Previous Article |
Table of Contents
| Next Article
Departments of * Ecology and Evolutionary Biology and
Communicated by Andrew Chi-Chih Yao, Princeton University,
Princeton, NJ, December 3, 1999 (received for review April 25, 1999)
We have expanded the field of "DNA computers" to RNA and
present a general approach for the solution of satisfiability problems. As an example, we consider a variant of the "Knight problem," which asks generally what configurations of knights can one place on an
n × n chess board such that no knight is
attacking any other knight on the board. Using specific ribonuclease
digestion to manipulate strands of a 10-bit binary RNA library, we
developed a molecular algorithm and applied it to a 3 × 3 chessboard as a 9-bit instance of this problem. Here, the nine spaces
on the board correspond to nine "bits" or placeholders in a
combinatorial RNA library. We recovered a set of "winning"
molecules that describe solutions to this problem.
DNA computing | satisfiability | RNA evolution | in
vitro selection | SELEX
Adleman (1) introduced
DNA-based computing as an approach to solving mathematical problems,
which uses DNA as a data carrier and techniques of molecular biology to
operate on DNA. Since then, there have been relatively few experimental
demonstrations of DNA-based computations (2, 3), although the
theoretical foundation is strong (4, 5). Here we introduce a method for
the construction of binary nucleic acid libraries, and we introduce RNA
as a molecule for computation to present a general approach for the
solution of the famous satisfiability (SAT) problems of propositional logic.
Using a combination of a binary RNA library and ribonuclease (RNase) H
digestion, we developed a destructive algorithm (6) that would
hydrolyze RNA strands that did not fit the constraints of a chosen
problem, instead of an algorithm that required efficient hybridization
extraction (1, 2). The use of restriction endonucleases (3) would have
also permitted a logical binary-style operation, as each restriction
enzyme cleaves only in the presence of its recognition site, and
cleaves the double-stranded DNA sufficiently to completion. However, by
using RNase H in the context of different sets of oligonucleotides, one
can go beyond the set of available restriction enzymes. Here, RNase H
acts as a "universal restriction enzyme" because it allows
selective marking of virtually any RNA strands for digestion in
parallel, and use of a thermostable RNase H (7) ensures fidelity of
hybridization between DNA and RNA strands, minimizing incorrect marking
of noncognate strands.
Chemical Synthesis of DNA "Half Libraries."
The DNA library was prepared as two halves by using mix and split
phosphoramidite chemistry with the sequence codes shown in Table
1. In brief, bit n set to 0 and spacer n were synthesized on one column, and bit
n set to 1 and spacer n were synthesized on the
other column. The columns were decrimped and the two resins poured
together and mixed, and then half of this mixture (containing approximately equal proportions of 0's and 1's at bit position n) was returned to each column for synthesis of the next
variable position, and the entire process was repeated (Fig.
1). Each of the four combinatorial
synthesis products was purified by polyacrylamide gel electrophoresis
on a 6% denaturing gel (Sequagel, National Diagnostics) and was
recovered by a "crush and soak" procedure (500 mM ammonium
acetate/1 mM EDTA/0.1% SDS) and ethanol precipitation (8). Annealing of the four half-sized strands in a 50-µl PCR reaction
containing 1 µM of each of four halves (9) and primer overlap
extension during five thermocycles (94°C for 30 sec, 45°C for 30 sec, and 72°C for 30 sec per cycle) generated the DNA library of full
sized strands with a total of 1,024 (210) unique
strands. (Note that the 3 × 3 instance of this problem considers
nine bits, or a total of 512 different chessboards. Bit 10 was unused
in the actual selections.) The degeneracy of the DNA pool was verified
by direct sequencing (10) using 5' end-radiolabeled primers TXR
(Prefix; [CAT]4CTCGAGAATT) and 32.41 (Suffix
complement; [CTA]4CGGGATCCTAATGACCAAGG) in
cycle sequencing reactions (SequiTherm Excel, Epicentre Tech).
