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Assuring Clonality on the Beacon Digital Cell Line Development Platform
Author(s) -
Le Kim,
Tan Christopher,
Le Huong,
Tat Jasmine,
Zasadzinska Ewelina,
Diep Jonathan,
Zastrow Ryan,
Chen Chun,
Stevens Jennitte
Publication year - 2020
Publication title -
biotechnology journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.144
H-Index - 84
eISSN - 1860-7314
pISSN - 1860-6768
DOI - 10.1002/biot.201900247
Subject(s) - line (geometry) , computer science , computational biology , biology , mathematics , geometry
During biomanufacturing cell lines development, the generation and screening for single‐cell derived subclones using methods that enable assurance of clonal derivation can be resource‐ and time‐intensive. High‐throughput miniaturization, automation, and analytic strategies are often employed to reduce such bottlenecks. The Beacon platform from Berkeley Lights offers a strategy to eliminate these limitations through culturing, manipulating, and characterizing cells on custom nanofluidic chips via software‐controlled operations. However, explicit demonstration of this technology to provide high assurance of a single cell progenitor has not been reported. Here, a methodology that utilizes the Beacon instrument to ensure high levels of clonality is described. It is demonstrated that the Beacon platform can efficiently generate production cell lines with a superior clonality data package, detailed tracking, and minimal resources. A stringent in‐process quality control strategy is established to enable rapid verification of clonal origin, and the workflow is validated using representative Chinese hamster ovary‐derived cell lines stably expressing either green or red fluorescence protein. Under these conditions, a >99% assurance of clonal origin is achieved, which is comparable to existing imaging‐coupled fluorescence‐activated cell sorting seeding methods.