PCR amplicons from the <i>E. coli</i> clinical isolates, grouped by primer set.

<p>Composite (negative) images from multiple agarose gels have been aligned against the matching isolate designation (left hand column) and below the primer names (top row). The image has been split so that Group 1 isolates are located in the top section, Group 2 isolates in the second and the positive and negative controls at the bottom. The HUSEC isolates within Group 2 are bounded by dashed lines and <i>E. coli</i> HUSEC041 indicated in red font.</p

Statistical performance metrics for diagnostic primer sets.

<p>The confusion matrix counts (TP: true positive; FP: false positive; TN: true negative; FN: false negative) derived from the experimental validation tests against unseen isolates of <i>E. coli</i> are presented. No false negatives were identified by any individual primer set. Derived performance measures are also indicated (PPV: positive predictive value; FPR: false positive rate; FDR: false discovery rate; F-measure: 2×recall×precision/(recall+precision)). All primer sets amplify all positive examples, and have specificity between 82–94%, with 9–22% false discovery rate.</p

Schematic diagram of the primer design process.

<p>A training set of whole (complete or draft) genome sequences is divided into positive and negative sequence groups. Members of the positive sequence group are placed into classes as appropriate (here as classes I–V on the basis of a nested hierarchical relationship). Primer sets are designed to all positive sequences in bulk (>1000 primer sets, black markers), and tested for cross-hybridisation <i>in silico</i>. Primer sets that amplify only members of a prescribed class (indicated by coloured markers, one for each class; black markers indicate non-specific primers) but do not amplify negative examples are retained as being potentially diagnostic of that class. Predicted discriminatory primers are validated against bacterial isolates that were not part of the training set. An expected mock PCR result is indicated for primers specific to group II against individual samples belonging to classes II, IV and V. A detailed description of the method is given in Supplementary Methods.</p

Flowchart of the primer design process.

<p>The locations of input training set sequence files, and their classifications, are read from a configuration file. Input sequences comprising several smaller sequences (e.g. contigs of a draft genome) are concatenated using a spacer sequence. Locations of coding sequences (CDS) are obtained from a GenBank file if available, or predicted using a genecaller. A large number (>1000) of primers is then designed to each input sequence. Primers that lie within CDS are tested <i>in silico</i> for their ability to cross-amplify other members of the training set, and compared against a larger set of off-target sequences to discard non-specific primers. The surviving primers are classified according to their ability to amplify specific classes of sequence from the training set. A more detailed flowchart of the pipeline is given in Supplementary <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0034498#pone.0034498.s001" target="_blank">Figure S1</a>.</p

Phenotypes of EibG-strains after agitation and static growth.

<p>Strain 2875/96 was inoculated for 20h at 37°C with and without shaking. Bacteria grown under agitated conditions grew homogenously and were turbid without biofilm formation (A). However, statically grown bacteria aggregated and deposited a biofilm (A). Aggregates and deposits were stained with crystal violet (B). Strain 659/97 was used as EibG negative control. Microscopically, shaken bacteria demonstrated single and non-aggregated cells whereas static grown bacteria formed coherent chains (C). The figures exemplify microscopic images of strain 2875/96 and 0520/99, magnified as indicated.</p

STEC strains used in this study.

<p>STEC strains used in this study.</p

EibG expression under static growth conditions and with agitation.

<p>Cells of several STEC strains carrying the <i>eib</i>G gene were inoculated in LB medium with (+) and without (-) shaking at 37°C for 16h. Proteins were separated by SDS-PAGE and immunoblotted. (A, B) To compare expression levels, identical protein quantities of 7.5 μg were loaded in each lane. EibG was detected with human IgG Fc conjugated with HRP on immunoblots and visualized by chemiluminescence. Glyceraldehyde-3-phosphate dehydrogenase (GAPDH) was used as marker protein and as control for loading. Marker sizes (M) and EibG proteins are indicated. (C) Proteins of strain 0520/99 were diluted serially as indicated and immunoblotted to demonstrate specifity and sensitivity to the detection platform. To standardize between immunoblots, the highest intensities were defined as 1.0 and the ratios of the diluted signals of three independent gel runs were calculated as means (± standard deviations of the means). Intensities of static grown bacteria and agitated cultures are shown by black and grey bars, respectively.</p

Phenotypical characteristics of EibG expression.

<p>Phenotypical characteristics of EibG expression.</p

Oligonucleotide primers used in PCR reaction.

<p>Oligonucleotide primers used in PCR reaction.</p

Temperature and pH have an influence on EibG expression.

<p>Bacteria were incubated in LB with different pH values as indicated at 37°C and 23°C with agitation (+) and under static growth conditions (-). Proteins were immunoblotted and EibG signals were measured using chemiluminescence. The influence of temperature (A), pH values (B) and both in combination (C) are shown for wild-type strain 2875/96. Marker sizes (M) are provided.</p