860. Molecular Characterization of Isolated Staphylococcus aureus Specimens Using Matrix-Assisted Laser Desorption/Ionization Time-of-Flight Mass Spectrometry (MALDI-TOF MS)

• Published in: Open forum infectious diseases Vol. 10; no. Supplement_2
• Main Authors: Dawning, Amber, Lin, Xiting, Jerris, Robert C, Thornton, Kevin, Mohamed, Noor, Immergluck, Lilly
• Format: Journal Article
• Language: English
• Published: US Oxford University Press 27.11.2023
• ISSN: 2328-8957; 2328-8957
• DOI: 10.1093/ofid/ofad500.905

Abstract Background Staphylococcus aureus (S. aureus) is a common cause of skin and soft tissue infections (SSTIs). Both the β-lactam resistant form, methicillin resistant S. aureus (MRSA), and non-resistant form, methicillin susceptible S. aureus (MSSA) are associated with disparate infections across age and race; community-associated infections are often due to S. aureus US300. Matrix-Assisted Laser Desorption/Ionization Time-of-Flight Mass Spectrometry (MALDI-TOF MS) is a used in clinical microbiology laboratories to identify bacterial species, but limited data is available on if this tool can identify different strains of S. aureus. We hypothesize that MALDI-TOF MS can be used to identify strain-specific peaks of S. aureus USA300. Methods Children were enrolled from emergency departments and swabbed for S. aureus (anterior nares, axilla, perirectal, oropharyngeal, and wounds) during two time periods (2006-2008 and 2015-2016). MALDI-TOF MS was performed on S. aureus cultured from study participants. Default parameters used for variance stability, smoothing, baseline subtraction, and normalization in R 4.4.3. and MALDIquant v1.22 were applied to raw data. Peak detection and alignment were performed with a signal-to-noise ratio of three and tolerance of 300 ppm. Binning and machine learning algorithms were used to identify intensity differences of each peak identified; significance of peaks was determined using Chi Square statistical analyses, comparing MRSA and MSSA, and then between all S. aureus isolates compared to USA300. Statistical significance was considered with p-value < 0.05 using R and SAS 9.4. Results From 57 MRSA and 53 MSSA isolates, 320 peaks were identified. 31 significant peaks were identified, with 14 unique peaks for MRSA and 17 for MSSA. With S. aureus USA300, eight of the 31 peaks remained statistically significant. Conclusion MALDI-TOF MS can identify unique peak differences between MRSA and MSSA. This tool can be potentially used to distinguish S. aureus at the strain level in a clinical setting. MALDI-TOF MS can be an impactful and rapid diagnostic tool to detect antibiotic resistance in S. aureus in a clinical setting. Disclosures Lilly Immergluck, MD,MS, Melinta: Grant/Research Support|Melinta: Grant/Research Support