Identification of Cronobacter species by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry with an optimized analysis method

• Published in: Journal of microbiological methods 2017-08, Vol.139, p.172-180
• Main Authors: Wang, Qi, Zhao, Xiao-Juan, Wang, Zi-Wei, Liu, Li, Wei, Yong-Xin, Han, Xiao, Zeng, Jing, Liao, Wan-Jin
• Format: Article
• Language: English
• Subjects: 16S rRNA gene; Bacterial Typing Techniques - methods; Cluster Analysis; Cronobacter; Cronobacter - classification; Cronobacter - genetics; Cronobacter - isolation & purification; Databases, Genetic; DNA, Bacterial - genetics; Food Microbiology; Humans; MALDI-TOF MS; RNA, Ribosomal, 16S - genetics; Sequence Analysis, DNA; Software; Species identification; Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization - methods; Statistics as Topic - methods; UPGMA clustering
• ISSN: 0167-7012; 1872-8359
• DOI: 10.1016/j.mimet.2017.05.016

Rapid and precise identification of Cronobacter species is important for foodborne pathogen detection, however, commercial biochemical methods can only identify Cronobacter strains to genus level in most cases. To evaluate the power of mass spectrometry based on matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF MS) for Cronobacter species identification, 51 Cronobacter strains (eight reference and 43 wild strains) were identified by both MALDI-TOF MS and 16S rRNA gene sequencing. Biotyper RTC provided by Bruker identified all eight reference and 43 wild strains as Cronobacter species, which demonstrated the power of MALDI-TOF MS to identify Cronobacter strains to genus level. However, using the Bruker's database (6903 main spectra products) and Biotyper software, the MALDI-TOF MS analysis could not identify the investigated strains to species level. When MALDI-TOF MS analysis was performed using the combined in-house Cronobacter database and Bruker's database, bin setting, and unweighted pair group method with arithmetic mean (UPGMA) clustering, all the 51 strains were clearly identified into six Cronobacter species and the identification accuracy increased from 60% to 100%. We demonstrated that MALDI-TOF MS was reliable and easy-to-use for Cronobacter species identification and highlighted the importance of establishing a reliable database and improving the current data analysis methods by integrating the bin setting and UPGMA clustering. •Biotyper RTC can rapidly identify Cronobacter strains at genus but not species level.•MALDI-TOF MS analysis was optimized by integrating bin setting and UPGMA clustering.•Optimized method can identify Cronobacter species with high accuracy.