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Human intestinal microbiota in health and disease- a microbiomics perspective -
Joël DoréINRA, Micalis, Jouy-en-Josas, France
Metagenome MetaprotomemRNADiversity, composition
Integrated microbiomics view:
Metabolome
Species diversity profiling indicates high inter-individual variations …
Zoetendahl et al. 1998 ; Sutren et al. 2000Seksik et al. 2003 ; Vanhoutte et al. 2004
14 healthy adults
…and stability over time
2 healthy adults
months
Only a fewbacterialspeciesappearconserved
Dominant microbiota
Sub-dominant microbiota
TransitingBacteria
1012
1011
1010
109
108
107
106
105
Bacteria/gfeces
L.rham
nosu
s
Lc lactis
L.plan
tarumL. c
aseiS.
therm
ophil
us
Phylogenetic groups and spp(qPCR assessment)
Enterococcus
E. coli
LactobacillusLeuconostoc
S. salivarius
BacteriaC. Leptumgroup
C. Coccoidesgroup
BacteroidesPrevotella
group
Bifidobacterium
J-P Furet et al., 2009
• Colonisation and immune imprinting - early times –
• Early colonisation and geographical location
w = weeks Mq = marqueur
Molecular signatures shared by different biological fractions Potential transfer from mother to newborn via maternal milk Streptococcus salivarius, Staphilococcus epidermidis, Bif. longum
P. Perez et al. 2007 Pediatrics
Maternal milk, source of active immune imprinting(n=7 mother-newborn couples)
Mq 2w 3w 4w 1w 2w 3w 4w1w 2w 3w 4w 1w 2w 3w 4w Mq Mq
Feces Blood cells Milk cells Feces
Mother NewbornBlood cellsBlood cells
Human milk cellHuman milk cell
Infant fecal microbiota differs from that of adults, until 2nd year of life.
Genus Bifidobacterium is most representedBacteroides and relatives are early colonizers following enterobacteria.Adult phylogenetic groups C. coccoides and C. leptum are not ‘yet’ dominant.
M. Fallani et al., JPGN 2010
0,42,4
0,8 1,83,5
42,2
5,6
11,1
74,0
6,1
0
20
40
60
80
100
Bifido
bacte
riaC.
cocc
oides
C.lep
tum
Atop
obium
Bacte
roide
sEn
tero
bact
eria
Lact
obac
illae
Stre
ptoc
occi
C.pe
rf+
C.dif
sp.
Tota
l%
n=606 ; 5 EU countries
Fecal microbiota of 6 weeks-old European infants FISH-FCM
Somme
Bifidobacterium
Nord-South gradient from Stockholm, Sweden to Granada, Spain : more bifids in the north ; early diversification in the south
(n=606)
Fecal microbiota of 6 weeks-old European infants
Spain
Sweden
Birth location has an incidence on composition of the fecal microbiota.
M. Fallani et al., JPGN 2010
Montecarlo testP = 0.024
age-related Bacteria
70 100Elena Biagi – Patrizia Brigidi –Claudio Francesci - University of Bologna
Lotta Nylund , Reetta Satokari & Willem M. de Vos University of Helsinki & Wageningen
the dominant fecal microbiota of elderly - specific alterations at the level of dominant species -
Under-represented:
Faecalibacterium sp.
Over-represented:
OxalobacterAkkermansia
Bifodobacterium
Metagenome MetaprotomemRNADiversity, composition
Core species Core genes
2% of non- 9% of non-redundant redundant
Core microbiome of the « normal » microbiota of healthy subjects ; a schematic view
Metagenome MetaproteomemRNADiversity, composition
inter-individual redundancy within theintestinal ecosystem at the level of
environmental proteome ?
