Evolution of Eukaryotic Translation Elongation and Termination Factors: Variations of Evolutionary Rate and Genetic Code Deviations

David Moreira, Stéphanie Kervestin, Olivier Jean-Jean and Hervé Philippe

Phylogénie, Bioinformatique et Génome, UMR 7622 CNRS and
Unité de Biochimie Cellulaire, UMR 7098 CNRS, Université Pierre et Marie Curie, 9, quai St Bernard 75005, Paris, France


    Abstract
 TOP
 Abstract
 Introduction
 Material and Methods
 Results
 Discussion
 Acknowledgements
 References
 
Translation is carried out by the ribosome and several associated protein factors through three consecutive steps: initiation, elongation, and termination. Termination remains the least understood of them, partly because of the nonuniversality of the factors involved. To get some insights on the evolution of eukaryotic translation termination, we have compared the phylogeny of the release factors eRF1 and eRF3 to that of the elongation factors EF-1{alpha} and EF-2, with special focus on ciliates. Our results show that these four translation proteins have experienced different modes of evolution. This is especially evident for the EF-1{alpha}, EF-2, and eRF1 ciliate sequences. Ciliates appear as monophyletic in the EF-2 phylogenetic tree but not in the EF-1{alpha} and eRF1 phylogenetic trees. This seems to be mainly because of phylogeny reconstruction artifacts (the long-branch attraction) produced by the acceleration of evolutionary rate of ciliate EF-1{alpha} and eRF1 sequences. Interaction with the highly divergent actin found in ciliates, or on the contrary, loss of interaction, could explain the acceleration of the evolutionary rate of the EF-1{alpha} sequences. In the case of ciliate eRF1 sequences, their unusually high evolutionary rate may be related to the deviations in the genetic code usage found in diverse ciliates. These deviations involve a relaxation (or even abolition) of the recognition of one or two stop codons by eRF1. To achieve this, structural changes in eRF1 are needed, and this may affect its evolutionary rate. Eukaryotic translation seems to have followed a mosaic evolution, with its different elements governed by different selective pressures. However, a correlation analysis shows that, beneath the disagreement shown by the different translation proteins, their concerted evolution can still be made apparent when they are compared with other proteins that are not involved in translation.


    Introduction
 TOP
 Abstract
 Introduction
 Material and Methods
 Results
 Discussion
 Acknowledgements
 References
 
Translation is the final step of the conversion of genetic information into proteins. Ribosomes are the site of protein synthesis, and they require the activity of several initiation, elongation, and termination factors for a proper function. The overall process is well understood, yet important questions concerning both the mechanism and evolution of termination remain open. Termination of protein synthesis occurs when the translation machinery encounters an in-frame stop codon on the mRNA. Hydrolysis of the ester bond linking the polypeptide chain and the last tRNA is triggered by the peptidyl transferase center of the ribosome and requires specific release factors (RFs) and GTP (Kisselev and Buckingham 2000Citation ). In eukaryotes, the release factor 1 (eRF1) recognizes stop codons and promotes the activation of the peptidyl transferase center, leading to the delivery of the nascent polypeptide (Frolova et al. 1994Citation ). Eukaryotic release factor 3 (eRF3) is a GTPase that enhances eRF1 activity (Zhouravleva et al. 1995Citation ). In this mechanism, eRF1 binds to the ribosomal A-site and functionally acts as a tRNA. The crystal structure of human eRF1 confirms that eRF1 displays structural similarities to tRNA molecule (Song et al. 2000Citation ). This release factor is organized into three distinct domains for which different functions have been proposed: the N-terminal domain, as responsible for stop-codon recognition, the middle domain, as responsible for the activation of the peptidyl transferase center, and the C-terminal domain, as responsible for the binding to eRF3 and other eRF1-interacting proteins. It has also been suggested that the GGQ motif at the tip of the middle domain triggers the hydrolytic activity of the peptidyl transferase center (Song et al. 2000Citation ). This motif is remarkably conserved in all eukaryotic and archaeal RF1 sequenced so far, as well as in bacterial release factors RF1 and RF2, despite the absence of conservation of the other regions of these proteins (see later). In addition, a highly conserved NIKS motif located at the tip of the N-terminal domain was supposed to be involved in the anticodon-like site (Song et al. 2000Citation ).

However, despite being essential for life, translation termination is not evolutionarily conserved because the bacterial release factors RF1 (which recognizes the stop codons UAA and UAG) and RF2 (which recognizes the stop codons UAA and UGA) are very dissimilar, perhaps even nonhomologous, to the eukaryotic factor eRF1 (which recognizes all three stop codons). Archaea possess a single release factor (aRF1), which is homologous to the eukaryotic eRF1. Important differences are also found in the GTPase factors RF3 and eRF3, used by bacteria and eukaryotes, respectively, for translation termination. The bacterial RF3 is very similar to the elongation factor EF-G (the homolog of the eukaryotic EF-2), whereas the eukaryotic eRF3 is more similar to the elongation factor EF-1{alpha} (the homolog of the bacterial EF-Tu). Therefore, despite being homologous between them and with the elongation factors, EF-G and EF-2, and EF-Tu and EF-1{alpha}, RF3 and eRF3 are not orthologous. Moreover, no RF3 or eRF3 homologue has been recognized in Archaea. Animals and yeast contain an additional factor, HBS1, which is close to eRF3 (Garcia-Cantalejo et al. 1994Citation ) but perhaps not involved in translation termination (Wallrapp et al. 1998Citation ). This surprising diversity at the molecular level reveals the complexity of the evolutionary history of translation termination.

