Download multicellular behavior in bacteria

Emergence and robustness of
multicellular behavior in bacteria
Joao B. Xavier
Computational and Systems Biology
Memorial Sloan-Kettering Cancer Center
Bacteria have many examples of social
interaction
•Strength by numbers
•Secretion of virulence factors
•Biofilm formation
•Quorum sensing
What prevents evolutionary cheating?
ಯPublic goodರ
+
Cooperator
"cheater"
Swarming: collective motility in
Pseudomonas aeruginosa
Swarming: collective motility in
Pseudomonas aeruginosa
Swarming benefits the colony but requires
biosurfactant synthesis by cells
What prevents
evolutionary
cheating?
With: Wook Kim, Kevin Foster
Biosurfactant synthesis is well
characterized
Wild-type
rhlA(Non-cooperator)
Different genotypes are distinguishable
using neutral colors
GFP
RFP
10
cells in colony
2x10
10
1x10
GFP
RFP
mix
mix
Biosurfactants are a
ಯpublic goodರ
Biosurfactant secretion is uncheatable
• Non-cooperators do
better than when alone…
• …but at expense of wildtype
• Not enough to distinguish
who wins, WT or rhlA-
Measured relative fitness:
0.99 0.05
rhlA expression is delayed until
stationary phase
P. aeruginosa
PA14 rhlAB-GFP
rhlAB expression OFF
[h]
rhlAB expression ON
Quorum sensing is necessary yet
not sufficient
High density
rhlAB ON
rhlA
Low density
rhlAB OFF
[h]
Quorum sensing is necessary yet
not sufficient
ΔlasI ΔrhlI without
autoinducers
Quorum sensing is necessary yet
not sufficient
ΔlasI ΔrhlI with
autoinducers
Expression of biosurfactant synthesis is
favored at lower nitrogen source levels
Carbon source: Glycerol (C3H5(OH)3)
Nitrogen source: (NH4)2SO4
rhlA regulation ensures
metabolic prudence
C
C
C
N
C
C
N
C
C
C
C
C
Medium both carbon
and nitrogen but
carbon is in excess
C
C
Cells grow while
thereಬs
nitrogen…
…then use excess
carbon to secrete
rhamnolipids
But only if thereಬs a quorum
Inducible rhlAB bypasses
metabolic pudence mechanism
No inducer
(behaves like noncooperator)
Inducer present
(strict cooperator)
Biosurfactant secretion in strict cooperator
is cheatable
Day 1
Day 2
Day 3
Day 4
Metagenomics: probing the microbiome
without bacterial culturing
Lee, et al. (2010)
Single dose of clindamycin can perturb
mice microbiota up to 28 days…
Phylotype color scheme:
Cecum (Clindamycin treated mice)
Relative abundance
Ileum (Clindamycin treated mice)
Relative abundance
Relative abundance
Relative abundance
With: Charlie Buffie, Eric Pamer
Ileum (control)
Cecum (control)
…and greatly increases the risk of
Clostridium difficile colitis
Relative abundance
Ileum (clindamycin + C. difficile)
Phylotype color scheme:
Relative abundance
Cecum (clindamycin + C. difficile)
Control mice
Clindamycin treated mice
A minimal ecological model of microbial
interactions in the intestine
Vanni Bucci, Serena Bradde
(sensitivity to antibiotic)
Antibiotic therapy and competition explain multistability and hysteresis in intestinal microbiota
(competitive ability of sensitives)
Problem:
Noise-free model predicts dominance states can last indefinitely. Can noise
describe return to sensitive dominated state?
Antibiotic pulses
Exposure to environmental microbes
explains microbiota recovery
Antibiotic tolerants
Antibiotic sensitives
(No noise)
Simulation time
DN=3.3x10-4
(noise level)
Simulation time
DN=1x10-3
(noise level)
Can we test the model with
metagenomic data?
Question:
Can we separate OTUs into ಯsensitivesರ and ಯtolerantsರ according to their
response to ciprofloxacin?
Dethlefsen & Relman (2011) PNAS
Antibiotic sensitive or antibiotic tolerant dynamics
identified from singular value decomposition
Data from subject D
Data from subject E
Data from subject F
OTUs that
correlate with
PC1
OTUs that
correlate with
PC2
Sample (day)
Sample (day)
Sample (day)
Summary
• Social interaction is key in microbial evolution and
ecology
• Multicellular cooperative traits are open to exploitation…
• …and therefore must have evolved with mechanisms for
robustness
• We can find the mechanisms stabilizing bacterial
multicellularity such as metabolic prudence
• Next gen sequencing and ecological modeling can unveil
the human microbiome
• And lead to applications for human health
Clinical application:
the microbiome of bone marrow transplantation
Timelines of bone marrow transplants:
Microbiota states:
State transitions:
With: Ying Taur, Eric Pamer
Acknowledgments
Xavier lab at MSKCC (est Dec 2009):
Eric Pamer
Dave van Ditmarsch
Charlie Buffie
Vanni Bucci
Carles Ubeda
Will Chang
Ying Taur
Laura de Vargas Roditi
Carlos Carmona-Fontaine
Serena Bradde (now at Curie Institute)
Kerry Boyle
Giulio Biroli (Institut Physique Theorique Saclay)
http://cbio.mskcc.org/xavierlab/
Foster lab at Oxford:
Kevin Foster
Wook Kim
Thanks also to:
Peter Greenberg, Pradeep Singh,
Deborah Hogan, Les Dethlefsen
Funding:
Lucille Castori Center for Microbes Inflammation
and Cancer