Research Group Network Analysis and Modelling
In the Network Analysis and Modelling group, we study plant metabolic and regulatory networks in the context of de-novo network inference, model-assisted data analysis. Our major goal is to uncover and investigate mechanisms of phenotype emergence and provide strategies for targeted breeding and metabolic engineering of crop plants. Currently, our research includes three major directions: evolution and modelling of C4 photosynthesis, modelling and engineering of acyl-lipid metabolism, and molecular principles of metabolic traits emergence.
Figure 1: (A) Comparison of C3 and C4 plants based on leaf cross section and metabolism. (B) Comparison of C4 cycle modes.
Plants with the C4 trait are able to supercharge their carbon fixation using a carbon pump. Plants without the trait, also called C3 plants, use only Rubisco to fix CO2. This enzyme is not only a slow enzyme but also not very specific for CO2 and hence inefficient. C4 plants largely resolve this problem by concentrating CO2 at the site of Rubisco through a cycle of biochemical reactions which requires compartmentation. C4 photosynthesis is a complex trait, the sum of anatomical, regulatory and metabolic sub-traits is numerous, yet it evolved more than 60 times independently. Using a combination of RNA-seq and model building we dissect the complex trait and its evolution. The complex trait of C4 photosynthesis offers three outstanding advantages: (i) a trait directly related to yield, as many of the very productive crop plants are indeed C4 plants, (ii) a large collection of plants with the trait available for study and corresponding multi-level omics data, and (iii) active efforts to recreate the trait using synthetic biology.
Past projects include the molecular identification of enzymes and transport proteins contributing to the C4 cycle and conceptual models of the cycle for Gynandropsis gynandra, different Flaveria species, Panicum maximum, and Zea mays, model extension to a branched rather than linear cycle, identification of energy requirements depending on decarboxylation enzymes, developmental control of cycle architecture, modeling of limits for cycle architecture, conceptual models about the architectural trait components, the role of photorespiration in the trait, and stoichiometric models to understand evolution.
Current projects include a meta-analysis of ten independent origins of C4 photosynthesis to test model predictions, stoichiometric model development, and regulatory networks underlying the C4 trait.
Systems biology of lipid metabolism
Lipid compounds are main determinants of oil crops quality traits, but due to their multiple molecular functions, they also control the overall plant performance. Lipid compounds build cellular and organellar membranes of plant cells, they are major energy, carbon and phosphate storage, and some are involved in signalling, transport and stabilization of protein complexes. The structural diversity of lipid compounds reflects their wide range of functions. Nowadays, mass-spectrometry-based profiling of plant tissues enables routine identification and quantification of more than 300 lipid compounds.However, the exact biosynthetic pathways and functions are known only for a relatively small set of them.
In this project, we work on the reconstruction of the plant lipid assembly pathways using metabolomic, chemometric and transcriptomic data from whole plant samples as well as from isolated organelles. Our major goal is to explain and simulate observed plant lipid diversity and devise strategies for bioengineering and targeted breeding of oil crops. In parallel, we extend existing metabolic models and study the interaction between acyl lipid turnover and primary and secondary metabolism of the plant cell in different developmental and genetic contexts.
Molecular origins of metabolic traits
Differential metabolic phenotypes of ecotypes or cultivars of a given plant species originate from a system-scale rearrangement of metabolic fluxes under selective pressure. Metabolic fluxes, however, are system-scale properties controlled by multiple enzymatic and regulatory processes. Therefore, change of any metabolite level requires fine adjustment of numerous metabolic factors and thus might be connected to the shift in activity and expression of multiple genes. This is one of the reasons why it took thousands of years of selective breeding to generate modern crop cultivars characterized by high yield and high nutritional value.
In our group, we use metabolic modelling and tools of network analysis and inference in combination with QTL and GWAS analysis to study the emergence of metabolic traits on a system scale and identify regulatory and biochemical cues required to achieve given metabolic phenotype. We study metabolic changes accompanying phenomena such as heterosis, and we devise strategies to speed-up breeding of new crop cultivars to investigate the transferability of beneficial phenotypic traits between crop cultivars and their wild ancestors.