Improving Gene-Editing Outcomes with Flow Cytometry

The advent of gene editing, particularly CRISPR, has greatly transformed how genomics can be used to answer biological questions. CRISPR has many applications including target validation, functional genomic analysis, and as a therapeutic. Hence, there is a growing need to streamline and enhance existing CRISPR/gene-editing workflows to improve speed and precision.

A typical gene-editing workflow involves selecting a target gene, designing the guide RNAs (gRNA), and transfecting the cells with the CRISPR/Cas9 gRNA complex. After the transfection is complete, the edited cells are isolated and sequenced to ensure that the gene editing has indeed taken place as expected. “One of the main bottlenecks in the CRISPR workflow is culturing hundreds of clones not really knowing whether or not you have a successfully edited cell population until the colonies are big enough to be sent for sequencing,” says Christopher Brampton, Ph.D., Global Product Manager for Flow Cytometry Applications & Reagents, Bio-Rad.

Improving the chances of success

Selecting for clones is typically done by limiting dilution, which is a manual process of plating out cells at very low densities to achieve

Using a cell sorter dramatically improves the chances that a fully viable and edited cell is plated into a well and that the growing cell populations are in fact monoclonal, thereby reducing any waste. “Selecting only those cells that were positively transfected with CRISPR elements combined with the ability of a cell sorter to fill up every well of a multiwell plate can make a drastic difference in the time it takes to get to the part of the workflow where you are screening monoclonal populations for gene editing,” adds Brampton. This is especially true if the cells are very delicate, tricky to culture, or slow growing.

“Flow cytometry can also be used to screen and sort cells prior to gene editing, for a particular cell cycle stage such as S phase in the case of gene editing, or for surface expression of endogenous proteins, or for engineered reporters for elements that enhance the likelihood of gene editing, so that you have a better chance of getting the coveted homology directed repair (HDR) edit,” says Brampton. Adding cell sorting also eliminates the need for antibiotic selection. “This not only helps improve cell viability down the road and reduces off-target effects, but it moves us toward ending the use of antibiotic resistance in cell selection,” explains Brampton. This is especially true in clinical applications where the resistance gene gives rise to concerns associated with the rise in antibiotic resistance and could be classified as a contaminant.

Gaining a better understanding of the cell

“Flow cytometry analysis is a critical tool in gene-editing and cell-engineering experiments as functional cellular analysis is an important component in genome-editing experiments,” says Natasha Jacobsen, Technical Sales Specialist, Flow Cytometry Instruments at Thermo Fisher Scientific. In addition, to understanding the functional impact and phenotypic changes to a gene-edited cell, combining flow cytometry with genetic assays has created a powerful tool for researchers to better understand their cellular system or model.

Mikolaj Slabicki, Ph.D., a postdoctoral research fellow in the laboratory of Dr. Benjamin Ebert at Broad Institute/Dana Farber Cancer Institute, is using flow cytometry for functional genomics applications. He is working with a new class of small molecule drugs called protein degraders, which are being developed to target non-enzyme proteins that were previously regarded as being “undruggable”. “We were able to dissect the components of the drug-induced protein degradation machinery by combining flow sorting with functional genomics,” says Slabicki. “We were interested in that rare population of cells that were resistant to degradation, which we were able to identify by flow sorting and later enriching for sequencing. It allowed us to identify receptors that bind to the degrader molecules and also distal components of the degradation pathway.”

Flow cytometry not only provides information on cellular composition and phenotype but can also provide a detailed analysis of cellular function or activation state, cellular signaling, and the impact of a particular genotype on a system’s physiological phenotype. “In other words, flow cytometry allows you to answer the question of ‘Now you have discovered a genetic point of interest, is it silent?’ or ‘How does it impact of the actual cell or animal system you are studying?,’” says Brampton.

Improving flow cytometry for better outcomes

According to Jacobsen, flow cytometry has now been successfully used in many genetic assays/workflows such as immunophenotyping for cell and gene therapy applications, viability and proliferation assays for edited cell populations, functional protein knock-down and knock-in experiments, fluorescent gene tagging, transfection optimization, optimization of viral delivery, and high-throughput screening assays. “Flow cytometers have become faster, more robust, extremely user-friendly, and easy to maintain and this has made it more accessible to researchers,” she says. “Additionally, advancements in single-cell sorting technology have helped flow cytometry provide rapid multiparameter analysis at a single-cell level. Improvements in automation have also greatly helped these applications.”

Brampton believes that a fundamental change has been the speed and gentleness of the modern cell sorter. “The jet and air sorter technology, for instance, provides high-speed sorting that leaves the cell relatively unscathed by the sorting process. That combined with a high accuracy for single-cell sorting, ensuring only fluorescently labeled edited cells go into the colony plate, gives you the highest probability of a successful outcome.”

Slabicki had considered using alternatives such as, immunoprecipitation followed by mass spectrometry, protein arrays, and different in vitro assays to identify the components binding to the drug or protein of interest and to identify the protein being degraded. However, he ended up using flow cytometry-based CRISPR screens to help identify the various components of the protein degradation pathway. “Flow cytometry offered a lot of flexibility and resolution for such positive selection screens.”

Image: Incorporating the S3e Cell Sorter can shorten gene-editing workflows by about 30 days, according to Bio-Rad.