Computer Sciences / Biochemistry
Molecular computation: RNA solutions to chess problems
, and
Computer Science, Princeton University, Princeton, NJ
08544
![]()
Abstract
Top
Abstract
Introduction
Materials and Methods
Results and Discussion
References
![]()
Introduction
Top
Abstract
Introduction
Materials and Methods
Results and Discussion
References
![]()
Materials and Methods
Top
Abstract
Introduction
Materials and Methods
Results and Discussion
References
Table 1.
Nucleotide sequences for each bit and spacer of the
combinatorial
library

View larger version (22K):
[in a new window]
Fig. 1.
Modular construction of the combinatorial DNA library from two
half-libraries. Linear mixing and splitting steps yield exponential
increases in pool complexity. Each half is synthesized on two columns
beginning with bit f or its reverse complement.
Synthesis of one half continues through bit a and the
prefix; the other half contains the reverse complement of bits
f through j and the suffix. Because the
halves are complementary at position f, primer extension
of the two halves creates the full-length 10-bit library. Black and
white boxes represent 1 and 0, respectively; shaded boxes represent
prefix, suffix, and spacer sequences.
DNA Bit Oligonucleotides. The set of DNA bit oligonucleotides used both to operate on the RNA library and as the downstream primers in readout PCR were from Operon Technologies (Alameda, CA) and are shown in Table 2.
|
Implementing the RNA Algorithm. RNase H digestions destroyed the RNA strand of RNA·DNA hybrids marked by hybridization of the pool RNA to the complementary bit oligonucleotides shown in Table 2. One hundred-microliter RNase H reactions contained 20 µg of gel-purified RNA (250 pmol), 1 nmol of each bit oligonucleotide, 5 units of Hybridase Thermostable RNase H (Epicentre Tech), 50 mM Tris·HCl (pH 7.5), 100 mM NaCl, and 10 mM MgCl2. After preincubation at 72°C for 3 min to denature strands, enzyme and MgCl2 were added at 45°C. The reaction was held at 45°C for 60 min and then was stopped by addition of 10 mM EDTA. Spin column chromatography (CLONTECH Chroma Spin-200, DEPC-H2O) was used to remove DNA bit oligonucleotides and short RNA digestion products. The eluted RNA was ethanol-precipitated, and remaining full-length (undigested) RNA was purified on a 5% denaturing polyacrylamide gel. Recovered RNA was reverse transcribed in 80 µl with 1.25 µM suffix complement (Superscript II, BRL). One-tenth of this reaction was amplified by PCR (200 µl, 1 µM primers T7TXR and 32.41, 2-5 cycles of 94°C for 30 sec, 60°C for 30 sec, and 72°C for 30 sec). After ethanol precipitation, the two halves of each pool were combined, and half of the DNA was transcribed in vitro for the next step in the algorithm.
Multiplex Colony PCR Readout.
PCR products were directly cloned by using the TOPO-TA cloning kit
(Invitrogen). Cells were grown on LB-agar plates containing 50 µg/ml ampicillin (8). Positive (white) colonies were randomly picked, were transferred to 50 µl of LB media containing 50 µg/ml ampicillin, and were grown for 4-6 hours at 37°C.
Colony PCR (11) of 2 µl of media (95°C for 5 min, followed by 25 cycles of 95°C for 30 sec, 60°C for 30 sec, and 72°C for 30 sec
with 0.2 µM primers TXR and 32.41) allowed rapid screening and
recovery of individual DNA library strands. To readout the bit settings
of cloned strands, 1 µl of a 1:100 dilution of the colony PCR product
was first amplified by linear PCR (9) (10 µl, 0.2 µM primer T7TXR;
10 cycles as above) in the presence of prefix only to generate an
excess of single-stranded DNA; then equimolar mixtures of 5'
end-radiolabeled "0"- or "1"-complementary DNA
oligonucleotides (
1 nM each) were added to the same tube, and the
reaction was continued for an additional five cycles. Reaction products
were separated on a 6% denaturing polyacrylamide gel (Long Ranger gel
solution, FMC Bioproducts). The dried gel was analyzed by
autoradiography on a PhosphorImager (Molecular Dynamics).
