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

项目摘要 需要开发低成本、快速和高质量的哺乳动物基因测序技术， 大小的基因组启发了许多基于纳米孔的方法。所有这些方法都有两个缺点 巨大的瓶颈，禁止所需的精度，因此阻碍了采用任何 这些方法作为一种实用的技术至今。这些瓶颈是：（1）不希望的噪声 用于将DNA碱基定位在读出位置的水平，和（2）难以控制捕获 纳米孔中的DNA分子。通过应对这两个关键挑战，我们建议 建立一个计算设计引擎（CDE），使DNA和RNA的测序在 物理定律所允许的最大精度。 第一个目标是减少DNA被读取时碱基的位置噪声。这一目标将 通过基于随机共振、棘轮 整流，蛋白质辅助降噪，和非酶静电陷阱。拟议的CDE将能够设计AC场的最佳特征，在酶和电压梯度的棘轮力之上。 第二个目的是增强在纳米孔处捕获非常大的DNA和RNA分子 用于后续测序。发动机的结构将包括所有关键部件 有助于捕获：熵障碍，RNA的内部结构，纠缠效应 DNA、静电学、电流体力学和纳米流体学。发动机将设计出最好的 实验协议，通过各种贡献力量的最佳组合，以调节 非常大的DNA和RNA的捕获效率。 对于这两个目标，一个广泛的多尺度建模套件，和聚合物物理学的先进理论 和非平衡态热力学，将以创新的方式使用。拟议的CDE将 基于聚合物物理学的合理定律，在各种情况下对测序准确性的理论界限 方法，以及如何实现其最大能力，并设计更好的 替代技术。

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.