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“Inspired by Carl:
Exploring the Microbial Dynamics Within”
Invited Talk
Looking in the Right Direction: Carl Woese and th...
Carl Woese Was My Mentor
for Microbial Genomics
To Carl Woese: “What I have always understood
is that you were responsible...
There are 100 billion stars in the
Andromeda galaxy…
…and 100 billion galaxies in the
known universe.
It’s a microbial world…
…there are 100 million times as many bacteria on Earth
as stars in the universe.
Microbiology is t...
Carl’s Late Thoughts on
the Critical Need for Research in Microbial Ecologies
The second major direction involves the natu...
PI Larry Smarr
Grant Announced January 17, 2006
Calit2 Microbial Metagenomics Cluster-
Next Generation Optically Linked Science Data Server
512 Processors
~5 Teraflops
~ ...
Calit2 CAMERA: 0ver 4000 Registered Users
From Over 90 Countries
The Human Gut Starting Showing Up
as a Another Microbial Environment Being Metagenomically Sampled
The Human Gut
as a Super-Evolutionary Microbial Cauldron
• Enormous Density
– 1000x Ocean Water
• Highly Dynamic Microbial...
To Better Understand the Human Gut Dynamics
I Have Turned My Body into a Genomic and Biomarker Observatory
One Blood Draw
...
Only One of My Blood Measurements
Was Far Out of Range--Indicating Chronic Inflammation
Normal Range <1 mg/L
27x Upper Lim...
Adding Stool Tests Revealed
Oscillatory Behavior in an Immune Variable Which is Antibacterial
Normal Range
<7.3 µg/mL
124x...
Evolving Microbiome Environmental Pressures:
Dynamical Innate and Adaptive Immune Oscillations in Colon
Normal <600
Innate...
For Deep Analysis of Changes in the Gut Microbiome Ecology
Our Team Compared a Healthy Population with 3 Types of IBD
5 Il...
To Map Out the Dynamics of Autoimmune Microbiome Ecology
Couples Next Generation Genome Sequencers to Big Data Supercomput...
UCSD’s Integrated Digital Infrastructure (IDI) Initiative
Enhanced Cyberinfrastructure to Support Knight Lab for Microbial...
Resulting Microbiome Profiles Allow Us to
Quickly Find 1 Unhealthy Person Out of 155 HMP “Healthy” Subjects
75 Most
Abunda...
Dell Analytics Separates The 4 Patient Types in Our Data
Using Our Microbiome Species Data
Source: Thomas Hill, Ph.D.
Exec...
I Built on Dell Analytics to Show Dynamic Evolution of My Microbiome
Toward and Away from Healthy State – Colonic Crohn’s
...
We Found Major State Shifts in Microbial Ecology Phyla
Between Healthy and Three Forms of IBD
Most
Common
Microbial
Phyla
...
We Find Large Changes in Gut Microbial Abundance:
Ileal CD Average Compared to Healthy Average by Family
30 Families >10x ...
Our Research Shows Even Larger Changes in Protein Family Abundance
Between Health and Disease – Ileal Crohns
Over 7000 KEG...
Our Relative Abundance Results Across ~300 People
Reveal Potential Diagnostic Species
UC 100x Healthy
UC 100x CD
We Produc...
The Woese Effect:
I Seem to Have a Large Amount of Archaea in my Gut
LS Average 175x Healthy Average
18%
First 7
Next Step: Discover How the Time Varying Immune System & Pharma
Drives Adaptive Changes in the Microbiome Ecology
...
To Expand IBD Project the Knight/Smarr Labs Were Just Awarded
~ 1 CPU-Century Supercomputing Time
• Smarr Gut Microbiome T...
Bringing the Lessons of Microbial Ecology
to Healthcare
We Must Move From Combating Single Microbe Diseases to
Developing the Human/Microbiome System Approach to Public Health
Ba...
The Coupled Neural, Immune, and Microbiome Systems
Provide a Model Explaining How Nutrition Can Alter Neurodevelopment
Thanks to Our Great Team!
UCSD Metagenomics Team
Weizhong Li
Sitao Wu
Calit2@UCSD
Future Patient Team
Jerry Sheehan
Tom De...
Inspired by Carl: Exploring the Microbial Dynamics Within
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Inspired by Carl: Exploring the Microbial Dynamics Within

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Looking in the Right Direction: Carl Woese and the New Biology University of Illinois, Urbana-Champaign, September 20, 2015

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Inspired by Carl: Exploring the Microbial Dynamics Within

  1. 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. 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. 3. There are 100 billion stars in the Andromeda galaxy… …and 100 billion galaxies in the known universe.
  4. 4. It’s a microbial world… …there are 100 million times as many bacteria on Earth as stars in the universe. Microbiology is the ultimate Big Data science!
  5. 5. 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.” -Carl Woese Current Biology 15: R111–R112 (2005). I started intensively working on microbial ecologies in 2005
  6. 6. PI Larry Smarr Grant Announced January 17, 2006
  7. 7. 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
  8. 8. Calit2 CAMERA: 0ver 4000 Registered Users From Over 90 Countries
  9. 9. The Human Gut Starting Showing Up as a Another Microbial Environment Being Metagenomically Sampled
  10. 10. 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
  11. 11. To Better Understand the Human Gut Dynamics I Have Turned My Body into a Genomic and Biomarker Observatory One Blood Draw For MeCalit2 64 Megapixel VROOM
  12. 12. 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
  13. 13. 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)
  14. 14. 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
  15. 15. 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)
  16. 16. 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
  17. 17. 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
  18. 18. Resulting Microbiome Profiles Allow Us to Quickly Find 1 Unhealthy Person Out of 155 HMP “Healthy” Subjects 75 Most Abundant Species
  19. 19. 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
  20. 20. 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
  21. 21. 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
  22. 22. We Find Large Changes in Gut Microbial Abundance: Ileal CD Average Compared to Healthy Average by Family 30 Families >10x or <1/10x (Out of 76 Families with > 0.1% Abundance) 1/320x 235x
  23. 23. 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
  24. 24. 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
  25. 25. The Woese Effect: I Seem to Have a Large Amount of Archaea in my Gut LS Average 175x Healthy Average 18%
  26. 26. 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 20142013201220112010 2015
  27. 27. 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
  28. 28. Bringing the Lessons of Microbial Ecology to Healthcare
  29. 29. 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
  30. 30. The Coupled Neural, Immune, and Microbiome Systems Provide a Model Explaining How Nutrition Can Alter Neurodevelopment
  31. 31. 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

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