Mapping of sequencing reads obtained from <i>B. anthracis</i>-spiked environmental samples to specified reference genomes.

<p><i>B. anthracis</i> Ames genomic DNA was combined with background nucleic acid extracted from either aerosol or soil-based material. Increasing genome copy numbers were spiked into samples at 10-fold concentration intervals. Samples were then subjected to whole genome amplification and next-generation sequencing. The resultant reads were mapped to either a target set (<i>B. anthracis</i> and plasmids) or a background set of DNA sequences, intended to assess non-specific alignment of <i>B. anthracis</i>-derived sequence reads to other genomes. The numbers of reads mapped were normalized to total reads obtained for each sample to standardize results. Shown are the percentage of reads mapped for <b>A</b>. Illumina reads from an aerosol background spiked with <i>B. anthracis</i> genomic DNA, <b>B</b>. Illumina reads from a soil background spiked with <i>B. anthracis</i> DNA, <b>C</b>. 454 reads from an aerosol background spiked with <i>B. anthracis</i> DNA, and <b>D</b>. 454 reads from a soil background spiked with <i>B. anthracis</i> DNA.</p

Alignment of unique 454 reads to <i>B. anthracis</i> and near-neighbor species.

<p>454 reads mapping only to <i>B. anthracis</i> or a close relative, discounting reads mapping to multiple reference genomes, were identified. The number of sequencing reads mapping uniquely to <i>B. anthracis</i> Ames DNA are shown compared to <b>A</b>. <i>B. thuringiensis</i> in aerosol samples, <b>B</b>. <i>B. thuringiensis</i> in soil samples, <b>C</b>. <i>B. cereus</i> in aerosol samples, and <b>D</b>. <i>B. cereus</i> in soil samples. As in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0073455#pone-0073455-g004" target="_blank">Figure 4</a>, this analysis was performed separately for each set of species.</p

Alignment of uniquely mapped Illumina reads to genomes from <i>B. anthracis</i> and two closely-related species.

<p>Due to the high degree of sequence similarity among the three examined <i>Bacillus</i> species, a unique mapping approach was used. DNA sequencing reads mapping to only <i>B. anthracis</i> or one of the two near neighbor species were identified; reads mapping to multiple reference genomes were ignored. This approach facilitated distinction among the three closely related species. The number of uniquely mapped reads for <i>B. anthracis</i> is given compared to <b>A</b>. <i>B. thuringiensis</i> in aerosol samples, <b>B</b>. <i>B. thuringiensis</i> in soil samples, <b>C</b>. <i>B. cereus</i> in aerosol samples, and <b>D</b>. <i>B. cereus</i> in soil samples. This analysis was performed separately for each species – unique reads between <i>B. anthracis</i> and <i>B. thuringiensis</i> were identified, followed by identification of unique reads between <i>B. anthracis</i> and <i>B. cereus</i> – thus the results of each comparison are shown in separate charts.</p

Mapping of Illumina reads to closely related <i>Bacillus</i> species.

<p>Following sequencing of <i>B. anthracis</i>-spiked environmental samples, mapping specificity was examined by determining the percent of total Illumina reads mapping to the closely related species <i>B. thuringiensis</i> Al Hakam and <i>B. cereus</i> biovar <i>anthracis</i> CI. Illumina reads were obtained from A. aerosol background DNA and <b>B</b>. soil background DNA samples spiked with increasing amounts of <i>B. anthracis</i> DNA. </p

Detection of <i>Bacillus anthracis</i> DNA in Complex Soil and Air Samples Using Next-Generation Sequencing

<div><p><i>Bacillus anthracis</i> is the potentially lethal etiologic agent of anthrax disease, and is a significant concern in the realm of biodefense. One of the cornerstones of an effective biodefense strategy is the ability to detect infectious agents with a high degree of sensitivity and specificity in the context of a complex sample background. The nature of the <i>B. anthracis</i> genome, however, renders specific detection difficult, due to close homology with <i>B. cereus</i> and <i>B. thuringiensis</i>. We therefore elected to determine the efficacy of next-generation sequencing analysis and microarrays for detection of <i>B. anthracis</i> in an environmental background. We applied next-generation sequencing to titrated genome copy numbers of <i>B. anthracis</i> in the presence of background nucleic acid extracted from aerosol and soil samples. We found next-generation sequencing to be capable of detecting as few as 10 genomic equivalents of <i>B. anthracis</i> DNA per nanogram of background nucleic acid. Detection was accomplished by mapping reads to either a defined subset of reference genomes or to the full GenBank database. Moreover, sequence data obtained from <i>B. anthracis</i> could be reliably distinguished from sequence data mapping to either <i>B. cereus</i> or <i>B. thuringiensis</i>. We also demonstrated the efficacy of a microbial census microarray in detecting <i>B. anthracis</i> in the same samples, representing a cost-effective and high-throughput approach, complementary to next-generation sequencing. Our results, in combination with the capacity of sequencing for providing insights into the genomic characteristics of complex and novel organisms, suggest that these platforms should be considered important components of a biosurveillance strategy.</p> </div

Modified WT amplification of non-clinical samples containing emerging virus.

