- Open Access
Discovery of the molecular mechanisms of the novel chalcone-based Magnaporthe oryzae inhibitor C1 using transcriptomic profiling and co-expression network analysis
© The Author(s) 2016
- Received: 24 May 2016
- Accepted: 26 September 2016
- Published: 22 October 2016
In our previous studies, we discovered a series of chalcone-based phytopathogenic fungus inhibitors. However, knowledge of their effects, detailed targets and molecular mechanisms in Magnaporthe oryzae (M. oryzae) remained limited.
To explore the expression and function of differentially expressed genes in M. oryzae after treatment with compound C1, we analyzed the expression profile of mRNAs using a microarray analysis and GO, KEGG and WGCNA analysis, followed by qRT-PCR and Western blots to validate our findings.
A total of 1013 up-regulated and 995 down-regulated mRNAs were differentially expressed after M. oryzae was treated with C1 compared to those of the control samples. Among these, cytochrome P450, glycylpeptide N-myristoyltransferase (NMT) and peroxisomal membrane protein 4 were identified as the most significant DEGs and were validated by experiments.
In conclusion, our study suggests that the combination of transcriptomic microarray, bioinformatics analysis and weighted gene co-expression networks can be used to predict potential therapeutic targets and to map the pathways regulated by small molecular natural product-like drugs.
- Magnaporthe oryzae
- Gene co-expression network
- Molecular docking
Fungal infections are one of the most important phytopathogens that affects agricultural output (Lu et al. 2014; Moghaddam et al. 2015; Moreira et al. 2015). Some fungicides have been used to control these diseases and protect livestock, but their use has led to toxic chemical accumulation in the environment, causing servere environmental and public health problems (Kim et al. 2014; Wang et al. 2015; Wu et al. 2014; Lopez et al. 2006, 2011; Svetaz et al. 2007). Of the phytopathogenic fungi, Magnaporthe oryzae is one of the most common rice blast pathogens; M. oryzae is resilient to environmental stresses such as changes in nutrients, illumination and temperature (Duan et al. 2014; Hao et al. 2012a, b). M. oryzae has gradually become resistant to existing fungicides; consequently, it is essential to discover novel, environmentally friendly compounds with high antifungal activity and clear molecular mechanisms of action (Xu et al. 2015; Dong et al. 2015; Wang et al. 2014; Chen et al. 2013).
In vitro antifungal assay
The antifungal activity of compound C1 against B. maydis, S. scleotiorum, M. orzae, G. zeae and B. cintrea was investigated by measuring the inhibitory effects of radial growth in a petri dish with agar medium. Briefly, compound C1 was dissolved in DMSO, diluted with a 1 % Tween solution to the appropriate concentration and added to a glucose/potato/water agar medium to reach the final concentration. The medium was then poured into 9.0 cm diameter sterile Petri dishes, and a mycelial disk (0.5-cm diameter) cut from the growing culture was placed in the center of the agar plate. The inhibitory effects of C1 on radial growth was measured after several days. Inhibitory growth ratios were calculated as the percentage of the inhibition of radial growth relative to the control group.
RNA isolation and labeling
Total mRNA was extracted from M. orzae samples using TRIzol, according to the manufacturer’s instructions. A NanoDrop ND-2000 was used to assess the concentration and quality of RNA before the extracted RNA was denatured for agarose gel electrophoresis. The purified RNA was amplified and transcribed into fluorescent cRNA after the removal of rRNA according to Agilent’s Quick Amp Labeling protocol.
Microarray analysis was performed by Boao Bio-tech, Beijing, China. Briefly, the labeled cRNAs were hybridized onto the 4 × 44 K Agilent Microarray (Arraystar, Rockville, MD) at 65 °C for 17 h. An Agilent Microarray Scanner G2565BA was used to collect the hybridization images. The transcriptomic data extraction and analysis were performed using the Agilent Feature Extraction package and GeneSpring GX v11.5.1 software, respectively.
The compound C1 was submitted to various web-based inverse docking servers: TarFisDock (Gao et al. 2008; Li et al. 2006), DRAR-CPI (Luo et al. 2011), and PharmMapper (Wang et al. 2016; Liu et al. 2010). These web servers selected the known target proteins within their collections to profile the scaffolds that had potential binding affinity.
The Target Fishing Dock (TarFisDock) identified the potential target proteins of submitted molecules in the Potential Drug Target Database using the DOCK 4.0 molecular docking program (Kang et al. 2004; Ewing et al. 2001); only the top 2 % of potential targets were considered for further study. The PharmMapper server is a structure-based pharmacophore approach that accelerates the screening of putative binding targets for small molecular drugs (Wang et al. 2016). The DRAR-CPI server predicts adverse drug reactions and therapeutic indications for small molecular drugs based on the interaction profile of molecules towards their targets (Iyer et al. 2015; Chen 2014).
