dna computing and robotics based on deoxyribozymes
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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:
AT
A T
G
C
C
G
A
T
A
T
C
G
T
A
T
A
C
GA TCGTTGAAG
Complementary Single strandedDNA (or RNA)
CT
CTTC
TAGTGA
C
A
CG
G
GC
A GC
TC
GAA
T
Deoxyribozyme
TA
CACT
F
TrAG
AG
AGAG
R
+
Substrate recognition region
Catalytic core
S
Substrate recognition region
TA
CACTF
TrA
OF
CC
A
CG
G
GC
A GC
TC
GAA
T
TAT
ATGCTAGCAT
GA TA TG CA TG C
rAG
F
R
Cleavage
Joyce 1995, 1997
GAAGAG
G
R
Introduction to deoxyribozymes II:
CT
CTTC
TAGTGA
C
A
CG
G
GC
A GC
TC
GAA
T
Deoxyribozyme
TA
CACT
F
TrAG
AG
AGAG
R
+
Substrate recognition region
Catalytic core
S
Substrate recognition region
TA
CACTF
TrA
OF
CC
A
CG
G
GC
A GC
TC
GAA
T
TAT
ATGCTAGCAT
GA TA TG CA TG C
rAG
F
R
Cleavage
Joyce 1995, 1997
+
E
S
Substrate recognition region
E*SSubstrate recognition region
kon
Catalytic core
P1
P2
kcat
+P1
P2
koff's
…and we can combine them with stem loops:
P1
P2
S
P1
P2
kcat
P1
P2
koff's
E
E
ES
P1
P2
…into a two-state switch:
0 1
Detector gateorsensororYES gateor…
Complete set of switches:
i1 i2 o0
1
1111
000 0
00
AND Gate:NOT Gate:
i1 o0
01
1
ANDANDNOT:
i1 i20
1
1100
000 0
00
i1 o0
1 11 1
1 1111
00
0
000
000
1
i3
Before we give examples of gates, a reminder:
CT
CTTC
TAGTGA
C
A
CG
G
GC
A GC
TC
GAA
T
Deoxyribozyme
TA
CACT
F
TrAG
AG
AGAG
R
+
Substrate recognition region
Catalytic core
S
Substrate recognition region
TA
CACTF
TrA
OF
CC
A
CG
G
GC
A GC
TC
GAA
T
TAT
ATGCTAGCAT
GA TA TG CA TG C
rAG
F
R
Cleavage GAAGAG
G
R
1 is an increase in fluorescence, 0 no such increase!
A bit more about FRET:
d1 < d2
GC
TA
C G
A T
C G
CG
CG
GC
TA
G C
AT
A
Fluorescein
TAMRA
480 nm520 nm
580 nm
d1C
C G
G
AT
CG
TA
GC
TA
C G
A T
C G
CG
CG
GC
TA
G C
AT
A
Fluorescein
TAMRA
480 nm520 nm
580 nm
d2
, FRET is stronger
Cleavage
ACAA
TGGA
CACA
TTGA
TA C A C T FTrA
CTCTTC
TAGTGA
C
A
CG
G
GC
A GC
TC
GAA
T
AGAAG
G G
GA
CC
A
CG
G
GC
A GC
TC
GAA
T
AGAAG
CA TT AT AG CG CT
AGC
TA
TA
AT
AT
CG
TA
TA
TA
CACT
F
TrAG
AG
AGAG
R A*S*IA
TAT
ATGCTAGCAT
GA TA TG CA TG C
rAG
F
R
+
Cleavage
Inactive Form
Active Form
A GG
AGG
IA
A
OF
S
IA
0 1
I1
Stojanovic et al., ChemBioChem 2001Stojanovic et al., J. Am. Chem. Soc. 2002
0
50000
100000
150000
200000
250000
0 100 200 300 400t (min)
FU
Catalytic Molecular Beacons as Sensor Gates
Joyce 1995, Breaker 1999, Tyagi, Kramer 1996
01
I2
C
ATGT
C CC
A
G
CGA
G ATC C
GGC
C
ATA
TTC
GCTAGCA 3'T
F
TC
TrAG
AG
AGAG
R3'
A
CAATG
CGA
CT
GT
TTGA
AT
C
ATGT
CCCA
G
CGA
GATC C
G
G
C
C
ATA
TTC
GCTAGCA 3'T
F
TC
TrAG
AG
AGAG
R3'
C
GA
T
GTAACCTGTCTTGAA
CATTGGACAGAACTT
B*IB
TA C A C T FTrA
B
IB
OF
NOT IB
IB
Inactive Form
Active Form
Cleavage
NOT Gates – Inverters:
Stojanovic et al., J. Am. Chem. Soc. 2002
0
50000
100000
150000
