Introduction to Transfections

Efficient transfection is critical for achieving reliable gene delivery, consistent expression and reproducible experimental outcomes across a wide range of cell types and applications. Selecting the appropriate transfection reagent and optimizing experimental conditions can significantly influence transfection efficiency, cell viability and downstream data quality.

Common types of genetic material used in transfection include plasmid DNA, small interfering RNA (siRNA) and mRNA for delivering genomic payloads to cells. These nucleic acids can be used to knock in a gene or silence a gene of interest within cells for use in downstream applications or studies.

Many factors must be considered when transfecting cells, including:

• The target cell type
• Selection of the promoter for the cell type
• Media conditions
• Cell status within the cell cycle, general health, and confluence
• Transfection mechanisms
• The need for stable or transient expression of the target gene
• Selection of vectors, i.e., plasmid DNA or RNA

Liposomal-Based Transfections: Lipofection

Transfections using liposomal-based reagents such as Lipofectamine 3000 enable the formation of cationic lipid aggregations on the surface of the phospholipid membrane of cells. This results in the entry of the lipid complexes carrying either DNA or RNA payloads via endocytosis into the target cells.¹

Following transfection, outcomes may include either stable or transient gene expression. Stable transfections occur when a plasmid DNA sequence integrates into the host genome or is expressed in an episomal manner. Transient expression systems can also be created with either DNA or RNA vectors and express the gene or protein of interest for a limited period. The use of DNA for transient expression is generally reported to be less efficacious than RNA for protein expression. When using RNA-based vectors, developers see a rapid onset of translation of target proteins, since the RNA does not need to penetrate the nuclear membrane for transcription before translation.^{2, 3}

Stable cell line production can be achieved by using a negative selection process, with a plasmid containing a resistance gene to a given antibiotic. Developers can use these selection systems by conducting kill curves with their target cell line using common antibiotics like puromycin and G418 to determine the lowest concentration required to kill the cells. These concentrations can then be used to select stably expressing cells and maintain high percentages of expressing cells throughout the culture. Developers can also use vectors that express fluorescent signals, such as green fluorescent protein (GFP), to confirm expression of the target gene or protein.¹

Methods of Evaluating Transfection Efficiency

Various methods to evaluate transfection efficiency exist, and suitability depends on the experimental context. Developers who use a vector containing a marker like GFP can use fluorescence microscopy or flow cytometry to measure expression of the target gene and determine transfection efficiency by dividing the number of expressing cells by the total number of cells.

Additional methods such as real-time PCR (RT-PCR) can measure the expression of the target sequence or inhibiting sequence, while techniques such as Western blots or immunofluorescence (IF) labeling measure direct protein production of the target protein.

Each method requires consideration. RT-PCR’s measurement of nucleic acids may be quantitative, but the expression of the protein is not being measured and could lead to a false positive. Protein-based assays like Western blots and IF can result in false negatives if non-specific antibodies are used, or if the wrong time points are collected after transfection.¹

Optimization & Considerations for Addressing Low Transfection Efficiency

Addressing low transfection efficiency requires consideration of multiple variables. These considerations range from plasmid sequence integrity and selecting the optimal eukaryotic promoter for the cell type, along with the addition of start and stop codons. Developers can also test the delivery of linear versus supercoiled plasmid or consider RNA vectors if a stable expression is not required.

Studies have shown that supercoiled plasmids are efficiently trafficked into the cells but exhibits reduced efficiency in recombining to integrate, while linear plasmids display the opposite characteristics after transfection.^{4, 5}

Another option for difficult-to-transfect cells is to use new DNA vectors, such as those with reduced backbones, like mini-circles, synthetic DNA or a Nanoplasmid. These reduced backbones result in improved transgene expression and, in many cases, reduced post-transfection toxicity.⁶

Optimization of the DNA-to-reagent ratios is also an avenue that developers can investigate. Chemical transfection reagents at higher dosages can produce cytotoxic effects, thereby impacting transfection efficiency. Along with reagent-DNA/RNA ratios, the media components used and the mixing of the reagent/DNA or RNA complexes can be negatively affected if, for example, bubbles are introduced into the mixture.¹

Primary mammalian cells and stem cells are often more challenging to transfect than immortalized cell lines. However, with proper optimization and different transfection approaches, edits or expressions can be achieved.¹

How Can Automated Liquid Handlers Help with Transfection Optimization?

Like all design of experiment approaches, optimizing transfection requires a significant amount of focused and specialized effort, particularly when accounting for biological and technical replicates. The tight timing involved in these protocols often prevents skilled personnel from engaging in other high-value tasks within the laboratory. Automating the workflow can substantially reduce hands-on time and minimize fatigue-related errors, while also freeing users to focus on more strategic activities.

Since reproducibility is essential in these optimizations, automation improves reliability in liquid handling and ensures precise control over timing between transfers. The ability of automated systems to deliver accurate and repeatable pipetting also helps reduce user-to-user variability across and between experiments, giving users greater confidence in the data produced for optimization. This results in improved experimental conditions from reduced variation stemming from traditional manual laboratory work.

Scientists can benefit from the introduction of automation through:

• Identifying kill curves for optimal antibiotic concentrations for selection
• Optimizing Lipofectamine 3000 and DNA/RNA ratios
• Refining media conditions and incubation times
• Comparing various plasmid DNA vectors or formats (e.g., linear vs. supercoiled)
• Evaluating different promoters used with DNA vectors for target cells
• Scaling multiple plates for the selection of successfully transfected cells

Automation can be utilized both upstream and downstream of the transfection process to support the entire workflow, allowing users to gain more control over their experimental conditions. By streamlining the steps involved in optimizing transfection conditions, automation helps reduce human error, save time, and increase experimental throughput—ultimately leading to improved productivity and faster answers to scientific questions.

Expand Your Understanding

  

Application note
Automated Cell Handling and Lipofection-Based Transient Transfection Design of Experiments (DOE) Using the Biomek i3 Benchtop Liquid Handler

 

  

Poster
Flexibility of the Biomek i3 Benchtop Liquid Handler Across Multiple Modalities: Evaluation of Genomic DNA Extraction and Transient Transfection Workflows

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References

1. Chong ZX, Yeap SK, Ho WY. Transfection types, methods and strategies: a technical review. PeerJ 2021;9:e11165. https://doi.org/10.7717/PEERJ.11165/SUPP-1.
2. Oh S, Kessler JA. Design, assembly, production and transfection of synthetic modified mRNA. Methods 2018;133:29–43. https://doi.org/10.1016/J.YMETH.2017.10.008.
3. Ylösmäki L, Polini B, Carpi S, et al. Harnessing therapeutic viruses as a delivery vehicle for RNA-based therapy. PLoS One 2019;14:e0224072. https://doi.org/10.1371/JOURNAL.PONE.0224072.
4. Hardee CL, Arévalo-Soliz LM, Hornstein BD, et al. Advances in non-viral DNA vectors for gene therapy. Genes 2017;8:65. https://doi.org/10.3390/GENES8020065.
5. Von Groll A, Levin Y, Barbosa MC, et al. Low-efficiency linear DNA transfection by liposome can be improved by the use of cationic lipid as a charge neutralizer. Biotechnol Prog 2006;22:1220–1224. https://doi.org/10.1021/BP060029S.
6. Williams JA, Paez PA. Improving cell and gene therapy safety and performance using next-generation Nanoplasmid vectors. Mol Ther Nucleic Acids 2023;32:494. https://doi.org/10.1016/J.OMTN.2023.04.003.

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