Using big data for the analysis of cellular translational control
Protein synthesis is essential for any living organism. However, how the dynamics of mRNA translation affect the formation of functional proteins is poorly understood. To gain new insights into the relationship between translation dynamics and protein folding, we analyze mutants that show codon-specific translation defects.
We analyze these mutants in detail using a variety of omics techniques such as ribosome profiling or pulse-chase proteomics. As all these methods generate large amounts of data, it is essential to be able to store and handle such large datasets. With the funding we received from the UniBern Forschungsstiftung, we purchased an extension to our redundant NAS storage system and a new analysis server. We have already used it to characterize key enzymes in translation dynamics (Wu et al., bioRxiv 2024; Lin et al., Mol Cell 2024).
The next goal is to develop machine learning strategies to analyze and integrate these datasets. However, the extension of our NAS system, combined with the purchase of a new analysis server, has already led to exciting new discoveries and will continue to do so in the future.
Prof. Dr. Sebastian A. LEIDEL
Department of Chemistry, Biochemistry and Pharmaceutical Sciences
Links:
– Wu et al., BioRxiv 2024: DOI: 10.1101/2024.02.27.582385
www.biorxiv.org/content/10.1101/2024.02.27.582385v2
– Lin et al., Molecular Cell 2024: DOI: 10.1016/j.molcel.2024.06.013