Additional file 1: Figure S1. of Nanoparticle exposure reactivates latent herpesvirus and restores a signature of acute infection

Average Size and size distribution of the used NP. Figure S2. Measurement of cell viability. Figure S3. Exposure to NP reactivates lytic virus in persistently infected cells in vitro in a dose dependent manner. Figure S4. Exposure to NP reactivates lytic virus in persistently infected cells independently of the particle aspect ratio. Figure S5. Short-time exposure of latently infected mice to NP differentially regulates gene expression in whole lung tissue cells independently of the particle aspect ratio. Figure S6. Confirmation of gene expression data by real-time quantitative PCR for selected genes. Figure S7. Exposure of latently infected mice to CNP leads to an increase in glycerophospholipids. Figure S8. Exposure of latently infected mice to DWCNT leads to an increase in glycerophospholipids. Figure S9. Exposure of persistently infected cells to TiO2 NP or DEP has differential effects on virus reactivation in vitro. Table S1. Gene expression values of selected genes (PDF 1767 kb

Distance dendrograms showing the similarity groups based on the pairwise comparison of the following metabolomes: cellular soluble (SN2) fraction from Santa Pola strains (A); cellular insoluble (pellet) fraction from Santa Pola strains (C); cellular soluble (SN2) fraction from Mallorca strains (C); and cellular insoluble (pellet) fraction from Mallorca strains.

<p>The blue line indicates the 10% clustering threshold (see below) for which no discriminant statistical model could be found to support the groupings observed. The green line indicates the 40% clustering threshold for which a good statistical support based on metabolite differences could be found. Diagram (B) shows the rarefaction curves based on distinct clustering threshold. Table (C) shows the correspondence of the Ward distance of the dendrogram with the percent of clustering of the strains. We take 100% clustering as a Ward distance of 26000. In green it is indicated the 40% threshold for which the grouping has statistical support, and in blue that of 10% for which no support was found. Some strains are marked with stars for comparison with <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0064701#pone-0064701-g001" target="_blank">Figure 1</a>.</p

Distribution in the different metabolic classes of the annotable metabolites responsible for the differences between old and new isolates in each of the analyzed datasets.

<p>Distribution in the different metabolic classes of the annotable metabolites responsible for the differences between old and new isolates in each of the analyzed datasets.</p

Number of metabolites responsible for the discrimination between old (reference strains) and new isolates for each experimental set.

<p>The number of masses corresponds to those identified as CHONS in where the isotopes had been removed. SN2 refers to the cellular soluble fraction, and PELLET to the cellular insoluble fraction. Annotable masses refer to those whose molecular formula could be assigned to a given metabolite using <i>Salinibacter ruber</i> strains genomic data.</p><p>1- Total number of masses in the corresponding fraction for the analyzed strain; in brackets, the range of metabolites found in the different strains.</p><p>2- In brackets, the percentage of masses of the discriminative metabolome, and the corresponding set of strains set of strains (new) or (old) respectively.</p

Left column: diagrams based on supervised OPLS analyses showing the discrimination of the different isolates old (blue dots) and new (black dots) of the fractions: cellular soluble fraction of Mallorca new isolates SN2-RM (A) and Santa Pola new isolates SN2- SP (B); and cellular insoluble fractions of Mallorca new isolates Pellet-RM (C) and Santa Pola new isolates Pellet- SP (D).

<p>Grey dots represent the core metabolome of all isolates that do not offer any discrimination. The selection of the compounds is done taking in account the different magnitude of correlation and covariance. The highest value for each list is associated the value 100%. This is the reference percentage and all other values are scaled accordingly to it. The value that present both value of percentages above 50% have been assumed to be a candidate that can be investigate in MassTRIX, the percentage has been set up as a cut-off of the data.</p

Number of metabolites responsible for the discrimination among the different metabolic types observed within each set of new strains of Santa Pola and Mallorca.

<p>The candidate discriminative metabolites have a VIP value equal or greater than 1.</p

Distribution in the different metabolic classes of the annotable discriminative metabolites responsible for the clusters shown in Figure S5.

<p>Data from all co-occuring strains (A) and from the different fractions (B).</p

Diagrams based on unsupervised PCA analysis of all metabolites present in the cellular soluble fraction of the new isolates (black dots) and old isolates (blue dots) showing the relative homogeneity of the old isolates.

<p>(A) PCA of the cellular soluble fraction (SN2– SP) of the experimental set of Santa Pola isolates; (B) PCA of the cellular soluble fraction (SN2– RM) of the experimental set of Mallorca isolates; (C) PCA of the cellular insoluble fraction (Pellet – SP) of the experimental set of Santa Pola isolates (in this case the best distribution was observed with the components 3 and 4; and (D) PCA of the cellular insoluble fraction (SN2– RM) of the experimental set of Mallorca isolates.</p

Similarity dendrogram (left) comparing the analyzed <i>Salinibacter ruber</i> strains using UPGMA analysis of their <i>Xba</i>I genomic restriction products separated by PFGE (right).

<p>Framed in red, reference strains isolated in 2000 and used here as controls. Stars mark pairs of closely related strains from the same origin for comparison with <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0064701#pone-0064701-g005" target="_blank">Figure 5</a>.</p