ROWETT INSTITUTE OF NUTRITION AND HEALTH

Predicting the impact of diet on the human intestinal microbiota

Sylvia H. Duncan and Harry J. Flint

Microbiology Group, Rowett Institute of Nutrition and Health, University of Aberdeen, UK

metabolism of dietary components

immune function, inflammation

pathogenesis

modification of host secretions (mucin, bile, gut receptors..)

Systemic health

Energy supply, satiety

Diabetes

Heart disease

Autoimmune disorders

Gut function, gut disorder

Infection, irritable bowel syndrome,

colitis, colorectal cancer

barrier function energy, nutrient supply

Impact of the gut microbiota on health

Anti-oxidant Molecules

Heterocyclic Amines

N-Nitrosamines

Polyamines

Bile Acids

Indoles Anti-Inflammatory Molecules

N

N N H

2 N H 2

O H

O H

O

O H

H

H

H H

N

N N

N H 2

O O H

O H

N N

O

O H

O

O H O

O H

Phytoestrogens

O

O H

Short Chain Fatty Acids

Damaging Protective

O H

O

O

O H O H

H

O H

Microbially derived metabolites

Human gut microbiota

Factors that impact on bacterial

persistence in the colon Host factors

-Microbiota acquired at birth; aging -Host immune response

Changes in the composition of the human colonic microbiota with aging

Proteobacteria E. coli F. prausnitzii

[Duncan and Flint, Maturitas 2013]

Human gut microbiota

Factors that impact on bacterial

persistence in the colon Host factors

-Microbiota acquired at birth; aging -Host immune response

Gut environmental factors nutrient availability/diet macronutrient and micronutrient

availability pH bile gut transit (wash out) anaerobiosis

Interplay between diet and microbiota on gut health

Protection against

colorectal cancer and

colitis

Exposure to metabolites and bacteria that promote

disease

Interplay between diet and microbiota

phenols, amines, indoles, N-nitroso compounds, H2S, amines, bile acids, faecapentaenes, heme

Nutrient supply to mucosa Barrier against infection

Release of phytochemicals

Principal substrates available for utilization by intestinal microbes

[from Cummings & Macfarlane (1991)]

Resistant starch

Non-starch polysaccharides

Unabsorbed sugars

Oligosaccharides

Dietary protein

Enzymes / secretions / mucus

50 40 30 20 10 Amount [gram per day]

Of dietary & intestinal origin: range

Fermentation of dietary macronutrients in the large intestine

Absorption

Short Chain Fatty Acids + H2 + CO2 + CH4

fermentation Dietary

Polysaccharides

Acetate Propionate Butyrate

1011/ g gut contents (large intestine) Outnumber human cells in the body by 10:1 Several hundred bacterial species colonise each individual Most are oxygen sensitive, but can be cultured

Overview of the microbiology of the human large intestine

Bacterial Groups

Bacteroidetes

Clostridial cluster IV

Clostridial cluster XIVa

Other clostridial clusters

Actinobacteria

Proteobacteria

Verrucomicrobia

10 20 30 40 50

Proportion of total bacteria (%)

Range

Red bars indicate Gram –ve bacterial groups and blue bars for Gram +ve groups

Several hundred bacterial species inhabit the large intestine

Approx. 99 % of colonic bacteria belong to 4 phyla •Bacteroidetes •Firmicutes •Actinobacteria •Proteobacteria

Faecalibacterium prausnitzii

Eubacterium rectale

Colinsella aerofaciens

Clostridium clostridioforme

Bacteroides vulgatus

Anaerostipes hadrus

Ruminococcus bromii

Eubacterium hallii

Blautia wexleri

Bacteroides dorei

Roseburia faecis

Dorea longicatena

Subdoligranulum variabile

Bacteroides uniformis

Ruminococcus obeum

Bacteroides ovatus

Blautia luti

Parabacteroides distasonis

sp nov A2-166

sp nov SR1/5

Lachnospira pectinoschiza

sp nov 80/3

Dialister invisus

Roseburia inulinivorans

Ruminococcus callidus

others

25 cultured species accounted for

approximately 50% of 16S rRNA sequences

Walker AW et al ISME J (2011)

Flint HJ et al Gut Microbes (2012)

Other 50% - 295 phylotypes

(72% uncultured)

Dominant species of human colonic bacteria (26 faecal samples - 6 overweight male volunteers)

16S rRNA sequence analysis of faecal samples

6 volunteers x 4 diets x approx 250 clones per library = 5,920 clones

10 dominant phylotypes phylum % clones Faecalibacterium prausnitzii * Firmicutes (IV) 7.98% Eubacterium rectale* Firmicutes (XIVa) 4.43% Clostridium clostridioforme Firmicutes (XIVa) 3.83% Collinsella aerofaciens Actinobacteria 3.67%

