Development and rapid identification of a self-constructed MALDI-TOF MS library for Mycoplasma pneumoniae clinical isolates
DOI:
https://doi.org/10.3855/jidc.21859Keywords:
Mycoplasma pneumoniae, MALDI-TOF MS, self-constructed library, rapid identificationAbstract
Introduction: To assess the diagnostic efficacy of matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) for rapid and precise identification of Mycoplasma pneumoniae in clinical microbiology workflows.
Methodology: A reference-calibrated MALDI-TOF MS spectral database was generated through a standardized formic acid/acetonitrile extraction protocol from the M. pneumoniae reference strain (M129). Forty-nine prospectively collected M. pneumoniae clinical isolates were obtained from respiratory tract specimens at Hangzhou First People's Hospital during August-October 2023. These isolates optimized the in-house MALDI-TOF MS database for M. pneumoniae identification and validated the diagnostic feasibility of liquid pre-culture coupled with MALDI-TOF MS analysis.
Results: When we randomly selected 40 strains for database validation, we found that the first phase validation of the M129-derived spectral database indicated that 87.5% (35/40) of the clinical isolates were initially detected, among which 57.5% (23/40) reached the ≥ 2.0 log value (score) threshold required for species-level identification. Post-optimization through iterative spectral refinement, 100% detection rate (40/40) was attained, with 75% (30/40) meeting strict diagnostic criteria (log(score) ≥ 2.0). The integrated liquid culture-MALDI-TOF MS platform achieved a mean identification time of 9.6 ± 1.4 days, demonstrating a 19.3% reduction in turnaround time compared to traditional chromogenic detection methods (11.9 ± 1.6 days; Independent Samples t-test, p < 0.001).
Conclusions: This study establishes MALDI-TOF MS as a CLSI-compliant diagnostic method for M. pneumoniae with superior accuracy and operational efficiency. Optimized liquid culture-MALDI-TOF MS integration reduces diagnostic latency by 2.3 days, enhancing respiratory pathogen management in clinical laboratories.
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Copyright (c) 2026 Ke Cen, Cong Qin, Jie Wang, Shenghai Wu

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