Deviations from the universal genetic code bring up a further level of complexity. In fact, the genetic code, although probably frozen at the time of the last common ancestor of living organisms (Freeland et al. 2000Citation ) and therefore almost identical in all species, shows some variations. These likely occur through codon reassignment (also known as codon capture), which was initially found in mitochondria and afterwards in bacteria and in the nuclear genome of eukaryotes (Caron and Meyer 1985Citation ; Osawa and Jukes 1989Citation ; Jukes and Osawa 1997Citation ). Among eukaryotes, ciliates show one of the most remarkable examples of codon reassignment. In several species, the stop codons UAA and UAG are translated into glutamine (Caron and Meyer 1985Citation ), whereas in the hypotrich genus Euplotes the glutamine codon usage is normal but the stop codon UGA is translated as cysteine (Harper and Jahn 1989Citation ). The distribution of these changes on the ciliate phylogenetic tree, constructed using 28S ribosomal RNA (rRNA) sequences, suggested that they have occurred independently several times within this phylum (Tourancheau et al. 1995Citation ). The discovery of a similar deviation (i.e., the translation of the stop codons UAA and UAG into glutamine) in several species of an independent phylum, the diplomonads (Keeling and Doolittle 1997Citation ), also supports the idea of a relative ease for nuclear code variation. An intriguing question is the reason behind this ease for genetic code changes in ciliates. Nevertheless, concerning the mechanism of codon reassignment, it must result from a complex interplay between tRNA and eRF1. It has been shown both in vivo and in vitro that eRF1 competes with nonsense suppressor tRNAs for the recognition of stop codons (Drugeon et al. 1997Citation ; Le Goff, Philippe, and Jean-Jean 1997Citation ). Nonsense suppressor tRNAs are altered tRNAs which are mutated in their anticodon and can suppress translational termination at stop codons. However, one cannot know with confidence which one appeared first, nonsense suppressor tRNAs or modified eRF1.

To get insights on the evolution of translation, we have studied the phylogeny of the eukaryotic elongation factors EF-1{alpha} and EF-2 and the release factors eRF1 and eRF3. These proteins develop their principal activity in a similar molecular environment (the A-site of the ribosome). In particular, to examine the impact that codon reassignment could have had on the evolution of RFs, we have focused on the ciliates. For this purpose, new ciliate sequences have been determined for the release factor eRF1 and for the elongation factor EF-2. In addition, new eRF1, eRF3, and HBS1 sequences have been retrieved from publicly available expressed tag sequences and complete genome ongoing sequencing projects. Our results show that the different proteins yield dissimilar trees, especially for the ciliates, probably because of important differences of evolutionary rate. We advance the hypothesis that accelerated evolutionary rates may be explained by the effect of genetic code deviation in the case of the eRF1 and by the interaction (or even lack of interaction) with proteins not involved in translation (in particular cytoskeletal proteins) in the case of the EF-1{alpha}. This suggests that the translation machinery, albeit being one of the most integrated cellular systems, has experienced a mosaic evolution characterized by a non–completely concerted evolution of its different proteins.


    Material and Methods
 TOP
 Abstract
 Introduction
 Material and Methods
 Results
 Discussion
 Acknowledgements
 References
 
Sequencing of EF-2 and eRF1 Genes
Genomic DNA from the ciliate species Euplotes aediculatus, Naxella sp., Spathidium sp., and Stentor coeruleus was purified using agarose inclusions (Moreira 1998Citation ), and the respective EF-2 genes were amplified by PCR using specific primers (Yamamoto et al. 1997Citation ; Moreira, Le Guyader, and Philippe 2000Citation ).

The E. aediculatus, Paramecium tetraurelia, and Trypanosoma brucei eRF1 genes were isolated from genomic DNA libraries. The E. aediculatus library was kindly provided by Anne Baroin-Tourancheau (Université Paris-Sud), and the P. tetraurelia genomic DNA library was kindly provided by Eric Meyer (Ecole Normale Superieure, Paris). The probe used for libraries screening, a generous gift of Yoshikazu Nakamura (University of Tokyo), was a 900-pb EcoRI restriction fragment of a pUC118 plasmid derivative containing the 3'-region of the T. thermophila eRF1 cDNA (Karamyshev et al. 1999Citation ). The plasmid containing the complete coding sequence of the eRF1 gene from T. brucei, clone 49I14 from the T. brucei-shared DNA library, was generously donated by Najib M. El-Sayed (The Institute for Genomic Research, USA). Library screening and DNA engineering were carried out using standard protocols (Sambrook, Fritsch, and Maniatis 1989Citation ). Phage plaques transferred on Hybond N+ filters (Amersham-Pharmacia Biotechnology) were screened by hybridization with the T. thermophila eRF1 cDNA probe labeled with a random priming kit (Boehringer Mannheim). Hybridization at nonstringent conditions was carried out for 1 h at 60°C, followed by slow cooling to 30°C and washing in 2x standard saline citrate (0.3 M NaCl, 30 mM sodium citrate)-0.1% sodium dodecyl sulfate at 35°C. Fragments of positive phage inserts were cloned in pBluescript II SK+ plasmid (Stratagene).