Bacteroides vulgatus Bacteroidetes 3.21% Anaerostipes hadrus* # Firmicutes (XIVa) 2.25% Ruminococcus bromii Firmicutes (IV) 2.11% Eubacterium hallii* Firmicutes (XIVa) 2.00% Blautia wexleri Firmicutes (XIVa) 1.89% Bacteroides dorei Bacteroidetes 1.67% * = butyrate producers Sum 33.0%

# =new species [Allen-Vercoe, et al. 2012]

4 pyruvate

acetyl- P

3 butyryl-CoA

3 butyrate

acetate

4 lactate

4 CO2

ATP

ADP

8 [H]

4 CoA

acetyl-CoA

2 NADH2

2 NAD

2 Fd 2 FdH2

Pi CoA

6 [H]

3 CoA

3 H2O 6 [H]

2 FdH2

4 Fd

2 H2

4 acetyl-CoA

2 acetyl-CoA +

2 acetate

Butyrate formation from lactate and acetate by Eubacterium hallii and Anaerostipes spp.

[Duncan et al, 2004] 4mols lactate+2 mols acetate 3 mols butyrate+4 mols CO2

0

5

10

15

20

25

30

Controls Quiescentcolitis

Mild colitis Moderatecolitis

Severecolitis

Con

cent

ratio

n (m

M)

Lactate accumulation in stool samples of colitis patients (Vernia et al., 1988)

phylum species & strain dahlia potato

no CHO scFOS HP inulin inulin starch XOS Firmicutes F. prausnitzii A2-165

Roseburia faecis M72/1

R. intestinalis L1-82

R. inulinivorans A2-194

R. hominis A2-183

Eubacterium rectale A1-86

Eubacterium hallii L2-7 Anaerostipes caccae L1-92

Coprococcus comes A2-232

C. eutactus L2-50

Actinobacteria Bifidobacterium longum 8809

B. longum 20219

B. infantis 20088

Bacteroidetes Bacteroides vulgatus B1447

B. thetaiotaomicron 5482

' OD650 < 1.0 > 0.4

' OD650 > 1.0

[Scott et al FEMS Microbiol Ecol (2014) - maximal ODs attained in 24h; 0.5% carbohydrate]

Selectivity of prebiotics for promoting growth of human colonic anaerobes in pure culture (YCFA medium)

FOS = fructo-oligosaccharides XOS = xylo-oligosaccharides

Butyrate-producers

Impact of low carbohydrate weight loss diets-human studies

18 human male volunteers; (av. Age 37 y); (av. BMI 35 kg/m2)

low CHO M

moderate CHO

moderate CHO

low CHO

4 weeks 4 weeks 1 week

M

Amount of dietary carbohydrate in the diet

Impact of diet on microbial metabolites in obese human subjects

Carbohydrate g

NSP g

Starch g

Protein g

Fat g

High carbohydrate 400 28 187 94 123 Moderate carbohydrate 170 12 95 127 74

Low carbohydrate 23 6 3 120 126

18 male volunteers (av. Age 37 y); obese (av. BMI 35 kg/m2)

Response of the major phylogenetic groups of human gut bacteria to dietary change

[Duncan, S.H, et al., AEM]

% Eubacterial (Eub338) count in faeces

***

****

***

*

*

0

5

10

15

20

25

30

35

40

Bac303

Fprau645

Rfla729 + Rbro730

Bif164

Erec482

Prop853

Rrec584

Erec - Rrec

log 10 total

Bacterial group (probe)

% Eu

b338

or E

ub33

8 /g

HighModerateLow

*** P < 0.001 * P< 0.05

Diet Carbohydrate Total SCFA Butyrate Butyrate (g) (mM) (mM) (%) High CHO 400 114 18 16 Moderate CHO 170 74 9 12 Low CHO 23 56 4 7

-5

0

5

10

15

20

25

30

8.0 8.5 9.0 9.5 10.0 10.5

log10 Rrec

But

yr

BuKBuMBuNKregression

Relationship between faecal butyrate concentration and bacteria detectable in faeces with the Rrec584 probe in obese human subjects

Diet M – ‘normal’ (high carb);; NK – high protein, medium carb; K – high protein, low carb

Correlation 0.68 (P<0.001)

Impact of diets upon bacterial fermentation products

0.00

5.00

10.00

15.00

20.00

25.00

propionate

butyrate

valer

ate

isova

lerate

isobutyr

ate

% to

tal S

CFA

M

MC

LC

Significant increases in branch chain fatty acids on high protein diets – from amino acid breakdown (leucine, valine, isoleucine)

* p < 0.005

*

* *

* *

*

Comparison of maintenance diet with week 4 mean values for :- medium carbohydrate high protein, low carbohydrate high protein diets

