A computational knowledge-base elucidates the response of Staphylococcus aureus to different media types

Area of Science:

• Microbiology
• Systems Biology
• Metabolic Engineering

Background:

• Staphylococcus aureus is a critical pathogen requiring new antibiotics.
• Understanding S. aureus' metabolic plasticity is vital for therapeutic development.
• Existing knowledge of S. aureus metabolic responses to diverse environments is limited.

Purpose of the Study:

• To develop a comprehensive genome-scale model (GEM-PRO) for S. aureus USA300 str. JE2 metabolism.
• To integrate 3D protein structures into the metabolic model for enhanced accuracy.
• To elucidate S. aureus' systems-level metabolic responses to different media.

Main Methods:

• Manual reconstruction of a genome-scale metabolic model (GEM-PRO) for S. aureus USA300 str. JE2.
• Incorporation of 854 genes, 1,440 reactions, 1,327 metabolites, and 673 3D protein structures.
• Validation against gene essentiality data (RB-TnSeq) and experimental physiological data.

Main Results:

• GEM-PRO achieved 85% agreement with gene essentiality data and 68% with physiological data.
• Identified non-essential biomass precursors and transcriptional regulation in Staphyloxanthin biosynthesis.
• Demonstrated essentiality of purine and amino acid biosynthesis in synthetic media.
• Revealed a metabolic switch to aerobic fermentation upon glucose exposure via exo-metabolomics integration.

Conclusions:

• The developed GEM-PRO serves as a valuable knowledge-based platform for studying S. aureus metabolism.
• The model enhances understanding of S. aureus' adaptive metabolic strategies in response to environmental cues.
• This work facilitates the discovery and development of novel antibiotics against S. aureus.