Prof. Dr. Nadine Töpfer

Research focus

Our research aims to gain a better understanding of the behaviour of plant metabolic systems and their interactions. The group uses computational approaches that are centered around the analysis of large-scale metabolic networks and works closely with experimental labs. Key topics include developing flux-balance methods to study plant metabolism at the cell type-, tissue- and whole-plant level as well as plant-environment interactions. We have also started to develop multi-scale models to better account for genetic, physical, and environmental influences on plant metabolism. On the technical side, we are developing open-source software packages for coherent and reproducible metabolic network curation. The gained knowledge will guide metabolic engineering strategies for improved crop plant productivity and quality.

Most important publications

  1. Camborda S, Weder JN, Töpfer N (2022) CobraMod: a pathway-centric curation tool for constraint-based metabolic models. Bioinformatics 38(9):2654-2656. doi: 10.1093/bioinformatics/btac119.
  2. Töpfer N (2021) Environment-coupled models of leaf metabolism. Biochem Soc Trans 49(1):119-129. doi: 10.1042/BST20200059.
  3. Töpfer N, Braam T, Shameer S, Ratcliffe RG, Sweetlove LJ (2020) Alternative Crassulacean Acid Metabolism Modes Provide Environment-Specific Water-Saving Benefits in a Leaf Metabolic Model. Plant Cell 32(12):3689-3705. doi: 10.1105/tpc.20.00132.
  4. Töpfer N, Fuchs LM, Aharoni A (2017) The PhytoClust tool for metabolic gene clusters discovery in plant genomes. Nucleic Acids Res 45(12):7049-7063. doi: 10.1093/nar/gkx404.
  5. Szymanski J, Levin Y, Savidor A, Breitel D, Chappell-Maor L, Heinig U, Töpfer N, Aharoni A (2017) Label-free deep shotgun proteomics reveals protein dynamics during tomato fruit tissues development. Plant J 90(2):396-417. doi: 10.1111/tpj.13490.
  6. Sajitz-Hermstein M, Töpfer N, Kleessen S, Fernie AR, Nikoloski Z (2016) iReMet-flux: constraint-based approach for integrating relative metabolite levels into a stoichiometric metabolic models. Bioinformatics 32(17):i755-i762. doi: 10.1093/bioinformatics/btw465.
  7. Töpfer N, Scossa F, Fernie A, Nikoloski Z (2014) Variability of metabolite levels is linked to differential metabolic pathways in Arabidopsis's responses to abiotic stresses. PLoS Comput Biol 10(6):e1003656. doi: 10.1371/journal.pcbi.1003656.
  8. Recht L, Töpfer N, Batushansky A, Sikron N, Gibon Y, Fait A, Nikoloski Z, Boussiba S, Zarka A (2014) Metabolite profiling and integrative modeling reveal metabolic constraints for carbon partitioning under nitrogen starvation in the green algae Haematococcus pluvialis. J Biol Chem 289(44):30387-30403. doi: 10.1074/jbc.M114.555144.
  9. Töpfer N, Caldana C, Grimbs S, Willmitzer L, Fernie AR, Nikoloski Z (2013) Integration of genome-scale modeling and transcript profiling reveals metabolic pathways underlying light and temperature acclimation in Arabidopsis. Plant Cell 25(4):1197-1211. doi: 10.1105/tpc.112.108852.
  10. Töpfer N, Jozefczuk S, Nikoloski Z (2012) Integration of time-resolved transcriptomics data with flux-based methods reveals stress-induced metabolic adaptation in Escherichia coli. BMC Syst Biol 6:148. doi: 10.1186/1752-0509-6-148.