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Transcript of Gene Expression Talk publish version - Virginia Techcourses.cs.vt.edu/~cs6404/CS6404_Gene Expression...
Computational Science and Engineering
Gene Expression and Gene Regulation
Yang Cao
Department of Computer Science
http://courses.cs.vt.edu/~cs6404
Computational Science and Engineering
Summary
• Gene Expression• Translation• Transcription • A biochemical Model
• Gene Regulation• Repressor• Activator• Feedback Control• Models for gene regulation network
Computational Science and Engineering
Gene Expression
Gene is just a small part of DNA. The gene expression follows the process of:
DNA ���� RNA ���� Protein
Gene expression shows big difference between prokaryotic and eukaryotic cells. Most of the models of gene networks proposed in literature are for prokaryotic cells.
Computational Science and Engineering
Transcription
Transcription from DNA to RNA is based on the base pair. However RNA doesn’t have “T”, instead it has “U”, which pairs with “A” just as “T” does.
DNA ���� RNA
Computational Science and Engineering
The Process of Transcription
1. Binding
2. Initiation
3. Elongation
4. Termination
Initiation figure
Computational Science and Engineering
Transcription (Continue)
• Transcription is carried out by the enzyme RNA Polymerase (RNAP)
• Several types of RNA are produced • mRNAs• rRNAs• tRNAs• Small RNAs (can regulate transcription)
• Transcription occurs only on one strand of DNA
Computational Science and Engineering
RNA Processing
• In Prokaryotic cells, mRNA can be immediately translated by ribosomes.
• In Eukaryotic cells, RNA has to be processed and then transported to cytoplasm.
Computational Science and Engineering
Translation: From RNA to Protein
• An mRNA sequence is decoded in sets of three nucleotides, called codon.
• Amino acids are specified by codons (not one by one). • Amino acids and codons are connected by tRNAs.
tRNA
Computational Science and Engineering
Translation: From RNA to Protein
• Genetic Code is universal
AUG = Met
Computational Science and Engineering
Translation: From RNA to Protein
• RNA message is decoded by Ribosomes• Initiation starts at binding site (prokaryotic) or “AUG”• Elongation • Termination
Computational Science and Engineering
A Model for Prokaryotic Gene Expression
1. Transcription Initiation (the binding and initiation)
2. Elongation (RBS is available before elongation terminates
3. Translation Initiation
4. Elongation
RNAPP RNAPP +→•
RNAPPRNAPP •→+
RNAPTr RNAPP →•
ElRNAPPRBSTrRNAP ++→
RibRBSRBS Ribosome →+
RBS RibosomeRibRBS +→
RBS ElRibRibRBS +→
decayRBS →
Protein ElRib →
decayProtein →
1-18
1 M10−
= sk
1
2 10−
= sk
1
3 1 −= sk
1
4 1 −= sk
1-18
5 M10 −= sk
1
6 25.2 −= sk
1
7 5.0 −= sk
1
8 3.0 −= sk
1
9 015.0 −= sk
15
10 1042.6 −−×= sk
Computational Science and Engineering
Simulation Results
Kierzek, A. M. et al. J. Biol. Chem. 2001;276:8165-8172
Computational Science and Engineering
Some Further Discussion
ElRNAPPRBSTrRNAP ++→
• The elongation process
• A more detailed model for that
RBS ElRibRibRBS +→
Protein ElRib →
1nn TrRNAPTrRNAP+
→
0TrRNAPP →• RNAP
ElRNAPPRBSTrRNAPN ++→
…A C
n n+1
G
N
RNAP
…Promoter
0
Computational Science and Engineering
Model Difference
1. From Exponential distribution to Gamma distribution
2. RNAP collision may happen (Dr. Kim pointed out this should never happen in the real cell)
…A C
n n+1
G
N
RNAP
…Promoter
PromoterT G
RNAP
NNAAAA →→→→
−110 L
a
N
i
N
i
iNataEttt ≈Γ=∑
=
),( then,)( e wher,1
pp
Computational Science and Engineering
Summary
• Gene Expression• Translation• Transcription • A biochemical Model
• Gene Regulation• Repressor• Activator• Feedback Control• Models for gene regulation network
Computational Science and Engineering
Some History: Lac Operon
.
