gut microbiota, diet, chronic inflammation and metabolic...

Matam Kumar

(Vijay)

Fred Carvalho

(La Machine)

Gut microbiota, diet, chronic

inflammation and metabolic syndrome

Andrew Gewirtz, Institute for Biomedical Sciences

Georgia State University, Atlanta GA

Illustration by Micah Lidberg , Proto, MGH

Mucosal defenses maintain permit host-microbiota coexistence

Muc2 (mucin layer)

Bacteria

Actin

DNA

Antimicrobial peptides (AMP)

IgA, IgG

TLRs/NLRs

AMP

Immune cell recruitment

Dysbiosis (i.e. perturbed microbiota)

Encroaching, pro-inflammatory microbiota

Chronic inflammation

Take-home message

Impairment of mucosal anti-microbial defense

1. Innate immune deficiency

2. Chemical disturbance of microbiota

3. Mucus atrophy from low fiber diet

Colitis Metabolic Syndrome

HIV

HIV-related metabolic abnormalities

Metabolic Syndrome: A constellation of metabolic abnormalities

associating with insulin resistance including obesity,

hyperglycemia, hyperlipidemia, and hypertension. Metabolic

syndrome often progress to type 2 diabetes, hypertension,

cardiovascular disease, and/or liver disease.

Similarities between metabolic syndrome and IBD

1)Increased expression of similar pro-inflammatory genes/markers.

2)Associated with alterations in gut microbiota

3)Require microbiota – i.e. No disease in germ-free mice.

4)Feature remodeling of adipose tissue

5)Increasing incidence in last 50 years (amidst constant genetics)

Inflammatory Bowel Diseases (IBD): Collective term for chronic

inflammatory diseases of the intestine including Crohn’s disease

and ulcerative colitis.

Inflammation: Central feature of a spectrum of diseases

HIV:

✔️

✔️

✔️

?

IL-8

S. typhimurium

Flagellin

Y

NF-kB

TLR5

TJ

Commensal microbes

IBD?

Flagellin receptor TLR5 Coordinates

clearance of motile bacteria

Flagellin monomers

(About 70,000 per flagella)

IEC

Immune cell recruitment

Rapid bacterial clearance

AMP

WT T5KO0.0

0.5

1.0

1.5

2.0

2.5

40%

WT T5KO0

1

2

3

4

28%

WT T5KO0.0

0.3

0.6

0.9

1.2

1.5

27%

Co

lon

wei

gh

t [

% b

od

y m

ass

]

Cec

um

wei

gh

t [

% b

od

y m

ass

]

Sp

leen

wei

gh

t [

% b

od

y m

ass

]

T5KO mice develop spontaneous colitisT5KO

(10%)52/500

WT

500/500

Vijay-Kumar et. al. 2007. J. Clin. Invest

T5KO mice develop obesity

4 6 8 10 12 14 16 18 20

20

25

30

35

Week

Bod

y W

eigh

t (g)

4 6 8 10 12 14 16 18 20

15

20

25

Week

Bod

y W

eigh

t (g)

Males Females

WT

T5KO

WT

T5KO

WT T5KO

Fat

Pad

[g

]

Males

WT T5KO

WT T5KO

Females

0.1

0.2

0.3*

0.25

0.50

0.75

*

Vijay-Kumar et. al. 2010. Science

0 30 60 90 120

100

150

200

250

300

350

400

Time [mins]

Blo

od

Glu

co

se [

mg

/dL

]

T5KO exhibit hyperglycemia/insulin resistance

*

WT T5KO

60

85

110

135

Fasti

ng

Glu

co

se

[mg

/dL

]

Glucose Tolerance

0 30 60 90 12050

60

70

80

90

100

Time [min]Blo

od

Glu

co

se [

% s

tart

ing

]

T5KO

WT

Insulin Sensitivity

+ Ins.

