L. Jostins, Host-microbe interactions have shaped the genetic architecture of inflammatory bowel disease, Nature, vol.491, pp.119-124, 2012.

X. C. Morgan, Associations between host gene expression, the mucosal microbiome, and clinical outcome in the pelvic pouch of patients with inflammatory bowel disease, Genome Biol, vol.16, pp.1-15, 2015.

R. B. Sartor and G. D. Wu, Roles for intestinal bacteria, viruses, and fungi in pathogenesis of inflammatory bowel diseases and therapeutic approaches, Gastroenterology, vol.152, pp.327-339, 2017.

A. D. Kostic, Genomic analysis identifies association of Fusobacterium with colorectal carcinoma, Genome Res, p.292, 2012.

N. Rolhion and A. Darfeuille-michaud, Adherent-invasive Escherichia coli in inflammatory bowel, Inflamm. Bowel Dis, vol.13, pp.1277-1283, 2018.
URL : https://hal.archives-ouvertes.fr/hal-02664972

N. Barnichab, J. Denizot, and A. E. Darfeuille-michaud, coli-mediated gut inflammation in genetically predisposed Crohn's disease patients, Pathol. Biol, vol.61, pp.65-69, 2013.

V. Pascal, A microbial signature for Crohn's disease, Gut, vol.66, pp.813-822, 2017.

D. Gevers, The treatment-naive microbiome in new-onset Crohn's disease, Cell Host Microbe, vol.15, pp.382-392, 2014.

Y. Vázquez-baeza, Guiding longitudinal sampling in IBD cohorts, 2017.

J. Halfvarson, Dynamics of the human gut microbiome in Inflammatory Bowel Disease, Nat. Microbiol, vol.2, p.17004, 2017.

A. N. Ananthakrishnan, Gut microbiome function predicts response to anti-integrin biologic therapy in inflammatory bowel diseases, Cell Host Microbe, vol.21, 2017.

J. Lloyd-price, Multi-omics of the gut microbial ecosystem in inflammatory bowel diseases, Nature, vol.569, pp.655-662, 2019.

P. J. Turnbaugh, An obesity-associated gut microbiome with increased capacity for energy harvest, Nature, vol.444, pp.1027-1031, 2006.

J. A. Ferreyra, Gut microbiota-produced succinate promotes C. difficile infection after antibiotic treatment or motility disturbance, Cell Host Microbe, vol.16, pp.770-777, 2014.

P. M. Smith, The microbial metabolites, short-chain fatty acids, regulate colonic treg cell homeostasis, Science, vol.341, pp.569-573, 2013.

J. P. Jacobs, A disease-associated microbial and metabolomics state in relatives of pediatric inflammatory bowel disease patients, Cell. Mol. Gastroenterol. Hepatol, vol.2, pp.750-766, 2016.

E. A. Franzosa, Gut microbiome structure and metabolic activity in inflammatory bowel disease, Nat. Microbiol, vol.4, pp.293-305, 2019.

G. M. Douglas, Multi-omics differentially classify disease state and treatment outcome in pediatric Crohn's disease, 2018.

A. Metwaly and D. Haller, Multi-omics in IBD biomarker discovery: the missing links, Nat. Rev. Gastroenterol. Hepatol, 2019.

H. Nagao-kitamoto, Functional characterization of inflammatory bowel disease-associated gut dysbiosis in gnotobiotic mice, Cell. Mol. Gastroenterol. Hepatol, vol.2, pp.468-481, 2016.

V. K. Ridaura, Gut microbiota from twins discordant for obesity modulate metabolism in mice, 2013.

M. Arrieta, M. Sadarangani, E. M. Brown, S. L. Russell, and M. Nimmo, A humanized microbiota mouse model of ovalbumin-induced lung inflammation, Gut Microbes, vol.7, pp.342-352, 2016.

G. J. Britton, Microbiotas from humans with inflammatory bowel disease alter the balance of gut Th17 and ROR g t + regulatory T cells and exacerbate colitis in mice healthy donors IBD donors article microbiotas from humans with inflammatory bowel disease alter the balan, Immunity, vol.50, pp.212-224, 2019.