Impact of high protein low carbohydrate diet

low carbohydrate

medium carbohydrate

maintenance

Increase of N-nitrosocompounds on high-protein diet:

0

500

1000 1500

2000

2500

3000

ATNC

(ug/

kg)

¾Low carbohydrate high-protein diets may increase the risk of disease → increase in genotoxic metabolites

[P<0.001]

Major fibre derived phenolics in faecal samples

2

4

6

8

10

12

Ferulic acid 3OMe4OHPPA 3,4OHPPA 3OHPPA

Maintenance Diet Low Carb. Diet 20+/-1 days Low Carb. Diet 27+/-1 days

Major fibre-associated phenolics

P < 0.05 P < 0.001

P < 0.05

Conc

entra

tion

(ug

cm-3

) (ferulic acid derivatives)

8 volunteers

[Russell et al, 2011] O

O H

O HO

O H

O O H

O H

O O H

O

O H

O O H

O

O H

O

O H

O O H

HO

O H

O O H

O

O H

O O H

hydrogenation demethylation dehydroxylation

0

10

20

30

40

50

Bact Erec Rrec2 Rrec1 Ehal Clep Fprau Rum CoAT Bifids

% o

f uni

vers

al 1

6S rR

NA g

ene

copi

es

background control inulin

Effect of inulin on the faecal microbiota of human volunteers

Cluster XIVa Cluster IV

P = 0.005

P = 0.027

INULIN

CONTROL

INULIN

CONTROL

21 DAYS 21 DAYS

Human volunteer cross-over study, 6 volunteers per group: Faeces: microbiota changes (real-time PCR)

[Ramirez-Farias et al. 2009]

Type of dietary carbohydrate

14 male volunteers with metabolic syndrome (mean age 54 years, mean BMI 39.4 kg/m2) M: maintenance diet NSP: high non-starch polysaccharide, low RS RS: high resistant starch, low NSP HPMC: high protein, moderate carbohydrate

M NSP RS HPMC 1 wk 3 wks 3 wks 3 wks

Collection of faeces

M NSP RS HPMC Mean dietary intake [g/d]: M 427 230 5 28 103 126 NSP 427 138 2 42 102 136 RS 434 275 26 13 109 127 HPMC 201 110 3 22 144 63

CHO: carbohydrate

Diet CHO starch RS NSP protein fat

Walker et al. 2011, ISME J

Resistant starch compared to non-starch polysaccharide diet

Weight maintenance Weight loss

added wheat bran

added type III resistant starch

Impact of dietary non-digestible carbohydrate

Human volunteer trial – 14 obese males

Res Starch M

Wheat bran

Wheat bran

Res Starch

3 weeks 3 weeks 1 week 3 weeks

Weight loss

Weight loss

M (n =7)

(n =7)

[+ P <0.001]

[Walker A.W. et al (2011) ISME J 5, 220-230]

Impact on the gut microbiota :-

[Walker et al. ISME J 2011]

Cluster IV Ruminococcus spp.

M NSP

WL

RS

0

10

20

30

40

50

0 10 20 30 40 50 60 70

M NSP RS HPMC

% o

f uni

vers

al 1

6S rR

NA g

ene

copi

es

11

12

17

18

19

23

24

Volunteer

0

10

20

30

40

50

60

70

80

0 10 20 30 40 50 60 70

M RS NSP HPMC 14 15 16 20 22 25 26

Volunteer

0

20

40

60

80

100

14 15 16 20 22 25 26 11 12 17 18 19 23 24 volunteer

% s

tarc

h di

gest

ibili

ty

RS diet NSP diet

Time (d) Time (d)

0%

20%

40%

60%

80%

100%

0 10 20 30 40 50

Time (h)

Volunteer 25 %

of r

esid

ual s

tarc

h

no addition

+ B. adolescentis + E. rectale

+ R. bromii

+ B. thetaiotaomicron

mean level of controls

R. bromii is a keystone species essential for extensive

RS fermentation

[Ze et al, ISME J 2012]

Ability of Ruminococcus bromii to restore resistant starch degradation

Human gut microbiota

Factors that impact on bacterial

persistence in the colon Host factors

-Microbiota acquired at birth -Host immune response

Gut environmental factors nutrient availability/diet macronutrient and micronutrient

availability pH bile gut transit (wash out) anaerobiosis

Large intestinal pH

Proximal colon lumen pH 5.2-6.5

Main site of carbohydrate fermentation

Transverse + distal colon lumen pH 6.0-7.0

Available carbohydrates slowly fermentable

Diet (fibre/starch)

