Author response: tRNA genes rapidly change in evolution to meet novel translational demands (2013)

Article Figures and data Abstract eLife digest Introduction Results Discussion Materials and methods Data availability References Decision letter Author response Article and author information Metrics Abstract Changes in expression patterns may occur when organisms are presented with new environmental challenges, for example following migration or genetic changes. To elucidate the mechanisms by which the translational machinery adapts to such changes, we perturbed the tRNA pool of Saccharomyces cerevisiae by tRNA gene deletion. We then evolved the deletion strain and observed that the genetic adaptation was recurrently based on a strategic mutation that changed the anticodon of other tRNA genes to match that of the deleted one. Strikingly, a systematic search in hundreds of genomes revealed that anticodon mutations occur throughout the tree of life. We further show that the evolution of the tRNA pool also depends on the need to properly couple translation to protein folding. Together, our observations shed light on the evolution of the tRNA pool, demonstrating that mutation in the anticodons of tRNA genes is a common adaptive mechanism when meeting new translational demands. https://doi.org/10.7554/eLife.01339.001 eLife digest Genes contain the blueprints for the proteins that are essential for countless biological functions and processes, and the path that leads from a particular gene to the corresponding protein is long and complex. The genetic information stored in the DNA must first be transcribed to produce a messenger RNA molecule, which then has to be translated to produce a string of amino acids that fold to form a protein. The translation step is performed by a molecular machine called the ribosome, with transfer RNA molecules bringing the amino acids that are needed to make the protein. The information in messenger RNA is stored as a series of letters, with groups of three letters called codons representing the different amino acids. Since there are four letters—A, C, G and U—it is possible to form 64 different codons. And since there are only 20 amino acids, two or more different codons can specify the same amino acid (for example, AGU and AGC both specify serine), and two or more different transfer RNA molecules can take this amino acid to the ribosome. Moreover, some codons are found more often than others in the messenger RNA molecules, so the genes that encode the related transfer RNA molecules are more common than the genes for other transfer RNA molecules. Environmental pressures mean that organisms must adapt to survive, with some genes and proteins increasing in importance, and others becoming less important. Clearly the relative numbers of the different transfer RNA molecules will also need to change to reflect these evolutionary changes, but the details of how this happens were not understood. Now Yona et al. have explored this issue by studying yeast cells that lack a gene for one of the less common transfer RNA molecules (corresponding to the codon AGG, which specifies the amino acid arginine). At first this mutation resulted in slower growth of the yeast cells, but after being allowed to evolve over 200 generations, the rate of growth matched that of a normal strain with all transfer RNA genes. Yona et al. found that the gene for a more common transfer RNA molecule, corresponding to the codon AGA, which also specifies arginine, had mutated to AGG. As a result, the mutated yeast was eventually able to produce proteins as quickly as wild type yeast. Moreover, further experiments showed that the levels of some transfer RNAs are kept deliberately low in order to slow down the production of proteins so as to ensure that the proteins assume their correct structure. But does the way these cells evolved in the lab resemble what happened in nature? To address this question Yona et al. examined a database of transfer RNA sequences from more than 500 species, and found evidence for the same codon-based switching mechanism in many species across the tree of life. https://doi.org/10.7554/eLife.01339.002 Introduction The process of gene translation is fundamental to the function of living cells, and as such its apparatus is highly conserved across the tree of life (Müller and Wittmann-Liebold, 1997; Itoh et al., 1999; Wolf et al., 2001). Yet, the capacity of the translation machinery to adaptively evolve is crucial in order to support life in changing environments. Therefore, a key open question is to identify the mechanisms by which the translation machinery adapts to changing conditions. A thoroughly studied aspect of translation that demonstrates its