Intestinal microbiota, diet and health. - SINU · Alimentazione Kieran Tuohy ... Intestinal microbiota, diet and health. The human gut microbiota ... .. 90% resistant to digestion

03/11/2014

Agricoltura

Migliore output con minore input Fondazione Edmund Mach

AlimentazioneKieran Tuohy

Fondazione Edmund Mach, TN

Research & Innovation Centre

Intestinal microbiota, diet and health.

The human gut microbiota

Interactions with;

•Diet

•Drugs

•Immune system

•Gut physiology

•Bile acids/liver

•Systemic metabolism

•Adipose tissue

•Brain development & function

Up to 1000 species

70% unculturable

Closely co‐evolved microbial partners

03/11/2014

Impact of Western style diet on

colonic fermentation

Altered mucosal permeability and systemic inflammation?

Proximal colon~ saccharolytic

SCFAAcetate

PropionateButyrate

Energy sourceApoptosis

DifferentiationEpigenetics

Gene expressionGut hormones

Gut permeability

Distal colon~ proteolytic

AminesIndoles

AmmoniaSulphidesN‐nitroso

DNA damageTumours

CytotoxicityLeaky gut

Liver disease

Modified from Geroge Macfarlane

03/11/2014

Impact of traditional diets rich in fiber,

polyphenols on colonic fermentation

High fiber diets, Paleolitic, Mediterranean, rural African and AsianEnhanced mucosal barrier function and immune homeostasis

Proximal colon~ saccharolytic

SCFAAcetate

PropionateButyrate

Energy sourceApoptosis

DifferentiationEpigenetics

Gene expressionGut hormones

Gut permeability

Distal colon~ proteolytic

AminesIndoles

AmmoniaSulphidesN‐nitroso

DNA damageTumours

CytotoxicityLeaky gut

Liver disease

Modified from Geroge Macfarlane

Koeth et al 2013 Nature Medicine•TMA/TMAO confirmed strong link with CVD in patients •confirmed microbiota metabolism of L-carnitine/choline → TMA→TMAO•TMA not produced in vegans•confirmed inflammatory activity & linked to macrophages reverse cholesterol transport •TMAO reduced bile acid pool

03/11/2014

birth weaningsbabies adultsinfants aged

2

4

6

8

10

12Bacteroids, Eubacterium, Peptococooccae

Group I

Group II

Group III

Bifidobacterium

Escherichia coli, Streptococcus

Lactobacillus

Clostridium perfringensLo

g c

ou

nt

of

bac

teri

a /g

fec

es

Human diet shaped our closely co-evolved human:microbe ecosystem

Dietary evolution

•Neolithic times: ~10,000 yrs BP (birth of agriculture)

•Agricultural/Industrial revolutions: Late 18th and early 19th century

•Recent changes: Over the last 50 yrs (Western-style diet)

Human microbiome evolution

03/11/2014

Estimated daily fiber intake in Palaeolithic /Traditional diets and Modern diet

Dietary pattern Fiber content

Palaeolithic diet first reported in 1985 (Eaton SB) 45.7g

Palaeolithic diet modified in 1990 (Eaton SB) >100g

Palaeolithic diet reported in 1996/1997 (Eaton SB) 104g

Rural Chinese diet 77g

Rural African diet 120g

Current US diet 10-20g

Recommended fiber content in US 25-38g

Current UK diet 12g

Recommended fiber content in UK 18g

(Tuohy et al. Current Pharmaceutical Design, 2009)

Total polyphenols

(catechin equivalents, mg/100 g)

Redrawn from: Mattivi F., Dietas Mediterráneas: La evidencia científica, 2004, 99-111

411

330291

641

475424 408

294 280

193 179

292

211

111 9840 38 28 27 21

645

57 54 54

231 211

0

200

400

600

800

Wild

bilb

erry

Wild

bla

ckbe

rry

Elde

rber

ry

Wild

ras

pber

ry

Blac

k cu

rran

t

Red

curr

ant

Wild

str

awbe

rry

Whi

te c

urra

nt

Blac

kber

ry (

n=3)

Blue

berr

y (n

=9)

Goo

sebe

rry,

whi

te

Rasp

berr

y (n

=5)

Stra

wbe

rry

(n=

9)

Sour

che

rry

Plum

(n=

6)

Cher

ry (

n=7)

Pom

egra

nate

Appl

e (n

=28

)

Peac

h

Pear

(n=

3)

Kiw

i

Man

go

Papa

ia

Pers

imm

on Fig

Bana

na

WILD BERRIES

CULTIVATED BERRIES

FRUITS

03/11/2014

Gut microbiota differs between children following Western-style diet in Italy and children in rural Africa following traditional diet.

