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Proc Natl Acad Sci U S A. 2016 Jun 28;113(26):E3801-9. doi: 10.1073/pnas.1523199113. Epub 2016 Jun 10.

Comparative genome-scale modelling of Staphylococcus aureus strains identifies strain-specific metabolic capabilities linked to pathogenicity.

Author information

1
Department of Biology, University of Florence, I-50019 Sesto Fiorentino, Italy;
2
Department of Bioengineering, University of California, San Diego, La Jolla, CA 92093-0412;
3
Department of Microbiology and Immunology, Faculty of Pharmacy, Cairo University, 11562 Cairo, Egypt;
4
Department of Pediatrics, University of California, San Diego, La Jolla, CA 92093-0760; Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California, San Diego, La Jolla, CA 92093-0760.
5
Department of Bioengineering, University of California, San Diego, La Jolla, CA 92093-0412; Department of Pediatrics, University of California, San Diego, La Jolla, CA 92093-0760; palsson@ucsd.edu.

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.

KEYWORDS:

core genome; mathematical modeling; pangenome; pathogenicity; systems biology

PMID:
27286824
PMCID:
PMC4932939
DOI:
10.1073/pnas.1523199113
[Indexed for MEDLINE]
Free PMC Article

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