Integrated experimental-computational analysis of a HepaRG liver-islet microphysiological system for human-centric diabetes research
Integrated experimental-computational analysis of a HepaRG liver-islet microphysiological system for human-centric diabetes research
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用于以人为中心的糖尿病研究的 HepaRG 肝胰岛微生理系统的综合实验计算分析
DOI：
10.1101/2021.08.18.456693
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发表时间：
2021
影响因子：
4.3
通讯作者：
G. Cedersund
中科院分区：
文献类型：
--
作者：
Belén Casas;L. Vilén;S. Bauer;Kajsa P. Kanebratt;Charlotte Wennberg Huldt;Lisa U. Magnusson;U. Marx;T. Andersson;P. Gennemark;G. Cedersund
微生理系统 (MPS) 是在体外模拟人体生理学和复制疾病进展的强大工具。与目前的动物模型相比，MPS 可以更好地预测人类结果，但实验结果的机械解释和体内外推仍然是重大挑战。在这里，我们使用集成的实验计算方法来解决这些挑战。这种方法允许在先前报道的 MPS 中进行葡萄糖代谢的计算机表示和预测，其中两个器官区室（肝脏和胰腺）与循环介质连接成闭环。我们开发了一个计算模型，描述 MPS 培养 15 天期间的葡萄糖代谢。该模型使用七个实验的数据在具体实验的基础上进行校准，其中单肝脏或肝岛培养物暴露于正常和高血糖条件下，类似于糖尿病中的高血糖水平。校准模型再现了 MPS 实验中观察到的葡萄糖和胰岛素的快速（即每小时）变化，以及葡萄糖耐量和胰岛素分泌的长期（即数周内）下降。我们还通过在计算机中模拟低血糖条件来研究系统在低血糖下的行为，并且该模型可以正确预测新 MPS 实验中测量的葡萄糖和胰岛素反应。最后，我们使用计算模型将实验结果转化为人类，结果与已发表的健康受试者对膳食的葡萄糖反应数据非常吻合。集成的实验计算框架为未来研究疾病机制和开发代谢紊乱新疗法开辟了新途径。
Microphysiological systems (MPS) are powerful tools for emulating human physiology and replicating disease progression in vitro. MPS could be better predictors of human outcome than current animal models, but mechanistic interpretation and in vivo extrapolation of the experimental results remain significant challenges. Here, we address these challenges using an integrated experimental-computational approach. This approach allows for in silico representation and predictions of glucose metabolism in a previously reported MPS with two organ compartments (liver and pancreas) connected in a closed loop with circulating medium. We developed a computational model describing glucose metabolism over 15 days of culture in the MPS. The model was calibrated on an experiment-specific basis using data from seven experiments, where single-liver or liver-islet cultures were exposed to both normal and hyperglycemic conditions resembling high blood glucose levels in diabetes. The calibrated models reproduced the fast (i.e. hourly) variations in glucose and insulin observed in the MPS experiments, as well as the long-term (i.e. over weeks) decline in both glucose tolerance and insulin secretion. We also investigated the behavior of the system under hypoglycemia by simulating this condition in silico, and the model could correctly predict the glucose and insulin responses measured in new MPS experiments. Last, we used the computational model to translate the experimental results to humans, showing good agreement with published data of the glucose response to a meal in healthy subjects. The integrated experimental-computational framework opens new avenues for future investigations toward disease mechanisms and the development of new therapies for metabolic disorders.
影响因子：
15.9
作者：
BERGMAN, RN;PHILLIPS, LS;COBELLI, C
通讯作者：
COBELLI, C
影响因子：
4.8
作者：
Hügl, SR;White, MF;Rhodes, CJ
通讯作者：
Rhodes, CJ