De Filippo et al., PNAS (2010)

Increasing


03/11/2014

Aberrant gut microbiota associated with Western-style diet

British Journal of Nutrition 2011

•SCFA about 3-4 fold higher in African children than Italian children•Abundance of Enterobacterial groups commonly associated with gastrointestinal disease higher in EU/Italian children


Gut microbiota differs between children following Western-style diet in Italy and children in rural Africa following traditional diet.


03/11/2014

a.

e.

d.

c.

b.

f.

Total daily food intake in relation to the average of maximum quantity ingested per dayg/day

Nutritional composition of foods is available from http://www.inran.it for EU and http://www.fao.org for BF

a) Millet; b) Millet flour; c‐d) black‐eyed peas, Niebè, e) Parkiabiglobosa tree (Néré); f) Soumbalà ,Nerè fruits fermented.

The diet of ‐BF rural children is low in fat and rich in fibers and plant‐polysaccharides and predominantly vegetarian‐BF urban children maintain the consumption of cereals and legumes but introduces milk, meat, fish, egg and peanuts.‐ EU is a a typical western diet high in animal protein, sugar, starch, and fat and low in fiber.

0

50

100

150

200

250

300

Protein Fat Carbohydrate(fiber

included)

Fiber

Daily Intake BF rural

BFurban

EU

0,0

10,0

20,0

30,0

40,0

50,0

60,0

Rural BF Urban BF EU

µmol/g

ACETIC*

*

0,0

2,0

4,0

6,0

8,0

10,0

12,0

14,0

16,0


µmol/g

BUTANOIC**

*

**

0,0

5,0

10,0

15,0

20,0

25,0

30,0

35,0


µmol/g

PROPANOIC

***

0,0

0,2

0,4

0,6

0,8

1,0

1,2

1,4

1,6

1,8


µmol/g

PENTANOIC*

Quantification of SCFAs in fecal samples from BF and EU populations by SPME‐GC‐MS.

03/11/2014

Gut microbiota….. but not as we know it!

• Currently 300 million people obese world-wide

• Obese adults are up to 80 times more likely to develop type 2 diabetes than non-obese adults

• Obese adults are 2-3 times more likely to develop heart disease

• Obese adults have a 40% increased risk of dieing from cancer

OBESITY EPIDEMIC

03/11/2014

The 3Ps: Probiotics, Prebiotics & Polyphenols

• PROBIOTICS....“live microorganisms which when administered in adequate amount confer a health benefit on the host” (FAO, 2001).

- Lactobacillus- Bifidobacterium- Escherichia coli Nissle 1917, Bacillus sporogenes, Enteorcoccus faecium, Clostridium

butyricum, Saccharomyces ceriviseae

• PREBIOTICS…. a selectively fermented ingredient that results in specific changes, in the composition and/or activity of the gastrointestinal microbiota, thus conferring benefit(s) upon host health. Gibson et al (2010)– Inulin, oligofructose, fructooligosaccharides, galactooligosaccharides, lactulose,

arabinogalactan, arabinoxylan, pectic‐oligosaccharides, glucooligosaccharides– Resistant starch and certain whole plant foods including whole grain wheat, whole grain

oats

• POLYPHENOLS….. 90% resistant to digestion and reach the colon, plant secondary metabolites, usually antioxidant, antimicrobial activities, enzyme/nutrient binding properties and possibly prebiotic type properties, e.g. red‐wine polyphenols, apple tannins

Gut microbiota and systemic health

Obesity

LaxationLipid

metabolism

Diarrhoea/IBS

Cancer (CRC)

Blood glucose

Mineral absorption

IBD

Satiety

Immune function

Probiotics

03/11/2014

• Lb. reuteri selected for Bile Salt Hydrolase activity (2 capsules/day at 2 x 109 CFU/capsule) for 9 weeks

• Randomized, double-blind, placebo-controlled, parallel-arm, multicenter study

• N=127 hypercholesterolemic patients• Probiotic reduced plasma

– TC by 9.14%– LDL-C by 11.64%– LDL-C/HDL-C ratio by 13.39%– Non-cholesterol plant sterols– Increased circulating deconjugated bile acids

• Proposed new cholesterol lowering activity of probiotics via modified absorption of lipids from the gut

Table 1. Cellular actions described for TGR5 in different cell types. ∗Macrophages include alveolar macrophages, Kupffer cells and THP-1 cells.

