Unveiling the protistan Effectors: Using a bioinformatic approach to determine the role effector proteins play in Phytomyxean parasite-host interactions
Student/in: Alexander Scheiflinge, BSc
Termin: 29.04.2024, 10:05 Uhr
Ort: Seminarraum 2 (ICT Gebäude)
1. Prüfer/in: Univ.-Prof. Mag. Dr. Sigrid Neuhauser
2. Prüfer/in: Ass.-Prof. Dr. Luis Miguel Rodriguez-Rojas
Vorsitzende/r: Univ.-Prof. Mag. Dr. Paul Illmer
Interessierte Kolleginnen und Kollegen sind herzlich willkommen!
Abstract
Effector Proteins are small secreted protein used by pathogens and parasites to facilitate invasion of a host. Here, we investigate 2 protistan phytomyxid parasites, Plasmodiophora brassicae and Maullinia ectocarpii, and attempt to characterize putative effector proteins using a bioinformatic pipeline approach coupled with experimental verification. Using Alphafold in combination with the structural alignment tool Foldseek, we identified a potential defense-associated metalloproteinase inhibitor suggested to be involved in facilitating disruption of infection response elements in the host of Maullinia ectocarpii. We subsequently experimentally verified the presence of the metalloproteinase inhibitor in a Maullinia ectocarpii/Ectocarpus siliculosus pathosystem, using single-molecule fluorescent in-situ hybridization. Further, using Alphafold-Multimer to predict effector-host protein interactions, we were able to test 12 candidates from P. brassicae, and 1 candidate from M. ectocarpii, all thought to be involved in manipulations of host cell cycle processes. These we compared against host proteins involved in regulation of the specificity of the Anaphase Promoting Complex. Through these 37 pairwise interactive tests we were able to show the putative effectors were not able to complex with the selected host proteins based on the generated models. We show that tertiary structure prediction coupled with structural alignment, are novel next generation tools which can help identify and characterize effector protein candidates, as well as help predict the interaction between effector protein and host target proteins.