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―The Systems Biology Dynamics of
the Human Immune System and Gut Microbiome‖

Invited Talk
UCI Systems Biology Seminar Series
Irvine, CA
October 14, 2013
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
1
http://lsmarr.calit2.net
Abstract
In the last few years great progress has been made on using genetic
sequencing to reveal the extraordinary microbial ecology that co-habits our
human bodies. Indeed, ~90% of the cells in our superorganism are microbial
and they contain ~99% of the DNA genes contained in our body. After birth, the
growing diversity of gut bacterial species acts as a series of training sets to
"boot up" the human immune system, leading to a lifetime coupled system of
immune components and microbial ecology. In health the constant feedback
between the immune system and microbiome leads to homeostasis in the gut.
However, in autoimmune diseases this balance fails leading to large oscillations
in immune variables and massive disruption of the microbial ecology. I will
demonstrate this dysbiotic state with data taken from my own gut over the last
five years. Deep metagenomic sequencing of the my gut microbiome reveals
system dynamics at the species or even strain level. After exhibiting the ability
to read out the immune system-microbiome dynamics, I will review current
efforts to model this important biological system computationally or in vitro.
I Arrived in La Jolla in 2000of My Body andin the Midwest
By Measuring the State After 20 Years ―Tuning‖ It
Using Nutrition and Exercise, Ithe Obesity Trend
and Decided to Move Against Became Healthier
Age
41

Age
51

Age
61

1999
2000
1999

1989

I Reversed My Body’s Decline By
Quantifying and Altering Nutrition and Exercise
http://lsmarr.calit2.net/repository/LS_reading_recommendations_FiRe_2011.pdf

2010
From One to a Billion Data Points Defining Me:
The Exponential Rise in Body Data in Just One Decade!
Billion:Microbial Genome
My Full DNA,
MRI/CT Images

Improving Body
SNPs
Million: My DNA SNPs,
Zeo, FitBit

Discovering Disease
Blood
Variables
One:
My
Weight Weight

Hundred: My Blood Variables

Each is a Personal Time Series
And Compared Across Population
Visualizing Time Series of
150 LS Blood and Stool Variables, Each Over 5 Years
Calit2 64 megapixel VROOM
I Discovered I Had Episodic Chronic Inflammation by
Tracking Complex Reactive Protein In My Blood Samples
27x Upper Limit

Antibiotics

Normal Range
<1 mg/L

Antibiotics
Normal

CRP is a Generic Measure of Inflammation in the Blood
By Adding Stool Samples, I Discovered I Had High
Levels of the Protein Lactoferrin Shed from Neutrophils
Typical
Lactoferrin
Value for
Active
IBD

Normal Range
<7.3 µg/mL

124x Upper Limit

Antibiotics

Antibiotics

Lactoferrin is a Protein Shed from Neutrophils An Antibacterial that Sequesters Iron
Confirming the IBD (Crohn’s) Hypothesis:
Finding the ―Smoking Gun‖ with MRI Imaging
Liver

Transverse Colon

Small Intestine

I Obtained the MRI Slices
From UCSD Medical Services
and Converted to Interactive 3D
Working With
Calit2 Staff & DeskVOX Software
Descending Colon

MRI Jan 2012
Cross Section

Diseased Sigmoid Colon

Major Kink

Sigmoid Colon
Threading Iliac Arteries
Converting MRI Slices Into 3D Interactive Virtual Reality
AND 3-D Printing

Research: Calit2 FutureHealth Team
Why Did I Have an Autoimmune Disease like IBD?

Despite decades of research,
the etiology of Crohn's disease
remains unknown.
Its pathogenesis may involve
a complex interplay between
host genetics,
immune dysfunction,
and microbial or environmental factors.
--The Role of Microbes in Crohn's Disease

So I Set Out to Quantify All Three!
Paul B. Eckburg & David A. Relman
Clin Infect Dis. 44:256-262 (2007)
I Wondered if Crohn’s is an Autoimmune Disease,
Did I Have a Personal Genomic Polymorphism?
From www.23andme.com

ATG16L1

Polymorphism in
Interleukin-23 Receptor Gene
— 80% Higher Risk
of Pro-inflammatory
Immune Response