BA, fat & glucose homeostasisInflammation (NF-κB)

Enterohepatic BA circulationmicrobiota

(deconjugation, 1°→ 2°)

Journal of Hepatology (2011)

FXRα

VDR

PXR

03/11/2014

Influencing the Gut:brain axis

03/11/2014

03/11/2014

GABA….. An effective immunomodulatory

molecule

•GABA receptors also on human PBMC, monocytes and neutraphils

GABA treatment improves IN sensitivity

03/11/2014

Lactobacillus plantarum/brevis FEM 1874:

GABA producer and BSH positive

0

20

40

60

80

100

120

140

High producers of GABA GABA PRODUCTION (mg/L)

Not all cheeses are equal.

03/11/2014

Smelly cheeses – live cheeses!

Anti‐pathogen activity of Trentino cheese

lactic acid bacteria

LAB Strain

Escherichiacoli

DSM 1103

Listeriamonocitogenes

309


306

Staphilococcusaureus

ATCC 25923

Bacilluscereus

DSM 345

Candidaalbicans

ATCC 14053

Salmonellaenterica

DSM 14221

LactobacillusparacaseiVi44 (6M) NI NI NI NI +++++ +++++ NI

Lactobacillusrhamnosus2360 +++++ NI +++++ +++++ +++++ NI +++++

LactobacillusdelbrueckiiP243

NI NI NI NI NI +++++ NI

Lactobacillusparacasei P210 (1M) +++++ +++++ +++++ +++++ +++++ +++++ +++++

Lactobacilluscas/par/rhamSt 2 (1M) +++++ +++++ +++++ +++++ +++++ NI +++++

EnterococcusfaecalisVi4 (3M) +++++ +++++ +++++ +++++ +++++ NI +++++

Lactobacillusparacasei 2689 +++ +++ NI NI NI NI NI

Lactobacilluscas/par/rhamS43 (2M) +++++ ++++ ++++ ++++ +++++ NI +++++

LeuconostocmesenteroidesVi 47 (3M) + + + + + NI +

LAB Strain

Escherichiacoli

DSM 1103


309


306

Staphilococcusaureus

ATCC 25923

Bacilluscereus

DSM 345

Candidaalbicans

ATCC 14053

Salmonellaenterica

DSM 14221

LactobacillusparacaseiVi44 (6M) NI NI NI NI +++++ +++++ NI

Lactobacillusrhamnosus2360 +++++ NI +++++ +++++ +++++ NI +++++

LactobacillusdelbrueckiiP243

NI NI NI NI NI +++++ NI

Lactobacillusparacasei P210 (1M) +++++ +++++ +++++ +++++ +++++ +++++ +++++

Lactobacilluscas/par/rhamSt 2 (1M) +++++ +++++ +++++ +++++ +++++ NI +++++

EnterococcusfaecalisVi4 (3M) +++++ +++++ +++++ +++++ +++++ NI +++++

Lactobacillusparacasei 2689 +++ +++ NI NI NI NI NI

Lactobacilluscas/par/rhamS43 (2M) +++++ ++++ ++++ ++++ +++++ NI +++++

LeuconostocmesenteroidesVi 47 (3M) + + + + + NI +

03/11/2014

Acid (pH 2) and bile tolerance of Trentino

cheese lactic acid bacteria

1,E+00

1,E+01

1,E+02

1,E+03

1,E+04

1,E+05

1,E+06

1,E+07

1,E+08

1,E+09

0 20 40 60 80 100 120 140

Minutes

Lo

g 1

0 C

FU

/ml

Lb paracasei P210

Lc mesenteroides Vi47

Lb cas/par/rham Sp43

E. faecalis V4

Lb cas/par/rham St2

Lb paracasei 2689

Lb paracasei 2360

Lb paracasei Vi44

Lb delbrueckii P243

‐0,05

0,00

0,05

0,10

0,15

0,20

0,25

0,30

0,35

P210 2689 2360 Sp43 St2 V4 Vi44 Vi47 P243

StrainGrowth Rate (h‐1)

0% 0.2 % 0.4 %

Survival of selected Trentino cheese lactic acid bacteria under simulated gastrointestinal conditions of pH and bile – a first screen for potential as probiotics

TrentinoGut Lorenza Conterno and Alice de Angelis

pH 2 incubation

In vitro Digestion

pH to 2.5Add pepsin gastric and gastric lipase 37 °C/ 2h.

pH (6N NaOH) to 6.5Add bile salts

Food ground in buffer

Mouth

Stomach

Liver & Pancreas

Large intestine

Amylase, trypsin, chymotrypsin, colipase 37 °C/ 1h

03/11/2014

Selection of putative probiotics from lactic

acid bacteria isolated from Trentino cheeses

•….

