Research Group Molecular Diagnostics Genomics and Bioinformatics, Department of Method Development and Analytics, Agroscope, Wädenswil, Switzerland.
Department of Plants and Plant Products, Agroscope Phytosanitary Service, Agroscope, Wädenswil, Switzerland.
PLoS One. 2022 Jul 25;17(7):e0270897. doi: 10.1371/journal.pone.0270897. eCollection 2022.
The unintentional movement of agronomic pests and pathogens is steadily increasing due to the intensification of global trade. Being able to identify accurately and rapidly early stages of an invasion is critical for developing successful eradication or management strategies. For most invasive organisms, molecular diagnostics is today the method of choice for species identification. However, the currently implemented tools are often developed for certain taxa and need to be adapted for new species, making them ill-suited to cope with the current constant increase in new invasive species. To alleviate this impediment, we developed a fast and accurate sequencing tool allowing to modularly obtain genetic information at different taxonomical levels. Using whole genome amplification (WGA) followed by Oxford nanopore MinION sequencing, our workflow does not require any a priori knowledge on the investigated species and its classification. While mainly focusing on harmful plant pathogenic insects, we also demonstrate the suitability of our workflow for the molecular identification of bacteria (Erwinia amylovora and Escherichia coli), fungi (Cladosporium herbarum, Colletotrichum salicis, Neofabraea alba) and nematodes (Globodera rostochiensis). On average, the pairwise identity between the generated consensus sequences and best GenBank BLAST matches was 99.6 ± 0.6%. Additionally, assessing the generated insect genomic dataset, the potential power of the workflow to detect pesticide resistance genes, as well as arthropod-infecting viruses and endosymbiotic bacteria is demonstrated.
由于全球贸易的加剧,农业害虫和病原体的无意识传播正在稳步增加。能够准确、快速地识别入侵的早期阶段对于制定成功的根除或管理策略至关重要。对于大多数入侵生物,分子诊断如今是物种鉴定的首选方法。然而,目前实施的工具通常是针对某些分类群开发的,需要针对新物种进行调整,因此不适合应对当前新入侵物种不断增加的情况。为了缓解这一障碍,我们开发了一种快速准确的测序工具,允许在不同的分类学水平上模块化地获取遗传信息。我们的工作流程使用全基因组扩增 (WGA) followed by Oxford nanopore MinION 测序,不需要对所研究的物种及其分类有任何先验知识。虽然主要关注有害的植物病原昆虫,但我们还证明了我们的工作流程适用于细菌(Erwinia amylovora 和 Escherichia coli)、真菌(Cladosporium herbarum、Colletotrichum salicis、Neofabraea alba)和线虫(Globodera rostochiensis)的分子鉴定。平均而言,生成的共识序列与最佳 GenBank BLAST 匹配之间的成对同一性为 99.6 ± 0.6%。此外,评估生成的昆虫基因组数据集,展示了该工作流程检测农药抗性基因以及感染节肢动物的病毒和内共生细菌的潜力。