Transfection Optimization
A transfection optimization experiment is a systematic approach to improve the efficiency of introducing foreign DNA into cells. By testing different concentrations of DNA and reagents, the optimal conditions for maximum transfection efficiency can be identified. Low transfection efficiency can hinder the success of experiments, leading to inconclusive results and wasted resources. By optimizing the transfection process, it ensures a higher proportion of cells receive genetic material. To test whether the quantities or ratios of DNA or Lipofectamine 2000 need adjustment, or if reagents need replacement, 25 separate wells of a 96-well plate were rested with different volumes and ratios on HEPG2 cells in a grid. To verify efficiency of the transfection, the same grid was set up using C2C12 cells on the other side of the plate with the same pattern and ratios. The HEPG2 and C2C12 cells were transfected with increasing amounts of GFP DNA: 0.5uL, 0.9uL, 1.8uL, 3.6uL, 7.2uL. The HEPG2 and C2C12 cells were also transfected with increasing amounts of Lipofectamine 2000: 0.5uL, 1.0uL, 2.0uL, 3.0uL.
Figure 1. Transfection Optimization of HEPG2 Cells
Figure 2. Transfection Optimization of C2C12 Cells
The results showed that the transfection was overall successful for both the HEPG2 and C2C12 cells. The optimal ratio of DNA to Lipofectamine was found to be 1.8uL to 1.0uL for HEPG2 cells.
Dual Luciferase Assay
The purpose of this assay is to test whether the V2 circuit detects cholesterol. The luciferase is a reporter gene that determines if the promoter is on or off. The luciferase gene is located inside the circuit, so when the substrate is added to the cells, it creates a reaction. This reaction produces luminescence, which is measured. The luminescence begins to decay after 12 minutes, so it is important to get luminescence readings before then. Low transfection efficiency will affect the results of the assay, so it is important to have multiple control wells to determine what or if anything went wrong in the assay. The ratio of the firefly to Renilla luminescence is compared between the control and transfected wells to determine if the V2 circuit and the assay are successful. Values of luminescence for firefly of the transfected cells should expect to be >10,000.
Figure 3. Dual Luciferase Assay of Vector V2 at Low, Standard, and High CHolesterol Conditions
The dual luciferase assay in Figure 3 did not provide significant results. However, it did allow us to characterize the SRE promoter as sensitive to cholesterol. These preliminary results show that the promoter is active at low cholesterol levels and inactive at high cholesterol levels.
Figure 4. Dual Luciferase Assay of Vector V2
The firefly and renilla genes in the V2 vector were shown to be functioning.
Figure 5. Dual Luciferase Assay of Putative Stable Cells Lines
Three putative stable cell lines were transfected with V2 vector DNA and then assayed. Cell lines exhibited signals from the renilla luciferase but not the firefly luciferase. This would imply that the V2 vector was only partially transfected into the cells such that the constitutive promoter was transfected while the pSRE inducible promoter was not. Further screening of cell lines transfected with the V2 vector is required.
qPCR
The goal is to confirm the gene targets that, in cells, may be employed to prevent the formation of cholesterol and serve as the cornerstone for the creation of the V3 gene circuit. There are 17 enzymes that work together to catalyze the cholesterol production pathway in liver cells. We select the enzymes squalene monooxygenase (SQLE) and farnesyl-diphosphate farnesyltransferase 1 (FDFT1) based on previous research. In order to determine which of these genes are potential targets for the inhibitory mechanism of the gene and to assess the gene expression of these two enzymes, it was necessary to analyze the levels of expression of the genes encoding FDFT1 and SQLE in wild-type HEPG2 cells.
Figure 6. SQLE Average ΔCq Values
Figure 7. FDFT1 Average ΔCq Values
* indicates significance with a p-value < 0.05
Lower ΔCq values indicate higher gene expression, with GAPDH serving as a control gene. Negative ΔCq values represent reduced gene expression. The results showed that SQLE siRNA successfully reduced SQLE gene expression, as its ΔCq values were significantly lower than controls. However, FDFT1 siRNA did not effectively reduce FDFT1 gene expression, as its ΔCq values were less negative than controls. This suggests that the siRNA, not the delivery method (RNAiMAX Lipofectamine), caused the gene inhibition. Future research will involve integrating the SQLE siRNA mechanism into a V3 circuit to regulate cholesterol synthesis and exploring additional siRNAs for FDFT1 or other cholesterol synthesis genes for potential inclusion in the V3 circuit.