RT Journal Article SR Electronic(1) A1 Jamin, Casper A1 De Koster, Sien A1 van Koeveringe, Stefanie A1 De Coninck, Dieter A1 Mensaert, Klaas A1 De Bruyne, Katrien A1 Perales Selva, Natascha A1 Lammens, Christine A1 Goossens, Herman A1 Hoebe, Christian A1 Savelkoul, Paul A1 van Alphen, LiekeYR 2021 T1 Harmonization of whole-genome sequencing for outbreak surveillance of Enterobacteriaceae and Enterococci JF Microbial Genomics, VO 7 IS 7 OP SP 000567 DO https://doi.org/10.1099/mgen.0.000567 PB Microbiology Society, SN 2057-5858, AB Whole-genome sequencing (WGS) is becoming the de facto standard for bacterial typing and outbreak surveillance of resistant bacterial pathogens. However, interoperability for WGS of bacterial outbreaks is poorly understood. We hypothesized that harmonization of WGS for outbreak surveillance is achievable through the use of identical protocols for both data generation and data analysis. A set of 30 bacterial isolates, comprising of various species belonging to the Enterobacteriaceae family and Enterococcus genera, were selected and sequenced using the same protocol on the Illumina MiSeq platform in each individual centre. All generated sequencing data were analysed by one centre using BioNumerics (6.7.3) for (i) genotyping origin of replications and antimicrobial resistance genes, (ii) core-genome multi-locus sequence typing (cgMLST) for Escherichia coli and Klebsiella pneumoniae and whole-genome multi-locus sequencing typing (wgMLST) for all species. Additionally, a split k-mer analysis was performed to determine the number of SNPs between samples. A precision of 99.0% and an accuracy of 99.2% was achieved for genotyping. Based on cgMLST, a discrepant allele was called only in 2/27 and 3/15 comparisons between two genomes, for E. coli and K. pneumoniae, respectively. Based on wgMLST, the number of discrepant alleles ranged from 0 to 7 (average 1.6). For SNPs, this ranged from 0 to 11 SNPs (average 3.4). Furthermore, we demonstrate that using different de novo assemblers to analyse the same dataset introduces up to 150 SNPs, which surpasses most thresholds for bacterial outbreaks. This shows the importance of harmonization of data-processing surveillance of bacterial outbreaks. In summary, multi-centre WGS for bacterial surveillance is achievable, but only if protocols are harmonized., UL https://www.microbiologyresearch.org/content/journal/mgen/10.1099/mgen.0.000567