DNA Computing and Robotics
Based on Deoxyribozymes
DAO-E Sierpinski triangle experiments
Paul Rothemund,
Nick Papadakis,
Erik Winfree,
PLoS Biology 2:
e424 (2004)
340nm
• Part 1: How do we program mixtures
of molecules in solution?
• Part 2: How do we program behavior
of an individual molecule?
Introduction to deoxyribozymes:
C T T C A A C G T A
G A A G T T G C A T
G A A G T T G C A T
Single stranded
DNA (or RNA)
Complementary
F
R
+
T
C
A
C
T
S A
T
rA
GG
A
A
G
A
G
Substrate recognition region
F
A
Deoxyribozyme
G
T
G
A
TA AG
A
C
T
G
T
C G
C C C
T
G C
T
AG
C
Catalytic core
T
C
Cleavage
Substrate recognition
region
R
TA
CG
AT
CG
TA
A TA AG
TA
C
rA
T
G
GT
C G
GC C C
G C
AT
AG
AT
GC
AT
GC
F
T
C
A
C
T
A
T
rA
OF
R
G
G
A
A
G
A
G
Joyce 1995, 1997
Introduction to deoxyribozymes II:
Substrate
recognition
region
S
kon
+
P1
kcat
P1
koff's
+
E
P2
E*S
F
R
+
T
C
A
C
T
S A
T
rA
GG
A
A
G
A
G
Substrate
recognition
region
P2
Catalytic core
Substrate recognition region
F
A
Deoxyribozyme
G
T
G
A
TA AG
A
C
T
G
T
C G
C C C
T
G C
T
AG
C
Catalytic core
T
C
Cleavage
Substrate recognition
region
R
TA
CG
AT
CG
TA
A TA AG
TA
C
rA
T
G
GT
C G
GC C C
G C
AT
AG
AT
GC
AT
GC
F
T
C
A
C
T
A
T
rA
OF
Joyce 1995, 1997
…and we can combine them with stem loops:
kcat
S
E
P1
P2
S
P1
E
koff's
P2
P1
P2
E
…into a two-state switch:
P1
P2
0
1
Detector gate
or
sensor
or
YES gate
or
…
Complete set of switches:
NOT Gate:
AND Gate:
i1 o
0 1
1 0
ANDANDNOT:
i1
0
1
0
1
i2
0
0
1
1
o
0
0
0
1
i1
0
1
0
0
1
1
0
1
i2
0
0
1
0
1
0
1
1
ii13
0
0
0
1
0
1
1
1
o
0
0
0
0
1
0
0
0
Before we give examples of gates, a reminder:
1 is an increase in fluorescence, 0 no such increase!
F
R
+
T
C
A
C
T
S A
T
rA
GG
A
A
G
A
G
Substrate recognition region
F
A
Deoxyribozyme
G
T
G
A
TA AG
A
C
T
G
T
C G
C C C
T
G C
T
AG
C
Catalytic core
T
C
Cleavage
Substrate recognition
region
R
TA
CG
AT
CG
TA
A TA AG
TA
C
rA
T
GT G
C G
GC C C
G C
AT
AG
AT
GC
AT
GC
F
T
C
A
C
T
A
T
rA
OF
R
G
G
A
A
G
A
G
A bit more about FRET:
580 nm
580 nm
TAMRA
TAMRA
A T
C G
G C
G C
A T
C G
C G
A T
C G
G C
A
A
T
d1
Cleavage
T
G
C
C
T
G
T
G C
T A
C G
A
C
G
G
A
C
A
d2
C
C
A
C
G
A
Fluorescein
T
G
G
T
G
C
A
Fluorescein
520 nm
480 nm
