Eight new genomes and synthetic controls increase the accessibility of rapid melt-MAMA SNP typing of Coxiella burnetii.

Abstract

The case rate of Q fever in Europe has increased dramatically in recent years, mainly because of an epidemic in the Netherlands in 2009. Consequently, there is a need for more extensive genetic characterization of the disease agent Coxiella burnetii in order to better understand the epidemiology and spread of this disease. Genome reference data are essential for this purpose, but only thirteen genome sequences are currently available. Current methods for typing C. burnetii are criticized for having problems in comparing results across laboratories, require the use of genomic control DNA, and/or rely on markers in highly variable regions. We developed in this work a method for single nucleotide polymorphism (SNP) typing of C. burnetii isolates and tissue samples based on new assays targeting ten phylogenetically stable synonymous canonical SNPs (canSNPs). These canSNPs represent previously known phylogenetic branches and were here identified from sequence comparisons of twenty-one C. burnetii genomes, eight of which were sequenced in this work. Importantly, synthetic control templates were developed, to make the method useful to laboratories lacking genomic control DNA. An analysis of twenty-one C. burnetii genomes confirmed that the species exhibits high sequence identity. Most of its SNPs (7,493/7,559 shared by >1 genome) follow a clonal inheritance pattern and are therefore stable phylogenetic typing markers. The assays were validated using twenty-six genetically diverse C. burnetii isolates and three tissue samples from small ruminants infected during the epidemic in the Netherlands. Each sample was assigned to a clade. Synthetic controls (vector and PCR amplified) gave identical results compared to the corresponding genomic controls and are viable alternatives to genomic DNA. The results from the described method indicate that it could be useful for cheap and rapid disease source tracking at non-specialized laboratories, which requires accurate genotyping, assay accessibility and inter-laboratory comparisons.