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

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

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

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

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”

Mass action chemical kinetics

An adjustable transcriptional switch

Networks of transcriptional switches

By RNA polymerase

ONONOFFOFF

By RNase

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

Experimental system

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

Components

RNAP RNase HRNase R

D12

D21

A2

A1

ATTGAGGTAAGAAAGGTAAGGATAATACGACTCACTATAGGGAGAAACAAAGAACGAACGACACTAATGAACTACTACTACACACTAATACTGACAAAGTCAGAAA

CTAATGAACTACTACTACACACTAATACGACTCACTATAGGGAGAAGGAGAGGCGAAGATTGAGGTAAGAAAGGTAAGGATAATACTGACAAAGTCAGAAA

TATTAGTGTGTAGTAGTAGTTCATTAGTGTCGTTC

TATTATCCTTACCTTTCTTACCTCAATCTTCGCCT

TTTCTGACTTTGTCAGTATTATCC TT ACC TTT C TT ACCTCAATCTTCGCCTCTCCTTCTCCCTATAGTGAGTCG

TTTC TGACTTTGTCAGTATTAGTGTGTAGTAGTAGTTCATTAGTGTCGTTCG TTCTTTGTTTCTCCCTATAGTGAGTCG

Transition curve – DNA inhibitor

T7 RNAPRNase H(1U)RNase R(200nM)

D21=100nMA=500nM

Sw21Inh1

Inh2

add DNA

Inhibitor 2

Atot dI1

I2

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

Fluorescence

OFF

ON

High signal

Low signal

Bistable switch

Inh2Inh1

Sw21

Sw12

Bistable switch

Sw12 ON

Sw

21 O

N

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

Possible complications

Inhibitor interacting with Switch/Enzyme complex

D

A

I RNAP

I + RDA -> RD + AI

I

A

D

RNAP

Abortive transcripts (Messiness #1)

D

RNAP

A

D

RNAP

A

I

R + DA <-> RDA -> R + DA + I60, I45, I14 ,I8

RNase R needs to clean up

I8, I14RNase R

RNase R

Rr + In <-> RrIn -> Rr

Activator crosstalk

D21A2

D21A2

D21 + A2 -> D21A2

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

Incomplete degradation by RNaseH (Messiness #2)

I45

A

hp RNase H

A

RNase HI

RhAI -> Rh + A + In + hp

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

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

Activator-activator or Inhibitor-inhibitor complex

I I

I

I

I + I -> II

RNA extension by RNAP

RNAP

I

I’

RNAP

R + I -> RI -> R + I’

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

Enzyme life-time

RNAP

R -> ø

NTP/buffer exhaustion

D

RNAP

A

D

RNAP

A

I

ATP GTP

CTP

UTP

RDA + 60NTP -> R+ DA + I

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

RNase degrading DNA

A

RNase H

RNase H

Rh + A -> RhA -> Rh

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

Initial burst

D

RNAP

A

D

RNAP

A

I

RDA -> R + DA + Ik(t)

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

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

Questions

• Bistable circuit phase diagram

• Oscillator circuit phase diagram

• Bistable circuit model reduction

• Oscillator circuit model reduction

• Transcription switch input/output model reduction