CAREER: Machine-guided design of enzymatically-synthesized polymers optimized for digital information storage

人们越来越需要新的信息存储方法来弥合数据生成和存储能力之间日益扩大的差距。分子信息存储是解决这一问题的一种很有前途的解决方案，因为它比传统的存储介质(如磁带和磁盘)具有关键优势。这些优势包括极高的密度、长的保质期和低的能源成本。然而，要使分子信息存储实用化，必须克服几个障碍。也就是说，与以分子形式读取和写入数据相关的相对较高的成本。这项研究的重点是利用最初为生命科学开发的两个有前途的技术领域(酶DNA合成和纳米孔DNA测序)的优势，开发一种基于合成聚合物的新信息存储介质，这种介质可以大规模、低成本地合成，并可以用廉价的笔记本电脑供电的纳米孔阅读器快速解码。与传统的基于DNA的数据存储相比，这些功能将降低该系统的成本、复杂性和延迟。作为这一奖项的一部分，研究人员还致力于培养学生和专业人员精通生物学和计算机的交叉，这是一个非常有前途的科学和经济发展的新领域。这些研究方向将被整合到一门新的专题课程中，在这门课程中，计算机科学专业的学生将接触到分子计算和信息存储的概念，同时还将获得分子生物学和计算机硬件方面的实践经验。该奖项旨在实现以下目标：(1)机器指导的新dNTP类似物的设计和化学合成；(2)利用酶合成将这些类似物串联成均聚和杂聚共聚物；(3)将数字信息编码为共聚序列的演示；(4)根据新的模拟序列预测纳米孔离子电流和将新的模拟kmer信号解码为代表性比特的计算模型。最终，研究人员希望能够在他们的结果中证明，合成扩展的聚合物字母表是可能的，使用它来编码数字信息也是可能的。使用纳米孔技术读出这些信息的能力将是该系统高通量和低延迟的关键驱动因素，这要归功于与质谱仪相比的便携性和成本，质谱仪是非天然聚合物的传统读数。总而言之，这项工作代表着在以分子形式对实用的大规模数字数据进行编码的可行性方面向前迈出了重要的一步。这一奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

There is a growing need for new information storage methods that can bridge the ever-widening gap between data generation and our ability to store it. Molecular information storage is a promising solution to this problem because it has key advantages over traditional storage media (e.g., magnetic tape and disk). These advantages include extremely high density, long shelf-life, and low energy costs. However, to make molecular information storage practical, several barriers must be overcome. Namely, the relatively high costs associated with reading and writing data in molecular form. This research is focused on harnessing the advantages of two promising technological areas originally developed for the life sciences (enzymatic DNA synthesis and nanopore DNA sequencing) by developing a new information storage medium based on synthetic polymers that can be synthesized at large scale and low cost, and can be quickly decoded with inexpensive laptop-powered nanopore readers. Together, these features will lower the cost, complexity, and latency of this system compared to traditional DNA-based data storage. As part of this award, the investigators are also committed to training students and professionals to be well versed in the intersection of biology and computing, which is a very promising new area of scientific and economic development. These research directions will be integrated into a new special topics course in which computer science students will be exposed to the concepts of molecular computing and information storage, while also gaining hands-on experience in molecular biology and computer hardware.This award aims to achieve the following goals: (1) Machine-guided design and chemical synthesis of new dNTP analogs; (2) Concatenation of these analogs into homo- and heteropolymer copolymers using enzymatic synthesis; (3) Demonstration of encoding digital information into copolymer sequences; (4) Computational models for predicting nanopore ionic currents from new analog sequences and for decoding new analog kmer signals into representative bits. Ultimately, the investigators expect to be able to demonstrate in their results that synthesis of an expanded polymer alphabet is possible as is encoding digital information using it. The ability to read this information out using nanopore technology will be a key driver of the system's high-throughput and low latency thanks to the portability and cost compared to mass spectrometry, which is the traditional readout for non-natural polymers. In its sum, this work represents a significant step forward in the feasibility of practical, large-scale digital data encoding in molecular form.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.