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Sept 25 Biochemical Networks
Chemotaxis and Motility in E. coliExamples of Biochemical and Genetic Networks
• Background
• Chemotaxis- signal transduction network
Bacterial Chemotaxis
Flagellated bacteria “swim” using a reversible rotary motor linked bya flexible coupling (the hook) to a thin helical propeller (the flagellarfilament). The motor derives its energy from protons driven into thecell by chemical gradients. The direction of the motor rotationdepends in part on signals generated by sensory systems, of whichthe best studied analyzes chemical stimuli.
Chemotaxis - is the directed movement of cells towards an“attractant” or away from a “repellent”.
• For a series of QuickTime movies showing swimming bacteria with fluorescentlystained flagella see: http://www.rowland.org/bacteria/movies.html
• For a review of bacterial motility see Berg, H.C. "Motile behavior of bacteria".Physics Today, 53(1), 24-29 (2000). (http://www.aip.org/pt/jan00/berg.htm)
A photomicrograph of three cellsshowing the flagella filaments.
Each filament forms an extend helixseveral cell lengths long.
The filament is attached to the cellsurface through a flexible ‘universaljoint’ called the hook.
Each filament is rotated by a reversible rotary motor, the direction of the motoris regulated in response to changing environmental conditions.
Rotationally averaged reconstruction of electron micrographs of purified hook-basalbodies. The rings seen in the image and labeled in the schematic diagram (right)are the L ring, P ring, MS ring, and C ring. (Digital print courtesy of David DeRosier,Brandeis University.)
The E. coli Flagellar Motor- a true rotary motor
Increasing attractant
No Gradient
Increasing repellent
Chemotactic Behavior of Free Swimming Bacteria
A ‘Soft Agar’ Chemotaxis Plate
A mixture of growth media and a low concentration of agar are mixed ina Petri plate. The agar concentration is not high enough to solidify themedia but sufficient to prevent mixing by convection.
The agar forms a mesh like network makingwater filled channels that the bacteria canswim through.
A ‘Soft Agar’ Chemotaxis Plate
As the bacteria grow to higher densities, they generate a gradientof attractant as they consume it in the media.
cells cells
AttractantConcentration
A ‘Soft Agar’ Chemotaxis Plate
The bacteria swim up the gradients of attractants to form‘chemotactic rings’ .
This is a ‘macroscopic’ behavior. The chemotactic ring is theresult of the ‘averaged” behavior of a population of cells. Eachcell within the population behaves independently and theyexhibit significant cell to cell variability (individuality).
A ‘Soft Agar’ Chemotaxis Plate
‘Serine’ ring
‘Aspartate’ ring
Each ‘ring’ consists of tens of millions of cells. The cells outside the rings arestill chemotactic but are just not ‘experiencing’ a chemical gradient.Serine and aspartate are equally effective “attractants”, but in this assay theattractant gradient is generated by growth of the bacteria and serine ispreferentially consumed before aspartate.
Swimming E. coli
Fluorescent Flagella Bundle
TetheredE. coli
Tracking E. coli
Assays of Bacterial Motility
BrownianMotion
Latex Beads
Assays of Bacterial Motility
Surface SwarmingSalmonella
Flow Chamber
Assay
PatternFormation
LaserTrap
The Molecular Machinery of Chemotaxis
OUTPUT
SignalTransduction
INPUT Attractant concentration
Directionof
rotation
The Molecular Machinery of Chemotaxis
OUTPUT
SignalTransduction
INPUT
Directionof
rotation
Attractants bind receptors at the cellsurface changing their “state”.(methylated chemoreceptors MCPS).
TsrTarTapTrg
The Molecular Machinery of Chemotaxis
OUTPUT
INPUT
Directionof
rotation
The MCPs regulate the activity of ahistidine kinase - autophosphorylateson a histidine residue.Tsr
TarTapTrg
CheA(CheW)
P~
The Molecular Machinery of Chemotaxis
OUTPUT
INPUT
Directionof
rotation
CheA transfers its phosphate to asignaling protein CheY to formCheY~P.Tsr
TarTapTrg
CheA(CheW)CheY
P~
P~
The Molecular Machinery of Chemotaxis
OUTPUT
INPUT
Directionof
rotation
CheY~P binds to the “switch” andcauses the motor to reverse direction.The signal is turned off by CheZwhich dephosphorylates CheY.