Discovered by Francois Jacob and Jacques Monod, They got
Nobel Prize in Physiology or Medicine in 1965
During World War II, Monod was testing the effects of combinations of sugars as nutrient sources for E.
coli. He found that bacteria grown with two different sugars often displayed two phases of growth. For example, if glucose and lactose were both provided, glucose would be metabolized first (growth phase I, see Figure 2) and then lactose (growth phase II). But why was there a delay between the two growth phases?
Computational Science and Engineering
Regulation Reactions in Gene Models
Gene expression becomes interesting when regulation system
Is added into it.
Add the following reaction set
into the initiation of transcription
or written as: RNAPP
ORNAPP •→+
ORNAPPORNAPP +•→++
RIRI
RIRI
RORO
RORO
+→
→+
+→
→+
−
−
−
−
Computational Science and Engineering
Feedback Control
K
x(k+1)=Ax(k)+Bu(k)y(k)=Cx(k)
u(k)
x(k)
y(k)Target System
Feedback Gain
-
+
d(k)
Control Law
Closed Loop System
Characteristic Equation
Computational Science and Engineering
Positive Feedback Regulation System
Gardner TS, Cantor CR, Collins JJ, Construction of a genetic toggle switch in
Escherichia coli, NATURE 403 (6767): 339-342 JAN 20 2000
Computational Science and Engineering
Simple Regulation in Biology – Circuits?
RNApA
OBpromoterOA
g2
ORB
RNAp
BA
OBpromoterOA
g1
AND
Computational Science and Engineering
Yes! Circuits!
Kitano H, Funahashi A, Matsuoka Y, et al., Using process diagrams for the graphical representation of biological networks, NATURE BIOTECHNOLOGY 23 (8): 961-966 AUG 2005
Computational Science and Engineering
Lambda-phage affected E. Coli
Stochastic effects play an important role
in lytic/lysogenic
decision network
Arkin et al. 1997, 1998
Lysis
Lysogeny
Computational Science and Engineering
Highlight the lambda phage regulation
cI
PL
PRN cro
PRM
cI Cro
If cI wins, PR and PL are repressed and the cell enters lysogeny
If Cro wins, PRM is repressed and the cells enters the lytic cycle
Computational Science and EngineeringcI must bind to OR1 to repress rightwards transcription
cI represses PR – shuts off cro
cI activates PRM – expression of cI
PRM
Computational Science and EngineeringcI must bind to the left operators to prevent left transcription
N
PL
cI
PRM
OL
321
cI represses PL – shuts off N
Computational Science and EngineeringCro must bind to OR3 to repress expression of repressor by PRM
Cro represses PRM – shuts off cI expression
PRMPRE
Computational Science and Engineering
Another Gene Network
Heat Shock Response Model
El-Samad H, Kurata H, Doyle JC, et al.
Surviving heat shock: Control strategies for robustness and performancePNAS 102 (8): 2736-2741 FEB 22 2005
Computational Science and Engineering
Temp
environ
Temp
cellFolded
Proteins
Unfolded
ProteinsAggregates
Loss of Protein
Function
CellDeath
Computational Science and Engineering
32σ mRNA
32σ
TranslationHeat
Translational Induction of heat shock transcription factor σσσσσσσσ3232 : evidence of
a built-in thermosensor. Morita et. al, Genes & Dev. 1999
Initiation codon
Computational Science and Engineering
σ70
RNAP
σ
RNAP
DNAK
Lon
ftsH
RNAP
DNAK
σ
σ
σ mRNA
DnaK
rpoH
FtsH Lon
Heat
Molecular
Modules
degradation
foldedunfolded
aggregate
σ
Computational Science and Engineering
Negative Feedback in Heat Shock Response (HSR)
σ DNAKσ
RNAP
RNAP
σ
DnaK FtsH
DNAK
Computational Science and Engineering
Time50 60 70
6
Time
Wild TypeNo FeedforwardLow S32 FluxConstitutive S32 DegNo DnaK interaction
8000
24000
0
1E+0
50 60 700
2
4
6
8
0
150
300
450
600
Free σ32
Total σ32DNAK
Unfolded