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Shigella and enteroinvasive Escherichia coli (EIEC) cause human bacillary dysentery with similar invasion mechanisms and share similar physiological, biochemical and genetic characteristics. Differentiation of Shigella from EIEC is important for clinical diagnostic and epidemiological investigations. However, phylogenetically, Shigella and EIEC strains are composed of multiple clusters and are different forms of E. coli , making it difficult to find genetic markers to discriminate between Shigella and EIEC. In this study, we identified 10 Shigella clusters, seven EIEC clusters and 53 sporadic types of EIEC by examining over 17000 publicly available Shigella and EIEC genomes. We compared Shigella and EIEC accessory genomes to identify cluster-specific gene markers for the 17 clusters and 53 sporadic types. The cluster-specific gene markers showed 99.64% accuracy and more than 97.02% specificity. In addition, we developed a freely available in silico serotyping pipeline named Shigella EIEC Cluster Enhanced Serotype Finder (ShigEiFinder) by incorporating the cluster-specific gene markers and established Shigella and EIEC serotype-specific O antigen genes and modification genes into typing. ShigEiFinder can process either paired-end Illumina sequencing reads or assembled genomes and almost perfectly differentiated Shigella from EIEC with 99.70 and 99.74% cluster assignment accuracy for the assembled genomes and read mapping respectively. ShigEiFinder was able to serotype over 59 Shigella serotypes and 22 EIEC serotypes and provided a high specificity of 99.40% for assembled genomes and 99.38% for read mapping for serotyping. The cluster-specific gene markers and our new serotyping tool, ShigEiFinder (installable package: https://github.com/LanLab/ShigEiFinder, online tool: https://mgtdb.unsw.edu.au/ShigEiFinder/), will be useful for epidemiological and diagnostic investigations.

Shigella and enteroinvasive Escherichia coli (EIEC) cause human bacillary dysentery with similar invasion mechanisms and share similar physiological, biochemical and genetic characteristics. Differentiation of Shigella from EIEC is important for clinical diagnostic and epidemiological investigations. However, phylogenetically, Shigella and EIEC strains are composed of multiple clusters and are different forms of E. coli , making it difficult to find genetic markers to discriminate between Shigella and EIEC. In this study, we identified 10 Shigella clusters, seven EIEC clusters and 53 sporadic types of EIEC by examining over 17000 publicly available Shigella and EIEC genomes. We compared Shigella and EIEC accessory genomes to identify cluster-specific gene markers for the 17 clusters and 53 sporadic types. The cluster-specific gene markers showed 99.64% accuracy and more than 97.02% specificity. In addition, we developed a freely available in silico serotyping pipeline named Shigella EIEC Cluster Enhanced Serotype Finder (ShigEiFinder) by incorporating the cluster-specific gene markers and established Shigella and EIEC serotype-specific O antigen genes and modification genes into typing. ShigEiFinder can process either paired-end Illumina sequencing reads or assembled genomes and almost perfectly differentiated Shigella from EIEC with 99.70 and 99.74% cluster assignment accuracy for the assembled genomes and read mapping respectively. ShigEiFinder was able to serotype over 59 Shigella serotypes and 22 EIEC serotypes and provided a high specificity of 99.40% for assembled genomes and 99.38% for read mapping for serotyping. The cluster-specific gene markers and our new serotyping tool, ShigEiFinder (installable package: https://github.com/LanLab/ShigEiFinder, online tool: https://mgtdb.unsw.edu.au/ShigEiFinder/), will be useful for epidemiological and diagnostic investigations.

Escherichia albertii is a recently recognized species in the genus Escherichia that causes diarrhoea. The population structure, genetic diversity and genomic features have not been fully examined. Here, 169 E. albertii isolates from different sources and regions in China were sequenced and combined with 312 publicly available genomes (from additional 14 countries) for genomic analyses. The E. albertii population was divided into two clades and eight lineages, with lineage 3 (L3), L5 and L8 more common in China. Clinical isolates were observed in all clades/lineages. Virulence genes were found to be distributed differently among lineages: subtypes of the intimin encoding gene eae and the cytolethal distending toxin gene cdtB were lineage associated, and the second type three secretion system (ETT2) island was truncated in L3 and L6. Seven new eae subtypes and one new cdtB subtype (cdtB-VI) were identified. Alarmingly, 85.9 % of the Chinese E. albertii isolates were predicted to be multidrug-resistant (MDR) with 35.9 % harbouring genes capable of conferring resistance to 10 to 14 different drug classes. The majority of the MDR isolates were of poultry source from China and belonged to four sequence types (STs) [ST4638, ST4479, ST4633 and ST4488]. Thirty-four plasmids with some carrying MDR and virulence genes, and 130 prophages were identified from 17 complete E. albertii genomes. The 130 intact prophages were clustered into five groups, with group five prophages harbouring more virulence genes. We further identified three E. albertii specific genes as markers for the identification of this species. Our findings provided fundamental insights into the population structure, virulence variation and drug resistance of E. albertii .

