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Identification and functional analysis of the NLP-encoding genes from the phytopathogenic oomycete Phytophthora capsici

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Abstract

Phytophthora capsici is a hemibiotrophic, phytopathogenic oomycete that infects a wide range of crops, resulting in significant economic losses worldwide. By means of a diverse arsenal of secreted effector proteins, hemibiotrophic pathogens may manipulate plant cell death to establish a successful infection and colonization. In this study, we described the analysis of the gene family encoding necrosis- and ethylene-inducing peptide 1 (Nep1)-like proteins (NLPs) in P. capsici, and identified 39 real NLP genes and 26 NLP pseudogenes. Out of the 65 predicted NLP genes, 48 occur in groups with two or more genes, whereas the remainder appears to be singletons distributed randomly among the genome. Phylogenetic analysis of the 39 real NLPs delineated three groups. Key residues/motif important for the effector activities are degenerated in most NLPs, including the nlp24 peptide consisting of the conserved region I (11-aa immunogenic part) and conserved region II (the heptapeptide GHRHDWE motif) that is important for phytotoxic activity. Transcriptional profiling of eight selected NLP genes indicated that they were differentially expressed during the developmental and plant infection phases of P. capsici. Functional analysis of ten cloned NLPs demonstrated that Pc11951, Pc107869, Pc109174 and Pc118548 were capable of inducing cell death in the Solanaceae, including Nicotiana benthamiana and hot pepper. This study provides an overview of the P. capsici NLP gene family, laying a foundation for further elucidating the pathogenicity mechanism of this devastating pathogen.

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Acknowledgements

This work was supported by the National Natural Science Foundation of China (no. 31671971), Natural Science Foundation of Yangzhou City (China) (no. YZ2016121), the Special Fund for Agro-Scientific Research in the Public Interest of China (no. 201303018) and the Yangzhou University 2016 Project for Excellent Young Key Teachers. The authors thank Dr. Paul Morris (Bowling Green State University, OH, USA) for his critical reading of the manuscript.

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  1. College of Horticulture and Plant Protection, Yangzhou University, No. 48 Wenhui Eastern Road, Yangzhou, 225009, Jiangsu, China

    Xiao-Ren Chen, Shen-Xin Huang, Ye Zhang, Gui-Lin Sheng, Yan-Peng Li & Feng Zhu

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Correspondence to Xiao-Ren Chen.

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Communicated by S. Hohmann.

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438_2018_1432_MOESM4_ESM.docx

Supplementary material 4 Online Resource 4 Phylogenetic relationship of 10 NLPs cloned from P. capsici and 7 other microorganism-derived NLPs. The analysis was performed using the maximum likelihood algorithm in MEGA7. Percent bootstrap values (1000 replicates) are shown above the forks. Accession numbers of species: AAM48170 (PsojNIP, P. sojae), AEZ06585 (HaNLP9, H. arabidopsidis), AAS45247 (VdNLP, V. dahlia,), XP_365630 (MoNLP, M. oryzae), CAF05864 (NcNLP, N. crassa), XP_748132 (AfNLP, A. fumigatus) and ELR02678 (PdNLP, P. destructans). The scale bar shows expected changes per site (DOCX 23 KB)

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Chen, XR., Huang, SX., Zhang, Y. et al. Identification and functional analysis of the NLP-encoding genes from the phytopathogenic oomycete Phytophthora capsici. Mol Genet Genomics 293, 931–943 (2018). https://doi.org/10.1007/s00438-018-1432-7

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