作者
Michelle Su, James T Lyles, Robert A Petit III, Jessica Peterson, Michelle Hargita, Huaqiao Tang, Claudia Solis-Lemus, Cassandra L Quave, Timothy D Read
发表日期
2020/3/24
期刊
PeerJ
卷号
8
页码范围
e8717
出版商
PeerJ Inc.
简介
Background
The delta-toxin (δ-toxin) of Staphylococcus aureus is the only hemolysin shown to cause mast cell degranulation and is linked to atopic dermatitis, a chronic inflammatory skin disease. We sought to characterize variation in δ-toxin production across S. aureus strains and identify genetic loci potentially associated with differences between strains.
Methods
A set of 124 S. aureus strains was genome-sequenced and δ-toxin levels in stationary phase supernatants determined by high performance liquid chromatography (HPLC). SNPs and kmers were associated with differences in toxin production using four genome-wide association study (GWAS) methods. Transposon mutations in candidate genes were tested for their δ-toxin levels. We constructed XGBoost models to predict toxin production based on genetic loci discovered to be potentially associated with the phenotype.
Results
The S. aureus strain set encompassed 40 sequence types (STs) in 23 clonal complexes (CCs). δ-toxin production ranged from barely detectable levels to> 90,000 units, with a median of> 8,000 units. CC30 had significantly lower levels of toxin production than average while CC45 and CC121 were higher. MSSA (methicillin sensitive) strains had higher δ-toxin production than MRSA (methicillin resistant) strains. Through multiple GWAS approaches, 45 genes were found to be potentially associated with toxicity. Machine learning models using loci discovered through GWAS as features were able to predict δ-toxin production (as a high/low binary phenotype) with a precision of. 875 and specificity of. 990 but recall of. 333. We discovered that mutants in the carA …
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