Genome Target Evaluator (GTEvaluator): A workflow exploiting genome dataset to measure the sensitivity and specificity of genetic markers

<div><p>Most of the bacterial typing methods used to discriminate isolates in medical or food safety microbiology are based on genetic markers used as targets in PCR or hybridization experiments. These DNA typing methods are important tools for studying prevalence and epidemiology, for conducting surveillance, investigations and control of biological hazard sources. In that perspective, it is crucial to insure that the chosen genetic markers have the greatest specificity and sensitivity. The wealth of whole-genome sequences available for many bacterial species offers the opportunity to evaluate the performance of these genetic markers. In the present study, we have developed GTEvaluator, a bioinformatics workflow which ranks genetic markers depending on their sensitivity and specificity towards groups of well-defined genomes. GTEvaluator identifies the most performant genetic markers to target individuals among a population. The individuals (i.e. a group of genomes within a collection) are defined by any kind of particular phenotypic or biological properties inside a related population (i.e. collection of genomes). The performance of the genetic markers is computed by a distance value which takes into account both sensitivity and specificity. In this study we report two examples of GTEvaluator application. In the first example <i>Bacillus</i> phenotypic markers were evaluated for their capacity to distinguish <i>B</i>. <i>cereus</i> from <i>B</i>. <i>thuringiensis</i>. In the second experiment, GTEvaluator measured the performance of genetic markers dedicated to the molecular serotyping of <i>Salmonella enterica</i>. In one <i>in silico</i> experiment it was possible to test 64 markers onto 134 genomes corresponding to 14 different serotypes.</p></div

Typological variables describing the ‘presence’ (i.e. i = 1 or j = 1) and ‘absence’ (i.e. i = 0 or j = 0) of genetic markers (x_ij) across subgroups of studied genomes (<i>g</i>).

<p>The genomes from the targeted subgroup and other subgroups are called <i>g</i>₁ and <i>g</i>₀, respectively.</p

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Graphical representation of the distances and uncertainties implemented in GTEvaluator for the genetic markers fliC and fljB for <i>Salmonella enterica</i> serotype Typhimurium.

<p>Confidence intervals of sensitivity and specificity of FliC (black) and FljB (grey) markers are represented according to their abilities to distinguish between 20 genomes of <i>S</i>. Typhimurium and 114 genomes of other serotypes of <i>Salmonella enterica</i>.</p

Simulated distances and uncertainties of specificity and sensibility implemented in GTEvaluator.

<p>A distance value (<i>d</i>) defines the performance of a marker in term of specificity (S_p) and sensitivity (S_e) across considered subgroups of genomes (Fig 2a). The uncertainty on specificity and sensitivity is presented for 100 (Fig 2b), 200 (Fig 2c), and 300 (Fig 2d) genomes in the dataset. A potential genomic marker of a given subgroup of genomes (x_ij) is defined by his presence (i or j = 1) and absence (i or j = 0) in genomes of this subgroup (i) and others (j). Specificity and sensitivity are constant values (i.e. S_e = 0.900 and S_p = 0.977), and the targeted subgroup represents 20% of the genome dataset in the present simulation.</p

GTEvaluator workflow.

<p>The lists of genetic markers and genomes are the input files of a ‘GTEvaluator’ script which is based on the ‘fuzznuc’ pattern finder, and constituted of ‘GTEvaluator_matrixMaker’ and ‘GTEvaluator_statistic’ scripts for matrix file production (i.e. presence or absence of genomic markers for each genome) and statistical computation (i.e. specificity, sensitivity, statistical distances, and confidence intervals), respectively.</p

Electron microscopy imaging of NEM316 WT, <i>ΔgbcO</i> mutant, and complemented strains.

<p>Bacteria were harvested in mid-log phase (OD_{600 nm} = 0.5), fixed, and prepared as described in Supporting <a href="http://www.plospathogens.org/article/info:doi/10.1371/journal.ppat.1002756#s3" target="_blank">Materials and Methods</a> (see <b><a href="http://www.plospathogens.org/article/info:doi/10.1371/journal.ppat.1002756#ppat.1002756.s005" target="_blank">Text S1</a></b>) (<b>A</b>) Representative views of scanning electron microcopy analysis illustrating the morphological alterations (size, form, and cell division abnormalities) due to <i>gbcO</i> inactivation. (<b>B, C</b>) Transmission electron microscopy views of uranyl acetate stained thin cryosections at two magnifications (see scale bars). The presence of the pellicle (electron dense outer layer) at the surface of WT and complemented strains observed at the higher magnification is highlighted with black arrows. An open triangle depicts the equatorial ring (EqR), a zone of active peptidoglycan synthesis seen in almost all WT and complemented cells but absent in the <i>ΔgbcO</i> mutant cells.</p

Structure of GBC and proposed scheme of GBC synthesis.

<p>(<b>A</b>) The multiantennary GBC is shown linked to an N-acetyl muramic (NAM) moiety, a component of PG. (<b>B</b>) The figure depicts the first steps of GBC synthesis where GbcO is proposed to catalyze the transfer of UDP-GlcNAc to a lipid phosphate carrier.</p

Decreased growth rate and lack of tunicamycin sensitivity of <i>ΔgbcO</i> mutant.

<p>(<b>A</b>) Growth curves of NEM316 WT (solid squares), Δ<i>gbcO</i> mutant (circles) and Δ<i>gbcO</i>pTCVΩ<i>gbcO</i> (empty squares) strains. Cultures were performed in TH medium without antibiotics at 37°C in 96 wells plates in triplicate. Optical densities were recorded at 600 nm in a Tecan M200 apparatus with 5 sec agitation before measure. Average values of a typical experiment are presented. (<b>B</b>) Effect of various concentrations of tunicamycin on the growth rate of WT (solid squares), <i>ΔgbcO</i> (black circles) and Δ<i>gbcO</i>pTCVΩ<i>gbcO</i> (empty squares) strains. Tunicamycin, a general inhibitor of UDP-GlcNAc:lipid phosphate carrier transferase activities, inhibits the growth of WT and complemented strains but not that of <i>ΔgbcO</i> mutant suggesting that GbcO carries this activity. Experiments were performed in triplicate and results are reported as a percentage of the growth rate in absence of tunicamycin. Error bars represent ± S.E. of triplicate experiments.</p

Fluorescent immunolocalization of the putative peptidoglycan hydrolase PcsB.

<p>Exponentially growing NEM316 WT, <i>ΔgbcO</i> mutant and Δ<i>gbcO</i>pTCVΩ<i>gbcO</i> complemented strains were harvested, transferred to glass slide, and fixed. IFM with anti-PcsB serum and DAPI staining were performed as described in <a href="http://www.plospathogens.org/article/info:doi/10.1371/journal.ppat.1002756#s3" target="_blank">Materials and Methods</a>.</p