adaptation capacities is the different proportions by which synonymous codons are used, a phenomenon known as ‘codon usage bias’. Although differential use of codons can be the result of neutral processes such as mutational biases and the genomic GC content (Urrutia and Hurst, 2001; Rao et al., 2011), natural selection also influences codon usage bias. Indeed, it has been demonstrated that codon choice affects expression level, protein folding, translational accuracy, and other translational features (Akashi, 1994; Parmley and Hurst, 2007; Zhou et al., 2009; Hudson et al., 2011). Since both neutral and selective processes govern codon usage bias, the balance between selection, mutational bias and drift is crucial in shaping the codon usage of each species (Bulmer, 1991). Importantly, although the selective advantage offered by alternative synonymous codons is considered to be moderate, it was recently demonstrated that selection can still shape codon usage patterns in vertebrates even with their small effective population sizes (Doherty and McInerney, 2013). Notably, the differential usage of codons represents the evolution of the ‘demand’ aspect of translation, namely the codon usage of all expressed genes. Yet, the adaptation mechanisms of the ‘supply’, namely the expression level of each tRNA type that is loaded with an amino acid, are not fully understood. While ribosomal genes do not exhibit appreciable changes in response to environmental alterations (Müller and Wittmann-Liebold, 1997; Itoh et al., 1999; Wolf et al., 2001), tRNA genes may provide an important source of evolutionary plasticity for fine tuning translation. tRNAs constitute a fundamental component in the process of translation, linking codons to their corresponding amino acids (Widmann et al., 2010). tRNA genes are classified into gene families according to their anticodon, with each gene family containing between one and several copies scattered throughout the genome. Importantly, it has been experimentally observed for Saccharomyces cerevisiae (Tuller et al., 2010) and Escherichia coli (Dong et al., 1996) that the cellular concentrations of each tRNA family in the cell (i.e., the tRNA pool) correlate with its genomic tRNA copy number (Percudani et al., 1997; Kanaya et al., 1999). Notably, the rate-limiting step of polypeptide elongation is the recruitment of a tRNA that matches the translated codon (Varenne et al., 1984). Thus, the translation efficiency is defined as the extent to which the tRNA pool can accommodate the transcriptome (Sharp and Li, 1987; Dos Reis et al., 2004; Stoletzki and Eyre-Walker, 2007), thereby affecting protein production and accuracy. In general, highly expressed genes exhibit a marked codon usage bias toward ‘optimal’ codons, whose corresponding tRNA gene copy number is high (Sharp and Li, 1986a, 1986b). The evolutionary force that acts to maintain optimal translation efficiency of such genes was coined ‘translational selection’ (Dos Reis et al., 2004). It was previously suggested that translational selection acts to maintain a balance between codon usage and tRNA availability. On the one hand, there is a selective pressure to increase the frequency of preferred codons in highly expressed genes. On the other hand, changes in the tRNA pool may also occur, for example duplication of tRNA genes for which high codon demand exists. Thus, codon frequencies and tRNA copy numbers coevolve toward a supply versus demand balance that facilitates optimal protein production (Higgs and Ran, 2008; Gingold et al., 2012). The fitness effects of an unmet translational demand and its potential role in shaping the tRNA pool are not fully characterized. Evolutionary changes to the tRNA pool were appreciated mainly via bioinformatics studies (Rawlings et al., 2003; Withers et al., 2006; Higgs and Ran, 2008; Bermudez-Santana et al., 2010; Rogers et al., 2010) and only a handful of experimental findings have been reported, which rely on genetic manipulations (Byström and Fink, 1989; Von Pawel-Rammingen et al., 1992; Aström et al., 1993) or direct mutagenesis (Saks et al., 1998). Sequence analyses of divergent genomes have demonstrated that both the sequence and copy number of tRNA genes may change among various species or strains. However, it is unclear whether the observed variations in the tRNA pool are a consequence of an adaptive process due to unbalanced translational demand or the result of random genomic processes, as tRNA genes are a known source of genomic instability (McFarlane and Whitehall, 2009). Further, the forces that direct and maintain low copy tRNA families remain unclear. Specifically, it is not clear whether translational selection acts only to favor optimal codons or also