The entire nucleotide sequence of the EF-2 PCR products and the selected fragments from the genomic DNA libraries, as well as the insert of clone 49I14 from T. brucei, was carried out on both strands by chromosome walking using the dideoxy chain termination method (Sanger, Nicklen, and Coulson 1977Citation ).

Sequences have been submitted to the GenBank Nucleotide Sequence Database (accession numbers AF149035, AF149036, AF278718, AF334757).

Identification of eRF1, eRF3, and HBS1 Genes in Databases
EF-1{alpha}, EF-2, eRF1, eRF3, and HBS1 sequences were identified through BLAST searches (Altschul and Koonin 1998Citation ) and retrieved from GenBank. Complete genome- and expressed tags-sequencing projects were also examined, which allowed retrieving the Entamoeba histolytica eRF1 sequence from the TIGR database (at http://www.tigr.org) and the aRF1 sequences from Methanosarcina barkeri and Ferroplasma acidarmanus from the JGI database (at http://www.jgi.doe.gov).

Phylogenetic Analyses
Sequences retrieved from data banks were aligned, together with the new sequences determined in this study, using CLUSTALW (Thompson, Higgins, and Gibson 1994Citation ), and the resulting multiple alignments were manually edited using the program ED from the MUST package (Philippe 1993Citation ). Ambiguously aligned positions were excluded from our analyses. Maximum likelihood (ML) trees were constructed with the program PROTML from the MOLPHY 2.3 package, using the quick search option and the JTT substitution model (options -jf -q -n 1,000) (Adachi and Hasegawa 1996Citation ). Branch lengths were recalculated on the best topology with the program PUZZLE (Strimmer and von Haeseler 1996Citation ) using a {Gamma}-law to correct for among-site rate variation. Bootstrap proportions were estimated using the RELL method (Kishino, Miyata, and Hasegawa 1990Citation ) upon the 1,000 top-ranking trees. Different tree topologies were statistically compared using the Kishino-Hasegawa (Kishino and Hasegawa 1989Citation ) and Shimodaira-Hasegawa (Shimodaira and Hasegawa 1999Citation ) tests with the programs PROTML (Adachi and Hasegawa 1996Citation ), PUZZLE (Strimmer and von Haeseler 1996Citation ), and CONSEL (http://www.ism.ac.jp/~shimo/). Frequencies of codon usage were obtained from the Codon Usage Database (Nakamura, Gojobori, and Ikemura 2000Citation ). Alignments and trees are available upon request.

Comparison of Evolutionary Rates
To investigate the possible factors leading to the incongruence observed for the topologies of the different phylogenetic trees, we have carried out a comparative analysis of the evolutionary rates of the proteins under study. For this purpose, each possible pair of proteins has been compared. For each protein, the number of substitutions for each species on a constrained phylogenetic tree was inferred by the ML method using the program PUZZLE (Strimmer and von Haeseler 1996Citation ) with a {Gamma}-law to address among-site rate variation. The constrained phylogenetic tree used was a conservative consensus of what we presently think about eukaryotic evolution (Philippe, Germot, and Moreira 2000Citation ). This tree, in parenthesized format, was as follows: (((Schizosaccharomyces, (Saccharomyces, Candida)), ((Caenorhabditis, Drosophila), Homo)), ((((((Tetrahymena, Paramecium), (Oxytricha, Euplotes)), Plasmodium), (Arabidopsis, Chlamydomonas)), (Leishmania, Trypanosoma)), (Entamoeba, Dictyostelium)), Giardia). For most data sets all the species were available, but when individual species were absent, comparisons were carried out only with the species common to the two data sets compared. For each protein-protein comparison, the number of substitutions inferred for the first protein was plotted against the number of substitutions inferred for the second protein. The dispersion of the cloud of points thus obtained, i.e., the degree of correlation, indicates whether the evolutionary rates of the two proteins have similar behaviors.


    Results
 TOP
 Abstract
 Introduction
 Material and Methods
 Results
 Discussion
 Acknowledgements
 References
 
Elongation- and Release-Factor Sequences
The molecular phylogeny of the elongation factor EF-1{alpha} has been profusely discussed, in particular in the case of ciliates, for which an extensive taxonomic sampling was already available (Moreira, Le Guyader, and Philippe 1999Citation ; Roger et al. 1999Citation ). On the contrary, only two ciliate EF-2 sequences were available, from the hypotrich Stylonychia mytilus and the oligohymenophorean Tetrahymena pyriformis (Moreira, Le Guyader, and Philippe 2000Citation ). To enrich the taxonomic sampling for this elongation factor, we have determined four new ciliate sequences, from the hypotrich E. aediculatus, the nassophorean Naxella sp., the litostomatean Spathidium sp., and the heterotrich S. coeruleus. Introns are found in two ciliate EF-2 coding sequences, E. aediculatus and T. pyriformis, in contrast with the ciliate EF-1{alpha} coding sequences, which show a complete absence of these genetic elements (Moreira, Le Guyader, and Philippe 1999Citation ). The presence of introns within these EF-2 coding sequences was suggested by the occurrence of frameshifts and verified by multiple sequence alignment, which revealed the existence of intervening sequences at the points of frameshift, flanked by the consensus intron end sequences (GT and AG). Two introns were thus found in the EF-2 gene sequence from E. aediculatus, and one in the EF-2 gene from T. pyriformis. This T. pyriformis intron was very AT-rich (78.9%), in contrast with the two E. aediculatus introns (51.7% and 58.8% AT). Interestingly, introns mapped at different locations in both species, which suggest either an independent acquisition or a high mobility. Two introns are also present in each one of the two P. tetraurelia eRF1 genes, but they are absent from the E. aediculatus gene. The positions of the two P. tetraurelia introns are not conserved with respect to those of other ciliate eRF1 introns (not shown).

