New paradigms for Salmonella source attribution based on microbial subtyping.

2.50
Hdl Handle:
http://hdl.handle.net/10029/621297
Title:
New paradigms for Salmonella source attribution based on microbial subtyping.
Authors:
Mughini-Gras, Lapo; Franz, Eelco; van Pelt, Wilfrid
Abstract:
Microbial subtyping is the most common approach for Salmonella source attribution. Typically, attributions are computed using frequency-matching models like the Dutch and Danish models based on phenotyping data (serotyping, phage-typing, and antimicrobial resistance profiling). Herewith, we critically review three major paradigms facing Salmonella source attribution today: (i) the use of genotyping data, particularly Multi-Locus Variable Number of Tandem Repeats Analysis (MLVA), which is replacing traditional Salmonella phenotyping beyond serotyping; (ii) the integration of case-control data into source attribution to improve risk factor identification/characterization; (iii) the investigation of non-food sources, as attributions tend to focus on foods of animal origin only. Population genetics models or simplified MLVA schemes may provide feasible options for source attribution, although there is a strong need to explore novel modelling options as we move towards whole-genome sequencing as the standard. Classical case-control studies are enhanced by incorporating source attribution results, as individuals acquiring salmonellosis from different sources have different associated risk factors. Thus, the more such analyses are performed the better Salmonella epidemiology will be understood. Reparametrizing current models allows for inclusion of sources like reptiles, the study of which improves our understanding of Salmonella epidemiology beyond food to tackle the pathogen in a more holistic way.
Citation:
New paradigms for Salmonella source attribution based on microbial subtyping. 2018, 71:60-67 Food Microbiol.
Journal:
Food Microbiol 2018; 71:60-7
Issue Date:
May-2018
URI:
http://hdl.handle.net/10029/621297
DOI:
10.1016/j.fm.2017.03.002
PubMed ID:
29366470
Type:
Article
Language:
en
ISSN:
1095-9998
Appears in Collections:
Miscellaneous

Full metadata record

DC FieldValue Language
dc.contributor.authorMughini-Gras, Lapoen
dc.contributor.authorFranz, Eelcoen
dc.contributor.authorvan Pelt, Wilfriden
dc.date.accessioned2018-02-06T12:09:15Z-
dc.date.available2018-02-06T12:09:15Z-
dc.date.issued2018-05-
dc.identifier.citationNew paradigms for Salmonella source attribution based on microbial subtyping. 2018, 71:60-67 Food Microbiol.en
dc.identifier.issn1095-9998-
dc.identifier.pmid29366470-
dc.identifier.doi10.1016/j.fm.2017.03.002-
dc.identifier.urihttp://hdl.handle.net/10029/621297-
dc.description.abstractMicrobial subtyping is the most common approach for Salmonella source attribution. Typically, attributions are computed using frequency-matching models like the Dutch and Danish models based on phenotyping data (serotyping, phage-typing, and antimicrobial resistance profiling). Herewith, we critically review three major paradigms facing Salmonella source attribution today: (i) the use of genotyping data, particularly Multi-Locus Variable Number of Tandem Repeats Analysis (MLVA), which is replacing traditional Salmonella phenotyping beyond serotyping; (ii) the integration of case-control data into source attribution to improve risk factor identification/characterization; (iii) the investigation of non-food sources, as attributions tend to focus on foods of animal origin only. Population genetics models or simplified MLVA schemes may provide feasible options for source attribution, although there is a strong need to explore novel modelling options as we move towards whole-genome sequencing as the standard. Classical case-control studies are enhanced by incorporating source attribution results, as individuals acquiring salmonellosis from different sources have different associated risk factors. Thus, the more such analyses are performed the better Salmonella epidemiology will be understood. Reparametrizing current models allows for inclusion of sources like reptiles, the study of which improves our understanding of Salmonella epidemiology beyond food to tackle the pathogen in a more holistic way.en
dc.language.isoenen
dc.rightsArchived with thanks to Food microbiologyen
dc.titleNew paradigms for Salmonella source attribution based on microbial subtyping.en
dc.typeArticleen
dc.identifier.journalFood Microbiol 2018; 71:60-7en
All Items in WARP are protected by copyright, with all rights reserved, unless otherwise indicated.