Overcoming the Hard-to-Transfect Cell Line Hurdle

CellEDIT: Overcoming the hard-to-transfect cell line hurdle. Overall, these hurdles hamper the generation of diseaserelevant cellular models using CRISPR/Cas-mediated genome engineering and therefore slow the progress of biomedical research. SK-MES-1 (CVCL_0630) cells are an example of a notoriously hard-to-transfect cell line that is derived from a patient with lung squamous cell carcinoma. The cell line is frequently used in cancer research and drug discovery. In addition to low transfection efficiencies, they are characterized by an unstable karyotype [1], low clonogenicity and a slow proliferation rate (~50h cell cycle). HPRT1 is a well-expressed gene, that is often used to normalize expression levels. The encoded enzyme plays a central role in the generation of purine nucleotides. Further, it has been shown to provide resistance to 6-thioguanine toxicity in cancer cells [2] and is therefore of interest in cancer research. Figure 1. The CellEDIT onboarding and optimization workflow: 1. Onboarding and characterization: Cells are thawed, expanded, tested for microbiological contaminations, and characterized. Then, a variety of single cell seeding, and outgrowth conditions are systematically tested. 2. Optimization of injection parameters: Injection parameters are optimized using the Arya software that controls the actions of the FluidFM OMNIUM platform. For each cell type, the optimal approach speed, the injection force, the injection time, and pressure are determined.Subject to change without notice. Version 1.0 | Copyright 2023 Cytosurge AG, Switzerland Application Note: CellEDIT: Overcoming the hard-to-transfect cell line hurdle. 2 Here, we present the CellEDIT workflow. A unique workflow that not only offers a gentle and controlled delivery method, but also circumvents the singulation challenges by starting the process with single cells. To demonstrate the power of CellEDIT we successfully generated HPRT1 SK-MES1 knockout cell lines. Methodology gRNA Design and RNP Preparation The gRNA targeting exon 4 of HPRT1 was designed using the IDT gRNA design tool. The characteristics of the gRNA are summarized in Table 1. Clonal Expansion and Analysis The expansion of every single cell into a colony was documented by a SPARK Multimode Reader (Tecan). Once cells reached colony sizes of more than 1000 cells, they were harvested for analysis. The targeted locus on the HPRT1 gene was amplified by PCR from the cell lysates. The samples were sequenced by Sanger sequencing (www.microsynth.com). The genotype was determined by alignment and deconvolution of the sequences using the Benchling Molecular Biology suite and DECODR (decodr. org). Results To tackle the problem of hard-to-transfect cell lines, Cytosurge devised the CellEDIT workflow that distinguished itself from traditional approaches in three major aspects: 1. Sophisticated onboarding process to optimize single cell transfection and outgrowth. 2. Transfection of singulated cells 3. Gentle intranuclear delivery using the FluidFM™ OMNIUM platform. Onboarding and Optimization Process During the onboarding phase (Figure 1, Step 1), cells were expanded for several passages to allow them to recover from cryopreservation, transport, and adaptation to the local cell culture facility. In addition, cells were tested routinely for mycoplasma and other microbial contamination. After the initial adaptation, the parameters for successful singulation and single cell outgrowth were determined. This comprises, but is not limited to, testing a variety of culture conditions and substrates (Figure 1, Step 1). The last and most crucial step is the optimization of the transfection parameters to ensure high viability and robustness of delivery of the RNPs to the nucleus of individual cells. In contrast to traditional transfection methods, delivery of RNPs is mediated by force sensitive, micro-channeled FluidFM Nanosyringe. A single cell was selected in the user interface of the Arya software and the injection parameters such as force, approach speed, pressure and injection time specified (Figure 1, step 2). The FluidFM Nanosyringe gently penetrates the cell membrane and the nuclear envelope and injects the solution (Figure 1, step 2). Plotting the force curve in relation to time and the distance of the FluidFM Nanosyringe from the cell allows determining the gentlest parameters to insure cell survival (Figure 1, step 2). To monitor the delivery of the cargo visually, the RNPs were labelled with a fluorescent tracer. Subsequently, cell survival was monitored over a period of 1-3 days. This process was repeated systematically for more than 200 individual cells, varying the parameters until the best tradeoff between delivery efficiency and cell survival was determined. Both the tracrRNA and crRNA were purchased from IDT (eu.idtdna.com) and annealed according to the supplier’s instructions. Of note, the tracrRNA was chemically modified by addition of Atto550, a fluorescent dye. Ribonucleoprotein complexes (RNPs) were assembled by incubation of Cas9 proteins and gRNAs at room temperature for 10 min in IDTE buffer. The final injection mix consisted of 0.366µM Cas9 and 0.5µM gRNA. Cell Culture and Singulation The SK-MES-1 cells were propagated according to the suppliers’ instructions. SK-MES-1 single cells were seeded to the center of an individual well of a 12-well plate. Once cells were attached to the substrate (12h), whole well scanning was performed using a SPARK Multimode Reader (Tecan) to document monoclonality. Single Cell Injection of RNPs Single cell injection was performed using the FluidFM™ OMNIUM platform. The underlying technology is a combination of microfluidics and force-feedback, and enables force-controlled injection of RNPs into cells with minimal impact on cell viability. An average volume of 100 femtoliters of injection mix was delivered directly into the nuclear compartment, resulting in the uptake of around 22’000 RNP complexes per nucleus. The injection success was validated by fluorescence imaging of the Atto550 dye incorporated in the tracRNA. Table 1. Summary of gRNA characteristics. On an off-target score above 50 are considered as suitable for genome engineering experiments. Subject to change without notice. Version 1.0 | Copyright 2023 Cytosurge AG, Switzerland Application Note: CellEDIT: Overcoming the hard-to-transfect cell line hurdle. 3 Singulation and Injection 34 SK-MES1 cells were plated in individual wells of 12- well plates and, once they adhered and were well spread, injected with RNPs. Microphotographs of cells were taken to document cell survival and injection success (Figure 2). A total of 22 cells showed an Atto550-positive signal, whereas 10 showed no detectable Atto550 fluorescence. Expansion & Analysis Cells were subsequently expanded using the conditions determined during the onboarding pages. The outgrowth of each colony was documented every 3 to 5 days by scanning each well (Figure 3). Of 34 injected cells, 22 formed viable cell lines resulting in a survival rate of 65% (Figure 4A). The 22 viable cell lines were sent for genotype analysis (Figure 4B), which revealed that 12 clones (55%) had editing on at least one allele and 6 (23%) had editing on all alleles that were identified (23%). Further sequence analysis and deconvolution showed that: • 7 clones (32%) were heterozygous (both edited and wild type alleles present). • 5 clones were edited on all alleles detected, of which 3 clones (14%) were compound heterozygous (all alleles edited with distinct sequences) and 2 clones (9%) showed a homozygous genotype (identical edit on all alleles). Editing consequences for all clones were determined by visual inspection and deconvolution of Sanger trace files. In Figure 5, the analysis of the genome editing outcomes of two representative clones are shown. In a first step, the Sanger trace files were aligned to the genomic sequence and editing identified either by obvious gaps in the alignment or distorted signal adjacent to the gRNA site (data not shown). Clones with evidence of editing were further characterized by sequence deconvolutionusing DECODR. Figure 2. Injection of SK-MES1 single cells using FluidFM™. A: A single SK-MES1 cell prior to