A genome-scale metabolic model of a globally disseminated hyperinvasive M1 strain of Streptococcus pyogenes
Year: 2024
Type: article
Abstract: ABSTRACT Streptococcus pyogenes is responsible for a range of diseases in humans contributing significantly to morbidity and mortality. Among more than 200 serotypes of S. pyogenes , serotype M1 strains hold the greatest clinical relevance due to their high prevalence in severe human infections. To enhance our understanding of pathogenesis and discovery of potential therapeutic approaches, we have developed the first genome-scale metabolic model (GEM) for a serotype M1 S. pyogenes strain, which we name iYH543. The curation of iYH543 involved cross-referencing a draft GEM of S. pyogenes serotype M1 from the AGORA2 database with gene essentiality and autotrophy data obtained from transposon mutagenesis-based and growth screens. We achieved a 92.6% (503/543 genes) accuracy in predicting gene essentiality and a 95% (19/20 amino acids) accuracy in predicting amino acid auxotrophy. Additionally, Biolog Phenotype microarrays were employed to examine the growth phenotypes of S. pyogenes, which further contributed to the refinement of iYH543. Notably, iYH543 demonstrated 88% accuracy (168/190 carbon sources) in predicting growth on various sole carbon sources. Discrepancies observed between iYH543 and the actual behavior of living S. pyogenes highlighted areas of uncertainty in the current understanding of S. pyogenes metabolism. iYH543 offers novel insights and hypotheses that can guide future research efforts and ultimately inform novel therapeutic strategies. IMPORTANCE Genome-scale models (GEMs) play a crucial role in investigating bacterial metabolism, predicting the effects of inhibiting specific metabolic genes and pathways, and aiding in the identification of potential drug targets. Here, we have developed the first GEM for the S. pyogenes highly virulent serotype, M1, which we name iYH543. The iYH543 achieved high accuracy in predicting gene essentiality. We also show that the knowledge obtained by substituting actual measurement values for iYH543 helps us gain insights that connect metabolism and virulence. iYH543 will serve as a useful tool for rational drug design targeting S. pyogenes metabolism and computational screening to investigate the interplay between inhibiting virulence factor synthesis and growth.
Source: mSystems
Institutions: University of California San Diego, The University of Osaka, J. Craig Venter Institute, Oregon Health & Science University, Center for Infectious Disease Education and Research, The University of Osaka, Research Institute for Microbial Diseases, The University of Osaka, Inserm, Ollscoil na Gaillimhe – University of Galway, Nutrition-Génétique et Exposition aux Risques Environnementaux, Université de Lorraine, APC Microbiome Institute
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $3,500
Funders: Japan Agency for Medical Research and Development, Fondation Leducq, Ministry of Education, Culture, Sports, Science and Technology, National Institutes of Health, Japan Society for the Promotion of Science, National Institute of Allergy and Infectious Diseases, National Institute of Dental and Craniofacial Research
Awards: Identification of Metabolic Mechanisms Contributing to the Exacerbation of Streptococcus pyogenes Infections and Exploration of Virulence Control Strategies, Analysis of the oral tumor microbiome and development of nucleic acid vaccines using bacterial-derived peptides, 肺炎球菌の細胞壁分解能が病態形成と薬剤耐性獲得に果たす役割の解明, G4170639157, G4468463265, G47547542, Investigation of the new control strategies for drug-resistant pathogenic streptococci using systems biology, G7833532353, G8067846226, G8165128545, Understanding Streptococcal Niche Expansion and Developing New Infection Control Methods, Investigating Membrane Alterations as a Mechanism of Acid Tolerance in Cariogenic Bacteria, Cathelicidin in Skin Immunity, Identifying the Most Effective Adjuvant(s) for Leading Group A Streptococcal Vaccine Antigens in Preclinical Mouse and Nonhuman Primate Models
OpenAlex ID: W4401705005