Metabolic and miR Profiling of TMV Infected Plants Figure 6. TMV and SHMV infected plants miRNAs and mRNA targets accumulation levels at early time points by qPCR. Relative accumulation of miRNAs 156, 164, 165/6, 167 and 171 (A,B), and miRNAs 156, 166, and 171 target genes (C,D) on virus-infected plants with low inoculum. A ratio between each virus- and mock-inoculated plants is shown at 6 days post inoculation (dpi) (A,C) and 11 dpi (B,D). * means p- value,0.1; ** means p-value,0.05 and *** means p-value,0.01. doi:10.1371/journal.pone.0028466.g006 correlation analysis, with the significance threshold set at p,0.001. The resultant matrix revealed a dense correlation network in infected plants comprising 249 significant connections (Figure 8A). In contrast the same analysis in mock-inoculated samples rendered a network of only 69 significant connections (Figure 8B). In order to reduce the complexity of the figure, all the detected fatty acid (fatty), all detected chlorogenate-related compounds (CGA) and all nicotianoside related compounds (Nicotianoside) detected were assembled in three single separated groups represented as three single nodes. In addition, in order to look for putative links between the global gene expression modulators miRNAs, and metabolic pathways networks following infection the same correlation analyses were calculated including metabolites and miRNAs profiles during virus infection. Correlations of miRNAs and metabolites were calculated in the same way as described above setting the threshold at R.0.5 and p = 0.01 due to the smaller sample size and only metabolite-miRNA and miRNA-miRNA correlations are shown. Once again, correlation network was obtained from the infected plants which displayed 49 significant connections (Figure 8C) whilst 37 significant connections were observed in mock-inoculated samples (Figure 8D). Furthermore, there were 31 new correlations in infected samples not present in the mock-inoculated samples and in contrast 17 that were present in the mock-inoculated samples were lost after infection. Interestingly miR408 was the miRNA showing a hub behavior with the highest number of links to metabolites. In inoculated samples miR408 correlated with metabolites of the respiratory pathway citrate, isocitrate, glutarate and pyruvate. In contrast, these links were not evidenced in mock-inoculated samples. Discussion Plant viral infections often produce a variety of disease symptoms, presumably by interfering with developmental process- es, including altering cell division and/or expansion and symmetry, and/or by causing loss of pigmentation [50]. Many different approaches have been used to study plant-virus interactions including microarray, small RNA deep sequencing, infection of mutant plants, mutant viruses, virus replication/ movement and NMR-based metabolomics [2,39,51,52,53,54,55]. Here, we obtained GC/LC-MS based metabolic profiles and miRNAs profiles during a compatible virus infection and both sets of data were analyzed in combination. We found that TMV infection triggers a systemic biphasic temporal regulation of metabolism. The first phase occurs 24 hours post-inoculation and is characterised by an increase in the levels of metabolites occurring in the absence of detectable virus in sampled tissue and potentially ‘‘priming the plant’’. The second phase was characterized by both, up- and down-regulated metabolites and the number of the changes correlated with the increment in virus accumulation over time. It seems reasonable to speculate that some metabolic changes observed at the early stage are probably the sensors and later PLoS ONE | www.plosone.org 7 December 2011 | Volume 6 | Issue 12 | e28466