or amylopectin. Starch is found in food crops such as cereals, pulses and tubers and usually found in a compact granular structure. - approx 30% is amylose and a small % amylopectin RS is starch which passes through the small intestine undigested and is a highly fermentable substrate High amylose forms of grain have been developed by CSIRO and others that increase the likelihood of starch reaching the large bowel

8. CRC-3 Objectives To understand faecal butyrate concentration variability within humans with time and across human populations To understand the influences of variables such as diet, age and gender (etc) on this variability To identify individuals who have high and low faecal butyrate concentrations To type enteric bacteria against butyrate producing capacity of human colonic contents Identify the key bacteria in the colon and how they respond to diet. Long range objectives Develop foods which reduce colorectal cancer risk Develop technology for the analysis of complex microbial populations (markers of disease or health risk)

9. Colonic Microbial Populations and SCFA Experimental Program Human clinical trials Pilot trial • 8 volunteers, regular diet for 12 week study, faecal collections • Established anaerobic protocols, isolated >21 Bt producing species, power analysis for major trial, sample storage conditions, in vitro fermentation protocols, >100 bacterial sequences added to phylogenetic trees , population profiles, FISH analyses Dietary intervention • 46 volunteers • 14 week crossover dietary intervention. • 2 phases • PCR/DGGE analysis of faecal bacteria populations, SCFA analyses, in vitro fermentations, FISH analyses, potential analyses of bacteria populations by functional genes.

10. Pilot Study:TotalSCFAoutput over 48 hours for 12 weeks

11. Molecular analysis of microbial populations Denaturing Gradient Gel Electrophoresis Description of the structure of bacterial communities without the need to culture bacteria. • DNA extraction • 16s rDNA PCR amplification • Polyacrylamide gradient gel • Silver stain/SYBR Gold • Density and binary matrix analysis

12. Pilot Trial: DGGE PopulationAnalysis -High degree of population stability within each individual -Populations dominated by 18-23 different bacterial species -Populations were highly specific to each individual (P<0.001, R>0.99) DGGE community fingerprint, demonstrating the variation in the dominant bacteria present in one individual over 12 weeks

13. nMDS of DGGE DGGE “fingerprints” were analysed for similarity of patterns (nMDS:non-metric multi-dimensional scaling)

14. Bacterial Populations • Molecular analysis revealed complex populations of Clostridia Including • Significant ‘uncultivated’ clades present in the majority of individuals. • ‘Key’ clades common to most individuals. • A number of groups related to different butyrate producers in the majority of individuals Populations are stable Populations are distinct to individuals Significant novel diversity of bacteria Potential for butyrate production in all individuals

15. Faecal Butyrate Concentration vs Microbial Abundance (PCR) Total bacteria (excl. Archaea) No association* Bacteroides (polysaccharide breakdown & nitrogen cycling) No association

16. Faecal butyrate concentration vs microbial abundance Clostridial Cluster XIVa (major Butyrate-producing bacteria cluster) Positive association Methanogens* (acetate consumers) Negative association (CLI)

17. Major Trial Diets Diet 1 Diet 2 High Fibre High Fibre + Resistant starch Bran plus 50g Barleyplus 30g Carrots 50g 3 bean mix 50g Couscous 50g Freekah 50g Bran 2g Hi-Maize 20g Total Dietary Fibre ~36g/day Weeks 0 2 4 6 8 10 12 14 Group1 Normal diet Diet 1 Normal diet Diet 2 Group2 Normal diet Diet 2Normal diet Diet 1

18. FaecalButyratevariation

19. Preliminary SCFA data N= 46 >1500 SCFA measures Phase Preliminary SCFA Diet order concentration data Significant difference Normal Diet v High Fibre x Normal diet v Resistant Starch Diet √ • Acetate +12% • Butyrate +23% Gender SCFA concentrations significantly higher in males than in females pH High Fibre diet marginally higher (+0.07) Resistant Starch diet significantly lower (-0.14)

20. Ruminococcus bromeii related F prau related

21. UPGMA Analysis ofMajor Trial DGGE Similarity of DGGE banding profiles (Eub primer) analysed by UPGMA (unweighted pair group method with arithmetic mean) Bacteria population compositions very similar during the normal diet at the beginning and end of the study -Resilience of the bacterial population -Population changes seem rapid given changes during the intervening period Loss of bands during high fibre only consumption Biggest difference in profiles between the high fibre and high fibre plus high RS diets

