Stalder, Luzia

2024, Stalder, Luzia, Croll, Daniel

Plants host diverse yet taxonomically structured communities of microorganisms. These microorganisms colonize every accessible plant tissue, influencing both plant growth and health. There is substantial interest to exploit beneficial members of plant microbiomes for new sustainable management strategies in crop production. However, our understanding of these interactions in field conditions, particularly at the species and strain level, is still limited. Moreover, microbial pathogens can rapidly adapt to changing environments such as the application of pesticides or host resistance. This thesis offers a comprehensive perspective on the genetic mechanisms of pathogen adaptation and the dynamics of microbial communities in crop plants, providing a high-resolution view of strain-specific microbial interactions that shape plant health. Mapping microbial genomic variation at the strain level in environmental samples has posed a significant challenge in the field. This thesis addresses this challenge through two interconnected and complementary approaches. The first approach involves wholegenome sequencing and comprehensive structural variant analysis of a large fungal pathogen population to detect genomic signatures indicative of recent adaptation. We examined how Rhynchosporium commune, a major fungal pathogen of barley, has adapted to the host environment and fungicide applications. We screened the genomes of 125 isolates from diverse global populations and identified 7879 gene duplications and 116 gene deletions, primarily resulting from segmental chromosomal duplications. While Copy Number Variations (CNVs) are usually under negative selection, we observed that genes impacted by CNVs are overrepresented in functions related to host exploitation, such as effectors and cell wall-degrading enzymes. We conducted genome-wide association studies (GWAS) and identified a large segmental duplication of the Cytochrome P450 Family 51 gene (CYP51A) that contributed to the emergence of azole resistance and a duplication encompassing an effector gene affecting virulence. We demonstrated that the adaptive CNVs were likely created by recently active transposable element families. Furthermore, we found that specific transposable element families are significant drivers of recent gene copy-number variation. Collectively, these findings demonstrate how extensive segmental duplications provide the raw material for recent adaptation in global populations of a fungal pathogen. The second method leverages whole-genome sequences to construct pangenomes, facilitating the creation of taxon-specific amplicons. These amplicons allow us to monitor strain diversity in the field and to build co-occurrence networks that reveal synergistic and antagonistic interactions between strains. Specifically, we developed and validated a pipeline for designing, multiplexing, and sequencing highly polymorphic taxon-specific long-read amplicons. We focused on the wheat microbiome as a proof-ofprinciple and achieved unprecedented resolution for the wheat-associated Pseudomonas microbiome and the ubiquitous fungal pathogen Zymoseptoria tritici. We achieved more than a three-fold increase in phylogenetic resolution compared to existing ribosomal amplicons. The designed amplicons accurately capture species and strain diversity, ii outperforming full-length 16S and Internally Transcribed Spacer (ITS) amplicons. To broaden the utility of our approach, we generated pangenome-informed amplicon templates for additional key bacterial and fungal genera. Pangenome-informed microbiome profiling allows tracking of microbial community dynamics in complex environments and overcomes limitations in phylogenetic resolution. We then used this approach to track microbial communities in the wheat phyllosphere across time and space, detecting fine-grained species and strain-specific dynamics. Our findings reveal a high level of strain-specificity in Pseudomonas interactions, both within and between kingdoms. Through systematic analysis of negative interactions, we discovered a consortium of ten taxa that potentially suppress seven fungal pathogens. We confirmed the strain-specific interactions of Pseudomonas with different strains of the major fungal pathogen Z. tritici using co-inoculation experiments involving Pseudomonas strains and Z. tritici isolates from the same field. Consistent with our prediction, we identified a Pseudomonas poae isolate as the most antagonistic towards Z. tritici. Overall, we demonstrate the potential of taxon-specific high-resolution network inference in studying microbial interaction networks. We highlight how understanding species and strain-specific dynamics can inform the development of effective biocontrol strategies.