Genotyping of Coxiella burnetii from domestic ruminants and human in Hungary: indication of various genotypes
1 Institute for Veterinary Medical Research, Centre for Agricultural Research, Hungarian Academy of Sciences, Budapest, Hungária körút 21 1143, Hungary
2 Center for Microbial Genetics and Genomics, Northern Arizona University, 1298 S. Knoles Drive Flagstaff, AZ 86011-4073, USA
3 Veterinary Diagnostic Directorate, National Food Chain Safety Office, Budapest, Tábornok utca 2 1143, Hungary
4 National Center for Epidemiology, Budapest, Gyáli út 2-6 1097, Hungary
BMC Veterinary Research 2014, 10:107 doi:10.1186/1746-6148-10-107Published: 7 May 2014
Information about the genotypic characteristic of Coxiella burnetii from Hungary is lacking. The aim of this study is to describe the genetic diversity of C. burnetii in Hungary and compare genotypes with those found elsewhere. A total of 12 samples: (cattle, n = 6, sheep, n = 5 and human, n = 1) collected from across Hungary were studied by a 10-loci multispacer sequence typing (MST) and 6-loci multiple-locus variable-number of tandem repeat analysis (MLVA). Phylogenetic relationships among MST genotypes show how these Hungarian samples are related to others collected around the world.
Three MST genotypes were identified: sequence type (ST) 20 has also been identified in ruminants from other European countries and the USA, ST28 was previously identified in Kazakhstan, and the proposed ST37 is novel. All MST genotypes yielded different MLVA genotypes and three different MLVA genotypes were identified within ST20 samples alone. Two novel MLVA types 0-9-5-5-6-2 (AG) and 0-8-4-5-6-2 (AF) (Ms23-Ms24-Ms27-Ms28-Ms33-Ms34) were defined in the ovine materials correlated with ST28 and ST37. Samples from different parts of the phylogenetic tree were associated with different hosts, suggesting host-specific adaptations.
Even with the limited number of samples analysed, this study revealed high genetic diversity among C. burnetii in Hungary. Understanding the background genetic diversity will be essential in identifying and controlling outbreaks.