520 nm
480 nm
d1 < d2, FRET is stronger
Catalytic Molecular Beacons as Sensor Gates
F
F
R
T A
CG
A T
CG
T A
Active Form A
TA AG
Cleavage
T A
C
rA
T
GT G
IA
C G
GC C C
G C
A T
A G
A GG
A T
AG
GC
A
A T
G
GC
A
CG
G
T
A A*S*IA A
T A
G
TA
A T
GC
GC
AT
C
T
G
G AA TT
A
C
T T A A
A
G
T
G
A
TA AG
G A
C
G
T
G
A T
C G
GC C C
A T
G C
A T
A G
GC
A T
G
A CG
T
A
A
G
A
I
A
T
C
T
C
A
ACA
+
T
C
A
C
T
S A
T
rA
GG
A
A
G
A
G
R
A
250000
200000
150000
FU 100000
Inactive Form
Y
I
ES
rA T A T C A C T
50000
A
0
0
F
OF
Joyce 1995, Breaker 1999, Tyagi, Kramer 1996
100 200
t (min)
300
400
I1
0
1
Stojanovic et al., ChemBioChem 2001
Stojanovic et al., J. Am. Chem. Soc. 2002
NOT Gates – Inverters:
GG
C CT
A
C
F
T A 3' C
C
G
CG C
T A 3'
AT
A T C
C
G
T
A
C G TA
A T
T A
T A
CG
GC
G
A T
T
A T ACC
GC
G
C
T
A T
AT
I
B
A
Active Form
rA  B*IB C G
T
C
B
rA
AT
G
GG
T AA
G
C
C
G
C C C T CG
G A
C
G A
A T Cleavage G C A
C
T
A TG
G
AT
A TC
T
A T GCGA
I
B
A
CG
G CG
A T
G
A
TA
T
A T A
G C
G
T T A
T
A
G CT
A T
G
G C
C CG A
F
R
3'
200000
R
Inactive Form
150000
3'
FU
NOT IB
rA T A T C A C T
OF
100000
50000
F
0
I2
1
0
100
t(min)
200
0
Stojanovic et al., J. Am. Chem. Soc. 2002
300
Dual Input Molecular Computation Elements: AND Gate
F
T
C
A
C
T
A
S T
rA
GG
A
A
G
A
G
+
R
T GTA
C
T
C
T
A
I
B G
A
A
T
GC GA
AT
CG
TA
A TA AG
TA
C
T T
T
G
G TC G
GC C C
AT
G C
AT
A G
C
G
AT
G
A CG
T
A
A
G
A
I
A
T
C
T
C
A
ACA
F
IA AND IB
T
C
A
C
T
A
T
rA
OF
180000
FU
160000
140000
AB
120000
100000
I1
I1
80000
60000
40000
20000
0
0
I2
I2
0
1
0
-20000 0
50
100
150
200
t(min)
250
Triple Input Elements: ANDANDNOT (INHIBIT)
F
T
C
A
C
T
A
T
rA
G
G
A
A
G
A
G
R
3'
ACTT
C
T
C
T
IB T
G
T
A
T
A
G
T A
C G
A T
C G
T A GT A C C
C
IA AND IB AND NOT IC
A TT
A
A
C
T A AC
GG
G
C
T
CC
T
C
GA C
G CA
T
T
G
I
A T GCGA
C
G
A
A T
T
T
GC
GT TA
A T
G CG
A
T
A
A
G
I
A
A
T
C
T
A A AC
C
I3
I3
I1
0
I1
0
0
I2
1
0
I1
0
F
T
C
A
C
T
A
T
rA
OF
I3
I3
I2
I2
0
I3
I2
I1
0
Triple Input Elements: ANDAND
T C AG
A
A
T
C
A
2 A
C
A
T
A
C AAC
A G
C T
T G
A A
A T
C T
GT A
C
C
C
A
A
C
TG
CC
G
T
TG
T
G A CG
G
A
A
A C
T
A G
A T
G
C TC
G T
A
A
A C
C
G AT
T
A
G
T
A
T
C
T
T
GA
T
A
T A
A
T C
G
A T
1 A
G C
T
A
A
C
G G
G T
GA C G
C T GA C
A C T
i
