vav ylon is 10302009
TRANSCRIPT
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Modeling cytoskeleton
self-assembly
Dimitrios Vavylonis
Department of Physics, Lehigh University
BIOS 10Lehigh University
Oct 30, 2009
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How does the cell achieveinternal organization?
How is it regulated?
Can we model cell structure and dynamics?
Cell organization
http://mgl.scripps.edu/people/goodsell/gallery/patterson.html
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Thermal and viscous forces are very
large on the scale of proteins
secm/9|proteinv
The result of this is diffusion
t= 0 t= 3 psec = 3 10-12 sec
in this time the protein travels
0.027 nm
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computer picks arandom direction (up/down/left/right)
with equal probability at each step
(a Monte Carlo method)
drunkards walk
Modeling diffusion: random walk on a lattice
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Brownian motion, continued
Diffusion coefficient D for a protein in the cell ~ 4 Pm2/sec
0 steps 100 steps 1000 steps
x(t) = constant (D t)1/2
x(t)
t= 0 fraction of a sec several sec
5 Pm
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Polymerization of proteins to filaments
Kovar, Harris, Mahaffy, Higgs, Pollard
Cell, 124 423 (2006)
D ~D/2 ~D/3
+ cross-links rigid, stationary cytoskeleton
Alberts et al, MBOC
actin filament
actin
monomers
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Microtubule filaments and cell organization
Alberts et al, MBOC
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Search and capture of chromosomes
by microtubules during mitosis
dividing cell
dynamic instability
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GTP-cap model of dynamic instability
Alberts et al, MBOC
GDP-tubulin
GTP-tubulin
cap
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GTP-cap toy model
GTP-tubulin monomers
diffuse in the cytoplasm
at concentration c
microtubule filament
hydrolysis at blue/red interface, rate khydrok+c
kcat
k-
Gillespie algorithm (a Monte Carlo method)1. pick an event at random according to rate constants
(polymerization, depolymerization, hydrolysis)
2. update configuration and time
krescue
GDP-tubulinGTP-tubulin
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Numerical simulations of the model
large GTP-tubulin monomer concentrations
small GTP-tubulin monomer concentrations
example of length
trajectory at small
concentrations:
Time (sec)
subu
nits
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Insights from simple model
time (sec)
su
bunits
other trajectories averageelongation rate
monomer
concentration
0
catastrophe
and rescue
region
c*
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Models of chromosome search and capture
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fission yeast
Wu lab, Ohio State Univ. 2007
Neuron growth
actin
Forscher lab, Yale Univ.
budding yeastAmberg Mol. Biol. Cell (1998)
Actin filaments and cell shape changes
actin patches actin cables
motile fibroblast (GFP-actin)Watanabe lab, Kyoto Univ.
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Actin polymerization: driving force for cellular motions
5 nm
barbed endpointed end
Svitkina et al J. Cell Biol. 139 397(1997)
Watanabe and Mitchison,Science, 295 8 (2002)
fibroblast
EGFP-actin
~5 Pm
movie
duration 156 sec
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Actin network within a motile cell
Svitkina et al. J. Cell Biol. 139 397(1997)
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Motility of cancer cells causes metastasis
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http://www.nytimes.com/2009/06/09/science/09cell.html
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Low concentrations of markers: actin speckles
Numerical simulations
of actin turnover based
on analysis of speckleimages
(ongoing project)
Naoki Watanabe, Kyoto University
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CHD-GFP
binds to sides of
actin filaments
spindle poles
Spb1Jian-Qiu Wu (Pollard lab, Yale Univ 2007)
Vavylonis, Wu, et al. Science 2008