•Aim: to select putative probiotics suitable for cheese applications from Trnetino dairy Microbiome

•TrentinoGut - Lorenza Conterno

•University of Camerino, Stefania Silvi and Alice de Angelis

•Strains kindly isolated and provided by Elena Franciosi

Putative Trentino probiotic survival under

gastrointestinal conditions in presence and

absernce of cheese matrix

0

10

20

30

40

50

60

70

2689 St2 2360Strain

Survival%

CultureBroth

CultureinModelCheese

2689 = Lactobacillus paracaseiSt2 = Lactobacillus casei paracasei rhamnosus2360 = Lactobacillus rhamnosus

TrentinoGut Lorenza Conterno and Alice de Angelis

03/11/2014







oats


CCC

03/11/2014

CCC


Obesity

LaxationLipid

metabolism

Diarrhoea/IBS

Cancer (CRC)

Blood glucose

Mineral absorption

IBD

Satiety

Immune function

Prebiotics

03/11/2014

Delaying the progression of obesity with fermentable carbohydrates and prebiotics

• Does dietary supplementation with prebiotics or fermentable CHO/fiber reduce body weight through enhanced satiety

• High fat fed animals (control)• High fat supplemented with Inulin (Synergy 1 (10% w/w)• High fat supplemented with β-glucan (10% w/w)

– Diets were isoenergetic with cellulose used to reduce calorie load of control, high fat diet.

– Measures: magnetic resonance imaging (whole body fat deposition and stimulation of hypothalamus appetite centres), PYY, gut microbiota and caecal/faecal metabolites

Tulika Arora, Gary Frost et al. PLoS One 2012

1 2 3 4 5 6 7 80

2

4

6

8

10Beta glucanInulin

Control

**** ***

* ***

Week

Cu

mu

lati

ve B

W g

ain

(g

)

1 2 3 4 5 6 7 80

25

50

75

100

125

150

175

200Beta glucanInulin

Control

******

******

***

**

*

Week

Cu

mu

lati

ve f

oo

d in

take

(g

)

0.0

0.5

1.0

1.5

2.0ControlBeta glucanInulin

Liver EpididymalAdipose tissue

Caecum Colon

*

*****

Tissue

Wei

gh

ts (

in g

)

Control Inulin Beta glucan0

5

10

15

20

25 * Control

Inulin

Beta glucan

Groups

% B

od

y ad

ipo

sity

Inulin and β-glucan reduce body weight gain

03/11/2014

Effect of inulin and β-glucan supplementation on adiposity

parameters and PYY level in high fat fed mice.

The values with different superscripts letters are significantly different from each other

HFD-C HFD-I HFD-BG

Epididymal adipose tissue (g)

1.14±0.16a 0.59±0.10b 0.77±0.10a

Whole body adiposity (%) 18.03±2.72a 8.95±1.66b 12.17±1.92a

Liver lipid content (%) 6.30±1.62a 6.02±1.97a 6.02±1.36a

Muscle lipid content (%) 0.96±0.149a 0.72±0.05a 1.29±0.57a

Visceral fat (g) 2.17±0.46a 1.23±0.17a 1.49±0.27a

Subcutaneous fat (g) 3.40±0.53a 2.08±0.13a 2.44±0.28a

Adipocyte size (μm) 122.25±10.2a 72.95±8.72b

111.19±4.03 ac

Adipocyte number (x107) 1.43E+08a 1.31E+08a 1.86E+08a

Liver size (g) 1.43±0.13a 1.23±0.15a 1.40±0.06a

Caecum (g) 0.21±0.01a 0.69±0.05b 0.49±0.03c

Colon (g) 0.13±0.01a 0.19±0.02a 0.14±0.02a

PYY (pmol/ml) 0.10±0.012a 0.10±0.008a

0.13±0.016a

Colonic PYY 27.3 3.7 22.8 5.3 19.9 1.6

Effect of inulin and β-glucan supplementation on changes in signal intensity in the appetite centres of the brain measured by MRI

-10

0

10

20

30

40

50

60

70

80

ControlInulinBeta glucan

*

10 20 40 60 80 100 120 140

Time (in mins)

No

rma

lize

d p

erc

en

t e

nh

an

ce

me

nt

Arcuate nucleus

-10

0

10

20

30

40

50

60


***

10 20 40 60 80 100 120 140

Time (in mins)

No

rma

lize

d p

erc

en

t e

nh

an

ce

me

nt

Ventromedial hypothalamic nucleus

The arrow shows the start of Mn2+ infusion and grey bar represents the duration of Mn2+ infusion.