2
AG T C
T
C
A
T
A
G
T
G T
A A
G C
A
C C
T AT
CG
A A
C
AT
F
C T
T
A T
T G
AC
T
A
A
C
C
AC T
C
T G
T
A GA T G
A
T A
3
C T
A
A A
T G
A T
T
A
A
T T
T T T GT A
G
C A
3
rA
A
C
T G
A
G
C
G A
G
G
C
C
A
A
A C
G
T T
A
A
T
T
A
G A
A A
C
G T G
T
T C
A
C
A
C
G A
R G TC
GA TG T
A T
G C
T
A G
C
C
A
TA
C A
T
A
T CA GA
AT
G T
T
G
T
A
C
A
A
T G
A
T
G
C T
A
G
C
C
C
C
A
G
C
T
T G C
A
T
G
G
T GA
C
i
i1, i2, i
c3
c3
i
i
i1
i1ANDi2ANDi3
FU
40000
12
30000
c3
c3
c3
3
1
0
0
1
0
0
0
1
1
0
F
3
3
c3
0
123
2
2
2
2
1
13
20000
23
3
1
10000
2
0
3
0
50
100
t(m in)
Harvey Lederman
150
0
Before we give examples of gates, a reminder:
1 is an increase in fluorescence, 0 no such increase!
F
R
+
T
C
A
C
T
S A
T
rA
GG
A
A
G
A
G
Substrate recognition region
F
A
Deoxyribozyme
G
T
G
A
TA AG
A
C
T
G
T
C G
C C C
T
G C
T
AG
C
Catalytic core
T
C
R
F
T
C
A
C
T
A
T
rA
OF
R
G
G
A
A
G
A
G
Substrate recognition
region
F
F
kcat
T
T
P1
P2
Q
Cleavage
TA
CG
AT
CG
TA
A TA AG
TA
C
rA
T
G
GT
C G
GC C C
G C
AT
AG
AT
GC
AT
GC
Q
First deoxyribozyme
kcat
P1
P2
Q
E*S
Q
Second deoxyribozyme
Let’s add A (0 or 1) and X (0 or 1) and get O (0 or 1, or 2):
A
+
X
=
O
0
1
0
1
0
1
2
00
01
00
01
00 01 10
GR GR GR
i1
i2
F
F
kcat
P1
P2
Q
T
T
Q
First deoxyribozyme
kcat
P1
P2
Q
E*S
Q
Second deoxyribozyme
0+0
Implement addition with gates:
9000
7000
5000
3000
1000
-1000
0
100
200
300
200
300
200
300
200
300
-3000
C S
-5000
0+1
10000
0 0
8000
6000
4000
i1
i2
i2
i1
i1
i1
i1
i2
S
F
T
01
1
i1
i2
0
0 1
i2
T
-2000
0
100
1+0
15000
0 1
i2
10000
5000
0
i 1 i2
10
2
i1
20000
i2
C
2000
T
0
i2
F
i1
100
-5000
i2
i1
i1
i2
1 0
1+1
35000
30000
25000
20000
C
S
15000
10000
5000
Stojanovic & Stefanovic, J. Am. Chem. Soc. 2003
0
-5000 0
100
Now, a twist:
1 is an increase in fluorescence, 0 no such increase!
F
R
+
T
C
A
C
T
S A
T
rA
GG
A
A
G
A
G
Substrate recognition region
F
A
Deoxyribozyme
G
T
G
A
TA AG
A
C
T
G
T
C G
C C C
T
G C
T
AG
C
Catalytic core
T
C
Cleavage
R
Substrate recognition
region
1
TA
CG
AT
CG
TA
A TA AG
TA
C
rA
T
GT G
C G
GC C C
G C
AT
AG
AT
GC
AT
GC
F
T
C
A
C
T
A
T
rA
OF
R
G
G
A
A
G
A
G
Here is 7-segment display:
A
d1
F
Segments required
B
G
d2
d3
d4
d5
d6
d7
d8
d9
E
C
D
A
B
C
D
E
F
G
1







