Pacheco Maria Pires, Ji Jimmy, Prohaska Tessy, García María Moscardó, Sauter Thomas
Department of Life Sciences and Medicine, University of Luxembourg, 4367 Belvaux, Luxembourg.
Luxembourg Centre for Systems Biomedicine, University of Luxembourg, 4367 Belvaux, Luxembourg.
Metabolites. 2022 Dec 2;12(12):1211. doi: 10.3390/metabo12121211.
Tumours are composed of various cancer cell populations with different mutation profiles, phenotypes and metabolism that cause them to react to drugs in diverse manners. Increasing the resolution of metabolic models based on single-cell expression data will provide deeper insight into such metabolic differences and improve the predictive power of the models. scFASTCORMICS is a network contextualization algorithm that builds multi-cell population genome-scale models from single-cell RNAseq data. The models contain a subnetwork for each cell population in a tumour, allowing to capture metabolic variations between these clusters. The subnetworks are connected by a union compartment that permits to simulate metabolite exchanges between cell populations in the microenvironment. scFASTCORMICS uses Pareto optimization to simultaneously maximise the compactness, completeness and specificity of the reconstructed metabolic models. scFASTCORMICS is implemented in MATLAB and requires the installation of the COBRA toolbox, rFASTCORMICS and the IBM CPLEX solver.
肿瘤由具有不同突变谱、表型和代谢的各种癌细胞群体组成，这导致它们以不同方式对药物产生反应。基于单细胞表达数据提高代谢模型的分辨率将更深入地洞察此类代谢差异，并提高模型的预测能力。scFASTCORMICS是一种网络情境化算法，可从单细胞RNA测序数据构建多细胞群体基因组规模模型。这些模型为肿瘤中的每个细胞群体包含一个子网，从而能够捕捉这些簇之间的代谢变化。子网通过一个联合隔室连接，该隔室允许模拟微环境中细胞群体之间的代谢物交换。scFASTCORMICS使用帕累托优化来同时最大化重建代谢模型的紧凑性、完整性和特异性。scFASTCORMICS在MATLAB中实现，需要安装COBRA工具箱、rFASTCORMICS和IBM CPLEX求解器。
