The ribosome CAR interaction surface is hypothesized to provide a layer of translation regulation through hydrogen-bonding to the +1 mRNA codon that is next to enter the ribosome A site during translocation. The CAR surface consists of three residues, 16S/18S rRNA C1054, A1196 (E. coli 16S numbering), and R146 of yeast ribosomal protein Rps3. R146 can be methylated by the Sfm1 methyltransferase which is downregulated in stressed cells. Through molecular dynamics analysis, we show here that methylation of R146 compromises the integrity of CAR by reducing the cation-pi stacking of the R146 guanidinium group with A1196, leading to reduced CAR hydrogen-bonding with the +1 codon. We propose that ribosomes assembled under stressed conditions have unmethylated R146, resulting in elevated CAR/+1 codon interactions, which tunes translation levels in response to the altered cellular context.
Aim To examine how circulating glucagon‐like peptide‐1 (GLP‐1) concentrations during liraglutide treatment relate to its therapeutic actions on glucose and weight, and to study the effects of liraglutide on other proglucagon‐derived peptides (PGDPs), including endogenous GLP‐1, glucagon‐like peptide‐2, glucagon, oxyntomodulin, glicentin and major proglucagon fragment, which also regulate metabolic and weight control. Materials and Methods Adults who were overweight/obese (body mass index 27‐40 kg/m2) with prediabetes were randomized to liraglutide (1.8 mg/day) versus placebo for 14 weeks. We used specific assays to measure exogenous (liraglutide, GLP‐1 agonist [GLP‐1A]) and endogenous (GLP‐1E) GLP‐1, alongside five other PGDP concentrations during a mixed meal tolerance test (MMTT) completed at baseline and at week 14 (liraglutide, n = 16; placebo, n = 19). Glucose during MMTT, steady‐state plasma glucose (SSPG) concentration for insulin resistance and insulin secretion rate (ISR) were previously measured. MMTT area‐under‐the‐curve (AUC) was calculated for ISR, glucose and levels of PGDPs. Results Participants on liraglutide versus placebo had significantly (P ≤ .004) decreased weight (mean −3.6%, 95% CI [−5.2% to −2.1%]), SSPG (−32% [−43% to −22%]) and glucose AUC (−7.0% [−11.5% to −2.5%]) and increased ISR AUC (30% [16% to 44%]). GLP‐1A AUC at study end was significantly (P ≤ .04) linearly associated with % decrease in weight (r = −0.54) and SSPG (r = −0.59) and increase in ISR AUC (r = 0.51) in the liraglutide group. Treatment with liraglutide significantly (P ≤ .005) increased exogenous GLP‐1A AUC (median 310 vs. 262 pg/mL × 8 hours at baseline but decreased endogenous GLP‐1E AUC [13.1 vs. 24.2 pmol/L × 8 hours at baseline]), as well as the five other PGDPs. Decreases in the PGDPs processed in the intestines are independent of weight loss, indicating a probable direct effect of GLP‐1 receptor agonists to decrease their endogenous production in contrast to weight loss‐dependent changes in glucagon and major proglucagon fragment that are processed in pancreatic alpha cells. Conclusions Circulating GLP‐1A concentrations, reflecting liraglutide levels, predict improvement in weight, insulin action and secretion in a linear manner. Importantly, liraglutide also downregulates other PGDPs, normalization of the levels of which may provide additional metabolic and weight loss benefits in the future.
The ribosome CAR interaction surface behaves as an extension of the decoding center A site and has H-bond interactions with the +1 codon, which is next in line to enter the A site. Through molecular dynamic simulations, we investigated the codon sequence specificity of this CAR–mRNA interaction and discovered a strong preference for GCN codons, suggesting that there may be a sequence-dependent layer of translational regulation dependent on the CAR interaction surface. Dissection of the CAR–mRNA interaction through nucleotide substitution experiments showed that the first nucleotide of the +1 codon dominates over the second nucleotide position, consistent with an energetically favorable zipper-like activity that emanates from the A site through the CAR–mRNA interface. Moreover, the CAR/+1 codon interaction is affected by the identity of nucleotide 3 of +1 GCN codons, which influences the stacking of G and C. Clustering analysis suggests that the A-site decoding center adopts different neighborhood substates that depend on the identity of the +1 codon.
The ribosome CAR interaction surface is hypothesized to provide a layer of translation regulation through hydrogen-bonding to the +1 mRNA codon that is next to enter the ribosome A site during translocation. The CAR surface consists of three residues, 16S/18S rRNA C1054, A1196 (E. coli 16S numbering), and R146 of yeast ribosomal protein Rps3. R146 can be methylated by the Sfm1 methyltransferase which is downregulated in stressed cells. Through molecular dynamics analysis, we show here that methylation of R146 compromises the integrity of CAR by reducing the pi stacking of the R146 guanidinium group with A1196, leading to reduced CAR hydrogen-bonding with the +1 codon. We propose that ribosomes assembled under stressed conditions have unmethylated R146, resulting in elevated CAR/+1 codon interactions, which tunes translation levels in response to the altered cellular context.
The ribosome CAR interaction surface behaves like an extension of the decoding center A site and has H-bond interactions with the +1 codon that is next in line to enter the A site. Through molecular dynamics simulations, we investigated the codon sequence specificity of this CAR-mRNA interaction and discovered a strong preference for GCN codons, suggesting that there may be a sequence-dependent layer of translational regulation dependent on the CAR interaction surface. Dissection of the CAR-mRNA interaction through nucleotide substitution experiments showed that the first nucleotide of the +1 codon dominates over the second nucleotide position, consistent with an energetically favorable zipper-like activity that emanates from the A site through the CAR-mRNA interface. The +1 codon/CAR interaction is also affected by the identity of nucleotide 3 of +1 GCN codons which influences the stacking of G and C. Clustering analysis suggests that the A site decoding center adopts different neighborhood substates that depend on the identity of the +1 codon.
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