in vitro biochemical circuits leader: erik winfree co-leader: jongmin kim 1.the synthetic biology...
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In vitro biochemical circuitsLeader: Erik Winfree co-leader: Jongmin Kim
1. The synthetic biology problem2. The experimental system we are investigating3. A general problem it motivates4. A specific problem to tackle
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In vitro biochemical circuitsLeader: Erik Winfree co-leader: Jongmin Kim
1. The synthetic biology problemReductionism: system behavior from component characteristicsThe complexity gapSynthesis of in vitro biochemical circuits
2. The experimental system we are investigating3. A general problem it motivates4. A specific problem to tackle
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In vitro biochemical circuitsLeader: Erik Winfree co-leader: Jongmin Kim
1. The synthetic biology problem2. The experimental system we are investigating
Circuits of rationally-designed transcriptional switches
3. A general problem it motivates4. A specific problem to tackle
?RNase
RNA
DNA
RNAP
promoterDA
RAI
R
[R]
[A]tot
[I]tot
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1. The synthetic biology problem2. The experimental system we are investigating3. A general problem it motivates
There are many subspecies and side reactions.
How do we obtain a simplified model for analysis?
4. A specific problem to tackle
By RNA polymerase
ONONOFFOFF
In vitro biochemical circuitsLeader: Erik Winfree co-leader: Jongmin Kim
By RNase
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In vitro biochemical circuitsLeader: Erik Winfree co-leader: Jongmin Kim
1. The synthetic biology problem2. The experimental system we are investigating3. A general problem it motivates4. A specific problem to tackle
Phase space analysis of simple circuits:a bistable switch and a ring oscillator
10
0
1
1 0
e.g. “cloud size”
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Mass action chemical kinetics
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An adjustable transcriptional switch
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Networks of transcriptional switches
By RNA polymerase
ONONOFFOFF
By RNase
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Michaelis-Menten reactions
Michaelis-Menten reactions lead to competition for - RNA polymerase by DNA templates- RNase by RNA products
Can have interesting consequences like Winner-take-all network
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Experimental system
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Sequence design
TCATGGAACTACAACAGGCAACTAATACGACTCACTATAGGGAGAAGCAACGATACGGTCTAGAGTCACTAAGAGTAATACAGAACTGACAAAGTCAGAAA
GCTGAGTGATATCCC TC TTCG TTGCTATG CCAGATCTCAGTGATTCT CATTAT GTCTTGACTG TTTC AGTCTTTGTGTTCCT AGTACCTTGATGTT GTCCGTTGATTAT
Promoter
8 5
27
hairpin
AGCAACGATACGGTCTAGAGTCACTAAGAGTAATACAGAA AAA
GG
GA
GA
CT
GA
C
GT
CA
G
AA
A
6
8 27 Signal
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Components
RNAP RNase HRNase R
D12
D21
A2
A1
ATTGAGGTAAGAAAGGTAAGGATAATACGACTCACTATAGGGAGAAACAAAGAACGAACGACACTAATGAACTACTACTACACACTAATACTGACAAAGTCAGAAA
CTAATGAACTACTACTACACACTAATACGACTCACTATAGGGAGAAGGAGAGGCGAAGATTGAGGTAAGAAAGGTAAGGATAATACTGACAAAGTCAGAAA
TATTAGTGTGTAGTAGTAGTTCATTAGTGTCGTTC
TATTATCCTTACCTTTCTTACCTCAATCTTCGCCT
TTTCTGACTTTGTCAGTATTATCC TT ACC TTT C TT ACCTCAATCTTCGCCTCTCCTTCTCCCTATAGTGAGTCG
TTTC TGACTTTGTCAGTATTAGTGTGTAGTAGTAGTTCATTAGTGTCGTTCG TTCTTTGTTTCTCCCTATAGTGAGTCG
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Transition curve – DNA inhibitor
T7 RNAPRNase H(1U)RNase R(200nM)
D21=100nMA=500nM
Sw21Inh1
Inh2
add DNA
Inhibitor 2
Atot dI1
I2
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Transition curve – RNA inhibitor
T7 RNAPRNase H(0.7U)RNase R(150nM)
D13=0-60nMD21=80nMA=400nM
Atot
Inhibitor 2Inhibitor 1Sw21
Sw13
Inh2Inh1
I2
I1
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Fluorescence
OFF
ON
High signal
Low signal
