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Quantitative Proteomics Reveals the Dynamic Regulation of the Tomato Proteome in Response to Phytophthora infestans.

ABSTRACT: Late blight (LB) disease is a major threat to potato and tomato production. It is caused by the hemibiotrophic pathogen, Phytophthora infestans. P. infestans can destroy all of the major organs in plants of susceptible crops and result in a total loss of productivity. At the early pathogenesis stage, this hemibiotrophic oomycete pathogen causes an asymptomatic biotrophic infection in hosts, which then progresses to a necrotrophic phase at the later infection stage. In this study, to examine how the tomato proteome is regulated by P. infestans at different stages of pathogenesis, a data-independent acquisition (DIA) proteomics approach was used to trace the dynamics of the protein regulation. A comprehensive picture of the regulation of tomato proteins functioning in the immunity, signaling, defense, and metabolism pathways at different stages of P. infestans infection is revealed. Among the regulated proteins, several involved in mediating plant defense responses were found to be differentially regulated at the transcriptional or translational levels across different pathogenesis phases. This study increases understanding of the pathogenesis of P. infestans in tomato and also identifies key transcriptional and translational events possibly targeted by the pathogen during different phases of its life cycle, thus providing novel insights for developing a new strategy towards better control of LB disease in tomato.

SUBMITTER: Fan KT

PROVIDER: S-EPMC8073981 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:The oomycete pathogen Phytophthora infestans causes potato and tomato late blight, a disease that is a serious threat to agriculture. P. infestans is a hemibiotrophic pathogen, and during infection, it scavenges nutrients from living host cells for its own proliferation. To date, the nutrient flux from host to pathogen during infection has hardly been studied, and the interlinked metabolisms of the pathogen and host remain poorly understood. Here, we reconstructed an integrated metabolic model of P. infestans and tomato (Solanum lycopersicum) by integrating two previously published models for both species. We used this integrated model to simulate metabolic fluxes from host to pathogen and explored the topology of the model to study the dependencies of the metabolism of P. infestans on that of tomato. This showed, for example, that P. infestans, a thiamine auxotroph, depends on certain metabolic reactions of the tomato thiamine biosynthesis. We also exploited dual-transcriptome data of a time course of a full late blight infection cycle on tomato leaves and integrated the expression of metabolic enzymes in the model. This revealed profound changes in pathogen-host metabolism during infection. As infection progresses, P. infestans performs less de novo synthesis of metabolites and scavenges more metabolites from tomato. This integrated metabolic model for the P. infestans-tomato interaction provides a framework to integrate data and generate hypotheses about in planta nutrition of P. infestans throughout its infection cycle.IMPORTANCE Late blight disease caused by the oomycete pathogen Phytophthora infestans leads to extensive yield losses in tomato and potato cultivation worldwide. To effectively control this pathogen, a thorough understanding of the mechanisms shaping the interaction with its hosts is paramount. While considerable work has focused on exploring host defense mechanisms and identifying P. infestans proteins contributing to virulence and pathogenicity, the nutritional strategies of the pathogen are mostly unresolved. Genome-scale metabolic models (GEMs) can be used to simulate metabolic fluxes and help in unravelling the complex nature of metabolism. We integrated a GEM of tomato with a GEM of P. infestans to simulate the metabolic fluxes that occur during infection. This yields insights into the nutrients that P. infestans obtains during different phases of the infection cycle and helps in generating hypotheses about nutrition in planta.

Project description:Potato late blight is one the most important crop diseases worldwide. Even though potato has been studied for many years, the potato disease late blight still has a vast negative effect on the potato production [1], [2], [3]. Late blight is caused by the pathogen Phytophthora infestans (P. infestans), which initiates infection through leaves. However, the biological activities during different stages of infection are poorly described, and could enable novel or improved ways of defeating late blight infection [4]. Therefore, we investigated the interactions between P. infestans (mixed strain culture) and potato (Solanum tuberosum). Three commercially available field potato cultivars of different resistance to late blight infection; Kuras (moderate), Sarpo Mira (highly resistant) and Bintje (very susceptable) were grown under controlled green house conditions and inoculated with a diversity of P. infestans populations. We used label-free quantitative proteomics to investigate the infection with P. infestans in a time-course study over 258 h. Several key issues limits proteome analysis of potato leaf tissue [5], [6], [7]. Firstly, the immense complexity of the plant proteome, which is further complicated by the presence of highly abundant proteins, such as ribulose bisphosphate carboxylase/oxygenase (RuBisCO). Secondly, plant leaf and potato, in particular, contain abundant levels amounts of phenols and polyphenols, which hinder or completely prevent a successful protein extraction. Hitherto, protein profiling of potato leaf tissues have been limited to few proteome studies and only 1484 proteins have been extracted and comprehensively described [5], [8], [9]. We here present the detailed methods and raw data by optimized gel-enhanced label free quantitative approach. The methodology enabled us to detect and quantify between 3248 and 3529 unique proteins from each cultivar, and up to 758 P. infestans derived proteins. The complete dataset is available via ProteomeXchange, with the identifier PXD002767.

Project description:AtGenExpress: A multinational coordinated effort to uncover the transcriptome of the multicellular model organism Arabidopsis thaliana (Hybridisations done at NASC) The activity of genes and their encoded products can be regulated in several ways, but transcription is the primary level, since all other modes of regulation (RNA splicing, RNA and protein stability, etc.) are dependent on a gene being transcribed in the first place. The importance of transcriptional regulation has been underscored by the recent flood of global expression analyses, which have confirmed that transcriptional co-regulation of genes that act together is the norm, not the exception. Moreover, many studies suggest that evolutionary change is driven in large part by modifications of transcriptional programs. An essential first step toward deciphering the transcriptional code is to determine the expression pattern of all genes. With this goal in mind, an international effort to develop a gene expression atlas of Arabidopsis has been underway since fall 2003. This project, dubbed AtGenExpress, is funded by the DFG, and will provide the Arabidopsis community with access to a large set of Affymetrix microarray data. As part of this collaboration, we have generated expression data from 80 biologicaly different samples in triplicate. Series 2: Base line experiment for pathogen infection. Growth and infection conditions: Seeds will be stratified for 3 days at 4°C and sown on soil. Plants are grown at 22°C under a 8/16 hour light/dark regime in Percival growth chambers. All pathogen treatments will be performed on leaves of 5-weeks old plants. Bacterial infiltrations will be performed with 10-8 cfu/ml in 10 mM MgCl2. 5x105 spores of Phytophthora infestans in water will be applied to leaf surfaces. LPS (100 µg/ml), HrpZ (1 µM), NPP1 (2 µM) or flagellin (1 µM flg22) will be applied in water. Experiments should be performed in triplicate at the time points indicated below. Experimenter name = Dierk Scheel , Frederic Brunner , Lore Westphal Experimenter institute = AtGenExpress Keywords: genetic_modification_design; organism_part_comparison_design; development_or_differentiation_design

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Quantitative Proteomics Reveals the Dynamic Regulation of the Tomato Proteome in Response to Phytophthora infestans.

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