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Oxford Inflammatory Bowel Disease & Hepatology MasterClass
The microbiota of gut and liver disease
Philippe Seksik
Hôpital Saint-Antoine, APHP MMBPI ERL U1057 / UMR7203
Philippe SEKSIK
ABBOTT
BIOCODEX
FERRING
MSD
Disclosures
Gut microbiota
Gut microbiota
Beginning to see the light
Why do we know so little ?
What do we know ? For gut & liver diseases
In the future ?
The gut microbiota
Oxford Inflammatory Bowel Disease & Hepatology MasterClass
3 difficulties in studying the microbiota
MICROBIOTA
All the micro-organisms within the gut
Bacteria
MICROBIOTA
All the micro-organisms within the gut
Bacteria
Virus
MICROBIOTA
All the micro-organisms within the gut
Bacteria
Virus (Phages)
MICROBIOTA
All the micro-organisms within the gut
Bacteria
Virus (Phages)
MICROBIOTA
All the micro-organisms within the gut
Bacteria
Virus (Phages)
Fungi
MICROBIOTA
All the micro-organisms within the gut
Bacteria
Virus (Phages)
Fungi
Archaea
3 difficulties in studying the microbiota
Bacteria
Virus (Phages)
Fungi
Archaea
First difficulty =
EXTREME CULTURE CONDITIONS
Cultivable fraction
20% of gut microbiota
Culture independent methods
Cultivable fraction
20% of gut microbiota
3 difficulties in studying the microbiota
Second difficulty = LARGE NUMBERS
Bacterial populations
Abundance : 1014 bacteria
Diversity : ~ 1000 species
Viral populations
Viral genome = 336Mb vast majority = phages or unknown
Minot S, et al Genome Res. 2011
3 difficulties in studying the microbiota
Third difficulty = COMPLEXITY Ecosystem
Bacteria
IgA
Milieu
Virus
Bacteria
IgA
Milieu
Virus Bacteriocins Quorum sensing
Bacteria
IgA
Nutriments Milieu
Virus Bile Acids
Xenobiotic
Bacteriocins Quorum sensing
Bacteria
IgA
Milieu
Virus Bacteriocins Quorum sensing
Nutriments
Xenobiotic
Bile Acids
Bacteria
sIgA
Epithelium
IgA
tight junctions
specialized cells Paneth, M
Milieu
Mucus
Virus
anti-microbial Peptides
Bacteriocins Quorum sensing
Nutriments
Xenobiotic
Bile Acids
Bacteria
sIgA
Epithelium
IgA
tight junctions
specialized cells Paneth, M
Milieu
Mucus
Virus
anti-microbial Peptides
Bacteriocins Quorum sensing
Nutriments
Xenobiotic
Bile Acids
What do we know ?
1. Implementation composition
2. Stability - change / resilience
3. Functions
3 major findings
What do we know ?
1. Implementation composition
2. Stability - Change / Resilience
3. functions
Implementation composition
Birth: sterile digestive tract
Acquisition of an "adult" microbiota (2-6 years)
Bacterial colonisation
Birth: sterile digestive tract
Acquisition of an "adult" microbiota (2-6 years)
Bacterial colonisation
Environment &
host factors
Fallani et al. JPGN 2010
Host factors
Rawls et al., Cell 2006
Reciprocal gut microbiota transplants
Host factors
Rawls et al., Cell 2006
Reciprocal gut microbiota transplants
Microbiota composition under the control of
genetic determinants
Rawls et al., Cell 2006
Reciprocal gut microbiota transplants
Microbiota composition under the control of
genetic determinants
Stewart et al., J. Med. Microbiol. 2005; Zoetendal et al., Microb. Ecol. Health Dis. 2001; Turnbaugh PJ et al .PNAS 2010
Bacterial populations
Actinobacteria Bacteroidetes
Firmicutes
Three major phyla
Li et al 2008 (n = 5, ~7000 seq) Eckburg et al 2006 (n = 3, ~2500 seq) Manichanh et al 2006 (n = 6, ~500 seq) Gill et al 2006 (n = 2, ~2000 seq)
What do we know ?