200000
0 100 200 300t(min)
FU
0 10
I2
I1I1
I2
0
TA
CACT
F
ACAA
TGGA
CACA
TTGA
TrAG
AG
AGAG
R
TA
CACTF
TrA
ACAAT
G A
CT G T
TTG
A
CTCTTC
TAGTG
C
A
CG
G
GC
A GC
TC
GAA
T
AGAAG
CACT
+IA AND IB
A B
TA
TT
G
IA
IB
OFS
Dual Input Molecular Computation Elements: AND Gate
-20000
0
20000
40000
60000
80000
100000
120000
140000
160000
180000
0 50 100 150 200 250
FU
t(min)
C
ATGT
C CC
A
G
CGA
G AT
C CG
GC
C
A
TTC
GTGA
GAA
ACAA
TGA
CACA
TTGA
A TG C
T
G
A
CAATG
CGA
CTG
TTTG
T
AT
TCTTT
G A
CA C T
TTG
A
TA
CACT
IB
IC
IA
T
A
TA
CACTF
TrA
IA AND IB AND NOT IC
OF
TA
CACT
F
TrAG
AG
AGAG
R3'
Triple Input Elements: ANDANDNOT (INHIBIT)
0 00 0
I2I2I1I1
1
I1
I3 I3 I3
0
I2I1
I3
0
I2
0
I3
Triple Input Elements: ANDAND
Harvey Lederman
TA
CA
CT
F
TrA
GG
AA
GA
GR
C
ATG
T
CCCA
CC
GA
G AT
GA
T
C
GC
A
TT
C
GT
GA
GA
A
T
GCAGA
A
CAGA
AT
T TA
TGC
T
G
G
TT
AGA
C
GAA
AGAT
GCC
T
A
C
TA
TAC
A
C A GA
AA
AC
TA
CA
CT
T
A
C
C
C
A
AT
CT
TT
TC
TAC
GG
G AT G
T GA
GC
AT T
A CG A
T GC A
T TA T
A AT A
T GC A
T GC T
A AC C
G CG A
T
TAG
CGCA
TTA
GCT
TC
C
ATGTC
CCA
CCGA
G A T GA
T
CG
C
A
TT
C
GTGA
GA
A
T
GC
AG
A
A
CAG
A
ATT
T
A
T
G
C
TG
G
TT
AGACG
AA
AGAT
GCC
TA
C
TA
TAC
A
C A GA
AA
ACTA
CA C T
T
A
TC
TG
CGTC
T
ATAA
AT
GT
TTG
TCTA
TA
T
G
T
i1ANDi2ANDi3
i1, i2, i3
c3
c3 i3
i2
i1
i1
i2
c3
2
1
3
0 0 0 0 0 0 1
F
1
c3 c3
2
3
0
c3
2
1 1
3
2
3
0
10000
20000
30000
40000
0 50 100 150
t(min)
FU12
13
123
23
1
2
3
0
Before we give examples of gates, a reminder:
CT
CTTC
TAGTGA
C
A
CG
G
GC
A GC
TC
GAA
T
Deoxyribozyme
TA
CACT
F
TrAG
AG
AGAG
R
+
Substrate recognition region
Catalytic core
S
Substrate recognition region
TA
CACTF
TrA
OF
CC
A
CG
G
GC
A GC
TC
GAA
T
TAT
ATGCTAGCAT
GA TA TG CA TG C
rAG
F
R
Cleavage GAAGAG
G
R
1 is an increase in fluorescence, 0 no such increase!
First deoxyribozyme
P1
P2
kcat
F
Q
F
QE*S
P1
P2
kcat
T
Q
T
QSecond deoxyribozyme
Let’s add A (0 or 1) and X (0 or 1) and get O (0 or 1, or 2):
A + X = O
1 1
01 01
0 0
00 00
0 1 2
100100
i1 i2
GR GRGR
First deoxyribozyme
P1
P2
kcat
F
Q
F
QE*S
P1
P2
kcat
T
Q
T
QSecond deoxyribozyme
F
T
Ti1
i1
i1
i1
i1
i1
i1
i2i2
i2
i1
i2i2
i2
i2i2
i1
i2
i1 i2
i2
i1
00
SC
0 1
10
01
C S
F T
C S
Stojanovic & Stefanovic, J. Am. Chem. Soc. 2003
0+1
-2000
0
2000
4000
6000
8000
10000
0 100 200 300
1+0
-5000
0
5000
10000
15000
20000
0 100 200 300
1+1
-5000
0
5000
10000
15000
20000
25000
30000
35000
0 100 200 300
Implement addition with gates:
10 012 1
0+0
-5000
-3000
-1000
1000
3000
5000
7000
9000
0 100 200 300
Now, a twist:
CT
CTTC
TAGTGA
C
A
CG
G
GC
A GC
TC
GAA
T
Deoxyribozyme
TA
CACT
F
TrAG
AG
AGAG
R
+
Substrate recognition region
Catalytic core
S
Substrate recognition region
TA
CACTF
TrA
OF
CC
A
CG
G
GC
A GC
TC
GAA
T
TAT
ATGCTAGCAT
GA TA TG CA TG C
rAG
F
R
Cleavage GAAGAG
G
R
1 is an increase in fluorescence, 0 no such increase!
