In vitro biochemical circuits

1
In vitro biochemical circuits

• Leader Erik Winfree co-leader Jongmin Kim

• The synthetic biology problem
• The experimental system we are investigating
• A general problem it motivates
• A specific problem to tackle

2
In vitro biochemical circuits

• Leader Erik Winfree co-leader Jongmin Kim

• The synthetic biology problem
• Reductionism system behavior from component
  characteristics
• The complexity gap
• Synthesis of in vitro biochemical circuits
• The experimental system we are investigating
• A general problem it motivates
• A specific problem to tackle

3
In vitro biochemical circuits

• Leader Erik Winfree co-leader Jongmin Kim

• The synthetic biology problem
• The experimental system we are investigating
• Circuits of rationally-designed transcriptional
  switches
• A general problem it motivates
• A specific problem to tackle

R
R
Itot
DA
Atot
promoter
A
I
R
4
In vitro biochemical circuits

• Leader Erik Winfree co-leader Jongmin Kim

• The synthetic biology problem
• The experimental system we are investigating
• A general problem it motivates
• There are many subspecies and side reactions.
• How do we obtain a simplified model for analysis?
  
• A specific problem to tackle

ON
OFF
ON
OFF
By RNA polymerase
By RNase
5
In vitro biochemical circuits

• Leader Erik Winfree co-leader Jongmin Kim

• The synthetic biology problem
• The experimental system we are investigating
• A general problem it motivates
• A specific problem to tackle
• Phase space analysis of simple circuits
• a bistable switch and a ring oscillator

e.g. cloud size
6
Mass action chemical kinetics
7
An adjustable transcriptional switch
8
Networks of transcriptional switches
9
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
10
Experimental system
11
Sequence design
TCATGGAACTACAACAGGCAACTAATACGACTCACTATAGGGAGAAGCAA
CGATACGGTCTAGAGTCACTAAGAGTAATACAGAACTGACAAAGTCAGAA
A
GCTGAGTGATATCCC TC TTCG TTGCTATG
CCAGATCTCAGTGATTCT CATTAT GTCTTGACTG TTTC AGTCTTT
GTGTTCCT AGTACCTTGATGTT GTCCGTTGATTAT
Promoter
A
A
A
GGGAGA
CTGAC
GTCAG
AGCAACGATACGGTCTAGAGTCACTAAGAGTAATACAGAA
AAA
12
Components
D12
ATTGAGGTAAGAAAGGTAAGGATAATACGACTCACTATAGGGAGAAACAA
AGAACGAACGACACTAATGAACTACTACTACACACTAATACTGACAAAGT
CAGAAA
TTTC TGACTTTGTCAGTATTAGTGTGTAGTAGTAGTTCATTAGTG
TCGTTCG TTCTTTGTTTCTCCCTATAGTGAGTCG
TATTATCCTTACCTTTCTTACCTCAATCTTCGCCT
A2
D21
CTAATGAACTACTACTACACACTAATACGACTCACTATAGGGAGAAGGAG
AGGCGAAGATTGAGGTAAGAAAGGTAAGGATAATACTGACAAAGTCAGAA
A
TATTAGTGTGTAGTAGTAGTTCATTAGTGTCGTTC
TTTCTGACTTTGTCAGTATTATCC TT ACC TTT C TT
ACCTCAATCTTCGCCTCTCCTTCTCCCTATAGTGAGTCG
A1
RNAP
RNase H
RNase R
13
Transition curve DNA inhibitor
T7 RNAP RNase H(1U) RNase R(200nM)
I2
D21100nM A500nM
Inhibitor 2
Inh2
add DNA
Sw21
dI1
Inh1
Atot
14
Transition curve RNA inhibitor
T7 RNAP RNase H(0.7U) RNase R(150nM)
I2
D130-60nM D2180nM A400nM
Inhibitor 2
Sw21
Inhibitor 1
Inh2
Inh1
Atot
I1
Sw13
15
Fluorescence
OFF
High signal
ON
Low signal
16
Bistable switch
Sw21
Inh2
Inh1
Sw12
17
Bistable switch
Sw21 ON
Sw12 ON
18
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