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Bistable switch
Inh2Inh1
Sw21
Sw12
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Bistable switch
Sw12 ON
Sw
21 O
N
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Summary
• Need better quantitative understanding
- make a better system
- understand how messy system works
Cells have misfolded, mutated species all the time
Neural networks have distributed architecture
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Possible complications
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Inhibitor interacting with Switch/Enzyme complex
D
A
I RNAP
I + RDA -> RD + AI
I
A
D
RNAP
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Abortive transcripts (Messiness #1)
D
RNAP
A
D
RNAP
A
I
R + DA <-> RDA -> R + DA + I60, I45, I14 ,I8
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RNase R needs to clean up
I8, I14RNase R
RNase R
Rr + In <-> RrIn -> Rr
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Activator crosstalk
D21A2
D21A2
D21 + A2 -> D21A2
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Nicked at -12/-13 has no crosstalk
I2
A1 or A2
D21
Stoichiometric amounts of activatorTranscription level (%)
sp non sp non
1x 0x 1x 2x 3x 1x 0x 1x 2x 3x
100 28 24 24 24 100 10 10 11 9
T7 RNAP
D21=100nM, 500nM
D21+A1
D21
D21+A2
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Incomplete degradation by RNaseH (Messiness #2)
I45
A
hp RNase H
A
RNase HI
RhAI -> Rh + A + In + hp
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RNase H can keep going
I45
A
RNase H
I27
A
RNase H
I14
A
RNase H
Rh + AIn <-> RhAIn -> Rh + AIm
I27
A
I14
A
RNase H
RNase H
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Lots of truncated RNA products
I2
I2 hairpin ?
R(0nM) R(100nM) R(200nM) R(400nM)
D21=30nMA=150nM
T7 RNAPRNase H(1.5U)RNase R
60 120 120 120 60180 180 180 12060 60 180
Sw21
Inh2sI2
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Activator-activator or Inhibitor-inhibitor complex
I I
I
I
I + I -> II
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RNA extension by RNAP
RNAP
I
I’
RNAP
R + I -> RI -> R + I’
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Extended RNA species
R(0nM) R(100nM) R(200nM) R(400nM)
D21=30nMA=150nM
T7 RNAPRNase H(1.5U)RNase R
60 120 120 120 60180 180 180 12060 60 180
Sw21
Inh2
Extended I2 complex
I2
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Enzyme life-time
RNAP
R -> ø
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NTP/buffer exhaustion
D
RNAP
A
D
RNAP
A
I
ATP GTP
CTP
UTP
RDA + 60NTP -> R+ DA + I
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I2 level is stable (up to ~6hr)
R(0nM) R(100nM) R(200nM) R(400nM)
D21=30nMA=150nM
T7 RNAPRNase H(1.5U)RNase R
60 120 120 120 60180 180 180 12060 60 180
Sw21
Inh2
I2
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RNase degrading DNA
A
RNase H
RNase H
Rh + A -> RhA -> Rh
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DNA bands are stable
R(0nM) R(100nM) R(200nM) R(400nM)
D21=30nMA=150nM
T7 RNAPRNase H(1.5U)RNase R
60 120 120 120 60180 180 180 12060 60 180
Sw21
Inh2
DNA sense
DNA temp
BH-A
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Initial burst
D
RNAP
A
D
RNAP
A
I
RDA -> R + DA + Ik(t)
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Model choice (basic)
D + A <-> DA
A + I <-> AI
DA + I <-> DAI -> D + AI
R + DA <-> RDA -> R + DA + I
R + D <-> RD -> R + D + I
Rh + AI <-> RhAI -> Rh + A
Rr + I <-> RrI -> Rr
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Model choice (with messiness)
D + A <-> DA A + In <-> AIn
DA + In <-> DAIn <-> D + AIn
R + DA <-> RDA -> R + DA + In
R + DAI1n <-> RDAI1
n -> R + DAI1n + I2
n’
R + D <-> RD -> R + D + In
Rh + AIn <-> RhAIn -> Rh + AIm (+ hp) Rr + In <-> RrIn -> Rr
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Questions
• Bistable circuit phase diagram
• Oscillator circuit phase diagram
• Bistable circuit model reduction
• Oscillator circuit model reduction
• Transcription switch input/output model reduction