Effect of Mitochondrial Transplantation on Reference Gene Stabilization in Healthy FHC Cells
Abstract
Objectives: RT-qPCR is frequently used to determine gene expression levels. Expression levels are calculated relative to consistently expressed reference genes. Although Gapdh and Actb are commonly used reference genes in mitochondrial transplantation (MTx) studies, no comprehensive research on gene selection has been found.
Materials and Methods: Healthy Fetal Human Colon (FHC) cells were used for MTx and mitochondrial isolation. Quality control was performed by measuring protein, ATP, membrane potential, and ROS levels in isolated mitochondria. Gapdh, Actb, Sod, and Cat levels were measured after MTx to evaluate and validate gene stability. The CV and ΔCq methods were used in stability analyses, along with the BestKeeper tool.
Results: Isolated mitochondrial protein, ATP, MMP, and ROS levels were measured as 52.23 μg/mL, 533.58 nmol, 92%, and ROS 2%, respectively. In CV calculations, Gapdh was found to be more consistent than Actb (2.15% versus 2.72%). The ΔCq method showed Actb to be slightly more stable (0.45 versus 0.46). The Bestkeeper found that the variation was lower for Gapdh (1.86% vs. 2.20%), but Actb was more consistent with the Bestkeeper index (0.982 vs. 0.971). Calculating the expression levels of Sod and Cat for different genes led to statistically significant changes.
Conclusion: According to the results, both genes are stable. However, Gapdh shows less variability, while Actb is more correlated with the BestKeeper index. GAPDH is a proper choice due to its low variation, but a combination of genes may provide more reliable normalization. The research findings indicate that the choice of reference gene can affect the results and that the stability of the reference gene must be checked to obtain reliable results.
Keywords
mitochondrial transplantation, reference gene, gene stabilization
References
- Curis E, Nepost C, Grillault Laroche D, Courtin C, Laplanche J-L, Etain B, et al. Selecting reference genes in RT-qPCR based on equivalence tests: a network based approach. Sci Rep. 2019;9(1):16231.
- Joshi CJ, Ke W, Drangowska-Way A, O'Rourke EJ, Lewis NE. What are housekeeping genes? PLoS Comput Biol. 2022;18(7):e1010295.
- Chen C, Wu J, Hua Q, Tel-Zur N, Xie F, Zhang Z, et al. Identification of reliable reference genes for quantitative real-time PCR normalization in pitaya. Plant Methods. 2019;15(1):70.
- Davies KA, Welch SR, Sorvillo TE, Coleman-McCray JD, Martin ML, Brignone JM, et al. Optimal reference genes for RNA tissue analysis in small animal models of hemorrhagic fever viruses. Sci Rep. 2023;13(1):19384.
- van de Moosdijk AAA, van Amerongen R. Identification of reliable reference genes for qRT-PCR studies of the developing mouse mammary gland. Sci Rep. 2016;6(1):35595.
- Sumbria D, Berber E, Mathayan M, Rouse BT. Virus infections and host metabolism—can we manage the interactions? Front Immunol. 2021;11:594963.
- Silver N, Best S, Jiang J, Thein SL. Selection of housekeeping genes for gene expression studies in human reticulocytes using real-time PCR. BMC Mol Biol. 2006;7(1):33.
- Boda E, Pini A, Hoxha E, Parolisi R, Tempia F. Selection of Reference Genes for Quantitative Real-time RT-PCR Studies in Mouse Brain. J Mol Neurosci. 2009;37(3):238-53.
- Vandesompele J, De Preter K, Pattyn F, Poppe B, Van Roy N, De Paepe A, et al. Accurate normalization of real-time quantitative RT-PCR data by geometric averaging of multiple internal control genes. Genome Biol. 2002;3:1-12.
- Andersen CL, Jensen JL, Ørntoft TF. Normalization of Real-Time Quantitative Reverse Transcription-PCR Data: A Model-Based Variance Estimation Approach to Identify Genes Suited for Normalization, Applied to Bladder and Colon Cancer Data Sets. Cancer Res. 2004;64(15):5245-50.