IRGM

NOD2

SNPs Associated with CD

Now Comparing
163 Known IBD SNPs
with 23andme SNP Chip
Variance Explained by Each of the 163 SNPs
Associated with IBD

• The width of the bar is proportional to the variance explained by that locus
• Bars are connected together if they are identified as being associated with both phenotypes
• Loci are labelled if they explain more than 1% of the total variance explained by all loci

―Host–microbe interactions have shaped the genetic architecture
of inflammatory bowel disease,‖ Jostins, et al. Nature 491, 119-124 (2012)
Crohn’s May be a Related Set of Diseases
Driven by Different SNPs
NOD2 (1)
rs2066844

Female
CD Onset
At 20-Years Old

Il-23R
rs1004819

Me-Male
CD Onset
At 60-Years Old
I Had My Full Human Genome Sequenced in 2012 1 Million/Year by 2015
Next Step: Compare Full Genome With IBD SNPs
My Anonymized Human Genome
is Available for Download

PGP Used Complete Genomics, Inc.
to Sequence my Human DNA

www.personalgenomes.org
Fine Time Resolution Sampling Reveals Unexpected
Dynamics of Innate and Adaptive Immune System
Innate Immune System

Normal

Therapy: 1 Month Antibiotics
+2 Month Prednisone

Adaptive Immune System
Normal

Time Points of
Metagenomic
Sequencing
of LS Stool Samples
LS Cultured Bacterial Abundance
Reveals Dynamic Microbiome Dysfunction

Time Points of Metagenomic Sequencing
of LS Stool Samples
Next: Analyze the Dynamics of My Microbiome Ecology85% of the Species Can Not Be Cultured
Your Body Has 10 Times
As Many Microbe Cells As Human Cells

99% of Your
DNA Genes
Are in Microbe Cells
Not Human Cells

Inclusion of the Microbiome
Will Radically Change Medicine
The Increasing Diversity of the Infant Gut Microbiome
―Boots Up‖ the Infant’s Immune System

―The neonatal microbiota varies erratically
until about 1-year-old when it stabilizes,
establishing a consortium that resembles that of adults.
During this initial period,
the neonatal immune system rapidly matures
under the influence of the microbiota.‖

―Reciprocal interactions of the intestinal microbiota and immune system,‖
Craig Maynard, et al. Nature 489, 231-241 (2012)
Delivery Mode Determines
Infant’s Initial Microbiome

―The composition of the initial microbiota may have implications
for nutritional and immune functions associated with the
developing microbiota. For example, recent studies suggest that
Cesarean-delivered babies may be more susceptible to allergies
and asthma.‖
Maria Dominguez-Belloa, et al. PNAS (2010) 107 11971–11975
The Infant Gut Microbiome Rapidly
Increases its Diversity After Birth

Adult Gut Microbiome Dominated
By Bacteroidetes/Firmicutes
―Succession of microbial consortia in the developing infant gut microbiome,‖
Jeremy Koeniga, et al. PNAS 108 Suppl 1:4578-85 (2011)
The Adult Healthy Gut Microbiome
Is Remarkably Stable Over Time

Source: Eric Alm, MIT
To Map My Gut Microbes, I Sent a Stool Sample to
the Venter Institute for Metagenomic Sequencing
Sequencing
Funding
Provided by
UCSD School of
Health Sciences

Shipped Stool Sample
December 28, 2011
I Received
a Disk Drive April 3, 2012
With Two 35 GB FASTQ Files
Weizhong Li, UCSD
NGS Pipeline:
230M Reads
Only 0.2% Human

Required 1/2 cpu-yr
Per Person Analyzed!
Gel Image of Extract from Smarr Sample-Next is Library Construction
Manny Torralba, Project Lead - Human Genomic Medicine
J Craig Venter Institute
January 25, 2012
Computational NextGen Sequencing Pipeline:
From ―Big Equations‖ to ―Big Data‖ Computing

PI: (Weizhong Li, CRBS, UCSD):
NIH R01HG005978 (2010-2013, $1.1M)
We Created a Reference Database
Of Known Gut Genomes
• NCBI April 2013
–
–
–
–

2471 Complete + 5543 Draft Bacteria & Archaea Genomes
2399 Complete Virus Genomes
26 Complete Fungi Genomes
309 HMP Eukaryote Reference Genomes

