Direct correction of haemoglobin E β-thalassaemia using base editors.
Mohsin BadatAyesha EjazPeng HuaSiobhan RiceWeijiao ZhangLance D HentgesChristopher A FisherNicholas D R DennyRon SchwessingerNirmani YasaraNoemi B A RoyFadi IssaAnindita RoyPaul TelferJim R HughesSachith MettanandaDouglas R HiggsJames O J DaviesPublished in: Nature communications (2023)
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.
Keyphrases
- crispr cas
- stem cells
- genome wide
- endothelial cells
- machine learning
- early onset
- induced pluripotent stem cells
- induced apoptosis
- single cell
- type diabetes
- dna methylation
- pluripotent stem cells
- gene expression
- emergency department
- big data
- artificial intelligence
- drug delivery
- oxidative stress
- mesenchymal stem cells
- wild type
- gestational age
- adverse drug
- dna binding
- insulin resistance