Advancing next-generation sequencing for optimization of rAAV production

推进下一代测序以优化 rAAV 生产

• 批准号: 10820589
• 负责人: Susanna L Lamers
• 金额: $ 29.59万
• 依托单位: BIOINFOEXPERTS
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-09-25 至 2024-09-24
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10820589
• 关键词: Advancing; next; generation; sequencing; optimization

1 BioInfoExperts develops pathogen-associated next-generation sequencing (NGS) analytics and software for a 2 growing number of industries that require genome characterization. In the proposed SBIR Phase I project, we 3 will develop NGS analytics for the recombinant adeno-associated viruses (rAAVs) manufacturing industry; in 4 Phase II, we will incorporate the NGS analytics into a a software-as-a-service (SaaS) where customers (rAAV 5 manufacturers) can access results from customized analytical pipelines designed explicitly for their processes. 6 There are >200 rAAV products in clinical trials and three FDA-approved rAAV-mediated gene therapies already 7 in the market. As the industry expands, the FDA is demanding more rigorous rAAV manufacturing quality control 8 (QC) methods to ensure patient safety. In fact, both the FDA and the Dark Horse Consulting group, an advisory 9 committee for the rAAV industry, have recommended NGS for rAAV QC; however, the methods for NGS 10 evaluation of rAAV data have not yet matured to the point where they are accurate or high throughput enough 11 for widespread adoption. NGS from rAAV is notoriously difficult to process, due in part to the production 12 processes and genomic structure of rAAV, combined with limitations of the sequencing platforms such as high 13 error rate, bias towards short reads, and potential for generating chimeric reads. With decades of pathogen- 14 related bioinformatics experience and a successful software-as-as-service business model, BIE plans to 15 aggressively enter this competitive market, and systematically address the issues associated with rAAV NGS 16 data. We will collaborate with Lacerta Therapeutics, a company with long experience with rAAV capsid 17 technology and scalable manufacturing platforms. In Phase I, we will assess the reliability, consistency, and 18 accuracy of NGS for quantifying production-induced mutations in rAAV vector DNA. We will generate sequence 19 data from encapsidated DNA of a self-complementary (sc)AAV vector produced in two different systems (human 20 and insect cell line). In Specific Aim 1, we will use single genome amplification (SGA) followed by Sanger 21 sequencing to generate highly accurate near-full length genomes (NFLG) of the vector DNA, which will enable 22 precise quantification of the actual production-induced mutation rate. In Specific Aim 2, we will generate data on 23 three NGS platforms: Oxford Nanopore, Pacific Bioscience Single Molecule Real Time, and Illumina. We will use 24 several different approaches for error-correction, including combining data from two or more sequencing 25 platforms, and compare results to the known mutations as identified through SGA. Our goal is to develop a 26 bioinformatics pipeline that leverages the power and efficiency of NGS while attaining the level of accuracy of 27 SGA for identifying true production induced mutations. In Phase II, we will continue to address other AAV NGS 28 quality control issues and build our SaaS in the cloud, where we will be able to quickly scale and innovate as 29 needed.

1 BioInfoExperts开发病原体相关的下一代测序（NGS）分析和软件， 2越来越多的行业需要基因组表征。在拟议的SBIR第一阶段项目中，我们 3将为重组腺相关病毒（rAAV）制造业开发NGS分析; 4第二阶段，我们将把NGS分析纳入软件即服务（SaaS），客户（rAAV） 5制造商）可以访问专门为其工艺设计的定制分析管道的结果。 目前已有超过200种rAAV产品在临床试验中，三种rAAV介导的基因疗法已经获得FDA批准。 7在市场上随着行业的扩大，FDA要求更严格的rAAV制造质量控制 8（QC）方法，确保患者安全。事实上，FDA和黑马咨询集团， 9个rAAV行业委员会推荐了NGS用于rAAV QC;然而，NGS的方法 rAAV数据的评估尚未成熟到足够准确或高通量的程度 11、广泛采用。众所周知，来自rAAV的NGS难以加工，部分原因是其生产过程中产生了大量的蛋白质。 12个过程和rAAV的基因组结构，结合测序平台的限制，如高 错误率、对短读段的偏倚和产生嵌合读段的潜力。几十年的病原体- 14相关的生物信息学经验和成功的软件即服务商业模式，BIE计划 积极进入这个竞争激烈的市场，并系统地解决与rAAV NGS相关的问题 16个数据。我们将与Lacerta Therapeutics合作，该公司在rAAV衣壳方面拥有长期经验 17个技术和可扩展的制造平台。在第一阶段，我们将评估可靠性、一致性和 图18 NGS用于定量rAAV载体DNA中产生诱导的突变的准确度。我们将生成序列 图19来自在两种不同系统（人）中产生的自身互补（sc）AAV载体的双核苷酸化DNA的数据 20和昆虫细胞系）。在特定目标1中，我们将使用单基因组扩增（SGA），然后使用桑格 21测序以产生载体DNA的高度准确的近全长基因组（NFLG），这将使 22实际生产诱导突变率的精确定量。在具体目标2中，我们将生成以下数据 23三个NGS平台：Oxford Nanopore、Pacific Bioscience Single Molecule真实的Time和Illumina。我们将使用 24几种不同的纠错方法，包括组合来自两个或更多个测序的数据 25个平台，并将结果与通过SGA鉴定的已知突变进行比较。我们的目标是发展一个 26个生物信息学管道，利用NGS的功能和效率，同时达到 27 SGA用于鉴定真正的生产诱导突变。在第二阶段，我们将继续解决其他AAV NGS 28个质量控制问题，并在云中构建我们的SaaS，在那里我们将能够快速扩展和创新， 29需要