Computational Design Engine for Accurate and Efficient Sequencing of DNA and RNA

项目总结

PROJECT SUMMARY The need to develop low-cost, rapid, and high-quality technologies for sequencing mammalian- sized genomes has inspired many nanopore-based methods. All of these methods suffer from two huge bottlenecks, which prohibit the required precision, and hence hinder the adoption of any of these methods as a practical technology as of today. These bottlenecks are: (1) undesirable noise levels for positioning DNA bases at read-out positions, and (2) difficulty in controlling capture of large DNA molecules at the nanopore. By tackling these two critical challenges, we propose to build a Computational Design Engine (CDE) to enable sequencing of DNA and RNA at the maximum accuracy allowed by laws of physics. The first aim is to reduce the positional noise of bases as DNA is being read. This goal will be accomplished by innovative implementation of ideas based on stochastic resonance, ratchet rectification, protein-assisted noise reduction, and non-enzymatic electrostatic traps. The proposed CDE will be able to design optimum features of AC fields, on top of ratcheting forces from enzymes and voltage gradients. The second aim is to enhance capture of very large DNA and RNA molecules at the nanopore for subsequent sequencing. The construction of the engine will incorporate all critical components contributing to capture: entropic barriers, internal structures of RNA, entanglement effects of DNA, electrostatics, electrohydrodynamics, and nanofluidics. The engine will design the best experimental protocols, by optimum combinations of various contributing forces, to regulate the capture efficiency of very large DNA and RNA. For both aims, a broad suite of multi-scale modeling, and advanced theories of polymer physics and non-equilibrium thermodynamics, will be used in innovative ways. The proposed CDE will put theoretical bounds, based on sound laws of polymer physics, on sequencing accuracy in various methods being pursued and how to attain their maximum capacities, and to designing better alternative technologies.