Biolojic Design, Ltd, Rehovot, Israel.
The Goodman Faculty of Life Sciences, Bar Ilan University, Ramat Gan, Israel.
Nucleic Acids Res. 2023 Jun 23;51(11):e61. doi: 10.1093/nar/gkad235.
Deep parallel sequencing (NGS) is a viable tool for monitoring scFv and Fab library dynamics in many antibody engineering high-throughput screening efforts. Although very useful, the commonly used Illumina NGS platform cannot handle the entire sequence of scFv or Fab in a single read, usually focusing on specific CDRs or resorting to sequencing VH and VL variable domains separately, thus limiting its utility in comprehensive monitoring of selection dynamics. Here we present a simple and robust method for deep sequencing repertoires of full length scFv, Fab and Fv antibody sequences. This process utilizes standard molecular procedures and unique molecular identifiers (UMI) to pair separately sequenced VH and VL. We show that UMI assisted VH-VL matching allows for a comprehensive and highly accurate mapping of full length Fv clonal dynamics in large highly homologous antibody libraries, as well as identification of rare variants. In addition to its utility in synthetic antibody discovery processes, our method can be instrumental in generating large datasets for machine learning (ML) applications, which in the field of antibody engineering has been hampered by conspicuous paucity of large scale full length Fv data.
深度平行测序（NGS）是监测 scFv 和 Fab 文库动力学的一种可行工具，在许多抗体工程高通量筛选工作中都有应用。尽管非常有用，但常用的 Illumina NGS 平台无法在单个读取中处理 scFv 或 Fab 的整个序列，通常侧重于特定的 CDR 或分别测序 VH 和 VL 可变域，从而限制了其在全面监测选择动力学方面的应用。在这里，我们提出了一种用于深度测序全长 scFv、Fab 和 Fv 抗体序列的简单而强大的方法。该过程利用标准分子程序和独特的分子标识符（UMI）来分别对 VH 和 VL 进行配对。我们表明，UMI 辅助的 VH-VL 匹配允许对大型高度同源的抗体文库中的全长 Fv 克隆动力学进行全面且高度准确的映射，并且能够鉴定稀有变体。除了在合成抗体发现过程中的实用性之外，我们的方法还可以为机器学习（ML）应用生成大型数据集提供帮助，在抗体工程领域，由于缺乏大规模的全长 Fv 数据，这一直是一个明显的问题。
