We are transfecting in viral RNAs (SARS2 Spike NC and ORF10) to test for TLR7 stimulation and downstream interferon production in primary human lung endothelial cells. We want to have a transfection negative control. He wants a human gene.
I am not an expert in this field, but I am very interested and have researched to find an answer. I received some assistance from tlooto.com for this response. Could you please review the response below to see if it is correct?
Yes, HPRT (Hypoxanthine-guanine phosphoribosyltransferase) RNA is a commonly used housekeeping gene and can serve as a transfection control for your experiments. However, GAPDH (Glyceraldehyde 3-phosphate dehydrogenase) and ACTB (Beta-actin) are also well-established housekeeping genes that are often used due to their consistent expression across various conditions [1]. Given your focus on transfecting viral RNAs (SARS2 Spike NC and ORF10) to study TLR7 stimulation and interferon production in primary human lung endothelial cells [2][3], any of these housekeeping RNAs should be suitable for serving as a reliable transfection negative control.
Reference
[1] Souyris, M., Cénac, C., Azar, P., Daviaud, D., Canivet, A., Grunenwald, S., Pienkowski, C., Chaumeil, J., Mejía, J. E., & Guéry, J. (2018). TLR7 escapes X chromosome inactivation in immune cells. Science Immunology, 3.
[2] Berghöfer, B., Frommer, T., Haley, G., Fink, L., Bein, G., & Hackstein, H. (2006). TLR7 ligands induce higher IFN-alpha production in females.. Journal of immunology, 177 4, 2088-96 .
[3] Fan, X., Yang, J., Wu, G., Wang, M., Cheng, X., Liu, C., Liu, Q., Wen, Y., Meng, S., Wang, Z., Lin, X., & An, L. (2022). Optimization of cationic polymer-mediated transfection for RNA interference. Genetics and Molecular Biology, 45.
It is a good idea to check out HPRT, since some of the commonly used housekeeping genes are B2M, YWHAZ, 18SrRNA, GAPDH, GUSB, HMBS, HPRT1, ACTB and GAPDH for mammalian cells.
Some packages that evaluate the stability of reference genes based on variance during the test conditions are geNorm, NormFinder, BestKeeper, and RefFinder to find the best combination of genes that can be used for accurate normalization.