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Direct correction of haemoglobin E β-thalassaemia using base editors

Haemoglobin E (HbE) β-thalassaemia causes approximately 50% of all severe thalassaemia worldwide; equating to around 30,000 births per year. HbE β-thalassaemia is due to a point mutation in codon 26 of the human HBB gene on one allele (GAG; glutamatic acid → AAG; lysine, E26K), and any mutation caus...

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Detalles Bibliográficos
Autores principales: Badat, Mohsin, Ejaz, Ayesha, Hua, Peng, Rice, Siobhan, Zhang, Weijiao, Hentges, Lance D., Fisher, Christopher A., Denny, Nicholas, Schwessinger, Ron, Yasara, Nirmani, Roy, Noemi B. A., Issa, Fadi, Roy, Andi, Telfer, Paul, Hughes, Jim, Mettananda, Sachith, Higgs, Douglas R., Davies, James O. J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10115876/
https://www.ncbi.nlm.nih.gov/pubmed/37076455
http://dx.doi.org/10.1038/s41467-023-37604-8
Descripción
Sumario:Haemoglobin E (HbE) β-thalassaemia causes approximately 50% of all severe thalassaemia worldwide; equating to around 30,000 births per year. HbE β-thalassaemia is due to a point mutation in codon 26 of the human HBB gene on one allele (GAG; glutamatic acid → AAG; lysine, E26K), and any mutation causing severe β-thalassaemia on the other. When inherited together in compound heterozygosity these mutations can cause a severe thalassaemic phenotype. However, if only one allele is mutated individuals are carriers for the respective mutation and have an asymptomatic phenotype (β-thalassaemia trait). Here we describe a base editing strategy which corrects the HbE mutation either to wildtype (WT) or a normal variant haemoglobin (E26G) known as Hb Aubenas and thereby recreates the asymptomatic trait phenotype. We have achieved editing efficiencies in excess of 90% in primary human CD34 + cells. We demonstrate editing of long-term repopulating haematopoietic stem cells (LT-HSCs) using serial xenotransplantation in NSG mice. We have profiled the off-target effects using a combination of circularization for in vitro reporting of cleavage effects by sequencing (CIRCLE-seq) and deep targeted capture and have developed machine-learning based methods to predict functional effects of candidate off-target mutations.