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ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » Molecular Plant Pathology Laboratory » Research » Research Project #433022

Research Project: Genome-Based Strategies and Physiological Biomarkers for Detection and Identification of plant Pathogenic Phytoplasmas and Spiroplasmas

Location: Molecular Plant Pathology Laboratory

Project Number: 8042-22000-306-000-D
Project Type: In-House Appropriated

Start Date: Feb 26, 2017
End Date: Feb 25, 2022

Objective 1: Discover new genomic and physiological biomarkers potentially useful for improving detection and identification of phytoplasmas and plant pathogenic spiroplasmas [NP 303; C1, PS1] • Sub-objective 1A: Identify genomic features correlated with divergent evolutionary trajectories of plant pathogenic spiroplasmas at differing levels of taxonomic rank. • Sub-objective 1B: Identify multilocus genomic features and molecular markers of phytoplasma-plant host interactions correlated with phytoplasma genetic diversity at differing levels of taxonomic rank. • Sub-objective 1C: Identify key primary and secondary metabolites involved in early stages of pathogenesis that may have global effects on disease resistance through either their bioactive nature or redox-status of the microbiome. • Sub-objective 1D: Identify, and characterize multilocus genomic markers of, phytoplasmas carried by vectors and nonvector phloem-feeding insects in diverse agricultural and natural ecosystems. Objective 2: Expand, refine, and advance gene-based phytoplasma and spiroplasma taxonomy and classification systems; evaluate new genomic and physiological biomarkers [NP 303; C1, PS1] • Sub-objective 2A: Detect and identify new phytoplasmas associated with emerging diseases; update the ribosomal RNA gene-based phytoplasma classification scheme; enhance the functionality of the iPhyClassifier. • Sub-objective 2B: Evaluate multilocus genomic features correlated with divergent evolutionary trajectories of phytoplasmas and spiroplasmas for enhanced detection, identification, and classification of exotic and emerging strains. • Sub-objective 2C: Evaluate metabolic markers of pathogenesis for earlier detection, and enhanced identification, and classification of exotic and emerging phytoplasmas. • Sub-objective 2D: Incorporate into the gene-based phytoplasma classification system additional molecular markers of evolutionarily conserved house-keeping genes.

The proposed project unites physiology, molecular biology, and genomics in synergistic multidisciplinary research. The goal is to discover and utilize new knowledge to devise and develop new, improved technologies to detect, identify, and classify wall-less bacteria (mollicutes), (noncultivable) phytoplasmas and (cultivable) spiroplasmas, that cause economically important plant diseases. The project will discover gene markers of previously unknown phytoplasmas; new strains will be incorporated into our classification scheme, forming new phylogenetic groups, and we will describe/name the new taxa. Small genomes, and evolutionary loss of metabolic functions, make mollicutes ideal models for comparative genomics. Comparative genomics will elucidate genotypic events in the evolution of phytoplasmas and spiroplasmas, and will help establish molecular markers at differing levels of taxonomic rank. Spiroplasma genus-universal and species-specific gene markers will be identified to facilitate spiroplasma identification, and established Spiroplasma species will serve as models to distinguish putative species and genera of phytoplasmas. Investigation of physiological and metabolic signals, and gene pathways regulating the oxidative (redox) and hormonal status, will open new avenues for early phytoplasma disease diagnosis - possibly before symptoms appear - and for control of redox sensitive plant pathogenic mollicutes. We will devise a scheme of combined rRNA-ribosomal protein-secY gene sequences to classify closely related phytoplasma strains, and will expand our online program for computer-assisted phytoplasma classification to accommodate automated analysis of diverse functional classes of genes. The new knowledge gained and technologies and tools devised will advance fundamental science, strengthen applied research, enhance disease management, and improve implementation of quarantine regulations worldwide.