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Gut microbiota for health: lessons of a metagenomic scan (by Joel Doré)
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Gut microbiota for health: lessons of a metagenomic scan (by Joel Doré)


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VHIR Seminar led by Joel Doré. Research Director. Institut National de la Recherche Agronomique (INRA). Jouy-en-Josas, France. …

VHIR Seminar led by Joel Doré. Research Director. Institut National de la Recherche Agronomique (INRA). Jouy-en-Josas, France.

Abstract: The human intestinal tract harbours a complex microbial ecosystem which plays a key role in nutrition and health. Interactions between food constituents, microbes and the host organism derive from a long co-evolution that resulted in a mutualistic association.

Current investigations into the human faecal metagenome are delivering an extensive gene repertoire representative of functional potentials of the human intestinal microbiota. The most redundant genomic traits of the human intestinal microbiota are identified and thereby its functional balance. These observation point towards the existence of enterotypes, i.e. microbiota sharing specific traits but yet independent of geographic origin, age, sex etc.. It also shows a unique segregation of the human population into individuals with low versus high gene-counts. In the end, it not only gives an unprecedented view of the intestinal microbiota, but it also significantly expands our ability to look for specificities of the microbiota associated with human diseases and to ultimately validate microbial signatures of prognostic and diagnostic value in immune mediated diseases.

Metagenomics of the human intestinal tract was applied to specifically compare obese versus lean individuals as well as to explore the dynamic changes associated with a severe calory-restricted diet. Microbiota structure differs with body-mass index and a limited set of marker species may be used as diagnostic model with a >85% predictive value. Among obese subjects; the overall phenotypic characteristics are worse in individuals with low gene counts microbiota, including a worse evolution of morphometric parameters over a period of 10 years, a low grade inflammatory context also associated with insulin-resistance, and the worst response to dietary constraints in terms of weight loss or improvement of biological and inflammatory characteristics. Low gene count microbiota is also associated with less favourable conditions in inflammatory bowel disease, such as higher relapse rate in ulcerative colitis patients.

Finally, microbiota transplantation has seen a regain of interest with applications expanding from Clostridium difficile infections to immune mediated and metabolic diseases.

The human intestinal microbiota should hence be regarded as a true organ, amenable to rationally designed modulation for human health.

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  • 1. Gut microbiota for health - lessons of a metagenomic scan Joël Doré Deputy head UMR 1319 Micalis Institute & Scientific Director US 1367 MetaGenoPolis INRA, Jouy en Josas, France
  • 2. Gut microbiota for health: lessons of a metagenomic scan Joël Doré, Photos : INRA UEPSD From the romantic « flora » Faecalibacterium prausnitzii Ruminococcus spp Clostridium difficile in a mouse caecum to the pragmatic ‘microbiota’ Bacteroides dorei Escherichia coli Segmented filamentous bacteria anchored in a Peyer’s Patch of mouse intestin Microscopic counts >> culture counts : great plate count anomaly
  • 3. The human intestinal microbiota  100 trillion microorganisms ; 10 times the number of human cells in our body (Savage 1977) ; >150 fold more genes than in the human genome  Predominantly not yet cultured to date (~70% of dominant species)  Central to Food-Microbiota-Host interactions (crosstalk between microbiome and human genome impact immune, neural and endocrine functions)  Mutualistic association & true organ, « protecting our health and well-being »« throughout all stages of our life » ; and amenable to modulations
  • 4. Phylogenetic view : gut bacteria in the ‘family’ tree of life Bacteroidetes Classification memo: Domain Phylum Class Order Family Genus species (strain) Actinobacteria Single gene 16S rDNA sequence : 3 major phyla among the >50 within currently known bacterial diversity Eckburg et al. 2005 (11831 séquences ; 391 espèces) Firmicutes