Whereas only a single copy of the EF-2 gene could be retrieved for all the ciliate species studied here, multiple independent duplications of the ciliate EF-1{alpha} genes have been reported (Moreira, Le Guyader, and Philippe 1999Citation ). This seems also to be the case for the eRF1 genes because two different gene copies were retrieved at least in the oligohymenophorean P. tetraurelia and in the hypotrichs Euplotes octocarinatus (Liang et al. 2001Citation ) and E. aediculatus (fig. 1 ). The topology of the eRF1 phylogenetic tree strongly suggests independent duplication events at the origin of these multiple copies. In the case of P. tetraurelia, the duplication seems to have occurred very recently because both copies show a reduced degree of divergence (98% of amino acid identity). Finally, database searches have allowed the recognition of HBS1 sequences in the kinetoplastid species Leishmania major and T. brucei, the alveolate Cryptosporidium parvum (partial sequence of 140 amino acids), the mycetozoan Dictyostelium discoideum (partial sequence of 247 amino acids), and the plants Arabidopsis thaliana and Oryza sativa. Therefore, the hypothesis that the duplication that gave rise to HBS1 was unique to metazoans and fungi (Philippe, Germot, and Moreira 2000Citation ) is no longer valid.



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Fig. 1.—ML phylogenetic tree for ciliate eRF1 sequences (417 positions), rooted on the apicomplexan P. falciparum. Numbers close to nodes are ML bootstrap proportions. The scale bar corresponds to 10 substitutions per 100 positions for a unit branch length

 
Phylogenetic Analyses
We have carried out a ML phylogenetic analysis of the ciliate eRF1 sequences, rooted on the apicomplexan P. falciparum (fig. 1 ). This analysis illustrates the strong differences of evolutionary rate found among the ciliate sequences and in particular, the extreme rate acceleration of the P. tetraurelia sequences (fig. 1 ). In addition, all ciliates exhibit much longer branches than that of the outgroup, indicating a general acceleration of the eRF1 evolutionary rate for this phylum. Nevertheless, the two ciliate classes represented by several species (oligohymenophoreans and hypotrichs) are monophyletic, but the relationships between them and the third class (heterotrichs) are not well supported.

We have compared the global eRF1 eukaryotic phylogeny with those based on other translation proteins, EF-1{alpha}, EF-2, and eRF3, using for all of them ML reconstruction methods and a similar taxonomic sampling to facilitate our comparative purposes. As previously reported, the EF-1{alpha} sequences yield a tree (fig. 2A ) characterized by the polyphyletic and early emergence of several ciliate sequences (Moreira, Le Guyader, and Philippe 1999Citation ). Even the monophyly of ciliate subgroups, such as the hypotrichs (E. aediculatus and S. mytilus), is not found. The tree shows a weak statistical support for its central part (containing most of the ciliate sequences), with bootstrap proportions (BP) ranging from 4% to 69%. This is especially true taking into account that these BP were calculated with the RELL method (Kishino, Miyata, and Hasegawa 1990Citation ), which tends to overestimate the statistical support. High BP are only found for the most basal (early emergence of Giardia intestinalis, BP of 99%) and apical (sisterhood of metazoans and fungi, BP of 96%) branches of the tree. The instability of the central, ciliate-containing part of the tree is further revealed by the different topologies obtained by applying other methods of phylogenetic reconstruction (neighbor-joining and maximum parsimony, not shown).



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Fig. 2.—ML phylogenetic trees for the elongation factors EF-1{alpha} (A, 362 positions) and EF-2 (B, 634 positions) and the release factors eRF1 (C, 346 positions) and RF3 (D, 341 positions). All trees are rooted on archaeal homologous sequences, except the RF3 tree, which is rooted on eukaryotic RFS sequences. Ciliate species names are in bold. Numbers close to nodes are ML bootstrap proportions. Scale bars correspond to 10 substitutions per 100 positions for a unit branch length

 
The elongation factor EF-2 sequences produce a very different tree (fig. 2B ), with only one early-emerging branch (corresponding to G. intestinalis). The monophyly of ciliates is retrieved with high BP (98%), and moreover, their expected sisterhood with apicomplexans (P. falciparum and C. parvum) is supported by a BP of 82%. Other well-established phylogenetic relationships, such as the sisterhood of metazoans and fungi (BP of 96%), are also well supported. Most nodes in the tree, therefore, show BP values >50%, in sharp contrast with the EF-1{alpha} phylogenetic tree. This is not unexpected because the EF-2 sequences are longer than the EF-1{alpha} sequences (634 vs. 362 positions).