03/11/2014

-10

0

10

20

30

40

50


**

10 20 40 60 80 100 120 140

Time (in mins)

No

rmalize

d p

erc

ent e

nh

an

ce

me

nt

Paraventricular nucleus

-10

0

10

20

30

40

50

60

70


*****

10 20 40 60 80 100 120 140

Time (in mins)

No

rmalize

d p

erc

en

t e

nh

an

ce

me

nt

Periventricular nucleus-4

-3

-2

-1

0

1

2

3

4

5

6

7

8


10 20 40 60 80 100 120 140

*

Time (in mins)N

orm

ali

zed

pe

rce

nt

en

ha

nc

em

en

t

Nucleus of tractus solitarius

Effect of inulin and β-glucan supplementation on changes in signal intensity in the appetite centres of the brain measured by MRI

The arrow shows the start of Mn2+ infusion and grey bar represents the duration of Mn2+ infusion.

Effect of inulin and β-glucan supplementation on murine gut microbiota compared to high fat diet supplemented with cellulose

9.5

10.0

10.5

11.0

11.5

Control Inulin Beta glucan

***

Lo

g10

cell

s/g

fae

ces

9.0

9.5

10.0

10.5

11.0


***

Lo

g10

cells/

g f

aece

s

8.5

9.0

9.5

10.0

10.5

11.0


***

Lo

g10

cells/

g f

aece

s

A: Total bacteria B: Mouse Intestinal Bacteria C: Eubacterium rectale-Clostridium coccoides

7

8

9

10


***

***

Log

10ce

lls/

g fae

ces

7

8

9

10


*** ***

Control week 0

Control week 4

Control week 8

Inulin week 0

Inulin week 4

Inulin week 8

Beta Glucan week 0

Beta Gllucan week 4

Beta Glucan week 8

Log

10ce

lls/

g fae

ces

D: Lactobacillus E: Bifidobacterium

Similar findings observed for caecal contents at week 8.

03/11/2014

Effect of inulin and β-glucan supplementation on murine faecal metabolite profiles (NMR) compared to high fat diet supplemented with cellulose

NMR based metabolomics separates cellulose from inulin or β-glucan supplemented animals on high fat diets

PCA scores plot of fecel metabolite profiles showing clear clustering patterns for mice fed with HFD-C, HFD-BG and HFD-I groups.

03/11/2014

Fermentable fibers/prebiotics reduce body weight but by different mechanisms

• β‐glucan reduced cumulative body weight apparantly through reduced stimulation of hypothalamic appetite centres, increased satiety and reduced food intake.

• Inulin appeared to reduce cumulative body weight gain through reduced adipocyte size and whole body adiposity

• SCFA concentrations in the caecum β‐glucan > inulin > high fat control

• Inulin gave increased caecum weight

• β‐glucan had higher excretion of glucose in faeces while high‐fat control had higher excretion of butyrate and propionate

Arora et al. PLoS One 2012

Whole grain oats vs non-whole grain breakfast cereal dietary intervention in subjects “at risk” of developing the metabolic syndrome

•Randomized, crossover study, 30 volunteers, male and female with slightly elevated levels of either total cholesterol or fasting glucose at risk of developing metabolic disorders

•Two 6 week treatment periods separated by 4 week washout periods.•Whole oat grain (WGO) vs non-whole grain cereal (NWG)•Samples collected before and after cereal consumption and then 4 weeks following end of consumption.•Blood (fasted), 24 hour urine, saliva and fecal samples

Connolly et al. In preparationSupported by Jordans Cereals

WGORun-in Wash out NWG

NWGRun-in Wash out WGO

Follow up

Follow up

2 weeks 6 weeks 4 weeks 6 weeks 4 weeks

03/11/2014

Whole grain oats modified gut microbiota in beneficial manner compared to non-whole grain cereal

Whole grain oats significantly increased faecal bifidobacteria and lactobacilli but no other bacterial groups measured.