acts in particular cases to keep other codons deliberately as ‘non-optimal’ by maintaining their tRNA supply at low level. Encoding genes with optimal codons might not always lead to higher protein expression levels (Kudla et al., 2009). Similarly, the use of ‘slow codons’ may not always result in lower levels of protein expression as they could have functional roles in improving expression, for example when enriched at the beginning of a transcript in order to reduce the energy of the RNA structure (Goodman et al., 2013) or to efficiently allocate ribosomes along the mRNA (Tuller et al., 2010). Additionally, it has been proposed that non-optimal codons may play a role in governing the process of cotranslational folding by slowing down translation, which supports proper folding between domain boundaries (Thanaraj, 1996; Kramer et al., 2009; Cabrita et al., 2010; Wilke and Drummond, 2010; Pechmann and Frydman, 2012). Yet, the contribution of non-optimal codons to proper protein folding was observed only for specific genes (Crombie et al., 1992; Komar et al., 1999; Cortazzo et al., 2002; Tsai et al., 2008; Zhang et al., 2009; Zhou et al., 2013). Thus, the extent and relevance of this phenomenon to the global folding state of the proteome needs to be substantiated. To elucidate the importance of restoring translational equilibrium, we used an experimental evolution approach. To this end, we genetically perturbed the tRNA pool of the budding yeast S. cerevisiae. In this yeast, the genetic code is decoded by 42 different tRNA families that make up a total of 274 tRNA genes (Chan and Lowe, 2009). Each tRNA gene family ranges from 1–16 copies, with 6 tRNA families consisting of only a single copy. In a recent study (Bloom-Ackermann et al., In press), we have systematically manipulated the tRNA pool in S. cerevisiae by individually deleting most tRNA genes from its genome. Here, we focus on one particular deletion strain that showed the most extreme fitness reduction among the viable deletion mutants in this tRNA deletion library. This tRNA exists in only one copy in the genome, thus after its deletion the cell is left without a tRNA with the corresponding anticodon. Lab-evolution experiments performed on this strain demonstrated that the translational balance was rapidly restored by mutations in other tRNA genes that compensated for the tRNA deletion. An extensive bioinformatic analysis revealed that a similar evolutionary trend is widespread in nature too, suggesting that the anticodon mutations we observed in the lab recapitulate an existing mechanism that shapes the tRNA pool. To shed light on the constraints that shape the size of tRNA gene families, we artificially overexpressed singleton tRNAs, rather than deleting them. We found that when low copy tRNAs were overexpressed, the protein quality control machinery was challenged due to increased proteotoxic stress. This observation suggests that low tRNA availability for particular codon can serve an essential means to ensure proper cotranslation folding of proteins. Results Deletion of singleton tRNA gene breaks the translational balance To demonstrate the importance of the balance between codon usage and the cellular tRNA pool we created a yeast strain in which the single copy of the arginine tRNA gene, tR(CCU)J, was deleted (designated ΔtRNAArgCCU). Consequently, in this deletion strain, the arginine codon AGG cannot be translated with its fully matched tRNA and it is presumably translated by another arginine tRNA, tRNAArgUCU, owing to a wobble interaction (Begley et al., 2007). This shortage in tRNA supply is particularly evident given the demand: AGG is the second most highly used codon for arginine in the yeast genome (Supplementary file 1A). Indeed, the ΔtRNAArgCCU strain showed a severe growth defect compared to the wild-type strain (Figure 1A, blue and green curves, respectively). This growth difference demonstrates the effect of translational imbalance on cellular growth. Although the deletion mutant of this single copy tRNA is viable (Clare et al., 1988; Kawakami et al., 1993), its severe growth defect also reveals the inability of the wobble interactions to fully compensate for the tRNA gene deletion. Figure 1 Download asset Open asset The growth defect associated with deletion of a singleton tRNA gene was rapidly rescued during the lab-evolution experiment. (A) Growth curve measurements of wild-type (WT) (green), ΔtRNAArgCCU (blue) and the evolved deletion (red) are shown in optical density (OD) values over time during continuous growth on rich medium at 30°C. (B) The mutation that was found to recover the deletion phenotype in the evolved strains is shown on the secondary structure of tRNAArgUCU. The UCU