Development of pathophysiologically relevant models of sickle cell disease and β-thalassemia for therapeutic studies

Abstract

Ex vivo cellular system that accurately replicates sickle cell disease and β-thalassemia characteristics is a highly sought-after goal in the field of erythroid biology. In this study, we present the generation of erythroid progenitor lines with sickle cell disease and β-thalassemia mutation using CRISPR/Cas9. The disease cellular models exhibit similar differentiation profiles, globin expression and proteome dynamics as patient-derived hematopoietic stem/progenitor cells. Additionally, these cellular models recapitulate pathological conditions associated with both the diseases. Hydroxyurea and pomalidomide treatment enhanced fetal hemoglobin levels. Notably, we introduce a therapeutic strategy for the above diseases by recapitulating the HPFH3 genotype, which reactivates fetal hemoglobin levels and rescues the disease phenotypes, thus making these lines a valuable platform for studying and developing new therapeutic strategies. Altogether, we demonstrate our disease cellular systems are physiologically relevant and could prove to be indispensable tools for disease modeling, drug screenings and cell and gene therapy-based applications.

Fig. 1. Development of cellular disease model systems, BEL-A SCM and BEL-A BTM.

A Schematics showing the workflow for the development of disease model cell lines using CRISPR/Cas9 coupled with piggyBac Transposon system, functional characterizations, and their applications. B Chromatogram showing Sickle cell mutation (GAG > GTG) in BEL-A SCM through Sanger sequencing. C Chromatogram showing β-thalassemia mutation (IVS1-5, G > C) in BEL-A BTM through Sanger sequencing. D Representative Giemsa images from different erythroblasts present at the end of the differentiation in BEL-A cells (WT, SCM, BTM) and HSPCs (WT, SCM, BTM) respectively (≥200 cell counts per field). Graph is plotted as relative proportion of erythroblasts by total number of cells. E Cell expansion profile of BEL-A (WT, SCM, BTM) and HSPCs (WT, SCM, BTM) during differentiation. Cells were counted with trypan blue exclusion dye. All data is shown as Mean ± S.D from three independent replicates (n = 3). Source data is provided in the Source file.

Fig. 2. Characterization of disease model cell lines, BEL-A SCM and BEL-A BTM.

A Enucleation presented as percentage of Hoechst 33342 negative cells in flow cytometry during the progression of differentiation till Day 12 and Day 21 of BEL-A cells (WT, SCM, BTM) and HSPCs (WT, SCM, BTM). B Percentage of enucleation in BEL-A cells and HSPCs at Day 12 and Day 21 of differentiation and comparisons of enucleation efficiency of disease cells with respective WT. C Analysis of relative mRNA levels of HBB, HBG, HBDgenes at day 6 of differentiation. The expression of the genes was normalized with the GAPDH housekeeping gene. The graph is plotted as mRNA levels of β-globin genes divided by α-gene levels. D Population of HbF antibody-stained positive cells in flow cytometry plots presented as percentage of F cell population. Percentage was normalized with its respective unstained controls.; E, F RP-HPLC analysis of globin chains was done at Day 10 and Day 21 of differentiation in (E) BEL-A SCM and HSPC SCM (F) BEL-A BTM and HSPC BTM respectively. All data is shown as Mean ± S.D from three independent replicates (n = 3). Statistical significance was determined by using two tailed student’s t-test. Source data is provided in the Source file.

Fig. 3. BEL-A SCM and BEL-A BTM are similar to disease specific HSPCs and recapitulate disease physiology.

