Matrix-assisted laser desorption ionisation time-of-flight mass spectrometry for identification of clinically significant bacteria that are difficult to identify in clinical laboratories

摘要

Aims Although the revolutionary matrix-assisted laser desorption ionisation time-of-flight mass spectrometry (MALDI-TOF MS) has been evaluated for identification of various groups of bacteria, its application in bacteria that are 'difficult-to-identify' by phenotypic tests has been less well studied. We aim to evaluate the usefulness of MALDI-TOF MS for identification of 'difficult-to-identify' bacterial isolates. Methods We evaluated the performance of the Bruker MALDI-TOF MS system for a collection of 67 diverse clinically important bacterial isolates that were less commonly encountered, possessed ambiguous biochemical profiles or belonged to newly discovered species. The results were compared with 16S rRNA gene sequencing as a reference method for species identification. Results Using 16S rRNA gene sequencing as the reference method, 30 (45％) isolates were identified correctly to species level (score ≥2.0), 20 (30％) were only identified to genus level (score ≥1.7), four (6％) were misidentified (incorrect species with score ≥2.0 or incorrect genus with score ≥1.7) and 13 (19％) showed 'no identification' (score ＜1.7). Aerobic Gram-positive bacteria showed the highest percentage of correct species identification, followed by aerobic Gram-negative, anaerobic Gram-positive and anaerobic Gram-negative bacteria. Sixteen isolates identified to genus level actually showed the correct species but with scores below the threshold for species identification. Most isolates which showed 'no identification' were due to the absence of the corresponding species in the Bruker database. Conclusions Expansion of commercial databases to include reference spectra of less commonly encountered and newly discovered species and to increase available spectra for each species is required to improve the accuracy of MALDI-TOF MS for identifying 'difficult-to-identify' bacteria.