scFBApy: A Python Framework for Super-Network Flux Balance Analysis

Constraint-based modelling (CBM) is a computational method used in systems biology to predict metabolic fluxes. However, modelling metabolic fluxes with CBM remains challenging due to the complexity of metabolism and the need for omics data integration. This study introduces scFBApy, a Python-based tool for simulating CBM and the metabolic cooperation between cells. It allows the flux simulation of a population of networks for a target objective, such as biomass production, with or without cooperation. The tool integrates single-cell transcriptomics data using Reaction Activity Scores and uses a denoising algorithm for pre-processing scRNA-seq data. Five real-world scRNA-seq datasets were used to demonstrate the applicability of the pipeline. Results showed that cooperation between cells increased biomass production compared to independent cell simulations. The scFBApy package provides an open-source alternative to MATLAB-based CBM tools.