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Updated: Aug 14, 2026

Identification of Rare Bacterial Pathogens by 16S rRNA Gene Sequencing and MALDI-TOF MS
Published on: July 11, 2016
Accurately Identifying Staphylococcus argenteus Using Matrix-Assisted Laser Desorption/Ionization Time-of-Flight Mass
Jia-Ruei Yu1, Kai-Wei Huang1, Jwu-Ching Shu2
1Department of Laboratory Medicine, Chang Gung Memorial Hospital, Linkou Main Branch, Taoyuan City 33305, Taiwan.
Abstract:
Background/Objectives:Staphylococcus argenteus is a recently recognized member of the Staphylococcus aureus complex that is almost identical to S. aureus phenotypically and by 16S rRNA gene sequences. Although genomic analyses demonstrate that S. argenteus is phylogenetically distinct from S. aureus, the two species exhibit more than 90% nucleotide identity and routine identification methods-including routine biochemical assays and matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS)-cannot reliably distinguish between the two. We develop and validate a MALDI-TOF MS-based model for accurate identification of S. argenteus. Methods: A multiplex PCR assay targeting crtM and NRPS genes served as the reference standard. MALDI-TOF MS spectra from 25 S. argenteus and 25 methicillin-susceptible S. aureus (MSSA) isolates were analyzed using ClinProTools to identify characteristic peaks and develop the identification model. The model was validated using 40 S. argenteus and 80 MSSA isolates, then applied to 130 randomly selected clinical isolates. Results: Five characteristic peaks-m/z values 5005, 5285, 5323, 6440, and 6526-were identified. Isolates exhibiting at least 4 of these 5 peaks were classified as S. argenteus; those exhibiting fewer than 4 were classified as S. aureus. The model achieved 100% specificity and 100% sensitivity in both the development and validation phases. In the clinical application phase, the model correctly classified all isolates, whereas conventional MALDI-TOF MS yielded several misidentifications. Conclusions: The identification model, and the simple peak-based rule it is based on, can accurately distinguish S. argenteus from MSSA, offering a practical diagnostic tool for clinical microbiology laboratories.
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