Cy3 Cy5
Cy3 Cy5
Cy5Cy3
1092 proteins commonto both subjects
397 proteinsspecific to subject 1
376 proteinsspecific to subject 2
1865 validated spots~ 59 % comigrating spots *
for 2 metaproteomes
subject 1
subject 2
Juste et al, unpublished
Core-proteins
Metaproteome of human intestinal microbiotaPilot study in 6 volonteers / cytosolic proteins of fecal bacteria
* up to 15% may be host proteins
Metagenome MetaprotomemRNADiversity, composition
Core microbiome ; a schematic view
Core species Core genes Core proteins
66/>1000 1,000’s / 3M 100’s />2000
Defining “normal” microbiota - Eubiosis - : density, diversity, composition, core-species, dynamics (stability and resilience) of structure and functions (core-microbiome),
Hence, it becomes possible to explore Dysbiosis of the dominant intestinal microbiota in patients compared to healthy subjects.
This opens novel fields of exploration : – rationality for strategies to restore Eubiosis / homeostasis.
– mechanisms by which dysbiosis of the intestinal microbiota acts in chronic, immune, metabolic or degenerative pathologies ; especially in the context of bacteria-cell crosstalk…
Eubiosis versus Dysbiosis
Frailty in seniors Van Tongeren et al., 2005Crohn Seksik et al., 2003; Sokol et al., 2006, 2008, 2009; Qin et al., 2010Ulcerative colitis Sokol et al., 2008; Martinez et al., 2008 Hutson unpublishedPouchitis Lim et al., 2009, Kühbacher et al., 2006Obesity Ley et al., 2007; Kalliomäki et al., 2008; Furet et al. 2010Type-2 diabetis Cani and Delzenne, 2009 ; Sun et al., 2010Type-1 diabetis Dessein et al., 2009; Wen et al., 2008Coeliac disease Nadal et al., 2007; Collado et al., 2009Allergy Kirjavainen et al., 2002; Björkstén, 2009Autism Finegold et al., 2002; Parracho et al., 2005
Disease suspicion for an involvement of the commensal microbiota(Animal studies, antibiotics, probiotics or clinical studies)
Indicators of dysbiosis in disease versus health
Bach JF, N Eng J Med 2002
Importance of microbiota inimmune diseases increasing in prevalence ?
INCIDENCE OF CROHN’S DISEASE
0
5
10
15
1920 1940 1960 1980 2000
US & CanadaSwedenUKSouth AfricaFranceItalySpainJapan
Cases per 100.000 persons-year
Data from Ekbom et al, in McDermott & Stenson ‘IBD’
PEDIATRIC CROHN’S DISEASE IN SCOTLAND
0
5
10
1920 1940 1960 1980 2000
UK
Cases per 100.000 persons-year
Sawcenko et al, Lancet 2001
In children <16 years
EPIDEMIOLOGY OF IBD:GENETIC SUSCEPTIBILITY
• First-degree relatives: RR 10.7 for IBD
• Concordance rates for IBD in twin pairsfor CD monozygotic twins: 33-50%dizygotic twins: 0-10%
for UCmonozygotic twins: 13-19%dizygotic twins: 0-5%
Orholm et al, N Eng J Med 1991; Thompson et al, BMJ 1996; Orholm et al, Scand J Gastroenterol 2000; Halfvarson et al, Gastroenterology 2003
Inflammatory Bowel Diseases- Crohn’s disease- Ulcerative colitis
Dysbiosis of the Gut Microbiota ?
Deregulation of the Immune Response
Genetic Predisposition
MUCOSA ASSOCIATED MICROBIOTA IN IBD
Ott et al,
GUT 2005
Number of spp.Diversity index
Num
bero
fspp
.
