Overlapping Yet Response-Specific Transcriptome Alterations Characterize the Nature of Tobacco–Pseudomonas syringae Interactions

Abstract

In this study transcriptomic alterations of bacterially induced pattern triggered immunity (PTI) were compared with other types of tobacco–Pseudomonas interactions. In addition, using pharmacological agents we blocked some signal transduction pathways (Ca2+ influx, kinases, phospholipases, proteasomic protein degradation) to find out how they contribute to gene expression during PTI. PTI is the first defense response of plant cells to microbes, elicited by their widely conserved molecular patterns. Tobacco is an important model of Solanaceae to study resistance responses, including defense mechanisms against bacteria. In spite of these facts the transcription regulation of tobacco genes during different types of plant bacterial interactions is not well-described. In this paper we compared the tobacco transcriptomic alterations in microarray experiments induced by (i) PTI inducer Pseudomonas syringae pv. syringae type III secretion mutant (hrcC) at earlier (6 h post inoculation) and later (48 hpi) stages of defense, (ii) wild type P. syringae (6 hpi) that causes effector triggered immunity (ETI) and cell death (HR), and (iii) disease-causing P. syringae pv. tabaci (6 hpi). Among the different treatments the highest overlap was between the PTI and ETI at 6 hpi, however, there were groups of genes with specifically altered activity for either type of defenses. Instead of quantitative effects of the virulent P. tabaci on PTI-related genes it influenced transcription qualitatively and blocked the expression changes of a special set of genes including ones involved in signal transduction and transcription regulation. P. tabaci specifically activated or repressed other groups of genes seemingly not related to either PTI or ETI. Kinase and phospholipase A inhibitors had highest impacts on the PTI response and effects of these signal inhibitors on transcription greatly overlapped. Remarkable interactions of phospholipase C-related pathways with the proteasomal system were also observable. Genes specifically affected by virulent P. tabaci belonged to various previously identified signaling routes, suggesting that compatible pathogens may modulate diverse signaling pathways of PTI to overcome plant defense.

Transcriptome changes in Arabidopsis thaliana infected with Pseudomonas syringae during drought recovery

“…Functional categorization of D, P and DRP stress transcriptome revealed not only enriched stress responses to drought stress and defense responses but also revealed many activated genes related to other stresses namely, cold, salt, oxidative stress, high light intensity, high temperature, wounding and herbivory (Supplementary Figs S11 and S12 , Supplementary File S3 ). This data and earlier literature information on these stresses 7 , 33 suggest a probable activation of basal stress responses in D, P and DRP plants. In order to further dissect these ‘common’ molecular events, we organized DEGs under DRP treatment into stress wise categories and mapped them to different pathways.…”

Chloroplast Redox Status Modulates Genome-Wide Plant Responses during the Non-host Interaction of Tobacco with the Hemibiotrophic Bacterium Xanthomonas campestris pv. vesicatoria

“…A recent report describing genome-wide responses of tobacco plants to different microorganisms also observed generalized induction of proteasome subunits upon leaf infiltration with two non-host Pseudomonas syringae pathovars preferentially eliciting PTI or ETI responses (Bozsó et al, 2016). …”

Unraveling the molecules hidden in the gray shadows of quantitative disease resistance to pathogens

“…Through expression analysis, it was possible to demonstrate that, during incompatible, compatible and non-host interactions, gene expression profiles were almost the same and that differences consisted in the intensity and kinetics of their induction (Tao et al, 2003). Other studies support the overlap between PAMP and ETI at the gene expression level (Navarro et al, 2004;Bozsó et al, 2009;Bozso et al, 2016). For QDR, several studies have reported a direct relationship between the expression level of some genes and the degree of resistance response.…”