Candidate Crinkler (CRN) effectors of P. parasitica (PpCRN)
Here, we explored the available genomes of P. parasitica deposited under the international project “Phytophthora parasitica genome initiative” database (https://www.ncbi.nlm.nih.gov/assembly/?term=phytophthora%20parasitica) to obtain the genome data of P. parasitica isolates from different hosts and geographic origins, to study the CRN effectors.
We identified 80 candidate genes encoding PpCRN effector proteins in the genome of P. parasitica isolate ‘IAC_01/95.1’ (Fig. 1). Similarly, candidate PpCRN effectors were found in the genomes of other P. parasitica isolates, with the isolate ‘P10297’ showing the highest number of PpCRN candidates (106), and the isolate ‘CHvinca01’ the least number (78). The conserved LxLFLAK motif was identified in several PpCRN candidates from distinct P. parasitica genomes, but it showed a variation in terms of quantity and sequence diversity from one genome to another (Fig. 1). Secretory signal peptides were predicted in only six PpCRN candidates, namely PpCRN2, PpCRN5, PpCRN7, PpCRN10, PpCRN14 and PpCRN20, which corresponds to 7.5% of total candidate proteins identified in the genome of isolate ‘IAC 01/95.1’.
The genome architecture can provide information about the function, regulation and adaptation of genes [15]. In Phytophthora species, some regions are rich in replicate and sparse genes, which are related to pathogenicity, including effector-coding genes. The P. parasitica genome shows a heterogeneous distribution according to the size of the intergenic regions. The genome architecture of the P. parasitica isolate IAC 01_95 is shown in Fig. 2. The flanking distance (intergenic region) between neighbouring genes provides a measurement of the local distribution of gene density, which can be plotted into two-dimensional graph based on the length of intergenic regions between neighbouring genes, at their 5′- and 3′-end. The genome architecture of P. parasitica shows that 20 selected CRN genes are located at the sparse region of the genome (Fig. 2). In the sparse region, due to its plasticity, the chances of emerging a new effector or simply evolving an already existing protein is more likely to happen than in the dense region.
In order to verify the similarity between the identified putative PpCRN protein sequences and previously described CRNs, a Neighbour-Joining tree was predicted using all identified PpCRNs and CRN sequences from the Uniprot database (Fig. 3a). The wide distribution of PpCRN sequences over the tree shows a great sequence divergence between them. This distribution pattern was also followed by the P. infestans sequences used in the tree. In order to address this high divergence between PpCRN sequences, we searched for common motifs between them. Twenty-two motifs were predicted as present in at least three of the total sequences (Fig. 3b). The identification of distinct CRN motifs was named from M1 to M22 (Fig. 3b). Sequences and additional information of the 80 PpCRN candidates are shown in the Additional file 1.
All 80 predicted PpCRNs from the isolate ‘IAC_01/95.1’ genome were used as query for searching homologous genes within other eight genomes from different isolates of P. parasitica, which are named ‘P1569.1’, ‘P1976.1’, ‘INRA-310.3’, ‘P10297.1’, ‘CJ01A1.1’, ‘CJ05E6.1’, ‘CHvinca01’,‘CJ02B3.1’ (Fig. 4). We have found similar PpCRNs in the genomes of other P. parasitica isolates by applying a Blastp search using the 80 PpCRN candidates protein sequences of the ‘IAC_01/95.1’ genome as query. This genomic approach revealed the distribution and proximity of genomes to the eighty PpCRNs of the ‘IAC_01/95.1’ isolate. Similar sequences to PpCRN7 and PpCRN20 were found in all nine P. parasitica genomes (Additional file 3: Fig. S1), whereas PpCRN4 and PpCRN40 are unique to the ‘IAC_01/95.1’ genome (Fig. 4a). Based on the 80 candidate PpCRNs, our analyses revealed that the closest genome to P. parasitica isolate ‘IAC_01/95.1’ is the isolates ‘P1569.1’ and ‘CJ05E6’ from citrus and tobacco (Fig. 4a). Most of the PpCRN candidates predicted in the isolate ‘IAC_01/95.1’ were also found in the other isolates, varying from 64 out of 80 candidates in the citrus isolate ‘P1569.1’ to 56 out of 80 candidates in the tobacco isolate ‘INRA-310.3’ (Fig. 4b). 35 predicted PpCRNs (43.75%) from isolate ‘IAC_01/95.1’ are also found in all other eight isolates, with at least one corresponding protein found in each P. parasitica isolate genome, presenting more than 95% identity and 50% coverage (Fig. 4c).