*

WT T5KO

0.25

0.50

0.75

1.00

Se

rum

In

su

lin

[n

g/m

L]

0.4

0.8

1.2

1.6

Seru

m I

nsu

lin

[n

g/m

l]

Glucose: - + - +

WT T5KO

*

Insulin Production

T5KO

WT


Tracking of inflammatory marker fecal lipocalin 2 (Lcn2)

126 8 104

Fecal Lcn2

(pg/mg stool)

101

102

103

100

Age (weeks)

Colitic T5KO

Met syn T5KO

WT

Carvalho et. al. 2012. Cell Host & Microbes

Colitic T5KO

WT

Non colitic

T5KO

Colitic T5KO

T5KO mice exhibit taxonomical

alterations in the gut microbiota

Summary 1

Innate immune deficiency (T5KO)

Compensatory Activation of other components of immune system

Mismanaged gut microbiota

Severe colitis

20% Failure rate

Lack of successful breeding

80% “Success”

Plentiful breeding

(but metabolic syndrome)

Microbiota

Increased caloric consumption (obesity)

Nutrient Excess

Endoplasmic reticulum stress

Pro-inflammatory Signaling (NF-kB, MAPK, JNK)

Desensitization of insulin receptor signaling (i.e. insulin resistance)

Metabolic Syndrome

“Inflammatory explanation” for insulin resistance (Hotamisligil)

T2D CVD NASH

(& other metabolic pathways)

How would low-grade inflammation cause metabolic syndrome?

Conv WT-GF T5KO-GF0

5

10

15

20

25

Fecal L

ipo

calin

2

[ng

/g f

eces]

GF-WT GF-T5KO18

20

22

24

26

28

30

Bo

dy W

eig

ht

[g]

GF-WT GF-T5KO0.0

0.5

1.0

1.5

Fat

Pad

[% B

od

y W

eig

ht]

7-log difference in 16s RNA

Conv WT-GF T5KO-GF

100

101

102

103

104

105

106

107

108

Cecal B

acte

ria [

CF

U/m

g]

Lack of Phenotype in Germ-freeT5KO mice

Carvalho et. al. 2012. Cell Host & Microbes

0

50

100

150

200

250

WT T5KO WT T5KO WT T5KO

Weeks Post-transplant:

0 2 4

Fecal

lip

ocalin

-2 6

2

4

g/m

ou

se/2

4 h

WT T5KO

Food consumption

Conventionalizing germ-free mice restores metabolic syndrome in T5KO

600

400

200

Epididymal fat pad

(mg)

WT T5KO

100

110

120

130

140

150

160

170

0 7 14 21 27 35 42 49 56 63 70 77 84

% w

eig

ht

gain

WT

T5KO

WT T5KO

Fasting glucose

(mg/ml)

Days post-conventionalization

75

100

125

T5KO microbiota is sufficient to transfer

metabolic syndrome to WT germfree mice

WT T5KO

60

80

100

120

4.0

4.5

5.0

5.5

0 20 40 600

50

100

Days post transplant

% W

eig

ht

Gain

WT T5KO

0.50

0.75

1.00

Fo

od

In

tak

e [

g/m

ou

se

/da

y]

Se

rum

In

su

lin

[n

g/m

l]

Fa

sti

ng

Glu

co

se

[m

g/d

L]

***

0.25

0.50

0.75

1.00

Fa

t P

ad

[g]

WT T5KO

0 50 100 150 200

50

75

100

Time [min]

Blo

od

Glu

co

se

[%

sta

rtin

g v

alu

e]

WT T5KO

*

T5KO

WT

WT T5KO

WT

T5KO


Day 0PC1 (13%)

PC2 (11%)

TLR5fl/fl

TLR5DIEC

Day 42PC1 (15%)

PC2 (10%)

TLR5fl/fl

TLR5DIEC

Day 84PC1 (17%)

PC2 (14%)TLR5fl/fl

TLR5DIEC

Loss of IEC TLR5 changes microbiota composition

Fli

C (

µg

/g f

ec

es

)

6 3 5 6 3 7 7

0

1 0 0 0

2 0 0 0

3 0 0 0

4 0 0 0 T L R 5f l / f l

T L R 5D IE C

LP

S (

µg

/g f

ec

es

)