• Total 10,741 genomes, ~30 GB of sequences

Now to Align Our 12.5 Billion Reads
Against the Reference Database

Source: Weizhong Li, Sitao Wu, CRBS, UCSD
We Used SDSC’s Gordon Data-Intensive Supercomputer
to Analyze a Wide Range of Gut Microbiomes
• ~180,000 Core-Hrs on Gordon
– KEGG function annotation: 90,000 hrs
– Mapping: 36,000 hrs
– Used 16 Cores/Node
and up to 50 nodes
– Duplicates removal: 18,000 hrs
Enabled by
a Grant of Time
– Assembly: 18,000 hrs
on Gordon from SDSC
– Other: 18,000 hrs
Director Mike Norman

• Gordon RAM Required

– 64GB RAM for Reference DB
– 192GB RAM for Assembly

• Gordon Disk Required
– Ultra-Fast Disk Holds Ref DB for All Nodes
– 8TB for All Subjects
Phyla Gut Microbial Abundance Without Viruses:
LS, Crohn’s, UC, and Healthy Subjects
Source: Weizhong Li, Sitao Wu, CRBS, UCSD

LS

Crohn’s

Ulcerative
Colitis

Healthy

Toward Noninvasive
Microbial Ecology Diagnostics
Using Scalable Visualization Allows Comparison of
the Relative Abundance of 200 Microbe Species

Comparing 3 LS Time Snapshots (Left)
with Healthy, Crohn’s, UC (Right Top to Bottom)

Calit2 VROOM-FuturePatient Expedition
Lessons from Ecological Dynamics I:
Gut Microbiome Has Multiple Relatively Stable Equilibria

―The Application of Ecological Theory Toward an Understanding of the Human Microbiome,‖
Elizabeth Costello, Keaton Stagaman, Les Dethlefsen, Brendan Bohannan, David Relman
Science 336, 1255-62 (2012)
Lessons From Ecological Dynamics II:
Invasive Species Dominate After Major Species Destroyed

”In many areas following these burns
invasive species are able to establish themselves,
crowding out native species.”
Source: Ponderosa Pine Fire Ecology
http://cpluhna.nau.edu/Biota/ponderosafire.htm
Almost All Abundant Species (≥1%) in Healthy Subjects
Are Severely Depleted in LS Gut Microbiome
Blooms of Rare Species for Top 20 Most Abundant
In LS vs. Average Healthy Subject
152x
765x
148x

Number Above
LS Blue Bar is Multiple
of LS Abundance
Compared to Average
Healthy Abundance
Per Species

849x
483x
220x
201x169x
522x

Source: Sequencing JCVI; Analysis Weizhong Li, UCSD
LS December 28, 2011 Stool Sample
Rare Firmicutes Bloom in Colon Disappearing
After Antibiotic/Immunosuppressant Therapy
Firmicutes Families

Parvimonas
spp.

LS Time 1

Healthy
Average

LS Time 2
Comparison of 35 Healthy
to 15 CD and 6 UC Gut Microbiomes
Expansion of
Actinobacteria

Collapse of
Bacteroidetes

Explosion of
Proteobacteria
Six LS Gut Microbiome by Phyla

Therapy

Six Metagenomic Time Samples Over 16 Months
From Taxonomy to Function:
Analysis of LS Clusters of Orthologous Groups (COGs)

Analysis: Weizhong Li & Sitao Wu, UCSD
Variation in Phyla Abundance in
Health and IBD Plus My Time Series
Inflammation Enables Anaerobic Respiration Which
Leads to Phylum-Level Shifts in the Gut Microbiome

Sebastian E. Winter, Christopher A. Lopez & Andreas J. Bäumler,
EMBO reports VOL 14, p. 319-327 (2013)
Does Intestinal Inflammation Select for
Pathogenic Strains That Can Induce Further Damage?
AIEC LF82

―Adherent-invasive E. coli (AIEC)
are isolated more commonly
from the intestinal mucosa of
individuals with Crohn’s disease
than from healthy controls.‖
―Thus, the mechanisms
leading to dysbiosis might also
select for intestinal colonization
with more harmful members of the
Enterobacteriaceae*
—such as AIEC—
thereby exacerbating inflammation
and interfering with its resolution.‖
Sebastian E. Winter , et al.,
EMBO reports VOL 14, p. 319-327 (2013)