Div
ersi
tyin
dex
Quantitative distortion in the density of mucosal microbiota(Swidsinski et al., Gastroenterology 2002)
Higher bacterial concentrations in mucosa associated microbiota of CD patients
Mucosa associated microbiota in IBD
Reduced Microbial Gene Diversity in IBD
Bacteroidetes371 clones33 OTUs
Firmicutes89 clones43 OTUs
20 (6)
79 Bifidobacterium longum (7)78 Bifidobacterium sp. (6)
81 Corynebacterium lipophiloflavum (3)80 Brachybacterium paraconglomeratum (1)
84(15)82 Coriobacterium sp. (17)
83(1)19 HuCC28 (14)
21 Adhufec61 (51) 22 Adhufec41 (9)
25 Bacteroides splanchnicus (2) 16 Adhufec367 (22)
18 Bacteroides vulgatus (77) 17 HuCB3 (5)
15 Adhufec151 (10)12 (33)
13 (10)14 (4)7 HuCA21 (1)
8 Bacteroides caccae (1)4 (1)
3 (1)1 Bacteroides thetaiotaomicron (4)
6 HuCC30 (3) 5 Bacteroides ovatus (3)
10 Bacteroides stercoris (16) 9 Bacteroides uniformis (56) 11 Bacteroides eggerthi (4)
24 Bacteroides merdae (3) 23 Baceroides distasonis (17) 30 (1)
34 (2) 33 (1)
31(1)32(1)
26 (1) 27 (2)
29 Bacteroides putredinis (4) 28 HuCB23 (5)
89 Bilophila wadsworthia (4)88 Escherichia coli K12 (16)
87 (1)86 (3)85(1)
71 Cadhufec079h7 (1)72 Dialister invisus (1)
70 Eubacterium biforme (1)44 (1)
45 (2)46 Cadhufec14h7 (11)
48 (2)47 Ruminococcus sp. (1)
49 (1)51 ckcm323-B (1)50 (1)
39 p-5459-2Wb (3)40 HuCB5 (8)
41 p-2559-9F5 (2)42 butyrate producing M12/2 (5) 43 Adhufec365 (2)
35 Adhufec311 (1)36 p-2053-s95 (1)37 Adhufec269 (2)
38 p-953-s962 (1)75 (1)
77 (1)76 (1)
73 HuCA6 (1)74 (1)
69 Clone p-2722 (1)54 Adhufec406 (1)
52 (1)53 Butyrovibrio crossotus (4)
62 C. catus (1)58 Uncultured bacterium A20 (5)60 Uncultured bacterium G36 (1)59 HuCB12 (2)
57 HuCA22 (1)55 p-3075-SwA (1)
56 (2)61 Cadhufec001h7 (2)66 p-2431-55G (1)68 HuCB10 (2)
67 (1)64 butyrate producing M104/1 (8)
65 butyrate producing M72/1 (1)63 Lachnospira pectinoschiza(1)
68
52
58
68 98
92
52
100
56
72
45 clones17 OTUs
35 clones17 OTUs
Proteobacteria25 clones5 OTUs
Actinobacteria50 clones7 OTUs
Clostridiumleptumgroup
Clostridiumcoccoides
group
Metagenomicclone name(Adhufec-x)
clone number
Healthy library
Bacteroidetes556 clones33 OTUs
Firmicutes37 clones13 OTUs
14 (3)15 (1)
51 Coriobacterium sp. (1) 56 Desulfovibrio piger (1)
49 Bifidobacterium pseudolongum (28) 50 (1)
40(5)39 (4)
41 (3)42 (2)43 (1)47 (3)
38 (1)36 (4)
34 HuCB5 (3) 35 butyrate producing M21/2 (2) 37 (1)
45 (1)44 (7)
52 Escherichia coli K12 (27) 55 (1)
54 (1)53 (1)
29 (1)23 Bacteroides putredinis (38) 31 (3)
30 (1)22 (1) 28 (1)
24 (6)25 (57)26 (30)
27 (1)21 Bacteroides splanchnicus (9)
19 Bacteroides merdae (34) 18 Bacteroides distasonis (10)
20 (1)33 (37)
32 (12)16 (2)11 HuCC21 (2)
17 (7)13 (1)
12 Adhufec61 (68) 9 (5)6 Bacteroides vulgatus (91)5 Adhufec367 (18)
7 (1)8 (3)
4 Bacteroides stercoris (15) 10 (7)
1 Bacteroides ovatus (2) 2 HuCC30 (17) 3 Bacteroides uniformis (71)
5194
30
87
100
35
14 clones5 OTUs
15 clones6 OTUs
31 clones5 OTUs
Proteobacteria
30 clones7 OTUs
Actinobacteria
Clostridium coccoidesgroup
Clostridium leptumgroup
Metagenomicclone name(Cadhufec-x)
clone number
Crohn library
Manichanh et al, Gut 2006
Fecal microbiota dysbiosis in Crohn’s disease
Lesser proportion of bacteria from the Clostridium leptum group in CD
In Feces In Mucosa
Fecal and mucosal microbiota dysbiosis in Crohn’s disease
Harry SokolManichanh et al., Gut 2006, Sokol et al., IBD 2006
FISH analysis of biopsies
M0surgical resection
M6colonoscopy
• Eub338 (Eubactia)• Bac303 (Bacteroides-Prevotella)• Ent1458 (Enterobacteria)• Erec482 (Clostridium coccoides)• Lab158 (Lactobacillus-Enterococcus)• Bif164 (Bifidobacterium)• Fprau645 (F. prausnitzii and relatives)
Still in remission
or
Endoscopic relapse