Error Analysis. To determine potential sources of error, we measured the efficiency and recovery of each operation.
Digestion of the RNA library by thermostable RNase H. 5' end radiolabeled RNA library (5 pmol) was subjected to RNase H digestion in the presence of combinations of DNA bit oligonucleotides (a0, f1, h1; b0, g1, i1; c0, d1, h1; d0, c1, i1; f0, a1, g1; g0, b1, f1; h0, a1, c1; i0, b1, d1; 75 pmol each; Table 2) under conditions as described above in 15 µl and 0.5 units RNase H. The digestion products were quantified on a 10% denaturing polyacrylamide gel by using a PhosphorImager. The amount of digestion products were in the expected range [12.5% undigested pool RNA, 12.5% first (longest), 25% second, and 50% third (shortest) digestion product]. Digestion of single RNA clones under the same conditions was almost complete (
98% in all cases but 96% for
i0, b1,
d1).
Spin-column chromatography and gel purification.
Column chromatography removed 5' end radiolabeled DNA bit
oligonucleotides (100 pmol) with >99% efficiency and recovery of 40-50% of 50 pmol 5' end radiolabeled RNA library. Recovery of 50 and
30 pmol of cloned RNA molecules (the expected range after a digestion
step) from a 6% denaturing polyacrylamide gel was 52% and 75%, respectively.
Reverse transcription and PCR.
Thirty and fifteen picomoles of three cloned RNA molecules were
reverse transcribed in the presence of 5' end radiolabeled primer
32.41. Efficiencies were 50% in one of the clones and 25% in two
other clones. One-tenth of these reactions was subjected to PCR (200 µl, 1 µM primers T7TXR and 5' end radiolabeled 32.41, 1-5 cycles
of 94°C for 30 sec, 60°C for 30 sec, and 72°C for 30 sec).
Samples were removed after each cycle and were resolved on a 12%
denaturing polyacrylamide gel. Amplification increased exponentially
after cycles 1-4, but plateaued after the fifth cycle of PCR.
| |
Results and Discussion |
|---|
|
|
|---|
The "Knight Problem." Chess problems create a class of SAT problems that are flexible in both scale and complexity. A "true" or "1" variable represents the presence of a knight at positions a-i whereas a "false" or "0" variable represents the absence of a knight at that position. This is a particular instance of a class of NP-complete SAT problems. For a 3 × 3 board
|
, "and";
, "or"):
((
h
f)
a)
((
g
i) 
b)
((
d
h)
c)
((
c
i)
d)
((
a
g)
f)
((
b
f)
g)
((
a
c)
h)
((
d
b)
i).
In this particular example, this simplifies to
((
h
f) 
a)
((
g
i) 
b)
((
d
h) 
c)
((
c
i) 
d)
((
a
g) 
f).
This reduces the number of operations that one has to perform.
Design and Synthesis of a 10-Bit RNA Library.
A 10-bit pool size was chosen because this represents a pool of
significant complexity, containing 1,024 different strands. Each strand
of RNA follows the template below (4):
|
|
Algorithm for Solving the Knight Problem Using the RNA Library.
We executed the algorithm for solving a variant of the knight problem
with our RNA combinatorial library as follows (Fig. 2): Initially we have a test-tube that
encodes all 1,024 possible 10-bit strings. Each string has the general
form x1...
