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Updated: Jul 26, 2025

Gene Editing of Primary Rhesus Macaque B Cells
Published on: February 10, 2023
A SMART method for efficiently isolating monoclonal antibodies from individual rhesus macaque memory B cells
Jason T Weinfurter1, Sarah N Bennett1, Matthew Reynolds1,2
1Department of Pathobiological Sciences, School of Veterinary Medicine, University of Wisconsin, Madison WI.
A new method using switching mechanism at the 5' ends of the RNA transcript (SMART) amplifies immunoglobulin variable (IgV) genes from single rhesus macaque B cells. This technique improves the isolation of antigen-specific antibodies for vaccine and infectious disease research.
Area of Science:
- Immunology
- Molecular Biology
- Primate Research
Background:
- Characterizing antigen-specific B cells in rhesus macaques (RMs) is vital for vaccine and infectious disease studies.
- Existing methods using 5' multiplex (MTPX) primers face challenges in capturing diverse RM IgV genes efficiently due to leader sequence variability.
Approach:
- Developed a novel switching mechanism at the 5' ends of the RNA transcript (SMART)-based method for amplifying IgV genes from single RM B cells.
- Optimized PCR conditions and utilized SMART 5' and 3' rapid amplification of cDNA ends (RACE) for full-length cDNA generation.
- Incorporated synthetic primer binding sites and universal 5' primers to enhance amplification of low-abundance antibody templates and simplify nested PCR.
Key Points:
- The SMART-based method enables unbiased capture of Ig heavy and light chain pairs from individual RM B cells.
- Successfully demonstrated the technique by isolating simian immunodeficiency virus (SIV) envelope-specific antibodies.
- The approach simplifies primer mixes and improves the recovery of matched antibody gene pairs.
Conclusions:
- This method enhances the isolation of antibodies from single RM B cells, facilitating genetic and functional characterization.
- It offers significant advantages over existing PCR cloning techniques for RM antibodies.
- The technique is expected to advance research in vaccine development and infectious diseases using RM models.
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