Interestingly, the phylogenetic tree constructed upon the release factor eRF1 sequences rooted with archaeal outgroup sequences displays a picture parallel to that shown by the EF-1{alpha} tree. The eRF1 phylogenetic tree shows a paraphyletic emergence of ciliate sequences in the basal region of the tree (fig. 2C ). Most BP, except for the monophyly of certain groups (such as metazoans, green plants, or kinetoplastids) are very weak, ranging between 13% and 55%. These low BP values suggest a high instability for the ciliate phylogeny obtained with both the EF-1{alpha} and eRF1 sequences. To test this possibility, we carried out statistical comparisons, taking or not into account among-site rate variation with a {Gamma}-law, of the best ML trees with trees where the monophyly of alveolates were imposed (see Material and Methods). The EF-1{alpha} significantly rejected the monophyly of alveolates, whereas the eRF1 rejected it only when the {Gamma}-law was not applied (not shown). In contrast with the EF-1{alpha} and eRF1, most nodes throughout eRF3 tree show high BP values (fig. 2D ). The only two ciliate eRF3 sequences available (the hypotrich species E. aediculatus and Oxytricha trifallax) are monophyletic. However, the poor ciliate taxonomic sampling for this gene renders the comparison with other phylogenetic markers less significant. In fact, these two ciliate species are also monophyletic in the eRF1 tree.

Sequence length can be an important factor for phylogenetic reconstruction. In fact, the results obtained using the longest marker (EF-2, with ~650 amino acids) seem to be better than those yielded by the shortest markers (EF-1{alpha} and eRF1, with ~350 amino acids). To test the possible influence of sequence length, we have constructed an additional phylogenetic tree using a fusion of EF-1{alpha} + eRF1 (756 amino acids, fig. 3 ). A general increase in the BP for most nodes with respect to the values obtained in the individual analyses is observed, but the resulting tree still shows an artifactual polyphyly of the ciliate sequences, as in the case of the individual analyses of both markers.



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Fig. 3.—ML phylogenetic tree for a fusion of EF-1{alpha} and eRF1 sequences (772 positions). Ciliate species names are in bold. Blepharisma sp. corresponds to the fusion of the B. japonicum EF-1{alpha} and the B. americanum eRF1 sequences. Numbers close to nodes are ML bootstrap proportions. The scale bar corresponds to 10 substitutions per 100 positions for a unit branch length

 
Comparison of Evolutionary Rates
We compared the evolutionary rates of the four proteins to know whether the incongruences observed among the different trees were caused by dissimilar evolutionary rates and thus by long-branch attraction artifacts (LBA). A cloud of points was obtained for each possible pair of markers (proteins or rRNA), where points represent, for a given branch, the number of substitutions inferred by ML for the first marker versus the number of substitutions inferred for the second marker (fig. 4 ). If the cloud of points is close to the regression line, this indicates that the two proteins have undergone the same relative acceleration and deceleration of their evolutionary rates on all the branches of the tree, even if one of the proteins evolves faster than the other. Despite the dissimilar shapes of the phylogenetic trees based on markers involved in translation (EF-1{alpha}, EF-2, eRF1 and rRNA), their correlation coefficients were very high (between 0.88 and 0.95). However, this was partly caused by the strong effect of the common long branch of G. intestinalis (see fig. 2 ) because when this species was not taken into account (i.e., when the points corresponding to this species are ignored in the calculations), the correlation coefficients dropped down from 0.95 to 0.86 (EF-1{alpha} vs. EF-2) or from 0.90 to 0.65 (EF-1{alpha} vs. eRF1). We analyzed the effect of other individual species in a similar way, but none of them produced such marked results (not shown). Despite their different roles during translation, elongation factors were well correlated with RFs. This high correlation could be because of the fact that they bind to the same site on the ribosome. The fact that these translation factors were also well correlated with the 18S rRNA suggests that this correlation is a general trend of all components involved in translation, which constitutes a single functional unit. As a result, the phylogenies based on genes involved in translation are globally congruent, though with some notable exceptions (e.g., open squares on fig. 4 , corresponding to ciliate sequences).



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Fig. 4.—Correlation analysis of the evolutionary rates of different proteins. Each panel represents a pairwise comparison of the number of substitutions inferred for one of the proteins plotted against the number of substitutions inferred for the other protein for each one of the species studied. Solid triangles correspond to E. hystolytica, solid squares correspond to G. intestinalis, open diamonds correspond to ciliates, and solid points correspond to other species. The box on the right upper corner shows the correlation analyses between each of the three domains of eRF1. The N-, M- and C-domains correspond to amino acids 1–142, 143–266, and 267–437 of the human eRF1. Numbers are the values of the correlation coefficient R. RF3 was not included in this analysis because of the lack of an adequate taxonomic sampling

 
We carried out a similar analysis with other phylogenetic markers (fig. 4 ). The cytosolic chaperon HSP70, which is indirectly involved in the process of protein synthesis, shows correlation coefficient values ranging between 0.88 and 0.92 (between 0.60 and 0.68 in the absence of the Giardia sequences) when compared with the EF-1{alpha}, EF-2, and eRF1. Interestingly, when these elongation factors and RFs were compared with proteins not related to translation, the correlation coefficient values were generally much lower: between 0.80 and 0.86 for actin (0.53–0.56 without Giardia), between 0.30 and 0.47 for {alpha}-tubulin (0.35–0.54 without Giardia), between 0.33 and 0.53 for ß-tubulin (0.28–0.68 without Giardia), and between 0.46 and 0.59 for {gamma}-tubulin (0.12–0.43 without Giardia). These values are in good agreement with the topologies shown by the trees based on cytoskeletal proteins, which are different from those based on translation proteins (Philippe and Adoutte 1998Citation ; Philippe et al. 2000Citation ). Actin may represent an exception, but its good correlation with some translation proteins, specially the EF-1{alpha}, is rather caused by the common presence of several long branches (e.g., Giardia and several ciliates).

