Chinese chestnut yellow crinkle disease influence microbiota composition of chestnut trees

Fei Ren; Wei Dong; Shengqing Shi; Guiming Dou; Dong-Hui Yan

doi:10.1016/j.micpath.2020.104606

Chinese chestnut yellow crinkle disease influence microbiota composition of chestnut trees

Microb Pathog. 2021 Mar:152:104606. doi: 10.1016/j.micpath.2020.104606. Epub 2020 Nov 7.

Authors

Fei Ren¹, Wei Dong², Shengqing Shi³, Guiming Dou⁴, Dong-Hui Yan⁵

Affiliations

¹ Institute of Cereal & Oil Science and Technology, Academy of National Food and Strategic Reserves Administration, Beijing, 100037, China; Research Institute of Forest Ecology, Environment and Protection, Chinese Academy of Forestry, The Key Laboratory of Forest Protection Affiliated to State Forestry and Grassland Administration of China, Beijing, 100091, China. Electronic address: feifei3080@163.com.
² China Electric Power Research Institute, Beijing, 100192, China. Electronic address: dongwei3@epri.sgcc.com.cn.
³ Research Institute of Forestry, Chinese Academy of Forestry, Beijing, 100091, China. Electronic address: shi.shengqing@caf.ac.cn.
⁴ Research Institute of Forest Ecology, Environment and Protection, Chinese Academy of Forestry, The Key Laboratory of Forest Protection Affiliated to State Forestry and Grassland Administration of China, Beijing, 100091, China. Electronic address: dougm@caf.ac.cn.
⁵ Research Institute of Forest Ecology, Environment and Protection, Chinese Academy of Forestry, The Key Laboratory of Forest Protection Affiliated to State Forestry and Grassland Administration of China, Beijing, 100091, China. Electronic address: yandh@caf.ac.cn.

PMID: 33171258
DOI: 10.1016/j.micpath.2020.104606

Abstract

Context: Candidatus-phytoplasma castaneae has been found as the causal agent of the Chinese chestnut yellow crinkle disease. However, the ecological impact of the disease on microbiota of chestnut trees is unknown.

Aims: The study aim was to clarify difference attributes in microbial community structure of asymptomatic and symptomatic chestnut leaves and twigs for chestnut tree health in orchard.

Methods: Sample collections were conducted with both symptomatic and asymptomatic chestnut trees. Total DNA was extracted. Fungal ITS rDNA and bacterial 16S rDNA were amplified. The PCR products were sequenced with Illumina HiSeq. Platform.

Results: A total number of 852 fungal and 1156 bacterial OTUs (operational taxonomic units) were detected. The asymptomatic samples had a higher fungal and bacterial diversity than symptomatic ones. Non-metric multidimensional scaling (NMDS) analysis showed microbial communities among symptomatic and asymptomatic leaves and twigs samples formed individual cluster. Overall, Ascomycota and Proteobacteria were the most abundant fungal and bacterial phyla, respectively. Significantly different taxa playing key roles for each microbiota structure were identified. In symptomatic trees, microbial groups of plant pathogens were more abundant.

Conclusion: Our results demonstrated that the phytoplasma pathogen may exert significant influence on the microbial community structure. The study will provide further fundamental clues for the little studied phytoplasma pathogens effects on host microbiota, phytoplasma pathogen control strategies.

Keywords: Castanea mollissima; Disease; Microbiota; Phytoplasma.

MeSH terms

Ascomycota* / genetics
Bacteria / genetics
China
Microbiota*
Trees