Preventative Health National Research FlagshipProtective Foods Stream, CRC-3 Project

Gut Bacterial Population Profiles andRelationships To Diet and Health

Dr. Michael ConlonCSIRO Human Nutrition

Adelaide, Australia

Broad Focus

Human studies examining the impact of dietary ResistantStarch (RS) and Fibre on changes in the population dynamicsof colonic bacteria and short chain fatty acid (SCFA)production

• 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)

Diet and Colorectal Cancer

FoodFoodShort-chain fatty acidsShort-chain fatty acids

ButyrateButyrate

Bacterial

Proliferation

Prebiosis

StarchStarch

pHpH

Protein Protein catabolitesProtein catabolites

Small IntestineSmall Intestine Large IntestineLarge Intestine

Interaction of Complex SystemsInfluencing Bowel Health

Food-Complex cocktail of substances-Combinatorial effects of components on physiology and biochemistry

Gut Microflora-The majority of bacteria in thecolon are poorly characterised due to lack of culturability, sheer numbersand variety.-The colonic bacteria carry out a massiverange of reactions relating to metabolismof dietary and host components.

Host-Individuals have distinctgenotypes and phenotypesand may respond differentlyto diet and harbour differentbacteria.

BowelHealth

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 tohelp maintain a normal colonic phenotype.

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 enzymicactivity, reaching the large bowel where they provide faecal bulking and promotelaxation.

Starch is found primarily as amylose or amylopectin.

Starch is found in food crops such as cereals, pulses and tubers and usuallyfound 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 highlyfermentable substrate

High amylose forms of grain have been developed by CSIRO and others that increasethe likelihood of starch reaching the large bowel

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 objectivesDevelop foods which reduce colorectal cancer riskDevelop technology for the analysis of complex microbial populations (markers of disease or health risk)

CRC-3 Objectives

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.

Human clinical trials

Colonic Microbial Populations and SCFAExperimental Program

Pilot Study:Total SCFA output over 48 hours for 12 weeks

week of study

1 2 3 4 5 6 7 8 9 10 11 12

SC

FA

mM

0

10

20

30

40

50

60

PH02. PH04. PH07. PH08.

Molecular analysis of microbial populations

• DNA extraction

• 16s rDNA PCR amplification

• Polyacrylamide gradient gel

• Silver stain/SYBR Gold

• Density and binary matrix analysis

Denaturing Gradient Gel Electrophoresis

Description of the structure of bacterial

communities without the need to

culture bacteria.

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

nMDS of DGGE

DGGE “fingerprints” were analysed for similarity of patterns

(nMDS:non-metric multi-dimensional scaling)

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 stablePopulations are distinct to individualsSignificant novel diversity of bacteriaPotential for butyrate production in all individuals

R2 = 0.0055

0

10

20

30

40

50

60

0 2000 4000 6000 8000 10000 12000

Eub abundanceB

uty

rate

mM

/L

R2 = 0.0256

0

10

20

30

40

50

60

0 1000 2000 3000 4000 5000 6000 7000 8000

Bact abundance

Bu

tyra

te m

M/L

Total bacteria (excl. Archaea)

No association*

Bacteroides(polysaccharide breakdown & nitrogen cycling)

No association

Faecal Butyrate Concentration vs Microbial Abundance (PCR)

R2 = 0.1945

0

10

20

30

40

50

60

10 510 1010 1510 2010 2510 3010

XIVa AbundanceB

uty

rate

mM

/L

R2 = 0.2721

0

5

10

15

20

25

30

35

40

45

50

0 0.5 1 1.5 2 2.5 3 3.5 4

Methanogen number

Bu

tyra

te m

M/L

Clostridial Cluster XIVa(major Butyrate-producing bacteria cluster)

Positive association

Methanogens*(acetate consumers)

Negative association(CLI)

Faecal butyrate concentration vs microbial abundance

Major Trial Diets

Diet 1 Diet 2High Fibre High Fibre + Resistant starchBran plus 50g Barleyplus 30gCarrots 50g 3 bean mix 50gCouscous 50g Freekah 50gBran 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 2 Normal diet Diet 1