Among the translation-related proteins analyzed in this work, the most important differences of evolutionary rate occurred for the eRF1 sequences, for which several ciliates showed very high evolutionary rates (figs. 1 and 4 ). To investigate whether these differences of evolutionary rate observed for the complete eRF1 sequences specially affect a particular domain of this protein, we have carried out a correlation analysis of its three domains independently. Evolutionary rates for each of these domains are well correlated with the two other ones, despite the few numbers of amino acid positions used (between ~120 and ~150) (see the box in fig. 4 ). Correlation coefficient values were of 0.97, 0.98, and 0.97 for the N-terminal, middle, and C-terminal eRF1 domain versus the complete eRF1 sequence, respectively. As in the previous cases, the long branch of G. intestinalis was partially responsible for these high values, although correlation was still high when this species was not taken into account (correlation coefficient values of 0.93, 0.92, and 0.88). All these data indicate that the variation of evolutionary rate has affected all the domains of the eRF1 and not particularly that involved in stop-codon recognition.


    Discussion
 TOP
 Abstract
 Introduction
 Material and Methods
 Results
 Discussion
 Acknowledgements
 References
 
Mosaic Evolution of Translation in Eukaryotes
As shown above, the phylogenetic trees constructed upon the different translation protein sequences display important differences, especially for the ciliate clade, which appears monophyletic in the EF-2 and eRF3 (although only two ciliate sequences are available for eRF3) trees but nonmonophyletic in the EF-1{alpha} and eRF1 trees (fig. 2 ). This indicates that these proteins have followed different modes and tempos of evolution, despite their involvement in a common process. This result may be especially surprising considering that despite their interactions with other molecules these proteins develop their main activity in a same molecular environment, the A-site of the ribosome. The differences observed in the phylogenetic trees can be caused by phylogenetic reconstruction artifacts or by problems of lateral gene transfer or hidden paralogy (or both). However, these two problems appear unlikely because eukaryote-to-eukaryote lateral gene transfer seems uncommon and because explaining all abnormal phylogenetic trees (e.g., EF-1{alpha} and eRF1) by the existence of unrecognized paralogs would imply that the ancestral eukaryote should possess a gene complement larger than that found in any contemporary species. On the other hand, reconstruction artifacts may be caused by two classes of phenomena: stochastic error and systematic error (Swofford et al. 1996Citation ). To minimize the first one, which could be important because of the relative small length of the EF-1{alpha} and eRF1 sequences (~350 positions), we have fused both proteins, but the statistical support for the nonmonophyly of ciliates was increased (fig. 3 ). This strongly suggests that the discrepancies are caused by systematic error, in this case, the unequal evolutionary rates among species. This leads to the well-known LBA, which produces an artificial regrouping of the fast-evolving sequences (Felsenstein 1978Citation ) and often, their misplacement toward the base of the phylogenetic tree when distant outgroup sequences are used (Philippe et al. 2000Citation ).

Ciliates offer an excellent example of how these problems can distort phylogenetic reconstruction. Despite the fact that the monophyly of this group is solidly supported both by structural and molecular data (Corliss 1975Citation ; Hammerschmidt et al. 1996Citation ; Budin and Philippe 1998Citation ), it is not retrieved using EF-1{alpha} or eRF1 sequences (or both) as phylogenetic markers (fig. 2 ). For both proteins, ciliates show an accelerated evolutionary rate (i.e., long branches) leading to LBA artifacts. In addition, not all ciliate species show the same degree of acceleration, with some of them showing a faster evolutionary rate (e.g., E. aediculatus and Spathidium sp. for the EF-1{alpha} and P. tetraurelia for the eRF1), which further makes it difficult to retrieve their monophyly. Statistical analyses of the EF-1{alpha} and eRF1 sequences showed that the monophyly of alveolates was significantly rejected. However, for the eRF1, the monophyly of alveolates was no longer rejected when among-site rate variation was taken into account. Similarly, for the EF-1{alpha}, we have previously shown that the same phenomenon was observed when a larger sampling of ciliate sequences was included in the analysis (Moreira, Le Guyader, and Philippe 1999Citation ). Both approaches (improved model of sequence evolution and large number of species) are known to reduce the impact of LBA artifact (Philippe and Laurent 1998Citation ). This further supports the idea that the ciliate polyphyly shown by both markers is caused by tree reconstruction artifacts.

Ciliate EF-2 sequences are also slightly accelerated with respect to their closest relatives (the apicomplexans P. falciparum and C. parvum), but their evolutionary rates are more homogeneous than those of ciliate EF-1{alpha} and eRF1 sequences (fig. 2B ). LBA does not necessarily misplace the fast-evolving sequences toward the base of the phylogenetic trees because it can cluster the long branches of fast-evolving species together rather than the long branch of the outgroup. An example can be found in the eRF1 tree, which shows a grouping of sequences with long branches (L. major, T. brucei, G. intestinalis, and E. histolytica) in the apical region of the tree (fig. 2C ).

