DNA 3.0: Developing novel enzymes for DNA synthesis with deep learning and combinatorial genetics

DNA 3.0：利用深度学习和组合遗传学开发用于 DNA 合成的新型酶

• 批准号: 10010243
• 负责人: Helge Zieler
• 金额: $ 37.45万
• 依托单位: PRIMORDIAL GENETICS, INC
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-04-15 至 2022-01-15
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10010243
• 关键词: Artificial Intelligence; Bioinformatics; Biological; Biological Process; Biotechnology; Capital; Cells; Chemicals; Chemistry; Collection; Computing Methodologies; Cost efficiency; Cystic Fibrosis; DNA; DNA Nucleotidylexotransferase; DNA biosynthesis; DNA-Directed DNA Polymerase; Data Set; Data Storage and Retrieval; Databases; Development; Diagnosis; Diagnostic; Enzymes; Equipment; Evolution; Feasibility Studies; Generations; Genes; Genetic; Genetic Diseases; HIV; Heart Diseases; In Vitro; Industrialization; Industry; Length; Libraries; Licensing; Malignant Neoplasms; Methods; Microbe; Modeling; Modernization; Molecular; Molecular Biology; Molecular Genetics; Molecular Machines; Mutation; Nucleotides; Oligonucleotides; Performance; Phase; Play; Polymerase; Population; Prevention; Process; Proteins; Randomized; Reagent; Reporting; Research Project Grants; Scanning; Single-Stranded DNA; Small Business Innovation Research Grant; Technology; Testing; Therapeutic; TimeLine; Training; Variant; Work; base; combinatorial; cost; deep learning; genetic technology; high throughput screening; human disease; improved; in vitro testing; machine learning algorithm; model development; next generation; novel; phosphoramidite; prediction algorithm; predictive test; research and development; synthetic biology; synthetic construct; tool

Project Summary/Abstract DNA synthesis has played a key role in the biotechnology revolution. The ready availability of synthetic DNA oligonucleotides and of genes assembled from them, has been invaluable for elucidating and unlocking biological function and enabling the new field of synthetic biology which can create novel cells, enzymes, therapeutics, diagnostics and other reagents of commercial value. Despite this impact, DNA synthesis uses chemical strategies developed over 30 years ago which are costly and limited to molecules of 200 nucleotides or less in length. Next-generation enzymatic DNA synthesis technologies are being explored that use template- independent DNA polymerases (TIDPs) for controlled addition of nucleotides to a growing DNA strand. Although advances have been reported recently, enzymatic DNA synthesis is still limited by the low efficiency of available TIDPs, and specifically by the relative inability of these polymerases to incorporate 3'-blocked nucleotides. In this Phase I Small Business Innovation Research (SBIR) project, Primordial Genetics Inc, a synthetic biology company with differentiated combinatorial genetic technology, and Denovium Inc., an artificial intelligence company pioneering novel Al methods for genetic discovery, are joining forces to develop novel and highly efficient TIDPs for enzymatic DNA synthesis in vitro. Denovium will use their computational capabilities based on machine learning algorithms to discover novel TIDPs with the desired activities from proprietary and public databases. Denovium will also perform proprietary artificial intelligence (AI) scans to determine the functional impact of all possible mutations on the selected TIDPs. Primordial Genetics will synthesize and express the resulting collection of sequences, and test them in vitro to identify the most active enzymes. The best 2 enzymes will be diversified using Primordial Genetics' proprietary Function Generator technology and other randomized diversification methods. Populations of genes encoding enzyme variants will be screened with ultra-high-throughput screens to identify the most active enzymes. The dataset resulting from this work will be used to train Denovium's sequence prediction algorithm to accelerate further enzyme improvements in Phase II. The proposed work is a feasibility study for isolating and developing novel enzymes suitable for enzymatic DNA synthesis, and also for creating a pipeline of enzyme optimization tools. The enzymes discovered and in this work will be directly useful for enzymatic DNA synthesis applications, and can be licensed or sold to leading DNA and gene manufaturers.

项目摘要/摘要 DNA合成在生物技术革命中发挥了关键作用。现成的可用 合成的DNA寡核苷酸和由它们组装的基因对 阐明和解锁生物功能，使合成生物学的新领域 可以创造新的细胞、酶、治疗学、诊断学和其他具有商业价值的试剂。 尽管有这种影响，DNA合成使用了30多年前开发的化学策略 是昂贵的，并且被限制在200个核苷酸或更少的分子长度。 下一代酶促DNA合成技术正在探索中，它使用模板- 独立DNA聚合酶(TIDPs)用于控制核苷酸与生长中的DNA的加成 斯特兰德。尽管最近报道了一些进展，但酶促DNA合成仍然受到以下因素的限制 现有TIDPs的低效率，特别是这些聚合酶的相对无能为力 加入3‘端被阻断的核苷酸。 在这个第一阶段小型企业创新研究(SBIR)项目中，Primorial Genetics Inc. 具有差异化组合基因技术的合成生物公司和Denovium Inc. 一家开创基因发现新方法的人工智能公司即将加入 推动开发新型高效的TIDPs，用于酶促DNA的体外合成。 Denovium将利用其基于机器学习算法的计算能力 从专有和公共数据库中发现具有所需活动的新型TIDP。丹尼尔氏菌 还将执行专有人工智能(AI)扫描，以确定所有 选定的TIDP上可能存在突变。原始遗传学将合成和表达 收集得到的序列，并在体外进行测试，以确定最具活性的酶。最好的 2种酶将使用Primorial Genetics公司专有的功能生成器技术进行多样化 和其他随机多样化的方法。编码酶变异体的基因群体将 用超高通量筛选，以确定最活跃的酶。数据集 将本工作得到的结果用于训练Denovium的序列预测算法进行加速 在第二阶段中酶的进一步改进。 这项工作是一项分离和开发适合于 酶DNA合成，也用于创建一系列酶优化工具。这个 在这项工作中发现的酶将直接用于酶DNA合成应用， 并可授权或出售给领先的DNA和基因制造商。