Y-H Cheng3, C-L Perng2, M-J Jian1, Y-H Cheng3, S-Y Lee4, J-R Sun5, H-S Shang6. 1. Graduate Institute of Medical Sciences, National Defense Medical Center, Taipei, Taiwan; Division of Clinical Pathology, Department of Pathology, Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan. 2. Graduate Institute of Pathology, National Defense Medical Center, Taipei, Taiwan; Division of Clinical Pathology, Department of Pathology, Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan. 3. Division of Clinical Pathology, Department of Pathology, Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan. 4. Division of Clinical Microbiology, Department of Pathology and Laboratory Medicine, Taipei Veterans General Hospital, Taipei, Taiwan. 5. Graduate Institute of Medical Sciences, National Defense Medical Center, Taipei, Taiwan; Division of Clinical Pathology, Department of Pathology, Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan; Institute of Preventive Medicine, National Defense Medical Center, Taipei, Taiwan. Electronic address: tsghsun@gmail.com. 6. Graduate Institute of Medical Sciences, National Defense Medical Center, Taipei, Taiwan; Division of Clinical Pathology, Department of Pathology, Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan. Electronic address: iamkeith001@gmail.com.
Abstract
OBJECTIVES: Rapid identification of Elizabethkingia species is essential because these species show variations in antibiotic susceptibility and clinical outcomes. Many recent inaccuracies in Elizabethkingia identification by matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) have been noted. Accordingly, in this study, we evaluated the use of MALDI-TOF MS with an amended database to identify isolates of Elizabethkingia anophelis, E. miricola and E. meningoseptica. We then investigated the antimicrobial susceptibility of Elizabethkingia. METHODS: MALDI-TOF MS spectra were acquired from formic acid extracts overlaid with α-cyano-4-hydroxycinnamic acid matrix on target slides in linear positive ion mode for m/z 2000 to 20 000 Da. Spectra were analysed and SuperSpectra were created with SARAMIS premium software. 16S rRNA gene sequencing was used as the reference standard for species identification. Antibiotic susceptibility was assessed by broth microdilution. RESULTS: A total of 103 E. anophelis, 21 E. miricola and 11 E. meningoseptica isolates were used to calculate the average spectra and exclude common peaks. SuperSpectra were added to the SARAMIS taxonomy database; all validation results were correct, even for isolates not included in SuperSpectra. Confirmation by direct colony formation was also performed. Overall, the positive predictive value of SuperSpectra was 100% for all isolates. E. miricola (77%, 17/22) was more susceptible to levofloxacin than E. anophelis (16%, 17/105). Doxycycline and minocycline were effective against all Elizabethkingia species. CONCLUSIONS: Spectral analysis software identified significant species-specific peaks to create reference masses for efficient and accurate identification of Elizabethkingia species, providing accurate information for clinical treatment of Elizabethkingia infections.
OBJECTIVES: Rapid identification of Elizabethkingia species is essential because these species show variations in antibiotic susceptibility and clinical outcomes. Many recent inaccuracies in Elizabethkingia identification by matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) have been noted. Accordingly, in this study, we evaluated the use of MALDI-TOF MS with an amended database to identify isolates of Elizabethkingia anophelis, E. miricola and E. meningoseptica. We then investigated the antimicrobial susceptibility of Elizabethkingia. METHODS: MALDI-TOF MS spectra were acquired from formic acid extracts overlaid with α-cyano-4-hydroxycinnamic acid matrix on target slides in linear positive ion mode for m/z 2000 to 20 000 Da. Spectra were analysed and SuperSpectra were created with SARAMIS premium software. 16S rRNA gene sequencing was used as the reference standard for species identification. Antibiotic susceptibility was assessed by broth microdilution. RESULTS: A total of 103 E. anophelis, 21 E. miricola and 11 E. meningoseptica isolates were used to calculate the average spectra and exclude common peaks. SuperSpectra were added to the SARAMIS taxonomy database; all validation results were correct, even for isolates not included in SuperSpectra. Confirmation by direct colony formation was also performed. Overall, the positive predictive value of SuperSpectra was 100% for all isolates. E. miricola (77%, 17/22) was more susceptible to levofloxacin than E. anophelis (16%, 17/105). Doxycycline and minocycline were effective against all Elizabethkingia species. CONCLUSIONS: Spectral analysis software identified significant species-specific peaks to create reference masses for efficient and accurate identification of Elizabethkingia species, providing accurate information for clinical treatment of Elizabethkingia infections.
Authors: Isin Y Comba; Audrey N Schuetz; Anisha Misra; Daniel Z P Friedman; Ryan Stevens; Robin Patel; Zane D Lancaster; Aditya Shah Journal: J Clin Microbiol Date: 2022-05-05 Impact factor: 11.677