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Single-Cell B-Cell Sequencing to Generate Natively Paired scFab Yeast Surface Display Libraries
Nathaniel Pascual1,2, Theodore Belecciu1,2, Sam Schmidt1,2
1Department of Chemical Engineering and Materials Science, Michigan State University, East Lansing, MI, USA.
Methods in Molecular Biology (Clifton, N.J.)
|July 5, 2023
Summary
This study presents a streamlined method for designing theranostic monoclonal antibodies using single-cell RNA sequencing to identify B-cell receptor sequences. This approach enables high-throughput characterization and optimization of antibody fragments for improved therapeutic applications.
Area of Science:
- Immunology
- Biotechnology
- Bioinformatics
Background:
- Single-cell RNA sequencing (scRNA-seq) offers powerful immune cell profiling capabilities.
- Theranostic monoclonal antibodies (mAbs) require precise design for targeted therapies.
- Current methods for antibody discovery can be complex and time-consuming.
Purpose of the Study:
- To present a simplified workflow for designing theranostic monoclonal antibodies.
- To leverage scRNA-seq for identifying natively paired B-cell receptor (BCR) sequences.
- To facilitate high-throughput characterization and optimization of antibody fragments.
Main Methods:
- Utilized scRNA-seq to determine paired BCR sequences from immunized mice.
- Developed a workflow for expressing single-chain antibody fragments (scFabs) on yeast surfaces.
- Integrated yeast surface display for high-throughput screening and directed evolution.
Main Results:
- Established a streamlined method for antibody fragment expression and characterization.
- Enabled rapid identification of functional BCR sequences for mAb design.
- Demonstrated a platform amenable to in silico optimization for affinity and stability.
Conclusions:
- The described method simplifies the design and optimization of theranostic mAbs.
- scRNA-seq combined with yeast display accelerates antibody discovery and development.
- This workflow supports the creation of improved antibody therapeutics with enhanced developability criteria.
