Comparative Evaluation of Computational Methods for Validating Housekeeping Gene RT-qPCR Data in 3T3-L1 Cells

Abstract

Background: Postbiotics with anti-adipogenic properties can significantly modify adipocyte metabolism by influencing key cellular pathways involved in lipid accumulation. In preliminary in vitro studies, it is essential to monitor various cellular and subcellular variables, including gene expression and protein synthesis potential, through RT-qPCR analysis. It is also crucial to select internal controls carefully and evaluate their stability for effective normalization and accurate interpretation of the results. Methods: In this study, we assessed the stability of six commonly used housekeeping genes: GAPDH, Actb, HPRT, HMBS, 18S, and 36B4. We analyzed their variability in mature 3T3-L1 adipocytes treated with supernatants from newly isolated Lacticaseibacillus paracasei strains. Our analysis combined classical statistical methods, a ∆Ct analysis, and software algorithms such as geNorm, NormFinder, BestKeeper, and RefFinder. Results: Our stepwise, multiparameter strategy for selecting reference genes led to the exclusion of Actb and 18S as the most variable reference genes. We identified HPRT as the most stable internal control. Additionally, HPRT and HMBS emerged as a stable pair, while the recommended triplet of genes for reliable normalization consists of HPRT, 36B4, and HMBS. Conclusions: The widely used putative genes in similar studies—GAPDH and Actb—did not confirm their presumed stability, which once again emphasizes the need for experimental validation of internal controls to increase the accuracy and reliability of gene expression. Combining a unique biological model—postbiotic-treated adipocytes—with multiple algorithms integrated into a single workflow allows us to provide a methodological template applicable to similar nutritional and metabolic research settings.