Comparison of 16S rRNA, 23S rRNA andgyrB genes sequences in phylogenetic relationships ofShigella isolates from Iran

Historical, current, and emerging tools for identification and serotyping of Shigella

The Shigella genus includes serious foodborne disease etiologic agents, with 4 species and 54 serotypes. Identification at species and serotype levels is a crucial task in microbiological laboratories. Nevertheless, the genetic similarity between Shigella spp. and Escherichia coli challenges the correct identification and serotyping of Shigella spp., with subsequent negative repercussions on surveillance, epidemiological investigations, and selection of appropriate treatments. For this purpose, multiple techniques have been developed historically ranging from phenotype-based methods and single or multilocus molecular techniques to whole-genome sequencing (WGS). To facilitate the selection of the most relevant method, we herein provide a global overview of historical and emerging identification and serotyping techniques with a particular focus on the WGS-based approaches. This review highlights the excellent discriminatory power of WGS to more accurately elucidate the epidemiology of Shigella spp., disclose novel promising genomic targets for surveillance methods, and validate previous well-established methods.

Identification of nonserotypeable Shigella spp. using genome sequencing: a step forward

AIM

Sequencing technology has replaced conventional methods in identifying and characterizing bacterial pathogens. We characterized 23 nonserotypeable Shigella that biochemically resembled Shigella spp. using whole genome sequencing.

MATERIALS & METHODS

Genome sequences were analyzed using online tools based on 16S rRNA, k-mer, gyrB sequences and analysis of O-antigen arrangement was done using PATRIC database for species identification. Sequence types, plasmid types, antimicrobial resistance and virulence genes were also investigated.

RESULTS

The SpeciesFinder using 16S rRNA sequences identified only 74% of the isolates, whereas KmerFinder and gyrB sequence analysis identified 100% of the isolates to its species level. Antimicrobial resistance, virulence and plasmid incompatibility groups were identified in all the isolates. Sequence types were determined.

CONCLUSION

This study shows that whole genome sequencing approach for Shigella O-antigen analysis has greater discriminative power than other methods using different bioinformatics pipeline for identification of nonserotypeable Shigella.