aqueous computing - writing on molecules -
DESCRIPTION
AQUEOUS COMPUTING - Writing on Molecules -. T. Head, M. Yamamura, and S. Gal Binghamton University. 1. Introduction. The only way to compute with DNA? 1 design sequences for DNA molecules 2 order many custom DNA molecules 3 anneal and filter ( 4 if failure goto 1 ). ↓ - PowerPoint PPT PresentationTRANSCRIPT
AQUEOUS COMPUTING- Writing on Molecules -
T. Head, M. Yamamura, and S. GalBinghamton University
7/9/99 CEC'99 2
1. Introduction
The only way to compute with DNA?1 design sequences for DNA molecules
2 order many custom DNA molecules
3 anneal and filter
( 4 if failure goto 1 )
↓ Aqueous computing
– framework for using molecular memory– laboratory implementation
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Molecular Memory
MemoryLSI HD
Address wired grid head pos.
Content electronic magnetic
1. molded together
2. fixed on solid materials
3. serial processing
AQUEOUS
DNA
specific subsequence
markings on molecules
1. individual access
2. randomize location
3. parallel processing
easily separate
mix again
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2. Mathematical Basis
Common algorithmic problem (CAP)– a description of the pattern of the problem
Aqueous algorithm– a way to use molecular memory
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Common algorithmic problem CAP
given S: finite set
F 2⊂ S (the forbidden subsets)
find the largest cardinal number n for which there is a subset T of S for which: |T|=n, U F U T.∀ ∈ ⊂
– NP-complete problems having the CAP pattern» maximum independent set
» minimum vertex cover
» Hamiltonian cycles
» Boolean satisfiability, etc.
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Example
Maximum independent set problemgiven: G=(V, A) (the arcs are forbidden)
find max |T| s.t. T⊂V , x,y T, {x,y} A∀ ∈ ∈
Find max # of animals you can keep in one cage?
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Aqueous Algorithm
Initialize;For each {s1, s2, ..., sk} in F DoPour (k)
1: SetToZero( s1 )2: SetToZero( s2 )
...k: SetToZero( sk )
UniteEndFor;MaxCountOfOnes
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Pour(2)
SetToZero(b) SetToZero(c)001,101 010,100
SetToZero(a) SetToZero(b)011 101
Pour(2)
ExampleInitialize: 111
a
bc
MaxCountOfOnes: 2001,101,010,100
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3. Biomolecular Implementation
DNA modification enzymes– how to write on molecules
DNA plasmid– use of bacteria and blue/white selection
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Write on molecules
Restriction enzyme– cuts DNA at a specific subsequence (site)
5’-TATCGA-3’ 3’-ATAGCT-5’ ↓ Hind III
5’-T ATCGA-3’3’-ATAGC T-5’
Circular DNA + modification enzymes– Bit =1 (site exists), =0 (no site)
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Cut/fill/paste
5’-TATCGA-3’ Bit=1, circular3’-ATAGCT-5’
cut ↓ restriction enzyme
5’-T ATCGA-3’ linear 3’-ATAGC T-5’
fill ↓ DNA polymerase
5’-TATCG ATCGA-3’ 3’-ATAGC TAGCT-5’
paste ↓ DNA ligase
5’-TATCGATCGA-3’ 3’-ATAGCTAGCT-5’ Bit=0, circular
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Cloning with DNA plasmid DNA plasmid
– circular, double stranded
– set of unique sites» multiple cloning site (MCS)
transform to bacteria– useful genes
» antibiotics resistance (ex.ampr)
» coloring matters (b-galactosidase)
amp
r
-ga
lact
osid
ase
MCS
NotI XbaI SpeI BamHI XmaI PstI EcoRI EcoRV HindIII ...5’-GCGGCCGCTCTAGAACTAGTGGATCCCCCGGGCTGCAGGAATTCGATATCAAGCTTATCGAT-3’3’-CGCCGGCGACATCTTGATCACCTAGGGGGCCCGACGTCCTTAAGCTATAGTTCGAATAGCTA-5’
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Genetic code translation
Genetic code– translated into a series of amino acids by groups
of 3 base pairs (codon) Reading frame
– 3 different meanings ex) 5’-GCTCTAGAACTAGTGGATCCCCCGGGCTGCAGGAATTCGATA
TC A L E L V D P P G C R N S I . . . . . . . . . . . . . . . . . . . . . . . . . . . .
(under construction)
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Blue / white selection initial DNA plasmid
express -galactosidase gene → blue↓
1st cut/fill/paste+4bp reading frame shift → white⇒
↓
2nd cut/fill/paste+8bp reading frame still shift → white⇒
↓ 3rd cut/fill/paste
+12bp readinf frame restored → ⇒ blue» useful as a debugging tool
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Blue/white example
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Preliminary results XbaI BamHI HindIII
pBSK GCTCTAGAACTAGTGGATCCCCCGGGCTGCAGGAATTCGATATCAAGCTTATCGATACCGTCG A L E L V D P P G C R N S I S S L S I P S
[H] GCTCTAGAACTAGTGGATCCCCCGGGCTGCAGGAATTCGATATCAAGCTAGCTTATCGATACC A L E L V D P P G C R N S I S S stop
[HB] GCTCTAGAACTAGTGGATCGATCCCCCGGGCTGCAGGAATTCGATATCAAGCTAGCTTATCGA A L E L V D R S P G L Q E F D I K L A Y R
[HBX] GCTCTAGCTAGAACTAGTGGATCGATCCCCCGGGCTGCAGGAATTCGATATCAAGCTAGCTTA A L A R T S G S I P R A A G I R Y Q A S L
sample blue / white accuracy
[H] 4 / 40 87%
[HB] 3 / 80 96%
[HBX] 97 / 17 85%
SetToZeroHind III
-> BamH I -> Xba I
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Example
[HB] (+8, white)
a=0(SpeI)
b=0(XhoI)
b=0(XhoI)
c=0(XbaI)
mix; +12 & +16(solution = +12, white)
a
bc
0 +4 +8 +12
under construction
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4. Discussion
Advantages as DNA computing– start with one DNA plasmid
» no custom DNA for individual problem
– amplify in bacteria» blue/white selection as debugging tool
» preserving the distribution of DNA plasmids
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5. Conclusion
Molecular Memory– Aqueous Algorithm
» general framework to use molecular memory
– Cut/fill/paste» laboratory implementation
Further issues– scale up & speed up– new algorithm fits bacteria
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International Connection
BinghamtonUniversity
(USA)
LeidenUniversity
(Netherlands)
Tokyo Institute ofTechnology
(Japan)
Aqueous Computing
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Acknowledgement
Xia Chen & Shalini Aggarwal in S.Gal Laboratory at Binghamton University
NSF CCR-9509831 DARPA/NSF CCR-9725021 JSPS-RFTF 96100101 LCNC at Leiden University