GO & KEGG enrichment analysis
Gene Ontology (GO) analysis is an annotation set including gene descriptions and gene product attributes for many organisms (http://www.geneontology.org) (Chicco and Masseroli 2016; Anney et al. 2011; Harris et al. 2004; Ashburner et al. 2000). Gene ontology has three components: cellular components, biological processes and molecular functions. The overlaps between the lists of DEGs were detected by Fisher’s exact test. P-value denotes the significance of a GO term enrichment in DEGs clusters and/or pathway correlations (P-value < 0.05 was considered significant). In addition, the pathway enrichment was used to map DEGs into KEGG pathways (Ogata et al. 1999; Ogata et al. 1998).
Weighted gene co-expression network analysis (WGCNA)
WGCNA is a statistical tool to cluster genes that have a similar expression pattern across a group of samples (Malki et al. 2013; DiLeo et al. 2011; Langfelder and Horvath 2008). The input data for the WGCNA were the normalized gene expression values for each sample. First, all available samples from each groups were collected to identify modules that had different expression patterns. Next, a soft threshold was assigned to create networks with a scale free topology, using the method developed by Horvath et al. After the networks were built, many gene modules with similar expression patterns were created, and the eigengenes of these modules were calculated. Finally, correlations between these eigengenes and the factor of interest were calculated.
Quantitative real-time PCR (qRT-PCR)
Total mRNA was extracted from M. orzae using TRIzol (Invitrogen), according to the manufacturer’s protocols. mRNAs were then converted into cDNA using a Fermentas RT kit. qRT-PCR was performed in a total reaction volume of 25 μL (including 12.5 μL of SYBR Premix Ex Taq (2×), 2 μL of cDNA, 1 μL of forward primer (10 μM), 1 μL of reverse primer (10 μM), 0.5 μL of ROX Reference Dye II (50×), and 8 μL of double-distilled water). The amplification conditions were as follows: 10 min at 95 °C to initiate denaturation; 40 cycles of 5 s at 95 °C, 30 s at 63 °C, and 30 s at 72 °C; and a final extension for 5 min at 72 °C. The amplification efficiency was evaluated using standard curve fitting. All samples were normalized to actin, and the experiment was performed with three duplicates.
Western blot analysis
Briefly, the total protein of C1-treated M. orzae was extracted with RIPA buffer (SolarBio, Beijing, China), which contained 1 % (v/v) PMSF (SolarBio), 0.3 % (v/v) protease inhibitor (Sigma, St. Louis, MO, USA) and 0.1 % (v/v) phosphorylated proteinase inhibitor (Sigma). Then, the supernatant was collected after centrifugation at 12,000 rpm for 10 min with refrigeration. The concentration of total protein was quantified using a BCA protein assay kit (Pierce, Waltham, MA, USA). The total protein was separated via standard SDS-PAGE gel electrophoresis and then transferred to PVDF membranes. The membranes were further treated with skimmed milk or BSA to block non-specific binding. The primary antibodies were added to PVDF membranes for two hours at room temperature or overnight at 4 °C. Finally, the primary antibodies bound to the membranes were incubated with HRP-conjugated secondary antibodies (Abmart, Shanghai, China). The target proteins were detected using an ECL kit (enhanced chemiluminescence kit, Millipore, Billerica, MA, USA) according to the manufacturer’s instructions.
C1 efficiently inhibited a panel of phytopathogens
The in vitro antifungal results of compound C1 are shown in Fig. 1b, c. The results demonstrate that C1 showed variable degrees of antifungal activity against the tested phytopathogen fungi. The inhibitory ratio at 20 μg/mL clearly demonstrates that C1 exhibited 100 % inhibition against R. solani and an inhibition of 60–80 % against B. maydis, S. scleotiorum, M. orzae, G. zeae and B. cintrea. Moreover, the EC50 index of compound C1 for the tested fungi was in the range of 1.20–37.84 at 20 μg/mL, much lower than that of the positive control compound, carbendazim, on R. solani and M. orzae (Fig. 1c).