A. López-garcía, Autologous haematopoietic stem cell transplantation for refractory crohn's disease: efficacy in a single-centre cohort, J. Crohn's Colitis, 2017.

A. M. Corraliza, Differences in peripheral and tissue immune cell populations following haematopoietic stem cell transplantation in Crohn's disease patients, J. Crohn's Colitis, vol.13, pp.634-647, 2019.

G. Battipaglia, Fecal microbiota transplantation before or after allogeneic hematopoietic transplantation in patients with hematologic malignancies carrying multidrug-resistance bacteria, Haematologica, vol.104, pp.1682-1688, 2019.
URL : https://hal.archives-ouvertes.fr/hal-02283788

J. Bilinski, Fecal microbiota transplantation in patients with blood disorders inhibits gut colonization with antibiotic-resistant bacteria: results of a prospective, single-center study, Clin. Infect. Dis, vol.65, pp.364-370, 2017.

I. González, K. L. Cao, M. J. Davis, and S. Déjean, Visualising associations between paired 'omics' data sets, BioData Min, vol.5, p.19, 2012.

H. Duboc, Connecting dysbiosis, bile-acid dysmetabolism and gut inflammation in inflammatory bowel diseases, Gut, vol.62, pp.531-539, 2013.
URL : https://hal.archives-ouvertes.fr/hal-00734237

A. Jauregui-amezaga, Improving safety of autologous haematopoietic stem cell transplantation in patients with Crohn's disease, 2016.

Y. Zhou, Increased Enterococcus faecalis infection is associated with clinically active Crohn disease, pp.1578-1585, 2016.

R. Dhiman, Gut microbiota, inflammation and hepatic encephalopathy: a puzzle with a solution in sight, J. Clin. Exp. Hepatol, vol.2, pp.1-4, 2012.

J. L. Smith and D. O. Bayles, The contribution of cytolethal distending toxin to bacterial pathogenesis, Crit. Rev. Microbiol, vol.32, pp.227-248, 2006.

J. Walter, A. M. Armet, B. B. Finlay, and F. Shanahan, Establishing or exaggerating causality for the gut microbiome: lessons from human microbiota-associated rodents, Cell, vol.180, pp.221-232, 2020.

L. L. Barton, N. L. Ritz, G. D. Fauque, and H. C. Lin, Sulfur Cycling and the Intestinal Microbiome, Dig. Dis. Sci, vol.62, pp.2241-2257, 2017.
URL : https://hal.archives-ouvertes.fr/hal-01622027

J. Loubinoux, J. Bronowicki, I. A. Pereira, J. Mougenel, and A. E. Le, Sulfatereducing bacteria in human feces and their association with inflammatory bowel diseases, FEMS Microbiol. Ecol, vol.40, pp.107-112, 2002.

M. Joossens, Dysbiosis of the faecal microbiota in patients with Crohn's disease and their unaffected relatives, Gut, vol.60, pp.631-637, 2011.

M. C. Pitcher and J. H. Cummings, Hydrogen sulphide: a bacterial toxin in ulcerative colitis?, Gut, vol.39, pp.1-4, 1996.

M. Medani, Emerging role of hydrogen sulfide in colonic physiology and pathophysiology, Inflamm. Bowel Dis, vol.17, pp.1620-1625, 2011.

L. D. Palmer and E. P. Skaar, Transition metals and virulence in bacteria, Annu. Rev. Genet, vol.50, pp.67-91, 2016.

T. Werner, Depletion of luminal iron alters the gut microbiota and prevents Crohn's disease-like ileitis, Gut, vol.60, pp.325-333, 2011.

T. W. Lee, M. R. Kolber, R. N. Fedorak, and S. V. Van-zanten, Iron replacement therapy in inflammatory bowel disease patients with iron deficiency anemia: a systematic review and meta-analysis, J. Crohn's Colitis, vol.6, pp.267-275, 2012.

