Speaker
Description
Organoids - 3D multicellular structures cultivated in vitro from self-aggregating stem cells - revolutionize preclinical research as an alternative to animal experimentation. But the design of in silico organoids is lagging behind, preventing modelling predictive control to optimize their characterization and production. The few numerical models developed mostly focus on tumoroids and do not leverage multi-omic data available nowadays.
Here, we present a first digital twin of a non-cancerous organoid: a numerical pipeline parametrized using omics data, simulating organoid growth dynamic. We propose a multi-scale approach combining Boolean Networks to model intra-cellular gene regulatory networks inserted into an Agent-Based Model (\cite{p}) simulating cell-cell communication and micro-environment interactions. Each cell type identified from single-cell RNA-seq data is associated with its own Boolean model guiding cell agent evolution rules in the Agent-Based Model. The position of each cell and its interaction with the micro-environment regulate growth factors reaching the cell gene regulatory network, modifying the BN. Transition probabilities model cell differentiation trajectories upon multiple divisions. We apply our pipeline to gastruloids (\cite{a}), organoids mimicking embryonic gastrulation,to identify optimal culture conditions ensuring differentiation toward the cardio-pharyngeal complex, which gives rise to the heart and pharyngeal muscles.
Bibliography
@article{a,
title={Gastruloids are competent to specify both cardiac and skeletal muscle lineages},
author={Argiro, Laurent and Chevalier, C{\'e}line and Choquet, Caroline and Nandkishore, Nitya and Ghata, Adeline and Baudot, Ana{\"\i}s and Zaffran, St{\'e}phane and Lescroart, Fabienne},
journal={Nature Communications},
volume={15},
number={1},
pages={10172},
year={2024},
publisher={Nature Publishing Group UK London}
}
@article{p,
title={PhysiBoSS 2.0: a sustainable integration of stochastic Boolean and agent-based modelling frameworks},
author={Ponce-de-Leon, Miguel and Montagud, Arnau and No{\"e}l, Vincent and Meert, Annika and Pradas, Gerard and Barillot, Emmanuel and Calzone, Laurence and Valencia, Alfonso},
journal={npj Systems Biology and Applications},
volume={9},
number={1},
pages={54},
year={2023},
publisher={Nature Publishing Group UK London}
}