1. Implementation composition
2. Stability - change / resilience
3. functions
Stability - change / resilience
Microbiota profile
Unique to each individual
«Bar Code»
Inter individual variability
Species diversity profiling of the dominant fecal microbiota of adults
Zoetendahl et al. 1998 Seksik et al. 2003 Vanhoutte et al. 2004
The faecal microbiota of adults is specific of individuals
14 healthy adults
10
0
95
90
S1
S2
S5
S4
S3
% similarity
Stability over 2 years
The dominant human faecal microbiota is stable
Relative stability in a same individual
Seksik et al. Gut 2003
Profiles in a same individual
Species diversity profiling of the dominant fecal microbiota of adults
Zoetendahl et al. 1998 Seksik et al. 2003 Vanhoutte et al. 2004
The faecal microbiota of adults is specific of individuals
14 healthy adults
Stability - change / resilience
Food
Antibiotics
Intestinal Infection
IBD flare
Others
Ley et al, science 2008
Food intake determines biodiversity
Community structure of faecal microbiota according to diet (cattle)
Diet determines composition
Shanks et al.AEM 2011
40
50
60
70
80
90
100
110
0 1 2 3 4 …. 30 …. 60
Time (days)
sim
ila
rit
y %
***
Dominant human faecal microbiota upon short-course antibiotic challenge (De la Cochetiere et al. JCM 2005)
Erythromycin 500mg/d 4 days
Antibiotics: an ecological disaster
40
50
60
70
80
90
100
110
0 1 2 3 4 …. 30 …. 60
Time (days)
sim
ila
rit
y %
***
Resilience of the microbiota
Erythromycin 500mg/d 4 days
Dominant human faecal microbiota upon short-course antibiotic challenge (De la Cochetiere et al. JCM 2005)
What do we know ?
1. Implementation composition
2. Stability - Change / Resilience
3. Functions
Functions
2 major functions
Metabolic functions
Immune / protection
Metabolic functions
Degradation of sugars, proteins
Control fat storage
Backhed et al., PNAS 2004
bacteria
Substrate
Epithelial cells
Backhed et al., PNAS 2004
Inhibition of fiaf
bacteria
Substrate
Epithelial cells
Selective repression of fiaf expression in the intestine
Backhed et al., PNAS 2004
Inhibition of fiaf
Activation of the LPL Energy recovery from food
bacteria
Substrate
Epithelial cells
Selective repression of fiaf expression in the intestine
Inhibition of fiaf
Activation of the LPL Energy recovery from food
energy balance
inputs
outputs
Better recovery of energy from food
Reduced use of energy reserves
bacteria
Substrate
Epithelial cells
Selective repression of fiaf expression in the intestine
Backhed et al., PNAS 2004
Changes in the intestinal microbiota in obese
Metabolic functions
Degradation of sugars, proteins
Control fat storage
Imbalance in microbiota composition
Dysbiosis
Firmicutes /Bacteroidetes ratio in obese mice and lean mice
Souris ob/ob : mutation sur le gène de la leptine
Relative increase in the Firmicutes at the expense of Bacteroidetes
Actinobacteria Bacteroidetes
Firmicutes
Microbiota in obese
→Dysbiosis
Ley et al., PNAS 2005
Gut microbiota drives the phenotype
Dysbiosis
ob/ob
Gut microbiota drives the phenotype
Dysbiosis
ob/ob
Wild type
Transfer microbiota
Obese phenotype
Dysbiosis
ob/ob
Transfer microbiota
Wild type
Wild type
Gut microbiota drives the phenotype
Example: TLR5 KO mice
Develop a 'metabolic syndrom'
Vigay-Kumar et al. Science 2010
Dysbiosis
TLR 5 KO
Gut microbiota drives the phenotype
Dysbiosis
TLR 5 KO
Transfer microbiota
Wild type
Gut microbiota drives the phenotype
Dysbiosis
TLR 5 KO
Transfer microbiota
Wild type
Gut microbiota drives the phenotype
Metabolic syndrome in wild type mice
Metabolic functions
Steatosis and dysmetabolic steato-hepatitis
Alcoholic hepatitis
Cirrhosis (carcinoma)
IgA plasma cells (repertoire)
Shaping immune response
Anti-microbial peptides
Epithelial proliferation (carcinogenesis)
Immunes / protection functions
Lindner et al. J exp med. 2012
In mice
Segmeted Filamentous Bacteria induit response Th17
Gaboriaud-Routhiau et al. Immunity 2009 Ivanov et al. Cell 2009
Atarashi et al. Science 2011
Shaping immune response
Clostridia : accumulation de Treg (Foxp3+) colon
In mice
Segmeted Filamentous Bacteria induit response Th17