Actin Cytoskeleton in Cell Division
fission yeast cdc25-22cell
Zhou and WangMol. Biol. Cell2008
GFP-actin kidney cell
Pollard and Earnshaw, Cell Biology (2002)
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Contractile ring assembles from ~ 63 myosin II nodes in ~ 10 min
~ 40 myosin II (Myo2p) molecules/node
~ 2 formin Cdc12p dimers/nodeWu and Pollard, Science 2005
Rlc1p-3GFP
Vavylonis, Wu, Hao, OShaughnessy, Pollard,
Science 2008
spinning disk confocal microscopy
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Actin meshwork establishes connections among nodes
red: nodes (Rlc1-RFP1)green: actin filaments (GFP-CHD)
cdc25-22cellsradial projection
0
2SR
arclengths
data: Wu (2007, 2008)
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actin filamentpolymerization
m/sec2.0~ P
actin filament capture
nm100~cr
traction on filamentsbetween nodes
pNF 4t
lifetime of connections
lifetime of filaments
sec20~
sec20~
Dynamic reestablishment of connections plasticity of network
Search, capture, pull and release model
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Simulations with search, capture, pull and release
30x time lapse,
20min
Simulated radial projection
red: nodes
green: actin
0 2SR experiment:
x model reproduces many observed features
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Dependence on parameter values
red: nodes
green: actin filaments
m/sec2.0 Ppolv
m/sec04.0 Ppo lv
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Hachet and Simanis, Genes and Development, 2008
Formin Mutant: clump formation
Wild type: robust ring formation
Some mutant cells form clumps
ring
clumps
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Clump formation kinetics
d
l
Qtclump
1|
Qt /1* |
Qdrcv2
00'|
22
orcQdD|
2/1*** )(Dttvl
00
*
/ rldrl
0t
clump size ~ r0
vrtclump /0
A B
Node
rootmean
square
displaceme
nt
time(Qt)
B: Slope 1(clump formation)
*l
*t
0r
A: Slope (diffusion)
clumpt
0.1 1 100.01
0.01
0.1
Monte Carlo Simulation of 2D bulk of nodes
Scaling arguments:
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Actin meshwork in the middle of a dividing yeast cell
4D confocal microscopy experiments (Jian-Qiu Wu, Ohio State)
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skeletonization(ridge point detection)
Tracking of polymerizing
actin filaments in vitro
Li et al. (ISBI 2009, MICCAI 2009)
Actin filament network in the middle of
dividing cell
Systematic image analysis of actin in cells and in vitro
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Pom1p
??
Mid1p
cytoplasmic
concentrtation
gradients?
Cell polarization and establishment of cell center
Padte et al. Curr. Biol 2006
Celton-Morizur et al. J. Cell Sci. 2006
Wu et al Dev Cell 2003
wildtype
Padte et al. Curr. Biol 2006
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Martin and Chang, Dev. Cell, 8, 479 (2006)
Kamasaki et al., Nature Cell Biol., 7, 916, (2005).
actin cables: bundles of actin
filaments
nucleated by formin For3pretrograde flow
Formin For3p and actin cable assembly
EM: bundles of ~ 10 actinfilaments
1.7 Pm
short filaments ~ 100 subunits
actin filament: 370 sub/Pm
Yang and Pon PNAS (2002)
v ~ 0.3 m/sec ~ 110 actin subunits/seP
budding yeast
cables nucleated
by forminsBnr1p, Bni1p
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3D actin cable turnover model
(based on model proposed by Martin and Chang)
~ 50
depends on actin polymerization
Wang and Vavylonis, PloS ONE(2008)
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Fluorescence recovery after For3p photobleaching
Martin and Chang (2006)
comparison of simulated recovery to experiment:
LatA: sequesters actin
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Acknowledgments
Nikola Ojkic, Matthew Smith, Tyler Drake
Hui Wang, Alex Veksler, Eddy Yusuf
Department of Physics,
Lehigh University
Xiaolei Huang, Tian Shen, Hongsheng LiDepartment of Computer Science,
Lehigh University
Naoki Watanabe
Department of Pharmacology
Kyoto University
Jian-Qiu Wu
Department of Molecular Genetics,Ohio State University
Thomas Pollard
Department of Molecular, Cellular and Developmental Biology,
Yale University
Support: HFSP, NIH, Lehigh University