Background
Methicillin-resistant Staphylococcus aureus (MRSA) and multidrug-resistant (MDR) S. aureus strains are well recognized as posing substantial problems in treating ocular infections. S. aureus has a vast array of virulence factors, including superantigens and enterotoxins. Their interactions and ability to signal antibiotics resistance have not been explored.
Objectives
To predict the relationship between superantigens and methicillin and multidrug resistance among S. aureus ocular isolates.
Methods
We used a DNA microarray to characterize the enterotoxin and superantigen gene profiles of 98 S. aureus isolates collected from common ocular sources. The outcomes contained phenotypic and genotypic expressions of MRSA. We also included the MDR status as an outcome, categorized as resistance to three or more drugs, including oxacillin, penicillin, erythromycin, clindamycin, moxifloxacin, tetracycline, trimethoprim-sulfamethoxazole and gentamicin. We identified gene profiles that predicted each outcome through a classification analysis utilizing Random Forest machine learning techniques.
Findings
Our machine learning models predicted the outcomes accurately utilizing 67 enterotoxin and superantigen genes. Strong correlates predicting the genotypic expression of MRSA were enterotoxins A, D, J and R and superantigen-like proteins 1, 3, 7 and 10. Among these virulence factors, enterotoxin D and superantigen-like proteins 1, 5 and 10 were also significantly informative for predicting both MDR and MRSA in terms of phenotypic expression. Strong interactions were identified including enterotoxins A (entA) interacting with superantigen-like protein 1 (set6-var1_11), and enterotoxin D (entD) interacting with superantigen-like protein 5 (ssl05/set3_probe 1): MRSA and MDR S. aureus are associated with the presence of both entA and set6-var1_11, or both entD and ssl05/set3_probe 1, while the absence of these genes in pairs indicates non-multidrug-resistant and methicillin-susceptible S. aureus.
Conclusions
MRSA and MDR S. aureus show a different spectrum of ocular pathology than their non-resistant counterparts. When assessing the role of enterotoxins in predicting antibiotics resistance, it is critical to consider both main effects and interactions.
Computational Sensing of Staphylococcus aureus on Contact Lenses Using 3D Imaging of Curved Surfaces and Machine Learning
