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Critical Reviews™ in Immunology
Facteur d'impact: 1.352 Facteur d'impact sur 5 ans: 3.347 SJR: 0.657 SNIP: 0.55 CiteScore™: 2.19

ISSN Imprimer: 1040-8401
ISSN En ligne: 2162-6472

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Critical Reviews™ in Immunology

DOI: 10.1615/CritRevImmunol.v30.i3.50
pages 277-289

Analysis of Early Host Responses for Asymptomatic Disease Detection and Management of Specialty Crops

Abhaya M. Dandekar
Plant Sciences, UC Davis, Davis, CA 95616, USA
Federico Martinelli
Department Plant Sciences, MS2, University of California
Cristina E. Davis
Mechanical and Aerospace Engineering Department
Abhinav Bhushan
Mechanical and Aerospace Engineering Department
Weixiang Zhao
Mechanical and Aerospace Engineering Department
Oliver Fiehn
Genome Center and Bioinformatics Program
Kirsten Skogerson
Genome Center and Bioinformatics Program
Gert Wohlgemuth
Genome Center and Bioinformatics Program
Raissa D'Souza
Mechanical and Aerospace Engineering Department; Genome Center and Bioinformatics Program
Soumen Roy
Center for Computational Science and Engineering
Russell L. Reagan
Department Plant Sciences, MS2, University of California, Davis
Dawei Lin
Genome Center and Bioinformatics Program
R. Bruce Cary
Mesa Tech International, Inc. Santa Fe, New Mexico, USA
Paige Pardington
Biosciences Division, Los Alamos National Laboratory, Los Alamos, New Mexico, USA
Goutam Gupta
Biosciences Division, Los Alamos National Laboratory, Los Alamos, NM 87545, USA

RÉSUMÉ

The rapid and unabated spread of vector-borne diseases within US specialty crops threatens our agriculture, our economy, and the livelihood of growers and farm workers. Early detection of vector-borne pathogens is an essential step for the accurate surveillance and management of vector-borne diseases of specialty crops. Currently, we lack the tools that would detect the infectious agent at early (primary) stages of infection with a high degree of sensitivity and specificity. In this paper, we outline a strategy for developing an integrated suite of platform technologies to enable rapid, early disease detection and diagnosis of huanglongbing (HLB), the most destructive citrus disease. The research has two anticipated outcomes: i) identification of very early, disease-specific biomarkers using a knowledge base of translational genomic information on host and pathogen responses associated with early (asymptomatic) disease development; and ii) development and deployment of novel sensors that capture these and other related biomarkers and aid in presymptomatic disease detection. By combining these two distinct approaches, it should be possible to identify and defend the crop by interdicting pathogen spread prior to the rapid expansion phase of the disease. We believe that similar strategies can also be developed for the surveillance and management of diseases affecting other economically important specialty crops.


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