20 patients with active CD, requiring ileo-caecal resection :
Mucosal Dysbiosis in Crohn’s DiseasePh. Marteau & Ph. Pochart
Harry Sokol, Philippe Langella et al. PNAS 2008
FISH analysis of biopsies
M0surgical resection
M6colonoscopy
• Eub338 (Eubactia)• Bac303 (Bacteroides-Prevotella)• Ent1458 (Enterobacteria)• Erec482 (Clostridium coccoides)• Lab158 (Lactobacillus-Enterococcus)• Bif164 (Bifidobacterium)• Fprau645 (F. prausnitzii and relatives)
Still in remission
or
Endoscopic relapse
F. prausnitzii at M0 (p=0.027)3.3% Remission at M60.3% Relapse at M6
Faecalibacterium prausnitzii is associated with protection from endoscopicinflammation relapse 6 months after surgery => anti-inflammatory properties
20 patients with active CD, requiring ileo-caecal resection :
Mucosal Dysbiosis in Crohn’s DiseasePh. Marteau & Ph. Pochart
Harry Sokol, Philippe Langella et al. PNAS 2008
A commensal bacterium with anti-inflammatoryproperties in vitro and in vivo
Sokol, et al. PNAS 2008Willing et al. IBD 2009 [dysbiosis : F prausnitzii - ; E coli + in ICD ]
Faecalibacterium prausnitzii ;
Anti-inflammatory properties of F. prausnitzii
Anti-inflammatory properties of F. prausnitzii A2-1651. In vitro experiments:• High IL10/IL12 cytokine release by Peripheral blood mononucleated cells
• Reduction of IL-1β induced IL-8 secretion by Caco-2 cells
• Supernatant abolished TNFalpha induced NF-kB activity in HT-29 cells
2. In vivo experiments:• Both F. prausnitzii and its supernatant reduced scores and blood parameters of
inflammation in TNBS-induced colitis in Balb/c mice • Administered IP, its supernatant protected mice from death induced by TNBS.
Sokol et al. PNAS 2008
TNBS induced Colitis :intraperitoneal administration of F. prausnitzii fractions
F prausnitziiSupernatant
DexamethasoneTNBS + PBS
0%
20%
40%
60%
80%
100%
D5 D10 D15 D20D2
Survival rate
Faecalibacterium prausnitzii supernatant contains “bioactives” that confer protection against a lethal condition caused by TNBS induced gut inflammation
Seungha Kang, Chris McSweeney, Mark Morrisson
qPCR validation of fecal microbiota dysbiosis (phylogenetic µarray) in Crohn vs healthy subjects
-30
-25
-20
-15
-10
-5
0
5
10R.albus
F.prausnitzii
specific PCR Systems
Fact
or(h
ealth
y/cr
ohn)
C.difficile
E.faecalis
Profiling-based assessment of fecal dysbiosis (PCR-DGGE) in Crohn patients vs healthy subjects
Several candidate marker-species differed in prevalence and relative intensities (P<0.05) and F. prausnitzii, B. adolescentis and R. gnavus were validated by qPCR
M. Joossens et al. submitted
RT-qPCR validation of fecal microbiota dysbiosis (metagenome) in Crohn patients vs healthy subjects
Crohn patients
Healthy controls
O. valericigenes is detected in 12% of Crohn patients vs 93% of controls, and with a higher abundance in controls than in CD patients (ΔCt = 17.33, P<0.001)
Subdoligranulum sp. R. bromii B. vulgatusP. distasonis O. valericigenes E.coli
S. Mondot et al. IBD 2010
S. Mondot et al. IBD 2010
Faecalibactrerium prausnitzii
Fecal microbiota dysbiosis (µarray) in Crohn patients vs healthy subjects (n=14+16)
d = 5
Scores and c lasses
N :N
Y :C D
Y :U C
Ax is3
d = 2
Y :U C
p-value: 0.031
Fecal Dysbiosis in Crohn’s Diseaseat the level of metagenome
Crohn Patients
UC Patients
HealthyControls
Francisco Guarner (Val d’Hebron Hospital, Barcelona)Wang Jun and colleagues (BGI-Shenzen) Junjie Qin et al Nature, March 2010Dusko Ehrlich, Patricia Lepage, Julien Tap (INRA)
• A cohort of 21 Spanish individuals• patients: n = 8• healthy: n = 13•Ranksum search for genes different in frequency(hits/kb/30 million reads) between the two groups in a 3.3 million gene catalog
3802 “CD related genes” found at p< 3*10-4
Ehrlich et al.
