Journal: Molecular therapy. Methods & clinical development
Article Title: Vector Copy Distribution at a Single-Cell Level Enhances Analytical Characterization of Gene-Modified Cell Therapies.
doi: 10.1016/j.omtm.2020.04.016
Figure Lengend Snippet: Figure 3. Single-Cell Vector Copy Number Assay on Two Cell Samples (A) Diagram of the scVCN workflow. The steps in the light blue box are performed within the closed Fluidigm C1 system. ddPCR analysis is performed on each single-cell preamplified material on the QX200 Bio-Rad system. (B and C) Single-cell VCN values from each duplex assay combination are shown for the low (B) or the high (C) pVCN samples, whereas the values from bulk gDNA analysis (gray) include all six combinations and are shown as reference. Combinations originating from RG1 are in light blue, whereas the combinations with RG2 are in dark blue. Each boxplot is represented with mean and standard deviation. (D and E) The mean of the six scVCN combinations is shown for each single cell in the low (D) and high (E) pVCN samples and represented with standard error and 95% confidence interval. Single cells are ordered by increasing mean values. (F and G) Proportion of single cells with predicted vector copy units determined by Bayesian analysis in the low (F) and high (G) pVCN samples. The percentage of single cells with five or more vector copies is grouped. pVCN from bulk population analysis is indicated at the bottom with the standard deviation, alongside the mean of the single-cell VCN predictions. See also Figure S3.
Article Snippet: A custom-made thermal protocol was designed with the C1 Script Builder (Fluidigm) to perform cell capturing, staining, and processing.
Techniques: Plasmid Preparation, Standard Deviation