A, B Heatmaps of proteomic data from (A) BEL-A SCM with SCM HSPCs and (B) BEL-A BTM with BTM HSPCs presented as log 10 normalized data. Red indicates high protein expression and blue indicates low protein expression. C, D Volcano plots of (C) BEL-A SCM with SCM HSPCs and (D) BEL-A BTM and BTM HSPCs are presented as -log10 p-value and -log2 fold change value. Upregulated proteins (fold change of ≥1.5) are depicted in green and downregulated proteins (fold change of ≤0.67) are depicted in red with p-values < 0.05. Quantile normalization was done and statistical significance was determined by two tailed t-test. E Representative micrographs of sickling assay done in BEL-A WT, BEL-A SCM, WT HSPC and SCM HSPC derived reticulocytes. Scale: 20 µm (F) Quantification of sickled cells in BEL-A WT, BEL-A SCM, WT HSCPs and SCM HSPCs derived reticulocytes. Percentage sickled cells presented as number of cells with sickle and abnormal morphology by total number of cells (≥200 cell counts). G Percentage of ROS in BEL-A (WT, SCM and BTM) and HSPCs (WT, SCM and BTM). Data is plotted as percentage positive cells in flow cytometric analysis. H Flow-cytometric analysis of β-like globin by α-globin in BEL-A (WT and BTM) and HSPCs (WT and BTM) derived erythroblasts. All experiments were done in triplicates independently (n = 3) and data is presented as Mean ± S.D. Statistical significance was determined by using two tailed student’s t-test. Source data is provided in the Source file.

Fig. 4. BEL-A SCM shows physiologically similar invasion efficiency as SCD patients derived RBCs.

A Representative Giemsa microscopic images of parasite invasion. WT RBCs and BEL-A WT reticulocytes showed normal merozoite invasion at 12 h post infection (hpi); while SCD erythrocytes and BEL-A SCM reticulocytes showed reduced invasion. Arrows indicate infected RBCs (Red Blood cells) successfully invaded by merozoites. B Quantification of parasite invasion by plotting percentage parasitemia. Data is presented as Mean ± S.D. C Representative microscopic images of Giemsa-stained smears at time points 6 hpi, 18 hpi, 30 hpi, 42 hpi and 54hpi for the parasite invasion assay done at 5% O2 condition and its (D, E) Quantification of parasite invasion efficiency by plotting percentage parasitemia. Data is presented as Mean ± S.D. F Representative microscopic images of Giemsa-stained smears at time points 6 hpi, 18 hpi, 30 hpi, 42 hpi and 54 hpi for the parasite invasion assay done at 0.2% O2 condition and its (G, H) Quantification (Mean ± S.D) of parasite invasion efficiency. All experiments were done in three independent replicates (n = 3). Scale bar: 10 µm. Statistical significance was determined by using two tailed student’s t-test. Source data is provided in the Source file.

Fig. 5. BEL-A SCM and BEL-A BTM are therapeutically relevant disease models for drug validation.

A Percentage of enucleation after drug treatment. B–D Estimation of increase in γ-globin gene expression. B Analysis of relative HBG1/2 gene expression after treatment in BEL-A SCM and BEL-A BTM at Day 6 of differentiation by qRT PCR. C Flow cytometry-based quantification of F-cell population after drug treatment in BEL-A SCM and BEL-A BTM cells. D RP-HPLC of globin chains. Data is presented as the abundance of γ globin by abundance of total β- like goblins (β + γ + δ). E–J Determination of rescue in disease phenotype and/or physiology at day 10 of differentiation (E) Percentage of ROS in BEL-A SCM and BEL-A BTM. F Flow-cytometric analysis of β-like globin divided by α-globin in BEL-A BTM differentiated cells. G, H RP-HPLC plotted as β-like globins (β + γ + δ) divided by α-globin in (G) BEL-A BTM differentiated cells and (H) BEL-A SCM differentiated cells treated with HU (hydroxyurea) and Pom (Pomalidomide). I Representative microscopic images of sickling in BEL-A differentiated cells at Day 12 (≥200 cell counts), Scale bar: 20 µm and its (J) quantification. All experiments were done in triplicates independently (n = 3) and data is presented as Mean ± S.D. Statistical significance was determined by using two tailed student’s t-test. Source data is provided in the Source file.