It has been recently speculated, on the basis of eRF1 and eRF3 phylogenetic analyses, that Giardia may represent a basal branch and therefore an ancient eukaryotic genus (Inagaki and Doolittle 2000Citation ). However, the basal position of G. intestinalis is no longer supported after the addition of new eRF1 sequences (in particular six ciliates and four other protists) (fig. 1 ). The addition of new sequences is known to be a powerful method to alleviate the effects of LBA (Hendy and Penny 1989Citation ). Therefore, the change in the position of G. intestinalis subsequent to the increase of the number of sequences suggests that its previous basal emergence in the eRF1 tree could be because of an LBA artifact. A similar case is shown by the EF-2 phylogeny because an exhaustive ML analysis of a more extensive taxonomic sampling does not support the basal position of this species (Moreira, Le Guyader, and Philippe 2000Citation ). In this sense, the poor taxonomic sampling of protist species available for the eRF3 makes uncertain the robustness of the basal position of G. intestinalis for this marker (fig. 1D ). The phylogenetic placement of this species remains elusive.

The differences of evolutionary rate among the different translation proteins may be related to changes in their mode of evolution in specific groups, such as the ciliates, resulting from changes of the selective constraints. As discussed in a previous work (Moreira, Le Guyader, and Philippe 1999Citation ), the acceleration of the ciliate EF-1{alpha} may be caused by changes in its interactions with cytoskeletal proteins, in particular actin. In fact, EF-1{alpha} interacts both with actin and tubulins in most eukaryotes (Yang et al. 1990Citation ; Shiina et al. 1994Citation ; Nakazawa et al. 1999Citation ). Tubulins are highly conserved in ciliates, contrary to actin, which is extremely variable because its function has been reduced to food vacuole formation only (Cohen, Garreau de Loubresse, and Beisson 1984Citation ). The phylogenetic analysis of eukaryotic actin yields a tree showing a polyphyletic and basal emergence of ciliates, as in the EF-1{alpha} tree (Philippe and Adoutte 1998Citation ). The acceleration of the evolutionary rate of ciliate EF-1{alpha} may have been produced either by its coevolution with the extremely fast-evolving actin or even by the loss of the interactions with this cytoskeletal protein. The fact that actin-binding domains are very divergent in ciliate EF-1{alpha} sequences supports this hypothesis (Moreira, Le Guyader, and Philippe 1999Citation ).

The correlation analysis carried out incorporating proteins not involved in translation suggests that despite the important differences observed, a concerted evolution of the elements of the translation machinery can still be detected. The correlation coefficient values obtained from the pairwise comparisons between the translation proteins were notably higher than those observed in the comparisons involving the other proteins. This conforms to the idea that proteins that interact show similar evolutionary tempos, regardless of whether they share a main function or not. An example is found in the concerted acceleration of the ciliate EF-1{alpha} and actin sequences (Moreira, Le Guyader, and Philippe 1999Citation ). Conversely, actin and tubulins show very weak correlation coefficient values (0.05, 0.11, and 0.34 for actin vs. {alpha}-, ß- and {gamma}-tubulin, respectively), despite the fact that all these proteins are involved in cytoskeletal function.

High Evolutionary Rate of Ciliate eRF1
The phylogenetic analysis of eRF1 sequences shown in figure 2C reveals two interesting features: the absence of monophyly of the ciliates and the very high evolutionary rate of Paramecium. To date, the only role attributed to eRF1 is its function in the translation termination process (Kisselev and Buckingham 2000Citation ). For two vertebrate species (Homo sapiens and Xenopus laevis) it has been established that the eRF1 recognizes all the three stop codons and activates the peptidyl transferase center of the ribosome, leading to the release of the polypeptide chain (Frolova et al. 1994Citation ). In some ciliate species, the codon usage differs from the universal genetic code in that one or two of the stop codons were reattributed. Thus, UAA and UAG encode glutamine in Tetrahymena, Paramecium, Stylonychia and Oxytricha, whereas UGA encodes cysteine in Euplotes species (Caron and Meyer 1985Citation ; Horowitz and Gorovsky 1985Citation ; Meyer et al. 1991Citation ) and tryptophan in Blepharisma americanum (Lozupone, Knight, and Landweber 2001Citation ). Because translation termination entails a competition between nonsense suppressor tRNAs and eRF1 in the ribosomal A-site, it seems clear now that the use of stop codons as sense codons involves changes in tRNAs and probably in the ability of eRF1 to recognize stop codons. Supporting this view, various situations are observed in ciliates concerning the tRNAs able to decode stop codons. In T. thermophila, two specific tRNAGln isoacceptors implicated in the decoding of UAA and UAG have been isolated (Kuchino et al. 1985Citation ). In E. octocarinatus, only one gene coding for the canonical tRNACys with GCA anticodon has been found in its macronuclear genome, and it has been suggested that this tRNACysGCA is responsible for the decoding of UGA in addition to the normal UGU- and UGC-cysteine codons (Grimm et al. 1998Citation ). Moreover, it has been recently shown that eRF1 from E. aediculatus does not recognize UGA codon, which supports the hypothesis that in all ciliates using variant genetic codes the eRF1 does not respond to reassigned stop codons (Kervestin et al. 2001Citation ). Thus, it is tempting to speculate that, in these organisms, the numerous modifications of the eRF1 amino acid sequence are responsible for the pattern of stop-codon recognition, and that the variable evolutionary rates of eRF1 in ciliates may be related to these modifications.

