Coxiella burnetii is a human pathogen that causes the serious zoonotic disease Q fever. It is ubiquitous in the environment and due to its wide host range, long-range dispersal potential and classification as a bioterrorism agent, this microorganism is considered an HHS Select Agent. In the event of an outbreak or intentional release, laboratory strain typing methods can contribute to epidemiological investigations, law enforcement investigation and the public health response by providing critical information about the relatedness between C. burnetii isolates collected from different sources. Laboratory cultivation of C. burnetii is both time-consuming and challenging. Availability of strain collections is often limited and while several strain typing methods have been described over the years, a true gold-standard method is still elusive. Building upon epidemiological knowledge from limited, historical strain collections and typing data is essential to more accurately infer C. burnetii phylogeny. Harmonization of auspicious high-resolution laboratory typing techniques is critical to support epidemiological and law enforcement investigation. The single nucleotide polymorphism (SNP) -based genotyping approach offers simplicity, rapidity and robustness. Herein, we demonstrate SNPs identified within 16S rRNA gene sequences can differentiate C. burnetii strains. Using this method, 55 isolates were assigned to six groups based on six polymorphisms. These 16S rRNA SNP-based genotyping results were largely congruent with those obtained by analyzing restriction-endonuclease (RE)-digested DNA separated by SDS-PAGE and by the high-resolution approach based on SNPs within multispacer sequence typing (MST) loci. The SNPs identified within the 16S rRNA gene can be used as targets for the development of additional SNP-based genotyping assays for C. burnetii.

Analysis of 16S ribosomal RNA (rRNA) genes is important in phylogenetic classification of known and novel bacterial genera and species and for detection of uncultivable bacteria. PCR amplification of 16S rRNA genes with universal primers produces a mixture of amplicons from all rRNA operons in the genome, and the sequence data is generally a consensus sequence. We describe here valuable data that is missing from consensus sequences, variable effects on sequence data generated from non-identical 16S rRNA amplicons, and the appearance of data displayed by different sequence software. These effects are illustrated by analysis of 16S rRNA genes from 50 strains of the Bacillus cereus group: Bacillus anthracis, B. cereus, B. mycoides, and B. thuringiensis These species have 11 to 14 rRNA operons, and sequence variability occurs among the multiple 16S rRNA genes. A single nucleotide polymorphism (SNP), previously reported as specific to B. anthracis was detected in some B. cereus strains. However, a different SNP at position 1139 was identified as specific to B. anthracis, which is a biothreat agent with high rates of mortality. Compared with visual analysis of the electropherograms, base caller software frequently missed gene sequence variations or could not identify variant bases due to overlapping base calls. Accurate detection of 16S rRNA gene sequences that include intra-genomic variations can improve discrimination between closely-related species, improve the utility of 16S rRNA databases, and assist in rapid bacterial identification by targeted DNA sequence analysis or by whole genome sequencing performed by clinical or reference laboratories.

Burkholderia pseudomallei strain Bp1651, a human isolate, is resistant to all clinically relevant antibiotics. We report here on the finished genome sequence assembly and annotation of the two chromosomes of this strain. This genome sequence may assist in understanding the mechanisms of antimicrobial resistance for this pathogenic species.