TY - JOUR
T1 - Pathoadapative Genomic Determinants of Staphylococcus aureus Community Skin Infections and Nasal Colonization
AU - Black, Cody A.
AU - So, Wonhee
AU - Benavides, Raymond
AU - Mercer, Julianne A.
AU - Dallas, Steven S.
AU - Shurko, James F.
AU - Bandy, Sarah M.
AU - Encino, Benjamin A.
AU - Lipscomb, Justina S.
AU - Vargus, Adriana
AU - Frei, Christopher R.
AU - Lee, Grace C.
N1 - Publisher Copyright:
© 2025 by the authors.
PY - 2025/9
Y1 - 2025/9
N2 - Staphylococcus aureus is a leading cause of skin and soft tissue infections (SSTIs), yet the bacterial genomic adaptations underlying the transition from nasal colonization to invasive infection remain incompletely defined. We sequenced and analyzed 157 S. aureus isolates (126 from SSTIs and 31 from asymptomatic nasal colonization) from a primary care network in South Texas. Using genome-wide association studies, non-synonymous single-nucleotide variant (NSNV) profiling, and machine learning, we identified strain-specific adaptations in metabolic and regulatory pathways. SSTI isolates exhibited significant enrichment of nitrogen assimilation, purine biosynthesis, menaquinone production, and anaerobic respiration genes. Elevated copy number and colocalization of phage-linked metabolic genes—including nirB, narH, and nifR3—suggest a pathoadaptive genomic island supporting infection-specific energy generation. The enrichment of α/β-hydrolase domain-encoding genes was associated with clinical severity. To quantify severity, we developed the Purulent Ulcer Skin (PUS) score, which integrates wound size, drainage, and erythema. The α/β-hydrolase and lipoprotein genes were significantly associated with higher PUS scores (higher SSTI severity) and phage-encoded virulence gene products were linked to larger wound size. Machine learning prioritized purL and other metabolic loci as key infection classifiers. NSNVs and unitig-level changes co-localized within nutrient transport, stress resistance, and cytolytic genes, supporting a model of multi-layered genomic selection. Metagenomic assemblies of nasal microbiota were enriched for Staphylococcus, Enterococcus, and Micrococcus species, core metabolic pathways, and taxon-specific virulence determinants. This underscores the roles of metabolic and virulent co-networks within nasal commensals and their adaptive capacity for pathogenic transition. These findings provide a potential genomic blueprint of S. aureus pathoadaptation during SSTI and are a step towards the development of novel therapeutic targets.
AB - Staphylococcus aureus is a leading cause of skin and soft tissue infections (SSTIs), yet the bacterial genomic adaptations underlying the transition from nasal colonization to invasive infection remain incompletely defined. We sequenced and analyzed 157 S. aureus isolates (126 from SSTIs and 31 from asymptomatic nasal colonization) from a primary care network in South Texas. Using genome-wide association studies, non-synonymous single-nucleotide variant (NSNV) profiling, and machine learning, we identified strain-specific adaptations in metabolic and regulatory pathways. SSTI isolates exhibited significant enrichment of nitrogen assimilation, purine biosynthesis, menaquinone production, and anaerobic respiration genes. Elevated copy number and colocalization of phage-linked metabolic genes—including nirB, narH, and nifR3—suggest a pathoadaptive genomic island supporting infection-specific energy generation. The enrichment of α/β-hydrolase domain-encoding genes was associated with clinical severity. To quantify severity, we developed the Purulent Ulcer Skin (PUS) score, which integrates wound size, drainage, and erythema. The α/β-hydrolase and lipoprotein genes were significantly associated with higher PUS scores (higher SSTI severity) and phage-encoded virulence gene products were linked to larger wound size. Machine learning prioritized purL and other metabolic loci as key infection classifiers. NSNVs and unitig-level changes co-localized within nutrient transport, stress resistance, and cytolytic genes, supporting a model of multi-layered genomic selection. Metagenomic assemblies of nasal microbiota were enriched for Staphylococcus, Enterococcus, and Micrococcus species, core metabolic pathways, and taxon-specific virulence determinants. This underscores the roles of metabolic and virulent co-networks within nasal commensals and their adaptive capacity for pathogenic transition. These findings provide a potential genomic blueprint of S. aureus pathoadaptation during SSTI and are a step towards the development of novel therapeutic targets.
KW - Staphylococcus aureus
KW - bacterial genomics
KW - colonization
KW - community
KW - genome-wide association study
KW - metabolic
KW - methicillin resistance
KW - pathogenicity
KW - purulent
KW - skin and soft tissue infection
UR - https://www.scopus.com/pages/publications/105017176365
UR - https://www.scopus.com/pages/publications/105017176365#tab=citedBy
U2 - 10.3390/microorganisms13092023
DO - 10.3390/microorganisms13092023
M3 - Article
C2 - 41011355
AN - SCOPUS:105017176365
SN - 2076-2607
VL - 13
JO - Microorganisms
JF - Microorganisms
IS - 9
M1 - 2023
ER -