SFEBES2018 Poster Presentations Obesity & metabolism (24 abstracts)
Background: Delivery of nutrient excess in obesity can disrupt protein folding in the endoplasmic reticulum (ER) within adipose tissue; this activates the unfolded protein response (UPR) and contributes to type 2 diabetes mellitus (T2DM) risk. Thus, the aims of this study were to utilise freeze-dried broccoli extract (BE) as a nutrient to mitigate such cellular damage in human adipocytes, understand the relevance of associated pathways, and create a mathematical model of the UPR to understand pathway dynamics.
Methods: Differentiated human adipocytes (Chub-S7; n=6) were treated with BE (hybrid Brassica oleracea var. italic; 10 ng/ml) alone or combined with tunicamycin (Tun; 750 ng/ml), an inducer of ER stress. UPR proteins (BiP, PERK, P-PERK, eIF2α, P-eIF2α) were measured at 18 time points (0 hr72 hr) using Western Blot; transcriptomics was utilised to gain insight of pathway changes at the most affected time point. Mass action kinetics was used to create ordinary differential Default (ODEs) to model the UPR over time for predictive analysis.
Results: Tun increased UPR proteins 9.5 fold (P<0.05), whilst BE+Tun reduced ER stress proteins by up to 94%, back to control levels in many instances (P<0.05). Transcriptomic analysis highlighted positive significant changes in the mevalonate pathway with use of BE in treated adipocytes (P<0,05), whilst time series data identified oscillatory behaviour of UPR proteins involved in translation attenuation. Finally, modelling pathway dynamics with more time point granularity improved the error between model output and experimental data by 23%, yielding a new enhanced qualitative model.
Conclusion: These studies highlight that BE acts to alleviate ER stress in human adipocytes by reducing the UPR through the mevalonate pathway. Furthermore, modelling pathway dynamics using experimental data for parameterisation may provide insight into predicting nutrient capabilities to reduce obesity mediated T2DM risk.
19 Nov 2018 - 21 Nov 2018