title: Use of the MicroSeq 500 16S rRNA gene-based sequencing for identification of bacterial isolates that commercial automated systems failed to identify correctly.
abstract: Reliable automated identification and susceptibility testing of clinically relevant bacteria is an essential routine for microbiology laboratories, thus improving patient care. Examples of automated identification systems include the Phoenix (Becton Dickinson) and the VITEK 2 (bioMerieux). However, more and more frequently, microbiologists must isolate "difficult" strains that automated systems often fail to identify. An alternative approach could be the genetic identification of isolates; this is based on 16S rRNA gene sequencing and analysis. The aim of the present study was to evaluate the possible use of MicroSeq 500 (Applera) for sequencing the 16S rRNA gene to identify isolates whose identification is unobtainable by conventional systems. We analyzed 83 "difficult" clinical isolates: 25 gram-positive and 58 gram-negative strains that were contemporaneously identified by both systems--VITEK 2 and Phoenix--while genetic identification was performed by using the MicroSeq 500 system. The results showed that phenotypic identifications by VITEK 2 and Phoenix were remarkably similar: 74% for gram-negative strains (43 of 58) and 80% for gram-positive strains were concordant by both systems and also concordant with genetic characterization. The exceptions were the 15 gram-negative and 9 gram-positive isolates whose phenotypic identifications were contrasting or inconclusive. For these, the use of MicroSeq 500 was fundamental to achieving species identification. In clinical microbiology the use of MicroSeq 500, particularly for strains with ambiguous biochemical profiles (including slow-growing strains), identifies strains more easily than do conventional systems. Moreover, MicroSeq 500 is easy to use and cost-effective, making it applicable also in the clinical laboratory.
authors.affiliation: Department of Experimental Medicine and Biochemical Sciences, Tor Vergata University of Rome, Via Montpellier 1, 00133 Rome, Italy. carla.fontana@uniroma2.it
authors.forename: Carla
authors.initials: C
authors.lastname: Fontana
authors.forename: Marco
authors.initials: M
authors.lastname: Favaro
authors.forename: Marco
authors.initials: M
authors.lastname: Pelliccioni
authors.forename: Enrico Salvatore
authors.initials: ES
authors.lastname: Pistoia
authors.forename: Cartesio
authors.initials: C
authors.lastname: Favalli
mesh_terms: D015373:Bacterial Typing Techniques; D004269:DNA, Bacterial / Q000032:analysis; D004275:DNA, Ribosomal / Q000032:analysis; D020459:Genes, rRNA; D006090:Gram-Negative Bacteria / Q000145:classification* / Q000235:genetics / Q000302:isolation & purification; D016905:Gram-Negative Bacterial Infections / Q000382:microbiology; D006094:Gram-Positive Bacteria / Q000145:classification* / Q000235:genetics / Q000302:isolation & purification; D016908:Gram-Positive Bacterial Infections / Q000382:microbiology; D006801:Humans; D008969:Molecular Sequence Data; D012336:RNA, Ribosomal, 16S / Q000235:genetics*; D017422:Sequence Analysis, DNA
chemical_list: D004269:DNA, Bacterial; D004275:DNA, Ribosomal; D012336:RNA, Ribosomal, 16S