6 3 5 6 3 7 7

0 . 0

0 . 5

1 . 0

1 . 5

2 . 0 T L R 5f l / f l

T L R 5D IE C

Fecal Flagellin Fecal LPS

Making it inherently more pro-inflammatory

Chassaing et. al. 2014. Gastro

Ba

cte

ria

/ m

g o

f co

lon

ic m

uco

sa

T L R 5f l/ f l

T L R 5D I E C

T L R 5DD C

1 0 4

1 0 5

1 0 6

Dis

tan

ce o

f ba

cte

ria

fro

m IE

C (

µm

)

T L R 5f l/ f l

T L R 5D I E C

T L R 5DD C

0

1 0

2 0

3 0

4 0

Loss of IEC TLR5 decreases microbiota-IEC distance

WT IEC-TLR5KO DC-TLR5KO

WT IEC-TLR5KO DC-TLR5KO WT IEC-TLR5KO DC-TLR5KO

Distance Adherent Bacteria

Chassaing et. al. 2014. Gastro

Microbiota encroachment is a feature of metabolic syndrome in humans

BMI = 21.1, Glucose = 114 mg/dL

HbA1C = 5.3, Diabetes mellitus = NoBMI = 34.33, Glucose =148 mg/dL

HbA1C = 7.7, Diabetes mellitus = Yes

Bacte

rial

dis

tan

ce t

o I

EC

(0-4

0m

M)

B lo o d g lu c o s e c o n c e n tra tio n (m g /d L )

Dis

tan

ce

of

ba

cte

ria

fro

m I

EC

(m

m)

1 0 0 2 0 0 3 0 0

0

1 0

2 0

3 0

4 0

B M I

Dis

tan

ce

of

ba

cte

ria

fro

m I

EC

(m

m)

2 0 3 0 4 0 5 0

0

1 0

2 0

3 0

4 0

H B A 1 C (% )

Dis

tan

ce

of

ba

cte

ria

fro

m I

EC

(m

m)

4 6 8 1 0

0

1 0

2 0

3 0

4 0

Blood Glucose50 200 20 50 4 10

BMI HBA1C

Chassaing et. al. 2017 CMGH

What might have changed the microbiota

and/or its promotion of inflammation?

Microbial environmental factors

Antibiotics

Hygiene

Loss of parasites

Presence or absence of viruses

Dietary factors

Altered macronutrient content (fat, fiber, protein carbs)

Altered micronutrient content (toxins, loss of labile nutrients)

2 Commonly used emulsifiers

Carboxymethylcellulose (CMC)Polysorbate 80 (PS80)

Increasingly used since mid-20th century in rough correlation with increasing

incidence of some chronic inflammatory diseases such as IBD and metabolic

syndrome.

Emulsifiers: Detergent-like molecules that stabilize mixtures of

immiscible liquids. Commonly used as food additives to improve

texture and homogeneity (shelf-life).

Dis

tan

ce

of

ba

cte

ria

fro

m I

EC

(m

m)

W a t e r C M C P 8 0

0

1 0

2 0

3 0

4 0

5 0

CMC and PS80 decrease bacteria-epithelial distance in WT mice

Water

CMC

PS80

Bacte

ria-e

pithelia

dis

tance, m

M

Water CMC PS80

Chassaing et. al 2015 Nature

Ba

cte

ria

/mg

of

co

lon

ic m

uc

os

a


1 04

1 05

Water

CMC

P80

PC1 (22%)

PC2 (13%)

WT

Emulsifiers increase adherent bacteria and change

microbiota composition

Bacte

ria/m

g c

olo

n

PC

2

PC1


Water CMC PS80

Water

CMC

PS80

T i m e ( d a y s )

FliC

(

mg

/g

fe

ce

s)

7 5 6 9 1

0

5

1 0

1 5 W a t e r

C M C

P 8 0

T i m e ( d a y s )

LP

S (µ

g/g

fe

ce

s)

7 5 6 9 1

0

1

2

3

Emulsifiers increase adherent bacteria and change

microbiota composition

WaterCMCPS80

WaterCMCPS80

Time (d) on emulsifiers

Flagellin LPS


* *

* *

#

T i m e ( d a y s )

