New Nanopore sequencing-based methodology for the detection and identification of microbial communities and plant pathogens

Microbial biodiversity remains largely unexplored, with most species yet to be discovered and described. Expanding our knowledge of microbial biodiversity through efficient identification methods could lead to improvements in several fields, including disease diagnostics and environmental monitoring. This is particularly relevant in plant pathology, where climate change and globalization are increasing the spread of plant pathogens, highlighting the need for rapid, sensitive, and specific diagnostic methods. In this context, the main objective of this thesis was to develop rapid, cost-effective, and accurate molecular methods for both the detection and identification of specific microorganisms and the broader taxonomic characterization of microbial communities. The aim was to create adaptable solutions for both small-scale and large-scale applications with different purposes, particularly to enable timely responses in phytosanitary monitoring and support the implementation of appropriate measures to track and mitigate outbreaks of quarantine pathogens. Oxford Nanopore Technology (ONT) was selected for its ability to generate long reads, which enhances the detection of genetic differences between closely related organisms and allows for higher taxonomic resolution. ONT’s portable sequencers also enable field applications, offering cost-effective and rapid results. To address the limited availability of bioinformatics tools optimized for Nanopore data, a custom pipeline, MONICA®, was proposed for the analysis and taxonomic classification of long-read sequences. This pipeline was designed to be adaptable for diverse applications, including microbial community profiling and pathogen detection, and was benchmarked against well-established tools in metabarcoding studies, demonstrating strong performance in estimating the relative abundances of different microbial communities. The combination of multiplex-PCR amplification, Nanopore sequencing, and MONICA® was then applied to develop diagnostic systems for EU-quarantine plant pathogens, including Xylella fastidiosa, Xanthomonas citri pv. citri and pv. aurantifolii, and Pantoea stewartii subsp. stewartii. The goal was to create a rapid, specific, and sensitive diagnostic workflow for screening imported plant materials and enabling early detection, even at low pathogen concentrations. Finally, Nanopore whole-genome sequencing was employed to characterize Pantoea stewartii subsp. stewartii strains isolated in Italy, allowing insights into their potential origin. These genomic sequences were then used for the design of new specific primers to create a new real-time PCR assay addressing the demand for more specific and sensitive detection of this pathogen. This thesis proposes a flexible framework, applicable to different target organisms and user needs, contributing to the advancement of diagnostic methodologies and providing important insights into the optimization of molecular techniques for accurate microbial community analysis.