Gaboriaud-Routhiau et al. Immunity 2009 Ivanov et al. Cell 2009
Atarashi et al. Science 2011
Round et al. Science 2011
Shaping immune response
Clostridia : accumulation de Treg (Foxp3+) colon
Bacteroides fragilis (PSA) oriente IL10 Treg
In mice
Feacalibacterium prausnitzii Sokol et al. PNAS 2008
Anti-inflammatory effect Induction of IL-10
Shaping immune response
In mice
Feacalibacterium prausnitzii Sokol et al. PNAS 2008
Anti-inflammatory effect Induction of IL-10
Shaping immune response
Dysbiosis in IBD
R2Ycum=0,719
- 3
- 2
- 1
0
1
2
3
- 6 - 5 - 4 - 3 - 2 - 1 0 1 2 3 4 5 6
t[2]=
0,0
85
t[1]=0,635
R2Ycum=0,772
- 4
- 3
- 2
- 1
0
1
2
3
4
- 5 - 4 - 3 - 2 - 1 0 1 2 3 4 5
t[2]=
0,0
79
t[1]=0,692
IBD in flare
Healthy subjects
IBD in remission
principal component analysis
6.0 3.6 2.4 1.2 1.3
0%
20%
40%
60%
80%
100%
Healthy IBD in remission IBD in flare
Bacteroidetes
Firmicutes
6.0 3.6 2.4 1.2 1.3
Dysbiosis in IBD
Firmicutes / Bacteroidetes
Sokol et al. IBD 2009
Lo
g10 C
FU
/g
*
*
7,00
7,50
8,00
8,50
9,00
9,50
10,00
10,50
11,00
11,50
12,00
Bacteria Bacteroides Firmicutes F. prausnitzii
Flare IBD (n= 35)
IBD in remission (n= 14)
Healthy (n=27)
Sokol et al. IBD 2009
Dysbiosis in IBD
Chronic inflammation
Metabolic activities
SCFA
bile acids
Bacterial toxin (B fragilis)
Wu et al. Nat Med 2009
Goodwin et al PNAS 2011
Epithelial proliferation (carcinogenesis)
Ou et al. Nutr Cancer 2012
Dysbiosis in colo-rectal cancer
Sobhani et al. Plos One 2011
Immune / protection functions
IBD
Colo-rectal cancer
IBS
Infectious-colitis / antibiotic-associated
Intestinal ‘Allergy’ – Celiac disease
Oxford Inflammatory Bowel Disease & Hepatology MasterClass
The Future
Human gut microbiota
Abundance : 1014 bacteria
Diversity : ~ 1000 species
Our other genome
Human gut microbiota
Sum of all bacterial DNAs = Metagenome
Abundance : 1014 bacteria
Diversity : ~ 1000 species
Our other genome
Human gut microbiota
Metagenome (bacterial DNA): ~108 genes
100 to 150 x the human genome
Sum of all bacterial DNAs = Metagenome
Abundance : 1014 bacteria
Diversity : ~ 1000 species
Our other genome
‘Metagenomic’ projects
Mullard A. The inside story, Nature 2008
Description of a bacterial functional core
Turnbaugh et al., Nature 2008; MetaHIT Project ; Qin et al , Nature 2010
Functional core
Description of a bacterial functional core
Turnbaugh et al., Nature 2008; MetaHIT Project ; Qin et al , Nature 2010
38% of the bacterial genes shared by >50% of individuals (9% shared by> 80%)
We are quite the same
Functional core
Description of a bacterial functional core
Turnbaugh et al., Nature 2008; MetaHIT Project ; Qin et al , Nature 2010
38% of the bacterial genes shared by >50% of individuals (9% shared by> 80%)
We are quite the same
Rare Genes Genes shared by ≤ 20 % of individuals = 2.4 millions genes
But far from identical Functional core
Description of a bacterial functional core
Turnbaugh et al., Nature 2008; MetaHIT Project ; Qin et al , Nature 2010
Dysbiosis: differential analysis of the metagenome
Healthy
UC
Crohn’s disease
MetaHIT Project ; Qin et al , Nature 2010
Microbiota +
Integrative platform
Data from the ecosytem
Genetic / metagenomics
Clinical data
Immune responses
Ecosystem interplay
Microbiota +
Integrative platform
Data from the ecosytem
Genetic / metagenomics
Clinical data
Immune responses
Ecosystem interplay
Bio-informatics
Goals
Better understanding of human physiology
To achieve normobiosis
Find new bio-markers
Summary
Gut microbiota = ‘real’ organ
Involved in physiology metabolism, inflammation, cancer
Involved in many gastro-intestinal and hepatic disorders and diseases
Maintaining biodiversity / balance
INRA Jouy-en-Josas Joel Doré Philippe Langella Luis Bermudez Chantal Bridonneau
ERL U1057 Germain Trugnan Ginette Thomas Sylvie Rajca Laurent Beaugerie Joelle Masliah Harry Sokol Bénédicte Arnaud Jean-Pierre Grill Dominique Rainteau Henri Duboc Marie-Anne Maubert Lydie Humbert Elodie Quevrain Antonin Lamazière Jacques Cosnes
UMRS 7203 Solange Lavielle Gérard Chassaing Jean-Maurice Mallet Olivier Lequin Rodrigue Marquant Joelle Runfola
Philippe Marteau