  • 5. Phylogenetics of the human intestinal tract Sequence-based phylogenetics of the dominant human intestinal microbiota was initiated in the mid 1990’s DNA amplification & extraction of SSUrDNA Sequencing & phylogenetic profiling Single gene - 16S rDNA sequence based approaches : • A few dominant phyla • High species diversity • Resistance and resilience = homeostasis • A few prevalent & dominant species = Core microbiota
  • 6. ‘sterile’ in utero, the intestine is colonized at birth • colonization is affected by: – – – – – Gestational term Mode of delivery (vaginal delivery or caesarean section) Maternal nutrition and maternal microbiome Hygiene of neonatal environment and antibiotic administration Mode of feeding (breast milk versus bottled milk) and weaning diet • early colonisation & hygiene hypothesis: exposure to low bacterial diversity in the neonatal period would prevent or delay maturation of the mucosal immune system and favor aberrant responses to allergens or auto-antigens and onset of associated pathologies Bach JF. N Engl J Med. 2002;347:911-920 Okada et al Clin Exp Immunol 2010 ; 160:1-9
  • 7. microbiome diversity is low in north-Americans compared to Amerindians and Malawians after the age of 3 Yatsunenko et al. Nature 2012
  • 8. Metagenomics of the human intestinal tract The metagenome is made of the combined genomes of all dominant microbes within a given ecosystem DNA extraction Whole Genome Shotgun sequencing Assembly and annotation Initial pilot studies in sequence based metagenomics: Manichanh Gut 2006 => Healthy versus Crohn Gill Science 2006 Kurokawa DNA Res 2008 Manichanh Nucl Acids Res 2008 Reference gene catalog and gene counts Qin, Raes et al, Nature 2010
  • 9. S.D. Ehrlich J. Doré L. Zhao Ashler Mullard. The inside story, Nature 453. May 2008. … International Human Microbiome Consortium - IHMC : INRA-Paris oct 2005 ; EMBL-Heidelberg nov 2008
  • 10. Humans share a core microbiome, and yet differ at the level of metagenomic species On average, each individual carries ~540 000 genes of the initial 3.3 million genes catalog (Qin, Raes et al, Nature 2010) Similarity: Yet, individuality: Core metagenome genes : ~50 % of an individual’s genes are shared by at least 50 % of individuals of the cohort Rare genes : genes shared by less than 20 % of individuals = 2.4 million genes We are all rather similar!, but not identical!!
  • 11. Humans differ at the level of ecological make-up of their intestinal microbiota In an attempt to characterize the ‘average’ human intestinal microbiota, we observed … An organisation of intestinal microbiomes into three assemblages of genes and microbial taxa that were named enterotypes: Arumugam, Raes et al, Nature 2011 … order in chaos !?! … les ‘entérotypes’
  • 12. Arumugam, Raes et al, Nature 2011 Humans studied so far belong to one of three enterotypes Danes n=85; Illumina Europeans, Americans, Asians. n=33 Sanger US n=154; 454 Bacteroides Prevotella Ruminococcus 3 enterotypes ; 3 microbial drivers ; 3 ecological settings
  • 13. Enterotypes may be regarded as preferred patterns in the ecological landscape of human intestinal microbiome Scheffer, Nature 2001 Data density (Fraction of data close to a central point ) ‘Density plots’ pour ~400 échantillons Enterotypes appear as densely populated zones within the ecological landscape of all possible compositions. They strongly suggest ecological driving forces. Arumugam et al. Nature 2012 Each metagenome appears quite stable, even at the finest level of nucleotide sequence at which variants (SNPs) remain over time within a person’s microbiome. Schloissnig et al. Nature 2012
  • 14. Sambo-MetaQuant - Quantitative Metagenomics SAMBO samples processing MetaQuant NGS Identification quantification 50+ million tags/sample Stool sample Gene counts profiles Total DNA Cardona et al BMC Microbiol. 2012 MetaHIT & iMOMi Databases • 4 - 8 million genes • 6000+ genomes Gene Catalog • Sub-populations • Client Specific • Environment Specific
  • 15. Humans differ by species, by enterotypes and also by gut bacterial gene counts n=277 Marker species for low/high gene-count microbiota Known species n=10 Low Gene count High Humans intestinal microbiota share large similarities but also differences that permit stratification, with potential applications in personalized / digitized medicine and nutrition Unknown species n=58 Each column is an individual Each row is a gene, 50 are displayed Colors reflect gene abundance low high
