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Developing a Bacterial XOR Gate and Hash Function Hunter iGEM 2012 - - PowerPoint PPT Presentation
Developing a Bacterial XOR Gate and Hash Function Hunter iGEM 2012 - - PowerPoint PPT Presentation
Developing a Bacterial XOR Gate and Hash Function Hunter iGEM 2012 Project Motivation & Structure Non-biology majors (including several CS) with an interest in quantitative biology... We wanted to work on biological computing. We
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Project Goals
➲ Develop bacterial XOR gate ➲ Integrate XOR gate into combinatorial cir-
cuit (hash function)
➲ Model and improve XOR gate designs
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What are logic gates?
➲ Computation with machines involves com-
binations of basic logical building blocks called logic gates. Here's a XOR gate:
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What are hash functions? What are hash functions?
A hash function encodes data as other data,
- pens the door to cryptographic hash func-
tions and biologically encoded data.
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Bacterial logic gates
➲ Bacterial colonies act as gates or gate
components.
➲ Combinatorial logic circuits require signaling
and bacterial colonies use quorum sensing to send signals, so they're a natural fit.
➲ Gram negative bacteria use both
universal and strain-specific signals (HSL signals).
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Signaling paradigms
➲ Signals are passed through environment
(agar plate) from colony to colony.
➲ Spatial considerations significant challenge. ➲ Simple signaling versus chained signaling
for a mixed system.
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Modeling to understand
➲ Using Python we simulated a bacterial XOR
hash function and developed kinetic reac- tion model using rule based modeling.
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Existing bacterial XOR designs are cumbersome
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Evaluating XOR designs
➲ Complex XOR gates with multiple simpler
gates
➲ Simpler designs included hybrid promoters
which toggle each other
➲ Even simpler is a design exploiting competi-
tive polymerase activity with
- pposing promoters.
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We identified an elegant XOR de- sign...
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...with a flaw.
Bacterial Hash Function Using DNA-Based XOR Logic Reveals Unexpected Behavior of the LuxR Promoter, A. Malcolm Campbell, et. al.
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Validate the data
➲ We transformed the Davidson XOR design
and characterized the fluorescent protein expression.
➲ Our results mirrored the published results
supporting the theory that backwards tran- scriptional activity was occuring.
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A plan to fix the promoter
➲ Consensus search for possible promoter
sequences utilized RSAT online tools.
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Site directed mutagenesis
➲
Antunes, L.C.M., R.B.R. Ferrerira, C.P. Lostroh, and E.P. Greenberg
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Challenges
➲ We experienced difficulty with ligation and
transforming ligated parts.
➲ Using quorum sensing in synthetic biology
is tricky due to promoter cross-activity.
➲ Our lab was focused on cell biology so we
had to perfect bacterial cloning methods from scratch.
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Next Steps
➲ Apply our plan for site directed mutagenesis ➲ Evaluate additional promoters with competi-
tive polymerase activity for logic gates use
➲ Evaluate additional designs using hybrid
promoters, etc.
➲ Use functional gates in combinatorial
circuits
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Feedback from synthetic biologists working on biological computation
➲ “The challenge seems to be in finding the kinds of
problems that are well-suited to biocomputation and that target set of problems changes regularly with ad- vances in parts, tools, techniques, and imagination.”
➲ “I worked in the lab that invented bacterial computers,
and I do not see a future in it. Synthetic biology de- vices will never compete with silicon computers, and no one should be trying to make them.”
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Acknowledgements
➲ Students at Hunter College: Daniel Packer, Dylan Sun,
Melanie Balmick, Clara Ng, Ephrayim Kishko, Mark Rukhman, Anna Feitzinger, Henna Ahmed, Yaroslav Mel- nyk, Victoria Tarasova, Svitlana Tchumek
➲ Hunter College Faculty Advisors: Dr. Weigang Qiu, Dr.
Derrick Brazill and our other Advisors: Dr. David Reeves, Sung Won Lim, Dr. Malcolm Campbell (Davidson).
➲ Special thanks to Hunter College, the wonderful Quantita-
tive Biology program, chair of the CS dept Dr. Virginia Teller, the office of the president of Hunter, and William DeLoache.
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