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Our Research Groups

Project area A: Spatiotemporal dynamics of oak’s bacterial leaf microbiota

Photo: Fanhao Kong
Fanhao Kong
Project A1: Spatial and temporal monitoring of leaf and tree status, and environment

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The main goal for my project is to do hyperspectral characterisation of leaf traits, microbiome diversity/abundance, as well as to monitor the abiotic environmental gradients for local crown climate and leaf microclimate. For this purpose, I use the hyperspectral cameras, climate tower and leaf climate sensors to collect data, then integrate machine learning models to capture the relationships between leaf traits, microbiome and environmental gradients.

Photo: Annabell Wagner
Annabell Wagner
Project A2: Spatial and temporal monitoring of the leaf microbiome

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My contribution to this project will be the characterization of the epiphytic bacterial oak leaf microbiome on micro- and macroscopic spatial and temporal scales such as the identification of abiotic and biotic factors, which influence its structure. For this purpose, we use DNA Sequencing techniques to analyze bacterial communities and design experiments to test bacterial reactions to abiotic and biotic factors. The data will be combined within the projects to discover all-over patterns related to community composition.

Photo: Jakob Wenning
Fiona Ullmann
Project A3: Library of cultured representatives of the leaf microbiota

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My main contribution to the Tree-M project will be the cultivation and isolation of the bacteria found on the leaves of Quercus robur. The resulting library will enable the characterization of these bacteria and the investigation of the functional role they play in the microbial community of epiphytic bacteria living on the oak tree.

Project area B: Bacterial adaptation strategies to the oak phyllosphere

More information following soon.
Project B1: Biosynthesis of secondary metabolites by leaf microbiota

Photo: Changqing Liu
Dr. Changqing Liu
Project B2: Carbon metabolism of bacterial leaf microbiota

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I am responsible for project B2: Carbon metabolism of bacterial leaf microbiota. For this purpose, we will isolate methanol- and isoprene-degrading bacteria and investigate their related enzyme such as methanol dehydrogenases and isoprene monooxygenases. In addition, genome editing will be used to study how the bacteria regulate isoprene oxidation, which will help us to understand the relationship between leaf, microbe and isoprene emissions, and thus the impact of oak trees on the atomosphere and humans.

Information following soon.
Project B3: Nitrogen fixation by diazotrophic bacteria of the leaf microbiota

Photo: Sandra Schuller
Dr. Sandra Schuller
Project B4: Resource-dependent regulation of bacterial primary and secondary metabolism

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With oscillating light during the daily cycle also the nutrition availability in the phyllosphere changes. How do bacteria on oak leaves adapt their metabolism to this? To answer this question, we would like to unravel the detailed mechanism of the Kai proteins from Methylobacteria – homologues from the circadian clock proteins in photosynthetic bacteria. We employ cryoEM as a powerful tool to solve the structure of varying states of Kai-complexes to gain insight into their mechanism of action.

Project area C: Interactions between microbiota and the oak leaf habitat

Photo: Susanne Walden
Dr. Susanne Walden
Project C1: Intraspecific, intraindividual and temporal variation of leaf traits

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Within this project, I will investigate to what extent structural, biochemical, and physiological properties of oak leaves can be predicted by (micro-)environmental conditions within the canopy and how these leaf traits affect the diversity and functions of the phyllosphere microbiome.

Second position in C1 yet to be filled. 

Photo: Finja Strehmann
Dr. Anjaharinony Andry Ny Aina Rakotomalala
Project C2: Leaf characteristics, metabolome, and herbivory

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My research aims to assess how abiotic factors, phyllosphere microbiome, leaf traits and metabolomes influence herbivory in pedunculate oak trees in forest ecosystems. The results of my research will provide insights into the defense mechanisms of oak trees against arthropod herbivores, particularly in the time of expected increase of herbivory pressure due to global warming.

Photo: Tobias Müller
Tobias Müller
Project C2: Leaf characteristics, metabolome, and herbivory

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Within the Tree-M project my role is to develop an automatic image analysis pipeline. My expertise lies in the confluence between biology and novel computer science methods. I will use modern computer vision and artificial intelligence techniques to develop a system to qualify and quantify the effects of herbivory and pathogens on Quercus robur leaves. At the same time, these findings will be related to the leaf characteristics and metabolome of the tree leaves. In doing so, I hope to decipher the mysterious picture behind these exciting interactions of nature pixel by pixel.

Photo: Lucy Sauereßig
Lucy Sauereßig
Project C3: Consequences of changes in microbiota for leaf traits, metabolome, and herbivory

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Within the project, I will investigate the relationship between microbial resistance, leaf characteristics and herbivory. In this regard I will test the resistance of sun and shade leaves to radiation stress and analyze how bacterial strains influence leaf traits and herbivory. Further, I will design synthetic bacterial communities to functionally modulate the leaf microbiome.

Cross-section project D: Data management platform

Photo: Lisa Bald
Lisa Bald
Data Analyst

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My main contribution to this project will be the processing, integration, and standardization of various experimental data and metadata collected across spatial and temporal scales. For this purpose, we will consolidate the extensive datasets from Tree-M into a shared research data management platform.

Photo: Kristian Peters
Dr. Kristian Peters
Computer Scientist

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Within the project, I am integrating the domain-specific data generated in the project in a generalized FAIR research data management platform, including secure data storage, provenance and (meta)data management. To compare results across domains, I am coordinating and also working on data analysis workflows using standardized reproducible cloud-based tools and workflow management systems.

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