FET: Small: DNA Storage and Computation with Strand Displacement Cascades

DNA具有令人难以置信的信息密度（比光学或磁性介质密度高出6个数量级）和稳定性（数千年可读）。以文本、图像和电影的形式存储和检索高达千兆字节的数字信息已经得到成功的证明。DNA存储通常被视为被动存储（“冷存储”）的形式，并且对存储的数据执行计算目前涉及对DNA进行测序、电子计算所需的转换以及合成新的DNA，这是昂贵且缓慢的循环。该项目旨在制造下一代动态DNA存储，其中化学相互作用可以操纵“记忆中”存储的信息。研究人员将开发用于数字数据计算的重要算法的分子版本，并使用可编程的DNA-DNA相互作用来实现它们。该项目还将有助于本科生和研究生教育，并支持本科生动手研究，以及提供培训的学生在应用计算机科学和电子工程的原则，以传统上不兼容的生物和化学领域。这个项目将开发的SIMD-DNA（单指令多数据DNA）使用DNA链置换反应来操纵记录在DNA底物的拓扑修饰（链断裂的位置）中的数字信息的范例。利用化学固有的并行性，这种数据处理方案将能够进行并行的内存计算，消除了每次数据更新时测序和合成新DNA的需要。更具体地说，该奖项将资助SIMD-DNA计算理论基础的开发，包括模拟各种数据处理算法的链置换程序，以及分子算法和方法的实验演示。此外，还将开发模拟和验证SIMD-DNA程序的软件。对生物来源和序列的DNA（天然DNA）上的链置换的理论和实验研究将用于理解和减少在没有常规序列设计的情况下可能发生的虚假相互作用。与化学合成的DNA相比，天然DNA具有提高保真度和显着降低成本的潜力。最后，将探索提高大链置换级联的速度和效率的新方法，这可能超出DNA存储的范围。该奖项反映了NSF的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。

DNA is incredibly information-dense (up to 6 orders of magnitude denser than optical or magnetic media) and stable (readable over millennia). Storage and retrieval of up to gigabytes of digital information in the form of text, images, and movies has already been successfully demonstrated. DNA storage is typically viewed as a form of passive storage (“cold storage”) and performing computation on the stored data currently involves sequencing the DNA, electronically computing the desired transformation, and synthesizing new DNA, which is an expensive and slow loop. This project seeks to make the next generation of dynamic DNA storage, where chemical interactions can manipulate the stored information “in memory.” Investigators will develop molecular versions of important algorithms for computation on digital data and implement them using programmable DNA-DNA interactions. The project will also contribute to undergraduate and graduate education and support undergraduate hands-on research, as well as provide training of students in applying the principles of computer science and electrical engineering to traditionally incompatible domains of biology and chemistry.This project will develop the SIMD-DNA (Single-Instruction Multiple-Data DNA) paradigm for using DNA strand displacement reactions to manipulate digital information recorded in the topological modification of the DNA substrate (location of strand breaks). Using the inherent parallelism of chemistry, this data processing scheme will be capable of parallel, in-memory computation, eliminating the need for sequencing and synthesizing new DNA on each data update. More specifically, the award will fund the development of the theoretical foundation of SIMD-DNA computation, including strand displacement programs to simulate various data-processing algorithms, as well as the experimental demonstration of the molecular algorithms and methodology. Further, software to simulate and verify SIMD-DNA programs will be developed. Theoretical and experimental studies on strand displacement on DNA of biological origin and sequence (native DNA) will be used to understand and decrease the spurious interactions that can occur in the absence of conventional sequence design. Native DNA has the potential to improve fidelity and significantly decrease cost compared to chemically synthesized DNA. Finally, new methods to improve the speed and efficiency of large strand displacement cascades will be explored, which may generalize beyond DNA storage.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.