Accelerating target deconvolution for therapeutic antibody candidates using highly parallelized genome editing

Jenny Mattsson; Ludvig Ekdahl; Fredrik Junghus; Ram Ajore; Eva Erlandsson; Abhishek Niroula; Maroulio Pertesi; Björn Frendéus; Ingrid Teige; Björn Nilsson

doi:10.1038/s41467-021-21518-4

Nature Communications (Feb 2021)

Accelerating target deconvolution for therapeutic antibody candidates using highly parallelized genome editing

Jenny Mattsson,
Ludvig Ekdahl,
Fredrik Junghus,
Ram Ajore,
Eva Erlandsson,
Abhishek Niroula,
Maroulio Pertesi,
Björn Frendéus,
Ingrid Teige,
Björn Nilsson

Affiliations

Jenny Mattsson: Department of Laboratory Medicine, Hematology and Transfusion Medicine
Ludvig Ekdahl: Department of Laboratory Medicine, Hematology and Transfusion Medicine
Fredrik Junghus: Department of Laboratory Medicine, Hematology and Transfusion Medicine
Ram Ajore: Department of Laboratory Medicine, Hematology and Transfusion Medicine
Eva Erlandsson: Department of Laboratory Medicine, Hematology and Transfusion Medicine
Abhishek Niroula: Department of Laboratory Medicine, Hematology and Transfusion Medicine
Maroulio Pertesi: Department of Laboratory Medicine, Hematology and Transfusion Medicine
Björn Frendéus: BioInvent International AB
Ingrid Teige: BioInvent International AB
Björn Nilsson: Department of Laboratory Medicine, Hematology and Transfusion Medicine

DOI: https://doi.org/10.1038/s41467-021-21518-4
Journal volume & issue: Vol. 12, no. 1
pp. 1 – 8

Abstract

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Efficient deconvolution of antibody targets is needed for phenotype-based discovery. Here, the authors investigate a deconvolution approach based on pooled CRISPR Cas9 to achieve 97% deconvolution success rate.

Published in Nature Communications

ISSN: 2041-1723 (Online)
Publisher: Nature Portfolio
Country of publisher: United Kingdom
LCC subjects: Science
Website: https://www.nature.com/ncomms/

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