Abstract
BackgroundAdvances in forward and reverse genetic techniques have enabled the discovery and identification of several plant defence genes based on quantifiable disease phenotypes in mutant populations. Existing models for testing the effect of gene inactivation or genes causing these phenotypes do not take into account eventual uncertainty of these datasets and potential noise inherent in the biological experiment used, which may mask downstream analysis and limit the use of these datasets. Moreover, elucidating biological mechanisms driving the induced disease resistance and influencing these observable disease phenotypes has never been systematically tackled, eliciting the need for an efficient model to characterize completely the gene target under consideration.ResultsWe developed a post-gene silencing bioinformatics (post-GSB) protocol which accounts for potential biases related to the disease phenotype datasets in assessing the contribution of the gene target to the plant defence response. The post-GSB protocol uses Gene Ontology semantic similarity and pathway dataset to generate enriched process regulatory network based on the functional degeneracy of the plant proteome to help understand the induced plant defence response. We applied this protocol to investigate the effect of the NPR1 gene silencing to changes in Arabidopsis thaliana plants following Pseudomonas syringae pathovar tomato strain DC3000 infection. Results indicated that the presence of a functionally active NPR1 reduced the plant’s susceptibility to the infection, with about 99% of variability in Pseudomonas spore growth between npr1 mutant and wild-type samples. Moreover, the post-GSB protocol has revealed the coordinate action of target-associated genes and pathways through an enriched process regulatory network, summarizing the potential target-based induced disease resistance mechanism.ConclusionsThis protocol can improve the characterization of the gene target and, potentially, elucidate induced defence response by more effectively utilizing available phenotype information and plant proteome functional knowledge.
Highlights
Advances in forward and reverse genetic techniques have enabled the discovery and identification of several plant defence genes based on quantifiable disease phenotypes in mutant populations
This enables the identification of differentially infected plants used to ascertain the role of non-expressor of pathogenesis-related 1 (NPR1) in Arabidopsis plant defence response with bacteria spore count data collected from Arabidopsis wild type (Wt) and npr1 mutant leaves 48 h post Pst-DC3000 infection as described in the “Methods” section
We predicted the potential NPR1-based regulatory network based on the identified set of putative proteins, enriched biological processes and pathways which participate in plant defence response
Summary
Advances in forward and reverse genetic techniques have enabled the discovery and identification of several plant defence genes based on quantifiable disease phenotypes in mutant populations. Pathogenic organisms have been repeatedly reported to cause outbreaks on bean, cucumber, stone fruit, kiwi and olive tree, as well as on other crop and noncrop plants [1]. Plants respond to these attacks by switching on an array of defence pathways whose end products serve to limit the progression of invading pathogens. The innate response is the first stratum and earliest form of response reported It involves interaction between pathogen associated molecular patterns (PAMP/MAMP) from the invading pathogen, and the plant’s membranelocalized pattern recognition receptors [2,3,4]. In 1999, Pieterse and Van Loon [8] highlighted the existence of yet another form of systemic response called induced systemic response (ISR), which can occur independently of the HR and SAR
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