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Molecular Genetics and Genomics

, Volume 293, Issue 4, pp 931–943 | Cite as

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

  • Xiao-Ren Chen
  • Shen-Xin Huang
  • Ye Zhang
  • Gui-Lin Sheng
  • Yan-Peng Li
  • Feng Zhu
Original Article
  • 296 Downloads

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.

Keywords

Phytophthora capsici Necrosis NLP Nlp24 Transcriptional pattern Virulence Agroinfiltration 

Notes

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.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

This article does not contain any studies with human participants or animals performed by any of the authors.

Supplementary material

438_2018_1432_MOESM1_ESM.pdf (413 kb)
Supplementary material 1 (PDF 412 KB)
438_2018_1432_MOESM2_ESM.pdf (315 kb)
Supplementary material 2 (PDF 315 KB)
438_2018_1432_MOESM3_ESM.xls (124 kb)
Supplementary material 3 (XLS 123 KB)
438_2018_1432_MOESM4_ESM.docx (24 kb)
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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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.College of Horticulture and Plant ProtectionYangzhou UniversityYangzhouChina

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