Genomic characterization and phylogenetic analysis of<i>Salmonella enterica</i>serovar Javiana

Hudson, Lauren K.; Constantine-Renna, Lisha; Thomas, Linda S; Moore, Charles A.; Qian, Xiaorong; Garman, Katie; Dunn, John R.; Denes, Thomas G.

doi:10.7717/peerj.10256

Cited by 4 publications

(6 citation statements)

References 139 publications

(194 reference statements)

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“…ceBGs are equivalent to eBurst groups (eBGs) from legacy 7-gene MLST and correspond to serovar designations ( 20 , 21 ). Typically, monophyletic serovars consist of a single eBG, while polyphyletic serovars consist of multiple eBGs ( 22 – 25 ). Lineage I isolates belonged to ceBGs 370, 12161, and 135213, lineage II isolates belonged to ceBGs 44, 391, and 401, and lineage III isolates belonged to ceBGs 120 and 65092 ( Table 1 , Fig.…”

Section: Resultsmentioning

confidence: 99%

“…The original prediction for amikacin resistance was 100%, due to all isolates containing the aac(6′)-Iaa gene. However, this gene has been shown to be cryptic and no longer confer phenotypic resistance to aminoglycosides ( 25 , 47 , 48 ), so the results were adjusted accordingly. The NARMS human clinical ABR data were downloaded from NARMS Now ( 33 ) for comparison purposes.…”

Section: Methodsmentioning

confidence: 99%

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Phylogeny and Genomic Characterization of Clinical Salmonella enterica Serovar Newport Collected in Tennessee

et al. 2023

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Section: Resultsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Phylogeny and Genomic Characterization of Clinical Salmonella enterica Serovar Newport Collected in Tennessee

et al. 2023

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“…Using the approach described in Methods - Putative non-monophyletic serovar prediction, we found 265/537 (49.3 %) putative non-monophyletic serovars, including Enteritidis, Typhimurium, Newport, Kentucky and Javiana. Subsequent manual literature curation indicated that 18 % of the evaluated serovars had previously been reported to be polyphyletic or paraphyletic [5, 37–48]. To confirm the validity of our approach to predict monophyly, we performed maximum-likelihood-based phylogenetic reconstruction of two serovars Choleraesuis and Paratyphi C that were predicted as non-monophyletic by our approach, but previously reported as monophyletic [49].…”

Section: Resultsmentioning

confidence: 99%

Section: Characterization Of Putative Non-monophyletic Serovarsmentioning

confidence: 99%

Large-scale comparative genomics to refine the organization of the global Salmonella enterica population structure

Hsiao

2022

Microbial Genomics

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The White–Kauffmann–Le Minor (WKL) scheme is the most widely used Salmonella typing scheme for reporting the disease prevalence of the enteric pathogen. With the advent of whole-genome sequencing (WGS), in silico methods have increasingly replaced traditional serotyping due to reproducibility, speed and coverage. However, despite integrating genomic-based typing by in silico serotyping tools such as SISTR, in silico serotyping in certain contexts remains ambiguous and insufficiently informative. Specifically, in silico serotyping does not attempt to resolve polyphyly. Furthermore, in spite of the widespread acknowledgement of polyphyly from genomic studies, the prevalence of polyphyletic serovars is not well characterized. Here, we applied a genomics approach to acquire the necessary resolution to classify genetically discordant serovars and propose an alternative typing scheme that consistently reflect natural Salmonella populations. By accessing the unprecedented volume of bacterial genomic data publicly available in GenomeTrakr and PubMLST databases (>180 000 genomes representing 723 serovars), we characterized the global Salmonella population structure and systematically identified putative non-monophyletic serovars. The proportion of putative non-monophyletic serovars was estimated higher than previous reports, reinforcing the inability of antigenic determinants to depict the complexity of Salmonella evolutionary history. We explored the extent of genetic diversity masked by serotyping labels and found significant intra-serovar molecular differences across many clinically important serovars. To avoid false discovery due to incorrect in silico serotyping calls, we cross-referenced reported serovar labels and concluded a low error rate in in silico serotyping. The combined application of clustering statistics and genome-wide association methods demonstrated effective characterization of stable bacterial populations and explained functional differences. The collective methods adopted in our study have practical values in establishing genomic-based typing nomenclatures for an entire microbial species or closely related subpopulations. Ultimately, we foresee an improved typing scheme to be a hybrid that integrates both genomic and antigenic information such that the resolution from WGS is leveraged to improve the precision of subpopulation classification while preserving the common names defined by the WKL scheme.

