Comparison of Brucella abortus population structure based on genotyping methods with different levels of resolution

Abstract

Numerous genotyping techniques based on different principles and with different costs and levels of resolution are currently available for understanding the transmission dynamics of brucellosis worldwide. We aimed to compare the population structure of the genomes of 53 Brazilian Brucella abortus isolates using eight different genotyping methods: multiple-locus variable-number tandem-repeat analysis (MLVA8, MLVA11, MLVA16), multilocus sequence typing (MLST9, MLST21), core genome MLST (cgMLST) and two techniques based on single nucleotide polymorphism (SNP) detection (parSNP and NASP) from whole genomes. The strains were isolated from six different Brazilian states between 1977 and 2008 and had previously been analyzed using MLVA8, MLVA11, and MLVA16. Their whole genomes were sequenced, assembled, and subjected to MLST9 MLST21, cgMLST, and SNP analyses. All the genotypes were compared by hierarchical grouping method based on the average distances between the correlation matrices of each technique. MLST9 and MLST21 had the lowest level of resolution, both revealing only four genotypes. MLVA8, MLVA11, and MLVA16 had progressively increasing levels of resolution as more loci were analyzed, identifying 6, 16, and 44 genotypes, respectively. cgMLST showed the highest level of resolution, identifying 45 genotypes, followed by the SNP-based methods, both of which had 44 genotypes. In the assessed population, MLVA was more discriminatory than MLST and was easier and cheaper to perform. SNP techniques and cgMLST provided the highest levels of resolution and the results from the two methods were in close agreement. In conclusion, the choice of genotyping technique can strongly affect one's ability to make meaningful epidemiological conclusions but is dependent on available resources: while the VNTR based techniques are more indicated to high prevalence scenarios, the WGS methods are the ones with the best discriminative power and therefore recommended for outbreaks investigation.