In Silico Serotyping Based on Whole-Genome Sequencing Improves the Accuracy of Shigella Identification

Abstract

Bacteria of the genus Shigella, consisting of 4 species and Ͼ50 serotypes, cause shigellosis, a foodborne disease of significant morbidity, mortality, and economic loss worldwide. Classical Shigella identification based on selective media and serology is tedious, time-consuming, expensive, and not always accurate. A molecular diagnostic assay does not distinguish Shigella at the species level or from enteroinvasive Escherichia coli (EIEC). We inspected genomic sequences from 221 Shigella isolates and observed low concordance rates between conventional designation and molecular serotyping: 86.4% and 80.5% at the species and serotype levels, respectively. Serotype determinants for 6 additional serotypes were identified. Examination of differentiation gene markers commonly perceived as characteristic hallmarks in Shigella showed high variability among different serotypes. Using this information, we developed ShigaTyper, an automated workflow that utilizes limited computational resources to accurately and rapidly determine 59 Shigella serotypes using Illumina paired-end whole-genome sequencing (WGS) reads. Shigella serotype determinants and species-specific diagnostic markers were first identified through read alignment to an in-house curated reference sequence database. Relying on sequence hits that passed a threshold level of coverage and accuracy, serotype could be unambiguously predicted within 1 min for an average-size WGS sample of ϳ500 MB. Validation with WGS data from 380 isolates showed an accuracy rate of 98.2%. This pipeline is the first step toward building a comprehensive WGS-based analysis pipeline of Shigella spp. in a field laboratory setting, where speed is essential and resources need to be more cost-effectively dedicated. IMPORTANCE Shigella causes diarrheal disease with serious public health implications. However, conventional Shigella identification methods are laborious and timeconsuming and can be erroneous due to the high similarity between Shigella and enteroinvasive Escherichia coli (EIEC) and cross-reactivity between serotyping antisera. Further, serotype interpretation is complicated for inexperienced users. To develop an easier method with higher accuracy based on whole-genome sequencing (WGS) for Shigella serotyping, we systematically examined genomic information of Shigella isolates from 53 serotypes to define rules for differentiation and serotyping. We created ShigaTyper, an automated pipeline that accurately and rapidly excludes non-Shigella isolates and identifies 59 Shigella serotypes using Illumina paired-end WGS reads. A serotype can be unambiguously predicted at a data processing speed of 538 MB/min with 98.2% accuracy from a regular laptop. Once it is installed, training in bioinformatics analysis and Shigella genetics is not required. This pipeline is particularly useful to general microbiologists in field laboratories.

Complete microbial genomes for public health in Australia and Southwest Pacific

“…AMR SNPs were detected using Ariba (35) v2.14.4 using the CARD database (36) and the built-in TB database. In silico serotyping was performed using emmtyper (37) v0.1.0 for Streptococcus pyogenes , kleborate (38) v0.3.0 for Klebsiella pneumoniae , legsta (39) v0.3.2 for Legionella pneumophilia , lissero (40) v0.2 for Listeria monocytogenes , meningotype (41) v0.8.2-beta for N. meningitidis , ngmaster (42) v0.5.5 for N. gonorrhoeae , seroba (43) v1.0.1 for Streptococcus pneumoniae , shigatyper (44) v1.0.5 for Shigella spp ., sistr (45) v1.0.2 for Salmonella enterica , and srst2 (46) v0.2.0 using the EcOH DB for Escherichia coli .…”

Genetic Characterization of the O-Antigen and Development of a Molecular Serotyping Scheme for Enterobacter cloacae

“…Because of these advantages, multiplex PCR has been applied widely for the detection of many bacterial strains (van der Veer et al, 2018;Kwack et al, 2020;Collins et al, 2020). In the past few years, several WGS-based in silico serotyping approaches have been presented and showed better resolution compared to conventional methods, and have been utilized for epidemiological investigation and tracing (Thrane et al, 2016;Ibrahim and Morin, 2018;Wu et al, 2019). However, all of those studies are based on a key prerequisite that is the full and deep understanding of the O-antigen and the genetic basis for its diversity/variation.…”

SeroTools: a Python package for Salmonella serotype data analysis

“…In recent years, significant technological advances have resulted in a wide range of molecular-based subtyping options, including highly sensitive approaches based on whole genome sequencing (WGS). One such approach involves the application of software tools to WGS data for in silico serovar prediction (Joensen, Tetzschner, Iguchi, Aarestrup, & Scheutz, 2015;Laing, Bessonov, Sung, & La Rose, n.d.;Watts & Holt, 2019;Wu, Lau, Lee, Lau, & Payne, 2019;Zhang et al, 2019Zhang et al, , 2015, including real-time prediction (Feng et al, 2020). SeqSero (a Salmonella-specific tool) and other in silico serovar designation tools have been adopted by U.S. public health agencies as an alternative to serological testing and for quality control applications (Dowdy, 2017;Timme, Sanchez Leon, & Allard, 2019).…”