Phylogenetic Triage and Risk Assessment: How to Predict Emerging Phytoplasma Diseases
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 benef...
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-05-01
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| Series: | Biology |
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| Online Access: | https://www.mdpi.com/2079-7737/12/5/732 |
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| author | Katrin Janik Bernd Panassiti Christine Kerschbamer Johannes Burmeister Valeria Trivellone |
| author_facet | Katrin Janik Bernd Panassiti Christine Kerschbamer Johannes Burmeister Valeria Trivellone |
| author_sort | Katrin Janik |
| collection | DOAJ |
| description | 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 ‘<i>Candidatus</i> 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. |
| first_indexed | 2024-03-11T03:56:14Z |
| format | Article |
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| issn | 2079-7737 |
| language | English |
| last_indexed | 2024-03-11T03:56:14Z |
| publishDate | 2023-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Biology |
| spelling | doaj.art-f4a9bc7412304cdf96a285fc538562522023-11-18T00:33:38ZengMDPI AGBiology2079-77372023-05-0112573210.3390/biology12050732Phylogenetic Triage and Risk Assessment: How to Predict Emerging Phytoplasma DiseasesKatrin Janik0Bernd Panassiti1Christine Kerschbamer2Johannes Burmeister3Valeria Trivellone4Laimburg Research Centre, Functional Genomics, Laimburg 6-Pfatten (Vadena), 39040 Auer, South Tyrol, ItalyIndependent Researcher, D-81543 Munich, GermanyLaimburg Research Centre, Functional Genomics, Laimburg 6-Pfatten (Vadena), 39040 Auer, South Tyrol, ItalyInstitute for Organic Farming, Soil and Resource Management, Bavarian State Research Center for Agriculture, 85354 Freising, GermanyIllinois Natural History Survey, Prairie Research Institute, University of Illinois at Urbana-Champaign, Champaign, IL 61820, USAPhytoplasma 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 ‘<i>Candidatus</i> 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.https://www.mdpi.com/2079-7737/12/5/732archivesbio-inventoriesaster yellowBavariaDAMA protocolgeographic distribution |
| spellingShingle | Katrin Janik Bernd Panassiti Christine Kerschbamer Johannes Burmeister Valeria Trivellone Phylogenetic Triage and Risk Assessment: How to Predict Emerging Phytoplasma Diseases Biology archives bio-inventories aster yellow Bavaria DAMA protocol geographic distribution |
| 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 | archives bio-inventories aster yellow Bavaria DAMA protocol geographic distribution |
| url | https://www.mdpi.com/2079-7737/12/5/732 |
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