xn, where a variable
xi is either 1 or 0, representing a bit
set to on or off. (In our experiment,
x1 = a,
x2 = b,... , x9 = i.) Then we
systematically perform the first operation to destroy strings that fail
to satisfy the first clause ((
h
f)
a) as follows:
(i) One executes an OR clause by dividing the library into
two "equal" collections. In one test-tube, we select those
strands that contain a 1 at position a by annealing DNA bit
oligonucleotide a0 to the library, hence
digesting those strands with position a set to 0 (thereby setting bit a to 1). Simultaneously, we destroy any 1's at
those bit positions that must be set to 0 to fulfill the clause (bits f and h in this case). In the other test-tube, we
anneal DNA bit oligonucleotide a1 to
perform the mirror operation setting bit position a to 0 (
a). (ii) Undigested molecules are recovered and reverse transcribed. After not more than five PCR cycles, the
contents of both tubes are mixed and amplified to high copy number
during T7 RNA polymerization. The library is split again to
execute the next OR clause, and this process is repeated until all
clauses have been processed. The combinations of bit oligonucleotides in each step were as follows: a
1:
a0, f1,
h1;
0: a1; b
1: b0, g1,
i1;
0: b1; c
1: c0, d1,
h1;
0: c1; d
1: d0, c1,
i1;
0: d1; f
1: f0, a1,
g1;
0: f1.
|
"Bit Shuffling." Recombination events are likely to occur during PCR amplification of heterogeneous target sequences (13), especially because the strands in our 10-bit library share several stretches of sequence identity constrained by the bit structure of the library. To measure this effect, the PCR products derived from two clones (wt-I 011 111 001 and wt-II 010 110 010, a, ... ,i) were combined and amplified for 25 cycles of PCR (0.2 µM primers TXR and 32.41; conditions as above). The resulting PCR products were cloned, and 20 clones were randomly chosen and analyzed by multiplex colony PCR readout at positions c, f, and h. Eight of twenty resulting clones (40%) were the product of bit shuffling. This indicates that bit shuffling poses a serious threat to successful execution of the algorithm; however, when only 15 instead of 25 PCR cycles were used, no bit shuffling was detected in 20 randomly chosen clones. This suggests that bit shuffling in our system is mostly due to a high proportion of incompletely extended strands annealing to heterologous target sequences, and it suggests that we can sufficiently reduce this problem by limiting the number of PCR cycles.
Consequently, no more than five cycles of PCR were performed between any two digestion steps and before cloning. Instead, we exploited T7 RNA polymerase as an amplifier, because this enzyme is more processive than Taq DNA polymerase.Methods of "Readout." Readout of a randomly sampled set of clones was accomplished by colony PCR (10) followed by multiplex linear PCR. This creates a "bar code" for each strand (Fig. 3). If one wanted to solve a stricter version of the knight problem, one could select the board containing the maximal number of knights by choosing sequences of unequal length for 1's and 0's and purifying either the longest or shortest strands (3), but the use of bit sequences of unequal length would preclude the quick and streamlined readout in Fig. 3 because it relies on equal length for 1's and 0's (Table 1) to generate a bar code pattern. Furthermore, unlike that of Ouyang et al. (3), our approach requires neither the isolation of plasmid DNA nor actual sequencing of any clones for readout.
|
RNA Solutions. After subjecting the RNA library to the algorithm outlined above, 43 clones were randomly chosen and interpreted by readout PCR. Forty-two of these represented solutions to our version of the Knight problem (Fig. 4). Ten solutions occurred more than once, even though they were selected at random. However, the overall distribution of these 42 clones was not significantly different from a random sampling of all 94 possible solutions (Table 3), with a very modest preference for higher numbers of knights. We did not attempt to recover the other 64 solutions, as they are all variants of the classes of solutions shown in Fig. 4, and it would require a much larger sampling to ensure representation of each unique solution at least once. One clone (represented as 010 111 011) contained two illegal interactions, resulting from incorrect placement of one knight. Hence, of 127 knights on 43 boards, only one knight had an unacceptable placement. This was effectively a 97.7% success rate in finding correct solution strands, which is indeed satisfactory for choosing a clone that is likely to encode a solution.
|
|
1015 is
approximately the number of RNA molecules that in vitro
selection protocols can currently search, this projects an upper bound
for the size of DNA or RNA computing experiments that could use
exhaustive search algorithms. Fortunately, this is on the same order as
many interesting problems in computer science, such as the Data
Encryption Standard (DES) (20).
