Plants use photosynthesis to produce biomass and oxygen from carbon dioxide and water. Since photosynthesis and cellular metabolism are tightly linked, plants must react rapidly to changes in environmental conditions in order to limit cell death and avoid damage to tissues. How these vital processes are regulated at the cellular level is not yet fully understood, largely because they have not been studied in sufficient detail to reveal their full complexity. Plant cells show a high degree of compartmentation, i.e. they contain distinct types of “reaction chambers”, in which different metabolic processes take place. These compartments include membrane-bound organelles, such as chloroplasts and mitochondria, in addition to the cytoplasm that forms the fluid phase of the cell. In a new DFG-funded project entitled “Subcellular Analysis of Metabolic Network Dynamics under elevated CO2 , LMU biologist Thomas Nägele, in cooperation with colleagues based at Stuttgart University and the Max Planck Institute for Molecular Plant Physiology in Potsdam-Golm, will investigate metabolic dynamics on a compartment-specific basis to obtain a more precise picture of how plant metabolism responds to increasing levels of atmospheric CO2.
The team will focus on three enzymes which are localized in different compartments. Using a combination of biochemical and genetic methods, the collaborating scientists will investigate the significance of these enzymes for plant metabolism and the regulation of metabolic networks when plants are exposed to higher concentrations of CO2. Nägele and his group will analyze the responses in detail with the aid of high-throughput techniques that permit the identification and quantification of all the metabolic products and proteins present in each compartment. In addition, the LMU researchers will evaluate the results obtained using machine-learning techniques and statistical procedures, which will enable them to recognize patterns in the data. “Our aim is to derive biochemically and physiologically interpretable conclusions from analyses of high-dimensional data with thousands of variables,” Nägele explains. “To achieve this, we will make use of what are known as deep-learning algorithms, since the underlying biochemical networks are organized in highly complex ways.”
Scientists cannot yet reliably forecast how plants – and whole ecosystems – will react to rising levels of CO2 in the atmosphere. Nägele has shown in previous studies that certain molecular switches and enzymes are involved in orchestrating the response of a plant species to increased concentrations of ambient CO2. “Now we want to uncover the precise molecular functions of these switches,” he says. “This could then open up new options for technical or genetic countermeasures, such as methodologies for the efficient removal of CO2 from the atmosphere.”