Nobori, Tatsuya 
ORCID: 0000-0002-1773-3361
(2019).
In planta multi-omic profiling of pathogenic and commensal bacteria.
PhD thesis, Universität zu Köln.
Abstract
Plant pathogens can cause serious diseases that impact global agriculture. Molecular mechanisms of the plant immune system have been intensively studied in the past decades, revealing mechanisms for pathogen recognition and immune signaling in plant cells. However, we still lack a fundamental knowledge of how plant immunity affects pathogen metabolisms to inhibit their growth in plants. In the case of bacterial pathogens, a major bottleneck is the difficulty in profiling bacterial responses in planta. Here, I established a method to isolate bacterial cells from Arabidopsis thaliana leaves to enrich bacterial information. I profiled the transcriptomes and proteomes of the foliar bacterial pathogen Pseudomonas syringae by using various combinations of host and bacterial genotypes and pretreatments. This unveiled that bacterial transcriptome changes affected by plant immunity explain bacterial growth suppression in the plant apoplast and identified that a bacterial iron acquisition pathway is a major plant immune target. Bacterial transcriptomes and proteomes were well correlated in general, but I also found that plant immunity affects the abundance of specific components of the bacterial type III secretion system, an essential component for bacterial virulence, only at the protein level. Together, these analyses provided insights into the long-standing question of how biological processes of bacterial pathogens are influenced by plant immunity. I also applied the in planta bacterial transcriptomics method to address an important open question in plant microbiota research: how does plant immunity influence the responses of microbiota members to affect the shape and functions of the plant microbiota? I profiled the co-transcriptomes of plants and bacteria in the monoassociation condition and revealed conserved and specific plant and bacterial responses during interaction events. This approach will help us understand how plants winnow different microbiota members and control the microbiota function, and transform the current plant microbiota research from descriptive studies to mechanistic studies. Taken together, this study sets the foundation for the comprehensive understanding of molecular events on both plant and bacterial sides during their interactions.
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