Bo

dy

we

igh

t (

re

lativ

e v

alu

es

)

0 2 0 4 0 6 0 8 0 1 0 0

1 0 0

1 1 0

1 2 0

1 3 0

1 4 0

1 5 0

W a t e r

C M C

P 8 0

Fa

t p

ad

(m

g)


0

2 0 0

4 0 0

6 0 0

8 0 0

Fo

od

in

tak

e (

g p

er 2

4h

pe

r m

ou

se

)


4

5

6

7

15

h f

as

tin

g b

loo

d g

luc

os

e (

mg

/dL

)


6 0

8 0

1 0 0

1 2 0

* *#

Emulsifiers CMC and P80 induce metabolic syndrome

Body weight Fat mass Food intake Fasting glucose

T i m e ( d a y s )

Bo

dy

we

igh

t (

re

lativ

e v

alu

es

)

0 2 0 4 0 6 0 8 0 1 0 0

1 0 0

1 5 0

2 0 0

2 5 0

3 0 0 W a t e r

C M C

P 8 0

Germ-FreeF

at

pa

d (

mg

)


0

2 0 0

4 0 0

6 0 0

8 0 0

Fo

od

in

tak

e (

g p

er 2

4h

pe

r m

ou

se

)


4

5

6

7

5h

fa

sti

ng

blo

od

glu

co

se

(m

g/d

L)


6 0

8 0

1 0 0

1 2 0

in a microbiota-dependent manner

Body weight Fat mass Food intake Fasting glucose


Chow

“High-fat” Diet

“High-fat diet” induces microbiota encroachment

0

2

4

6

8

Dis

tan

ce

of

ba

cte

ria

to

IE

C (m

m)

Chow HFD

10

20

30

40

0

Zou et. al. Cell Host & Microbe (2018)

“High-fat” diet

Lard, Casein, Maltodextrin, Sucrose, Cellulose, Soybean Oil,

Mineral Mix, Calcium Phosphate Calcium Carbonate,

Potassium Citrate, Vitamin Mix, Choline Bitartrate, dye

Assembled from purified ingredients, 60% calories from fat:

Grain-based, relatively unrefined ingredients, 10-12% calories from fat:

Dehulled soybean meal, ground corn, dried beet pulp, fish meal, ground oats,

dehydrated alfalfa meal, cane molasses, brewers dried yeast, wheat germ,

whey, citric acid-preserved porcine animal fat, wheat middlings, porcine meat

and bone meal, salt, vitamin/mineral mix.

“Low-fat diet”: Purina 5001

18-22% fiber, both soluble (fermentable) and insoluble (not easily fermentable)

5% fiber, insoluble (not easily fermentable)

Chow

CD

D (

10%

)

CD

D (

60%

)

0 .0

0 .2

0 .4

0 .6

0 .8

1 .0

Co

lon

we

igh

t (g

/10

0g

of

BW

)

Chow

CD

D (

10%

)

CD

D (

60%

)

0 .0

0 .5

1 .0

1 .5

2 .0

2 .5

Ce

ac

um

we

igh

t (g

/10

0g

of

BW

)

Defined diets result in profound loss of gut mass

Chow HFDLow-fat

control

Chow HFDLow-fat

controlChow HFD

Low-fat

control

Colon weight

(g/100g BW)

Cecum weight

(g/100g BW)

Chassaing et. al. 2016. AJP-Gastro

Chow HFD

HFD: + Cell HFD: + Inul

Chow + Cell + Inul

HFDCho

w

50 c

ell

200

cell

200

inul

400

500

600

700

800

900

Co

lon

cry

pt

len

gth

(m

m) **

**

Chow + Cell + Inul

HFD

**

**

Chow

HFD

+50

Cel

l

HFD

+200

Cel

l

HFD

+200

Inul

100

150

200

Co

lon

weig

ht

(mg

)

“High-fat diet” (HFD) results in gut atrophy;

restored by fermentable fiber inulin


Cho

w

50 C

ell

200

Cel

l

200

Inul

0

5

10D

ista

nc

e o

f b

ac

teri

a t

o I

EC

(m

m)

