UNIVERSITY OF COLOGNE

We are interested in revealing and understanding the constraints and capacities of leaf metabolism. In the past, we have used large-scale metabolic models to study CAM photosynthesis and alternative water-saving flux modes. Our current work studies metabolic flux modes and cellular energetics of C₃, C₃-C₄ intermediate, and C₄ photosynthesis in its leaf anatomical context (collaboration with AG Weber, HHU). Moreover, we study guard cell metabolism and their interactions with the mesophyll to resolve the guard cell’s role in providing energy and osmolytes for efficient stomatal opening (collaboration with Lee Sweetlove and George Ratcliffe (University of Oxford)). The gained knowledge shall help developing crop plants that are better adapted to adverse future climates.

PlantEd — A Serious Game for Education and Outreach

We have developed Plant-Ed — a strategy computer game for science communication and teaching. The player strategically allocates biomass to grow leaves, branches, roots, and flowers, faces dynamic weather conditions, manages resources efficiently, and fights with herbivores with the aim of maximizing seed biomass within a 35-day timeframe model. The game uses a whole-plant metabolic model and dynamic flux-balance analysis to allow the player to develop resource allocation strategies for optimal growth and survival. PlantEd is educative and fun; it teaches some basics of plant physiology and immerses the player into the fascinating world of plants. This project is in collaboration with AG Szymanski (IPK Gatersleben, FZ Jülich).

Integrating Plant Metabolic and Architectural Models

Plant architecture and metabolism mutually influence each other. In order to describe these dependencies, we have started to couple large-scale metabolic and functional-structural plant models. The latter provide a representation of whole-plant architecture and allow for the incorporation of meteorological datasets. We will employ our integrated model to better understand carbon and nitrogen partitioning and resource allocation towards different organs in wheat under different and changing environmental scenarios (including soil nitrogen levels and weather conditions). Our gained knowledge shall inform breeding strategies for improved traits in the next generation of wheat.

Flux Modelling During Seedling Development and Growth

During germination, plants depend on seed storage compounds for energy and macromolecule synthesis. Carbohydrates, lipids, and proteins act as major storage compounds. However, how storage compound usage is coordinated in various seed types remains poorly understood. In collaboration with AG Hildebrandt (UoC), we develop a time-resolved metabolic model to analyze carbon and nitrogen fluxes in the developing and growing seedling and parameterize this model with proteomics and metabolomics data from Arabidopsis thaliana and Lupinus albus seeds grown under ambient and adverse conditions. This study will shed light on metabolic adaptations for using lipids or proteins as major seed storage compounds. The findings will inform crop breeding strategies for enhanced seed composition.

In natural environments, plants share their habitat with a variety of microorganisms including bacteria, fungi, oomycetes, archaea, and viruses. This results in highly complex and dynamic interactions both among microbes and also between microbes and the host plant. The effects of these interactions can be categorized as harmful (amensalism) or beneficial (mutualism, synergism, or commensalism) or neutral. For example, plants rely on their microbiome for specific traits and functions, including nutrient acquisition and tolerance towards (a)biotic factors. Despite great diversity within the plant microbiome, four phyla dominate (Actinobacteria, Bacteroidetes, Firmicutes, and Proteobacteria) the microbiota. In collaboration with AG Thomma (UoC) we aim to understand fundamental processes of metabolic mediators of interactions between the host plant and individual strains of the microbiome. These insights will provide an important step towards understanding what creates, shapes, and drives the plant-microbial interactions.

Modelling predictions strongly depend on the quality of the underlying metabolic network reconstruction. These network reconstructions comprise hundreds to thousands of reactions which are typically assembled from metabolic pathway databases and are thus sensitive to annotation errors and error propagation. To address this issue we are supplying open-source software packages which offer coherent and reproducible curation workflows to the community. Recently, we developed CobraMod - a pathway-centric curation tool for constraint-based metabolic models.