E. coli/Shigella Phylogenetic Tree
Miquel, et al.
PLOS ONE, v. 5, p. 1-16 (2010)
*Family Containing E. coli
Chronic Inflammation Can Accumulate
Cancer-Causing Bacteria in the Human Gut
Escherichia coli Strain NC101
Phylogenetic Tree
778 Ecoli strains
=6x our 2012 Set

B2

D

E

B1

S

A
We Divided the 778 E. coli Strains into 40 Groups,
Each of Which Had 80% Identical Genes
Group 0: D
Group 5: B2
Group 26: B2
Group 7: B2

NC101 LF82

Group 2: E
Group 4: B1

Group 3: A, B1

LS00
1
LS00
2
LS00
3

Median
CD
Median
UC
Median
HE

Group 9: S

Group 18,19,20: S
Reduction in E. coli Over Time
With Major Shifts in Strain Abundance
Therapy

Strains >0.5% Included
Systems Biology Immunology Modeling:
An Emerging Discipline

Immunol Res 53:251–265 (2012)

Annu Rev Immunol. 29: 527–585 (2011)
Early Attempts at Modeling the Systems Biology of
the Gut Microbiome and the Human Immune System
Next Step: Time Series of Metagenomic Gut Microbiomes
and Immune Variables in an N=100 Clinic Trial

Goal: Understand
The Coupled Human Immune-Microbiome
Dynamics
In the Presence of Human Genetic Predispositions
Thanks to Our Great Team!
UCSD Metagenomics Team
Weizhong Li
Sitao Wu

JCVI Team
Karen Nelson
Shibu Yooseph
Manolito Torralba

Calit2@UCSD
Future Patient Team
Jerry Sheehan
Tom DeFanti
Kevin Patrick
Jurgen Schulze
Andrew Prudhomme
Philip Weber
Fred Raab
Joe Keefe
Ernesto Ramirez

SDSC Team
Michael Norman
Mahidhar Tatineni
Robert Sinkovits

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The Systems Biology Dynamics of the Human Immune System and Gut Microbiome

