Modelling the Induction of the nan
Operon in E.coli
Dominique Chu
School of Computing
University of Kent
Canterbury
United Kingdom
D.F.Chu@kent.ac.uk
Collaborator
Dr. Ian Blomfield
Fimbriation (E.coli)
Phase Variation
phase “on”
phase “off”
This is essentially a molecular random number generator
At any time, no more than 10% of cells are fimbriate
…sialic acid (nutrient)
…fimbriate cell
…afimbriate cell
…sialic acid (nutrient)
…fimbriate cell
…afimbriate cell
…sialic acid (nutrient)
…fimbriate cell
…afimbriate cell
Standard hypothesis

Bacteria exploit vulnerability of the host to
scavenge nutrient. [FALSE]
-
How did system evolve?
-
How does it work?
-
What are its computational properties?
-
Over which time scales does it work?
Briefly about evolution
Environment
+
Agents and Rules
Environment
Mutations
+
Agents and Rules
1e+07
simulated
evolved
predicted (0.4)
predicted (0.2)
group selection
Average population number
1e+06
100000
0.075
0.08
0.085
0.09
0.095
10000
1000
0
0.05
0.1
0.15
0.2
Proportion of fimbriate cells
0.25
0.3
0.35
Induction of nan/nag operons
Organisation of the fim/nan/nag operons
(simplified view)
GlcNac regulates
by displacing NagC
-- NagC ++
nan/nag operons
-- NanR ++
Metabolism/uptake
of sialic acid
Sialic acid regulates
by displacing NanR
fim operon
Expression of fimbriae/
activates host defenses
Organisation of the fim/nan/nag operons
1.4kb
yjhS yjhT nanC
-- NagC ++
-- NanR ++
fimB
A
E
I
fimS
Sialic acid activates
by displacing NanR
NanR --
nanATEK
GlcNAc-6P
activates by displacing NagC
NagC --
nagABCD
C
Sialic Acid: T=0
yjhS yjhT nanC
-- NagC ++
-- NanR ++
fimB
A
E
I
fimS
Sialic acid activates
by displacing NanR
NanR -GlcNAc-6P
activates by displacing NagC
NagC --
nanATEK
nagABCD
C
Sialic Acid T=T1
yjhS yjhT nanC
-- NagC ++
fimB
A
E
I
fimS
Sialic acid uptake/metabolism
is active
nag not yet active
GlcNac-6P produced
but genes not yet induced
NagC --
nanATEK
nagABCD
C
Sialic Acid T=T2
fimB
yjhS yjhT nanC
A
E
I
fimS
C
Sialic acid uptake/metabolism
is active
nanATEK
nag is active
nagABCD
Growth
Induction Problem



GlcNac-6P has been shown to be toxic.
There is a delay between induction of nan and
induction of nag.
From this, we would expect transient
GlcNac-6P accumulation.
Graph prepared by Jo Roobol
Problem:


Why does the NanR mutant show toxicity, but
not the WT?
The model points to a 2-stage induction
mechanism of nan
-
NanR is inefficiently replaced by sialic acid.
-
Methylation of NanR binding site

Activates sialic acid metabolism

Prevents NanR re-binding
Sialic Acid: T=0
yjhS yjhT nanC
-- NagC ++
-- NanR ++
fimB
A
E
I
fimS
Sialic acid activates
by displacing NanR
NanR -GlcNAc-6P
activates by displacing NagC
NagC --
nanATEK
nagABCD
C
Sialic Acid T=T1
yjhS yjhT nanC
-- NagC ++
fimB
-- NanR ++
A
E
I
fimS
Sialic acid uptake/metabolism
is partially active
NanR --
nag not yet active
Little GlcNac-6P accumulation!
NagC --
nanATEK
nagABCD
C
Sialic Acid T=T2
fimB
yjhS yjhT nanC
-- NanR ++
A
E
I
fimS
C
Sialic acid uptake/metabolism
is partially active
NanR --
nanATEK
nag is active
nagABCD
Growth
Sialic Acid T=T3
fimB
yjhS yjhT nanC
**
A
E
I
fimS
C
Sialic acid uptake/metabolism
is active
**
nanATEK
nag is active
nagABCD
Growth
Molecular scale model
Modelling the fim-switch



DNA contains a large number of non-specific
binding sites.
How do TF find the specific sites: 1D vs 3D
random walks.
We model the case of FimB