Biophysical Society Thematic Meeting | Trieste 2024

Emerging Theoretical Approaches to Complement Single-Particle Cryo-EM

Poster Abstracts

15-POS Board 15 A KINETIC MODEL FOR TRANSLATION ELONGATION FROM THE STEADY STATE DISTRIBUTION OF RIBOSOME INTERMEDIATES Federico Marotta 1 ; Maria Zimmermann-Kogadeeva 2 ; Sophia Rudorf 3 ; Julia Mahamid 1,4 ; Peer Bork 1,5 ; 1 European Molecular Biology Laboratory, Structural and Computational Biology Unit, Heidelberg, Germany 2 European Molecular Biology Laboratory, Genome Biology Unit, Heidelberg, Germany 3 Leibniz University Hannover, Institute of Cell Biology and Biophysics, Hannover, Germany 4 European Molecular Biology Laboratory, Cell Biology and Biophysics Unit, Heidelberg, Germany 5 University of Wurzburg, Department of Bioinformatics, Biocenter, Wurzburg, Germany Protein synthesis is one of the fundamental processes of molecular biology, with the ribosome playing a crucial role. Recently, it became possible to explore the intermediate states of translation elongation directly within living cells using cryogenic electron tomography (cryo ET). Specifically, this gave us a picture of the occupancy of each state in the model organism Mycoplasma pneumoniae. Nevertheless, cryo-ET is still unable to provide a dynamic, time resolved view of biological processes. In this work, we develop a kinetic model of translation elongation that integrates data from biochemical experiments in E. coli and transfers this information to M. pneumoniae under a "minimal evolution" assumption. This approach allows us to estimate the transition rates between intermediates in a way that can account for the observed steady-state distribution. Our findings indicate that the translation elongation cycle in M. pneumoniae is considerably slower and more error-prone than in E. coli. Furthermore, the mycoplasma ribosome has a marked tendency to remain in the non-rotated pre-translocation state, compared to the E. coli ribosome. Finally, we investigate whether the model can explain the effect of ribosome-targeting antibiotics such as chloramphenicol. Our methodology can potentially be extended to other biological processes where both cryo-ET and biochemical datasets are available, even if they are derived from different organisms. This allows for the estimation of the process dynamics in vivo, complementing the static cryo-ET snapshots.

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