NAuRA: Genomic Tool to Identify Staphylococcal Enterotoxins in Staphylococcus aureus Strains Responsible for FoodBorne Outbreaks
Identifieur interne : 000697 ( Main/Exploration ); précédent : 000696; suivant : 000698NAuRA: Genomic Tool to Identify Staphylococcal Enterotoxins in Staphylococcus aureus Strains Responsible for FoodBorne Outbreaks
Auteurs : Déborah Merda [France] ; Arnaud Felten [France] ; Noémie Vingadassalon [France] ; Sarah Denayer [Belgique] ; Yacine Titouche [Algérie] ; Lucia Decastelli [Italie] ; Bernadette Hickey [Irlande (pays)] ; Christos Kourtis [Chypre (pays)] ; Hristo Daskalov [Bulgarie] ; Michel-Yves Mistou [France] ; Jacques-Antoine Hennekinne [France]Source :
- Frontiers in Microbiology [ 1664-302X ] ; 2020.
Abstract
Food contamination by staphylococcal enterotoxins (SEs) is responsible for many food poisoning outbreaks (FPOs) each year, and they represent the third leading cause of FPOs in Europe. SEs constitute a protein family with 27 proteins. However, enzyme immunoassays can only detect directly in food the five classical SEs (SEA-SEE). Thus, molecular characterization methods of strains found in food are now used for FPO investigations. Here, we describe the development and implementation of a genomic analysis tool called NAuRA (Nice automatic Research of alleles) that can detect the presence of 27 SEs genes in just one analysis- and create a database of allelic data and protein variants for harmonizing analyses. This tool uses genome assembly data and the 27 protein sequences of SEs. To include the different divergence levels between SE-coding genes, parameters of coverage and identity were generated from 10,000 simulations and a dataset of 244 assembled genomes from strains responsible for outbreaks in Europe as well as the RefSeq reference database. Based on phylogenetic inference performed using maximum-likelihood on the core genomes of the strains in this collection, we demonstrated that strains responsible for FPOs are distributed throughout the phylogenetic tree. Moreover, 71 toxin profiles were obtained using the NAuRA pipeline and these profiles do not follow the evolutionary history of strains. This study presents a pioneering method to investigate strains isolated from food at the genomic level and to analyze the diversity of all 27 SE-coding genes together.
Url:
DOI: 10.3389/fmicb.2020.01483
PubMed: 32714310
PubMed Central: 7344154
Affiliations:
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<front><div type="abstract" xml:lang="en"><p>Food contamination by staphylococcal enterotoxins (SEs) is responsible for many food poisoning outbreaks (FPOs) each year, and they represent the third leading cause of FPOs in Europe. SEs constitute a protein family with 27 proteins. However, enzyme immunoassays can only detect directly in food the five classical SEs (SEA-SEE). Thus, molecular characterization methods of strains found in food are now used for FPO investigations. Here, we describe the development and implementation of a genomic analysis tool called NAuRA (Nice automatic Research of alleles) that can detect the presence of 27 SEs genes in just one analysis- and create a database of allelic data and protein variants for harmonizing analyses. This tool uses genome assembly data and the 27 protein sequences of SEs. To include the different divergence levels between SE-coding genes, parameters of coverage and identity were generated from 10,000 simulations and a dataset of 244 assembled genomes from strains responsible for outbreaks in Europe as well as the RefSeq reference database. Based on phylogenetic inference performed using maximum-likelihood on the core genomes of the strains in this collection, we demonstrated that strains responsible for FPOs are distributed throughout the phylogenetic tree. Moreover, 71 toxin profiles were obtained using the NAuRA pipeline and these profiles do not follow the evolutionary history of strains. This study presents a pioneering method to investigate strains isolated from food at the genomic level and to analyze the diversity of all 27 SE-coding genes together.</p>
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</author>
<author><name sortKey="Cui, Y" uniqKey="Cui Y">Y. Cui</name>
</author>
</analytic>
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</TEI>
<affiliations><list><country><li>Algérie</li>
<li>Belgique</li>
<li>Bulgarie</li>
<li>Chypre (pays)</li>
<li>France</li>
<li>Irlande (pays)</li>
<li>Italie</li>
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</list>
<tree><country name="France"><noRegion><name sortKey="Merda, Deborah" sort="Merda, Deborah" uniqKey="Merda D" first="Déborah" last="Merda">Déborah Merda</name>
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<name sortKey="Felten, Arnaud" sort="Felten, Arnaud" uniqKey="Felten A" first="Arnaud" last="Felten">Arnaud Felten</name>
<name sortKey="Hennekinne, Jacques Antoine" sort="Hennekinne, Jacques Antoine" uniqKey="Hennekinne J" first="Jacques-Antoine" last="Hennekinne">Jacques-Antoine Hennekinne</name>
<name sortKey="Mistou, Michel Yves" sort="Mistou, Michel Yves" uniqKey="Mistou M" first="Michel-Yves" last="Mistou">Michel-Yves Mistou</name>
<name sortKey="Vingadassalon, Noemie" sort="Vingadassalon, Noemie" uniqKey="Vingadassalon N" first="Noémie" last="Vingadassalon">Noémie Vingadassalon</name>
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<country name="Belgique"><noRegion><name sortKey="Denayer, Sarah" sort="Denayer, Sarah" uniqKey="Denayer S" first="Sarah" last="Denayer">Sarah Denayer</name>
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<country name="Algérie"><noRegion><name sortKey="Titouche, Yacine" sort="Titouche, Yacine" uniqKey="Titouche Y" first="Yacine" last="Titouche">Yacine Titouche</name>
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</country>
<country name="Italie"><noRegion><name sortKey="Decastelli, Lucia" sort="Decastelli, Lucia" uniqKey="Decastelli L" first="Lucia" last="Decastelli">Lucia Decastelli</name>
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<country name="Irlande (pays)"><noRegion><name sortKey="Hickey, Bernadette" sort="Hickey, Bernadette" uniqKey="Hickey B" first="Bernadette" last="Hickey">Bernadette Hickey</name>
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</country>
<country name="Chypre (pays)"><noRegion><name sortKey="Kourtis, Christos" sort="Kourtis, Christos" uniqKey="Kourtis C" first="Christos" last="Kourtis">Christos Kourtis</name>
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</country>
<country name="Bulgarie"><noRegion><name sortKey="Daskalov, Hristo" sort="Daskalov, Hristo" uniqKey="Daskalov H" first="Hristo" last="Daskalov">Hristo Daskalov</name>
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</record>
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