MCC: automated mass and charge curation at the genome scale applied to C. tuberculostearicum

Abstract

The rise of antibiotic resistance has made it essential to explore alternative treatments for bacterial infections, particularly those caused by respiratory tract colonizers like Corynebacterium tuberculostearicum . Understanding the metabolic behavior of these bacteria and their interactions with the human host or microbiota is crucial. Genome-scale metabolic models (GEMs) are powerful tools for investigating these interactions, but they are time-consuming to build. Our new Python package, Mass and Charge Curation, automates a crucial step in the GEM reconstruction process—mass and charge balancing—making it more efficient and reliable. By applying this tool, we developed a high-quality, functional metabolic model for C. tuberculostearicum ( i CTUB2024RM), which provides deeper insights into the organism’s growth in a simulated human nasal environment. This work offers a foundation for future research into microbial communities and their role in human health.