Predicted PpCRNs are transcriptionally deregulated during Citrus-P. parasitica interaction
Twenty PpCRN candidates were selected for gene expression analysis during the plant-pathogen interaction between P. parasitica and two Citrus species (C. sunki and P. trifoliata). We chose these two citrus species because they have contrasting response to Phytophthora parasitica infection; Citrus sunki is susceptible and Poncirus trifoliata is resistant to this pathogen. These candidates, PpCRN1 to PpCRN20, were selected based on the presence of one or more of the following features: (i) presence of a secretion signal peptide; (ii) absence of transmembrane domains; (iii) differential gene expression in other plant-pathogen interaction studies; (iv) presence of conserved CRN domain; (v) nuclear or subcellular localization signals; (vi) sequence homology with effectors from other species; (vii) PpCRN gene located at the sparse regions of the genome.
Gene expression analysis revealed an expressional dynamics of PpCRN effectors during the interaction of P. parasitica with the citrus plants. Our analysis showed that these PpCRN family members had their transcriptional levels altered, according to the citrus species and infective stage [11, 21] (Figs. 5, 6 and Additional file 4: Figure S2). Figure 5 shows that, in P. trifoliata, the vast majority of PpCRNs candidate genes were up-regulated along the time points, except for PpCRN1, PpCRN7 and PpCRN10 that were suppressed, at least in one time-point. PpCRN4, which is unique to the isolate ‘IAC 01/95.1’ genome, had the highest differential expression level detected among the PpCRN candidates, followed by PpCRN16 and PpCRN18, both exhibiting high levels of transcripts. The candidates PpCRN9, PpCRN11 and PpCRN12, showed constant expression levels throughout the time points analysed. In addition, PpCRN7 expression were initially suppressed at 3 h post inoculation (hpi) and then returned steadily to basal levels at the 6 h time-point onwards, whereas PpCRN20 were slightly induced 6 dpi onwards (Fig. 5).
In C. sunki, most of PpCRNs were transcriptionally induced (Fig. 6). However, PpCRN4, PpCRN9 and PpCRN12 transcripts were down-regulated at all time-points. PpCRN8 and PpCRN13 expression showed partial suppression in most of the time-points; at 96 hpi, an increase in their transcriptional levels were detected. Contrastingly, PpCRN7 and PpCRN20 expression were induced throughout the development of the disease, with PpCRN7 showing the highest differential expressional level among all PpCRN candidates (Fig. 6). Recently our group published data showing that P. parasitica has the ability to recognize and regulate gene expression levels of effectors CRN, RxLR, Elicitin, CBEL and NPP-1 over time and as a function of interaction with C. sunki and P. trifoliata [11].
Functional characterization of the PpCRN7 and PpCRN20
Functional genomics were further taken to explore the potential role of two candidate PpCRN effectors, which are supposed to modulate cellular and molecular responses in host plants. Our in silico analyses identified that the candidate effectors PpCRN7 and PpCRN20 would be good candidates for characterization, as both showed: (i) secretory peptide signals; (ii) absence of transmembrane domains; (iii) genome location at the sparse regions; (iv) presence in all genomes of P. parasitica isolates herein analyzed, with a high degree of sequence identity; and (v) presence of known conserved CRN domains (Additional file 3: Figure S1 and Additional file 1).
Therefore, to reveal the functional role of PpCRN7 and PpCRN20, a transient expression assay was carried out via agrotransformation in N. benthamiana leaves. The insertion of PpCRN7 and PpCRN20 transgenes in the plant-expressing vector pCambia1302 (Additional file 5: Figure S3A) was confirmed by gel eletroforesis after enzymatic digestion. The nucleotide fragments corresponds to the expected size of PpCRN7 (430 pb) and PpCRN20 (439 pb) (Additional file 5: Figure S3B). Furthermore, the expression of the proteins PpCRN7 and PpCRN20 in plant was confirmed by Western blotting (Additional file 5: Figure S3C). These constructs were then used to evaluate the effect of PpCRN7 and PpCRN20 to induce or supress HR in N. benthamiana leaves by co-expressing them along with the elicitin INF-1 - a known cell death induction factor [22, 23]. The elicitin INF-1 is well known to induce HR in Nicotianae species. Therefore, it is commonly used in functional characterization studies of effectors [23].
PpCRN7 enhances INF-1-induced HR response
To test the effect of PpCRN7 expression towards the HR mediated by the elicitin INF-1, we performed agrotransformation of plant expressing vectors containing (i) empty vector, (ii) PpCRN7, (iii) INF-1, and (iv) co-expression of PpCRN7 + INF-1 (Fig. 7a). No symptoms were observed in leaves infiltrated with the empty vector or PpCRN7-containing vector alone. However, INF-1-expressing leaves showed HR response, with evident tissue necrosis in the agroinfiltrated area, as also observed in leaves co-infiltrated with PpCRN7 along with INF-1 (Fig. 7a). Therefore, transient expression of PpCRN7 + INF-1 in N. benthamiana leaves revealed a synergistic activity of the CRN effector with the elicitin, as the HR response was intensified, leading to an anticipated and more prominent occurrence of PCD.
