Nicolas Pons INRA Ins(tut Micalis Plateforme MetaQuant Jouy- en- Josas, France

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1 Nicolas Pons INRA Ins(tut Micalis Plateforme MetaQuant Jouy- en- Josas, France

2 Special Science Online Collec-on: Dealing with Data (feb 2011)

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4 DNA Protein

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6 TTGTGGATAACCTCAAAACTTTTCTCTTTCTGACCTGTGGAAAACTTTTTCGTTTTATGATAGAATCAGAGGACAAGAATAAAGA! TGGAGAATTGATAAAATGACCGAAAAAGAGCATTTTTTTTGGAATAAGCTCTTAGAGCTGGCCAAAGAAGAACTAACACAAGCCA! CTTTTGATTATTATGTCCTAGATACCAAGCTCATCAAAATTCAAGATAACGTTGCTACAATTCTGCTTGAAGAAGTCAAGAAACT! TTGTGGATAACCTCAAAACTTTTCTCTTTCTGACCTGTGGAAAACTTTTTCGTTTTATGATAGAATCAGAGGACAAGAATAAAGA! TGGAGAATTGATAAAATGACCGAAAAAGAGCATTTTTTTTGGAATAAGCTCTTAGAGCTGGCCAAAGAAGAACTAACACAAGCCA! CTTTTGATTATTATGTCCTAGATACCAAGCTCATCAAAATTCAAGATAACGTTGCTACAATTCTGCTTGAAGAAGTCAAGAAACT! TTGTGGATAACCTCAAAACTTTTCTCTTTCTGACCTGTGGAAAACTTTTTCGTTTTATGATAGAATCAGAGGACAAGAATAAAGA! TGGAGAATTGATAAAATGACCGAAAAAGAGCATTTTTTTTGGAATAAGCTCTTAGAGCTGGCCAAAGAAGAACTAACACAAGCCA! CTTTTGATTATTATGTCCTAGATACCAAGCTCATCAAAATTCAAGATAACGTTGCTACAATTCTGCTTGAAGAAGTCAAGAAACT! TTGTGGATAACCTCAAAACTTTTCTCTTTCTGACCTGTGGAAAACTTTTTCGTTTTATGATAGAATCAGAGGACAAGAATAAAGA! TGGAGAATTGATAAAATGACCGAAAAAGAGCATTTTTTTTGGAATAAGCTCTTAGAGCTGGCCAAAGAAGAACTAACACAAGCCA! CTTTTGATTATTATGTCCTAGATACCAAGCTCATCAAAATTCAAGATAACGTTGCTACAATTCTGCTTGAAGAAGTCAAGAAACT! TTGTGGATAACCTCAAAACTTTTCTCTTTCTGACCTGTGGAAAACTTTTTCGTTTTATGATAGAATCAGAGGACAAGAATAAAGA! AAAAAGAGCATTTTTTTTGGAATAAGCTCTTAGAGCTGGCCAAAGAAGAACTAACACAAGCCACTTTTGATTATTATGTCCTAGA! CTTTTGATTATTATGTCCTAGATACCAAGCTCATCAAAATTCAAGATAACGTTGCTACAATTCTGCTTGAAGAAGTCAAGAAACT! TTGTGGATAACCTCAAAACTTTATCCGGGTCTGACCTGTGGAAAACTTTTTCGTTTTATGATAGAATCAGAGGACAAGAATAAAGA! TGGAGAATTGATAAAATGACCGAAAAAGAGCATTTTTTTTGGAATAAGCTCTTAGAGCTGGCCAAAGAAGAACTAACACAAGCCA! CTTTTGATTATTATGTCCTAGATACCAAGCTCATCAAAATTCAAGATAACGTTGCTACAATTCTGCTTGAAGAAGTCAAGAAACT! TTGTGGATAACCTCAAAACTTTTCTCTTTCTGACCTGTGGAAAACTTTTTCGTTTTATGATAGAATCAGAGGACAAGAATAAAGA! TGGAGAATTGATAAAATGACCGAAAAAGAGCATTTTTTTTGGAATAAGCTCTTAGAGCTGGCCAAAGAAGAACTAACACAAGCCA! CTTTTGATTATTATGTCCTAGATACCAAGCTCATCAAAATTCAAGATAACGTTGCTACAATTCTGCTTGAAGAAGTCAAGAAACT! TTGTGGATAACCTCAAAACTTTTCTCTTTCTGACCTGTGGAAAACTTTTTCGTTTTATGATAGAATCAGAGGACAAGAATAAAGA! TGGAGAATTGATAAAATGACCGAAAAAGAGCATTTTTTTTGGAATAAGCTCTTAGAGCTGGCCAAAGAAGAACTAACACAAGCCA! AGCTCATCAAAATTCAAGATAACGTTGCTACAATTCTGCTTGAAGAAGTCAAGAAACTCTGGCCAAAGAAGAACTAACACAAGCC! ACTTTTGATTATTATGTCCTAGACTTTTGATTATTATGTCCTAGATACCAAGCTCATCAAAATTCAAGATAACGTTGCTACAATT! TTGTGGATAACCTCAAAACTTTTCTCTTTCTGACCTGTGGAAAACTTTTTCGTTTTATGATAGAATCAGAGGACAAGAATAAAGA! TGGAGAATTGATAAAATGACCGAAAAAGAGCATTTTTTTTGGAATAAGCTCTTAGAGCTGGCCAAAGAAGAACTAACACAAGCCA! CTGGCCAAAGAAGAACTAACACAAGCCACTTTTGATTATTATGTCCTAGACTGGCCAAAGAAGAACTAACACAAGCCACTTTTGA! ATTTTGATTATTATGTCCTAGATACCAAGCTCATCAAAATTCAAGATAACGTTGCTACAATTCTGCTTGAAGAAGTCAAGAAACT! TTGTGGATAACCTCAAAACTTTTCTCTTTCTGACCTGTGGAAAACTTTTTCGTTTTATGATAGAATCAGAGGACAAGAATAAAGA! TGGAGAATTGATAAAATGACCGAAAAAGAGCATTTTTTTTGGAATAAGCTCTTAGAGCTGGCCAAAGAAGAACTAACACAAGCCA!

