In silico analysis of 16S rRNA gene sequencing based methods for identification of medically important aerobic Gram-negative bacteria

Abstract

This study provides guidelines on the usefulness of full and 527 bp 16S rRNA gene sequencing and Microseq databases for identifying medically important aerobic Gram-negative bacteria. Overall, full and 527 bp 16S rRNA gene sequencing can identify 26.1 % and 32.6 %, respectively, of medically important aerobic Gram-negative bacteria confidently to the species level, whereas the full-MicroSeq and 500-MicroSeq databases can identify 15.2 % and 26.1 %, respectively, of medically important aerobic Gram-negative bacteria confidently to the species level. Among the major groups of aerobic Gram-negative bacteria, the methods and databases are least useful for identification of Aeromonas, Bordetella and Bartonella species. None of the Aeromonas species can be confidently or doubtfully identified, whereas only 0 % and 0-33.3 % of Bordetella species and 0-10 % and 0-10 % of Bartonella species can be confidently and doubtfully identified, respectively. On the other hand, these methods and databases are most useful for identification of members of the families Pasteurellaceae and Legionellaceae and Campylobacter species: 29.6-59.3 % and 7.4-18.5 % of members of Pasteurellaceae, 36-52 % and 12-24 % of members of Legionellaceae, and 26.7-60 % and 0-13.3 % of Campylobacter species can be confidently and doubtfully identified, respectively. Thirty-nine medically important aerobic Gram-negative bacteria that should be confidently identified by full 16S rRNA gene sequencing are not included in the full-MicroSeq database. Twenty-three medically important aerobic Gram-negative bacteria that should be confidently identified by 527 bp 16S rRNA gene sequencing are not included in the 500-MicroSeq database. Compared with results of our previous studies on anaerobic and Gram-positive bacteria, full and 527 bp 16S rRNA gene sequencing are able to confidently identify significantly more anaerobic Gram-positive and Gramnegative bacteria than aerobic Gram-positive and Gram-negative bacteria.

Benchmarking of Methods for Genomic Taxonomy

“…Examples, which are also observed in this study, include its inadequacy for the delineation of species within the Borrelia burgdorferi sensu lato complex and the Mycobacterium tuberculosis complex (35). Similarly, in silico studies of the applicability of the 16S rRNA gene for the identification of medically important bacteria led to the authors concluding that although the method is useful for identification to the genus level, it is able to identify only 62% of anaerobic bacteria (36) and less than 30% of aerobic bacteria (37) confidently to the species level.…”

Genome sequence analyses show that Neisseria oralis is the same species as ‘ Neisseria mucosa var. heidelbergensis’

“…The genus Neisseria is an instructive model for the development of novel bacterial characterization techniques as it comprises a number of organisms poorly distinguished by conventional methods including biochemical tests and 16S and 23S rRNA analyses (Harmsen et al , 2001; Teng et al , 2011; Zhu et al , 2003). Different species of the genus Neisseria nevertheless exhibit distinct and stable differences in their phenotypes, particularly as regards their pathogenicity (Maiden, 2008).…”

“…The rMLST approach provides more resolution of sequence clusters than 16S or 23S rRNA gene phylogenies and has been applied at the whole domain level (Jolley et al, 2012a) and to examine species and subspecies structuring within the genus Neisseria (Bennett et al, 2012;Jolley et al, 2012b). The genus Neisseria is an instructive model for the development of novel bacterial characterization techniques as it comprises a number of organisms poorly distinguished by conventional methods including biochemical tests and 16S and 23S rRNA analyses (Harmsen et al, 2001;Teng et al, 2011;Zhu et al, 2003). Different species of the genus Neisseria nevertheless exhibit distinct and stable differences in their phenotypes, particularly as regards their pathogenicity (Maiden, 2008).…”

Genomic analysis of Elizabethkingia species from aquatic environments: Evidence for potential clinical transmission

“…Interestingly, all speciation methods we used, including MALDI-TOF MS, Kraken2 and SpeciesFinder, gave conflicting results. The issues regarding MS and Kraken2 misidentifications likely arose from using standard databases ( Lin et al., 2019a ) while SpeciesFinder uses 16S rRNA gene sequences, which are known to be limited for taxonomic purposes ( Larsen et al., 2014 ) with studies demonstrating less than 30% accuracy for aerobic bacteria to the species level ( Teng et al., 2011 ). These data suggest that in lieu of WGS, future Elizabethkingia spp.…”