Genetic and Nutritional Dynamics of SynCom in Suppressing Apple Fire Blight
Fire blight disease, caused by Erwinia amylovora, occurs in apples and other Rosaceae plants and is known to cause significant economic damage. The pathogen usually infects flowers during the reproductive growth period of plants, colonizes, and penetrates by producing exopolysaccharides in the stigm...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Hanrimwon Publishing Company
2025-06-01
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| Series: | The Plant Pathology Journal |
| Subjects: | |
| Online Access: | http://ppjonline.org/upload/pdf/PPJ-OA-03-2025-0040.pdf |
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| Summary: | Fire blight disease, caused by Erwinia amylovora, occurs in apples and other Rosaceae plants and is known to cause significant economic damage. The pathogen usually infects flowers during the reproductive growth period of plants, colonizes, and penetrates by producing exopolysaccharides in the stigma. A synthetic microbial community (SynCom) is an artificial community of microorganisms designed to enhance host viability. To construct SynCom, we attempted to identify and utilize the microbial characteristics of apple trees that are not infected with the pathogen compared to those that are infected. In our previous study, we composed SynCom with strains expected to reduce the density of fire blight pathogens through microbiome analysis, strain isolation, and continuous replacement culture. We are able to observe the disease control effect of the constructed SynCom. However, no study has been conducted to clearly determine the genetic mechanism underlying this effect of the SynCom. Here, we present that potential secondary metabolite candidates and nutritional competition with the pathogen were confirmed as biochemical mechanisms through whole genome analysis of SynCom strains. Additionally, by co-cultivating SynCom with the pathogen in limited nutrient conditions, such as apple blossom extracts, which are susceptible to the pathogen, we confirmed the potential of SynCom treatment to reduce the pathogen densities. This study demonstrates that genetic selection using metagenomics can effectively identify microorganisms with potential functional capabilities. |
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| ISSN: | 1598-2254 2093-9280 |