WGO WGO

Whole grain oats improved blood cholesterol profiles

•Whole grain oats significantly reduced LDL and total cholesterol, reversing a trend towards elevated LDL and TC in the non-whole grainbreakfast cereal treatment.

WGOWGO

03/11/2014

Impact of wheat bran fibre (WBF) on gut microbiota & markers of CVD in overweight adults

WBF (bread, biscuits, breakfast cereals)Run-in

Cellulose (bread, biscuits, breakfast cereals)Run-in

2 weeks 8 weeks

•Subjects: n=80, BMI > 27

•FEM & Santa Chiara Hospital (Dr Carlo Pedrolli), APSS, Trento

•Biomarkers of CVD risk

•Gut microbiota (454-pyrosequencing, FISH, qPCR)

•MS based metabolomics (targeted and untargeted)







oats


03/11/2014


Obesity

LaxationLipid

metabolism

Diarrhoea/IBS

Cancer (CRC)

Blood glucose

Mineral absorption

IBD

Satiety

Immune function

Polyphenols

American Journal of Clinical Nutrition, 2012

0

2

4

6

8

10

12

14

Enter

ococ

cus

Lacto

bacil

lus

Clostri

dium

Clostri

dium

hist

olyti

cum

gro

up

Blautia

cocc

oide

s-Eub

acte

rium

recta

le g

roup

Bacte

roid

es

Bacte

roid

es u

nifor

mis

Prevo

tella

Bifidob

acte

rium

Egger

thell

a le

nta

16S

rR

NA

gen

e co

pie

s/g

fae

ces,

mea

n +

/- S

D,

n=

10

Basline

De-alcoholized red wine

Red wine

Gin

* * **

* *

*

* *

03/11/2014

(2011) 93:62-72.

03/11/2014

Measuring the impact of raspberries of different polyphenol content on gut microbiota

•Raspberries digested and fermented

•Alpen Gold (yellow), Tulameen (red), Anne (yellow), Sugana Yellow (yellow), Sugana Red (red)

•Controls (inulin and cellulose)

qPCR (total, Enterobacteriaceae, LAB, Bifidobacterium spp)FISH (totals, Bifidobacterium spp., Bacteroidaceae e Prevotellaceae (Bac303), Clostridium hystoliticum (Chis), Clostridium coccoides-Eubacterium rectale (Erec), Faecalibacterium prausnitzii (Fpra)ARISA

Targeted Metabolomic: Anthocyanins and Ellagitannins (UPLC-MS)SCFA (GC-MS)

03/11/2014

Significant increase in bifidobacterial

abundance as measured by FISH

6,4

6,6

6,8

7

7,2

7,4

7,6

7,8

8

8,2

8,4

Alpen

Gold

Tulamee

n

Anne

Sugan

aYellow

Sugan

a Red

Inuline

Cellulose

Log10

cel

ls/m

L

0

5

10

24

a a a a a a

HOURS

a: average of five significantly higher

Total anthocyanins and anthocyanins profile during fermentation for Tulameen or Sugana Red

0

1000

2000

3000

4000

5000

6000

Alpen Gold Tulameen Anne Sugana

Yellow

Sugana

Red

Inuline Cellulose

ng/ml

T0

T5

T10

T24

0

1000

2000

3000

4000

5000

pg3glu cy3glu cy3gal cy3samb cy3rut cy3soph

anthocyanin

ng

/ml

051024

0

1000

2000

3000

4000

5000

pg3glu cy3glu cy3gal cy3samb cy3rut cy3soph

anthocyanin

ng

/ml

051024

pg: pelargonidincy: cyanidin

glu: glucosidegal: galactosidesamb: sambubiosiderut: rutinosidesoph: sophoroside

03/11/2014

Ellagitannins measured during raspberry fermentation

Casuarictin: monomerSanguiin: dimerLambertianin: trimer

0,00

0,05

0,10

0,15

Alpen Gold

Tulameen Anne Sugana Yellow

Sugana Red

Inuline Cellulose

ng/ml

Lambertianin CT 0T 5T 10T 24

Increasing fruit and vegetable intake in vivo – FLAVURS project

Flavonoid‐poor F&V

Flavonoid‐rich F&V+2 + 4

+2

+ 6

+ 4 + 6

Habitual diet

Wk 0

Visit 1Wk 6

Visit 2

Wk 12

Visit 3Wk 18

Visit 4

?

