ArticleProceedings of the National Academy of Sciences of the United States of America2016
Comparative genome-scale modelling of Staphylococcus aureus strains identifies strain-specific metabolic capabilities linked to pathogenicity.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 153 papers.
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153 citing papers in PubMed.
- Amino acid availability influences Staphylococcus aureus interaction with the nasal microbiota in a strain- and community-specific manner.Microbiome · 2026Article
- Integrated Genome-Wide Association Study and Machine Learning Approach for Characterizing the Determinants of Biofilm Formation in Staphylococcus aureus.Interdisciplinary sciences, computational life sciences · 2026Article
- High-throughput generation and comparison of genome-scale metabolic models reveal strain-specific metabolic diversity in 439mSystems · 2026Article
- Multi-strain analysis ofmSystems · 2026Article
- Distinct genetic programs drive antibiotic resistance and intracellular invasion in emerging MRSA strains.mSystems · 2026Article
- AntiPan: a genome-informed in silico pipeline for advancing subunit vaccine discovery against Staphylococcus aureus.Scientific reports · 2026Article
- Gempipe: a tool for drafting, curating, and analyzing pan and multi-strain genome-scale metabolic models.mSystems · 2026Article
- From Single Organisms to Communities: Modeling Methanotrophs and Their Satellites.Microorganisms · 2025Review
- A metabolic atlas of the Klebsiella pneumoniae species complex reveals lineage-specific metabolism and capacity for intra-species co-operation.PLoS biology · 2025Article
- Multi-strain Analysis ofbioRxiv : the preprint server for biology · 2025Article
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- Mass Spectrometry-Based Analysis of Surface Proteins inJournal of proteome research · 2025Article
- Yeast adapts to diverse ecological niches driven by genomics and metabolic reprogramming.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- sRNA-mediated crosstalk between cell wall stress and galactose metabolism in Staphylococcus aureus.Nucleic acids research · 2025Article
- Genome-scale metabolic model-guided systematic framework for designing customized live biotherapeutic products.NPJ systems biology and applications · 2025Review
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- Differential stress responsiveness determines intraspecies virulence heterogeneity and host adaptation in Listeria monocytogenes.Nature microbiology · 2024Article
- Pan-genome-scale metabolic modeling ofmSystems · 2024Article
- Facemask acne attenuation through modulation of indirect microbiome interactions.NPJ biofilms and microbiomes · 2024Article
- Model-driven characterization of functional diversity ofMicrobial genomics · 2024Article
93 more citing papers are in PubMed but not listed here.
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6 authors.
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Abstract
Staphylococcus aureus is a preeminent bacterial pathogen capable of colonizing diverse ecological niches within its human host. We describe here the pangenome of S. aureus based on analysis of genome sequences from 64 strains of S. aureus spanning a range of ecological niches, host types, and antibiotic resistance profiles. Based on this set, S. aureus is expected to have an open pangenome composed of 7,411 genes and a core genome composed of 1,441 genes. Metabolism was highly conserved in this core genome; however, differences were identified in amino acid and nucleotide biosynthesis pathways between the strains. Genome-scale models (GEMs) of metabolism were constructed for the 64 strains of S. aureus These GEMs enabled a systems approach to characterizing the core metabolic and panmetabolic capabilities of the S. aureus species. All models were predicted to be auxotrophic for the vitamins niacin (vitamin B3) and thiamin (vitamin B1), whereas strain-specific auxotrophies were predicted for riboflavin (vitamin B2), guanosine, leucine, methionine, and cysteine, among others. GEMs were used to systematically analyze growth capabilities in more than 300 different growth-supporting environments. The results identified metabolic capabilities linked to pathogenic traits and virulence acquisitions. Such traits can be used to differentiate strains responsible for mild vs. severe infections and preference for hosts (e.g., animals vs. humans). Genome-scale analysis of multiple strains of a species can thus be used to identify metabolic determinants of virulence and increase our understanding of why certain strains of this deadly pathogen have spread rapidly throughout the world.
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