To verify if PpCRN7 effector also affects the release of reactive oxygen species (ROS) and oxidative burst, a biochemical and colorimetric assay was performed on N. benthamiana agroinfiltrated leaves (Fig. 7b). In this assay, the substrate DAB (3,3′-diaminobenzidine) is oxidized by hydrogen peroxide, to generate a dark brown precipitate, which allows the visual detection – the darker the tissue, the more ROS released. The INF-1-expressing area appears greatly dark, indicating that ROS were produced by still-living cells, whereas in the area co-infiltrated INF-1 with PpCRN7 showed mild dark staining, compared to the area expressing INF-1 only (Fig. 7b). It suggests that cells in this area are already dead, due to the anticipation and amplification of ROS release and subsequent HR, driven by the synergistic activity of the effector PpCRN7 along with INF-1. Very likely, the biochemical target of the PpCRN7 effector is present down-stream the activation of ROS-release by INF-1, since, when alone, without INF-1, the PpCRN7 effector has no activity regarding release of ROS or induced PCD.
Additionally, we tested if the A. tumefaciens concentration, for the transient expression assay would be related to the observed HR amplification (Additional file 6: Figure S4). Agronfiltration solution were adjusted to an OD600 of 0.5 and 1.0 and used to co-infiltrate PpCRN7 along with INF-1, and empty vector (EV) along with INF-1. The results were similar as PpCRN7 enhanced INF-1-induced HR response, independent of A. tumefaciens concentration, confirming that PpCRN7 acts synergistically with INF-1 in the manipulation of plant defence mechanisms, which results in oxidative burst, programmed cell death and tissue necrosis (Additional file 6: Fig. 4).
PpCRN20 suppresses INF-1-induced HR response
The same approach was carried out to test the effect of PpCRN20 expression towards the HR mediated by INF-1. We performed agroitransformation of plant expressing vectors containing (i) empty vector, (ii) PpCRN20, (iii) INF-1, and (iv) PpCRN20 + INF-1. No symptoms were observed in leaves infiltrated with the empty vector or PpCRN20-containing vector alone (Fig. 8a). However, as expected INF-1-expressing leaves showed HR response, with evident tissue necrosis in the area that was agroinfiltrated (Fig. 8b). The co-infiltration of INF-1 along with PpCRN20 presented a strong reduction on INF-1-induced symptoms. This result suggests that PpCRN20 acts as a suppressor of INF-1-induced HR response (Fig. 8b).
The DAB assay on N. benthamiana leaves showed no ROS production when expressing either an empty vector or PpCRN20-containing vector (Fig. 8c). However, leaves co-expressing PpCRN20 along with INF-1 showed a significant decrease in ROS production when compared to INF1-expressing site (Fig. 8d). The absence of tissue necrosis and decrease on ROS production indicates that PpCRN20 may act as HR suppressor.
Transient expression of PpCRN7 and PpCRN20 increases N. benthamiana susceptibility
To understand the biological role mediated by PpCRN7 and PpCRN20 during the process of P. parasitica infection, N. benthamiana leaves were inoculated with zoospores of P. parasitica, 24 h after agrotransformation with PpCRN7- or PpCRN20-containing vectors. Leaves, transiently expressing PpCRN7 and PpCRN20, inoculated with P. parasitica zoospores developed symptoms, measured at 72 and 144 h post inoculation (hpi), including severe wilt and tissue necrosis. Whereas P. parasitica-inoculated leaves, without PpCRN expression, showed symptoms only at 144 hpi (Fig. 9a). No symptoms were observed on leaves without P. parasitica inoculation expressing either an empty vector or any PpCRN (Fig. 9a).
P. parasitica genomic DNA from leaf tissues was quantified by RT-qPCR for samples collected at 72 hpi, to verify the growth rate and colonization of the oomycete, an indicative of N. benthamiana susceptibility (Fig. 9b). Significant differences were detected in P. parasitica-inoculated plants previously infiltrated with any PpCRN-expressing vectors, and only inoculated plants (Fig. 9c). Higher amount of P. parasitica genomic DNA was found in leaves expressing PpCRN7 and PpCRN20 compared to leaves without PpCRN expression (Fig. 9b,c). Significant differences were detected in transformed and subsequently inoculated samples, when compared to only inoculated plants at 72 hpi. Leaves expressing PpCRN20 presented the highest significant amount of P. parasitica genomic DNA, followed by leaves expressing PpCRN7.