1
d6
d4
d9
d5
d1
d2
d3
d8
d7
A B C D E F G
1
2
3
4
5
6
7
8
9
A
F
G
D
B
E C
A
F
G
D
B
E C
A
F
G
D
B
E C
Segments required
J. Macdonald, Columbia University
Here is 7-segment display:
Test by constructing simple 2+2-bit adder
1 0 1 02+2: + =
A1 A0 X1 X0+
0 1 0 11+1: + =
Binary inputs
0 1 1 01+2: + =
1 0 0 12+1: + =
Non generalDisplay output
Expected display
Adder result “hard-wired” into
decoder
Designate 4 oligonucleotides as binary inputs
J. Macdonald, Columbia University
More arithmetical operations:
• Determine logic gates required, and layout in wells (via Microsoft Excel) Non-general adder
output gates
Segment AYes A0Yes X0
Segment BYes A0Yes A1
Segment CYes X1Yes A1
Segment DYes A0Yes X0
Segment EA0 AND X0
Segment FA1 AND X1
Segment GYes A1Yes A0
Non-general adder output gates
Segment AYes A0Yes X0
Segment BYes A0Yes A1
Segment CYes X1Yes A1
Segment DYes A0Yes X0
Segment EA0 AND X0
Segment FA1 AND X1
Segment GYes A1Yes A0
Segment AYes A0Yes X0
Segment BYes A0Yes A1
Segment CYes X1Yes A1
Segment DYes A0Yes X0
Segment EA0 AND X0
Segment FA1 AND X1
Segment GYes A1Yes A0
Very simple logic gate arrangement required: • 4 YES gates • 2 AND gates
Fully constructible from reagents in freezer
Tested with all input combinations….
1 0 1 02+2: + =
A1 A0 X1 X0+
0 1 0 11+1: + =
Binary inputs
0 1 1 01+2: + =
1 0 0 12+1: + =
Non generalDisplay output
1 0 1 02+2: + =
A1 A0 X1 X0+
0 1 0 11+1: + =
Binary inputs
0 1 1 01+2: + =
1 0 0 12+1: + =
Non generalDisplay output
J. Macdonald, Columbia University
Adding 2+2 with visual display:
Adding 2+2 with visual display:
Perfect digital behaviorConstructed &
tested in a single day
(A1A0 + X1X0 display)
01+01= 01+10= 10+01= 10+10= No inputs
(1+1=2) (1+2=3) (2+1=3) (2+2=4) Background
Binary inputs:
7-segmentDisplay
Arithmetic
B&W imagerwithin ~1hr
Color photograph~5hrs
Fluorescence reader~20-30mins
J. Macdonald, Columbia University; DNA 13, 2007
2x2 multiplier with visual display:
Segment AA0 AND X1A1 AND X0
Segment BA0 and X0
A0 and X1 not A1A1 and X0 not X1A1 not A0 not X0
Segment CA1 and A0X1 and X0A1 and X1A0 and X0Segment D
A1 and A0X1 and X0A0 and X1A1 and X0
Segment EA1 and X0 not A0A0 and X1 not X0
Segment FA1 and X1
Segment GYes A1Yes X1
Segment AA0 AND X1A1 AND X0
Segment BA0 and X0
A0 and X1 not A1A1 and X0 not X1A1 not A0 not X0
Segment CA1 and A0X1 and X0A1 and X1A0 and X0Segment D
A1 and A0X1 and X0A0 and X1A1 and X0
Segment EA1 and X0 not A0A0 and X1 not X0
Segment FA1 and X1
Segment GYes A1Yes X1
Gate arrangement
19 gates required
J. Macdonald, Columbia University
(A1A0 × X1X0 display)
01 × 01 =
(1×1=1)Arithmetic
Binary inputs:
7-segmentDisplay
01 × 10 = 01 × 11 = 10 × 01 = 10 × 10 =
10 × 11 = 11 × 01 = 11 × 10 = 11 × 11 = (00 × 00)
(1×2=2) (1×3=3) (2×1=2) (2×2=4)
(2×3=6)Arithmetic (3×1=3) (3×2=6) (3×3=9) no inputcontrol
Binary inputs:
7-segmentDisplay
Color photography
J. Macdonald, Columbia University
2x2 multiplier with visual display:
(A1A0 × X1X0 display)
i11 i12 i13 i14
i11 i11
i11
i12 i12
i12
i13 i13
i13
i14 i14
i14
i22 i23 i21 i23
i24 i24
i21 i22
i24
i21 i22
i23
i11 i12 i13 i14
i11 i11
i11
i12 i12
i12
i13 i13
i13
i14 i14
i14
i22 i23 i21 i23
i24 i24
i21 i22
i24
i21 i22
i23
i11 i12 i13 i14
i11 i11
i11
i12 i12
i12
i13 i13
i13
i14 i14
i14
i22 i23 i21 i23
i24 i24
i21 i22
i24
i21 i22
i23
i11 i12 i13 i14
i11 i11
i11
i12 i12
i12
i13 i13
i13
i14 i14
i14
i22 i23 i21 i23
i24 i24
i21 i22
i24
i21 i22
i23
Silicomimetic automata project (MAYA):
Macdonald et al. Nano Lett. 2006Stojanovic&Stefanovic. Nat.Biotech. 2003
MAYA: MAYA-II: MAYA-III:
Pei, Matamoros, et al. in testing
Human designed
Goal: Demonstrate power of molecular computing!
