Performance and Accuracy of Four Open-Source Tools for In Silico Serotyping of Salmonella spp. Based on Whole-Genome Short-Read Sequencing Data
-
Laura Uelze [1] ; Maria Borowiak [1] ; Carlus Deneke [1] ; István Szabó [1] ; Jennie Fischer [1] ; Simon H. Tausch [1] ; Burkhard Malorny [1]
-
[1] a German Federal Institute for Risk Assessment (BfR), Berlin, Germany
-
- Localización: Applied and Environmental Microbiology, ISSN 0099-2240, Vol. 86, Nº 5, 2020
- Idioma: inglés
- Enlaces
-
Resumen
Salmonella spp. are important foodborne pathogens. To reduce the number of infected patients, it is essential to understand which subtypes of the bacteria cause disease outbreaks. Traditionally, characterization of Salmonella requires serological testing, a laboratory method by which Salmonella isolates can be classified into over 2,600 distinct subtypes, called serovars. Due to recent advances in whole-genome sequencing, many tools have been developed to replace traditional testing methods with computational analysis of genome sequences. It is crucial to validate that these tools, many already in use for routine surveillance, deliver accurate and reliable serovar information. In this study, we set out to compare which of the currently available open-source command-line tools is most suitable to replace serological testing. A thorough evaluation of the differing computational approaches is highly important to ensure the backward compatibility of serotyping data and to maintain comparability between laboratories.
