Theologidis Ioannis, Karamitros Timokratis, Vichou Aikaterini-Eleni, Kizis Dimosthenis
Laboratory of Toxicological Control of Pesticides, Scientific Directorate of Pesticides' Control & Phytopharmacy, Benaki Phytopathological Institute, 8 St. Delta Street, 14561 Athens, Attica, Greece.
Bioinformatics and Applied Genomics Unit, Department of Microbiology, Hellenic Pasteur Institute, 127 Vasilissis Sofias Avenue, 11521 Athens, Attica, Greece.
J Fungi (Basel). 2023 Nov 18;9(11):1119. doi: 10.3390/jof9111119.
Metabarcoding approaches for the identification of plant disease pathogens and characterization of plant microbial populations constitute a rapidly evolving research field. Fungal plant diseases are of major phytopathological concern; thus, the development of metabarcoding approaches for the detection of phytopathogenic fungi is becoming increasingly imperative in the context of plant disease prognosis. We developed a multiplex metabarcoding method for the identification of fungal phytopathogens and endophytes in olive young shoots, using the MinION sequencing platform (Oxford Nanopore Technologies). Selected fungal-specific primers were used to amplify three different genomic DNA loci (ITS, beta-tubulin, and 28S LSU) originating from olive twigs. A multiplex metabarcoding approach was initially evaluated using healthy olive twigs, and further assessed with naturally infected olive twig samples. Bioinformatic analysis of basecalled reads was carried out using MinKNOW, BLAST+ and R programming, and results were also evaluated using the BugSeq cloud platform. Data analysis highlighted the approaches based on ITS and their combination with beta-tubulin as the most informative ones according to diversity estimations. Subsequent implementation of the method on symptomatic samples identified major olive pathogens and endophytes including genera such as , , , , and others.
用于鉴定植物病害病原体和表征植物微生物群落的宏条形码方法构成了一个快速发展的研究领域。真菌性植物病害是植物病理学的主要关注点；因此，在植物病害预后的背景下，开发用于检测植物病原真菌的宏条形码方法变得越来越迫切。我们使用MinION测序平台（牛津纳米孔技术公司）开发了一种多重宏条形码方法，用于鉴定橄榄嫩梢中的植物病原真菌和内生真菌。选用真菌特异性引物扩增来自橄榄嫩枝的三个不同基因组DNA位点（ITS、β-微管蛋白和28S LSU）。最初使用健康的橄榄嫩枝评估多重宏条形码方法，并进一步用自然感染的橄榄嫩枝样本进行评估。使用MinKNOW、BLAST+和R编程对碱基识别读数进行生物信息学分析，结果也使用BugSeq云平台进行评估。数据分析突出了基于ITS及其与β-微管蛋白组合的方法，根据多样性估计，这些方法信息最丰富。随后在有症状样本上实施该方法，鉴定出主要的橄榄病原体和内生真菌，包括 、 、 、 等属。