anticodon nucleotides are marked with black circles, and the red circle indicates the mutation that occurred in the anticodon, that is T→C transition. (C) MutΔtRNAArgCCU in which the same mutation that was found in the evolved strain was deliberately engineered, exhibits similar growth as the WT. Growth curve measurements of WT (green) and of MutΔtRNAArgCCU (magenta) are shown in OD600 values over time during continuous growth on rich medium at 30°C. https://doi.org/10.7554/eLife.01339.003 The tRNA pool can rapidly evolve to meet translational demands To learn how genomes adapt to translational imbalances, we performed lab-evolution experiments on the ΔtRNAArgCCU strain, employing the procedure of daily growth and dilution to a fresh medium (Lenski et al., 1991). The deletion strain was grown under optimal laboratory conditions (rich medium at 30°C) and was diluted daily into a fresh medium by a factor of 120, corresponding to approximately 7 generations per cycle. Every 50 generations, the growth of the evolving population was compared to both the wild-type and the ancestor ΔtRNAArgCCU strains. Strikingly, after 200 generations we observed a full recovery of the growth defect of the ancestor strain ΔtRNAArgCCU, as the growth curve of the evolved population was indistinguishable from that of the wild-type strain (Figure 1A, red curve). Similar dynamics were observed in all four independent evolutionary lines. In search of the potential genetic adaptations underlying this rapid recovery, we first looked for genetic alterations in other arginine tRNA genes. We found a single point mutation in another arginine tRNA gene that codes for tRNAArgUCU. This mutation changed the anticodon triplet of tRNAArgUCU from UCU to CCU (i.e., T→C transition). Consequently, the evolved tRNAArgUCU perfectly matched the AGG codon (Figure 1B). Unlike the singleton tRNAArgCCU, there are 11 copies of tRNAArgUCU in the yeast genome. Although each of the 4 independent lab-evolution experiments showed the exact same solution (that is, a mutation in the anticodon of a tRNAArgUCU gene), 3 different copies of this gene were changed among the 4 lines (i.e., 1 of the 11 copies of tRNAArgUCU was mutated in 2 repetitions; see ‘Materials and methods’). To confirm that a single point mutation in the anticodon of tRNAArgUCU is sufficient to fully compensate for the growth defect of ΔtRNAArgCCU, we artificially inserted the same T→C mutation into the deletion ΔtRNAArgCCU mutant. We inserted the mutation into 1 of the 11 copies of the tRNAArgUCU genes, a copy that resides on chromosome XI, and thus spontaneously mutated in 1 of the evolution lines. Indeed, the artificially mutated strain, termed as MutΔtRNAArgCCU, showed a full recovery of the deletion adverse phenotype (Figure 1C). This indicates that the T→C mutation in the anticodon is sufficient for the full recovery of the tRNAArgCCU deletion phenotype. Mutated tRNAArgUCU is functional despite sequence dissimilarities with respect to the deleted tRNAArgCCU In general, all copies of each tRNA gene family tend to be highly similar in sequence in S. cerevisiae (Chan and Lowe, 2009). In particular, the sequences of the 11 copies of tRNAArgUCU are 100% identical to each other. Yet, the 2 arginine tRNA, tRNAArgUCU, and tRNAArgCCU, differ in 21 of their 72 nucleotides (including the third anticodon position, Figure 2A). Thus, the evolutionary solution that occurred in our experiments created a ‘chimeric’ tRNA with a CCU anticodon, whereas the rest of the tRNA sequence (termed as the ‘tRNA scaffold’) remained as tRNAArgUCU. The sequence identity among all members of the tRNAArgUCU family suggests a functional role for the tRNA scaffold in addition to that of the anticodon (Schultz and Yarus, 1994; Konevega et al., 2004; Cochella and Green, 2005; Olejniczak et al., 2005; Saks and Conery, 2007; Schmeing et al., 2011). Therefore, it is surprising that the chimeric tRNA performed just as well as the deleted tRNAArgCCU in terms of cell growth, despite the major sequence differences between the two tRNA scaffolds. Thus, we raised the hypothesis that more challenging growth conditions may expose possible inadequacies in the chimeric tRNA. To test this notion, we compared the rescued strain, MutΔtRNAArgCCU, which carries the chimeric tRNA, to the wild-type strain under an array of challenging conditions. Surprisingly, under all the examined conditions, we observed no significant growth difference between the two strains (Figure 2B). Hence, the chimeric tRNA provides a direct in vivo indication that the scaffolds of tRNAs, which encode for the same amino acid, may be interchangeable in terms of their effect on cellular growth under the conditions we tested. Figure 2 with 