Faecal Butyrate variation

CRC3 Faecal Butyrate concentrations and diet

0

5

10

15

20

25

30

35

40

N N D1 D1 N D2 D2

Diet Phase

But

yrat

e m

mol

/L

PH211

PH220

PH235

PH253

PH255

PH264

PH218

Preliminary SCFA data

N= 46>1500 SCFA measures

Phase

Preliminary SCFA Diet order

concentration data Significant difference Normal Diet v High Fibre xNormal diet v Resistant Starch Diet √

• Acetate +12% • Butyrate +23%

GenderSCFA concentrations significantly higher in males than in females

pHHigh Fibre diet marginally higher (+0.07)Resistant Starch diet significantly lower (-0.14)

F prau related

Ruminococcus bromeii related

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 normaldiet at the beginning and end of the study

-Resilience of the bacterial population-Population changes seem rapid given changes during theintervening period

Loss of bands during high fibre only consumption

Biggest difference in profiles between the high fibre and high fibreplus high RS diets

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 starchhydrolysis?)-5 are related to Mollicutes-1 each belong to Bacteroides and Lactobacilli

A large proportion of bacteria potentially involved in RS fermentationand butyrate production (and colonic health?) are poorly characterised

nMDS plot of Phase I

High Fibre

High Fibre plus Resistant Starch

Study Messages

Human individuals have a distinct gut microflora

Butyrate concentrations vary considerably between individualsbut 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-producersincrease as a percentage of the total population in response todietary resistant starch

Dietary RS appears to be protective in the large bowel in waysthat include:

- maintenance of the mucus layer integrity andprotection of underlying tissues- promotion of bacterial population dynamicsthat may select against bacteria causing disease

Individuals have a distinct gut bacteria profile that may result in eachindividual having a different risk profile for disease and a different capacityto utilise dietary components.

A greater understanding of the complex interactions between diet, gut bacteria and host tissues is likely to lead tostrategies to improve health

Technologies that facilitate this (eg. gene microarrays andchips, as well as proteomics) by analysing large parcelsof information and then extracting trends are currently

being examined

Technologies BeingImplemented for Enumerationand Identification of Faecal Bacteria

Conventional Microbiology (culturing bacteria and counting colonies)

PCR and DGGE

Fluorescence In Situ Hybridisation (FISH) and an automated microscopemethod 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 ChrisMcSweeney and others at LI)

Microbiome chips and proteomics are also being discussed

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

Enumeration of Faecal Bacteriaby FISH

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

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

Detected F. prausnitzii bacteria after applying strict size-shape-morphology-brightness criteria.

Chris McSweeney Stuart DenmanCSIRO Livestock Industries

Methanogens(CH4)

Acetogens(acetate)

Sulfate - reducers(H2S)

SO4

Saccharolytic flora

Hydrogenotrophic flora

Polysaccharides

Fibrolytic flora

Cross-feeding

Intermediate metabolites of fermentation

Acetate Propionate Butyrate CO2 H2

Fibrolytic flora

Fragments

H2

tranfer

Development of a microbial community and functional gene microarray for the colon

CO2

CHO-MFR

CHO-H4MPT

CH≡H4MPT

CH2=H4MPT

CH3-H4MPT

CH3-S-CoM

CH4

H4MPT

HS-CoM + HS-CoB

CoM-S-S-CoB

H4MPT

MFR

H2

H2

H2

H2

MFR

CO2

CHO-MFR

CHO-H4MPT

CH≡H4MPT

CH2=H4MPT

CH3-H4MPT

CH3-S-CoM

CH4

H4MPT

HS-CoM + HS-CoB

CoM-S-S-CoB

H4MPT

MFR

H2H2

H2H2

H2H2

H2H2

MFR

A functional array to monitor key enzymatic pathways

Sulfate reduction Methanogenesis Butyrate production

CRC 3 Butyrate and Colonic Health The Team

HSN AdelaideSandi McOrist Guy AbellMichael ConlonDavid ToppingTony Bird

Caroline Cooke Thelma BridleKerry NylandRhys BushellBrad KlingnerRobb Muirhead

Michelle Vuaran Jennifer KeoghHSN Clinic

CMISIan SaundersAloke PhatakHarri KiiveriPaul JackwayVolker HilsensteinRichard Beare

CSIRO P-HealthTrevor LockettLynne Cobiac

CLIChris McSweeneyAndre-Denis Wright