RESUMEN
Data sharing enables research communities to exchange findings and build upon the knowledge that arises from their discoveries. Areas of public and animal health as well as food safety would benefit from rapid data sharing when it comes to emergencies. However, ethical, regulatory and institutional challenges, as well as lack of suitable platforms which provide an infrastructure for data sharing in structured formats, often lead to data not being shared or at most shared in form of supplementary materials in journal publications. Here, we describe an informatics platform that includes workflows for structured data storage, managing and pre-publication sharing of pathogen sequencing data and its analysis interpretations with relevant stakeholders.
Asunto(s)
Bases de Datos Factuales , Difusión de la Información , Bacterias/clasificación , Metagenómica , Filogenia , Interfaz Usuario-ComputadorAsunto(s)
Adhesinas de Escherichia coli/genética , Proteínas de Escherichia coli/genética , Escherichia coli Patógena Extraintestinal/clasificación , Escherichia coli Patógena Extraintestinal/genética , Proteínas Fimbrias/genética , Programas Informáticos , Alelos , Escherichia coli Patógena Extraintestinal/patogenicidad , Genoma Bacteriano , HumanosRESUMEN
The aim of this study was to construct a valid publicly available method for in silico fimH subtyping of Escherichia coli particularly suitable for differentiation of fine-resolution subgroups within clonal groups defined by standard multilocus sequence typing (MLST). FimTyper was constructed as a FASTA database containing all currently known fimH alleles. The software source code is publicly available at https://bitbucket.org/genomicepidemiology/fimtyper, the database is freely available at https://bitbucket.org/genomicepidemiology/fimtyper_db, and a service implementing the software is available at https://cge.cbs.dtu.dk/services/FimTyper FimTyper was validated on three data sets: one containing Sanger sequences of fimH alleles of 42 E. coli isolates generated prior to the current study (data set 1), one containing whole-genome sequence (WGS) data of 243 third-generation-cephalosporin-resistant E. coli isolates (data set 2), and one containing a randomly chosen subset of 40 E. coli isolates from data set 2 that were subjected to conventional fimH subtyping (data set 3). The combination of the three data sets enabled an evaluation and comparison of FimTyper on both Sanger sequences and WGS data. FimTyper correctly predicted all 42 fimH subtypes from the Sanger sequences from data set 1 and successfully analyzed all 243 draft genomes from data set 2. FimTyper subtyping of the Sanger sequences and WGS data from data set 3 were in complete agreement. Additionally, fimH subtyping was evaluated on a phylogenetic network of 122 sequence type 131 (ST131) E. coli isolates. There was perfect concordance between the typology and fimH-based subclones within ST131, with accurate identification of the pandemic multidrug-resistant clonal subgroup ST131-H30. FimTyper provides a standardized tool, as a rapid alternative to conventional fimH subtyping, highly suitable for surveillance and outbreak detection.