Because in vitro selection experiments (18) that search for
binding or function within an enormous sequence space have captured molecules as unique as one in a quadrillion, and because these molecules may even encode the solution to a mathematical problem, like
knights on a chessboard, nucleic acid-based computing may be viewed as
a natural extension of simulated evolution experiments to searches of a
defined mathematical space.
| |
Acknowledgements |
|---|
We thank Steve Lawrie, Vernadette Simon, and Saw Kyin for synthesis of the oligonucleotide portions of the combinatorial pool. We also thank Leonard Adleman, Paul Rothemund, and Erik Winfree for helpful discussions and two anonymous reviewers for comments. This research was supported in part by the National Science Foundation/Defense Advanced Research Planning Agency, the Air Force Office of Scientific Research, and a Deutsche Forschungsgemeinschaft fellowship to D.F.
| |
Abbreviation |
|---|
SAT, satisfiability.
| |
Footnotes |
|---|
To whom reprint requests should be addressed.
E-mail: LFL{at}princeton.edu.
See commentary on page 1328.
| |
References |
|---|
|
|
|---|
| 1. |
Adleman, L. M.
(1994)
Science
266,
1021-1023 |
| 2. | Guarnieri, F., Fliss, M. & Bancroft, C. (1996) Science 273, 220-223[Abstract]. |
| 3. |
Ouyang, Q., Kaplan, P. D., Shumao, L. & Libchaber, A.
(1997)
Science.
278,
446-449 |
| 4. |
Lipton, R. J.
(1995)
Science.
268,
542-545 |
| 5. | Landweber, L. F. & Baum, E. B., eds. (1999) DNA Based Computers II (Am. Math. Soc., Providence, RI). |
| 6. | Amos, M., Gibbons, A. & Hodgson, D. (1999) in DNA Based Computers II, eds. Landweber, L. F. & Baum, E. B. (Am. Math. Soc., Providence, RI), pp. 151-161. |
| 7. | Porter, D. & Curthoy, N. P. (1997) Anal. Biochem. 247, 279-286[CrossRef][ISI][Medline] . |
| 8. | Sambrook, J., Maniatis, T. & Fritsch, E. F. (1989) Molecular Cloning: A Laboratory Manual (Cold Spring Harbor Lab. Press, Plainview, NY). |
| 9. | Landweber, L. F. & Kreitman, M. (1993) Methods Enzymol. 218, 17-26[Medline] . |
| 10. | Rao, V. B. (1994) PCR Methods Appl. 4, S15-S23[Medline] . |
| 11. | Trower, M. K. (1996) Methods Mol. Biol. 58, 329-333[Medline] . |
| 12. |
Zuker, M.
(1989)
Science
244,
48-52 |
| 13. |
Meyerhans, A., Vartanian, J. & Wain-Hobson, S
(1990)
Nucleic Acids Res.
18,
1687-1691 |
| 14. |
Frutos, A. G., Liu, Q., Thiel, A. J., Sanner, A. M. V., Condon, A. E., Smith, L. M. & Corn, R. M.
(1997)
Nucleic Acids Res.
25,
4748-4757 |
| 15. | Smith, L. M., Corn, R. M., Condon, A. E., Lagally, M. G., Frutos, A. G., Liu, Q. & Thiel, A. J. (1998) J. Comp. Biol. 5, 255-267. |
| 16. |
James, K. D., Boles, A. R., Henckel, D. & Ellington, A. D.
(1998)
Nucleic Acids Res.
26,
5203-5211 |
| 17. |
Stemmer, W. P.