2







3







4







5







6







7







8







9







J. Macdonald, Columbia University
More arithmetical operations:
Test by constructing simple 2+2-bit adder
Binary inputs
A1 A0 + X1 X0
1+1:
Designate 4
oligonucleotides
as binary inputs
0 1 + 0 1
Non general
Display output
=
Expected display
1+2:
0 1 + 1 0
=
2+1:
1 0 + 0 1
=
2+2:
1 0 + 1 0
=
Adder result
“hard-wired” into
decoder
J. Macdonald, Columbia University
Adding 2+2 with visual display:
Non-general adder
• Determine logic gates required, and layout
wells (via Microsoft Excel)
outputin
gates
Binary inputs
A1 A0 + X1 X0
1+1:
1+2:
0 1 + 0 1
0 1 + 1 0
Non general
Display output
Segment A
Yes A0
Yes X0
Segment F
Segment B
A1 AND X1
Yes A0
Yes A1
=
=
2+1:
1 0 + 0 1
=
2+2:
1 0 + 1 0
=
Segment G
Yes A1
Yes A0
Segment E
A0 AND X0
Segment C
Yes X1
Yes A1
Segment D
Yes A0
Yes X0
Very simple logic
gate arrangement
required:
• 4 YES gates
• 2 AND gates
Fully constructible
from reagents in
freezer
Tested with all input
combinations….
J. Macdonald, Columbia University
Adding 2+2 with visual display:
(A1A0 + X1X0  display)
Binary inputs: 01+01=
01+10=
10+01=
10+10= No inputs
Perfect digital
behavior
Constructed &
tested in a
single day
Fluorescence reader
~20-30mins
7-segment
Display
B&W imager
within ~1hr
Color photograph
~5hrs
Arithmetic
(1+1=2)
(1+2=3)
(2+1=3)
(2+2=4)
Background
J. Macdonald, Columbia University; DNA 13, 2007
2x2 multiplier with visual display:
(A1A0 × X1X0  display)
Gate arrangement
19 gates required
Segment A
A0 AND X1
A1 AND X0
Segment B
Segment F
A0 and X0
A1 and X1
A0 and X1 not A1
A1 and X0 not X1
A1 not A0 not X0
Segment G
Yes A1
Yes X1
Segment C
Segment E
A1 and A0
A1 and X0 not A0
X1 and X0
A0 and X1 not X0
A1 and X1
Segment D A0 and X0
A1 and A0
X1 and X0
A0 and X1
A1 and X0
J. Macdonald, Columbia University
2x2 multiplier with visual display:
Color photography
Binary inputs:
(A1A0 × X1X0  display)
01 × 01 =
01 × 10 =
01 × 11 =
10 × 01 =
10 × 10 =
(1×1=1)
(1×2=2)
(1×3=3)
(2×1=2)
(2×2=4)
10 × 11 =
11 × 01 =
11 × 10 =
11 × 11 =
(00 × 00)
(2×3=6)
(3×1=3)
(3×2=6)
(3×3=9)
no input
control
7-segment
Display
Arithmetic
Binary inputs:
7-segment
Display
Arithmetic
J. Macdonald, Columbia University
Silicomimetic automata project (MAYA):
MAYA:
MAYA-II:
MAYA-III:
i11
i12
i11
i13
i22
i14
i24
i14
Stojanovic&Stefanovic.
Nat.Biotech. 2003
Human designed
Macdonald et al. Nano Lett. 2006
Computer designed
i12
i21
i13
i22
i21
i22
i13
i23
i14
i13
i22
i14
i24
i23
i12
i24
i11
i21
i22
i13
i21
i12
i11
i24
i12
i21
i14
i13
i23
i22
i11
i24
i11
i23
i12
i23
i12
i24
i14
i14
i11
i21
i12
i11
i14
i24
i14
i23
i22
i11
i22
i21
i22
i13
i13
i13
i12
i13
i13
i14
i11
i12
i21
i23
i13
i24
i11
i14
i13
i12
i24
i22
i21
i23
i12
i11
i12
i21
i21
i23
i22
i11
i24
i24