  • 1. ―The Systems Biology Dynamics of the Human Immune System and Gut Microbiome‖ Invited Talk UCI Systems Biology Seminar Series Irvine, CA October 14, 2013 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 1 http://lsmarr.calit2.net
  • 2. Abstract In the last few years great progress has been made on using genetic sequencing to reveal the extraordinary microbial ecology that co-habits our human bodies. Indeed, ~90% of the cells in our superorganism are microbial and they contain ~99% of the DNA genes contained in our body. After birth, the growing diversity of gut bacterial species acts as a series of training sets to "boot up" the human immune system, leading to a lifetime coupled system of immune components and microbial ecology. In health the constant feedback between the immune system and microbiome leads to homeostasis in the gut. However, in autoimmune diseases this balance fails leading to large oscillations in immune variables and massive disruption of the microbial ecology. I will demonstrate this dysbiotic state with data taken from my own gut over the last five years. Deep metagenomic sequencing of the my gut microbiome reveals system dynamics at the species or even strain level. After exhibiting the ability to read out the immune system-microbiome dynamics, I will review current efforts to model this important biological system computationally or in vitro.
  • 3. I Arrived in La Jolla in 2000of My Body andin the Midwest By Measuring the State After 20 Years ―Tuning‖ It Using Nutrition and Exercise, Ithe Obesity Trend and Decided to Move Against Became Healthier Age 41 Age 51 Age 61 1999 2000 1999 1989 I Reversed My Body’s Decline By Quantifying and Altering Nutrition and Exercise http://lsmarr.calit2.net/repository/LS_reading_recommendations_FiRe_2011.pdf 2010
  • 4. From One to a Billion Data Points Defining Me: The Exponential Rise in Body Data in Just One Decade! Billion:Microbial Genome My Full DNA, MRI/CT Images Improving Body SNPs Million: My DNA SNPs, Zeo, FitBit Discovering Disease Blood Variables One: My Weight Weight Hundred: My Blood Variables Each is a Personal Time Series And Compared Across Population
  • 5. Visualizing Time Series of 150 LS Blood and Stool Variables, Each Over 5 Years Calit2 64 megapixel VROOM
  • 6. I Discovered I Had Episodic Chronic Inflammation by Tracking Complex Reactive Protein In My Blood Samples 27x Upper Limit Antibiotics Normal Range <1 mg/L Antibiotics Normal CRP is a Generic Measure of Inflammation in the Blood
  • 7. By Adding Stool Samples, I Discovered I Had High Levels of the Protein Lactoferrin Shed from Neutrophils Typical Lactoferrin Value for Active IBD Normal Range <7.3 µg/mL 124x Upper Limit Antibiotics Antibiotics Lactoferrin is a Protein Shed from Neutrophils An Antibacterial that Sequesters Iron
  • 8. Confirming the IBD (Crohn’s) Hypothesis: Finding the ―Smoking Gun‖ with MRI Imaging Liver Transverse Colon Small Intestine I Obtained the MRI Slices From UCSD Medical Services and Converted to Interactive 3D Working With Calit2 Staff & DeskVOX Software Descending Colon MRI Jan 2012 Cross Section Diseased Sigmoid Colon Major Kink Sigmoid Colon Threading Iliac Arteries
  • 9. Converting MRI Slices Into 3D Interactive Virtual Reality AND 3-D Printing Research: Calit2 FutureHealth Team
  • 10. Why Did I Have an Autoimmune Disease like IBD? Despite decades of research, the etiology of Crohn's disease remains unknown. Its pathogenesis may involve a complex interplay between host genetics, immune dysfunction, and microbial or environmental factors. --The Role of Microbes in Crohn's Disease So I Set Out to Quantify All Three! Paul B. Eckburg & David A. Relman Clin Infect Dis. 44:256-262 (2007)
  • 11. I Wondered if Crohn’s is an Autoimmune Disease, Did I Have a Personal Genomic Polymorphism? From www.23andme.com ATG16L1 Polymorphism in Interleukin-23 Receptor Gene — 80% Higher Risk of Pro-inflammatory Immune Response IRGM NOD2 SNPs Associated with CD Now Comparing 163 Known IBD SNPs with 23andme SNP Chip
