Integrated experimental-computational analysis of a HepaRG liver-islet microphysiological system for human-centric diabetes research

PLoS Comput Biol. 2022 Oct 19;18(10):e1010587. doi: 10.1371/journal.pcbi.1010587. eCollection 2022 Oct.

Abstract

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 HepaRG 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 behaviour 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.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animals
  • Blood Glucose / metabolism
  • Diabetes Mellitus* / metabolism
  • Glucose / metabolism
  • Humans
  • Insulin Secretion
  • Insulin* / metabolism
  • Liver / metabolism

Substances

  • Insulin
  • Glucose
  • Blood Glucose

Grants and funding

The authors acknowledge funding from the Swedish Research Council [https://www.vr.se/], grant numbers: 2018-05418 and 2018-03319 (GC), CENIIT [http://ceniit.lith.liu.se//], grant number: 15.09 (GC), the Swedish Foundation for Strategic Research [https://strategiska.se/en/], grant number: ITM17-0245 (GC), the SciLifeLab/KAW [https://www.scilifelab.se/] National COVID-19 Research Program, financed by the Knut and Alice Wallenberg Foundation, grant number: 2020.0182 (GC), and the H2020 project PRECISE4Q [https://precise4q.eu/], grant number: 777107 (GC). Additional support for GC came from The Swedish Fund for Research without Animal Experiments [https://forskautandjurforsok.se/], grant number: F2019-0010, and ELLIIT [https://elliit.se/], grant number: 2020-A12. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.