GUT HEALTH/ GUT DISORDER

Microbial activity

Colonic pH

Microbial community structure

Gut transit

pH influences the composition of the colonic microbiota

pH responses of two Bacteroides spp. and two butyrate-producing Firmicutes in pure culture (Duncan SH et al Environ Microbiol 2009)

Bacteroides thetaiotaomicron Bacteroides vulgatus Eubacterium rectale Roseburia inulinivorans

continuous flow fermentor (Walker AW et al AEM 2005 Duncan SH et al Env Micro 2009)

Short chain fatty acids -

5.5Community profile (16S rRNA) -

6.5

Impact of pH on SCFA formation by the human colonic microbiota

Bacteroides E. rectale/Roseburia

0

10

20

30

40

50

60

70

0 50 100 150 200 250 300 350

Time (hours)

SCFA

Con

c. (m

M)

FormateAcetatePropionateI - ButyrateButyrateI - ValerateValerateLactateSuccinateCaproateTotal

butyrate

propionate

acetate

total

pH 5.5 pH 6.56.2

[substrate – dietary polysaccharides (mainly starch)]

Carbohydrates (hexoses)

lactate

formate/

H2 + CO

2

ACETATE

butyryl CoA

PROPIONATE

BUTYRATE

6. Butyrate producers Faecalibacterium prausnitzii Eubacterium rectale, Roseburia spp.

Eubacterium hallii, Anaerostipes spp. (Firmicutes)

3. Acetogens Blautia hydrogenotrophica Marvinbryantia formatixigenes (Firmicutes)

4. Methanogens Methanobrevibacter smithii (Archaea)

5. Sulfate reducers Desulfovibrio piger (Proteobacteria)

1. Carbohydrate fermentors widespread - Bacteroidetes,

Firmicutes, Actinobacteria

2. Propionate producers Bacteroidetes

Veillonellaceae

pyruvate

acetyl CoA

3

2

1

5 CH4 4

SO4

H2S

6

Short chain fatty acid metabolism - functional groups

succinate

[Flint HJ et al Nat Rev GH, 2012]

NSP starch protein

propionate

Modelling the impact of diet on microbial fermentation in the colon*

H2 + CO2

oligo-saccharides, sugars

lactate

butyrate

acetate

succinate

formate

CH4

B10 B9

B7

B2, B4, B5 B3, B6 B1

B5, B6 B8

PEP

pyruvate

acetyl CoA

B1-B9

B1

B1-B9

B3, B1

(*Kettle H et al, 2014 “Modelling the emergent dynamics of communities of human colonic microbiota: response to pH and peptide” -

Bacterial functional groups :- B1 = Bacteroidetes B2 = Firmicutes (eg. R. bromii) B3 = Firmicutes (eg. E. eligens) B4 = Actinobacteria B5 = Roseburia group B6 = F. prausnitzii B7 = Negativicutes B8 = E. hallii, Anaerostipes B9 = acetogens B10 = methanogens

Modelling gut metabolism – (Kettle H et al 2014)

predicted observed (Walker et al 2005)

Agreement – butyrate, acetate – excellent propionate – good succinate, formate - overestimated

Bacterial populations -

Dominance of B1 (Bacteroides) at pH 6.5 well reproduced based on experimentally determined pH profiles.

SCFA -

Conclusions Adequate dietary fibre may be critical in delivering long term health benefits

Both the amount and type of carbohydrate (Inulin, NSP, RS) in the diet can impact on the composition of the gut microbiota and microbially-produced metabolites

Carbohydrate enriched diets increased faecal concentrations of butyrate and ferulic acid derivatives compared to low carbohydrate diets Studies on isolated bacteria and consortia can provide the key information needed to model the behaviour of the system

Future challenges! Understand how diet determines microbial competition and metabolic outputs from the

gut microbial community using theoretical modelling

Understand the causes and consequences of inter-individual variation in gut microbiota composition

Microbial Ecology Harry Flint (Head of group)

Faith Chung

Xiaolei Ze

Alvaro Belenguer

Shui Ping Wang

Jenny Laverde

Alan Walker

Petra Louis

Freda Farquharson

Karen Scott

Jenny Martin

OMH, HNU Gerald Lobley

Alex Johnstone

Molecular Nutrition Wendy Russell

BioSS

Helen Kettle

Grietje Holtrop

Collaborators:

Julian Parkhill, Trevor Lawley (Sanger Institute, Cambridge, UK)

Hermie Harmsen, Gjalt Welling (U. Groningen, The Netherlands)

Mireia Lopez-Siles and Jesus Garcia Gill (U. Girona, Spain)

Jerry Wells and Oriana Rossi (U. Wageningen, The Netherlands)

George Macfarlane (U. Dundee, UK)

Annick Bernalier and Christophe Chassard (INRA, Clermont Ferrand, France)

Acknowledgements