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.

项目概要/摘要 DNA合成在生物技术革命中发挥了关键作用。随时可用 合成的 DNA 寡核苷酸以及由它们组装的基因对于 阐明和解锁生物功能并开启合成生物学新领域 可以创造新的细胞、酶、治疗剂、诊断剂和其他具有商业价值的试剂。 尽管存在这种影响，DNA 合成仍使用 30 多年前开发的化学策略， 其成本昂贵且仅限于长度为 200 个核苷酸或更短的分子。 正在探索使用模板的下一代酶促 DNA 合成技术 独立的 DNA 聚合酶 (TIDP)，用于控制向生长中的 DNA 添加核苷酸 股。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 TIDP 的效率低，特别是这些聚合酶的相对无能 掺入 3'-封闭的核苷酸。 在这个第一阶段小企业创新研究 (SBIR) 项目中，Primordial Genetics Inc 拥有差异化组合遗传技术的合成生物学公司和 Denovium Inc.， 一家人工智能公司开创了用于基因发现的新型人工智能方法，正在加入 迫使开发新型高效的 TIDP 用于体外酶促 DNA 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。德诺维姆 还将执行专有的人工智能 (AI) 扫描，以确定所有功能的影响 所选 TIDP 上可能发生的突变。原始遗传学将合成并表达 由此产生的序列集合，并在体外测试它们以识别最活跃的酶。最好的 2 种酶将利用 Primordial Genetics 专有的 Function Generator 技术实现多样化 和其他随机多样化方法。编码酶变体的基因群体将 通过超高通量筛选来筛选最活跃的酶。数据集 这项工作的成果将用于训练 Denovium 的序列预测算法以加速 第二阶段进一步改进酶。 拟议的工作是分离和开发适合的新型酶的可行性研究 酶促 DNA 合成，还用于创建一系列酶优化工具。这 在这项工作中发现的酶将直接用于酶促 DNA 合成应用， 并可授权或出售给领先的 DNA 和基因制造商。