Escherichia albertii is a recently recognized species in the genus Escherichia that causes diarrhoea. The population structure, genetic diversity and genomic features have not been fully examined. Here, 169 E. albertii isolates from different sources and regions in China were sequenced and combined with 312 publicly available genomes (from additional 14 countries) for genomic analyses. The E. albertii population was divided into two clades and eight lineages, with lineage 3 (L3), L5 and L8 more common in China. Clinical isolates were observed in all clades/lineages. Virulence genes were found to be distributed differently among lineages: subtypes of the intimin encoding gene eae and the cytolethal distending toxin gene cdtB were lineage associated, and the second type three secretion system (ETT2) island was truncated in L3 and L6. Seven new eae subtypes and one new cdtB subtype (cdtB-VI) were identified. Alarmingly, 85.9 % of the Chinese E. albertii isolates were predicted to be multidrug-resistant (MDR) with 35.9 % harbouring genes capable of conferring resistance to 10 to 14 different drug classes. The majority of the MDR isolates were of poultry source from China and belonged to four sequence types (STs) [ST4638, ST4479, ST4633 and ST4488]. Thirty-four plasmids with some carrying MDR and virulence genes, and 130 prophages were identified from 17 complete E. albertii genomes. The 130 intact prophages were clustered into five groups, with group five prophages harbouring more virulence genes. We further identified three E. albertii specific genes as markers for the identification of this species. Our findings provided fundamental insights into the population structure, virulence variation and drug resistance of E. albertii .

Salmonella enterica serovar Enteritidis is a major cause of foodborne Salmonella infections and outbreaks in humans. Effective surveillance and timely outbreak detection are essential for public health control. Multilevel genome typing (MGT) with multiple levels of resolution has been previously demonstrated as a promising tool for this purpose. In this study, we developed MGT with nine levels for S. Enteritidis and characterised the genomic epidemiology of S. Enteritidis in detail. We examined 26 670 publicly available S. Enteritidis genome sequences from isolates spanning 101 years from 86 countries to reveal their spatial and temporal distributions. Using the lower resolution MGT levels, globally prevalent and regionally restricted sequence types (STs) were identified; avian associated MGT4-STs were found that were common in human cases in the USA; temporal trends were observed in the UK with MGT5-STs from 2014 to 2018 revealing both long lived endemic STs and the rapid expansion of new STs. Using MGT3 to MGT6, we identified multidrug resistance (MDR) associated STs at various MGT levels, which improves precision of detection and global tracking of MDR clones. We also found that the majority of the global S. Enteritidis population fell within two predominant lineages, which had significantly different propensity of causing large scale outbreaks. An online open MGT database has been established for unified international surveillance of S. Enteritidis. We demonstrated that MGT provides a flexible and high-resolution genome typing tool for S. Enteritidis surveillance and outbreak detection.

Salmonella enterica serovar Enteritidis is a major cause of foodborne Salmonella infections and outbreaks in humans. Effective surveillance and timely outbreak detection are essential for public health control. Multilevel genome typing (MGT) with multiple levels of resolution has been previously demonstrated as a promising tool for this purpose. In this study, we developed MGT with nine levels for S. Enteritidis and characterised the genomic epidemiology of S. Enteritidis in detail. We examined 26 670 publicly available S. Enteritidis genome sequences from isolates spanning 101 years from 86 countries to reveal their spatial and temporal distributions. Using the lower resolution MGT levels, globally prevalent and regionally restricted sequence types (STs) were identified; avian associated MGT4-STs were found that were common in human cases in the USA; temporal trends were observed in the UK with MGT5-STs from 2014 to 2018 revealing both long lived endemic STs and the rapid expansion of new STs. Using MGT3 to MGT6, we identified multidrug resistance (MDR) associated STs at various MGT levels, which improves precision of detection and global tracking of MDR clones. We also found that the majority of the global S. Enteritidis population fell within two predominant lineages, which had significantly different propensity of causing large scale outbreaks. An online open MGT database has been established for unified international surveillance of S. Enteritidis. We demonstrated that MGT provides a flexible and high-resolution genome typing tool for S. Enteritidis surveillance and outbreak detection.

