Usefulness of the MicroSeq 500 16S Ribosomal DNA-Based Bacterial Identification System for Identification of Clinically Significant Bacterial Isolates with Ambiguous Biochemical Profiles

摘要

Due to the inadequate automation in the amplification and sequencing procedures, the use of 16S rRNA gene sequence-based methods in clinical microbiology laboratories is largely limited to identification of strains that are difficult to identify by phenotypic methods. In this study, using conventional full-sequence 16S rRNA gene sequencing as the “gold standard,” we evaluated the usefulness of the MicroSeq 500 16S ribosomal DNA (rDNA)-based bacterial identification system, which involves amplification and sequencing of the first 527-bp fragment of the 16S rRNA genes of bacterial strains and analysis of the sequences using the database of the system, for identification of clinically significant bacterial isolates with ambiguous biochemical profiles. Among 37 clinically significant bacterial strains that showed ambiguous biochemical profiles, representing 37 nonduplicating aerobic gram-positive and gram-negative, anaerobic, and Mycobacterium species, the MicroSeq 500 16S rDNA-based bacterial identification system was successful in identifying 30 (81.1%) of them. Five (13.5%) isolates were misidentified at the genus level (Granulicatella adiacens was misidentified as Abiotrophia defectiva, Helcococcus kunzii was misidentified as Clostridium hastiforme, Olsenella uli was misidentified as Atopobium rimae, Leptotrichia buccalis was misidentified as Fusobacterium mortiferum, and Bergeyella zoohelcum was misidentified as Rimerella anatipestifer), and two (5.4%) were misidentified at the species level (Actinomyces odontolyticus was misidentified as Actinomyces meyeri and Arcobacter cryaerophilus was misidentified as Arcobacter butzleri). When the same 527-bp DNA sequences of these seven isolates were compared to the known 16S rRNA gene sequences in the GenBank, five yielded the correct identity, with good discrimination between the best and second best match sequences, meaning that the reason for misidentification in these five isolates was due to a lack of the 16S rRNA gene sequences of these bacteria in the database of the MicroSeq 500 16S rDNA-based bacterial identification system. In conclusion, the MicroSeq 500 16S rDNA-based bacterial identification system is useful for identification of most clinically important bacterial strains with ambiguous biochemical profiles, but the database of the MicroSeq 500 16S rDNA-based bacterial identification system has to be expanded in order to encompass the rarely encountered bacterial species and achieve better accuracy in bacterial identification.