Search

Cell culture plays a crucial role in addressing fundamental research questions, particularly in studying insulin resistance (IR) mechanisms. Multiple in vitro models are utilized for this purpose, but their technical distinctions and relevance to in vivo conditions remain unclear. This study aims to assess the effectiveness of existing in vitro models in inducing IR and their ability to replicate in vivo IR conditions., Background: Insulin resistance (IR) is a cellular condition linked to metabolic disorders. Despite the utility of cell culture in IR research, questions persist regarding the suitability of various models. This study seeks to evaluate these models' efficiency in inducing IR and their ability to mimic in vivo conditions. Insights gained from this research could enhance our understanding of model strengths and limitations, potentially advancing strategies to combat IR and related disorders., Objective: 1- Investigate the technical differences between existing cell culture models used to study molecular mediators of insulin resistance (IR). 2- Compare the effectiveness of present in vitro models in inducing insulin resistance (IR). 3- Assess the relevance of the existing cell culture models in simulating the in vivo conditions and environment that provoke the induction of insulin resistance (IR)., Methods and Material: In vitro, eight sets of 3T3-L1 cells were cultured until they reached 90% confluence. Subsequently, adipogenic differentiation was induced using a differentiation cocktail (media). These cells were then divided into four groups, with four subjected to normal conditions and the other four to hypoxic conditions. Throughout the differentiation process, each cell group was exposed to specific factors known to induce insulin resistance (IR). These factors included 2.5nM tumor necrosis factor-alpha (TNFα), 20 ng/ml interleukin-6 (IL-6), 10 micromole 4-hydroxynonenal (4HNE), and high insulin (HI) at a concentration of 100nM. To assess cell proliferation, DAPI staining was employed, and the expression of genes associated with various metabolic pathways affected by insulin resistance was investigated using Real-Time PCR. Additionally, insulin signaling was examined using the Bio-plex Pro cell signaling Akt panel., Results: We induced insulin resistance in 3T3-L1 cells using IL-6, TNFα, 4HNE, and high insulin in both hypoxic and normoxic conditions. Hypoxia increased HIF1a gene expression by approximately 30% (P<0.01). TNFα reduced cell proliferation by 10-20%, and chronic TNFα treatment significantly decreased mature adipocytes due to its cytotoxicity. We assessed the impact of insulin resistance (IR) on metabolic pathways, focusing on genes linked to branched-chain amino acid metabolism, detoxification, and chemotaxis. Notably, ALDH6A1 and MCCC1 genes, related to amino acid metabolism, were significantly affected under hypoxic conditions. TNFα treatment notably influenced MCP-1 and MCP-2 genes linked to chemotaxis, with remarkable increases in MCP-1 levels and MCP-2 expression primarily under hypoxia. Detoxification-related genes showed minimal impact, except for a significant increase in MAOA expression under acute hypoxic conditions with TNFα treatment. Additional genes displayed varying effects, warranting further investigation. To investigate insulin signaling's influence in vitro by IRinducing factors, we assessed phospho-protein levels. Our results reveal a significant p-Akt induction with chronic high insulin (10%) and acute TNFα (12%) treatment under hypoxia (both P<0.05). Other insulin resistance-related phospho-proteins (GSK3B, mTOR, PTEN) increased with IL-6, 4HNE, TNFα, and high insulin under hypoxia, while p-IRS1 levels remained unaffected., Conclusion: In summary, different in vitro models using inflammatory, oxidative stress, and high insulin conditions under hypoxic conditions can capture various aspects of in vivo adipose tissue insulin resistance (IR). Among these models, acute TNFα treatment may offer the most robust approach for inducing IR in 3T3-L1 cells., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.)