Campylobacter concisusis an emerging enteric pathogen that is associated with several gastrointestinal diseases, such as inflammatory bowel disease (IBD), which includes Crohn’s disease (CD) and ulcerative colitis (UC). Currently, only three completeC. concisusgenomes are available and more completeC. concisusgenomes are needed in order to better understand the genomic features and pathogenicity of this emerging pathogen. DNA extracted from 22C.concisusstrains were subjected to Oxford Nanopore genome sequencing. Complete genome assembly was performed using Nanopore genome data in combination with previously reported short-read Illumina data. Genome features of completeC. concisusgenomes were analysed using bioinformatic tools. The enteric disease associations ofC. concisusplasmids were examined using 239C.concisusstrains and confirmed using PCRs. Proteomic analysis was used to examine T6SS secreted proteins. We successfully obtained 13 completeC. concisusgenomes in this study. Analysis of 16 completeC. concisusgenomes (3 from public databases) identified multiple novel plasmids. pSma1 plasmid was found to be associated with severe UC. Sec-SRP, Tat and T6SS were found to be the main secretion systems inC. concisusand proteomic data showed a functional T6SS despite the lack of ClpV. T4SS was found in 25% of completeC. concisusgenomes. This study also found that GS2 strains had larger genomes and higher GC content than GS1 strains and more often had plasmids. In conclusion, this study provides fundamental genomic data for understandingC. concisusplasmids, genomospecies features, evolution, secretion systems and pathogenicity.

Salmonella enterica serovar Typhimurium is the leading cause of salmonellosis in Australia, and the ability to identify outbreaks and their sources is vital to public health. Here, we examined the utility of whole-genome sequencing (WGS), including complete genome sequencing with Oxford Nanopore technologies, in examining 105 isolates from an endemic multi-locus variable number tandem repeat analysis (MLVA) type over 5 years. The MLVA type was very homogeneous, with 90 % of the isolates falling into groups with a five SNP cut-off. We developed a new two-step approach for outbreak detection using WGS. The first clustering at a zero single nucleotide polymorphism (SNP) cut-off was used to detect outbreak clusters that each occurred within a 4 week window and then a second clustering with dynamically increased SNP cut-offs were used to generate outbreak investigation clusters capable of identifying all outbreak cases. This approach offered optimal specificity and sensitivity for outbreak detection and investigation, in particular of those caused by endemic MLVA types or clones with low genetic diversity. We further showed that inclusion of complete genome sequences detected no additional mutational events for genomic outbreak surveillance. Phylogenetic analysis found that the MLVA type was likely to have been derived recently from a single source that persisted over 5 years, and seeded numerous sporadic infections and outbreaks. Our findings suggest that SNP cut-offs for outbreak cluster detection and public-health surveillance should be based on the local diversity of the relevant strains over time. These findings have general applicability to outbreak detection of bacterial pathogens.

Salmonella enterica serovar Typhimurium is the leading cause of salmonellosis in Australia, and the ability to identify outbreaks and their sources is vital to public health. Here, we examined the utility of whole-genome sequencing (WGS), including complete genome sequencing with Oxford Nanopore technologies, in examining 105 isolates from an endemic multi-locus variable number tandem repeat analysis (MLVA) type over 5 years. The MLVA type was very homogeneous, with 90 % of the isolates falling into groups with a five SNP cut-off. We developed a new two-step approach for outbreak detection using WGS. The first clustering at a zero single nucleotide polymorphism (SNP) cut-off was used to detect outbreak clusters that each occurred within a 4 week window and then a second clustering with dynamically increased SNP cut-offs were used to generate outbreak investigation clusters capable of identifying all outbreak cases. This approach offered optimal specificity and sensitivity for outbreak detection and investigation, in particular of those caused by endemic MLVA types or clones with low genetic diversity. We further showed that inclusion of complete genome sequences detected no additional mutational events for genomic outbreak surveillance. Phylogenetic analysis found that the MLVA type was likely to have been derived recently from a single source that persisted over 5 years, and seeded numerous sporadic infections and outbreaks. Our findings suggest that SNP cut-offs for outbreak cluster detection and public-health surveillance should be based on the local diversity of the relevant strains over time. These findings have general applicability to outbreak detection of bacterial pathogens.