Department of Biology
Department ofBiology
German Society for Plant SciencesSilja Seemann receives the DBG prize for the best master's thesis in plant science in 2025
16 February 2026, by Website Team Biologie
Photo: AlphaFold Data 2022 (DeepMind Technologies Limited)
Silja Seemann received the German Society for Plant Sciences (DBG) prize for the best master's thesis of 2025 in botany and plant sciences at the University of Hamburg for her work "Identification of amino acid residues critical for the activity, dimerisation, and regulation of the small GTPase, Arabidopsis immune-associated nucleotide-binding protein 12 (AtIAN12), by site-directed mutagenesis."
In her research project, Silja investigated the plant protein AtIAN12, which plays a crucial role in the immune system of Arabidopsis. Through a variety of molecular and structural analyses, an amino acid was identified that is essential for the activation and function of the protein. The results contribute to a better understanding of the complex regulatory mechanisms of plant immunity.
"I was honoured to receive this award, as it recognizes the effort I put into my project. I really enjoyed working on it, especially thanks to my research group. The MoPS Master's program gave me a fantastic chance to learn and grow personally.",said Silja after receiving the award. Silja completed her master's degree in the research unit Plant Biochemistry & Infection Biology under Prof. Dr. Sigrun Reumann.
A scientific abstract of the master's thesis can be found at German Society for Plant Sciences.
Photo: UHH/Bio
Presentation by Silja Seemann at the award ceremony during the IPM New Year's Reception 2026
Photo: AlphaFold Data 2022 (DeepMind Technologies Limited)
Cartoon representation of AtIAN12. The AtIAN12 structure model predicted by the AlphaFold Protein Structure Database (AF-Q9T0F3-F1-v4). Secondary structure elements are shown, and model confidence is colour-coded (dark blue: pLDDT > 90, very high; light blue: 90 > pLDDT > 70, high; yellow: 70 > pLDDT > 50, low; orange: pLDDT < 50, very low). The figure was adapted from the AlphaFold Protein Structure Database no. AF-Q9T0F3-F1-v4 (Jumper et al., 2021; Varadi et al., 2024; AlphaFold Data Copyright (2022) DeepMind Technologies Limited).