“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
Carl Woese Was My Mentor
for Microbial Genomics
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
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
Last visit to Carl and Gay at their house Sept 20, 2009
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 the ultimate Big Data science!
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
PI Larry Smarr
Grant Announced January 17, 2006
Calit2 Microbial Metagenomics ClusterNext Generation Optically Linked Science Data Server
Source: Phil Papadopoulos, SDSC, Calit2
512 Processors
~5 Teraflops
~ 200 Terabytes Storage
1GbE
and
10GbE
Switched
/ Routed
Core
~200TB
Sun
X4500
Storage
10GbE
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 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
To Better Understand the Human Gut Dynamics
I Have Turned My Body into a Genomic and Biomarker Observatory
Calit2 64 Megapixel VROOM
One Blood Draw
For Me
Only One of My Blood Measurements
Was Far Out of Range--Indicating Chronic Inflammation
27x Upper Limit
Episodic Peaks in Inflammation
Followed by Spontaneous Drops
Normal Range <1 mg/L
Complex Reactive Protein (CRP) is a Blood Biomarker
for Detecting Presence of Inflammation
Adding Stool Tests Revealed
Oscillatory Behavior in an Immune Variable Which is Antibacterial
Typical
Lactoferrin Value for
Active Inflammatory
Bowel Disease
(IBD)
124x Upper Limit for Healthy
Normal Range
<7.3 µg/mL
Lactoferrin is a Protein Shed from Neutrophils An Antibacterial that Sequesters Iron
Evolving Microbiome Environmental Pressures:
Dynamical Innate and Adaptive Immune Oscillations in Colon
Adaptive Immune System
Normal 50 to 200
Innate Immune System
Normal <600
These Must Be Coupled to
A Dynamic Microbiome Ecology
For Deep Analysis of Changes in the Gut Microbiome Ecology
Our Team Compared a Healthy Population with 3 Types of IBD
Each Sample Has 100-200 Million Illumina Short Reads (100 bases)
“Healthy” Individuals
Inflammatory Bowel Disease (IBD) Patients
250 Subjects
1 Point in Time
2 Ulcerative Colitis Patients,
6 Points in Time
Larry Smarr
(Colonic Crohn’s)
7 Points in Time
5 Ileal Crohn’s Patients,
3 Points in Time
Total of 27 Billion Reads
Or 2.7 Trillion Bases
Source: Jerry Sheehan, Calit2
Weizhong Li, Sitao Wu, CRBS, UCSD
To Map Out the Dynamics of Autoimmune Microbiome Ecology
Couples Next Generation Genome Sequencers to Big Data Supercomputers
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
Illumina HiSeq 2000 at JCVI
SDSC Gordon Data Supercomputer
UCSD’s Integrated Digital Infrastructure (IDI) Initiative
Enhanced Cyberinfrastructure to Support Knight Lab for Microbial Genomics
Knight 1024 Cluster
In SDSC Co-Lo
Gordon
Knight Lab
Data Oasis
7.5PB,
100GB/s
CHERuB
100Gbps
120Gbps
10Gbps
FIONA
12 Cores/GPU
128 GB RAM
3.5 TB SSD
48TB Disk
10Gbps NIC
Emperor & Other Vis Tools
40Gbps
Prism@UCSD
64Mpixel Data Analysis Wall
Resulting Microbiome Profiles Allow Us to
Quickly Find 1 Unhealthy Person Out of 155 HMP “Healthy” Subjects
75 Most
Abundant
Species
Dell Analytics Separates The 4 Patient Types in Our Data
Using Our Microbiome Species Data
Ulcerative Colitis
Colonic Crohn’s
Healthy
Ileal Crohn’s
Source: Thomas Hill, Ph.D.
Executive Director Analytics
Dell | Information Management Group, Dell Software
I Built on Dell Analytics to Show Dynamic Evolution of My Microbiome
Toward and Away from Healthy State – Colonic Crohn’s
Seven Time Samples Over 1.5 Years
Healthy
Colonic Crohn’s
Ileal Crohn’s
We Found Major State Shifts in Microbial Ecology Phyla
Between Healthy and Three Forms of IBD
Average HE
Most
Common
Microbial
Phyla
Average
Ulcerative Colitis
Average LS
Colonic Crohn’s Disease
Average
Ileal Crohn’s Disease
Explosion of
Proteobacteria
Hybrid of UC and CD
High Level of Archaea
Collapse of Bacteroidetes
Explosion of Actinobacteria
We Find Large Changes in Gut Microbial Abundance:
Ileal CD Average Compared to Healthy Average by Family
235x
30 Families >10x or <1/10x (Out of 76 Families with > 0.1% Abundance)
1/320x
Our Research Shows Even Larger Changes in Protein Family Abundance
Between Health and Disease – Ileal Crohns
Ratio of Ileal CD Average to Healthy Average for Each Nonzero KEGG
KEGGs Greatly Increased
In the Disease State
Note Hi/Low
Symmetry
Most KEGGs Are Within 10x
In Healthy and Ileal Crohn’s Disease
KEGGs Greatly Decreased
In the Disease State
Over 7000 KEGGs Which Are Nonzero
in Health and Disease States
Our Relative Abundance Results Across ~300 People
Reveal Potential Diagnostic Species
UC 100x Healthy
Healthy 100x CD
UC 100x CD
We Produced Similar Results for ~2500 Microbial Species
The Woese Effect:
I Seem to Have a Large Amount of Archaea in my Gut
18%
LS Average 175x Healthy Average
Next Step: Discover How the Time Varying Immune System & Pharma
Drives Adaptive Changes in the Microbiome Ecology
Immune &
Inflammation
Variables
2009
2010
2011
2012
2013
2014
2015
Weekly
Symptoms
Pharma
Therapies
First 7
Stool
Samples
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
8x Compute Resources
Over Prior Study
– Re-annotation of Reference Genomes, Functional / Taxonomic Variations
– Novel Compute-Intensive Assembly Algorithms from Pavel Pevzner
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
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
The Coupled Neural, Immune, and Microbiome Systems
Provide a Model Explaining How Nutrition Can Alter Neurodevelopment
Thanks to Our Great Team!
UCSD Metagenomics Team
JCVI Team
Weizhong Li
Sitao Wu
Karen Nelson
Shibu Yooseph
Manolito Torralba
Calit2@UCSD
Future Patient Team
SDSC Team
Jerry Sheehan
Tom DeFanti
Kevin Patrick
Jurgen Schulze
Andrew Prudhomme
Philip Weber
Fred Raab
Joe Keefe
Ernesto Ramirez
Dell/R Systems
Ayasdi
Devi Ramanan
Pek Lum
Michael Norman
Mahidhar Tatineni
Robert Sinkovits
Brian Kucic
John Thompson
UCSD Health Sciences Team
Rob Knight Lab
William J. Sandborn
Elisabeth Evans
John Chang
Brigid Boland
David Brenner