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      Computational models in plant-pathogen interactions: the case of Phytophthora infestans

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          Abstract

          Background

          Phytophthora infestans is a devastating oomycete pathogen of potato production worldwide. This review explores the use of computational models for studying the molecular interactions between P. infestans and one of its hosts, Solanum tuberosum.

          Modeling and conclusion

          Deterministic logistics models have been widely used to study pathogenicity mechanisms since the early 1950s, and have focused on processes at higher biological resolution levels. In recent years, owing to the availability of high throughput biological data and computational resources, interest in stochastic modeling of plant-pathogen interactions has grown. Stochastic models better reflect the behavior of biological systems. Most modern approaches to plant pathology modeling require molecular kinetics information. Unfortunately, this information is not available for many plant pathogens, including P. infestans. Boolean formalism has compensated for the lack of kinetics; this is especially the case where comparative genomics, protein-protein interactions and differential gene expression are the most common data resources.

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          Most cited references59

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          Phytophthora genome sequences uncover evolutionary origins and mechanisms of pathogenesis.

          Draft genome sequences have been determined for the soybean pathogen Phytophthora sojae and the sudden oak death pathogen Phytophthora ramorum. Oömycetes such as these Phytophthora species share the kingdom Stramenopila with photosynthetic algae such as diatoms, and the presence of many Phytophthora genes of probable phototroph origin supports a photosynthetic ancestry for the stramenopiles. Comparison of the two species' genomes reveals a rapid expansion and diversification of many protein families associated with plant infection such as hydrolases, ABC transporters, protein toxins, proteinase inhibitors, and, in particular, a superfamily of 700 proteins with similarity to known oömycete avirulence genes.
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            Elicitors, effectors, and R genes: the new paradigm and a lifetime supply of questions.

            The plant basal immune system can detect broadly present microbe-associated molecular patterns (MAMPs, also called PAMPs) and induce defenses, but adapted microbes express a suite of effector proteins that often act to suppress these defenses. Plants have evolved other receptors (R proteins) that detect these pathogen effectors and activate strong defenses. Pathogens can subsequently alter or delete their recognized effectors to avoid defense elicitation, at risk of a fitness cost associated with loss of those effectors. Significant research progress is revealing, among other things, mechanisms of MAMP perception, the host defense processes and specific host proteins that pathogen effectors target, the mechanisms of R protein activation, and the ways in which pathogen effector suites and R genes evolve. These findings carry practical ramifications for resistance durability and for future resistance engineering. The present review uses numerous questions to help clarify what we know and to identify areas that are ripe for further investigation.
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              Organization of genes controlling disease resistance in the potato genome.

              Nineteen single dominant genes (R genes) for resistance to viruses, nematodes, and fungi have been positioned on the molecular map of potato using DNA markers. Fourteen of those genes are located in five "hotspots" for resistance in the potato genome. Quantitative trait loci (QTL) for resistance to late blight caused by the oomycete Phytophthora infestans, to tuber rot caused by the bacterium Erwinia carotovora ssp. atroseptica, and to root cyst nematodes have been identified on all 12 potato chromosomes. Some QTL for resistance to different pathogens are linked to each other and/or to resistance hotspots. Based on the genetic clustering with R genes, we propose that some QTL for resistance have a molecular basis similar to single R genes. Mapping potato genes with sequence similarity to cloned R genes of other plants and other defense-related genes reveals linkage between candidate genes, R genes, and resistance QTL. To explain the molecular basis of polygenic resistance in potato we propose (a) genes having structural similarity with cloned R genes and (b) genes involved in the defense response. The "candidate gene approach" enables the identification of markers highly useful for marker-assisted selection in potato breeding.
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                Author and article information

                Journal
                Theor Biol Med Model
                Theoretical Biology & Medical Modelling
                BioMed Central
                1742-4682
                2009
                12 November 2009
                : 6
                : 24
                Affiliations
                [1 ]Mycology and Phytopathology Laboratory, Department of Biological Sciences, Universidad de los Andes, Bogotá, Colombia
                [2 ]Bioinformatics center, Colombian EMBnet node, Biotechnology Institute, National University of Colombia, Bogotá, Colombia
                [3 ]Department of Chemical Engineering, Virginia Polytechnic Institute and State University, Blacksburg Virginia, USA
                [4 ]Grupo de Diseño de Productos y Procesos, Department of Chemical Engineering, Los Andes University, Bogotá, Colombia
                [5 ]Fundación IDEA, Centro de Biociencias, Hoyo de la puerta, Baruta 1080, Venezuela
                Article
                1742-4682-6-24
                10.1186/1742-4682-6-24
                2787490
                19909526
                ce9dbaff-4a5c-42f8-91cb-ad0ac6968e42
                Copyright ©2009 Pinzón et al; licensee BioMed Central Ltd.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 30 April 2009
                : 12 November 2009
                Categories
                Review

                Quantitative & Systems biology
                Quantitative & Systems biology

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