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Rapid Differentiation of Haemophilus influenzae and Haemophilus haemolyticus by Use of Matrix-Assisted Laser Desorption Ionization-Time of Flight Mass Spectrometry with ClinProTools Mass Spectrum Analysis.

Jonathan Hon Kwan ChenVincent C C ChengChun-Pong WongSally C Y WongWing-Cheong YamKwok-Yung Yuen
Published in: Journal of clinical microbiology (2017)
Haemophilus influenzae is associated with severe invasive disease, while Haemophilus haemolyticus is considered part of the commensal flora in the human respiratory tract. Although the addition of a custom mass spectrum library into the matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) system could improve identification of these two species, the establishment of such a custom database is technically complicated and requires a large amount of resources, which most clinical laboratories cannot afford. In this study, we developed a mass spectrum analysis model with 7 mass peak biomarkers for the identification of H. influenzae and H. haemolyticus using the ClinProTools software. We evaluated the diagnostic performance of this model using 408 H. influenzae and H. haemolyticus isolates from clinical respiratory specimens from 363 hospitalized patients and compared the identification results with those obtained with the Bruker IVD MALDI Biotyper. The IVD MALDI Biotyper identified only 86.9% of H. influenzae (311/358) and 98.0% of H. haemolyticus (49/50) clinical isolates to the species level. In comparison, the ClinProTools mass spectrum model could identify 100% of H. influenzae (358/358) and H. haemolyticus (50/50) clinical strains to the species level and significantly improved the species identification rate (McNemar's test, P < 0.0001). In conclusion, the use of ClinProTools demonstrated an alternative way for users lacking special expertise in mass spectrometry to handle closely related bacterial species when the proprietary spectrum library failed. This approach should be useful for the differentiation of other closely related bacterial species.
Keyphrases
  • mass spectrometry
  • respiratory tract
  • genetic diversity
  • escherichia coli
  • endothelial cells
  • high resolution
  • adverse drug