i14
i13
i12
i23
i12
i11
i11
i21
i23
i22
i11
i14
i13
i12
i14
i14
i24
i13
i23
i14
Pei, Matamoros, et al. in testing
Human designed
Goal:
Goal:
Goal:
Demonstrate power of
molecular computing!
What does it take to coordinate
large number of gates?
Field programmable arrays of gates!
-Teaching “by example”
-Selecting strategy (“carving”)
Implementation of tic-tac-toe playing algorithm with deoxiribozymes:
Molecular Array of YES and ANDANDNOT Gates (MAYA)
Stojanovic, Stefanovic, Nat. Biotech. 2003
MAYA vs. Milan: losing game
Mg2+
From Sci. Am. 2008
Is it possible to have serial circuits?
o
U
i1
(Upstream enzyme)
D
communication component
(downstream enzyme)
Intergate Communication : Ligase-Cleavase
G
C
T
A
A
T T T
S2
C A
C
T
G
T G
C
S
1 Union
C T G G
A
T
A
C
T
C
A
A
PIM
A
A
G
C
G
HO
T
T
G
A
C C A
G
T A G G G
T
C
C
T T T
T
T G
A
Cleavage
A C A CT
A G A G A AG A
A
A
A A
S3
C
A R
GP
G
G A GAA
1
T
G
C
C
T A T C AC T
A G
T G C T C T T C TG rA
A
C
A
A A A T AGT
C
T
C
G
C A A
C G
C
G
A CG T
YES 1
G C
G
T
F
P
Ligase E47
5
4
3
2
1
0
0
50
100
150
200
250
tim e (m in)
Stanka Semova, Dmitry Kolpashchikov
Ligase-cleaves XOR circuit:
XOR
IA
IB
1
2
2
1
O
IA IB O
O1
F
o1
0
0
0
1
0
1
0
1
1
1
1
0
Rn
10
8
1
6
2
1,2
4
P
2
O
0
0
50
100
150
200
250
t(min)
JACS 2005
What about cleavase-cleavase?
b.
a.
+
o
U
D
a. Substrate as inhibitor
U
b. product as activator
o
d.
c.
U
o
D
o
D
c. Substrate as activator
+
U
D
d. product as inhibitor
Cf. Uri Alon, Nat. Rev. Genetics 2007, 450 “Network Motifs: Theory and Experimental Approaches”
Connection type I: Substrate as inhibitor
a.
2500000
o
- inhibitor
F
2000000
U
D
+inhibitor
1500000
+ Enzyme
1000000
500000
o
+inhibitor
- Enzyme
0
0
U
1
2
Time (h)
3
4
5
D
Ben-Tov, Tamburi
6
Connection type II: Product as activator
b.
+
MB
U
o
D
30
+i,p
FU
+U
20
+MB
10
cont
0
0
+
U
80
160
240
t(min)
320
50nM d-8-17, 500nM d-sub, 500nM stemloop, 50nM up-8-17, 500nM input
o
D
Renjun Pei
Connection type III: Substrate as activator
c.
U
o
D
36
+act
FU
28
20
+U
12
cont
4
0
100
200
t(min)
300
400
100nM E6, 500nM d-sub, 500nM activator, 50nM 8-17
U
o
D
Renjun Pei, Aihua Shen
Connection type IV: Product as inhibitor
o
d.
15
+
D
U
FU
P
12
+MB
9
6
+U
o
3
0
+
U
D
80
160
240 t(mins)
100nM E6, 500nM d-sub, 250nM stem-loop, 50nM 8-17
Renjun Pei, Aihua Shen
AND cascade:
FU
9
p
7
2 Es
S1
U1
o
S2
U2
D
5
E-1
E-2
2 inhs
3
0
40
80
120
t(mins)
160
100nM E6, 500nM d-sub, 350nM inh-1,
350nM inh-2, 50nM 8-17-1, 50nM 8-17-2
Now we can do signal threshold:
i1
30
FU
25
U i1
o
o
D
20
15
10
5
one eq.
i1< D i1 >D+U
i1 <D+U
0
D-loop > U-loop
100nM D, 500nM d-sub, 20nM U, 200nM inh
at time 180 minutes.
0
40
80
120
160
200
concentration of i1 (nM)
Circuits by Winfree’s group:
Inputs
Input Translation
In
Computational
subcircuit
Signal restoration