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      Broad-spectrum chemicals block ROS detoxification to prevent plant fungal invasion

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          Summary

          Plant diseases cause a huge impact on food security and are of global concern. While application of agrochemicals is a common approach in the control of plant diseases currently, growing drug resistance and the impact of off-target effects of these compounds pose major challenges. The identification of pathogenicity-related virulence mechanisms and development of new chemicals that target these processes are urgently needed. One such virulence mechanism is the detoxification of reactive oxygen species (ROS) generated by host plants upon attack by pathogens. The machinery of ROS detoxification might therefore serve as a drug target for preventing plant diseases, but few anti-ROS-scavenging drugs have been developed. Here, we show that in the model system Botrytis cinerea secretion of the cytochrome c-peroxidase, BcCcp1 removes plant-produced H 2O 2 and promotes pathogen invasion. The peroxidase secretion is modulated by a Tom1-like protein, BcTol1, through physical interaction. We show that BcTol1 is regulated at different levels to enhance the secretion of BcCcp1 during the early infection stage. Inactivation of either BcTol1 or BcCcp1 leads to dramatically reduced virulence of B. cinerea. We identify two BcTol1-targeting small molecules that not only prevent B. cinerea invasion but also have effective activity against a wide range of plant fungal pathogens without detectable effect on the hosts. These findings reveal a conserved mechanism of ROS detoxification in fungi and provide a class of potential fungicides to control diverse plant diseases. The approach described here has wide implications for further drug discovery in related fields.

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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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            Protein and ligand preparation: parameters, protocols, and influence on virtual screening enrichments.

            Structure-based virtual screening plays an important role in drug discovery and complements other screening approaches. In general, protein crystal structures are prepared prior to docking in order to add hydrogen atoms, optimize hydrogen bonds, remove atomic clashes, and perform other operations that are not part of the x-ray crystal structure refinement process. In addition, ligands must be prepared to create 3-dimensional geometries, assign proper bond orders, and generate accessible tautomer and ionization states prior to virtual screening. While the prerequisite for proper system preparation is generally accepted in the field, an extensive study of the preparation steps and their effect on virtual screening enrichments has not been performed. In this work, we systematically explore each of the steps involved in preparing a system for virtual screening. We first explore a large number of parameters using the Glide validation set of 36 crystal structures and 1,000 decoys. We then apply a subset of protocols to the DUD database. We show that database enrichment is improved with proper preparation and that neglecting certain steps of the preparation process produces a systematic degradation in enrichments, which can be large for some targets. We provide examples illustrating the structural changes introduced by the preparation that impact database enrichment. While the work presented here was performed with the Protein Preparation Wizard and Glide, the insights and guidance are expected to be generalizable to structure-based virtual screening with other docking methods.
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              The Top 10 fungal pathogens in molecular plant pathology.

              The aim of this review was to survey all fungal pathologists with an association with the journal Molecular Plant Pathology and ask them to nominate which fungal pathogens they would place in a 'Top 10' based on scientific/economic importance. The survey generated 495 votes from the international community, and resulted in the generation of a Top 10 fungal plant pathogen list for Molecular Plant Pathology. The Top 10 list includes, in rank order, (1) Magnaporthe oryzae; (2) Botrytis cinerea; (3) Puccinia spp.; (4) Fusarium graminearum; (5) Fusarium oxysporum; (6) Blumeria graminis; (7) Mycosphaerella graminicola; (8) Colletotrichum spp.; (9) Ustilago maydis; (10) Melampsora lini, with honourable mentions for fungi just missing out on the Top 10, including Phakopsora pachyrhizi and Rhizoctonia solani. This article presents a short resumé of each fungus in the Top 10 list and its importance, with the intent of initiating discussion and debate amongst the plant mycology community, as well as laying down a bench-mark. It will be interesting to see in future years how perceptions change and what fungi will comprise any future Top 10. © 2012 THE AUTHORS. MOLECULAR PLANT PATHOLOGY © 2012 BSPP AND BLACKWELL PUBLISHING LTD.
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                Author and article information

                Journal
                9107782
                Curr Biol
                Curr Biol
                Current biology : CB
                0960-9822
                1879-0445
                02 August 2022
                02 August 2022
                05 August 2022
                13 October 2022
                : 32
                : 18
                : 3886-3897.e6
                Affiliations
                [1 ]College of Plant Health and Medicine, Engineering Research Center for Precision Pest Management for Fruits and Vegetables of Qingdao, Shandong Engineering Research Center for Environment-Friendly Agricultural Pest Management, Shandong Province Key Laboratory of Applied Mycology, Qingdao Agricultural University, Qingdao 266109, China
                [2 ]Tobacco Research Institute of CAAS, Qingdao 266100, China
                [3 ]College of Life Sciences, Qingdao Agricultural University, Qingdao 266109, China
                [4 ]Department of Biochemistry, University of Cambridge, Cambridge CB2 1GA, UK
                Author notes
                [* ]Correspondence: wliang1@ 123456qau.edu.cn
                [6]

                Lead contact

                Article
                EMS152247
                10.1016/j.cub.2022.07.022
                7613639
                35932761
                3637ff1e-825e-4448-b0c3-b813d4fcfd9a

                This work is licensed under a CC BY 4.0 International license.

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                Life sciences
                Life sciences

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