Title Rapid isolation of antigen-specific B-cells using droplet microfluidics /
Authors Ding, Ruihua ; Hung, Kuo-Chan ; Mitra, Anindita ; Ung, Lloyd W ; Lightwood, Daniel ; Tu, Ran ; Starkie, Dale ; Cai, Liheng ; Mažutis, Linas ; Chong, Shaorong ; Weitz, David A ; Heyman, John A
DOI 10.1039/d0ra04328a
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Is Part of RSC advances.. Cambridge : Royal Society of Chemistry. 2020, vol. 10, iss. 45, p. 27006-27013.. eISSN 2046-2069
Keywords [eng] microfluidics ; B-cells ; antibodies
Abstract [eng] Monoclonal antibodies are powerful tools for scientific research and are the basis of numerous therapeutics. However, traditional approaches to generate monoclonal antibodies against a desired target, such as hybridoma-based techniques and display library methods, are laborious and suffer from fusion inefficiency and display bias, respectively. Here we present a platform, featuring droplet microfluidics and a bead-based binding assay, to rapidly identify and verify antigen-binding antibody sequences from primary cells. We used a defined mixture of hybridoma cells to characterize the system, sorting droplets at up to 100 Hz and isolating desired hybridoma cells, comprising 0.1% of the input, with a false positive rate of less than 1%. We then applied the system to once-frozen primary B-cells to isolate rare cells secreting target-binding antibody. We performed RT-PCR on individual sorted cells to recover the correctly paired heavy- and light-chain antibody sequences, and we used rapid cell-free protein synthesis to generate single-chain variable fragment-format (scFv) antibodies from fourteen of the sorted cells. Twelve of these showed antigen-specific binding by ELISA. Our platform facilitates screening animal B-cell repertoires within days at low cost, increasing both rate and range of discovering antigen-specific antibodies from living organisms. Further, these techniques can be adapted to isolate cells based on virtually any secreted product. This journal is.
Published Cambridge : Royal Society of Chemistry
Type Journal article
Language English
Publication date 2020
CC license CC license description