  • 16. Gut microbiota is an organ of the host ! Although it has a genome of its own, the microbiota • exerts unique functionalities, essentially protective, many of which are conserved in humans & complementary to human-gene encoded functions • intimately interacts with food and with human cells, with the immune & neural systems, and organs far beyond the gut (liver, adipose tissue, brain) • is markedly distorted in many immune mediated diseases = dysbiosis • is a great source of biomarkers with use in stratification of disease/risk Because it has a genome of its own, it may be modulated, with perspective to maintain or restore normobiosis/homeostasis in disease or risk • in structure and probably even more so in functions • by diet, by functional foods • by full fecal microbiota transplantation (FMT), currently tested in immune disorders (A. Vrieze et al Gastroenterology 2012)
  • 17. 0.1 Metagenomic signatures of dysbiosis in immune mediated diseases inflammatory bowel diseases Guarner (HUVH, Barcelona) Wang Jun (BGI, Shenzen) Ehrlich, Lepage, Tap (INRA) 842 1 5586 aeruginosa.LESB58 ulum.v ariabile us.bromii.L2.63 ubacterium.rectale.M104.1 H1 P76 ndidatus.Sulcia.muelleri.GWSS olescentis ctus anisolv ens.XB1A ens.16.4 .subsp..multocida.str..Pm70 nalis.M50.1 y riv cola ibrio.f ibrisolv L2.50 pillosus ccus.obeum.A2.162 occus.comes.SL7.1 es.merdae oncisus.13826 ardii.ATCC.8290 cae gum.subsp..inf antis.CCUG.52486 uinis.SK36 f ormis p..D1 ves.odontoly ticus ibacter.smithii.DSM2375 mentum.IFO.3956 rev e nensis.DSM.16047 .sp.Nov eticus.DPC.4571 .pamelaeae.gen.nov prophilus eri.SD2112 senteroides.subsp..mesenteroides.ATCC.8293 a.stadtmanae.DSM.3091 generans mutans.UA159 eroides.distasonis.ATCC.8503 ccus.lactaris .thermophilus.LMD.9 coccus.torques.L2.14 antella.f rof orme ormatexigens TCC.25302 us.ATCC.15305 ium.v entriosum us.colihominis is.stercorihominis idium.phy tof ermentans.ISDg AA.381 dium.sp.SS2.1 C.BAA.835 5 d=5 BMI UC Patients Y :UC Crohn Patients N:N Y :CD 842 .siraeum.70.3 1 5586 aeruginosa.LESB58 ulum.v ariabile us.bromii.L2.63 H1 ubacterium.rectale.M104.1 P76 ndidatus.Sulcia.muelleri.GWSS is.SH0165 olescentis ctus anisolv ens.XB1A ens.16.4 .subsp..multocida.str..Pm70 nalis.M50.1 cola ibrio.f ibrisolv y riv pillosus L2.50 ccus.obeum.A2.162 occus.comes.SL7.1 oncisus.13826 antis.CCUG.52486 es.merdae ardii.ATCC.8290 cae gum.subsp..inf uinis.SK36 f ibacter.smithii.DSM2375 p..D1 ormis veticus.DPC.4571 mentum.IFO.3956 rev e es.odontoly nensis.DSM.16047 .sp.Nov .pamelaeae.gen.nov prophilus ormatexigens senteroides.subsp..mesenteroides.ATCC.8293 eri.SD2112 ticus generans us a.stadtmanae.DSM.3091 mutans.UA159 eroides.distasonis.ATCC.8503 .thermophilus.LMD.9 ccus.lactaris coccus.torques.L2.14 antella.f aracasei.subsp..paracasei.ATCC.25302 ssotus rof orme ticus.subsp..saprophy ticus.ATCC.15305 plei.str..Twist nsonii.NCC.533 dens saprophy ium.v tena entriosum us.colihominis is.stercorihominis cter.hominis.ATCC.BAA.381 m.hallii idium.phy tof ermentans.ISDg ansia.muciniphila.ATCC.BAA.835 dium.sp.SS2.1 5 s and obesity Scores and classes Healthy Controls Pedersen (SDC, Copenhagen) Wang Jun (BGI, Shenzen) Ehrlich (INRA, Paris) p-value: 0.031 d=2 We identify bacterial genes & genomes specific of the microbiome of patients
  • 18. Mucosal Dysbiosis in Crohn’s Disease 20 patients with active CD, requiring ileo-caecal resection : Harry Sokol, Philippe Langella et al. PNAS 2008 M0 surgical resection FISH analysis of biopsies •Eub338 (Eubactia) • Bac303 (Bacteroides-Prevotella) • Ent1458 (Enterobacteria) • Erec482 (Clostridium coccoides) • Lab158 (Lactobacillus-Enterococcus) • Bif164 (Bifidobacterium) • Fprau645 (Faecalibacterium prausnitzii) M6 colonoscopy Still in remission or Endoscopic relapse F. prausnitzii at M0 (p=0.027) 3.3% 0.3%  Remission at M6  Relapse at M6 Faecalibacterium prausnitzii is associated with protection from endoscopic inflammation relapse 6 months after surgery. … It’s a bacterial signature of high gene count microbiota …