19
Possible complications
20
Inhibitor interacting with Switch/Enzyme complex
RNAP
RNAP
I RDA -gt RD AI
21
Abortive transcripts (Messiness 1)
RNAP
RNAP
R DA lt-gt RDA -gt R DA I60, I45, I14 ,I8
22
RNase R needs to clean up
RNase R
I8, I14
RNase R
Rr In lt-gt RrIn -gt Rr
23
Activator crosstalk
A2
D21 A2 -gt D21A2
24
Nicked at -12/-13 has no crosstalk
D21A1
D21A2
D21
T7 RNAP
D21100nM, 500nM
D21
I2
A1 or A2
Stoichiometric amounts of activator
Transcription level ()
25
Incomplete degradation by RNaseH (Messiness 2)
RNase H
I45
hp
RNase H
A
RhAI -gt Rh A In hp
26
RNase H can keep going
RNase H
I45
Rh AIn lt-gt RhAIn -gt Rh AIm
A
RNase H
I27
I27
RNase H
A
A
RNase H
RNase H
I14
I14
A
A
27
Lots of truncated RNA products
R(0nM)
R(100nM)
R(200nM)
R(400nM)
T7 RNAP RNase H(1.5U) RNase R
60
120
120
120
60
180
180
180
120
60
60
180
D2130nM A150nM
I2
Inh2
sI2
Sw21
I2 hairpin ?
28
Activator-activator or Inhibitor-inhibitor complex
I
I
I I -gt II
29
RNA extension by RNAP
RNAP
I
I
RNAP
R I -gt RI -gt R I
30
Extended RNA species
R(0nM)
R(100nM)
R(200nM)
R(400nM)
T7 RNAP RNase H(1.5U) RNase R
60
120
120
120
60
180
180
180
120
60
60
180
Extended I2 complex
D2130nM A150nM
I2
Inh2
Sw21
31
Enzyme life-time
RNAP
R -gt ø
32
NTP/buffer exhaustion
RNAP
CTP
ATP
GTP
UTP
RNAP
RDA 60NTP -gt R DA I
33
I2 level is stable (up to 6hr)
R(0nM)
R(100nM)
R(200nM)
R(400nM)
T7 RNAP RNase H(1.5U) RNase R
60
120
120
120
60
180
180
180
120
60
60
180
D2130nM A150nM
I2
Inh2
Sw21
34
RNase degrading DNA
RNase H
RNase H
Rh A -gt RhA -gt Rh
35
DNA bands are stable
R(0nM)
R(100nM)
R(200nM)
R(400nM)
T7 RNAP RNase H(1.5U) RNase R
60
120
120
120
60
180
180
180
120
60
60
180
D2130nM A150nM
DNA sense
DNA temp
Inh2
BH-A
Sw21
36
Initial burst
RNAP
RNAP
RDA -gt R DA I
k(t)
37
Model choice (basic)

• D A lt-gt DA
• A I lt-gt AI
• DA I lt-gt DAI -gt D AI
• R DA lt-gt RDA -gt R DA I
• R D lt-gt RD -gt R D I
• Rh AI lt-gt RhAI -gt Rh A
• Rr I lt-gt RrI -gt Rr

38
Model choice (with messiness)

• D A lt-gt DA
• A In lt-gt AIn
• DA In lt-gt DAIn lt-gt D AIn
• R DA lt-gt RDA -gt R DA In
• R DAI1n lt-gt RDAI1n -gt R DAI1n I2n
• R D lt-gt RD -gt R D In
• Rh AIn lt-gt RhAIn -gt Rh AIm ( hp)
• Rr In lt-gt RrIn -gt Rr

39
Questions

• Bistable circuit phase diagram
• Oscillator circuit phase diagram
• Bistable circuit model reduction
• Oscillator circuit model reduction
• Transcription switch input/output model reduction