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January 23, 2026Water0 citationsOpen Access

Utilizing MALDI-TOF MS for Legionella pneumophila Subspecies Typing and Classification

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LMLana MadagiSEShimon EdelsteinHBHila Ben-Amram

Key Points

  • The aim is to assess MALDI-TOF MS for accurately subtyping Legionella pneumophila strains.
  • Evaluated 70 L. pneumophila strains from various geographic regions using MALDI-TOF MS
  • Characterized strains based on Multi-Locus Variable Number Tandem Repeat Analysis (MLVA-8) genotypic groups
  • Applied Random Forest and Decision Tree algorithms for data analysis
  • Achieved over 85% classification accuracy using the Random Forest model
  • Obtained over 71% accuracy with the Decision Tree algorithm
  • Identified distinct m/z peaks associated with genotypes, notably m/z 5358 for GT15 strains

Abstract

Legionella pneumophila (L. pneumophila), the primary causative agent of Legionnaires’ disease, is a waterborne bacterial pathogen that poses significant public health concern. This opportunistic pathogen commonly inhabits both natural and man-made water systems, particularly drinking water distribution systems (DWDSs), where it can proliferate and pose a risk to human health. In this study, we evaluated the potential of Matrix-Assisted Laser Desorption Ionization Time-of-Flight Mass Spectrometry (MALDI-TOF MS) for rapid and accurate subtyping of L. pneumophila. Our analysis included 70 L. pneumophila strains collected from the Middle East, representing one of the largest and most comprehensive MALDI-TOF MS-based subtyping of strains from this geographically underrepresented region. These strains, representing three Multi-Locus Variable Number Tandem Repeat Analysis (MLVA-8) genotypic groups (GT4, GT6, and GT15), have been extensively characterized in previous studies for their virulence traits, cytotoxicity patterns, and antimicrobial susceptibility profiles. Our findings revealed distinct genotype-associated spectral signatures with 30 discriminatory m/z peaks (p ≤ 0.005). These markers enabled accurate genotype-level classification, achieving over 85% classification accuracy with a Random Forest model and over 71% accuracy using a Decision Tree algorithm. Importantly, the m/z peak at 5358 was uniquely present in the GT15 strains, whereas m/z 5353 was consistently detected in both GT4 and GT6 isolates, demonstrating the potential of specific mass peaks to serve as reliable genotype markers. Furthermore, GT15 strains consistently formed a separate cluster in both Principal Component Analysis (PCA) and hierarchical analyses, whereas GT4 and GT6 exhibited partial overlap, reflecting their exceptionally high genomic similarity.

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Cite This Study

Madagi et al. (2026) studied this question.

synapsesocial.com/papers/69730f9fc8125b09b0d1f58ahttps://doi.org/10.3390/w18020269
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