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Updated: Apr 24, 2026

Identification of Rare Bacterial Pathogens by 16S rRNA Gene Sequencing and MALDI-TOF MS
Published on: July 11, 2016
The construction and evaluation of reference spectra for the identification of human pathogenic microorganisms by
Di Xiao1, Changyun Ye1, Huifang Zhang1
1State Key Laboratory for Infectious Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China; Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Hangzhou, China.
Abstract:
Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) is an emerging technique for the rapid and high-throughput identification of microorganisms. There remains a dearth of studies in which a large number of pathogenic microorganisms from a particular country or region are utilized for systematic analyses. In this study, peptide mass reference spectra (PMRS) were constructed and evaluated from numerous human pathogens (a total of 1019 strains from 94 species), including enteric (46 species), respiratory (21 species), zoonotic (17 species), and nosocomial pathogens (10 species), using a MALDI-TOF MS Biotyper system (MBS). The PMRS for 380 strains of 52 species were new contributions to the original reference database (ORD). Compared with the ORD, the new reference database (NRD) allowed for 28.2% (from 71.5% to 99.7%) and 42.3% (from 51.3% to 93.6%) improvements in identification at the genus and species levels, respectively. Misidentification rates were 91.7% and 57.1% lower with the NRD than with the ORD for genus and species identification, respectively. Eight genera and 25 species were misidentified. For genera and species that are challenging to accurately identify, identification results must be manually determined and adjusted in accordance with the database parameters. Through augmentation, the MBS demonstrated a high identification accuracy and specificity for human pathogenic microorganisms. This study sought to provide theoretical guidance for using PMRS databases in various fields, such as clinical diagnosis and treatment, disease control, quality assurance, and food safety inspection.
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