Chow - Cell Inul

HFD

Inulin restores IEC-bacterial distance


Chow - Cell Inul

HFD

Chow - Cell Inul

HFD

GF miceConventional miceCho

w

50 C

ell

200 Cell

200 Ilu

n

Cho

w

50 C

ell

200 Cell

200 Ilu

n

0

100

200

300

400

Co

lon

Weig

ht

(mg

)

400

600

800

1000

Co

lon

villi len

gth

(m

m)

Effects of inulin are microbiota dependent

Chow - Cell Inul

HFD

Chow - Cell Inul

HFD

GF miceConventional mice


Cry

pt

len

gth

, m

M

HFD alters/depletes microbiota: Inulin restores

Chow - Cell Inul

106

107

bacteria / m

g o

f feces

HFD

Ba

cte

ria/m

g f

ece

s

106

107

Chow

HFD

+ Cellulose

+ Inulin

and changes


Inulin rescues some aspects of HFD-induced

metabolic syndrome

Fa

t p

ad

(m

g) **

***

**

*

Chow

HFD

+50 C

ell

HFD

+200

Cel

l

HFD

+200

Inul

Chow

HFD

+50 C

ell

HFD

+200

Cel

l

HFD

+200

Inul

Chow

HFD

+50 C

ell

HFD

+200

Cel

l

HFD

+200

Inul

500

1000

Epididymal fat

Mesenteric fat

Subcutaneous fat

Fat

pad

(m

g)

Chow

HFD

+50

Cel

l

HFD

+200

Cel

l

HFD

+200

Inul

50

100

150

200

5 h

fasti

ng

glu

co

se (

mg

/dl)

Chow 50 Cell 200 Cell 200 Inul

HFD

**

**

Cho

w

HFD

+50

Cel

l

HFD

+200

Cel

l

HFD

+200

Inul

0

20000

40000A

UC

(T

ota

l A

rea ,

a.u

.)

Chow 50 Cell 200 Cell 200 Inul

HFD

**

**


Inulin increases SCFA levels; blocked by hops b-acids


Blockade of SCFA production did not block inulin’s impact

(SCFA are overrated)


Inulin’s fortification of the gut requires IL-22


Expression of IL-22 Enterocyte

proliferation

Mucosal defense

Antimicrobial

signals (Reg3γ)ILC3

HFD enriched

with fermentable fiber

Microbiota encroachment

Colon atrophy

Adipose inflammation

Metabolic syndrome

Antimicrobial

signals

HFD lacking fermentable

fiber

Dysbiosislumen

HFD alters/depletes microbiota: Inulin restores

Chow - Cell Inul

106

107

bacteria / m

g o

f feces

HFD

Ba

cte

ria/m

g f

ece

s

106

107

Chow

HFD

+ Cellulose

+ Inulin

and changes


“Extreme colitis” in DSS-treated mice fed

inulin-supplemented purified diet

Chow Cell. Inul.

+ DSS

Con

Chow/DSS

Cell./DSS Inul./DSS

Con

Zou et. al. Inflamm. Bowel. Dis. (2017)

Fermentable fiber induces hepatocellular carcinoma

(HCC) in dysbiotic mice

Sing et. al. Cell, In Press

T5KO mice fed defined (10% fat) enriched with inulin

Just bring us some real food with lots of fermentable fiber

Emory/GSU

Vijay Kumar

Fred Carvalho

Benoit Chassaing

Shanthi Sitaraman

Ifor Williams

Andrew Neish

Host Defense, Osaka, JP

Shizuo Akira

Cornell/Max Planck

Ruth Ley

U. Colorado/SanDiego

Rob Knight

Acknowledgements

Supported by NIH

and CCFA

Penn State /Toledo U

Vijay Kumar

Vishal Singh

USDA

Michael Flythe

Genentech

Wenjun Ouyang

Matam Vijay Kumar

Benoit Chassaing

Jun ZouAlexis Bretin

gut microbiota, diet, chronic inflammation and metabolic...

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