TsrTarTapTrg
CheA(CheW)CheYCheZ
P~
P~
MCPCheA
(CheW)
CheY~P CheZ CheY
Motor
+ attractant inactive
Excitatory Pathway
At ‘steady state’, CheY~P levels in the cell are constant and there is someprobability of the cell tumbling. Binding of attractant of the receptor-kinase complex, results in decreased CheY~P levels and reduces theprobability of tumbling and the bacteria will tend to continue in the samedirection.
The Molecular Machinery of Chemotaxis
OUTPUT
INPUT
Directionof
rotation
TsrTarTapTrg
CheA(CheW)CheYCheZ
CheRCheB
P~
P~
Adaptation involves two proteins, CheRand CheB, that modify the receptor tocounteract the effects of the attractant.
Adaptation Pathway
MCP-(CH3)0 MCP-(CH3)3 MCP-(CH3)4MCP-(CH3)1 MCP-(CH3)2
MCP-(CH3)0
+AttractantMCP-(CH3)3
+AttractantMCP-(CH3)4
+AttractantMCP-(CH3)1
+AttractantMCP-(CH3)2
+Attractant
CheR
CheB~P
In a receptor dimer there will 65 possible states (5 methylation states and twooccupancy states per monomer). If receptors function in receptor clusters,essentially a continuum of states may exist.
Some Issues in Chemotaxis:
• Sensing of Change in Concentration not absolute concentrationi.e. temporal sensing
• Exact Adaptation
• Sensitivity and Amplification
• Signal Integration from different Attractants/Repellents
The range of concentration of attractants that will cause a chemotacticresponse is about 5 orders of magnitude (nM ‡ mM)
Spiro, P. A., Parkinson, J. S. & Othmer, H. G. (1997) Proc. Natl. Acad. Sci. USA94: 7263–7268.
Barkai, N. & Leibler, S. (1997) Nature (London) 387: 913–917.
Tau-Mu Yi, Yun Huang , Melvin I. Simon, and John Doyle (2000)Proc. Natl. Acad. Sci. USA 97: 4649–4653.*
Bray, D., Levin, M. D. & Morton-Firth, C. J. (1998) Nature (London)393: 85–88. *
References on Modeling Chemotaxis
* - these models have incorporated the Barkai model.
Robustness in simple biochemical networksN. Barkai & S. Leibler
Departments of Physics and Molecular Biology, Princeton University, Princeton, New Jersey 08544, USA
Simplified modelof the chemotaxissystem.
Mechanism for robust adaptation
E is transformed to a modified form, Em, by theenzyme R; enzyme B catalyses the reversemodification reaction. Em is active with a probabilityof am(l), which depends on the input level l. Robustadaptation is achieved when R works at saturationand B acts only on the active form of Em. Note thatthe rate of reverse modification is determined bythe system’s output and does not depend directlyon the concentration of Em (vertical bar at the endof the arrow).
Some parameters used to characterize the network.
Tumble frequencySteady-State Tumble Frequency
Adaptation TimeAdaptation precision
The system activity, A, of a model system which was subject to a series ofstep-like changes in the attractant concentration, is plotted as a function oftime. Attractant was repeatedly added to the system and removed after 20min, with successive concentration steps of l of 1, 3, 5 and 7 mM. Note theasymmetry to addition compared with removal of ligand, both in theresponse magnitude and the adaptation time.
Chemotactic response and adaptation in the Model.
Adaptation precision
Adaptation Time
How robust is the model with respect to variation in parameters?
Testing the predictions of the Barkai modelRobustness in bacterial chemotaxis.U. Alon, M. G. Surette, N. Barkai & S. Leibler
• The concentration of che proteins were altered as a simple method tovary network parameters.
• The behavior of the cells were measured (adaptation precision,adaptation time and steady-state tumble frequency).
• In each case the predictions of the model we observed.