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11 Year Sequenced object Sequencing unit 1990 Genes & operons Kbase 1995 Bacterial genome Mbase 2001 Human genome Gbase 2010 Human metagenome Tbase Amount of sequence we generate has increased mes in 20 years, greatly exceeding the Moore s law

12 MetaQuant plarorm (since 2008) 1 SOLiD sequencer More than 500 samples 18 E 9 short read sequences 700 E 9 bases files for 20 TB Human Genome Project (2001) 3 years 16 sequencing centers 22 E 9 bases

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14 Data managment Data analysis Data browsing

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16 100 trillion microorganisms ; 10- fold more cells than the human body; 2 kg of mass! Interface between food and epithelium In contact with the 1st pool of immune cells and the 2nd pool of neural cells of the body with a major role in health & disease!

17 Use of Metagenomics

18 can be defined as the ensemble of genes of the microbes from a given ecological niche allows to characterize composi-on, proper-es and dynamics of a microbiome by studying the metagenome

19 Direct lysis of cells from matrix Lysis Metagenomic DNA vectors 16S pyrosequencing 16S primers Recombinant host Metagenomic library Full sequencing Phylogenomics metagenomics screening

20 Short sequences Mapping short sequences and coun2ng genes Stool sample Reference gene catalog Gene abundance profiles Metabolism reconstruc2on Ecosystem reconstruc2on Sta2s2cal analysis & diagnos2c Gene2c variability A powerful microscope!

21 Establishing a reference gene catalog by metagenomic & genomic sequencing of the Human GI tract microbes Developing generic tools for profiling the GI tract microbiota genes : arrays and high throughput DNA sequencing Using Quan-ta-ve Metagenomics to search associa-ons of microbial genes and chronic disease in Obesity and Inflammatory Bowel Diseases

22 Samples Library type Sequencing type Read length (bp) Tags per sample 124 individuals (85 Danes, 39 Spaniards) 15 samples 200bp 109 samples 140bp 350bp Paired-end (PE) sequencing 45 b (15 samples) 75 b (109 samples) 31million ±0.5 million In total, ~0.58 Terabase sequence

23 March million bacterial gene catalog : 150- fold human genome Each individual has ~ of the 3.3 million genes 85% of abundant gut genes from a cohort of 124 individuals 70-86% of genes from the US & Japanese studies

24 T 0 W 6 W cal/d strict diet Follow the microbiota dynamic and signatures of obesity and in the microbiote DNA sequencing (SOLiD) of 215 faecal samples of 49 obese individuals sequenced at 3 differents -me- points (t0, w6, w12 and extra- -me) 300 Gbases sequenced Read projec-on against the MetaHIT gene catalog (Qin et al., 2010) (3.3 millions genes) 150 Gbases projected

25 Poor knowledge of the microorganisms living in the gut

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27 Reference catalog (3.3 million genes) Individuals (363) item s1_cho_ol_t0 s10_laj_an_t0 s11_emo_ma_t0 s13_meu_ka_t0 s14_pet_ma_t0 s15_bor_cl_t0 s16_cab_ro_t

28 Hierarchical descendant graph & DAPC clustering (Almeida et al., 2011) By computa-on of spearman correla-on for each couple of gene profile 3.3 E 6 x E 12 correla-ons to calculate With one CPU : more than a year to do it MetaProf (Boumezbeur, Arslan et al., 2011) CUDA programming 1H10 in 40 GPU

29 17317 clusters from 10 to genes (~2.34M genes, ~71%) 628 meta- species with more than 1000 genes

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31 Strict diet Maintenance 0 week 1 week 6 weeks 12 weeks Important of gene during the first part of the diet More stable in the second part

32 Network of rela-ons between the species (circles represent species, lines the co- variance, with R 0.4) Par-cular constella-ons of bacterial species in individuals

33 May 2011

34 Enterotypes can be likened to blood groups but the reasons for their existence remains to be elucidated They should allow pa-ent stra-fica-on & aid to develop personalized medicine and nutri-on

35 & tests soon arrays, sequencing, Q- PCR; immunomarkers (?) Beaer treatments next personalized medicine Novel treatments last modula-on of microbiota Promoters Inhibitors transplanta-on of microbiota

36 Dr. S.D. Ehrlich : Take- home message: Our other genome has much more variability than the first one Personalized medicine should target it

37 Data deluge is not finished 3rd genera-on sequencing In our lab: 2 SOLiD 5500xl sequencers the next week Data managing dcache / HDF5 Cloud Interna-onal repository Data analysis GPU oriented programming (OpenGPU project) Data browsing

38 MetaQuant Dusko Ehrlich Sean Kennedy Nicolas Pons Nathalie Galleron Benoît Quinquis Micro- Obes Food- Microbiomes Team «Bactéries Alimentaires et Commensales» Emmanuelle Le Chatellier Mathieu Almeida Fouad Boumebzeur Biology Chris-ne Delorme Eric Guédon Séverine Layec Ghalia Kaci Céline Gau-er Nicolas Sanchez Pierre Renault Team Jean- Michel Bavo Pierre Léonard Bouziane Moumen hvp://www.netvibes.com/metahit#live_news hvp://twiver.com/metagenomics hvp://paper.li/metahit/microbiomics

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