Fecal Dysbiosis in Crohn’s Diseaseat the level of metagenome : CD related genes can be identified.
Phenotype CD genes (median)
Healthy 3038 out of 562 271CD 643 out of 425 397
“Gene loss” in CDp<2*10-13
(one‐tailed t test)
HealthyPatients
Ehrlich et al. => diagnostic model with a limited set ofmarker-species (5 Firmicutes candidates)
Fecal Dysbiosis in Crohn’s Diseaseat the level of metagenome : CD related genes can be identified.
12 participants (age & sex matched)6 Crohn’s Disease patients (CD) vs 6 healthy controls (HC)
Catherine Juste & Saint-Antoine Hospital INRA platforms PICT & PAPSSO
-2.0 -1.5 -1.0 -0.5 0. 0 0.5 1.0 1.5 2.0
Log2 Fold Change
threshold
39 under-expressed in CD 41 over-expressed in CD
B s
tatis
tic
unchanged
Differential protein expression from 2D-DIGE experiments
Protein spot identification using LC-MS/MS, in progress:- 66 spots identified out of 84 already analysed (~78% yield)- over-expressed proteins associated with Bacteroides (several known as “immunoactive”, and/or with eucaryotic homologs)- under-expressed proteins mainly associated with Firmicutes
2007 spots
Participants (duplicates)
HCCD
Prot
eins(
80 d
iffer
entia
llyex
pres
sed)
Metaproteomic signatures in Crohn
PLS-DA Scores plot, R2Y=89.7%, Q2Y=61.1%
Control
Crohn’s
PCA Scores plot (Paretto Scaling)
Highlights several discriminating metabolites (under-represented in Crohn)
Metabolomic signatures in Crohn12 volonteers : 6 healthy vs 6 Crohn
Jansson et al (PLoS ONE July 2009) : metabolites discriminating ICD from CCD and health
Tyrosine metabolism, amino-acids, bile acid metabolism, …
Bile acid metabolism in ICD > CCD > Healthy (P value concn. ICD vs others)Glycocholate 5/6 4/8 0/10 .001Taurocholate 5/6 2/8 2/10 .002Glycochenodeoxycholate 5/6 2/8 1/10 .002
Dysbiosis in Crohn’s disease => vicious circle favoring aggravation and chronicity• increased bacterial density at mucosal level (Swidzinski 2002)• increased proportion of immuno-agressive commensals
(Gram-negative, subdominant in health?) (Darfeuille Michaud 2004, Sokol 2009, Willing 2009)• reduced proportion of anti-inflammatory commensals
(Gram-positive Firmicutes?, Actinobacteria?) (Sokol 2009, Willing 2009)• increased proportion of proteins potentially promoting auto-immunity (Juste submitted)
Further contributions of Dysbiosis : disruption of tolerance, alteration of mucosal healing, secretion of defensins, … ?
