Genes adopt non-optimal codon usage to generate cell cycle-dependent oscillations in protein levels

Abstract

The cell cycle is a temporal program that regulates DNA synthesis and cell division. When we compared the codon usage of cell cycle-regulated genes with that of other genes, we discovered that there is a significant preference for non-optimal codons. Moreover, genes encoding proteins that cycle at the protein level exhibit non-optimal codon preferences. Remarkably, cell cycle-regulated genes expressed in different phases display different codon preferences. Here, we show empirically that transfer RNA (tRNA) expression is indeed highest in the G2 phase of the cell cycle, consistent with the non-optimal codon usage of genes expressed at this time, and lowest toward the end of G1, reflecting the optimal codon usage of G1 genes. Accordingly, protein levels of human glycyl-, threonyl-, and glutamyl-prolyl tRNA synthetases were found to oscillate, peaking in G2/M phase. In light of our findings, we propose that non-optimal (wobbly) matching codons influence protein synthesis during the cell cycle. We describe a new mathematical model that shows how codon usage can give rise to cell-cycle regulation. In summary, our data indicate that cells exploit wobbling to generate cell cycle-dependent dynamics of proteins.

Figure 1

The tRNA concentration during the cell cycle of S. cerevisiae. The concentration was calculated as an average of the different points in the same phases of the cell cycle according to Table II.

Figure 2

Total fluorescence as a function of the time during two cell cycles for YFP-tagged proteins, glycyl-tRNA synthetase (GARS), threonyl-tRNA synthetase (TARS), tryptophanyl-tRNA synthetase (WARS), and glutamyl-prolyl-tRNA synthetase (EPRS), when compared with GAPDH and ARGLU1 . (A) The lines represent the average fluorescence (±standard error) from >15 individual cells during two generations for the synthetases that show significant cell cycle-dependent protein dynamics. ARGLU1 is used as a positive control. (B) The total fluorescence (±standard error) for WARS and GAPDH as a negative control. WARS and GAPDH do not show the cell cycle-dependent protein dynamics. Source data is available for this figure in the Supplementary Information.

Figure 3

Comparison of CCCS for proteins with cell cycle-dependent protein dynamics versus proteins with non-cell cycle-dependent protein dynamics. The CCCS evaluates the proportion of wobble codon–anticodon base pairing similar to that of the top-600 genes. A red line represents the distribution mean.

Figure 4

A schematic presentation of the additional level of protein translation regulation via the tRNA pool. (A) The translation of poly-TTC and poly-TTT chains (used as an example) when the pool of charged tRNAs includes many TTC-tRNA^Phe. (B) Changes in the translation rate of poly-TTC and poly-TTT chains if few TTC-tRNA^Phe are available. (C) The oscillating tRNA pool may produce cell cycle-dependent translation of genes, which use wobble codon–anticodon base pairing. The translation rate of proteins using optimal codons stays constant.