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Comparing serotyping with whole-genome sequencing for subtyping of non-typhoidal Salmonella enterica: a large-scale analysis of 37 serotypes with a public health impact in the USA

Serotyping has traditionally been used for subtyping of non-typhoidal Salmonella (NTS) isolates. However, its discriminatory power is limited, which impairs its use for epidemiological investigations of source attribution. Whole-genome sequencing (WGS) analysis allows more accurate subtyping of stra...

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Autores principales: Elnekave, Ehud, Hong, Samuel L., Lim, Seunghyun, Johnson, Timothy J., Perez, Andres, Alvarez, Julio
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Microbiology Society 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7643971/
https://www.ncbi.nlm.nih.gov/pubmed/32845830
http://dx.doi.org/10.1099/mgen.0.000425
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author Elnekave, Ehud
Hong, Samuel L.
Lim, Seunghyun
Johnson, Timothy J.
Perez, Andres
Alvarez, Julio
author_facet Elnekave, Ehud
Hong, Samuel L.
Lim, Seunghyun
Johnson, Timothy J.
Perez, Andres
Alvarez, Julio
author_sort Elnekave, Ehud
collection PubMed
description Serotyping has traditionally been used for subtyping of non-typhoidal Salmonella (NTS) isolates. However, its discriminatory power is limited, which impairs its use for epidemiological investigations of source attribution. Whole-genome sequencing (WGS) analysis allows more accurate subtyping of strains. However, because of the relative newness and cost of routine WGS, large-scale studies involving NTS WGS are still rare. We aimed to revisit the big picture of subtyping NTS with a public health impact by using traditional serotyping (i.e. reaction between antisera and surface antigens) and comparing the results with those obtained using WGS. For this purpose, we analysed 18 282 sequences of isolates belonging to 37 serotypes with a public health impact that were recovered in the USA between 2006 and 2017 from multiple sources, and were available at the National Center for Biotechnology Information (NCBI). Phylogenetic trees were reconstructed for each serotype using the core genome for the identification of genetic subpopulations. We demonstrated that WGS-based subtyping allows better identification of sources potentially linked with human infection and emerging subpopulations, along with providing information on the risk of dissemination of plasmids and acquired antimicrobial resistance genes (AARGs). In addition, by reconstructing a phylogenetic tree with representative isolates from all serotypes (n=370), we demonstrated genetic variability within and between serotypes, which formed monophyletic, polyphyletic and paraphyletic clades. Moreover, we found (in the entire data set) an increased detection rate for AARGs linked to key antimicrobials (such as quinolones and extended-spectrum cephalosporins) over time. The outputs of this large-scale analysis reveal new insights into the genetic diversity within and between serotypes; the polyphyly and paraphyly of certain serotypes may suggest that the subtyping of NTS to serotypes may not be sufficient. Moreover, the results and the methods presented here, leading to differentiation between genetic subpopulations based on their potential risk to public health, as well as narrowing down the possible sources of these infections, may be used as a baseline for subtyping of future NTS infections and help efforts to mitigate and prevent infections in the USA and globally.
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spelling pubmed-76439712020-11-09 Comparing serotyping with whole-genome sequencing for subtyping of non-typhoidal Salmonella enterica: a large-scale analysis of 37 serotypes with a public health impact in the USA Elnekave, Ehud Hong, Samuel L. Lim, Seunghyun Johnson, Timothy J. Perez, Andres Alvarez, Julio Microb Genom Research Article Serotyping has traditionally been used for subtyping of non-typhoidal Salmonella (NTS) isolates. However, its discriminatory power is limited, which impairs its use for epidemiological investigations of source attribution. Whole-genome sequencing (WGS) analysis allows more accurate subtyping of strains. However, because of the relative newness and cost of routine WGS, large-scale studies involving NTS WGS are still rare. We aimed to revisit the big picture of subtyping NTS with a public health impact by using traditional serotyping (i.e. reaction between antisera and surface antigens) and comparing the results with those obtained using WGS. For this purpose, we analysed 18 282 sequences of isolates belonging to 37 serotypes with a public health impact that were recovered in the USA between 2006 and 2017 from multiple sources, and were available at the National Center for Biotechnology Information (NCBI). Phylogenetic trees were reconstructed for each serotype using the core genome for the identification of genetic subpopulations. We demonstrated that WGS-based subtyping allows better identification of sources potentially linked with human infection and emerging subpopulations, along with providing information on the risk of dissemination of plasmids and acquired antimicrobial resistance genes (AARGs). In addition, by reconstructing a phylogenetic tree with representative isolates from all serotypes (n=370), we demonstrated genetic variability within and between serotypes, which formed monophyletic, polyphyletic and paraphyletic clades. Moreover, we found (in the entire data set) an increased detection rate for AARGs linked to key antimicrobials (such as quinolones and extended-spectrum cephalosporins) over time. The outputs of this large-scale analysis reveal new insights into the genetic diversity within and between serotypes; the polyphyly and paraphyly of certain serotypes may suggest that the subtyping of NTS to serotypes may not be sufficient. Moreover, the results and the methods presented here, leading to differentiation between genetic subpopulations based on their potential risk to public health, as well as narrowing down the possible sources of these infections, may be used as a baseline for subtyping of future NTS infections and help efforts to mitigate and prevent infections in the USA and globally. Microbiology Society 2020-08-26 /pmc/articles/PMC7643971/ /pubmed/32845830 http://dx.doi.org/10.1099/mgen.0.000425 Text en © 2020 The Authors http://creativecommons.org/licenses/by-nc/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution NonCommercial License. This article was made open access via a Publish and Read agreement between the Microbiology Society and the corresponding author’s institution.
spellingShingle Research Article
Elnekave, Ehud
Hong, Samuel L.
Lim, Seunghyun
Johnson, Timothy J.
Perez, Andres
Alvarez, Julio
Comparing serotyping with whole-genome sequencing for subtyping of non-typhoidal Salmonella enterica: a large-scale analysis of 37 serotypes with a public health impact in the USA
title Comparing serotyping with whole-genome sequencing for subtyping of non-typhoidal Salmonella enterica: a large-scale analysis of 37 serotypes with a public health impact in the USA
title_full Comparing serotyping with whole-genome sequencing for subtyping of non-typhoidal Salmonella enterica: a large-scale analysis of 37 serotypes with a public health impact in the USA
title_fullStr Comparing serotyping with whole-genome sequencing for subtyping of non-typhoidal Salmonella enterica: a large-scale analysis of 37 serotypes with a public health impact in the USA
title_full_unstemmed Comparing serotyping with whole-genome sequencing for subtyping of non-typhoidal Salmonella enterica: a large-scale analysis of 37 serotypes with a public health impact in the USA
title_short Comparing serotyping with whole-genome sequencing for subtyping of non-typhoidal Salmonella enterica: a large-scale analysis of 37 serotypes with a public health impact in the USA
title_sort comparing serotyping with whole-genome sequencing for subtyping of non-typhoidal salmonella enterica: a large-scale analysis of 37 serotypes with a public health impact in the usa
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7643971/
https://www.ncbi.nlm.nih.gov/pubmed/32845830
http://dx.doi.org/10.1099/mgen.0.000425
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