Absolute Quantification of Genomic Targets for Cell Counting

M. Cauble, H-J He, J. Almeida, S. Sarkar
National Institute of Standards and Technology,
United States

Keywords: cell count, digital PCR


Cell counting is an important and common measurement with wide-ranging applications from cell-based assays in research, development, and manufacturing to starting material characterization for tissue engineered products and product release for cell-based therapeutics. There are many methods to measure a cell count however there is no consensus on a reference method for cell count. Imaging and flow-based methods for cell count rely on user-based definitions of cells, debris, and various cell populations. In contrast, obtaining cell count based on the number of genome copies provides a biologically based definition of cells that can easily be transferred from site to site. An additional advantage of this approach is the ability to identify and count cell populations with specified genomic markers. We are implementing droplet digital polymerase chain reaction (droplet dPCR) to count the number of genome copies and then convert this value to a cell count. Droplet dPCR is becoming a more common technique in cell-based product manufacturing and testing, and this approach could allow the critical cell count value to be obtained simultaneously with other droplet dPCR assays. For method development, we are using a set of clonal Jurkat cell lines with defined copy numbers of a reference lentiviral vector expressing green fluorescent protein (GFP) integrated into their genomes. Our droplet dPCR assay targets include the HIV-1 Rev response element (RRE) in the integrated lentiviral provirus DNA, and human ribosomal protein L32 (RPL32) gene in human genome. Key steps for this method include: (1) cell cycle analysis, or the number of genome copies per cell, (2) DNA extraction with quantification, (3) droplet dPCR assays, and (4) calculations to convert the number of genome copies determined by ddPCR to a cell count. The accuracy of this cell count relies on the accuracy of each individual step. Our results suggest that we can obtain cell samples with defined cell cycle populations (G1, S, and G2 phase) using techniques such as G1 cell sorting, cell cycle synchronization, and cell cycle optimization. We are further able to incorporate these results in the calculation of cell count from the number of genome copies determined by droplet dPCR. We have also established a method to quantify DNA recovery during extraction that is independent of assumptions based on cell cycle or starting cell count. We used a mouse DNA control material as a spike-in during various stages of the DNA extraction process. By counting a genomic target with the mouse DNA, we can quantify DNA loss and matrix effects. Our ongoing work includes evaluating different DNA extraction techniques including direct PCR methods, to optimize DNA recovery and reduce uncertainty in genomic target based absolute cell counting.