Insights into establishment and maintenance of lichen communities through structural bioinformatics and synthetic microbial consortia

Lichens are remarkable examples of complex microbial cross-kingdom communities, thriving in some of the harshest environments on Earth. These symbioses, comprising fungi (mycobionts) and photosynthetic partners like algae or cyanobacteria (photobionts) but also additional bacterial members, have been traditionally difficult to study due to their complexity. A detailed molecular understanding of interactions between the community members is still missing.

The main focus of our research is therefore to elucidate the mechanisms that control the formation, stabilization, and maintenance of lichens. From other fungal interactions, it is already known that secreted proteins play a vital role in recognition, facilitation of cell-cell contact, regulation of growth, and production of metabolites. Known as effector proteins, these molecules have key roles in both symbiotic but also pathogenic interactions.

For this reason, we are focusing on the identification and classification of secreted proteins through bioinformatic mining of sequenced genomes of Peltigera lichens. By leveraging structural prediction and clustering algorithms, our bioinformatic pipeline is able to identify effector proteins that traditional sequence-based methods often miss. This approach already allowed us to identify structurally conserved proteins also found in pathogenic fungi but revealed a large number of currently uncharacterized protein families. However, a detailed functional understanding of these proteins is currently lacking.

As lichens are not efficiently amenable to genetic manipulation, we will use synthetic communities composed of well-characterized model microbes. These communities comprise Synechocystis, Saccharomyces cerevisiae, and the dimorphic fungus Ustilago maydis, and allow us to investigate the effects of candidate effector proteins. As the members in a lichen community are spatially closely associated, we plan to incorporate surface-presented proteins that allow us to connect the individual organisms in a controllable manner. To this end, we develop a U. maydis-based surface display system, making use of the carbohydrate-binding properties of lectins – a class of secreted proteins that have been shown to facilitate cell-to-cell contacts and are also present in lichens.

By unraveling the molecular secrets of lichen effector proteins, we hope to shed light on the fundamental principles of microbial cooperation using these ancient symbionts as exemplars.