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Transcript of Programming Bacterial Communities to Function as Massively Parallel Computers Jeff Tabor Voigt Lab...
![Page 1: Programming Bacterial Communities to Function as Massively Parallel Computers Jeff Tabor Voigt Lab University of California, San Francisco.](https://reader036.fdocuments.net/reader036/viewer/2022062409/56649e025503460f94aecfdc/html5/thumbnails/1.jpg)
Programming Bacterial Communities to Function as Massively Parallel Computers
Jeff Tabor Voigt Lab
University of California, San Francisco
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Cells can perform logical computations
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Biological computers are slow and noisy
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To engineer an efficientbiological computer…
• Choose a problem which is– Computationally simple– Scales well with many parallel processors
• Number of bacterial computers that can be grown inexpensively in one day:– 224(hr)/20(min)=272=4x1021
– ~1011 transistors in a PC– ~1010 PCs worth of computational power
• Image Processing– Amenable to parallel efforts (many independent variables)
c/o Zack B. Simpson
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Bacterial edge detector
Projector
Petri dish
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Steps to engineering a bacterial edge detector
1. Make blind E.coli ‘see’
2. Engineer a bacterial ‘film’
3. Program film to compute light/dark boundaries
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Step1: Engineering E.coli to see light
Levskaya et al., Nature 2005
Bla
ck P
igm
en
t
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Patterning bacterialgene expression with light
Levy, Tabor, Wong. IEEE SPM 2006
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Step 2: Bacterial photography
ImageMask
BacterialLawn
‘Blind’E.coli
Levskaya et al., Nature 2005
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Bacterial portraiture
Escherichia EllingtonE.coli self-portraitPhoto: Marsha Miller
Levskaya et al., Nature 2005
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Bacterial films show continuous input-output response
Light Intensity
Outp
ut
Levskaya et al., Nature 2005
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Continuous response allows grayscale fidelity
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Conclusions – Bacterial Photography
• Theoretical resolution of 100 Megapixels per square inch– 10x higher than modern high-resolution printers
• Direct printing of biological materials– Spider silks– Metal precipitates
• Light offers exquisite spatiotemporal control– Spatial: Chemical inducers diffuse – Temporal: Chemical inducers must decay
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Genetic circuit for edge detection
Only occurs at light/dark boundary
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LOW output from gate 1 interpreted as HIGH input at gate 2
Light inhibition isincomplete
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Matching gates through RBS redesign
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Step 3: Bacterial Edge Detection
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Bacterial Edge Detection
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Conclusions – Edge Detector
• Scale-free (size-independent) computation time – Quadratic scaling in serial computers
• Largest de novo synthetic genetic system to date– 17.7kb
• Communication facilitates transition from simple single cell logic to emergent community-level behaviors
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Acknowledgements
• Zack Simpson (UT-Austin)• Aaron Chevalier (UT-Austin)• Edward Marcotte (UT-
Austin)• Andy Ellington (UT-Austin)• Anselm Levskaya• Chris Voigt