  • 19. Gut microbial dysbiosis in Crohn’s Disease beyond Faecalibacterium prausnitzii Reference F. prausnitzii under-represented Other species under-represented Sokol et al, PNAS 2008 yes Not explored Willing et al. 2009 yes Subdoligranulum sp, Roseburia sp. Qin et al, Nature 2010 yes yes Kang et al, IBD 2010 yes Ruminococcus sp, Bacteroides group. Mondot et al, IBD 2010 yes Subdoligranulum sp, Ruminococcus sp. Oscillibacter sp, Bifidobacterium sp,.. Joossens et al. 2011 yes Ruminococcus sp, Bifidobacterium sp,.. For review: Legage et al Gut 2012 Many are bacterial signatures of high gene count microbiota …
  • 20. Faecalibacterium prausnitzii in UC: associated with Relapse Rate 10 10 * 9 8 10 7 10 6 10 5 High RELATIVE ABUNDANCE Copies Fp / 1000 Bacteria Copies Fp / g stool CONCENTRATION IN FECAL SAMPLES * 6 4 2 0 Low relapse rate Below 108 copies per g: OR 2.29 (1.07-4.90) for relapsing condition (p<0.05) * p<0.05 vs. High High relapse rate: > 1 per year Low relapse rate: < 1 per year High Low relapse rate Below 3 copies per 1000: OR 3.13 (1.40-6.96) for frequent relapsing condition (p<0.01) Recovery of the F. prausnitzii population after relapse was associated with maintenance of clinical remission Varela, Manichanh et al, APT 2013 … It’s a bacterial signature of high gene count microbiota …
  • 21. associated to time since last relapse: associated to relapse frequency: most frequent relapses in low gene counts Nulber of genes per dominant metagenome Low Gene-counts in UC: associated with higher Relapse Rate
  • 22. Low Gene-counts in UC: predictive of non-response to microbiota stabilization by a probiotic 2 weeks run-in Probiotic versus placebo consumption T0 (baseline) T2 (12 sem.) T1 (6 sem.) Randomized Double-Blind Placebo-Controlled Trial Microbiome stability computed based on quantitative metagenomic profiling p=0.01 p=0.06 p=0.01 Microbiota stability Microbiota stability p=0.06 controls Placebo Probiotic All patients Placebo Probiotic High gene-count microbiome patients Microbiome diversity permits stratification in responders/non-responders. HUVH, Barcelona, Guarner et al.; Danone, Derrien et al.
  • 23. Intestinal Microbiota and Obesity in human Metagenomic species show a good discrimination power between obese and lean, in contrast to human genome 12 MGS AUC = 0.84 n= 154 Danes True positive Linear additive model ROCs for individual MGS 18 obesity risk loci AUC = 0.58 n = 6,510 middleaged Danes False positive rate Andreasen et al. Diabetes 2010 Le chatelier et al, Nature, 2013 False positive
  • 24. Low gene count n=31 High gene count n=68 ∆ 240 K genes, 40% Low gene count n=13 High gene count n=23 ∆ 230 K genes, 35% Micro Obes The low gene count individuals display increased adiposity, insulin resistance, dyslipidaemia, and inflammation Le chatelier et al, Nature, 2013; Cottillard et al, Nature, 2013
  • 25. Obese people differ by gut bacterial gene counts, and species Each column is an individual Each row is a set of 50 gene per species Colors reflect gene abundance low high 6 weeks hyper low caloric diet Le chatelier et al, Nature, 2013; Cottillard et al, Nature, 2013
  • 26. Low Gene-counts in obesity: predictive of a poor response to nutritional intervention intervention stabilization Low High High gene count patients Low gene count patients Time (weeks) Although partly corrected by calory-restriction, a low gene count of the microbiota predicts a lesser response in terms of weight loss, insulin resistance and correction of inflammatory tone intervention 1200-1500 Kcal : low fat, high protein and low glycemic index carbohydrates with a large variety of fibers from fruits and vegetables. Cotillard et al, Nature 2013
  • 27. Functional and phylogenetic shifts in the LGC microbiome Le chatelier et al, Nature, 2013
  • 28. Microbiome diversity is a key stratifier : A low gene count (low species richness) microbiome may predict less healthy outcome in Spanish UC patients (F Guarner, Barcelona): • diversity is consistently lower in patients microbiota • Lower gene count predicts higher relapse rate of chronic acute phases in Danish obese patients (O Pederson, Copenhagen): • indicates higher weight gain over time • higher inflammatory context and biomarkers of risk of comorbidities in French obese patients (K Clément, Paris): • higher inflammatory context and biomarkers of risk of comorbidities • Low gene count predicts worst response to calory-restricted diet in terms of weight loss, improvement of inflammatory tone, Micro Obes biology and adiposity.