<p>Purified viral RNA from a wide range of virus-positive cell culture supernatants (SN) or QCMD panel samples was amplified by WTA using the P-N6/SSIII RT-reaction. Virus-specific real-time PCR was performed before and after the amplification step, and fold increase was calculated using ΔC_t-values and dilution factors for each sample tested. (A) Fold increase of WT-amplified emerging viruses belonging to different virus genera. The two QCMD panel samples (WNV10-01 and WNV10-07) containing mixtures of different flaviviruses are highlighted. (B) The correlation between fold increase in WT amplification and viral sample content (C_t before WT amplification).</p

Identification of Genome-Wide Mutations in Ciprofloxacin-Resistant <i>F</i>. <i>tularensis</i> LVS Using Whole Genome Tiling Arrays and Next Generation Sequencing

<div><p><i>Francisella tularensis</i> is classified as a Class A bioterrorism agent by the U.S. government due to its high virulence and the ease with which it can be spread as an aerosol. It is a facultative intracellular pathogen and the causative agent of tularemia. Ciprofloxacin (Cipro) is a broad spectrum antibiotic effective against Gram-positive and Gram-negative bacteria. Increased Cipro resistance in pathogenic microbes is of serious concern when considering options for medical treatment of bacterial infections. Identification of genes and loci that are associated with Ciprofloxacin resistance will help advance the understanding of resistance mechanisms and may, in the future, provide better treatment options for patients. It may also provide information for development of assays that can rapidly identify Cipro-resistant isolates of this pathogen. In this study, we selected a large number of <i>F</i>. <i>tularensis</i> live vaccine strain (LVS) isolates that survived in progressively higher Ciprofloxacin concentrations, screened the isolates using a whole genome <i>F</i>. <i>tularensis</i> LVS tiling microarray and Illumina sequencing, and identified both known and novel mutations associated with resistance. Genes containing mutations encode DNA gyrase subunit A, a hypothetical protein, an asparagine synthase, a sugar transamine/perosamine synthetase and others. Structural modeling performed on these proteins provides insights into the potential function of these proteins and how they might contribute to Cipro resistance mechanisms.</p></div

Multiple drug resistance testing of <i>F</i>. <i>tularensis</i> LVS Ciprofloxacin resistant clones.

<p>Units are in μg/mL.</p

Structural model of FTL_0601 with two mutation positions Ala69, and Asp110 labeled.

<p>Left plot: a ribbon representation of two subunits forming homodimer with mutation positions Ala69 and Asp110 shown as spheres colored in red and blue respectively (the asterisk indicates residue from the second subunit of the dimer). Asp110 is located on the surface of the protein within conserved helical region outside the interface area. Right plot: close-up of the region showing Ala69 located at the end of the helical segment Asn58-Ala69 which is a part of the interface between subunits. Examples of three residue positions within this helical region are shown as yellow sticks and their functional importance can be described based on annotation of corresponding positions in other homologous aminotransferases. In particular: two residues Asn58 and Arg68 from both ends of the helix contribute to the interface formation by interacting with Asn224* and Ser92* respectively, the residues Thr60 and Asn224* are both highly conserved and are involved in stabilizing interaction between ligand and protein [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0163458#pone.0163458.ref021" target="_blank">21</a>–<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0163458#pone.0163458.ref024" target="_blank">24</a>]. Ala69 is located on the edge of the interface in close proximity of these residues.</p

Microarray analysis correctly identifies emerging viruses in clinical samples.

<p>The results of microarray analysis of WT-amplified virus-positive clinical samples, using the SSI analysis method. Graphs show the signal mean for the probe intensities for each detected virus. The bar across the graph demonstrates the signal threshold at the 99^th percentile of the random control intensities. (A) Microarray analysis of a Dengue-positive serum sample. (B) Microarray analysis of another Dengue-positive serum sample. (C) Microarray analysis of a WNV-positive urine sample. (D) Microarray analysis of another WNV-positive urine sample.</p