Department of Chemical Engineering and Materials Science, University of Minnesota, Minneapolis, Minnesota.
Pharmaceuticals Division, Biologics Development Department, Bayer HealthCare, Berkeley, California.
Biotechnol Prog. 2020 Jul;36(4):e2978. doi: 10.1002/btpr.2978. Epub 2020 Feb 17.
During the development of cell lines for therapeutic protein production, a vector harboring a product transgene is integrated into the genome. To ensure production stability and consistent product quality, single-cell cloning is then performed. Since cells derived from the same parental clone have the same transgene integration locus, the identity of the integration site can also be used to verify the clonality of a production cell line. In this study, we present a high-throughput pipeline for clonality verification through integration site analysis. Sequence capture of genomic fragments that contain both vector and host cell genome sequences was used followed by next-generation sequencing to sequence the relevant vector-genome junctions. A Python algorithm was then developed for integration site identification and validated using a cell line with known integration sites. Using this system, we identified the integration sites of the host vector for 31 clonal cell lines from five independent vector integration events while using one set of probes against common features of the host vector for transgene integration. Cell lines from the same lineage had common integration sites, and they were distinct from unrelated cell lines. The integration sites obtained for each clone as part of the analysis may also be used for clone selection, as the sites can have a profound effect on the transgene's transcript level and the stability of the resulting cell line. This method thus provides a rapid system for integration site identification and clonality verification.
在治疗性蛋白生产的细胞系开发过程中，携带产物转基因的载体被整合到基因组中。为了确保生产稳定性和一致的产品质量，然后进行单细胞克隆。由于来自同一亲本克隆的细胞具有相同的转基因整合位点，整合位点的同一性也可用于验证生产细胞系的克隆性。在这项研究中，我们通过整合位点分析提出了一种高通量的克隆性验证的流水线。使用基因组片段的序列捕获，这些片段既包含载体又包含宿主细胞基因组序列，然后进行下一代测序以对相关载体-基因组连接点进行测序。然后开发了一种用于整合位点识别的 Python 算法，并使用具有已知整合位点的细胞系进行了验证。使用该系统，我们鉴定了五个独立载体整合事件中 31 个克隆细胞系的宿主载体的整合位点，同时针对转基因整合的宿主载体的常见特征使用了一组探针。来自同一谱系的细胞系具有共同的整合位点，并且与不相关的细胞系不同。作为分析的一部分，每个克隆获得的整合位点也可用于克隆选择，因为这些位点可能对转基因的转录水平和产生的细胞系的稳定性产生深远影响。因此，该方法提供了一种快速的整合位点识别和克隆性验证系统。