  • 29. Dysbiosis/loss of diversity (richness) => also loss of host-microbiome crosstalk? Microbiome-transcriptome correlation analysis in genetically identical humans: healthy individuals UC-affected discordant twins host transcripts quantitative data spearman rank correlation -0.5<r<0.5 false discovery rate ≤ 5% bacterial genera no correlation positive correlation negative correlation Lepage & Häsler et al., Gastroenterol 2011 Stefan Schreiber Lab
  • 30. Why bother ? Dysbiosis/loss of diversity => loss of host-microbiome crosstalk? Microbiome-transcriptome correlation analysis in genetically identical humans: healthy individuals UC-unaffected UC-affected discordant twins discordant twins host transcripts  Loss of correlation  Genetic effect  Non-genetic effect bacterial genera no correlation positive correlation negative correlation Lepage & Häsler et al., Gastroenterol 2011 Stefan Schreiber Lab
  • 31. Dysbiosis in chronic immune diseases: the vicious circle should be tackled and broken chicken or egg ; does it matter? … by a combined modulation of: Environment, Environment, microbiota Genetic Predisposition inflammation ! and diet, life-style diet, life-style Stressors Dysbiosis of the Gut Microbiota & crosstalk Low grade inflammation Stressors Altered intestinal ecology vicious circle … with fascinating questions altered host physiology of intestinal ecology
  • 32. Microbiota remodeling may be associated with a resolution of insulin resistance – 2 examples Fecal Microbiota Transplantation in T2D patients Bariatric Surgery in morbid obesity : gut microbiota & crosstalk modulation Increased diversity & restored crosstalk Vrieze et al, Gy, 2012 Kong et al, Am J Clin Nutr, 2013
  • 33. Causal agents, contributors, consequence ? Play a role in chronicity ? Mechanisms ? As opposed to pathogens - host interactions, the cross-talk mechanisms with the commensal microbiota are poorly understood Which are the genes (and from which bacterial species) that are responsible for interactions with the host and what are their role ? (Inflammatory or anti-inflammatory effects ? …) How to study these interactions when 70 to 80 % of the commensals are not yet cultured ? Functional metagenomics
  • 34. Functional Metagenomic - 1 Selection Bacterial Fraction Metagenomic DNA Picking Epi FOS-5 Cloning in E. coli Gloux et al., AEM, 2007 Lakhdari et al., PLoS one, 2010 Metagenomic Library
  • 35. Functional Metagenomic - 2 9 Metagenomic libraries = 340 000 clones Metagenomic Library HTS Human Intestinal Epithelial reporter cells (Luciferase) Gloux et al., AEM, 2007 Lakhdari et al., PLoS one, 2010 Identification of • clones • genes • molecules modulating key functions in IECs 30 bioactive clones • Immunity (NF-kB) • Cell Proliferation • Metabolism (PPAR g)
  • 36. Commensal bacteria develop functional crosstalk with human cells (epithelial, immune cells, beyond..) Modulation of immune functions - NF-kB & AP1 pathways, TSLP, … Transcription factors Genes of interest Modulation of epithelial cell turnover - AP1, … Modulation of cellular metabolism - PPAR gamma, Fiaf, … 20 screens developed ; >50,000 clones or strains screened ; ~ 30 bioactive clones and strains identified Lakhdari 2010, 2011, Madi 2010, Gloux 2011, Kaci 2011, Nepelska 2012, Santos Rocha 2012, Cultrone 2013
  • 37. Immunomodulatory metagenomic clones on NF-kB Activators of immune defenses NF-kB activity stimulators Metagenomic Clones Control E. coli inhibitors Inhibitors, anti-inflammatory Growth of metagenomic clones Growth of metagenomic clones (DO 600nm) Lakhdari et al, PLoS One 2010
