Evaluating the performance of Fourier transform infrared spectroscopy for typing and outbreak investigation of methicillin-resistant and -susceptible <i>Staphylococcus aureus</i>

Abstract

<p>Infections caused by methicillin-susceptible <em>Staphylococcus aureus</em> (MSSA) and methicillin-resistant <em>Staphylococcus aureus</em> (MRSA) can be life-threatening and complicated to manage. Especially in the healthcare environment, MRSA is a notorious cause of outbreaks inflicting a significant disease burden. Assessing the relatedness of isolates is a key challenge for outbreak management. We aimed to assess the utility and performance of Fourier transform infrared (FTIR) spectroscopy (IR Biotyper; Bruker Daltonics GmbH & Co. KG, Bremen, Germany) by comparing it with <em>spa</em> typing and whole-genome sequencing (WGS). <em>S. aureus</em> was cultured under standard conditions on Müller-Hinton agar, and the second subculture was used for spectral acquisition. Eighty-eight MRSA isolates and 89 MSSA isolates were included from both screening and clinical MRSA specimens, and blood culture MSSA specimens were identified at the clinical microbiology laboratory of Turku University Hospital, Southwest Finland. Among non-outbreak strains, two or three possible subtypes were detected with FTIR within 16 different <em>spa</em> types. Two suspected healthcare-associated outbreaks comprising nine and four isolates, respectively, were detected. WGS confirmed the outbreak with four isolates. Within the other outbreak, WGS revealed five closely related and four unrelated isolates. FTIR analysis correctly differentiated two of the unrelated isolates, while two unrelated isolates were erroneously clustered in a principal component analysis. Although the discriminatory power of FTIR was lower than WGS, false-negative clustering was not observed. FTIR showed a lower analysis cost per specimen and was superior in processing speed to both WGS and <em>spa</em> typing. Our findings suggest the potential use of FTIR in preliminary screening, supporting almost real-time outbreak analysis and hence outbreak management.<br></p>