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Microbiota and the Human Body Ecosystem Experimental Design Methodology Study Aims

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Microbiota and the Human Body Ecosystem Experimental Design Methodology Study Aims Stability and Resilience in the Human Microbiome: Response of Gut Microbiota to Colonic Lavage Laurie Rumker, Dr. Les Dethlefsen, Dr. David Relman Department of Microbiology and Immunology, Stanford University School of Medicine Microbiota and the Human Body Ecosystem Experimental Design Methodology Study Aims • = Fecal and Urine ! Aim 1. Compare rou?ne unperturbed dynamics to varied • Bacteria contribute 90% of cells, Samples Taken ! responses to lavage; characterize effect of disturbance 99% of genes in human body Colonic • Roles of microbiota in health: Lavage! • Aim 2. Evaluate applicaon of ecological principles to human gut - Pathogen resistance microbiota in context of colonic lavage disturbance - Metabolizaon - Xenobio?c modificaons Baseline Stability! Disturbance! Recovery Dynamics! (Weekly Sampling)! (Daily Sampling)! (Weekly Sampling)! • Aim 3. Iden?fy features characteris?c of resilient communi?es - Immune system regulaon • Contributes to malnutri?on, obesity, heart disease, • Study Subjects: 8 healthy volunteer adult par?cipants Body Sites and Predominant inflammatory bowel disease, • Fecal and urine samples at each ?me point analyzed three ways: Proof of Concept: An<bio<c Disturbance Taxa of the Microbiota Crohn’s disease, many more (Dethlefsen and Relman, 2007) Fluctuaons of α-Diversity Metrics in Response to an An?bio?c Series • Marker gene amplified, sequenced 16S rDNA • Conserved iden?ficaon tag An?bio?cs An?bio?cs Research Ques<ons Sequencing • Reveals changes in taxonomic 80 composi?on, relave abundances 60 • How consistently does the microbiome retain its composi?on and 40 ac?vity over ?me? 20 • Fragmented, sequenced whole Rela<ve Diversity • 0 How easily can the health benefits conferred upon a host by the Shotgun genome microbiota be lost due to a disturbance of the community? 0 50 100 150 200 250 300 350 Metagenomic • Reveals relave gene frequencies Day of Sampling Sequencing • Computaonal reassembly associates Phylogene?c Diversity Applying Macroecological Theory genes with specific taxa Taxonomic Diversity (Shannon Index, Values *10) OTU Richness (Values/10) • Stability = ability of system to return to equilibrium quickly, with • An?bio?c series triggered dramac temporary decrease in α- minimal deviaon aer temporary disturbance • Iden?fies small molecules produced diversity metrics based on 16S rDNA data (Dethlefsen, 2011) • Equilibrium = set of defined values for relevant key variables Metabolomic Mass • Present study expands upon this one with longer ?mescale, Spectrometry • (Analyses performed by collaborators • Resilience = when challenged with disturbance, ecosystem ability at University College London) greater sampling depth, use of metagenomics and metabolomics to adapt and retain func?on, structure, iden?ty, and feedbacks • Colonic lavage is less selec?ve disturbance causing greater • Disturbance could induce regime shif to new stable state decrease in total biomass Ecosystem Project Status Variaon Around Stable Equilibrium Alternave Subjects DNA Send Stable State Design Study Recruit Metagenomic Data Processing Sample Extrac?on 16S Metabolomics and Obtain and Enroll Sequencing and with QIIME and and from Fecal Sequencing Urine and Fecal Ecosystem Stable States or “Basins of Ahrac?on” IRB Approval Subjects Reassembly Phyloseq Cleanout Samples Samples • Possible predictors of microbiome resilience: - Taxonomic diversity - Intermediate stability week-to-week or day-to-day 3 par?cipants currently sampling, 5 par?cipants’ samples DNA extracted, 16S sequenced - Func?onal redundancy (the Insurance Hypothesis) about to undergo cleanout, will complete on HISeq2500 with 150nt paired-reads, produced - Specific constellaon of taxa sampling December 2014 >98 million reads, metagenomics preparaons ongoing .
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