“Mapping the Human Gut Microbiome in Health and Disease Using Sequencing, Supercomputing, and Data Analysis” Invited Talk Delivered by Mehrdad Yazdani,

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“Mapping the Human Gut Microbiome in Health and Disease Using Sequencing, Supercomputing, and Data Analysis” Invited Talk Delivered by Mehrdad Yazdani, Calit2 Ayasdi Sponsored Lunch & Learn American Society of Human Genetics (ASHG) San Diego Convention Center October 19, 2014 Dr. Larry Smarr Director, California Institute for Telecommunications and Information Technology Harry E. Gruber Professor, Dept. of Computer Science and Engineering Jacobs School of Engineering, UCSD http://lsmarr.calit2.net

Your Body Has 10 Times As Many Microbe Cells As Human Cells Inclusion of the Microbiome Will Radically Change Medicine and Wellness Your Body Has 10 Times As Many Microbe Cells As Human Cells 99% of Your DNA Genes Are in Microbe Cells Not Human Cells Challenge: Map Out Microbial Ecology and Function

A Year of Sequencing a Healthy Gut Microbiome Daily - Remarkable Stability with Abrupt Changes Days Genome Biology (2014) David, et al.

To Map Out the Dynamics of Autoimmune Microbiome Ecology Couples Next Generation Genome Sequencers to Big Data Supercomputers Illumina HiSeq 2000 at JCVI Metagenomic Sequencing JCVI Produced ~150 Billion DNA Bases From Seven of LS Stool Samples Over 1.5 Years We Downloaded ~3 Trillion DNA Bases From NIH Human Microbiome Program Data Base 255 Healthy People, 21 with IBD Supercomputing (Weizhong Li, JCVI/HLI/UCSD): ~180,000 Core-Hours SDSC’s Gordon ~35,000 Core-Hours Dell HPC Cloud Produced Relative Abundance of ~10,000 Bacteria, Archaea, Viruses in ~300 People ~3Million Filled Spreadsheet Cells SDSC Gordon Data Supercomputer

Collapse of Bacteroidetes Explosion of Actinobacteria We Found Major State Shifts in Microbial Ecology Phyla Between Healthy and Two Forms of IBD Average HE Most Common Microbial Phyla Average Crohn’s Disease Average Ulcerative Colitis Average LS Explosion of Proteobacteria Hybrid of UC and CD High Level of Archaea Collapse of Bacteroidetes Explosion of Actinobacteria

Using Ayasdi to Discover Hidden Patterns in Our Data topological data analysis 

Categorical Data Lens to Separate Healthy from Disease States All Healthy All Healthy All Ileal Crohn’s Healthy, Ulcerative Colitis, and LS All Healthy

Group Comparisons using Ayasdi’s Statistical Tools

Using Multidimensional Scaling Lens with Correlation Metric Ayasdi Enables Discovery of Differences Between Healthy and Disease States Using Microbiome Species LS Healthy High in Healthy and LS High in Healthy and Ulcerative Colitis High in Both LS and Ileal Crohn’s Disease Ileal Crohn’s Ulcerative Colitis Using Multidimensional Scaling Lens with Correlation Metric

Moving from Ecological Taxonomy to Cellular Pathways Dataset from Larry Smarr Team With 60 Subjects (HE, CD, UC, LS) Each with 10,000 KEGGs - 600,000 Cells Source: Pek Lum, Chief Data Scientist, Ayasdi

Next Step: Apply What We Have Learned to New Microbiome Datasets Larry Smarr is a Member of the Pioneer 100 Our Team Now Has the Gut Microbiomes of the Pioneer 100 We Plan to Analyze Them for Differences Using Ayasdi Tools Do Metagenomics on Those Who Are Outliers Will Grow to 1000, then 10,000 http://isbmolecularme.com/tag/100-pioneers/

Thanks to Our Great Team! UCSD Metagenomics Team Weizhong Li Sitao Wu Calit2@UCSD Future Patient Team Jerry Sheehan Tom DeFanti Kevin Patrick Jurgen Schulze Andrew Prudhomme Philip Weber Fred Raab Joe Keefe Ernesto Ramirez Ayasdi Devi Sanjnan Pek JCVI Team Karen Nelson Shibu Yooseph Manolito Torralba SDSC Team Michael Norman Mahidhar Tatineni Robert Sinkovits UCSD Health Sciences Team William J. Sandborn Elisabeth Evans John Chang Brigid Boland David Brenner