Faculty Sponsor: Michael P. Weir
Evelyn Zhou
Evelyn Zhou is a rising senior(’24) coming from Kunming, China. She is double major in Biology and Neuroscience & Behavior at Wesleyan University and would like to continue her study in a graduate school and probably work in the field of neurology. Her interests including stand-up comedy, swimming and doing Kpop dance covers.
Abstract: In the universal genetic code, most amino acids can be encoded by multiple tri-nucleotide codons, and the choice among available codons can influence position-specific translation elongation rates. In previous transcriptome-wide ribosome profiling studies it was found that C/U-ending codon pairs sharing the same tRNA family ending with a G in the anti-codon wobble position are translated at different rates depending on whether they are translated via G:U wobble base-pairing or standard G:C base-pairing. In our recent bioinformatics analysis of published ribosome profiling data in S. cerevisiae, we observed that amongst G:C/G:U pairing codons, ribosome densities were higher for U-ending (NNU) codons when they were followed by a G-starting (+1 GNN) codon; the C-ending (NNC) codons remained mostly unaffected. One possible explanation for this effect is that it is mediated by the ribosome CAR interaction surface, which we hypothesize provides a layer of translation regulation via hydrogen-bonding to the +1 mRNA codon next to enter the ribosome A site during translocation. Consistent with our ribosome profiling analysis, CAR preferentially hydrogen bonds with +1 codons starting with G (+1 GNN). In this study we present a Molecular Dynamics analysis of how wobble nucleotides in G:C/G:U pairing codons in the A-site affect the A-site anticodon:codon and CAR:+1 codon hydrogen bonding network. We observe when NNU codons are followed by a +1 GCU codon, there is accentuated CAR:+1 codon hydrogen bonding, suggesting that CAR may help ribosomes to occupy these NNU codons for longer, producing the elevated densities observed in our analysis of ribosome profiling data.
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