Genome-Wide Identification of HrpL-Regulated Genes in the Necrotrophic Phytopathogen Dickeya dadantii 3937

Abstract

Background Dickeya dadantii is a necrotrophic pathogen causing disease in many plants. Previous studies have demonstrated that the type III secretion system (T3SS) of D. dadantii is required for full virulence. HrpL is an alternative sigma factor that binds to the hrp box promoter sequence of T3SS genes to up-regulate their expression.Methodology/Principal FindingsTo explore the inventory of HrpL-regulated genes of D. dadantii 3937 (3937), transcriptome profiles of wild-type 3937 and a hrpL mutant grown in a T3SS-inducing medium were examined. Using a cut-off value of 1.5, significant differential expression was observed in sixty-three genes, which are involved in various cellular functions such as type III secretion, chemotaxis, metabolism, regulation, and stress response. A hidden Markov model (HMM) was used to predict candidate hrp box binding sites in the intergenic regions of 3937, including the promoter regions of HrpL-regulated genes identified in the microarray assay. In contrast to biotrophic phytopathgens such as Pseudomonas syringae, among the HrpL up-regulated genes in 3937 only those within the T3SS were found to contain a hrp box sequence. Moreover, direct binding of purified HrpL protein to the hrp box was demonstrated for hrp box-containing DNA fragments of hrpA and hrpN using the electrophoretic mobility shift assay (EMSA). In this study, a putative T3SS effector DspA/E was also identified as a HrpL-upregulated gene, and shown to be translocated into plant cells in a T3SS-dependent manner.Conclusion/SignificancesWe provide the genome-wide study of HrpL-regulated genes in a necrotrophic phytopathogen (D. dadantii 3937) through a combination of transcriptomics and bioinformatics, which led to identification of several effectors. Our study indicates the extent of differences for T3SS effector protein inventory requirements between necrotrophic and biotrophic pathogens, and may allow the development of different strategies for disease control for these different groups of pathogens.

Negative Autogenous Control of the Master Type III Secretion System Regulator HrpL inPseudomonas syringae

“…HrpL readily formed insoluble inclusion bodies when overexpressed for protein purification, here (data not shown) and in previous studies (12, 27). Therefore, the solubility of HrpL and HrpL ΔR4.2 was maintained via copurification in complex with an E. coli RNAP with a His tag at the β subunit (28).…”

HopX1 in Erwinia amylovora Functions as an Avirulence Protein in Apple and Is Regulated by HrpL

“…Forty-four percent of the set of genes predicted in our work probably differ because the profiles used differ in the set of hrp boxes and the alignment of the training set. As in previous work (16,17,26,37,40), our profiles are conserved in the Ϫ35 region of the promoter sequences; however, they differ in the spacer region length and the Ϫ10 region (GGAAC-19-20-ACNNA). These differences are enough to identify different promoter sequences on the same genome or produce different scores.…”

“…phaseolicola 1448A (16,17) and hrp boxes characterized in E. amylovora (31). The recent work of Yang et al (40) identified 73 genes preceded by putative hrp boxes in Dickeya dadantii using HMM profiles based on a training set of 69 hrp boxes from E. amylovora, D. dadantii, Pectobacterium atrosepticum, and P. syringae. Only one orthologous gene was common to our findings.…”

Galaxy tools and workflows for sequence analysis with applications in molecular plant pathology

“…This package aims to identify a specific secretion signal in the N-terminal region of bacterial proteins. An alternative approach to identification of type III effectors, taking into account genomic context, would be to identify the distinctive HrpL alternative sigma factor binding site often found upstream of type III effector genes (Yang et al, 2010; Baltrus et al, 2011; McNally et al, 2011). In general, expression in parasitic life stages is a useful criterion for identifying candidate effector genes, and so tools for the prediction or identification of promotor binding sites are an area we hope to incorporate into our Galaxy setup.…”