Advancing next-generation sequencing for optimization of rAAV production

BioInfoExperts开发病原体相关的下一代测序（NGS）分析和软件

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.