  • 12. Variance Explained by Each of the 163 SNPs Associated with IBD • The width of the bar is proportional to the variance explained by that locus • Bars are connected together if they are identified as being associated with both phenotypes • Loci are labelled if they explain more than 1% of the total variance explained by all loci ―Host–microbe interactions have shaped the genetic architecture of inflammatory bowel disease,‖ Jostins, et al. Nature 491, 119-124 (2012)
  • 13. Crohn’s May be a Related Set of Diseases Driven by Different SNPs NOD2 (1) rs2066844 Female CD Onset At 20-Years Old Il-23R rs1004819 Me-Male CD Onset At 60-Years Old
  • 14. I Had My Full Human Genome Sequenced in 2012 1 Million/Year by 2015 Next Step: Compare Full Genome With IBD SNPs My Anonymized Human Genome is Available for Download PGP Used Complete Genomics, Inc. to Sequence my Human DNA www.personalgenomes.org
  • 15. Fine Time Resolution Sampling Reveals Unexpected Dynamics of Innate and Adaptive Immune System Innate Immune System Normal Therapy: 1 Month Antibiotics +2 Month Prednisone Adaptive Immune System Normal Time Points of Metagenomic Sequencing of LS Stool Samples
  • 16. LS Cultured Bacterial Abundance Reveals Dynamic Microbiome Dysfunction Time Points of Metagenomic Sequencing of LS Stool Samples
  • 17. Next: Analyze the Dynamics of My Microbiome Ecology85% of the Species Can Not Be Cultured Your Body Has 10 Times As Many Microbe Cells As Human Cells 99% of Your DNA Genes Are in Microbe Cells Not Human Cells Inclusion of the Microbiome Will Radically Change Medicine
  • 18. The Increasing Diversity of the Infant Gut Microbiome ―Boots Up‖ the Infant’s Immune System ―The neonatal microbiota varies erratically until about 1-year-old when it stabilizes, establishing a consortium that resembles that of adults. During this initial period, the neonatal immune system rapidly matures under the influence of the microbiota.‖ ―Reciprocal interactions of the intestinal microbiota and immune system,‖ Craig Maynard, et al. Nature 489, 231-241 (2012)
  • 19. Delivery Mode Determines Infant’s Initial Microbiome ―The composition of the initial microbiota may have implications for nutritional and immune functions associated with the developing microbiota. For example, recent studies suggest that Cesarean-delivered babies may be more susceptible to allergies and asthma.‖ Maria Dominguez-Belloa, et al. PNAS (2010) 107 11971–11975
  • 20. The Infant Gut Microbiome Rapidly Increases its Diversity After Birth Adult Gut Microbiome Dominated By Bacteroidetes/Firmicutes ―Succession of microbial consortia in the developing infant gut microbiome,‖ Jeremy Koeniga, et al. PNAS 108 Suppl 1:4578-85 (2011)
  • 21. The Adult Healthy Gut Microbiome Is Remarkably Stable Over Time Source: Eric Alm, MIT
  • 22. To Map My Gut Microbes, I Sent a Stool Sample to the Venter Institute for Metagenomic Sequencing Sequencing Funding Provided by UCSD School of Health Sciences Shipped Stool Sample December 28, 2011 I Received a Disk Drive April 3, 2012 With Two 35 GB FASTQ Files Weizhong Li, UCSD NGS Pipeline: 230M Reads Only 0.2% Human Required 1/2 cpu-yr Per Person Analyzed! Gel Image of Extract from Smarr Sample-Next is Library Construction Manny Torralba, Project Lead - Human Genomic Medicine J Craig Venter Institute January 25, 2012
  • 23. Computational NextGen Sequencing Pipeline: From ―Big Equations‖ to ―Big Data‖ Computing PI: (Weizhong Li, CRBS, UCSD): NIH R01HG005978 (2010-2013, $1.1M)
  • 24. We Created a Reference Database Of Known Gut Genomes • NCBI April 2013 – – – – 2471 Complete + 5543 Draft Bacteria & Archaea Genomes 2399 Complete Virus Genomes 26 Complete Fungi Genomes 309 HMP Eukaryote Reference Genomes • Total 10,741 genomes, ~30 GB of sequences Now to Align Our 12.5 Billion Reads Against the Reference Database Source: Weizhong Li, Sitao Wu, CRBS, UCSD
  • 25. We Used SDSC’s Gordon Data-Intensive Supercomputer to Analyze a Wide Range of Gut Microbiomes • ~180,000 Core-Hrs on Gordon – KEGG function annotation: 90,000 hrs – Mapping: 36,000 hrs – Used 16 Cores/Node and up to 50 nodes – Duplicates removal: 18,000 hrs Enabled by a Grant of Time – Assembly: 18,000 hrs on Gordon from SDSC – Other: 18,000 hrs Director Mike Norman • Gordon RAM Required – 64GB RAM for Reference DB – 192GB RAM for Assembly • Gordon Disk Required – Ultra-Fast Disk Holds Ref DB for All Nodes – 8TB for All Subjects