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“…By this approach, we found 265/537 (49.3%) putative non-monophyletic serovars including Enteritidis, Typhimurium, Newport, Kentucky, and Javiana. Subsequent manual literature curation indicated that 18% of the evaluated serovars had been previously reported to be polyphyletic or paraphyletic (5,(33)(34)(35)(36)(37)(38)(39)(40)(41). Furthermore, the evaluation of the maximum distance required to link genomes of the same in-silico serovar assignments in a single cluster revealed genomes of 209/537 (38.9%) serovars required a distance of >2,000 allelic differences to be linked in a single cluster (Fig.…”

Section: Characterization Of Putative Non-monophyletic Serovarsmentioning

confidence: 95%

Large-scale comparative genomics of Salmonella enterica to refine the organization of the global Salmonella population structure

2021

Preprint

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Since the introduction of the White-Kauffmann-Le Minor (WKL) scheme for Salmonella serotyping, the nomenclature remains the most widely used for reporting the disease prevalence of Salmonella enterica across the globe. With the advent of whole genome sequencing (WGS), traditional serotyping has been increasingly replaced by in-silico methods that couple the detection of genetic variations in antigenic determinants with sequence-based typing. However, despite the integration of genomic-based typing by in-silico serotyping tools such as SeqSero2 and SISTR, in-silico serotyping in certain contexts remains ambiguous and insufficiently informative due to polyphyletic serovars. Furthermore, in spite of the widespread acknowledgement of polyphyly from genomic studies, the serotyping nomenclature remains unaltered. To prompt refinements to the Salmonella typing nomenclature for disease reporting, we herein performed a systematic characterization of putative polyphyletic serovars and the global Salmonella population structure by comparing 180,098 Salmonella genomes (representing 723 predicted serovars) from GenomeTrakr and PubMLST databases. We identified a range of core genome MLST typing thresholds that result in stable population structure, potentially suitable as the foundation of a genomic-based typing nomenclature for longitudinal surveillance. From the genomic comparisons of hundreds of predicted serovars, we demonstrated that in-silico serotyping classifications do not consistently reflect the population divergence observed at the genomic level. The organization of Salmonella subpopulations based on antigenic determinants can be confounded by homologous recombination and niche adaptation, resulting in shared classification of highly divergent genomes and misleading distinction between highly similar genomes. In consideration of the pivotal role of Salmonella serotyping, a compendium of putative polyphyletic serovars was compiled and made publicly available to provide additional context for future interpretations of in-silico serotyping results in disease surveillance settings. To refine the typing nomenclatures used in Salmonella surveillance reports, we foresee an improved typing scheme to be a hybrid that integrates both genomic and antigenic information such that the resolution from WGS is leveraged to improve the precision of subpopulation classifications while preserving the common names defined by the WKL scheme. Lastly, we stress the importance of controlled vocabulary integration for typing information in open data settings in order for the global Salmonella population dynamics to be fully trackable.

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Genomic characterization and phylogenetic analysis ofSalmonella entericaserovar Javiana

Cited by 4 publications

References 139 publications

Phylogeny and Genomic Characterization of Clinical Salmonella enterica Serovar Newport Collected in Tennessee

Phylogeny and Genomic Characterization of Clinical Salmonella enterica Serovar Newport Collected in Tennessee

Large-scale comparative genomics to refine the organization of the global Salmonella enterica population structure

Large-scale comparative genomics of Salmonella enterica to refine the organization of the global Salmonella population structure

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