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Evaluation of the Hologic Panther Fusion MRSA Assay for the detection of MRSA in ESwab specimens obtained from nose, throat, and perineum.

Mette Damkjær BartelsDanah KnudsenHenrik WesthKristian Schønning
Published in: European journal of clinical microbiology & infectious diseases : official publication of the European Society of Clinical Microbiology (2021)
Enrichment culture (EC) remains gold standard for detecting MRSA colonisation, but molecular methods shorten turnaround time. The CE-marked automated Hologic Panther Fusion MRSA Assay (HPFM) is validated for nasal swabs. We compared HPFM with EC following an in-house PCR for detection of MRSA in nasal, pharyngeal, and perineal ESwabs. The same ESwabs were analysed using HPFM and inoculated in selective Tryptic Soy Broth (TSB) for overnight incubation. TSBs were screened by a PCR targeting nuc, femA, mecA, and mecC. Only samples with PCR results compatible with MRSA presence were inoculated onto 5% blood agar and chromogenic MRSA plates. HPFM detected MRSA in 103 of 132 EC positive samples indicating a sensitivity of 78.0% across sample types. When paired TSBs of 29 EC positive/HPFM negative samples were re-analysed by HPFM, MRSA was detected in 17/29 TSBs indicating that enrichment will increase the sensitivity of HPFM. HPFM analyses of cultured isolates from the remaining 12 EC positive/HPFM negative samples failed to detect orfX. HPFM reported the presence of MRSA in 22 samples where EC failed to identify MRSA. Fifteen of these ESwabs had been kept and direct culture without enrichment identified MRSA in seven samples. HPFM was useful for all sample sites. Compared to EC, the sensitivity of HPFM was limited because of lack of analytical sensitivity and failure to detect all MRSA variants. Failure of some MRSA-containing samples to enrich in cefoxitin-containing TSB indicates an unappreciated limitation of EC, which may lead to underestimation of the specificity of molecular assays.
Keyphrases
  • methicillin resistant staphylococcus aureus
  • staphylococcus aureus
  • high throughput
  • machine learning
  • gene expression
  • deep learning
  • mass spectrometry
  • genome wide
  • quantum dots