1. “Inspired by Carl: Exploring the Microbial Dynamics Within” Invited Talk Looking in the Right Direction: Carl Woese and the New Biology University of Illinois, Urbana-Champaign September 20, 2015 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 1

2. Carl Woese Was My Mentor for Microbial Genomics To Carl Woese: “What I have always understood is that you were responsible for ‘turning Larry Smarr on’ to biology, to evolution, to the adventures in living systems.” – John Wooley, July 26, 2006 To Larry Smarr: “I want to talk to you about setting up a megabase sequencing unit at the U of I I take this as necessary to the survival of good biology on this campus, for it is clear that megabase sequencing will be a major biological activity in the future. - Carl Woese, July 6, 1995 Last visit to Carl and Gay at their house Sept 20, 2009

3. There are 100 billion stars in the Andromeda galaxy… …and 100 billion galaxies in the known universe.

4. It’s a microbial world… …there are 100 million times as many bacteria on Earth as stars in the universe. as stars in the universe. Microbiology is the ultimate Big Data science! Microbiology is the ultimate Big Data science!

6. Carl’s Late Thoughts on the Critical Need for Research in Microbial Ecologies The second major direction involves the nature of the global ecosystem.... Bacteria are the major organisms on this planet— in numbers, in total mass, in importance to the global balances. Thus, it is microbial ecology that... is most in need of development, both in terms of facts needed to understand it, and in terms of the framework in which to interpret them.”microbial ecology -Carl Woese Current Biology 15: R111–R112 (2005). I started intensively working on microbial ecologies in 2005

7. PI Larry Smarr Grant Announced January 17, 2006

8. Calit2 Microbial Metagenomics Cluster- Next Generation Optically Linked Science Data Server 512 Processors ~5 Teraflops ~ 200 Terabytes Storage 1GbE and 10GbE Switched / Routed Core ~200TB Sun X4500 Storage 10GbE Source: Phil Papadopoulos, SDSC, Calit2

9. Calit2 CAMERA: 0ver 4000 Registered Users From Over 90 Countries

10. The Human Gut Starting Showing Up as a Another Microbial Environment Being Metagenomically Sampled

11. The Human Gut as a Super-Evolutionary Microbial Cauldron Enormous Density –1000x Ocean Water Highly Dynamic Microbial Ecology –Hundreds to Thousands of Species Horizontal Gene Transfer Phages Adaptive Selection Pressures (Immune System) –Innate Immune System –Adaptive Immune System –Macrophages and Antimicrobial proteins Constantly Changing Environmental Pressures –Diet –Antibiotics –Pharmaceuticals

12. To Better Understand the Human Gut Dynamics I Have Turned My Body into a Genomic and Biomarker Observatory One Blood Draw For Me Calit2 64 Megapixel VROOM

13. Only One of My Blood Measurements Was Far Out of Range--Indicating Chronic Inflammation Normal Range <1 mg/L 27x Upper Limit Complex Reactive Protein (CRP) is a Blood Biomarker for Detecting Presence of Inflammation Episodic Peaks in Inflammation Followed by Spontaneous Drops

14. Adding Stool Tests Revealed Oscillatory Behavior in an Immune Variable Which is Antibacterial Normal Range <7.3 µg/mL 124x Upper Limit for Healthy Lactoferrin is a Protein Shed from Neutrophils - An Antibacterial that Sequesters Iron Typical Lactoferrin Value for Active Inflammatory Bowel Disease (IBD)

15. Evolving Microbiome Environmental Pressures: Dynamical Innate and Adaptive Immune Oscillations in Colon Normal <600 Innate Immune System Normal 50 to 200 Adaptive Immune System These Must Be Coupled to A Dynamic Microbiome Ecology

16. For Deep Analysis of Changes in the Gut Microbiome Ecology Our Team Compared a Healthy Population with 3 Types of IBD 5 Ileal Crohn’s Patients, 3 Points in Time 2 Ulcerative Colitis Patients, 6 Points in Time “Healthy” Individuals Source: Jerry Sheehan, Calit2 Weizhong Li, Sitao Wu, CRBS, UCSD Total of 27 Billion Reads Or 2.7 Trillion Bases Inflammatory Bowel Disease (IBD) Patients 250 Subjects 1 Point in Time 7 Points in Time Each Sample Has 100-200 Million Illumina Short Reads (100 bases) Larry Smarr (Colonic Crohn’s)

