Janik, K.; Panassiti, B.; Kerschbamer, C.; Burmeister, J.; Trivellone, V. Phylogenetic Triage and Risk Assessment: How to Predict Emerging Phytoplasma Diseases. Biology2023, 12, 732.
Janik, K.; Panassiti, B.; Kerschbamer, C.; Burmeister, J.; Trivellone, V. Phylogenetic Triage and Risk Assessment: How to Predict Emerging Phytoplasma Diseases. Biology 2023, 12, 732.
Janik, K.; Panassiti, B.; Kerschbamer, C.; Burmeister, J.; Trivellone, V. Phylogenetic Triage and Risk Assessment: How to Predict Emerging Phytoplasma Diseases. Biology2023, 12, 732.
Janik, K.; Panassiti, B.; Kerschbamer, C.; Burmeister, J.; Trivellone, V. Phylogenetic Triage and Risk Assessment: How to Predict Emerging Phytoplasma Diseases. Biology 2023, 12, 732.
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 COI sequence metabarcoding. In about 1% of the analyzed samples, phytoplasma DNA was detected. Phytoplasma group identification was performed by 16S rRNA gene sequence analysis and the detected phytoplasmas could be assigned to the 16SrI subgroups B and L. 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 our knowledge, this is the first time that the DAMA protocol has been applied in the field of phytopathology and vector-borne plant diseases.
Biology and Life Sciences, Agricultural Science and Agronomy
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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