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Phylogenetic Triage and Risk Assessment: How to Predict Emerging Phytoplasma Diseases
SIMPLE SUMMARY: Phytoplasma diseases are a major threat to economically important crops and are usually only managed after the disease has occurred. In this study, the presence of two phytoplasmas in the aster yellows group were detected in insect samples collected from different agricultural settin...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10215655/ https://www.ncbi.nlm.nih.gov/pubmed/37237544 http://dx.doi.org/10.3390/biology12050732 |
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author | Janik, Katrin Panassiti, Bernd Kerschbamer, Christine Burmeister, Johannes Trivellone, Valeria |
author_facet | Janik, Katrin Panassiti, Bernd Kerschbamer, Christine Burmeister, Johannes Trivellone, Valeria |
author_sort | Janik, Katrin |
collection | PubMed |
description | SIMPLE SUMMARY: Phytoplasma diseases are a major threat to economically important crops and are usually only managed after the disease has occurred. In this study, the presence of two phytoplasmas in the aster yellows group were detected in insect samples collected from different agricultural settings in South Germany during a biodiversity survey. We used these findings to apply a proactive document-assess-monitor-act (DAMA) protocol to assess the potential for phytoplasma disease outbreaks in croplands in Bavaria, Germany. Notably, we carried out a phylogenetic triage and assessment to generate a risk heat map to select a minimum of seven leafhopper species that may serve as insect vectors of aster yellow phytoplasmas. To detect the presence of aster yellow phytoplasma in susceptible crops (e.g., wheat and barley) in Bavaria, we suggest specific monitoring activities and screening of these insect species as a proactive measure. This is the first time the DAMA protocol is applied in the field of phytopathology. ABSTRACT: Phytoplasma diseases pose a substantial threat to diverse crops of agricultural importance. Management measures are usually implemented only after the disease has already occurred. Early detection of such phytopathogens, prior to disease outbreak, has rarely been attempted, but would be highly beneficial for phytosanitary risk assessment, disease prevention and mitigation. In this study, we present the implementation of a recently proposed proactive disease management protocol (DAMA: Document, Assess, Monitor, Act) for a group of vector-borne phytopathogens. We used insect samples collected during a recent biomonitoring program in southern Germany to screen for the presence of phytoplasmas. Insects were collected with malaise traps in different agricultural settings. DNA was extracted from these mass trap samples and subjected to PCR-based phytoplasma detection and mitochondrial cytochrome c oxidase subunit I (COI) metabarcoding. Phytoplasma DNA was detected in two out of the 152 insect samples analyzed. Phytoplasma identification was performed using iPhyClassifier based on 16S rRNA gene sequence and the detected phytoplasmas were assigned to ‘Candidatus Phytoplasma asteris’-related strains. Insect species in the sample were identified by DNA metabarcoding. By using established databases, checklists, and archives, we documented historical associations and records of phytoplasmas and its hosts in the study region. For the assessment in the DAMA protocol, phylogenetic triage was performed in order to determine the risk for tri-trophic interactions (plant–insect–phytoplasma) and associated disease outbreaks in the study region. A phylogenetic heat map constitutes the basis for risk assessment and was used here to identify a minimum number of seven leafhopper species suggested to be monitored by stakeholders in this region. A proactive stance in monitoring changing patterns of association between hosts and pathogens can be a cornerstone in capabilities to prevent future phytoplasma disease outbreaks. To the best of our knowledge, this is the first time that the DAMA protocol has been applied in the field of phytopathology and vector-borne plant diseases. |
format | Online Article Text |
id | pubmed-10215655 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-102156552023-05-27 Phylogenetic Triage and Risk Assessment: How to Predict Emerging Phytoplasma Diseases Janik, Katrin Panassiti, Bernd Kerschbamer, Christine Burmeister, Johannes Trivellone, Valeria Biology (Basel) Article SIMPLE SUMMARY: Phytoplasma diseases are a major threat to economically important crops and are usually only managed after the disease has occurred. In this study, the presence of two phytoplasmas in the aster yellows group were detected in insect samples collected from different agricultural settings in South Germany during a biodiversity survey. We used these findings to apply a proactive document-assess-monitor-act (DAMA) protocol to assess the potential for phytoplasma disease outbreaks in croplands in Bavaria, Germany. Notably, we carried out a phylogenetic triage and assessment to generate a risk heat map to select a minimum of seven leafhopper species that may serve as insect vectors of aster yellow phytoplasmas. To detect the presence of aster yellow phytoplasma in susceptible crops (e.g., wheat and barley) in Bavaria, we suggest specific monitoring activities and screening of these insect species as a proactive measure. This is the first time the DAMA protocol is applied in the field of phytopathology. ABSTRACT: Phytoplasma diseases pose a substantial threat to diverse crops of agricultural importance. Management measures are usually implemented only after the disease has already occurred. Early detection of such phytopathogens, prior to disease outbreak, has rarely been attempted, but would be highly beneficial for phytosanitary risk assessment, disease prevention and mitigation. In this study, we present the implementation of a recently proposed proactive disease management protocol (DAMA: Document, Assess, Monitor, Act) for a group of vector-borne phytopathogens. We used insect samples collected during a recent biomonitoring program in southern Germany to screen for the presence of phytoplasmas. Insects were collected with malaise traps in different agricultural settings. DNA was extracted from these mass trap samples and subjected to PCR-based phytoplasma detection and mitochondrial cytochrome c oxidase subunit I (COI) metabarcoding. Phytoplasma DNA was detected in two out of the 152 insect samples analyzed. Phytoplasma identification was performed using iPhyClassifier based on 16S rRNA gene sequence and the detected phytoplasmas were assigned to ‘Candidatus Phytoplasma asteris’-related strains. Insect species in the sample were identified by DNA metabarcoding. By using established databases, checklists, and archives, we documented historical associations and records of phytoplasmas and its hosts in the study region. For the assessment in the DAMA protocol, phylogenetic triage was performed in order to determine the risk for tri-trophic interactions (plant–insect–phytoplasma) and associated disease outbreaks in the study region. A phylogenetic heat map constitutes the basis for risk assessment and was used here to identify a minimum number of seven leafhopper species suggested to be monitored by stakeholders in this region. A proactive stance in monitoring changing patterns of association between hosts and pathogens can be a cornerstone in capabilities to prevent future phytoplasma disease outbreaks. To the best of our knowledge, this is the first time that the DAMA protocol has been applied in the field of phytopathology and vector-borne plant diseases. MDPI 2023-05-17 /pmc/articles/PMC10215655/ /pubmed/37237544 http://dx.doi.org/10.3390/biology12050732 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Janik, Katrin Panassiti, Bernd Kerschbamer, Christine Burmeister, Johannes Trivellone, Valeria Phylogenetic Triage and Risk Assessment: How to Predict Emerging Phytoplasma Diseases |
title | Phylogenetic Triage and Risk Assessment: How to Predict Emerging Phytoplasma Diseases |
title_full | Phylogenetic Triage and Risk Assessment: How to Predict Emerging Phytoplasma Diseases |
title_fullStr | Phylogenetic Triage and Risk Assessment: How to Predict Emerging Phytoplasma Diseases |
title_full_unstemmed | Phylogenetic Triage and Risk Assessment: How to Predict Emerging Phytoplasma Diseases |
title_short | Phylogenetic Triage and Risk Assessment: How to Predict Emerging Phytoplasma Diseases |
title_sort | phylogenetic triage and risk assessment: how to predict emerging phytoplasma diseases |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10215655/ https://www.ncbi.nlm.nih.gov/pubmed/37237544 http://dx.doi.org/10.3390/biology12050732 |
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