E. Eichhorn, J. R. Van-der-ploeg, M. A. Kertesz, and T. Leisinger, Characterization of ?-ketoglutarate-dependent taurine dioxygenase from Escherichia coli, J. Biol. Chem, vol.272, pp.23031-23036, 1997.

H. Laue, K. Denger, and A. M. Cook, Taurine reduction in anaerobic respiration of Bilophila wadsworthia RZATAU, Appl. Environ. Microbiol, vol.63, pp.2016-2021, 1997.

F. Mao, Increased sulfation of bile acids in mice and human subjects with sodium taurocholate cotransporting polypeptide deficiency, J. Biol. Chem, 2019.

C. J. Hawkey, Autologous hematopoetic stem cell transplantation for refractory Crohn disease: a randomized clinical trial, JAMA, vol.314, pp.2524-2534, 2015.

A. Jauregui-amezaga, Improving safety of autologous haematopoietic stem cell transplantation in patients with Crohn's disease, Ann. Rheum. Dis, vol.75, pp.1661-1666, 2016.

J. A. Snowden, Autologous haematopoietic stem cell transplantation (AHSCT) in severe Crohn's disease: a review on behalf of ECCO and EBMT, J. Crohns Colitis, vol.12, pp.476-488, 2018.

U. Erben, Original article a guide to histomorphological evaluation of intestinal inflammation in mouse models, Int. J. Clin. Exp. Pathol, vol.7, pp.4557-4576, 2014.

J. Godon, E. Zumstein, P. Dabert, and R. I. Habouzit, Molecular microbial diversity of an anaerobic digestor as determined by small-subunit rDNA sequence analysis. Molecular microbial diversity of an anaerobic digestor as determined by small-subunit rDNA sequence analysis, Appl. Environ. Microbiol, vol.63, pp.2802-2813, 1997.
URL : https://hal.archives-ouvertes.fr/hal-02686242

D. Berry, K. B. Mahfoudh, M. Wagner, and A. Loy, Barcoded primers used in multiplex amplicon pyrosequencing bias amplification, Appl. Environ. Microbiol, vol.77, pp.7846-7849, 2011.

A. Klindworth, Evaluation of general 16S ribosomal RNA gene PCR primers for classical and next-generation sequencing-based diversity studies, Nucleic Acids Res, vol.41, pp.1-11, 2013.

I. Lagkouvardos, IMNGS: a comprehensive open resource of processed 16S rRNA microbial profiles for ecology and diversity studies, Sci. Rep, vol.6, pp.1-9, 2016.

R. C. Edgar, UPARSE: highly accurate OTU sequences from microbial amplicon reads, Nat. Commun, vol.10, pp.996-998, 2013.

R. C. Edgar, B. J. Haas, J. C. Clemente, C. Quince, and R. Knight, UCHIME improves sensitivity and speed of chimera detection, Bioinformatics, vol.27, pp.2194-2200, 2011.

Q. Wang, G. M. Garrity, J. M. Tiedje, J. R. Cole, and W. E. Al, Naive bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy, Appl. Environ. Microbiol, vol.73, pp.5261-5267, 2007.

C. Quast, The SILVA ribosomal RNA gene database project: Improved data processing and web-based tools, Nucleic Acids Res, vol.41, pp.590-596, 2013.

O. Kim, Introducing EzTaxon-e: a prokaryotic 16S rRNA gene sequence database with phylotypes that represent uncultured species, Int. J. Syst. Evol. Microbiol, vol.62, pp.716-721, 2012.

I. Lagkouvardos, S. Fischer, N. Kumar, and T. Clavel, Rhea: a transparent and modular R pipeline for microbial profiling based on 16S rRNA gene amplicons, 2017.

G. M. Douglas, PICRUSt2: an improved and extensible approach for metagenome inference, 2019.

M. Hall, The WEKA data mining software: an update, SIGKDD Explor. Newsl, vol.11, pp.10-18, 2009.

A. M. Bolger, M. Lohse, and B. Usadel, Trimmomatic: a flexible trimmer for Illumina sequence data, Bioinformatics, vol.30, pp.2114-2120, 2014.

