High-throughput retrieval of physical DNA for NGS-identifiable clones in phage display library

MAbs. 2019 Apr;11(3):532-545. doi: 10.1080/19420862.2019.1571878. Epub 2019 Feb 12.

Abstract

In antibody discovery, in-depth analysis of an antibody library and high-throughput retrieval of clones in the library are crucial to identifying and exploiting rare clones with different properties. However, existing methods have technical limitations, such as low process throughput from the laborious cloning process and waste of the phenotypic screening capacity from unnecessary repetitive tests on the dominant clones. To overcome the limitations, we developed a new high-throughput platform for the identification and retrieval of clones in the library, TrueRepertoire™. This new platform provides highly accurate sequences of the clones with linkage information between heavy and light chains of the antibody fragment. Additionally, the physical DNA of clones can be retrieved in high throughput based on the sequence information. We validated the high accuracy of the sequences and demonstrated that there is no platform-specific bias. Moreover, the applicability of TrueRepertoire™ was demonstrated by a phage-displayed single-chain variable fragment library targeting human hepatocyte growth factor protein.

Keywords: Antibody discovery; NGS; antibody library; antibody library sequencing; clone retrieval; lead antibody; monoclonal antibody; phage display; rare clones.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animals
  • Avian Proteins* / biosynthesis
  • Avian Proteins* / chemistry
  • Avian Proteins* / genetics
  • Bacteriophages / genetics
  • Cell Surface Display Techniques / methods*
  • Chickens
  • Single-Chain Antibodies* / biosynthesis
  • Single-Chain Antibodies* / chemistry
  • Single-Chain Antibodies* / genetics

Substances

  • Avian Proteins
  • Single-Chain Antibodies

Grants and funding

This research was supported by Global Research Development Center Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science and ICT(MSIT) (2015K1A4A3047345); the Brain Korea 21 Plus Project in 2018; grant of the Korea Health Technology R&D Project of the Korea Health Industry Development Institute (KHIDI) funded by the Ministry of Health & Welfare, Republic of Korea (HI18C2282); the Bio & Medical Technology Development Program of the National Research Foundation (NRF) funded by the Korean government (MSIT) (2018M3A9D7079488). This work was supported by the Brain Korea 21 Plus Project in 2018.