List of MLST primers used in this study.

<p>5’- 3’oligonucleotide sequences are shown.</p

An ArcGIS map indicating the location of AOD-affected sites in England, sampled in this study.

<p>The shape indicates the distribution of the ancestral clusters 1 and 2, i.e. square = both clusters, circle = cluster 2 only as estimated by maximum likelihood method and STRUCTURE analysis (Figs <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0178390#pone.0178390.g003" target="_blank">3</a> and <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0178390#pone.0178390.g005" target="_blank">5</a>, respectively). Green background indicate woodland areas.</p

Phylogenetic tree of 44 <i>B</i>. <i>goodwinii</i> strains based on a concatenated sequence of 7 housekeeping gene fragments (abc, dnaJ, dnaN, gyrB, infB, nusA, rpoB).

<p>The evolutionary history was inferred by using the Maximum Likelihood method based on the Hasegawa-Kishino-Yano model (HKY+G+I) <i>with</i> estimated transition/transversion bias value. The tree with the highest log likelihood (-13387.9427) is shown. Initial tree for the heuristic search was obtained automatically by applying Neighbor-Join and BioNJ algorithms to a matrix of pairwise distances estimated using the Maximum Composite Likelihood approach, and then selecting the topology with superior log likelihood value. The tree is drawn to scale, with branch lengths measured in the number of substitutions per site. The numbers at the nodes represent the relative distance between the strains with bootstrap support from 1000 resampled datasets. Individual Sequence Type (ST) numbers are indicated. Different colour nodes show the four corresponding clusters estimated by the Discriminant Analysis of Principal Components (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0178390#pone.0178390.g004" target="_blank">Fig 4</a>). Blue and orange colour branches indicate a separation into 2 clusters of STs within the population, whereas green colour branch indicate the recombinant genotype as estimated by STRUCTURE analysis (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0178390#pone.0178390.g005" target="_blank">Fig 5</a>). <i>Gibbsiella quercinecans</i> type strain FRB97 (Brady <i>et al</i>., 2010) was used as the outgroup (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0178390#pone.0178390.s001" target="_blank">S1 Fig</a>).</p

A scatterplot of the discriminant analysis of principal components (DAPC) of <i>B</i>. <i>goodwinii</i> Sequence Types, showing four clusters of STs.

<p>Only the first two principal components of the DAPC are shown (horizontal and vertical axes, respectively). Green rectangle indicates ST3 which is estimated to be an admixed genotype by STRUCTURE with the cluster assignment ratio at 50:50% (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0178390#pone.0178390.g005" target="_blank">Fig 5</a>).</p

Bar chart showing frequency of STs within the studied population of 44 <i>B</i>. <i>goodwinii</i> strains.

<p>A frequency of ST occurrence is represented on the Y axis.</p

Average abundance of culturable pathogen indicator bacteria in sediment (CFU/100 g wet weight) and water (CFU/100<b> </b>ml) across 21 estuarine sample sites.

<p>Average abundance of culturable pathogen indicator bacteria in sediment (CFU/100 g wet weight) and water (CFU/100<b> </b>ml) across 21 estuarine sample sites.</p

Sediment Composition Influences Spatial Variation in the Abundance of Human Pathogen Indicator Bacteria within an Estuarine Environment

<div><p>Faecal contamination of estuarine and coastal waters can pose a risk to human health, particularly in areas used for shellfish production or recreation. Routine microbiological water quality testing highlights areas of faecal indicator bacteria (FIB) contamination within the water column, but fails to consider the abundance of FIB in sediments, which under certain hydrodynamic conditions can become resuspended. Sediments can enhance the survival of FIB in estuarine environments, but the influence of sediment composition on the ecology and abundance of FIB is poorly understood. To determine the relationship between sediment composition (grain size and organic matter) and the abundance of pathogen indicator bacteria (PIB), sediments were collected from four transverse transects of the Conwy estuary, UK. The abundance of culturable <i>Escherichia coli</i>, total coliforms, enterococci, <i>Campylobacter</i>, <i>Salmonella</i> and <i>Vibrio</i> spp. in sediments was determined in relation to sediment grain size, organic matter content, salinity, depth and temperature. Sediments that contained higher proportions of silt and/or clay and associated organic matter content showed significant positive correlations with the abundance of PIB. Furthermore, the abundance of each bacterial group was positively correlated with the presence of all other groups enumerated. <i>Campylobacter</i> spp. were not isolated from estuarine sediments. Comparisons of the number of culturable <i>E. coli</i>, total coliforms and <i>Vibrio</i> spp. in sediments and the water column revealed that their abundance was 281, 433 and 58-fold greater in sediments (colony forming units (CFU)/100<b> </b>g) when compared with the water column (CFU/100<b> </b>ml), respectively. These data provide important insights into sediment compositions that promote the abundance of PIB in estuarine environments, with important implications for the modelling and prediction of public health risk based on sediment resuspension and transport.</p></div

Quantitative PCR analysis of amplification efficiencies of an artificial microbial community comprising five cloned 16S rRNA genes of canine oral bacteria.

<p>The artificial community was generated by mixing ratios of known gene copy number (A9, C10, F10, E3 and E9 in the ratio of 1:3:8:2:10, respectively), followed by 10, 20 or 30 cycles of PCR amplification using the universal bacterial primer set applied in this study. The resulting community PCR amplicons were subjected to qPCR analysis using clone-specific primer sets to determine the relative ratios of each clone in the final amplification mix. Error bars represent the standard error of the mean from 3 independent biological replicates. Data from each biological replicate were obtained from three experimental replicates.</p

Bacterial abundance (CFU/100 g wet weight) compared to sediment grain size, organic matter content in sediments and bacterial abundance in the water column (CFU/100 ml), across four transverse transects.

<p>(A) Transect 1, (B) Transect 2, (C) Transect 3, (D) Transect 4. The X-axis represents sample points (n = 3 replicate samples for A, B, C and D except for sediment samples site 13, n = 2), mean values are plotted and error bars represent the SEM).</p

Abundance of the sequenced reverse-transcribed Small Sub-Unit rRNA molecules from the canine oral cavity.

<p>Domain- and phylum level classification and abundance of Archaea, Bacteria and Eukarya using BION-meta and SILVA database version 115. Only phyla with a relative abundance > 0.1% have been included.</p