Measuring blood sugar.

Abstract

<h3>Abstract</h3> <i>Francisella tularensis</i>, the bacterium that causes the zoonosis tularemia, and its genetic near neighbor species, can be difficult or impossible to cultivate from complex samples. Thus, there is a lack of genomic information for these species that has, among other things, limited the development of robust detection assays for <i>F. tularensis</i> that are both specific and sensitive. The objective of this study was to develop and validate approaches to capture, enrich, sequence, and analyze <i>Francisella</i> DNA present in DNA extracts generated from complex samples. RNA capture probes were designed based upon the known pan genome of <i>F. tularensis</i> and other diverse species in the family <i>Francisellaceae</i>. Probes that targeted genomic regions also present in non-<i>Francisellaceae</i> species were excluded, and probes specific to particular <i>Francisella</i> species or phylogenetic clades were identified. The capture-enrichment system was then applied to diverse, complex DNA extracts containing low-level <i>Francisella</i> DNA, including human clinical tularemia samples, environmental samples (<i>i.e.</i>, animal tissue and air filters), and whole ticks/tick cell lines, which was followed by sequencing of the enriched samples. Analysis of the resulting data facilitated rigorous and unambiguous confirmation of the detection of <i>F. tularensis</i> or other <i>Francisella</i> species in complex samples, identification of mixtures of different <i>Francisella</i> species in the same sample, analysis of gene content (<i>e.g.</i>, known virulence and antimicrobial resistance loci), and high-resolution whole genome-based genotyping. The benefits of this capture-enrichment system include: even very low target DNA can be amplified; it is culture-independent, reducing exposure for research and/or clinical personnel and allowing genomic information to be obtained from samples that do not yield isolates; and the resulting comprehensive data not only provide robust means to confirm the presence of a target species in a sample, but also can provide data useful for source attribution, which is important from a genomic epidemiology perspective.