RBApy: Extending resource allocation modeling to eukaryotes in complex environments

Abstract Motivation Resource allocation modeling—as the Resource Balance Analysis (RBA) framework— provides a way to understand and predict how limited cellular resources (e.g., energy, proteins, etc.) in cells are distributed among competing cell processes within a limited cellular space. Currently, resource allocation modeling for any eukaryotes remains limited due to the lack of software capable of generating calibrated RBA models for these types of cells, unlike prokaryotes, which benefit from the software tools RBApy, RBAtools and the RBAml format for model encoding. Results Here we extended the RBA toolkit (RBApy, RBAtools and RBAml) to account for specific aspects of eukaryotic cells growing in complex environments such as varying temperature, light or nutritional conditions. We used them to generate and simulate RBA models of both prokaryotic (Escherichia coli) and eukaryotic (Arabidopsis thaliana) cells for varying temperatures. The resulting models show excellent prediction capabilities when benchmarked against published experimental datasets. The upgraded RBA toolkit will pave the way to creating, calibrating and running resource allocation models for crops, livestock or humans for a wide range of medical, biotechnological or agricultural applications in the future. Availability and implementation RBApy and RBAtools are available via PyPI, and at https://github.com/RBAgroup.