Computer designed Human designed
Goal: What does it take to coordinate large number of gates?
Goal: 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?
oi1U D
communication component(Upstream enzyme)
(downstream enzyme)
Intergate Communication : Ligase-Cleavase
Stanka Semova, Dmitry Kolpashchikov
AT
AT
GC
TA
GC
TA
TA
CG
T TT
CG G
C GA
AC
GTA
GC
AT
GC
CG T
A
AT
TA
GC G
C
PIMHO
GC
TT
TT
Ligase E47
GA
A A CT
C
A
GC
GA
C A C T
C T C T T C T A G TC
A
CG
GG
CAG C
T CGA AT
A G A A G AA
C A AT
G
A
CA
GA
T T GA
TA
C
TA C A C T FTrAG
AG
AGAGR
Cleavage
UnionS1
S2
P1
S3
YESP1
0
1
2
3
4
5
0 50 100 150 200 250
time (min)
Ligase-cleaves XOR circuit:
JACS 2005
F
2
o1
O1
1
12
0
2
4
6
8
10
0 50 100 150 200 250
t(min)
Rn
1
2
1,2
P
O
OIA
IB
XOR
IA IB O
1
1
1 1
1
1
0
0
0
0
00
What about cleavase-cleavase?
U D
oa.
U D
+o
b.
U
+D
od.
a. Substrate as inhibitor
c. Substrate as activator
b. product as activator
d. product as inhibitor
o
DU
c.
Cf. Uri Alon, Nat. Rev. Genetics 2007, 450 “Network Motifs: Theory and Experimental Approaches”
Ben-Tov, Tamburi
0
500000
1000000
1500000
2000000
2500000
0 1 2 3 4 5 6Time (h)
F
+ Enzyme
- Enzyme
- inhibitor
+inhibitor
+inhibitorU D
oa.
Connection type I: Substrate as inhibitor
U D
o
Connection type II: Product as activator
U D
+o
b.
50nM d-8-17, 500nM d-sub, 500nM stem-loop, 50nM up-8-17, 500nM input
0
10
20
30
0 80 160 240 320t(min)
FU
+MB
cont
+U
+i,p
MB
U D
+o
Renjun Pei
Connection type III: Substrate as activator
o
DU
c.
100nM E6, 500nM d-sub, 500nM activator, 50nM 8-17
4
12
20
28
36
0 100 200 300 400t(min)
FU +act
+U
cont
Renjun Pei, Aihua Shen
oD
U
Connection type IV: Product as inhibitor
U
+D
od.
100nM E6, 500nM d-sub, 250nM stem-loop, 50nM 8-17
3
6
9
12
15
0 80 160 240 t(mins)
FUP
+MB
+U
Renjun Pei, Aihua Shen
U
+D
o
AND cascade:
U2D
oU1
S1
S2
100nM E6, 500nM d-sub, 350nM inh-1, 350nM inh-2, 50nM 8-17-1, 50nM 8-17-2
3
5
7
9
0 40 80 120 160t(mins)
FUp
E-1
2 Es
2 inhsE-2
0
5
10
15
20
25
30
0 40 80 120 160 200concentration of i1 (nM)
FU
Now we can do signal threshold:
oi1U D
i1
< Di1 >D+Ui1<D+Ui1
o
D-loop U-loop>100nM D, 500nM d-sub, 20nM U, 200nM inhat time 180 minutes.
one eq.
In
Circuits by Winfree’s group:
Inputs Input Translation Computational subcircuit Signal restoration
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