E. Kopylova, L. Noé, and H. Touzet, SortMeRNA: fast and accurate filtering of ribosomal RNAs in metatranscriptomic data, Bioinformatics, vol.28, pp.3211-3217, 2012.
URL : https://hal.archives-ouvertes.fr/hal-00748990

P. Yilmaz, The SILVA and 'all-species Living Tree Project (LTP)' taxonomic frameworks, Nucleic Acids Res, vol.42, pp.643-648, 2014.

D. Kim, B. Langmead, and S. L. Salzberg, HISAT: a fast spliced aligner with low memory requirements, Nat. Methods, vol.12, pp.357-360, 2015.

D. Li, C. M. Liu, R. Luo, K. Sadakane, and T. W. Lam, MEGAHIT: an ultra-fast single-node solution for large and complex metagenomics assembly via succinct de Bruijn graph, Bioinformatics, vol.31, pp.1674-1676, 2015.

F. A. Von-meijenfeldt, K. Arkhipova, D. D. Cambuy, F. H. Coutinho, and B. E. Dutilh, Robust taxonomic classification of uncharted microbial sequences and bins with CAT and BAT, 2019.

D. Hyatt, Prodigal: prokaryotic gene recognition and translation initiation site identification, BMC Bioinform, vol.11, pp.1471-2105, 2010.

B. Buchfink, C. Xie, and D. H. Huson, Fast and sensitive protein alignment using DIAMOND, Nat. Methods, vol.12, pp.59-60, 2014.

B. Bushnell, BBMap: A Fast, Accurate, Splice-Aware Aligner, 2014.

N. Segata, Metagenomic biomarker discovery and explanation, Genome Biol, vol.12, p.60, 2011.

M. Kanehisa, Y. Sato, and K. Morishima, BlastKOALA and GhostKOALA: KEGG tools for functional characterization of genome and metagenome sequences, J. Mol. Biol, vol.428, pp.726-731, 2016.

A. S. Martinez-vernon, F. Farrell, and O. S. Soyer, MetQy-an R package to query metabolic functions of genes and genomes, Bioinformatics, vol.34, pp.4134-4137, 2018.

H. Tsugawa, MS-DIAL: data-independent MS/MS deconvolution for comprehensive metabolome analysis, Nat. Methods, vol.12, pp.523-526, 2015.

R. Wehrens, Improved batch correction in untargeted MS-based metabolomics, Metabolomics, vol.12, p.88, 2016.

E. A. Thévenot, A. Roux, Y. Xu, E. Ezan, and C. Junot, Analysis of the human adult urinary metabolome variations with age, body mass index, and gender by implementing a comprehensive workflow for univariate and OPLS statistical analyses, J. Proteome Res, vol.14, pp.3322-3335, 2015.

M. B. Kursa and W. R. Rudnicki, Feature selection with the boruta package, J. Stat. Softw, vol.36, pp.1-13, 2010.

F. Rohart, B. Gautier, A. Singh, and K. Lê-cao, mixOmics: an R package for 'omics feature selection and multiple data integration, PLOS Comput. Biol, vol.13, p.1005752, 2017.

E. Szyma?ska, E. Saccenti, A. K. Smilde, and J. A. Westerhuis, Double-check: validation of diagnostic statistics for PLS-DA models in metabolomics studies, Metabolomics, vol.8, pp.3-16, 2012.

M. Arumugam, Enterotypes of the human gut microbiome, Nature, 2011.
URL : https://hal.archives-ouvertes.fr/cea-00903625

S. T. Wu, K. Cao, S. J. Bonacorsi, . Jr, H. Zhang et al., Distinguishing a phosphate ester prodrug from its isobaric sulfate metabolite by mass spectrometry without the metabolite standard, Rapid Commun. Mass Spectrom, vol.23, pp.3107-3113, 2009.