  • 38. Clone 5A LAB F4 (from Healthy library) M.Nepelska Stimulates NF-kB, AP1 pathways & TSLP in HT-29, and PIgR & TSLP in Caco-2 Sequence related to Firmicutes (C. Leptum, F. prausnitzii) Secreted factor: trypsin sensitive, heat resistant, 2-3 kDa Key genes for bioactivity encode ABC transporters Bioactivity is MyD88 independent hence TLR independent 2500 *** * Il-8 (pg/ml) control PMA LB Epi F4 6A5 D5F4t * 2000 1500 1000 500 THP-1 MyD88-/- t D5 F4 6A 5 F4 Ep i LB co nt ro l PM A 0 1.0 0.5 2 3 4 LP S Transposon insertions are in ABC transporters (18 KO/200 mutants) EZ-TN5 1 Il1 TN F A ep i F4 5 0.0 co nt ro l OD(600) THP-1 *** 1.5 Also stimulates IL-8 secretion 5 6 7 8 9 10 11 12 13 14 15 16 17 181920 21 23 24 22 25 26 27 28 29 30 31 32 33 34 35 36 38 37 39 EZ-TN5 40 41 42 43 44 45 46 47
  • 39. New experimental approach to study the properties of probiotics and bioactive metagenomic clones Tsilingiri et al Gut 2012 luminal compartment Sealed cylinder Glue Tissue specimen Organ culture inset Collab. with Maria Rescigno et al, IEO - Milan
  • 40. Bioactive metagenomic clone F4 protects against Salmonella (FB62)-induced tissue destruction Tissue with without Salmonella control medium control E.coli CTRL EPI300 clone F4 F4 luminal compartment Sealed cylinder Glue Tissue specimen with Salmonella FB62 Organ culture inset Tsilingiri 2012 FB62 EPI300 + FB62 Collab. with Maria Rescigno et al, IEO - Milan F4 + FB62 human tissues
  • 41. Key messages : 1) Reduced microbial diversity (species richness) is a robust indicator of altered intestinal ecology and physiology 2) Altered intestinal ecology associated with immune-mediated disease conditions may correspond to alternative stable states 3) Whether cause or consequence, altered intestinal ecology may contribute to the maintenance of chronic conditions with altered crosstalk between the gut and the microbiota 4) A dietary intake of diverse plant fibers may promote microbiota diversification 5) Non-empirical interventions to restore normobiosis and healthy crosstalk will require a thorough understanding of gut ecology… 6) Functional metagenomics, a new window into microbe-cell crosstalk 7) Microbiome-based stratification appears promissing --/--
  • 42. Stratification based on microbiome - future perspectives Relevant to the push for personalized and digital medicine Relevant for health, preventive nutrition and medical applications  Prediction of responders / non-responders  Prediction of relative risk of disease onset in healthy subjects  Prediction of risk of aggravation and co-morbidities in patients Useful to assist in diagnosis/prognosis, in prescription and clinical management of patients Useful to provide rationale targets and strategies for microbiota modulation
  • 43. Full and Complete understanding of Human Physiology Blottière, De Vos, Ehrlich and Doré, COMICR, 2013
  • 44. Merci de votre attention INRA Jouy-en-Josas Christel Béra-Maillet Hervé Blottière Marion Leclerc Patricia Lepage Catherine Juste Nicolas Lapaque Tomas de Wouters Antonella Cultrone Malgorsata Nepelska Elsa Jacouton ChenHong Zhang Julien Tap Stanislas Mondot Omar Lakhdari European Community & ANR-France S Dusko Ehrlich, Jean Weissenbach (Genoscope, Evry), Wang Jun (BGI, Shenzhen), Peer Borck (EMBL Heidelberg), Francisco Guarner (Val d’Hebron Hospital Barcelona), Oluf Pedersen (SDC Copenhagen), Maria Rescigno (IEO Milan), Liping Zhao (Shanghai JiaoTong University), Jim Versalovic (Baylor College of Medicine, Houston), Baghi Singh (Western Ontario, London) and EUMetaHIT and IHMS Consortia Karine Clément (INSERM U972, CR des Cordeliers), Denis Le Paslier & Eric Pelletier, (CEA-Genoscope), Liping Zhao (Shanghai JiaoTong University) and ANR MicroObese consortium A PLATFORM OF EXCELLENCE DEDICATED TO QUANTITATIVE AND FUNCTIONAL METAGENOMICS, FUNDED BY FRENCH GOVERNMENT’S FUTURES INVESTMENTS Philippe Langella and col. Bruno Pot Corinne grangette and col. Micro Obes Philippe Seksik Harry Sokol Philippe Marteau http://
  • 45. Muchas gracias & please, come visit our new web-platform !