2 supplements see all Download asset Open asset The growth of MutΔtRNAArgCCU carrying the chimeric tRNA compared to wild-type (WT) under different conditions. (A) The sequence of the chimeric tRNA is drawn showing the scaffold of tRNAArgUCU with the mutated CCU anticodon. The anticodon triplet is marked with black circles. The evolved mutation is marked with a red circle. All 20 nucleotide differences between tRNAArgUCU and tRNAArgCCU are marked with blue background, next to which, in green letters, the original nucleotide of tRNAArgCCU are written. (B) Growth curve measurements of WT (green) and of MutΔtRNAArgCCU (magenta) are shown in OD600 values over time during continuous growth. https://doi.org/10.7554/eLife.01339.004 To examine the generality of our observation, we once again perturbed the tRNA pool in a wild-type (WT) strain by deletion of an entire serine tRNA family, tRNASerGCU that has four copies in the genome. A complete deletion of this gene family is lethal, indicating that the tRNASerGCU is essential in S. cerevisiae. Although we could not evolve that strain, we did find that this quadruple deletion strain was viable when supplemented with a centromeric carrying the tRNASerGCU Thus, the is from the tRNA and is not due to other effects (Figure We as with tRNAArgCCU, other chimeric serine tRNAs that a anticodon, with the scaffold of another tRNA for also the observed Indeed, a strain carrying a chimeric tRNA with a scaffold of and the anticodon is viable on the of the deletion (Figure Therefore, we that the identity of the anticodon is essential for the function of the tRNASerGCU gene Thus, it that for the examined tRNAs the anticodon is a in terms of cellular other sequence switching is a widespread phenomenon in nature Although the anticodon of a tRNA gene was rapidly mutated under our laboratory conditions, thus proper translational equilibrium, it is unclear to what extent this mechanism in species across the tree of life. To address this we performed a systematic bioinformatics for tRNA switching in We defined an as a of a tRNA whose nucleotide sequence is to a tRNA gene with a different anticodon than to a tRNA gene with the same anticodon. To this end, we all the known tRNA sequences from the tRNA (Chan and Lowe, a that the tRNA of We the anticodon triplet as in all tRNA genes, all tRNA sequences from each species individually and a tree for each each tRNA we the to another tRNA with the same anticodon (designated and the to another tRNA with a different anticodon (designated each species, we defined its of tRNA switching as in which ‘Materials and Figure data analysis and We found that tRNA switching are in all of as we at 1 tRNA switching per species in and 1 species (Figure A revealed that most switching occurred due to a mutation in the first in the anticodon triplet that to the third codon details in ‘Materials and methods’). we as of nucleotides the tRNA molecule, and found a higher of compared to the anticodon triplet (Figure file 1B). Figure 3 with 1 see all Download asset Open asset switching is a widespread phenomenon in (A) of species with at one tRNA switching in each domain of life. 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We thus that an increase in the copy number of a tRNA, but not of an might result in a effect on the Indeed, of a containing a tRNAArgCCU gene to a wild-type strain (termed as resulted in a growth reduction when compared to wild-type cells carrying an (termed In when we created a strain with a similar that the tRNAArgUCU gene, as a growth to that of was observed (Figure findings are with the evolutionary for yeast to keep a low copy number of tRNAArgCCU and that a high copy number of such tRNAs is to Figure 4 with 3 supplements see all Download asset Open asset a growth defect compared to and demonstrates higher levels of proteins. (A) Growth curve measurements of and are shown in optical density (OD) values over time during continuous growth. The strain carrying a high copy number tRNAArgCCU demonstrates slower growth compared to cells with an or with a tRNAArgUCU that is mainly by a growth (B) A of a cell in which the proteins with a phenotype when the protein quality control machinery is with proteins. (C) A cell in which the quality control machinery is not with other is to the and were with a containing and under the cells per strain were for or of the protein. The fold change in the number of cells containing was then by to the The is The mRNA fold change of genes by values are the mean of two biological The of the fold change differences was examined a with or To demonstrate the generality of our we the same in two we examined 2 serine tRNAs, the singleton and that is found in the genome in 11