03/11/2014

High Flavonoid group

Apple crumble Dried cranberries/ blueberries

Fruit smoothies (Strawberry and raspberry/ Blackberry and blueberry)

Fruit juices(Blackcurrant /apple/cranberry/orange )

Roasted peppers Pepperdew cherry peppers

All fruits and vegetables contain ≥ 15mg/100g of flavonoids

Low Flavonoid group

Rhubarb crumbleDried fruits (raisins, currants, mango)

Fruit smoothies (tropical mix)

Fruit juices (mango/pineapple)

GuacamoleHoumous

Soups (Carrot & coriander/broccoli & stilton)

Canned chopped tomatoesAll fruits and vegetables contain < 5mg/100g of flavonoids

03/11/2014

FLAVONOIDS

Dietary intake: HF dose dependent increaseHF higher vs LF & CT +2,+4,+6 Time x treatment (P=0.006)

Biomarker : 24h urinary flavonoid & metabolitesHF dose dependent increaseHF higher vs LF & CT +2, +4, +6Time x treatment (P=0.0001)

+2 +4 +6Additional F&V portions


VITAMIN C

Dietary intake: HF & LF dose increaseHF & LF vs CT higher +2, +4, +6Time x treatment (P=0.0001)

Biomarker: Plasma vitamin CHF & LF dose increase HF & LF vs CT higher +2, +4, +6Time x treatment (P=0.0001)



03/11/2014

CAROTENOIDS

Dietary intake : LF dose dependent increaseHF & LF higher CT all pointsTime x treatment (P=0.001)

Biomarker : Total plasma carotenoidsLF dose dependent increaseHF & LF higher CT all pointsTime x treatment (P=0.0001)

Die

tary

car

ote

ne

(µg

/day

)



Non-starch polysaccharide (NSP) changes

HF & LF higher than the CT all time pointsLF dose dependent increase

Time x treatment interaction (P=0.0001).

03/11/2014

F&V impact on arterial stiffness measured by PWA

HF and LF attenuated increase shown in CT groupTime x treatment P=0.009 when standardised for HR75 P=0.03

Other blood parameters



Total plasma nitrate/nitriteHF higher than LF & CT +6Time x treatment (p=0.03)

Plasma FRAP HF dose dependent increaseLF higher +4 & +6 vs baseline Time x treatment (P=0.009)

03/11/2014

High fruit and veg diet appears to modulate

gut microbiota in “benificial”manner

Bifidobacteria

8,90

9,00

9,10

9,20

9,30

9,40

9,50

9,60

9,70

0,00 2,00 4,00Lo

g10

cel

ls/g

fae

ces

(mea

n +

/- S

EM

)

Lactobacilli

8,10

8,20

8,30

8,40

8,50

8,60

8,70

8,80

8,90

9,00

0,00 2,00 4,00Lo

g10

cel

ls/g

fae

ces

(mea

n +

/- S

EM

)Atopobium

9,20

9,30

9,40

9,50

9,60

9,70

9,80

0,00 2,00 4,00Lo

g10

cel

ls/g

fae

ces

(mea

n +

/- S

EM

)

C. perfringens/histolyticum

8,50

8,60

8,70

8,80

8,90

9,00

9,10

9,20

0,00 2,00 4,00Lo

g10

cel

ls/g

fae

ces

(mea

n +

/- S

EM

)

•Small changes

•In “right”direction

•HF Eu. rectale

•LF F. prausnitzii

•LF Bacteroides

HF LF▲ CT

P<0.05 Sig diff to wk 0 Wilcoxon Test; P<0.05 sig diff to CT Kruskal-Wallis Test

UNTARGETED METABOLOMIC ANALYSIS

OF URINE

• Urine dilution 1:5

• HPLC Analysis on RP column in positive and negative ionization mode

• XL Orbitrap in Full Scan MS and MS/MS within high resolution and mass accuracy Approaches

• Substances considered as biomarkers when p<0.005 (t-test)• Annotation of metabolites:

− Mass accuracy of precursor ion [M+H]+ (< 3 ppm error)− Isotopic pattern distribution

• Databases used for annotation: In-house data base, Human Metabolome Database, Metlin, MAssBank, LipidMaps

03/11/2014

Metabolomics workflow

Sample preparation: extraction of all analytes

Statistic analysis

Untargeted analysis withHR mass spectrometer

Biomarker identification

Samples: urine, plasma, fecal water

C+

NHO

F

CH3

NN

CH3

Separation on LC column

ALLIGNMENT OF CHROMATOGRAMS, BATCH CORRECTIONS, PEAK PICKING UNIVARIATE ANALYSIS with XCMS

Data processing - XCMS using the “matchedFilter” peak picking method with SpectraFilter Window Mower function.For each mass feature two linear mixed models were fitted, diet-time interaction andtime alone.