(1995)
Science
270,
1510 |
| 18. | Landweber, L. F. (1999) in DNA Based Computers II, eds. Landweber, L. F. & Baum, E. B. (Am. Math. Soc., Providence, RI), pp. 181-189. |
| 19. | Boneh, D., Dunworth, C., Lipton, R. J. & Sgall, J. (1999) in DNA Based Computers II, eds. Landweber, L. F. & Baum, E. B. (Am. Math. Soc., Providence, RI), pp. 163-170. |
| 20. | Boneh, D., Dunworth, C. & Lipton, R. J. (1999) in DNA Based Computers, eds. Lipton, R. J. & Baum, E. B. (Am. Math. Soc., Providence, RI), pp. 37-65. |
Related Commentary in PNAS:
This article has been cited by other articles in HighWire Press-hosted journals:
![]() |
S. Beyer and F. C. Simmel A modular DNA signal translator for the controlled release of a protein by an aptamer Nucleic Acids Res., March 17, 2006; 34(5): 1581 - 1587. [Abstract] [Full Text] [PDF] |
||||
![]() |
J. J. Tabor, M. Levy, and A. D. Ellington Deoxyribozymes that recode sequence information. Nucleic Acids Res., January 1, 2006; 34(8): 2166 - 2172. [Abstract] [Full Text] [PDF] |
||||
![]() |
D. Tulpan, M. Andronescu, S. B. Chang, M. R. Shortreed, A. Condon, H. H. Hoos, and L. M. Smith Thermodynamically based DNA strand design Nucleic Acids Res., September 6, 2005; 33(15): 4951 - 4964. [Abstract] [Full Text] [PDF] |
||||
![]() |
M. R. Shortreed, S. B. Chang, D. Hong, M. Phillips, B. Campion, D. C. Tulpan, M. Andronescu, A. Condon, H. H. Hoos, and L. M. Smith A thermodynamic approach to designing structure-free combinatorial DNA word sets Nucleic Acids Res., September 2, 2005; 33(15): 4965 - 4977. [Abstract] [Full Text] [PDF] |
||||
![]() |
F. Tanaka, A. Kameda, M. Yamamoto, and A. Ohuchi Design of nucleic acid sequences for DNA computing based on a thermodynamic approach Nucleic Acids Res., February 8, 2005; 33(3): 903 - 911. [Abstract] [Full Text] [PDF] |
||||
![]() |
K. A. Schmidt, C. V. Henkel, G. Rozenberg, and H. P. Spaink DNA computing using single-molecule hybridization detection Nucleic Acids Res., September 23, 2004; 32(17): 4962 - 4968. [Abstract] [Full Text] [PDF] |
||||
![]() |
R. Adar, Y. Benenson, G. Linshiz, A. Rosner, N. Tishby, and E. Shapiro Stochastic computing with biomolecular automata PNAS, July 6, 2004; 101(27): 9960 - 9965. [Abstract] [Full Text] [PDF] |
||||
![]() |
X. Su and L. M. Smith Demonstration of a universal surface DNA computer Nucleic Acids Res., June 4, 2004; 32(10): 3115 - 3123. [Abstract] [Full Text] [PDF] |
||||
![]() |
M. Andronescu, R. Aguirre-Hernandez, A. Condon, and H. H. Hoos RNAsoft: a suite of RNA secondary structure prediction and design software tools Nucleic Acids Res., July 1, 2003; 31(13): 3416 - 3422. [Abstract] [Full Text] [PDF] |
||||
![]() |
Y. Benenson, R. Adar, T. Paz-Elizur, Z. Livneh, and E. Shapiro DNA molecule provides a computing machine with both data and fuel PNAS, March 4, 2003; 100(5): 2191 - 2196. [Abstract] [Full Text] [PDF] |
||||
![]() |
K. Sakamoto, H. Gouzu, K. Komiya, D. Kiga, S. Yokoyama, T. Yokomori, and M. Hagiya Molecular Computation by DNA Hairpin Formation Science, May 19, 2000; 288(5469): 1223 - 1226. [Abstract] [Full Text] |
||||
![]() |
J. Chen and D. H. Wood Computation with biomolecules PNAS, February 15, 2000; 97(4): 1328 - 1330. [Full Text] [PDF] |
||||
![]() |
R. S. Braich, N. Chelyapov, C. Johnson, P. W. K. Rothemund, and L. Adleman Solution of a 20-Variable 3-SAT Problem on a DNA Computer Science, April 19, 2002; 296(5567): 499 - 502. [Abstract] [Full Text] [PDF] |
||||
| |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||