In their phylogenetic analysis, Tourancheau et al. (1995)Citation , show evidence that genetic code changes in ciliates were caused by several independent events. These events could have consisted of a minor change in one of the tRNAs, such as a single mutation at the third base of the anticodon. Note that, in Euplotes, the only increase in the abundance of the canonical tRNACysGCA could have been sufficient for decoding UGA. Thus, it is easily conceivable that tRNAs able to decode stop codons appeared first in some ciliate species. As these tRNAs are in competition with the eRF1 for stop-codon recognition, probably only a small fraction of stop codons were decoded as sense codons, thus minimizing the potentially deleterious effect of the modification of the termination site. In addition, ciliates have short, A-T rich, 3' untranslated regions that also reduces the consequences of stop codon readthrough. We assume then that the accumulation of discrete changes across the entire eRF1 sequence induced a progressive decrease in the accuracy of eRF1 to recognize one or two of the stop codons and thus expanded the use of the reassigned stop codons in the coding sequences. This progressive loss of eRF1 ability to respond to some stop codons could explain why the accelerated eRF1 evolutionary rate is supported by the entire sequence.

In a recent study on ciliate eRF1 amino acid sequences, Lozupone, Knight, and Landweber (2001)Citation have proposed that a few amino acid substitutions at specific positions of the eRF1 N-terminal domain may be at the basis of genetic code change in ciliates. Our results are not in favor of the hypothesis that eRF1 abruptly lose its ability to recognize one of the stop codons. Indeed, this hypothesis is hardly reconcilable with the observed variations in eRF1 evolutionary rate, particularly because the evolutionary rates of the three domains of eRF1 appear well correlated between themselves (see the box in fig. 4 ).

As suggested previously, a consequence of the progressive loss of eRF1 activity is an increase in the use of stop codons as sense codons. For Tetrahymena, Paramecium, and Oxytricha species, we have estimated the frequency of use of reattributed UAA and UAG codons and canonical CAA- and CAG-glutamine codons using data from the Codon Usage Database (Nakamura, Gojobori, and Ikemura 2000Citation ). Because of the low number of sequences available for individual ciliate species and assuming that the evolutionary rate of eRF1 is constant in a genus, we have calculated the ratio UAG + UAA/CAG + CAA + UAG + UAA for each genus (Tetrahymena, Paramecium, and Oxytricha). This ratio, expressed as a percentage, was 42.3% for Oxytricha, 54.7% for Tetrahymena, and 68.7% for Paramecium. These values can be compared to the evolutionary rate observed in the ciliate eRF1 tree (fig. 1 ) for O. nova, T. thermophila, and P. tetraurelia (55.4, 58, and 87 substitutions per 100 positions, respectively, as estimated from the ancestral ciliate node up to the tip of each species branch). Although three points are clearly insufficient for a reliable correlation estimate, these data suggest that the use of reattributed stop codons and the eRF1 evolutionary rate might be indeed correlated. It may be especially significant that the genus having the highest use of UAA and UAG codons, Paramecium, clearly shows the longest branch among ciliates in eRF1 tree (fig. 1 ) but not for the other markers (fig. 2 ). Note that, on the contrary, the use of UGA represents only 23% of the cysteine codons (UGU, UGC, UGA) in Euplotes, which exhibits short eRF1 branches among ciliates. Nevertheless, it is important to remember here that ciliate eRF1 sequences have been obtained only from species with deviant genetic code usage. In this sense, the determination of ciliate eRF1 sequences from species that use the canonical code, as well as a fine mapping of the interactions of the eRF1 with other proteins, would be of great value to test this hypothesis.

As recently suggested by Inagaki and Doolittle (2001)Citation , the mechanism of eRF1 codon recognition may be very complex and not specifically linked to a few particular positions on this release factor sequence, as deduced from the comparison of the substitution patterns across the eRF1 between sequences from canonical- and deviant-code species. In agreement with this idea, our correlation analysis suggests that changes in codon assignment in ciliates cannot be attributed to a particular region of the eRF1 polypeptide, not even to the domain involved in codon recognition (fig. 4 ). This implies that the eRF1, as most likely occurs with the rest of translation proteins, forms a functional and structural unit for which the changes of function affect the evolutionary rate of the whole protein (Philippe and Lopez 2001Citation ). This reflects the situation found at a further level of complexity, i.e., multiprotein interactions, because in composite systems such as the translation machinery, changes on one of the elements may affect the evolutionary rate of the whole system.


    Acknowledgements
 TOP
 Abstract
 Introduction
 Material and Methods
 Results
 Discussion
 Acknowledgements
 References
 
We thank Philippe Lopez for critical reading of the manuscript, Yoshikazu Nakamura for the plasmid containing eRF1 gene of Tetrahymena, Anne Baroin-Tourancheau for E. aediculatus library, Eric Meyer for P. tetraurelia library, and the Institute for Genomic Research for access to sequence data and the plasmid containing eRF1 gene from T. brucei. O. J.-J. was supported by grant number 5511 from the Association pour la Recherche sur le Cancer. S.K. held fellowships from the French Ministère de la Recherche et de l'Enseignement Supérieur.


    Footnotes
 
Mark Ragan, Reviewing Editor

Keywords: ciliophora elongation factor eukaryotic phylogeny genetic code long-branch attraction release factor Back

Address for correspondence and reprints: Hervé Philippe, Phylogénie, Bioinformatique et Génome, UMR 7622 CNRS, Université Pierre et Marie Curie, 9, quai St Bernard 75005, Paris, France. herve.philippe{at}snv.jussieu.fr . Back


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Accepted for publication October 8, 2001.