Fig. 6. CRISPR-mediated genome editing recapitulates HPFH3 genotype and rescues disease phenotype.

CRISPR/Cas9-mediated genome editing was utilized for generating HPFH3 deletion (Indian HPFH3). A Schematics showing target region for HPFH3 genotype recapitulation at β-globin cluster on Chromosome11. B Efficiency of HPFH3 deletion in BEL-A SCM and BEL-A BTM cells estimated using ddPCR. (C) Enucleation percentage of unedited and HPFH3-edited BEL-A SCM and BEL-A BTM cells. D–F Estimation of increase in γ-globin gene expression. (D) Relative HBG1/2 gene expression of unedited and HPFH3-edited BEL-A SCM and BEL-A BTM cells. E Flow cytometry-based quantification of F-cell population of unedited and HPFH3 edited BEL-A SCM and BEL-A BTM cells. F RP-HPLC of globin chains in BEL-A SCM and BEL-A BTM HPFH3 edited cells. Data is presented as the abundance of γ-globin by abundance of total β-like globins (β + γ + δ). G–L Determination of rescue in disease phenotype and/or physiology at day 10 of differentiation (G) Percentage of ROS in unedited and HPFH3 edited BEL-A SCM and BEL-A BTM cells. H Flow-cytometric analysis of β-like globins divided by α-globin in unedited and HPFH3 edited BEL-A BTM differentiated cells (I, J) RP-HPLC plotted as β-like globins (β + γ + δ) divided by α-globin in (I) BEL-A BTM unedited and HPFH3 edited differentiated cells and (J) BEL-A SCM unedited and HPFH3 edited differentiated cells. K Representative microscopic images of sickling in BEL-A SCM unedited and edited differentiated cells at Day 12 (≥200 cell counts), Scale bar:20 µm and its (L) quantification. All experiments were done in triplicates independently (n = 3) and data is presented as Mean ± S.D. Statistical significance was determined by using two tailed student’s t-test. Source data is provided in the Source file.

Fig. 7. Genome editing in HBG1/2 promoter region rescues disease phenotype.

Genome editing was performed for disrupting the −114 to −118 position of HBG1/2 gene (repressor binding site). A Indel efficiency of HBG1/2 promoter editing in BEL-A SCM (SCM Ed.) and BEL-A BTM (BTM Ed.) cells estimated using Amplicon sequencing. B Enucleation percentage of unedited and HBG1/2promoter edited BEL-A SCM and BEL-A BTM cells (C-D) Estimation of increase in γ-globin gene expression. C Relative HBG1/2 gene expression of unedited and HBG1/2 promoter edited BEL-A SCM and BEL-A BTM cells. D Flow cytometry-based quantification of F-cell population of unedited and HBG1/2 promoter edited BEL-A SCM and BEL-A BTM cells. E RP-HPLC of globin chains. Data is presented as the abundance of γ globin by the abundance of total β-like goblins (β + γ + δ). F–K Determination of rescue in disease phenotype and/or physiology at day 10 of differentiation. F Percentage of ROS in unedited and HBG1/2 promoter edited BEL-A SCM and BEL-A BTM cells. G Flow-cytometric analysis of β-like globin divided by α-globin in unedited and HBG1/2 promoter edited BEL-A BTM differentiated cells. H, I RP-HPLC plotted as β-like globins (β + γ + δ) divided by α-globin in (H) BEL-A BTM unedited and HBG1/2promoter edited differentiated cells. I BEL-A SCM unedited and HBG1/2 promoter edited differentiated cells. J Representative microscopic images of sickling in BEL-A SCM unedited and edited differentiated cells at Day 12 (≥200 cell counts), Scale bar: 20 µm and its (K) quantification. All experiments were done in triplicates independently (n = 3) and data is presented as Mean ± S.D. Statistical significance was determined by using two tailed student’s t-test. Source data is provided in the Source file.