Next-Generation-Sequencing Genomic and Metagenomic Analysis of Phytopathogenic Prokaryotes

Phytopatology, as a discipline that deals with the complexity of living communities, needs methods to screen what could be considered ‘useful’ data from ‘background noise’. Until the Nineties, this was achieved by simplifications that were deemed adequate enough: from Koch’s postulates that require microorganisms to be culturable, to DNA barcoding that assumed genetic markers to be universal and precise enough to distinguish minute differences, to the disease triangle model that mostly downplayed the role of the micro-community context the pathogens find themselves in. With the introduction of whole genome sequencing (WGS) tecnologies in the last thirty years, we started to realise that those simplifications, while not wrong, constituted sufficient but not necessary conditions: some pathogens (e.g. phytoplasmas) are remarkably difficult to cultivate in vitro, DNA structural variations can produce diverse strains without changing markers, and the micro-community can significantly impact on a pathogen’s ability to spread. This work shows, from different perspectives all tied by the use of WGS data and analysis, how a deeper understanding of these complex dynamics can prompt new practical concepts to manage economically impactful plant diseases: The characterisation of Pseudomonas sp. strain Pf4 shows how the most fit strains, both from pathogens and biocontrol agents, derive their qualities from sizable sets of ‘secondary’ – but in fact crucial, as we are now aware – metabolites (SM) gene clusters; The comparison of the biocontrol activity of Pf4 and Pf11 shows that while a wide set of SM clusters is important, the inclusion of such set doesn’t necessarily translate into a ‘stronger’ control activity, but points to a better adaptability to changing environmental conditions; The use of third-generation WGS, which produces longer (~10,000 nts) reads, was essential to characterise the CRAFRU 12.29 and 14.08 strains – one producing hypersentive response (HR) on leaves, the other not –, as their difference lies in a transposon-mediated structural variation that would not have been possible to identify with older sequencing methods; Developing the Phytoassembly pipeline contributed to a novel method of obtaining phytoplasma (and other non-culturable organism) genome, which circumvent the laborious in vitro protocols employed so far to obtain similar results; The Phytoassembly pipeline showed its potentiality by not only isolating a Chicory Phyllody (ChP) phytoplasma, but allowing to detect the presence of a companion spiroplasma, later shown to frequently occur together in mixed infections of chicory; Phytoassembly also helped characterising a Cassava Frogskin Disease (CFSD) phytoplasma, which showed some differences from other representative in the group; The spatialisation of the genomic samples from the kiwifruit endophyte populations allows to correlate their spatial and temporal variation to the severity of the symptoms displayed by the plants and the time of Pseudomonas syringae pt. actinidiae (Psa) infection. On the whole, the research projects presented in this work give insights into the greater complexity of microbial genome structure and variation, the dynamics between pathogens and the wider microbial community, the necessity for research methodologies based on more complex data, and the essential role that WGS technologies plays and will play in plant protection research and development.