the eukaryotic cell cycle : molecules, mechanisms, and mathematical models
DESCRIPTION
The Eukaryotic Cell Cycle : Molecules, Mechanisms, and Mathematical Models. John J. Tyson Virginia Tech Bela Novak Tech Univ Budapest. DNA. …TACCCGATGGCGAAATGC. mRNA. …AUGGGCUACCGCUUUACG. …Met -Gly -Tyr -Arg -Phe -Thr. Protein. -P. Enzyme. ATP. ADP. E 4. E 1. E 3. - PowerPoint PPT PresentationTRANSCRIPT
The Eukaryotic Cell Cycle :The Eukaryotic Cell Cycle :Molecules, Mechanisms, and Molecules, Mechanisms, and
Mathematical ModelsMathematical Models
John J. TysonJohn J. Tyson
Virginia TechVirginia Tech
Bela NovakBela Novak
Tech Univ BudapestTech Univ Budapest
Computational Molecular Biology
DNA
mRNA
Protein
Enzyme
Reaction Network
Cell Physiology
…TACCCGATGGCGAAATGC...
…AUGGGCUACCGCUUUACG...
…Met -Gly -Tyr -Arg -Phe -Thr...
ATP ADP
-P
X Y ZE1
E2
E3E4
M(anaphase)
M(telophase)
cell divisio
n
G1
S
G2
M(metaphase)
Start
M(anaphase)
M(telophase)
cell divisio
n
Finish
G1
S
G2
M(metaphase)
G2 Checkpoint
G1 Checkpoint
Metaphase Checkpoint
Cdk1
Cln2
Clb5
Clb2Cdc20
Cdh1
Sic1
Cln3
Mass
Budding
Cln2SBF
Bck2
and
Clb5MBF
DNA synthesisClb?
SCFP Sic1
Cln2
Sic1
Sic1 Clb5
Swi5
Sister chromatid separation
Unaligned Xsomes
Cdc20 Cdc20Clb5Clb2
Cdh1
Cdh1
Clb2Cdc20
Cdc20
Sic1 Clb2
Clb2Mcm1
Mitosis
'1 1 2
d[Cln2][SBF] [Cln2]
dk k k
t
' '3 3 4 4 5
d[Clb2][Mcm1] [Cdh1] [Clb2] [Sic1][Clb2]
dk k k k k
t
' '6 6 T 7 7
6 T 7
[Cdc20] [Cdh1] [Cdh1] [Clb5] [Cdh1]d[Cdh1]
d [Cdh1] [Cdh1] [Cdh1]
k k k k
t J J
synthesis degradation
synthesis degradation binding
activation inactivation
0 50 100 150
0.0
0.5
1.0
1.5
0.0
0.5
0.0
0.5
1.0
1
2
Time (min)
Sic1
mass
Clb2
Cln2
Cdh1
Simulation of the budding yeast cell cycle
G1 S/M
Cdc20
CdkCycB
Cdh1 CK
I
Cdc20 ClnCdk
+APC
CK
I
ClnCdk
+APC
CKI = Sic1
Table 6. Properties of clb, sic1, and hct1 mutants
mass at birth
mass at
SBF 50%
mass at
DNA repl.
mass at bud ini.
mass at division
TG1
(min)
changed
parameter
Comments
1 wild type
(daughter) 0.71 1.07
(71’) 1.15 (84’)
1.15 (84’)
1.64 (146’)
84 CT 146 min (time of occurrence of event)
2 clb1 clb2
0.71 1.07 1.16 1.16 No mit k's,b2 = 0
k"s,b2 = 0 Surana 1991 Table 1, G2 arrest.
3 clb1 clb2
1X GAL-CLB2 0.65 1.10 1.19 1.19 1.50 105 k's,b2 = 0.1
k"s,b2 = 0 Surana 1993 Fig 4, 1X GAL-CLB2 is OK, 4X GAL-CLB2 (or 1X GAL-CLB2db) causes telophase arrest.
4 clb5 clb6 0.73 1.07
(65’) 1.30 (99’)
1.17 (80’)
1.70 (146’)
99 k's,b5 = 0 k"s,b5 = 0
Schwob 1993 Fig 4, DNA repl begins 30 min after SBF activation.
5 clb5 clb6
GAL-CLB5 0.61 0.93 0.92 0.96 1.41 73 k's,b5 = 0.1
k"s,b5 = 0 Schwob 1993 Fig 6, DNA repl concurrent with SBF activation in both GAL-CLB5 and GAL-CLB5db.
6 sic1 0.66 1.00
(73’) 0.82 (37’)
1.06 (83’)
1.52 (146’)
38 k's,c1 = 0 k"s,c1 = 0
Schneider 1996 Fig 4, sic1 uncouples S phase from budding.
7 sic1 GAL-SIC1 0.80 1.07 1.38 1.17 1.86 94 k's,c1 = 0.1 k"s,c1 = 0
Verma 1997 Fig3B, Nugroho & Mendenhall 1994 Fig 2, most cells are viable.
8 hct1 0.73 1.08 1.17 1.18 1.69 82 k"d,b2 = 0.01 Schwab 1997 Fig 2, viable, size like WT, Clb2 level high
throughout the cycle. 9 sic1 hct1
0.71 No SBF 0.72 No bud No mit k's,c1 = 0
k"d,b2 = 0.01 Visintin 1997, telophase arrest.
10 sic1 GAL-CLB5
first cycle second cycle
0.71 0.52
0.74
0.73
No repl
0.76
1.20
k's,b5 = 0.1 k"s,b5 = 0 k's,c1 = 0
Schwob 1994 Fig 7C, inviable. First cycle OK, DNA repl advanced; but pre-repl complexes cannot form and cell dies after the first cycle.
Why do these calculations?
Is the model “yeast shaped”?
Bioinformatics role: the model organizes lots of experimental information.
New science: prediction, insight
0 1 20.0
0.5
1.0
0
50
100
150Cdc20
Cdk1
Clb2,5
Cln2
Sic1Cdh1
G1
M
period
mass
Cd
k1 a
ctiv
ity
0 1 20.0
0.5
1.0
G1
M
cell mass
Bifurcation diagram
Cdc20
Cdk1
Clb2,5
Cln2
Sic1Cdh1
Cd
k1 a
ctiv
ity
How can CS help?
Experimental Database
Wiring Diagram
Differential Equations Parameter Values
Analysis Simulation
Visualization-Translation
Experimental Database
Problem-Solving Environment
Cliff Shaffer
Naren Ramakrishnan
Marc Vass
Layne Watson
Jason Zwolak
Parameter Estimation
DatabaseSimulation Translation
Prop 1Prop 1 Good fit
Prop 2Prop 2 Bad fit
...... ...
Error Function (parameters)
Parameter Estimation
Kurt Kohn (1999) Mol Biol Cell