22. Identification of Bacteria Increased in No. by RS 22 of 29 GDDE bands were found to be upregulated by high RS Sequencing of bands has revealed -22 of the bands are related to butyrate-producing Clostridia -2 very close to (appear to be) Faecalibacterium prausnitzii -2 very close to Fusobacterium/Roseburia cluster -9 related to Ruminococcus bromeii (involved in starch hydrolysis?) -5 are related to Mollicutes -1 each belong to Bacteroides and Lactobacilli A large proportion of bacteria potentially involved in RS fermentation and butyrate production (and colonic health?) are poorly characterised

23. nMDS plot of Phase I High Fibre High Fibre plus Resistant Starch

24. Study Messages Human individuals have a distinct gut microflora Butyrate concentrations vary considerably between individuals but generally appear to increase in response to RS The faecal bacterial population dynamics, but probably not type, change in response to diet The order of RS/Fibre consumption may have a significant effect on some aspects of bacterial responses We have identified large numbers of uncharacterised/poorly characterised faecal bacteria Many of the bacteria closely related to known butyrate-producers increase as a percentage of the total population in response to dietary resistant starch

25. Dietary RS appears to be protective in the large bowel in ways that include: - maintenance of the mucus layer integrity and protection of underlying tissues - promotion of bacterial population dynamics that may select against bacteria causing disease Individuals have a distinct gut bacteria profile that may result in each individual having a different risk profile for disease and a different capacity to utilise dietary components.

26. A greater understanding of the complex interactions between diet, gut bacteria and host tissues is likely to lead to strategies to improve health Technologies that facilitate this (eg. gene microarrays and chips, as well as proteomics) by analysing large parcels of information and then extracting trends are currently being examined

27. Technologies Being Implemented for Enumeration and Identification of Faecal Bacteria • Conventional Microbiology (culturing bacteria and counting colonies) • PCR and DGGE • Fluorescence In Situ Hybridisation (FISH) and an automated microscope • method being developed with Paul Jackway and Volker Hilsenstein • (CMIS) • Microarrays to detect changes in a large range of known bacteria (based • on 16s rRNA sequences) and functional genes (developed by Chris • McSweeney and others at LI) • Microbiome chips and proteomics are also being discussed

28. Enumeration of Faecal Bacteria by FISH The task is to detect and count particular species of bacteria found in human faeces A fluorescent RNA probe is hybridized to bacteria of interest in the sample Various artefacts including autofluorescence of the background and other bacteria, clumping and inhomogeneity of spatial distribution, non-specificity of probe, can make this an extremely challenging image analysis problem A state-of-the-art segmentation scheme has been developed A candidate image object must satisfy strict size, shape, and intensity criteria before being counted

29. Dilute faeces stained with a Cy3 (red) labelled rRNA probe specific for the F. prausnitzii bacterium.

30. Segmentation result. Note the segmenter is designed to delineate all bright image objects

31. Detected F. prausnitziibacteria after applying strict size-shape-morphology-brightness criteria.

32. Development of a microbial community and functional gene microarray for the colon Chris McSweeney Stuart Denman CSIRO Livestock Industries Polysaccharides Fibrolytic flora Cross-feeding Fragments Fibrolytic flora Saccharolytic flora Intermediate metabolites of fermentation H2 tranfer Acetate H2 Propionate Butyrate CO2 SO4 Hydrogenotrophic flora Methanogens (CH4) Acetogens (acetate) Sulfate - reducers (H2S)

33. A functional array to monitor key enzymatic pathways Sulfate reduction Methanogenesis Butyrate production

34. CRC 3 Butyrate and Colonic HealthThe Team HSN Adelaide Sandi McOrist Guy Abell Michael Conlon David Topping Tony Bird Caroline Cooke Thelma Bridle Kerry Nyland Rhys Bushell Brad Klingner Robb Muirhead Michelle Vuaran Jennifer Keogh HSN Clinic CSIRO P-Health Trevor Lockett Lynne Cobiac CMIS Ian Saunders Aloke Phatak Harri Kiiveri Paul Jackway Volker Hilsenstein Richard Beare CLI Chris McSweeney Andre-Denis Wright