Zur Kurzanzeige

2021-02-10Zeitschriftenartikel
Toward an Integrated Genome-Based Surveillance of Salmonella enterica in Germany
dc.contributor.authorUelze, Laura
dc.contributor.authorBecker, Natalie
dc.contributor.authorBorowiak, Maria
dc.contributor.authorBusch, Ulrich
dc.contributor.authorDangel, Alexandra
dc.contributor.authorDeneke, Carlus
dc.contributor.authorFischer, Jennie
dc.contributor.authorFlieger, Antje
dc.contributor.authorHepner, Sabrina
dc.contributor.authorHuber, Ingrid
dc.contributor.authorMethner, Ulrich
dc.contributor.authorLinde, Jörg
dc.contributor.authorPietsch, Michael
dc.contributor.authorSimon, Sandra
dc.contributor.authorSing, Andreas
dc.contributor.authorTausch, Simon H.
dc.contributor.authorSzabo, Istvan
dc.contributor.authorMalorny, Burkhard
dc.date.accessioned2024-07-25T11:13:04Z
dc.date.available2024-07-25T11:13:04Z
dc.date.issued2021-02-10none
dc.identifier.other10.3389/fmicb.2021.626941
dc.identifier.urihttp://edoc.rki.de/176904/11843
dc.description.abstractDespite extensive monitoring programs and preventative measures, Salmonella spp. continue to cause tens of thousands human infections per year, as well as many regional and international food-borne outbreaks, that are of great importance for public health and cause significant socio-economic costs. In Germany, salmonellosis is the second most common cause of bacterial diarrhea in humans and is associated with high hospitalization rates. Whole-genome sequencing (WGS) combined with data analysis is a high throughput technology with an unprecedented discriminatory power, which is particularly well suited for targeted pathogen monitoring, rapid cluster detection and assignment of possible infection sources. However, an effective implementation of WGS methods for large-scale microbial pathogen detection and surveillance has been hampered by the lack of standardized methods, uniform quality criteria and strategies for data sharing, all of which are essential for a successful interpretation of sequencing data from different sources. To overcome these challenges, the national GenoSalmSurv project aims to establish a working model for an integrated genome-based surveillance system of Salmonella spp. in Germany, based on a decentralized data analysis. Backbone of the model is the harmonization of laboratory procedures and sequencing protocols, the implementation of open-source bioinformatics tools for data analysis at each institution and the establishment of routine practices for cross-sectoral data sharing for a uniform result interpretation. With this model, we present a working solution for cross-sector interpretation of sequencing data from different sources (such as human, veterinarian, food, feed and environmental) and outline how a decentralized data analysis can contribute to a uniform cluster detection and facilitate outbreak investigations.eng
dc.language.isoengnone
dc.publisherRobert Koch-Institut
dc.rights(CC BY 3.0 DE) Namensnennung 3.0 Deutschlandger
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/de/
dc.subjectsalmonellaeng
dc.subjectsurveillanceeng
dc.subjectfood-borne disease outbreakeng
dc.subjectwhole genome sequencingeng
dc.subjectcgMLSTeng
dc.subject.ddc610 Medizin und Gesundheitnone
dc.titleToward an Integrated Genome-Based Surveillance of Salmonella enterica in Germanynone
dc.typearticle
dc.identifier.urnurn:nbn:de:0257-176904/11843-8
dc.type.versionpublishedVersionnone
local.edoc.container-titleFrontiers in Microbiologynone
local.edoc.container-issn1664-302Xnone
local.edoc.pages13none
local.edoc.type-nameZeitschriftenartikel
local.edoc.container-typeperiodical
local.edoc.container-type-nameZeitschrift
local.edoc.container-urlhttps://www.frontiersin.org/journals/microbiologynone
local.edoc.container-publisher-nameFrontiers Meadia S.A.none
local.edoc.container-volume12none
local.edoc.container-reportyear2021none
dc.description.versionPeer Reviewednone

Zur Kurzanzeige