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      Two salivary proteins Sm10 and SmC002 from grain aphid Sitobion miscanthi modulate wheat defense and enhance aphid performance

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          Abstract

          The grain aphid Sitobion miscanthi is a serious pest of wheat that causes severe economic damage by sucking phloem sap and transmitting plant viruses. Here, two putative salivary effector homologs from S. miscanthi (Sm10 and SmC002) were selected based on sequence similarity to other characterized aphid candidate effectors. These effectors were then delivered into wheat cells separately via the type III secretion system of Pseudomonas fluorescens to elucidate their functions in the regulation of plant defenses and host fitness. The results showed that the delivery of either Sm10 or SmC002 into wheat plants significantly suppressed callose deposition and affected the transcript levels of callose synthase genes. The expression levels of salicylic acid (SA)-associated defense genes were upregulated significantly in wheat leaves carrying either Sm10 or SmC002. Moreover, LC-MS/MS analysis revealed that wheat SA levels significantly increased after the delivery of the two effectors. The results of aphid bioassays conducted on the wheat plants carrying Sm10 or SmC002 showed significant increases in the survival and fecundity of S. miscanthi. This study demonstrated that the Sm10 and SmC002 salivary effectors of S. miscanthi enhanced host plant susceptibility and benefited S. miscanthi performance by regulating wheat defense signaling pathways.

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          Most cited references58

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          Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) Method.

          The two most commonly used methods to analyze data from real-time, quantitative PCR experiments are absolute quantification and relative quantification. Absolute quantification determines the input copy number, usually by relating the PCR signal to a standard curve. Relative quantification relates the PCR signal of the target transcript in a treatment group to that of another sample such as an untreated control. The 2(-Delta Delta C(T)) method is a convenient way to analyze the relative changes in gene expression from real-time quantitative PCR experiments. The purpose of this report is to present the derivation, assumptions, and applications of the 2(-Delta Delta C(T)) method. In addition, we present the derivation and applications of two variations of the 2(-Delta Delta C(T)) method that may be useful in the analysis of real-time, quantitative PCR data. Copyright 2001 Elsevier Science (USA).
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            The plant immune system.

            Many plant-associated microbes are pathogens that impair plant growth and reproduction. Plants respond to infection using a two-branched innate immune system. The first branch recognizes and responds to molecules common to many classes of microbes, including non-pathogens. The second responds to pathogen virulence factors, either directly or through their effects on host targets. These plant immune systems, and the pathogen molecules to which they respond, provide extraordinary insights into molecular recognition, cell biology and evolution across biological kingdoms. A detailed understanding of plant immune function will underpin crop improvement for food, fibre and biofuels production.
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              NLStradamus: a simple Hidden Markov Model for nuclear localization signal prediction

              Background Nuclear localization signals (NLSs) are stretches of residues within a protein that are important for the regulated nuclear import of the protein. Of the many import pathways that exist in yeast, the best characterized is termed the 'classical' NLS pathway. The classical NLS contains specific patterns of basic residues and computational methods have been designed to predict the location of these motifs on proteins. The consensus sequences, or patterns, for the other import pathways are less well-understood. Results In this paper, we present an analysis of characterized NLSs in yeast, and find, despite the large number of nuclear import pathways, that NLSs seem to show similar patterns of amino acid residues. We test current prediction methods and observe a low true positive rate. We therefore suggest an approach using hidden Markov models (HMMs) to predict novel NLSs in proteins. We show that our method is able to consistently find 37% of the NLSs with a low false positive rate and that our method retains its true positive rate outside of the yeast data set used for the training parameters. Conclusion Our implementation of this model, NLStradamus, is made available at:
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                Author and article information

                Contributors
                Journal
                Front Plant Sci
                Front Plant Sci
                Front. Plant Sci.
                Frontiers in Plant Science
                Frontiers Media S.A.
                1664-462X
                28 March 2023
                2023
                : 14
                : 1104275
                Affiliations
                [1] 1 State Key Laboratory for Biology of Plant Diseases and Insect Pests, Institute of Plant Protection, Chinese Academy of Agricultural Sciences , Beijing, China
                [2] 2 Ministry of Agricultural and Rural Affairs-Centre for Agriculture and Bioscience International (MARA-CABI) Joint Laboratory for Bio-Safety, Institute of Plant Protection, Chinese Academy of Agricultural Sciences , Beijing, China
                Author notes

                Edited by: Isabel Diaz, Polytechnic University of Madrid, Spain

                Reviewed by: Bernardus C. J. Schimmel, University of Bern, Switzerland; Archana Singh, University of Delhi, India

                *Correspondence: Yong Zhang, zhangyong02@ 123456caas.cn ; Julian Chen, chenjulian@ 123456caas.cn

                This article was submitted to Plant Pathogen Interactions, a section of the journal Frontiers in Plant Science

                Article
                10.3389/fpls.2023.1104275
                10086322
                255ee4df-ec87-49e3-9f71-fc62b16a0b09
                Copyright © 2023 Fu, Liu, Wang, Liu, Cheng, Li, Zhang and Chen

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 22 November 2022
                : 13 March 2023
                Page count
                Figures: 10, Tables: 1, Equations: 0, References: 58, Pages: 13, Words: 6671
                Funding
                Funded by: National Natural Science Foundation of China , doi 10.13039/501100001809;
                Award ID: 31871979, 31901881
                Funded by: Agricultural Science and Technology Innovation Program , doi 10.13039/501100012421;
                Award ID: CAAS-ZDRW202108
                This study was financially supported by the National Natural Science Foundation of China (Nos. 31871979, 31901881), Agricultural Science and Technology Innovation Program (CAAS-ZDRW202108) and China’s Donation to the CABI Development Fund (IVM10051).
                Categories
                Plant Science
                Original Research

                Plant science & Botany
                sitobion miscanthi,salivary effectors,wheat,defense responses,aphid performance,bacteria type iii secretion system

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