Inverse docking results
Differential expression of genes after C1 treatment determined by transcriptome microarray
Numbers of mRNAs differentially expressed after C1 treatment 24 h
Number of DEGs
The top GO biological process terms of DEGs
GO:0055114 (oxidation–reduction process)
GO:0044271 (cellular nitrogen compound biosynthetic process)
GO:0005375 (copper ion transmembrane transporter activity)
GO:0009103 (lipopolysaccharide biosynthetic process)
GO:0043581 (mycelium development)
GO:0000105 (histidine biosynthetic process)
The enriched KEGG pathways in the DEGs
The first level
Xenobiotics biodegradation and metabolism
Metabolism of terpenoids and polyketides
Amino acid metabolism
Transport and catabolism
Biosynthesis of other secondary metabolites
Metabolism of cofactors and vitamins
Amino acid metabolism
Weighted gene co-expression analysis
qRT-PCR and Western-blot confirmation
As a novel chalcone-based phytopathogenic fungi inhibitor, C1 has good potency in protecting against the infections of various pathogens. In the current study, we found that the compound C1 could efficiently inhibit the mycelium development of M. oryzae, one of the most important pathogenic fungi of rice. After performing reverse-docking using three different methods, we predicted the potential target proteins of compound C1. The results indicated the possibility that cytochrome p450, N-myristoyltransferase (NMT), β(1,3)-glucansynthase and chitin synthase interact with compound C1. Furthermore, we evaluated the differential expression of mRNAs between C1-treated and control samples of M. oryzae using microarray analysis. Among the 13,448 embedded genes, 2008 were significantly differentially expressed. Furthermore, cytochrome p450, N-myristoyltransferase (NMT) and peroxisomal membrane protein 4 (PXMP4) were significantly differentially expressed. Collectively, these findings showed that compound C1 influenced the expression of P450, NMT and PXMP4 in M. oryzae and that inhibited mycelium development and exerted oxidative stress via regulation of relative downstream gene expression. In line with these results, GO analysis revealed that the DEGs were mainly enriched for GO terms associated with the response to mycelium development and oxidation–reduction processes. The KEGG pathway analysis also indicated that metabolism-associated pathways, such as xenobiotics biodegradation metabolism pathways, were the most enriched pathways. The pathway enrichment results are consistent with those of the GO term analysis, supporting the notion that mycelium development is blocked at an early stage of metabolism inhibition. Based on our data from the GO and pathway analysis, we constructed a weighted gene co-expression network to further analyze the correlations of DEGs. It has been suggested that P450, NMT and PXMP4 may be hub genes and correlate with cell death and the regulation of metabolism induced by compound C1 treatment. In general, Cytochrome P450 genes (CYPs) were key heme-proteins in primary and secondary metabolism pathways and are responsible for most oxidative/reductive reactions in the xenobiotics metabolism (Hernandez-Martinez et al. 2016; Aung et al. 2014). CYPs could detoxified and transformed various xenobiotic compounds, e.g. CYPs could converted some aromatic hydrophobic xenobiotic chemicals into non-toxic and water-soluble less metabolites via the diverse xenobiotics degradation and metabolism processes. In addition, it has been reported that M. oryzae and other rice blast pathogenic fungus species could tolerated high concentrations nonpolar xenobiotic chemicals. Herein, we identified that cytochrome P450 genes that might be involved in the biodegradation of xenobiotic compounds of the host plants and in sterol biosynthesis and resistance to environmental stress. It had been well known that CYPs family was one of the most abundant and diverse in M. oryzae. Numbers of reports had suggested that members of CYPs family to lipopolysaccharide metabolism, drug resistance, and xenobiotics metabolism by the oxidation/reduction pathways (Hernandez-Martinez et al. 2016; Huang et al. 2014; Chen et al. 2014). The CYPs family had a number of isoforms that exhibit diverse conversion capacities towards long chain alkanes, fatty acids or related molecules with different structures. In particular, it was reported that CYP proteins such as CYP1A1 could maintained signals by its trans-membrane domains and then made them localized ER proteins (Cotman et al. 2004; Szczesna-Skorupa and Kemper 2001; Szczesna-Skorupa et al. 2003). On the contrary, when such signals is lacking, proteins are transported to other regions within the cell, as was the case for the human CYP1A1. Therefore, the peroxisomal CYPs might played important roles in the metabolism of xenobiotic compounds, biosynthesis of cholesterol and hydroxylation of lipopolysaccharide, etc. In previous studies, some studies also suggested mitochondrial P450 cytochromes could be stimulated by ER P450s (Hernandez-Martinez et al. 2016; Jung and Di Giulio 2010); moreover, further studies were demanded to better understand the role of the diverse biological functions of P450s in M. oryzae. To confirm the above analyses, the expression of mRNAs and proteins were detected using qRT-PCR and Western blotting, respectively. These experimental results were highly consistent with the microarray and bioinformatics analyses; taken together, our findings indicate that P450 and NMT are the direct target proteins of compound C1 and that PXMP4 plays an important role in the signaling transduction networks induced by C1.
In conclusion, our study suggests that the combination of transcriptomic microarray, bioinformatics analysis and weighted gene co-expression networks can be used to predict the potential targets and regulated pathways of small molecular natural product-like drugs. Moreover, we have shown that these high-throughput and computational results could be validated using various experimental methods. We have indicated an approach for profiling potential target and molecular mechanism in species with limited genomic and/or signaling pathway knowledge. We believe that this target profiling workflow can be helpful for identifying novel targets for therapeutics and for overcoming drug resistance to rare pathogens.
RL and TH conceived and designed the experiments; HC and XW performed the experiments; HC and HJ analyzed the data; HC, RL and TH wrote the paper. All authors read and approved the final manuscript.
This work is financially supported by the National Natural Science Foundation of China (81402245).
The authors declare that they have no competing interests.
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