The exceptionality of stress response in Magnaporthe oryzae: a set of “salt stress-induced” genes unique to the rice blast fungus
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The ability of pathogens to signal perception and adaptation to environmental changes is an important prerequisite for successful colonization of the host organism. Filamentous phytopathogenic fungi, for example, have to cope with rapid changes in the environment during invasive growth in planta. Consequently, they have evolved a range of specific factors contributing to environmental adaptation facilitating host invasion. In addition to conserved pathways, including genes participating in stress response, unique/individual genes within the pathogens might represent determinants of pathogenicity. Therefore, identification of unique genes could provide a set of excellent candidates for novel and specific fungicide targets. One of the environmental changes during host invasion comprises the accumulation of osmolytes, which are present in varying concentrations inside the plant. Transcriptional profiling of the rice blast fungus Magnaporthe oryzae undergoing osmotic stress revealed interesting results. We identified a set of 239 genes which were regulated significantly by salt stress. Among these “salt stress-regulated” genes, 176 (75%) of the upregulated and all of the downregulated genes were found to have no homologues in yeast when interrogation against the yeast protein database was performed. Functional annotation analysis by InterProScan and clustering of genes based on gene ontology (GO) enrichment analysis was conducted to annotate each of the “salt stress-regulated” genes and to identify functional categories of biological processes associated with environmental stress response. Finally, we present a set of “salt stress-regulated” genes suggested as unique in the rice blast fungus.
KeywordsNGS Pathogenicity Environmental stress Fungicide target Osmoregulation Magnaporthe oryzae Salt stress-induced genes
The transcriptome reflects differential gene expression patterns by defining a dynamic link between an organism’s genome and its physiological properties. We conducted a comprehensive genome-wide differential expression analysis (RNA-seq) regarding 0.5 M KCl stress in the filamentous phytopathogenic fungus Magnaporthe oryzae in order to find unique gene expression profiles under “host-mimicking” environmental stresses. Using salt stress as a host-mimicking agent appears to be feasible, because salt ion concentration of nearly 0.5 M for K+ has already been documented in plant tissues [5, 6]. The resulting “salt stress-induced” genes provide a promising reservoir for novel fungicide targets, since osmoregulation of phytopathogenic fungi is already known to be a suitable target location for crop protection. The high osmolarity glycerol pathway is a druggable signalling pathway comprising different target proteins [11, 13]. Thus, the identification of genes contributing to osmoregulation or genes responsible for adaption to environmental stresses is of high interest for fungicide research.
Conidia of M. oryzae were collected from eleven-day-old complete medium agar plates  and adjusted to 105 conidia/ml. Spore suspensions were used as inoculum for liquid complete medium and incubated for 48 h at 28 °C at 100 rpm. These cultures were used to inoculate the main axenic cultures, which were cultivated for a further 24 h at 28 °C at 100 rpm. Total RNA from three biological replicates was extracted as an untreated control using the RNeasy Mini Kit (QIAGEN, plant protocol). Subsequently, RNA was extracted from the same cultures after 25-min treatment with 0.5 M KCl. Prior to transcriptome sequencing, equal amounts of total RNA derived from three biological replicates for each condition (untreated and 25 min after KCl induction) were pooled together. Library preparation was carried out using 1.5 μg of total RNA for each. The RNA-Seq readings were obtained from a 2 × 100 bp paired-end Illumina HiSeq 2000 single lane run for each condition investigated, followed by a quality check using Qualimap version 2.2  and removal of adaptor sequences. The readings retained were merged using FLASH 1.2.9 (FLASH source: http://sourceforge.net/projects flashpage/?source = dlp) and aligned to the reference genome of Magnaporthe oryzae 70-15 version 8 obtained from the Broad Institute by employing TopHat 2.0.11 . Expression levels for each gene were determined by using the CuffDiff quantification method , and reading counts were expressed as FPKM (“Fragments Per Kilobase of transcript per Million fragments mapped”) values. Only those genes, having at least a fivefold change and displaying the FPKM value of at least ten in any of the conditions investigated, affirmed by a p value of ≤ 0.05, were considered as significantly differentially expressed and were selected for further analysis. The BLASTp search against the National Centre for Biotechnology Information non-redundant database was conducted to identify functional annotation orthologues in other fungal organisms, using the taxonomy filter “fungi” (taxa 4751, Fungi) and an E-value threshold of 1.0E-3. Furthermore, a local BLASTp interrogation (using 1.0E-30 as an E-value cut-off) against the Saccharomyces cerevisiae (S288C) protein sequences obtained from the Saccharomyces cerevisiae genome database was performed to examine the proportion of corresponding DE genes. Additionally, gene ontology and functional annotation of the protein sequences deduced were employed using Blast2GO 4.0.2  via searching for best hits with the following cut-offs: E-value 1.0E-6 and an internal annotation cut-off value of 55, to classify genes into GO terms based on molecular function, biological processes and cellular components. The results from the BLASTp analysis, functional domain comparisons from InterProScan (restricted to BlastProDom, HMMPfam and TMHMM) implemented in Blast2GO and the prediction of signal peptides with SignalP 4.1 software ; http://www.cbs.dtu.dk/services/SignalP/), as well as interrogation against the PHI database (version 4.0) were used to make final assignments to GO functional categories of each gene, indicated in the final table as “customized category”. Finally, GO enrichment (by focusing exclusively on the biological process) of DE genes was computed using the TopGO package (release version 2.26.0;  implemented in Bioconductor 3.3, employing Fisher’s exact test for statistical significance to extract the maximal meaning of the RNA-Seq data. The enriched GO terms at p-values of ≤ 0.05 were retained and then slimmed in REVIGO ; http://revigo.irb.hr/) by removing redundant GO terms. Treemaps were produced to visualize enriched and non-redundant GO categories. A total of 130 of the “salt stress-regulated” genes were not suitable for GO enrichment analysis, because they represented hypothetical proteins or displayed no identity to other proteins with assigned GO terms in the database. The total list of DE genes obtained from RNA-seq analysis, containing comprehensive information regarding functional signatures for each gene, is provided in Table S1. GO annotation obtained from JGI (http://genome.jgi.doe.gov/Maggr1/Maggr1.home.html) is also provided in Table S1 for augmented comparative analysis.
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