Presentation on theme: "Molecular Computation with Automated Microfluidic Sensors (MCAMS) Laura Landweber * Princeton University L. L. Sohn† M. Singh A. Sahai R. Weiss Stanford."— Presentation transcript:
Molecular Computation with Automated Microfluidic Sensors (MCAMS) Laura Landweber * Princeton University L. L. Sohn† M. Singh A. Sahai R. Weiss Stanford University C. Webb R. Davis UC Berkeley A. P. Alivisatos *DARPA Biocomp PI †NSF ITR PI
Molecular Computation with Automated Microfluidic Sensors (MCAMS) Accelerate the field of molecular-based computing by increasing sensitivity and throughput and enabling “hands-free” molecular computation. Combine microfluidic technology and biophysical methods for detecting nucleic acids with recently-developed algorithms of RNA-based computing to create a compact, automated, scalable, nucleotide-based computational device capable of rapidly and directly detecting the computational output. New Ideas Impact/Relevance
The sensing device EBL on quartz is time consuming Etched samples have finite lifetimes- after ~5 msmts., too dirty to clean and reuse Solution: Embed pore in PDMS- make one master, cast from it forever… Seal PDMS to glass slip that holds electrodes
The master Negative pore: Electron-beam-defined polystyrene line (height, width adjustable 450 nm to <100 nm), or photolith defined etched quartz (1x1 m and bigger) Negative reservoirs: SU-8 photoresist (5 m thick)
Saleh and Sohn’s device in PDMS AFM on PDMS shows successful casting down to 200 nm line width Optical image of sealed devices a small and quickly fabricated pore! PDMS Reservoir Pore Reservoir
Measuring DNA Each downward spike=single DNA molecule Pore: diameter~300 nm, 4 m long Why does peak size vary? Varying DNA conformation?
selection principle: DNA input and transport principle
Scheduled Milestones/Success Metrics Design prototype microfluidic system Identify methods for sizing and detection of RNA-based computation outputs, such as electrical detection. Develop microfluidic chip to perform RNA-based computation Explore ways to make the chip versatile for different computing algorithms Design microfluidic chip with reaction wells and switching valves Identify methods to detect 15-nt bits in RNA computation Solve an instance of a SAT problem using microfluidic device Year 1Year 2
Molecular Computation with Automated Microfluidic Sensors Princeton University L. F. Landweber (15%)* L. L. Sohn (10%) † M. Singh A. Sahai (5%) R. Weiss Danny van Noort (100%) Omar A. Saleh (30%) Zhao Huang (50%) Stanford University C. Webb (10%) R. Davis (1%) W. Tongparsit (50%) UC Berkeley A. P. Alivisatos (10%) Christine Micheel (40%) Teresa Pelelgrino (20%) *DARPA Biocomp PI †NSF ITR PI
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