17. To Map Out the Dynamics of Autoimmune Microbiome Ecology Couples Next Generation Genome Sequencers to Big Data Supercomputers Illumina HiSeq 2000 at JCVI SDSC Gordon Data Supercomputer Example: Inflammatory Bowel Disease (IBD) We Used 25 CPU-Years to Compute Comparative Gut Microbiomes of my 7 Time Samples, 255 Healthy, and 20 IBD Patients

18. UCSD’s Integrated Digital Infrastructure (IDI) Initiative Enhanced Cyberinfrastructure to Support Knight Lab for Microbial Genomics FIONA 12 Cores/GPU 128 GB RAM 3.5 TB SSD 48TB Disk 10Gbps NIC Knight Lab 10Gbps Gordon Prism@UCSD Data Oasis 7.5PB, 100GB/s Knight 1024 Cluster In SDSC Co-Lo CHERuB 100Gbps Emperor & Other Vis Tools 64Mpixel Data Analysis Wall 120Gbps 40Gbps

19. Resulting Microbiome Profiles Allow Us to Quickly Find 1 Unhealthy Person Out of 155 HMP “Healthy” Subjects 75 Most Abundant Species

20. Dell Analytics Separates The 4 Patient Types in Our Data Using Our Microbiome Species Data Source: Thomas Hill, Ph.D. Executive Director Analytics Dell | Information Management Group, Dell Software Healthy Ulcerative Colitis Colonic Crohn’s Ileal Crohn’s

21. I Built on Dell Analytics to Show Dynamic Evolution of My Microbiome Toward and Away from Healthy State – Colonic Crohn’s Healthy Ileal Crohn’s Seven Time Samples Over 1.5 Years Colonic Crohn’s

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

23. We Find Large Changes in Gut Microbial Abundance: Ileal CD Average Compared to Healthy Average by Family 30 Families >10x or 0.1% Abundance) 1/320x 235x

24. Our Research Shows Even Larger Changes in Protein Family Abundance Between Health and Disease – Ileal Crohns Over 7000 KEGGs Which Are Nonzero in Health and Disease States Ratio of Ileal CD Average to Healthy Average for Each Nonzero KEGG Most KEGGs Are Within 10x In Healthy and Ileal Crohn’s Disease KEGGs Greatly Increased In the Disease State KEGGs Greatly Decreased In the Disease State Note Hi/Low Symmetry

25. Our Relative Abundance Results Across ~300 People Reveal Potential Diagnostic Species UC 100x Healthy UC 100x CD We Produced Similar Results for ~2500 Microbial Species Healthy 100x CD

26. The Woese Effect: I Seem to Have a Large Amount of Archaea in my Gut LS Average 175x Healthy Average 18%

27. First 7 Next Step: Discover How the Time Varying Immune System & Pharma Drives Adaptive Changes in the Microbiome Ecology Immune & Inflammation Variables Weekly Symptoms Pharma Therapies Stool Samples 2009 2014 20132012 2011 2010 2015

28. To Expand IBD Project the Knight/Smarr Labs Were Just Awarded ~ 1 CPU-Century Supercomputing Time Smarr Gut Microbiome Time Series –From 7 Samples Over 1.5 Years –To 50 Samples Over 4 Years IBD Patients: From 5 Crohn’s Disease and 2 Ulcerative Colitis Patients to ~100 Patients –50 Carefully Phenotyped Patients Drawn from Sandborn BioBank –43 Metagenomes from the RISK Cohort of Newly Diagnosed IBD patients New Software Suite from Knight Lab –Re-annotation of Reference Genomes, Functional / Taxonomic Variations –Novel Compute-Intensive Assembly Algorithms from Pavel Pevzner 8x Compute Resources Over Prior Study

29. Bringing the Lessons of Microbial Ecology to Healthcare

30. We Must Move From Combating Single Microbe Diseases to Developing the Human/Microbiome System Approach to Public Health Bach (2002) N Engl J Med, Vol. 347, 911-920 2014 For Public Health It is Still About Microbes, But from Single Species to Entire Ecologies

31. The Coupled Neural, Immune, and Microbiome Systems Provide a Model Explaining How Nutrition Can Alter Neurodevelopment

32. 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 Ramanan Pek Lum JCVI Team Karen Nelson Shibu Yooseph Manolito Torralba SDSC Team Michael Norman Mahidhar Tatineni Robert Sinkovits UCSD Health Sciences Team Rob Knight Lab William J. Sandborn Elisabeth Evans John Chang Brigid Boland David Brenner Dell/R Systems Brian Kucic John Thompson