ena-STUDY-Centre for Epidemiology and Microbiology-21-02-2019-14:00:53:690-113
Surveillance of invasive meningococcal disease based on whole genome sequencing (WGS), Czech Republic, 2015.
AIM:To test the potential of whole genome sequencing (WGS) for molecular surveillance of invasive meningococcal disease in the Czech Republic. To check the success of the new method in the identification of gene and protein variants and to compare the outcomes between WGS and conventional sequencing methods.MATERIAL AND METHODS:WGS was carried out in a set of 20 N. meningitidis isolates from invasive meningococcal disease cases in the Czech Republic in 2015. WGS was performed using the Illumina MiSeq platform. The WGS data were processed by the Velvet de novo Assembler software, and the resultant genome contigs were submitted to the Neisseria PubMLST web database containing allelic and genomic data on strains of the genus Neisseria. The genomes were analysed and compared using the BIGSdb Genome Comparator, which is part of the PubMLST database. WGS data were compared at several levels of resolution: MLST (Multi Locus Sequence Typing), rMLST (ribosomal MLST), cgMLST (core genome MLST), and "all loci", i.e. all genes of N. meningitidis defined in the PubMLST database by 6 November 2017 (3028 loci). The WGS method was used to characterise in detail the genes of antigens involved in vaccines against N. meningitidis B.RESULTS:The new WGS method provided detailed characteristics of N. meningitidis isolates, which improved the results obtained previously by conventional sequencing methods. High quality WGS data made it possible to identify novel alleles and novel sequence types that could not be recognized by conventional sequencing methods. The analysis of genetic diversity confirmed closer relatedness between isolates belonging to the same clonal complex. The most accurate information on genetic diversity of isolates was obtained by the comparison of WGS data at the cgMLST and "all loci" levels. Distant relatedness of three clonal complexes (cc32, cc35, and cc269) was found. WGS data also provided more accurate information on the coverage of isolates by MenB vaccines in comparison with conventional sequencing data.CONCLUSIONS:The WGS method showed a higher discrimination potential and allowed a more accurate determination of genetic characteristics of N. meningitidis. The integration of the WGS method in routine molecular surveillance of invasive meningococcal disease in the Czech Republic is desirable.
AIM:To test the potential of whole genome sequencing (WGS) for molecular surveillance of invasive meningococcal disease in the Czech Republic. To check the success of the new method in the identification of gene and protein variants and to compare the outcomes between WGS and conventional sequencing methods.MATERIAL AND METHODS:WGS was carried out in a set of 20 N. meningitidis isolates from invasive meningococcal disease cases in the Czech Republic in 2015. WGS was performed using the Illumina MiSeq platform. The WGS data were processed by the Velvet de novo Assembler software, and the resultant genome contigs were submitted to the Neisseria PubMLST web database containing allelic and genomic data on strains of the genus Neisseria. The genomes were analysed and compared using the BIGSdb Genome Comparator, which is part of the PubMLST database. WGS data were compared at several levels of resolution: MLST (Multi Locus Sequence Typing), rMLST (ribosomal MLST), cgMLST (core genome MLST), and "all loci", i.e. all genes of N. meningitidis defined in the PubMLST database by 6 November 2017 (3028 loci). The WGS method was used to characterise in detail the genes of antigens involved in vaccines against N. meningitidis B.RESULTS:The new WGS method provided detailed characteristics of N. meningitidis isolates, which improved the results obtained previously by conventional sequencing methods. High quality WGS data made it possible to identify novel alleles and novel sequence types that could not be recognized by conventional sequencing methods. The analysis of genetic diversity confirmed closer relatedness between isolates belonging to the same clonal complex. The most accurate information on genetic diversity of isolates was obtained by the comparison of WGS data at the cgMLST and "all loci" levels. Distant relatedness of three clonal complexes (cc32, cc35, and cc269) was found. WGS data also provided more accurate information on the coverage of isolates by MenB vaccines in comparison with conventional sequencing data.CONCLUSIONS:The WGS method showed a higher discrimination potential and allowed a more accurate determination of genetic characteristics of N. meningitidis. The integration of the WGS method in routine molecular surveillance of invasive meningococcal disease in the Czech Republic is desirable.