  • 26. Phyla Gut Microbial Abundance Without Viruses: LS, Crohn’s, UC, and Healthy Subjects Source: Weizhong Li, Sitao Wu, CRBS, UCSD LS Crohn’s Ulcerative Colitis Healthy Toward Noninvasive Microbial Ecology Diagnostics
  • 27. Using Scalable Visualization Allows Comparison of the Relative Abundance of 200 Microbe Species Comparing 3 LS Time Snapshots (Left) with Healthy, Crohn’s, UC (Right Top to Bottom) Calit2 VROOM-FuturePatient Expedition
  • 28. Lessons from Ecological Dynamics I: Gut Microbiome Has Multiple Relatively Stable Equilibria ―The Application of Ecological Theory Toward an Understanding of the Human Microbiome,‖ Elizabeth Costello, Keaton Stagaman, Les Dethlefsen, Brendan Bohannan, David Relman Science 336, 1255-62 (2012)
  • 29. Lessons From Ecological Dynamics II: Invasive Species Dominate After Major Species Destroyed ”In many areas following these burns invasive species are able to establish themselves, crowding out native species.” Source: Ponderosa Pine Fire Ecology http://cpluhna.nau.edu/Biota/ponderosafire.htm
  • 30. Almost All Abundant Species (≥1%) in Healthy Subjects Are Severely Depleted in LS Gut Microbiome
  • 31. Blooms of Rare Species for Top 20 Most Abundant In LS vs. Average Healthy Subject 152x 765x 148x Number Above LS Blue Bar is Multiple of LS Abundance Compared to Average Healthy Abundance Per Species 849x 483x 220x 201x169x 522x Source: Sequencing JCVI; Analysis Weizhong Li, UCSD LS December 28, 2011 Stool Sample
  • 32. Rare Firmicutes Bloom in Colon Disappearing After Antibiotic/Immunosuppressant Therapy Firmicutes Families Parvimonas spp. LS Time 1 Healthy Average LS Time 2
  • 33. Comparison of 35 Healthy to 15 CD and 6 UC Gut Microbiomes Expansion of Actinobacteria Collapse of Bacteroidetes Explosion of Proteobacteria
  • 34. Six LS Gut Microbiome by Phyla Therapy Six Metagenomic Time Samples Over 16 Months
  • 35. From Taxonomy to Function: Analysis of LS Clusters of Orthologous Groups (COGs) Analysis: Weizhong Li & Sitao Wu, UCSD
  • 36. Variation in Phyla Abundance in Health and IBD Plus My Time Series
  • 37. Inflammation Enables Anaerobic Respiration Which Leads to Phylum-Level Shifts in the Gut Microbiome Sebastian E. Winter, Christopher A. Lopez & Andreas J. Bäumler, EMBO reports VOL 14, p. 319-327 (2013)
  • 38. Does Intestinal Inflammation Select for Pathogenic Strains That Can Induce Further Damage? AIEC LF82 ―Adherent-invasive E. coli (AIEC) are isolated more commonly from the intestinal mucosa of individuals with Crohn’s disease than from healthy controls.‖ ―Thus, the mechanisms leading to dysbiosis might also select for intestinal colonization with more harmful members of the Enterobacteriaceae* —such as AIEC— thereby exacerbating inflammation and interfering with its resolution.‖ Sebastian E. Winter , et al., EMBO reports VOL 14, p. 319-327 (2013) E. coli/Shigella Phylogenetic Tree Miquel, et al. PLOS ONE, v. 5, p. 1-16 (2010) *Family Containing E. coli
  • 39. Chronic Inflammation Can Accumulate Cancer-Causing Bacteria in the Human Gut Escherichia coli Strain NC101
  • 40. Phylogenetic Tree 778 Ecoli strains =6x our 2012 Set B2 D E B1 S A
  • 41. We Divided the 778 E. coli Strains into 40 Groups, Each of Which Had 80% Identical Genes Group 0: D Group 5: B2 Group 26: B2 Group 7: B2 NC101 LF82 Group 2: E Group 4: B1 Group 3: A, B1 LS00 1 LS00 2 LS00 3 Median CD Median UC Median HE Group 9: S Group 18,19,20: S
  • 42. Reduction in E. coli Over Time With Major Shifts in Strain Abundance Therapy Strains >0.5% Included
  • 43. Systems Biology Immunology Modeling: An Emerging Discipline Immunol Res 53:251–265 (2012) Annu Rev Immunol. 29: 527–585 (2011)
  • 44. Early Attempts at Modeling the Systems Biology of the Gut Microbiome and the Human Immune System
  • 45. Next Step: Time Series of Metagenomic Gut Microbiomes and Immune Variables in an N=100 Clinic Trial Goal: Understand The Coupled Human Immune-Microbiome Dynamics In the Presence of Human Genetic Predispositions
  • 46. Thanks to Our Great Team! UCSD Metagenomics Team Weizhong Li Sitao Wu JCVI Team Karen Nelson Shibu Yooseph Manolito Torralba Calit2@UCSD Future Patient Team Jerry Sheehan Tom DeFanti Kevin Patrick Jurgen Schulze Andrew Prudhomme Philip Weber Fred Raab Joe Keefe Ernesto Ramirez SDSC Team Michael Norman Mahidhar Tatineni Robert Sinkovits