Lin Wang

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• Lin Wang
• Advisor Sima Setayeshgar

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Chemotaxis in E. coli
Physical constants Cell speed 20-30
µm/sec Mean run time 1 sec Mean tumble time
0.1 sec

• Dimensions
• Body size 1 µm in length
• 0.4 µm in radius
• Flagellum 10 µm long

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Adaptation in E. coli chemotaxis network

• Adaptation is the restoration of pre-stimulus
  behavior following a change in external stimulus.

Adaptation to addition /removal of
stimuli. Attractant 30 µM MeAsp. Repelent 100
µM NiCl2 YFP/CFP cheYp
The left most curve is the relation between the
adaptation time of E. coli and MeAsp (1e-2
1e4 µM).
Why does E. colis vary its response?
Sourjik et al. PNAS (2002), Howard C. Berg, PNAS
(1975)
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E. coli Chemotaxis network as a biological
signaling network

• Purpose of E. coli chemotaxis network
• As a chemical signaling network, E. coli
  chemotaxis network converts external signal to
  intracellular signal that regulates E. colis
  motile behavior.
• Role of Evolution
• Evolution optimizes performance of biological
  systems, which includes chemical signaling
  network.
• Evolution optimized functionality of E. coli
  chemotaxis network.

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Motivation

• E. coli chemotaxis as a well-characterized
  model chemical signaling network, amenable to
  quantitative analysis from the standpoint of
  information processing concepts, such as signal
  to noise, adaptation and memory.
• As a basic information processing system, E. coli
  chemotaxis network maximize the input-output
  mutual information transmission.

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Outline

• Modeling E. coli chemotaxis network
• Chemical signal transduction pathway (reactions)
• Numerical implementation of transduction pathway
  (stochsim package)
• Couple motor response, output of transduction
  pathway,to cell motion
• Preliminary numerical results
• Model validation (excitation and adaptation,
  motile behavior, etc)
• Input-output mutual information transmission
• Future work

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Modeling Chemotaxis in E. coli numerical
implementation scheme
Stimulus
Signal Transduction Pathway
Motor Response
Flagellar Response (?)
Motion
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Reactions

• Table I Signal Transduction Chemical Reactions

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Reactions cont.

• Table I Signal Transduction Chemical Reactions

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Simulating reactions

• We use Stochsim package, a general platform for
  simulating reactions using a stochastic method,
  to simulate reactions. Reactions have a
  probabilities, not rates, to occur.

• Unimolecular reaction

• Bimolecular reaction

n number of molecules from reaction system
n0 number of pseudomolecules NA Avogadro
constant
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Simulation ParametersReceptor Activation
En methylated receptor complex activation
probability, P1(n) Ena ligand-bound receptor
complex activation probability, P2(n) En
active form of En Ena active form of
Ena Table II Activation Probabilities
n P1(n) P2(n)
0 0.02 0.00291
1 0.1 0.02
2 0.312 0.1
3 0.94 0.345
4 0.997 0.98
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Simulation parameters proteins in chemotaxis
signal transduction
Table III Initial Numbers of Molecules
Molecule Number Concentration (µM)
Y 15684 18
Yp 0 0
R 250 0.29
E 6276 -
B 1928 2.27
Bp 0 0

• Reaction Volume 1.41 x 10-15 liter
• Rate constants given above.

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Simulation parametersmotor response

• Table IV parameters values

Paramter Value Literature value
KR 5.9 µM 312 µM
KT 1.7 µM 17 µM
Kf(0) 1.0e-5 µM 3.35e-4 µM
Kb(0) 1.5e4 µM 2.2e4 µM
µ 2.21 1.61
Linda Turner et al. Biophysical Journal (1999),
Philippe Cluzel et al., Science (2000)
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Motion

• Output of the chemotaxis network is the motor
  state which determines the motile behavior.
• R ? run T ? tumble

v 20 µm/s Dr 0.06205 s-1

• Run
• Tumble

? 4 µ -4.6 ß 18.32
Zou et al., Biophys. J. (2003), Berg and Brown,
Nature (1972)
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Outline

• Modeling E. coli chemotaxis network
• Chemical signal transduction pathway (reactions)
• Numerical implementation of transduction pathway
  (stochsim package)
• Couple motor response, output of transduction
  pathway, to cell motion
• Preliminary numerical results
• Model validation (excitation and adaptation,
  motile behavior, etc)
• Input-output mutual information transmission
• Future work

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Model validationstep impulse response
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Model validationadaptation time
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Input-Output mutual informationconstruct
input-output relation
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Outline

• Modeling E. coli chemotaxis network
• Chemical signal transduction pathway (reactions)
• Motor and flagella response, and cell motion
• Numerical implementation (stochsim package)
• Preliminary numerical results
• Model validation (excitation and adaptation,
  motile behavior, etc)
• Input-output mutual information transmission
• Future work

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Future work
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• Thank you.