Figure 5. Temporal profiling of miRNAs accumulation follow- ing TMV infection. Systemic, non-inoculated tobacco leaves were sampled from virus- and mock-inoculated plants (n = 6 for each day and treatment) at 5, 15 and 22 dpi. miRNAs accumulation in TMV-inoculated plants were compared to those corresponding to mock-inoculated plants and the relative accumulation was calculated as the ratio between virus- and mock-inoculated samples at each time point. These ratios were log2 transformed and further analyzed with hierarchical clustering with average linkage. False-color scale indicates lower (green) or greater (red) miRNA accumulation in TMV-infected plants respect to mock-inoculated ones. The horizontal bar shows the log2-based scale. See Materials and Methods for further details. doi:10.1371/journal.pone.0028466.g005 The Supplemental Figure S5 show a ratio of CP level between infected and non infected plants for each time point; only 11 dpi showed a statistically difference, and at this time point the TMV- CP accumulation was less than 1% of the maximum level detected at 22 dpi (Supplemental Figure S5) indicating that at 11 dpi the sampled leaf is at the early stages of virus accumulation. At 6 dpi both virus infections produced a reduction of miRNA levels (Figure 6 A) of miRNAs belonging to Cluster A (miR 165/6, miR167 and mir171) confirming the microarray results at early time point. On this work we focused on miRNAs of cluster A since those miRNAs possess established link with stress response and were clear exponents of the biphasic alteration. Comparing both infections, the most severe virus (TMV) seems to produce faster effects. To determine the activity of those miRNA changes, the levels of their targets were quantified in the same samples. Even though quite recently Frazier et al [49] reported miRNAs sequences, gene structure prediction and same miRNAs sequence validation in tobacco, scarcely data about miRNA target was available for tobacco, so it was first required to select and validate Metabolic and miR Profiling of TMV Infected Plants tobacco miRNA target mRNAs. We were able to find and validated three of target genes by RNA ligase-mediated rapid amplification of cDNA ends (RLM-RACE) (Supplemental Figure S6). The target genes were: a miR156-regulated Squamosa promoter binding protein-like 2 (SPL2), a miR165/166-regulated Homeobox gene 8 (ATHB-8) and a miR170/171-regulated Scarecrow-like transcription factor 6 (SCL6). Interestingly, at 6 dpi ATHB-8 mRNA negatively correlated with miR166 levels in the TMV (most severe)-infected plants but not in the mild ShMV virus (Figure 6C). At 11 dpi in TMV-infected plants, miR156 and miR164 were up-regulated in a statistically significant manner (Figure 6B) evidencing the transition from the first to the second phase, where most of the miRNAs accumulate to higher levels (Figure 5). On the other hand, ShMV-infected plants showed an overall reduction in miRNAs accumulation levels, being miR165/166 and miR171 of statistical significance. These results suggested that miRNAs and target genes alteration might be delayed in the plants infected with the less severe virus. At 11 dpi, ShMV and TMV-infected plants showed a statistically significant increase of miR165/6 and miR171 targets (Figure 6D). Furthermore, the up-regulation of miR156 in TMV-infected plants at 11 dpi did not produce the expected alteration on SPL2 mRNA at the same infection stage. This latter behavior may indicate a reduction on the miRNA activity together with its increased accumulation levels, probably due to the virus PTGS suppressor activity. Pre-miR166 accumulation is altered upon virus infection In order to analyze whether the observed alteration on miRNAs levels at early stages of infection had a transcriptional component as observed on an earlier work at late stages of infection in Arabidopsis [21], we decided to analyze the accumulation of immature precursors of miRNAs (pre-miRNAs) by qPCR in the same samples used before (Figure 6). In spite of our effort to identify the pre-miRNAs sequence for each detected mature miRNA using the tomato (Solanum lycopersicum) and Arabidopsis orthologous genes sequences, we were only able to PCR-amplify pre-miR166a. Figure 7A shows the comparisons of sequences and the predicted structure of the tomato pre-miR166a and the tobacco fragment isolated. At 6 dpi, only the TMV-infected plants presented significant lower level of pre-miR166a compared to the mock-inoculated plants (Figure 7B). However at 11 dpi both viruses produced reductions on pre-miR166a levels (Figure 7C), in agreement with the reduced accumulation of the mature miRNAs observed, suggesting a possible transcriptional down-regulation mechanism. These data all together suggest that in the absence of detectable virus in systemic leaves (6 dpi), miR166 and pre-miR166a accumulation decrease and its target mRNA increase following the infection in the TMV-infected plants (Figures 6A and C and 7B). However, at 11 dpi the amount of pre-miRNA is reduced in plants infected with both virus (Figure 7C) showing the expected increase of ATHB-8 target mRNA level (Figure 6D). In conclusion, in agreement with the levels of symptoms both virus produced on tobacco, the most severe virus (TMV) altered miRNA accumulation and activity more rapidly than ShMV did. A massive increase in the density of correlation networks indicates a complex reprogramming of the regulatory pathways triggered by viral infection In order to assess the integrated behavior of the metabolic network during virus infection, a combinatorial analysis of metabolites was run by non-parametric Spearman’s rank-order PLoS ONE | www.plosone.org 6 December 2011 | Volume 6 | Issue 12 | e28466