Modeling and Analysis Challenges in Biology: From Genes to Cells to Systems Francis J. Doyle III...
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Transcript of Modeling and Analysis Challenges in Biology: From Genes to Cells to Systems Francis J. Doyle III...
Modeling and Analysis Challenges in Biology: From Genes to Cells to Systems
Francis J. Doyle IIIDept. of Chemical Engineering
Biomolecular Science & EngineeringInstitute for Collaborative Biotechnologies
F.J. Doyle III US-EC Workshop on Infrastructure Needs for Systems Biology, Boston, May 3, 2007
Role of Models & Analysis
[Kitano, 2002]
F.J. Doyle III US-EC Workshop on Infrastructure Needs for Systems Biology, Boston, May 3, 2007
Spectrum of Network Modeling
[Stelling, 2005]
All models are abstractions of reality [Bolouri/Davidson]
All models are wrong … some are useful [Box]
Models are most useful when they are wrong [Various]
F.J. Doyle III US-EC Workshop on Infrastructure Needs for Systems Biology, Boston, May 3, 2007
Modeling for Analysis
Analysis Robustness – design principles, hypothesis
generation Sensitivity for design of experiment Sensitivity for ID of targets Identifiability analysis for ID of markers
Issues Context is key Multi-scale issues Stochastic issues Local vs. Global behavior Model “validation”
F.J. Doyle III US-EC Workshop on Infrastructure Needs for Systems Biology, Boston, May 3, 2007
Validation, Verification, Consistency, etc.
Validation or verification is critical step in any model identification problem [Ljung, 1999]
Typically: ~half of data used for regression; ~half for “testing”
Matching of data (to date): “consistency” In practice, only “invalidation” is possible [Poolla et al., 1994]
Contradiction w/ data is often the most valuable role of a model Model discrimination can suggest new experiments
Competing hypotheses can be resolved
Data sets can be invalidated
Various statistical tools for model invalidation Measure of error
Confidence intervals
Likelihood ratios
F.J. Doyle III US-EC Workshop on Infrastructure Needs for Systems Biology, Boston, May 3, 2007
Circadian Clock Circuits Across Organisms
Proteins
Genes
Networks
Cells
Organism
Organs
Length,Time
Multi-Scale Systems Analysis of Circadian Rhythm
F.J. Doyle III US-EC Workshop on Infrastructure Needs for Systems Biology, Boston, May 3, 2007
Mammalian Circadian Clock Circuits
Traditional control engineering elements:
positive and negative feedback loopsredundant loops
time delaygain modulation
hierarchical architecture
But… what is the purpose???
F.J. Doyle III US-EC Workshop on Infrastructure Needs for Systems Biology, Boston, May 3, 2007
Robust Yet Fragile (Gene Level)
T=transcription/translationTR=intracellular transportGR=gene regulationP=phosphorylationDP=dephosphorylationDG/DL=degradation
open=single loopfilled=double loop
3 (modified) architectures• single loop• dual loop• redundant dual loop
Insights from control-theoretic analysis:[Stelling et al., PNAS, 2004]
(i) 2-loop architecture used for clock precision(ii) robustness (local) at the expense of fragility (global)
F.J. Doyle III US-EC Workshop on Infrastructure Needs for Systems Biology, Boston, May 3, 2007
Robust Yet Fragile (Cell Level)
[Ruoff et al., 2005]
[Herzog et al., 2004]
X
X
X
X
X
Insights from control-theoretic analysis:
(i) Timekeeping is robust to expected disturbances (Temp)(ii) Timekeeping is fragile to “attack” (VIP)
F.J. Doyle III US-EC Workshop on Infrastructure Needs for Systems Biology, Boston, May 3, 2007
Testing Old Hypotheses
“A daily program is useless (indeed disadvantageous) unless it can be phased correctly to local time. Thus it is the phase-control, more than the period control, inherent in entrainment which is the principal dividend selection has reaped in converting a daily program into an oscillator by assuring its automatic re-initiation…”
[Pittendrigh & Daan, 1976]
