Genome-wide networks reveal emergence of epidemic strains of Salmonella Enteritidis
Copyright © 2022 The Authors. Published by Elsevier Ltd.. All rights reserved..
OBJECTIVES: To enhance monitoring of high-burden foodborne pathogens, there is opportunity to combine pangenome data with network analysis.
METHODS: Salmonella enterica subspecies Enterica serovar Enteritidis isolates were referred to the New South Wales (NSW) Enteric Reference Laboratory between August 2015 and December 2019 (1033 isolates in total), inclusive of a confirmed outbreak. All isolates underwent whole genome sequencing. Distances between genomes were quantified by in silico multiple-locus variable-number tandem repeat analysis (MLVA) as well as core single nucleotide polymorphisms (SNPs), which informed the construction of undirected networks. Centrality-prevalence spaces were generated from the undirected networks. Components on the undirected SNP network were considered alongside a phylogenetic tree representation.
RESULTS: Outbreak isolates were identified as distinct components on the MLVA and SNP networks. The MLVA network-based centrality-prevalence space did not delineate the outbreak, whereas the outbreak was delineated in the SNP network-based centrality-prevalence space. Components on the undirected SNP network showed a high concordance to the SNP clusters based on phylogenetic analysis.
CONCLUSIONS: Bacterial whole-genome data in network-based analysis can improve the resolution of population analysis. High concordance of network components and SNP clusters is promising for rapid population analyses of foodborne Salmonella spp. owing to the low overhead of network analysis.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2022 |
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| Erschienen: |
2022 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:117 |
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| Enthalten in: |
International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases - 117(2022) vom: 15. Apr., Seite 65-73 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Svahn, Adam J [VerfasserIn] |
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| Links: |
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| Themen: |
Foodborne pathogen |
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| Anmerkungen: |
Date Completed 31.03.2022 Date Revised 01.04.2022 published: Print-Electronic Citation Status MEDLINE |
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| doi: |
10.1016/j.ijid.2022.01.056 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
NLM336421559 |
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| 245 | 1 | 0 | |a Genome-wide networks reveal emergence of epidemic strains of Salmonella Enteritidis |
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| 500 | |a Date Revised 01.04.2022 | ||
| 500 | |a published: Print-Electronic | ||
| 500 | |a Citation Status MEDLINE | ||
| 520 | |a Copyright © 2022 The Authors. Published by Elsevier Ltd.. All rights reserved. | ||
| 520 | |a OBJECTIVES: To enhance monitoring of high-burden foodborne pathogens, there is opportunity to combine pangenome data with network analysis | ||
| 520 | |a METHODS: Salmonella enterica subspecies Enterica serovar Enteritidis isolates were referred to the New South Wales (NSW) Enteric Reference Laboratory between August 2015 and December 2019 (1033 isolates in total), inclusive of a confirmed outbreak. All isolates underwent whole genome sequencing. Distances between genomes were quantified by in silico multiple-locus variable-number tandem repeat analysis (MLVA) as well as core single nucleotide polymorphisms (SNPs), which informed the construction of undirected networks. Centrality-prevalence spaces were generated from the undirected networks. Components on the undirected SNP network were considered alongside a phylogenetic tree representation | ||
| 520 | |a RESULTS: Outbreak isolates were identified as distinct components on the MLVA and SNP networks. The MLVA network-based centrality-prevalence space did not delineate the outbreak, whereas the outbreak was delineated in the SNP network-based centrality-prevalence space. Components on the undirected SNP network showed a high concordance to the SNP clusters based on phylogenetic analysis | ||
| 520 | |a CONCLUSIONS: Bacterial whole-genome data in network-based analysis can improve the resolution of population analysis. High concordance of network components and SNP clusters is promising for rapid population analyses of foodborne Salmonella spp. owing to the low overhead of network analysis | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a Foodborne pathogen | |
| 650 | 4 | |a Genotype network | |
| 650 | 4 | |a Salmonella Enteritidis | |
| 700 | 1 | |a Chang, Sheryl L |e verfasserin |4 aut | |
| 700 | 1 | |a Rockett, Rebecca J |e verfasserin |4 aut | |
| 700 | 1 | |a Cliff, Oliver M |e verfasserin |4 aut | |
| 700 | 1 | |a Wang, Qinning |e verfasserin |4 aut | |
| 700 | 1 | |a Arnott, Alicia |e verfasserin |4 aut | |
| 700 | 1 | |a Ramsperger, Marc |e verfasserin |4 aut | |
| 700 | 1 | |a Sorrell, Tania C |e verfasserin |4 aut | |
| 700 | 1 | |a Sintchenko, Vitali |e verfasserin |4 aut | |
| 700 | 1 | |a Prokopenko, Mikhail |e verfasserin |4 aut | |
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