An NmrA-Like Protein, Lws1, Is Important for Pathogenesis in the Woody Plant Pathogen Lasiodiplodia theobromae
文献类型: 外文期刊
作者: Peng, Junbo 1 ; Aluthmuhandiram, Janith V. S. 1 ; Chethana, K. W. Thilini 2 ; Zhang, Qi 1 ; Xing, Qikai 1 ; Wang, Hui 1 ; Liu, Mei 1 ; Zhang, Wei 1 ; Li, Xinghong 1 ; Yan, Jiye 1 ;
作者机构: 1.Beijing Acad Agr & Forestry Sci, Inst Plant & Environm Protect, Beijing Key Lab Environm Friendly Management Dis, Beijing 100097, Peoples R China
2.Mae Fah Luang Univ, Ctr Excellence Fungal Res, Chiang Rai 57100, Thailand
3.Mae Fah Luang Univ, Sch Sci, Chiang Rai 57100, Thailand
关键词: Lasiodiplodia theobromae; short-chain dehydrogenase/reductase; pathogenicity; nutrition metabolism
期刊名称:PLANTS-BASEL ( 影响因子:4.658; 五年影响因子:4.827 )
ISSN:
年卷期: 2022 年 11 卷 17 期
页码:
收录情况: SCI
摘要: The NmrA-like proteins have been reported to be important nitrogen metabolism regulators and virulence factors in herbaceous plant pathogens. However, their role in the woody plant pathogen Lasiodiplodia theobromae is less clear. In the current study, we identified a putative NmrA-like protein, Lws1, in L. theobromae and investigated its pathogenic role via gene silencing and overexpression experiments. We also evaluated the effects of external carbon and nitrogen sources on Lws1 gene expression via qRT-PCR assays. Moreover, we analyzed the molecular interaction between Lws1 and its target protein via the yeast two-hybrid system. The results show that Lws1 contained a canonical glycine-rich motif shared by the short-chain dehydrogenase/reductase (SDR) superfamily proteins and functioned as a negative regulator during disease development. Transcription profiling revealed that the transcription of Lws1 was affected by external nitrogen and carbon sources. Interaction analyses demonstrated that Lws1 interacted with a putative GATA family transcription factor, LtAreA. In conclusion, these results suggest that Lws1 serves as a critical regulator in nutrition metabolism and disease development during infection.
- 相关文献
作者其他论文 更多>>
-
Microfungi Associated with Peach Branch Diseases in China
作者:Zhou, Ying;Li, Shifang;Zhou, Ying;He, Zhizheng;Zhang, Wei;Liu, Mei;Song, Jinyan;Yan, Jiye;Zhou, Ying;Fan, Zaifeng;Manawasinghe, Ishara S.
关键词:diversity; peach diseases; morphology; phylogenetic analyses; new species; new records
-
TrG2P: A transfer-learning-based tool integrating multi-trait data for accurate prediction of crop yield
作者:Li, Jinlong;Zhang, Dongfeng;Yang, Feng;Zhang, Qiusi;Pan, Shouhui;Zhao, Xiangyu;Zhang, Qi;Han, Yanyun;Wang, Kaiyi;Zhao, Chunjiang;Li, Jinlong;Zhang, Dongfeng;Yang, Feng;Zhang, Qiusi;Pan, Shouhui;Zhao, Xiangyu;Zhang, Qi;Han, Yanyun;Wang, Kaiyi;Zhao, Chunjiang;Yang, Jinliang;Yang, Jinliang
关键词:crop; genotype to phenotype; transfer learning; yield prediction; multi-trait
-
Porphyrin-based covalent organic framework as oxidase mimic for highly sensitive colorimetric detection of pesticides
作者:Liu, Qingju;Zhu, Junyi;Wang, Hui;Luan, Yunxia;Zhang, Zhikun
关键词:Porphyrin-based covalent organic framework; Oxidase mimics; Colorimetric detection; Pesticides
-
Quantification of adulterated fox-derived components in meat products by drop digital polymerase chain reaction
作者:Wang, Hui;Chen, Chen;Zhang, Yan;Chen, Boxu;Li, Yongyan;Zhou, Wei;Jia, Wenshen;Chen, Jia
关键词:Droplet digital PCR; meat adulteration; quantitative study; fox; artificial adulteration
-
Research on quantitative detection technology of raccoon-derived ingredient adulteration in sausage products
作者:Wang, Hui;Chen, Chen;Xie, Mengying;Zhang, Yan;Chen, Boxu;Li, Yongyan;Zhou, Wei;Jia, Wenshen;Chen, Jia;Chen, Jia;Zhou, Wei
关键词:droplet digital PCR; quantitative study; raccoon; sausage adulteration
-
Current trends, limitations and future research in the fungi?
作者:Hyde, Kevin D.;Gui, Heng;Hu, Yuwei;Mortimer, Peter E.;Wanasinghe, Dhanushka N.;Hyde, Kevin D.;Gui, Heng;Hu, Yuwei;Mortimer, Peter E.;Wanasinghe, Dhanushka N.;Hyde, Kevin D.;de Farias, Antonio R. Gomes;Gonkhom, Didsanutda;Jayawardena, Ruvishika S.;Khyaju, Sabin;Luangharn, Thatsanee;Phonemany, Monthien;Thongklang, Naritsada;Walker, Arttapon;Hyde, Kevin D.;Bahkali, Ali H.;Hyde, Kevin D.;Doilom, Mingkwan;Manawasinghe, Ishara S.;Senanayake, Indunil C.;Hyde, Kevin D.;Manawasinghe, Ishara S.;Baldrian, Petr;Kohout, Petr;Chen, Yanpeng;Chethana, K. W. Thilini;Maharachchikumbura, Sajeewa S. N.;Gonkhom, Didsanutda;Jayawardena, Ruvishika S.;Khyaju, Sabin;Phonemany, Monthien;Thongklang, Naritsada;Walker, Arttapon;De Hoog, Sybren;Goncalves, Micael F. M.;Hilario, Sandra;Goncalves, Micael F. M.;Gui, Heng;Hu, Yuwei;Mortimer, Peter E.;Wanasinghe, Dhanushka N.;Hilario, Sandra;Jayawardena, Ruvishika S.;Kirk, Paul M.;Maharachchikumbura, Sajeewa S. N.;Niego, Allen Grace T.;Sandargo, Birthe;Stadler, Marc;Surup, Frank;Sandargo, Birthe;Stadler, Marc;Surup, Frank;Senanayake, Indunil C.
关键词:AMF; Biocircular economy; Biocontrol; Data repositories; Drug discovery; Ecology; Emerging diseases; Functional genomics; Fungal classification; HTS; Machine learning; Mycoremediation; Nanotechnology; Novel compounds; Phylogenomics; Plant pathology; Species numbers
-
Prediction of maize cultivar yield based on machine learning algorithms for precise promotion and planting
作者:Han, Yanyun;Wang, Kaiyi;Yang, Feng;Pan, Shouhui;Liu, Zhongqiang;Zhang, Qiusi;Zhang, Qi;Han, Yanyun;Wang, Kaiyi;Yang, Feng;Pan, Shouhui;Liu, Zhongqiang;Zhang, Qiusi;Zhang, Qi
关键词:Prediction of maize cultivar yield; Machine learning; Random forest; Levenberg - Marquardt neural network; Multilayer perceptron neural network; Assessment of varieties