Both models were adjusted for baseline. p values for all features were corrected formultiple testing according to the two-stage Benjamini and Hochberg step-up falsediscovery rate (FDR).

03/11/2014

Rt Annotation; Elemental Composition, MW, adjusted p value

1.10 ProlineBetaine; MMW: 143.0946, p 0.002 ↑Diet A;

2.20 N-acetyl-S-(2-hydroxypropyl) cysteine, MMW: C8H15NO4S; p

3.80 Hydroxy Hippuric Acid (isomer); MMW: 195.0531, p 0.02 ↑Diet A;

4.40 Hydroxy Hippuric Acid (isomer); MMW: 195.0531, p 0.002 ↑Diet A,

4.82 Vanilloylglycine, MMW: 225.0637; p.0.03 ↑ Diet A, B;

5.70 Hippuric Acid, MMW: 179.0582; p 0.002 ↑Diet A

5.89 Phenylacetylglutamine, MMW: 264.1110, p 0.04 ↑Diet A;

6.15 FerulicAcid Sulfate , MMW: 274.0731, p 0.04; ↑Diet B

6.26 Dihydroxyphenyl-γ-valerolactone-O-sulphate MMW:288.0306 p 0.0003 ↑Diet A;

6.56 Dihydroxyphenyl-γ-valerolactone-O-methyl-O-GLC, p 0.01 ↑ Diet A;

7.14 Cresol-Glucuronide, MMW: 284.0896; p 0.001 ↓Diet A;

7.35 Hydroxy Hippuric Acid (isomer), MMW: 195.0531, p 0.01 ↑ Diet A;

7.76 Hydroxy-tridecenoic acid GLC, MMW: 404.2046, p 0.001 ↑ Diet A;

12.38 Iberin N-acetyl-cysteine MMW: p 0.0001 ↑ Diet A & p 0.001↑ Diet B

Alimentazione

Adding value to the food chain FOOD QUALITY AND NUTRITION DEPARTMENT

Apples Gut Microbiota Modulation

Nutrition and Nutrigenomics

Biological samples: Blood, Urine and Faecal samples

Measurements•% body fat composition, DEXA•blood pressure, •vascular stiffness (pulse wave analysis, PWA) •and vascular reactivity (laser Doppler imaging, LDI)•Gut microbiota (454‐pyrosequencing)•Untargeted metabolomics.

8 weeks

Group 1

Group 2

Visit 1 (V1)

0 week

Whole Apple (WA) Wash out Apple Juice (AJ)

Apple Juice (AJ) Wash out

Pre ‐

treatment

2 weeks

Habitual

diet

Whole Apple (WA)

8 weeks 4 weeks

Visit 2 (V2)

8 week

Visit 4 (V4)

21 week

Visit 3 (V3)

13 week

03/11/2014

“Conslusions: Adherence to an MD pattern is associated with better HRQL. Theassociation is stronger with mental health than with physical health. Dietary totalantioxidant and fibre content independently explain this relationship”.

Dietary patterns – Mediterranean diet & Gut

Microbiome “ecosystem support”

Barilla Centre for Food Nutrition: Double Pyramid: healthy food for people, sustainable food for the planet

http://www.barillacfn.com/en/position-paper/pp-doppia-piramide-alimentazione/

INRAN, FAO Double Pyramid

GUT MICROBIOTA PYRAMID

CHRONIC DISEASE PYRAMID

03/11/2014

Fondazione Edmund Mach

•Thank you: SINU, Professor Brighenti

•Fulvio Mattivi, Duccio Cavalieri and Roberto Viola, FEM-IASMA

•NN Group: Lorenza Conterno, Francesca Fava, Elena Franciosi, Carlotta de Filippo, Athanasios Koutsos, Ilaria Caraffa, Florencia Ceppa, Andrea Manchini

•University of Reading, Glenn Gibson, Bob Rastall, Julie Lovegrove, Parveen Yaqoob, Christine Williams, Ian Rowland, Michael Connolly

•Gary Frost, Imperial College London, Daniele Del Rio, University of Parma

Documents

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