Literature DB >> 33643365

Quantitative High-Throughput, Real-Time Bioassay for Plant Pathogen Growth in vivo.

Chunqiu Zhang1,2, Ben N Mansfeld2, Ying-Chen Lin2, Rebecca Grumet2.   

Abstract

Effective assessment of pathogen growth can facilitate screening for disease resistance, mapping of resistance loci, testing efficacy of control measures, or elucidation of fundamental host-pathogen interactions. Current methods are often limited by subjective assessments, inability to detect pathogen growth prior to appearance of symptoms, destructive sampling, or limited capacity for replication and quantitative analysis. In this work we sought to develop a real-time, in vivo, high-throughput assay that would allow for quantification of pathogen growth. To establish such a system, we worked with the broad host-range, highly destructive, soil-borne oomycete pathogen, Phytophthora capsici. We used an isolate expressing red fluorescence protein (RFP) to establish a microtiter plate, real-time assay to quantify pathogen growth in live tissue. The system was successfully used to monitor P. capsici growth in planta on cucumber (Cucumis sativus) fruit and pepper (Capsicum annuum) leaf samples in relation to different levels of host susceptibility. These results demonstrate usefulness of the method in different species and tissue types, allowing for highly replicated, quantitative time-course measurements of pathogen growth in vivo. Analyses of pathogen growth during initial stages of infection preceding symptom development show the importance of very early stages of infection in determining disease outcome, and provide insight into points of inhibition of pathogen growth in different resistance systems.
Copyright © 2021 Zhang, Mansfeld, Lin and Grumet.

Entities:  

Keywords:  Phytophthora capsici; cucumber; early pathogen growth; pepper; quantitative bioassay

Year:  2021        PMID: 33643365      PMCID: PMC7902728          DOI: 10.3389/fpls.2021.637190

Source DB:  PubMed          Journal:  Front Plant Sci        ISSN: 1664-462X            Impact factor:   5.753


  20 in total

Review 1.  The oomycete broad-host-range pathogen Phytophthora capsici.

Authors:  Kurt H Lamour; Remco Stam; Julietta Jupe; Edgar Huitema
Journal:  Mol Plant Pathol       Date:  2011-10-20       Impact factor: 5.663

2.  Image-Based Quantification of Plant Immunity and Disease.

Authors:  Bradley Laflamme; Maggie Middleton; Timothy Lo; Darrell Desveaux; David S Guttman
Journal:  Mol Plant Microbe Interact       Date:  2016-12-20       Impact factor: 4.171

Review 3.  Quantitative and qualitative phenotyping of disease resistance of crops by hyperspectral sensors: seamless interlocking of phytopathology, sensors, and machine learning is needed!

Authors:  Anne-Katrin Mahlein; Matheus Thomas Kuska; Stefan Thomas; Mirwaes Wahabzada; Jan Behmann; Uwe Rascher; Kristian Kersting
Journal:  Curr Opin Plant Biol       Date:  2019-08-03       Impact factor: 7.834

4.  Changes in Winter Squash Fruit Exocarp Structure Associated with Age-Related Resistance to Phytophthora capsici.

Authors:  Safa A Alzohairy; Raymond Hammerschmidt; Mary K Hausbeck
Journal:  Phytopathology       Date:  2019-12-30       Impact factor: 4.025

5.  Advances in Research on Phytophthora capsici on Vegetable Crops in The United States.

Authors:  Leah L Granke; Lina Quesada-Ocampo; Kurt Lamour; Mary K Hausbeck
Journal:  Plant Dis       Date:  2012-11       Impact factor: 4.438

6.  Sensitive detection of gene expression in mycobacteria under replicating and non-replicating conditions using optimized far-red reporters.

Authors:  Paul Carroll; Lise J Schreuder; Julian Muwanguzi-Karugaba; Siouxsie Wiles; Brian D Robertson; Jorge Ripoll; Theresa H Ward; Gregory J Bancroft; Ulrich E Schaible; Tanya Parish
Journal:  PLoS One       Date:  2010-03-23       Impact factor: 3.240

7.  Image-based phenotyping of plant disease symptoms.

Authors:  Andrew M Mutka; Rebecca S Bart
Journal:  Front Plant Sci       Date:  2015-01-05       Impact factor: 5.753

8.  Transcriptomic and metabolomic analyses of cucumber fruit peels reveal a developmental increase in terpenoid glycosides associated with age-related resistance to Phytophthora capsici.

Authors:  Ben N Mansfeld; Marivi Colle; Yunyan Kang; A Daniel Jones; Rebecca Grumet
Journal:  Hortic Res       Date:  2017-05-24       Impact factor: 6.793

Review 9.  The use of Gompertz models in growth analyses, and new Gompertz-model approach: An addition to the Unified-Richards family.

Authors:  Kathleen M C Tjørve; Even Tjørve
Journal:  PLoS One       Date:  2017-06-05       Impact factor: 3.240

Review 10.  Challenges and Strategies for Breeding Resistance in Capsicum annuum to the Multifarious Pathogen, Phytophthora capsici.

Authors:  Derek W Barchenger; Kurt H Lamour; Paul W Bosland
Journal:  Front Plant Sci       Date:  2018-05-15       Impact factor: 5.753

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