Analysis of Mycobacterium tuberculosis genetic lineages circulating in Riga and Riga region, Latvia, isolated between 2008 and 2012.

Although the number of new tuberculosis (TB) cases registered per year has decreased by 3-fold between 2001 and 2017 in Latvia, the TB incidence and rates of multidrug resistant TB in this Baltic country remain substantially higher than in most other European countries. Molecular typing methods of Mycobacterium tuberculosis (MTB) play an important role both in clinical studies of the disease and the epidemiological investigations, allowing to describe and characterize the pathogen's population structure and spread of particular genotypes. Aim of this study was to examine the prevalence of MTB lineages in Riga and Riga region of Latvia within a five-year period (2008-2012), and to evaluate the discriminatory power (DP) of spoligotyping, standard 24-locus MIRU-VNTR and IS6110-RFLP methods in this setting. The results showed that the main MTB spoligotype families were Beijing (25.3%) and LAM (24.3%), followed by T (22.1%), Ural (11.2%), Haarlem (6.6%) and X superfamily (3.4%). This distribution remained stable over the five consecutive years. 67.6% of MTB isolates were pan-susceptible, and 32.4% were resistant to any drug; multi-drug resistance was found in 5.8% of MTB strains, and 7.6% of MTB isolates were extensively drug-resistant. Drug resistance was associated with SIT1, SIT283 and SIT42 genotypes, while SIT1 and SIT42 were overrepresented among multi drug-resistant MTB strains. Overall, DP of spoligotyping method alone was 0.8953, while DP of both 24-locus MIRU-VNTR analysis and IS6110 RFLP was higher (DP = 0.9846 and 0.9927, respectively), mainly due to the improvement of the resolution for the Beijing strains. In conclusion, this work represents the first comprehensive molecular epidemiological description of TB in Latvia, highlighting the high genetic diversity of MTB strains circulating in Riga and Riga region. In combination with detailed epidemiological data this approach was helpful for the in-depth understanding of epidemiological processes in settings where the Next-Gen sequencing is not available as a routine method.