Dysbiosis of the Gut Microbiota
Deregulation of the Immune Response
Genetic Predisposition
Complex interactions underlying polygenic obesity
NutritionExercise Viruses
AllergiesSocial Status
Food Abundance
Peer pressure
PollutionTechnologicalProgress
Psychology
NutritionExercise Viruses
AllergiesSocial Status
Food Abundance
Peer pressure
PollutionTechnologicalProgress
PsychologyPsychology
Mutch D & Clement K, Plos genet 2006
GUTMicrobiota
Endo
crin
egl
and
Transcriptional interaction networks in human adipose tissue
Overexpressed in obese AT Underexpressed in obese AT
Centrality (%) Henegar, Genome biology, 2008Prifti, Bioinformatics, 2008
Altered metabolism
Increased inflammation
Bypass surgery Switch of functions / weight loss (3mo)
Overexpressed themes Underexpressed themes
Transcriptional domain cover
Improvedinflammatorycontext
ImprovedMetabolismTissue remodeling
Metabolism & inflammation improvement after GBPMetabolism & inflammation improvement after GBP
Wilcoxon pairé; * p<0.05 vs M0 ; *entre M3 et M6
Before GBP (M0)3m after GBP (M3)6mois after GBP (M6)
Calorie intake (kcal)
** *
Glycemia (mmol/l)
**
hsCRP (mg/dl)* *
Weight (kg)
** *
-22%-50%
0
10
20
30
40
50
60
1 2 3
Leptin (ng/ ml)
0 3m 6m
-50%
* *
0 3m 6m 0 3m 6m
Bacteria groups increasing with weight lossBacteria groups increasing with weight loss
Variation associates (- neg) with corpulence (BMI, FM, Leptin)
But dependant on calorie ( LME).
Wilcoxon, * p<0.05 vs C; Wilcoxon pairé, * vs M0
*
* *
Amount of bacteria = log10 (bacteria) - log10 (total bacteria)
Bacteroides/PrevotellaBacteroides/Prevotella
* *
Associations (-ve) with BMI, FM, Leptin (R -0.53 p < 0.001)
Remained if calorie adjusted
E. coliE. coliPhyllum: ProtéobactériesProtéobactéries
Furet JP, Kong LC et al Diabetes 2010
Positive correlations (+pos) with BMI, % fat mass, Leptin, Insulin (R 0.30, P<0.05) / depend on calorie intake (ajustments)
Wilcoxon paired, * vs M0
* *
BifidobacteriumPhyllum: Actinobactéries
* *
LactobacillusPhyllum: Firmicutes
Bacteria groups decreasing with weight lossBacteria groups decreasing with weight loss
Furet JP, Kong LC et al Diabetes 2010
F.prausnitzii is lower in diabetics Negative correlations with inflammatory markers : basal & kinetics
hsCRP (R -0.39), Interleukin 6 (R -0.35), p< 0.0001
Wilcoxon; * p<0.05 D vs C/ND
Bacteria groups associate with low-grade inflammation F.prausnitzii
C.leptumC.leptum;; Phyllum: Firmicutes
C : control leanD: diabeticsND: non diabetiics*
Furet JP, Kong LC et al Diabetes 2010
ConclConcl (1) Gut microbiota differentially adapts after GBP(1) Gut microbiota differentially adapts after GBP
**differential adaptationdifferential adaptation
Bacteroides(-neg)E.coli(-neg)
Metabolism
BMI, fat mass, Leptin,Insulin, etc
Bifido, Lacto(+pos)
Inflammation
CRPus, IL-6, etc
F. prausnitzii(-neg)
**links (links (BactBact--MetaMeta--InflInfl))
**Food intakeFood intakeModel effectSequencing
? ? ? ? ?
Microbiota-host interactions in obesity & related complications
Cani PD and Delzenne NM. Curr Opin Clin Nutr Metab Care 2007; 10:729–734
Obesity state
Gut Microbiota
?
Conserved traits at various levels of integration :Core microbiome
Criteria to qualify normobiosis/eubiosis
Microbiome specificities in diseases, towards : identification of predictive biomarkers, new targets and strategies for nutritional and/or therapeutic applications
in intestinal disorders