Locomotor timing relative to clock
clock precision required
robust to clock error
F.J. Doyle III US-EC Workshop on Infrastructure Needs for Systems Biology, Boston, May 3, 2007
Other Performance Metrics[Bagheri, Stelling, Doyle III, Bioinformatics, 2007]
Mouse
Drosophila
F.J. Doyle III US-EC Workshop on Infrastructure Needs for Systems Biology, Boston, May 3, 2007
Clock “Performance” is Context Dependent
[Herzog et al., 2004]
in vivo
explants
isolated
Period Cycle-to-cyclevariation
F.J. Doyle III US-EC Workshop on Infrastructure Needs for Systems Biology, Boston, May 3, 2007
Model Formulation [To, Henson, Herzog, Doyle III, Biophys. J., 2007]
Modified Neuron Model
VIP release
local VIP profile
)()( , taMt iPi
N
jjiji tt
1
)()(
D
Teq K
RC
kcAMPeq
10
T
eq
R
tC )(
*2
*
*1
**
1
1
CBK
CB
CBK
CB
CBdt
dCB
PPP
K
T
P
CkRkdt
dCrf VIP/VAPC2 complex
receptor saturation
equilibrium cAMP
fraction of phosphorylated CREB
1
1/2
1
1/2
1/√2 1/√5
1√5 1/2√2
1
1 unit
Coupling Rule
GRN Module
STN Module
ICC Module
F.J. Doyle III US-EC Workshop on Infrastructure Needs for Systems Biology, Boston, May 3, 2007
Entrainment Behavior
0 24 48 72 96 120 144 168 192 216 2400
2
4
6
Time (hr)
per
mR
NA
(nM
)
0 24 48 72 96 120 144 168 192 216 2400
1
2
3
4
Time (hr)
Ave
rag
e pe
r m
RN
A (
nM)
VIP pulse
0 12 24 36 48 60 72 84 96 108 1200
5
10
Time (hr)
per
mR
NA
(nM
)
0 12 24 36 48 60 72 84 96 108 1200
5
10
Time (hr)
per
mR
NA
(nM
)0 12 24 36 48 60 72 84 96 108 120
0
5
10
Time (hr)
per
mR
NA
(nM
)
A.
B.
C.
VIP Entrainment Photic Entrainment
Insights from control-theoretic analysis:[To et al., Biophys J, 2007]
(i) intercellular coupling allows coherent timekeeping with relatively heterogeneous cells
(ii) synchronicity depends on cell-specific propertiesas well as network (coupling) properties
[Aton et al., 2005]
Reverse “clock genetics” showed that Cry1 and Cry2 are each dispensable in circadian behavior
WT Cry1-/- Cry2-/-Cry1-/-:Cry2-/-
van der Horst, 1999
New data [Kay lab]: Clock defects in single cells are autonomous, but not necessarily in SCN slice or animal
behavior
SingleSCN
neurons
WT Cry2-/- Cry1-/- Per1-/-
F.J. Doyle III US-EC Workshop on Infrastructure Needs for Systems Biology, Boston, May 3, 2007
Stochastic Cellular Network Model
ContinuumM-M kinetics
Stochastic firingof elementary
reactions
i
isPsPc KC
CBTvvi
n
ijj ji
jPPii r
MM
,1 ,2
1
2
1
Coupling viaPer transcription rateCore
(molecular)oscillator
stochasticsimulation
model}
Stochastic Mutant Response[Liu et al., Cell, 2007]
cell network (Cry1 -/-) isolated cells (Cry1 -/-)
F.J. Doyle III US-EC Workshop on Infrastructure Needs for Systems Biology, Boston, May 3, 2007
The Ultimate Level: Organism Performance
Proteins
Genes
Networks
Cells
Organism
Organs
Length,Time
Multi-scale Robust Performance Issues
Phase/period control
Protein activity/level control
Distribution control
Context-dependent control
Organism Activity Control
Insights from control analyses:
(i) Robust performance requirements vary across scales(context is key!)
(ii) Analysis of upper level in hierarchy requires appropriate detail at lower level (different from reductionism!)
F.J. Doyle III US-EC Workshop on Infrastructure Needs for Systems Biology, Boston, May 3, 2007
Summary – Infrastructure Needs
Modeling/Analysis
Get beyond intracellular focus
Efficient/hierarchical/multi-scale/stochastic models
Seamless incorporation of analysis tools
Modular model merging? (a la CAPE-OPEN)
Formalized hypothesis testing?
Modeling and Analysis Challenges in Biology: From Genes to Cells to Systems
Francis J. Doyle IIIDept. of Chemical Engineering
Biomolecular Science & EngineeringInstitute for Collaborative Biotechnologies
Dr. Rudi Gunawan Neda Bagheri Kirsten Meeker Henry Mirsky Stephanie Taylor Tsz Leung To Melanie Zeilinger Dr. Peter Chang
Collaborators: M. Henson (UMass), E. Herzog (WashU), S. Kay (Scripps),
L. Petzold (UCSB), J. Stelling (ETH)