Critical roles for a genetic code alteration in the evolution of the genus Candida
2007; Springer Nature; Volume: 26; Issue: 21 Linguagem: Inglês
10.1038/sj.emboj.7601876
ISSN1460-2075
AutoresRaquel M. Silva, João A. Paredes, Gabriela Moura, Bruno Manadas, Tatiana Lima-Costa, Rita Rocha, Isabel M. Miranda, Ana Catarina Gomes, Marian J.A. Groot Koerkamp, Michel Perrot, Frank C. P. Holstege, Hélian Boucherie, Manuel A. S. Santos,
Tópico(s)Molecular Biology Techniques and Applications
ResumoArticle11 October 2007free access Critical roles for a genetic code alteration in the evolution of the genus Candida Raquel M Silva Raquel M Silva Department of Biology and CESAM, University of Aveiro, Aveiro, Portugal Search for more papers by this author João A Paredes João A Paredes Department of Biology and CESAM, University of Aveiro, Aveiro, Portugal Search for more papers by this author Gabriela R Moura Gabriela R Moura Department of Biology and CESAM, University of Aveiro, Aveiro, Portugal Search for more papers by this author Bruno Manadas Bruno Manadas Centre for Neurosciences and Cell Biology, University of Coimbra, Coimbra, Portugal Search for more papers by this author Tatiana Lima-Costa Tatiana Lima-Costa Department of Biology and CESAM, University of Aveiro, Aveiro, Portugal Search for more papers by this author Rita Rocha Rita Rocha Department of Biology and CESAM, University of Aveiro, Aveiro, Portugal Search for more papers by this author Isabel Miranda Isabel Miranda Department of Biology and CESAM, University of Aveiro, Aveiro, Portugal Search for more papers by this author Ana C Gomes Ana C Gomes Department of Biology and CESAM, University of Aveiro, Aveiro, Portugal Search for more papers by this author Marian JG Koerkamp Marian JG Koerkamp Department of Physiological Chemistry, University Medical Center Utrecht, Utrecht, The Netherlands Search for more papers by this author Michel Perrot Michel Perrot Institut de Biochimie et Génétique Cellulaires, CNRS, Bordeaux, France Search for more papers by this author Frank CP Holstege Frank CP Holstege Department of Physiological Chemistry, University Medical Center Utrecht, Utrecht, The Netherlands Search for more papers by this author Hélian Boucherie Hélian Boucherie Institut de Biochimie et Génétique Cellulaires, CNRS, Bordeaux, France Search for more papers by this author Manuel A S Santos Corresponding Author Manuel A S Santos Department of Biology and CESAM, University of Aveiro, Aveiro, Portugal Search for more papers by this author Raquel M Silva Raquel M Silva Department of Biology and CESAM, University of Aveiro, Aveiro, Portugal Search for more papers by this author João A Paredes João A Paredes Department of Biology and CESAM, University of Aveiro, Aveiro, Portugal Search for more papers by this author Gabriela R Moura Gabriela R Moura Department of Biology and CESAM, University of Aveiro, Aveiro, Portugal Search for more papers by this author Bruno Manadas Bruno Manadas Centre for Neurosciences and Cell Biology, University of Coimbra, Coimbra, Portugal Search for more papers by this author Tatiana Lima-Costa Tatiana Lima-Costa Department of Biology and CESAM, University of Aveiro, Aveiro, Portugal Search for more papers by this author Rita Rocha Rita Rocha Department of Biology and CESAM, University of Aveiro, Aveiro, Portugal Search for more papers by this author Isabel Miranda Isabel Miranda Department of Biology and CESAM, University of Aveiro, Aveiro, Portugal Search for more papers by this author Ana C Gomes Ana C Gomes Department of Biology and CESAM, University of Aveiro, Aveiro, Portugal Search for more papers by this author Marian JG Koerkamp Marian JG Koerkamp Department of Physiological Chemistry, University Medical Center Utrecht, Utrecht, The Netherlands Search for more papers by this author Michel Perrot Michel Perrot Institut de Biochimie et Génétique Cellulaires, CNRS, Bordeaux, France Search for more papers by this author Frank CP Holstege Frank CP Holstege Department of Physiological Chemistry, University Medical Center Utrecht, Utrecht, The Netherlands Search for more papers by this author Hélian Boucherie Hélian Boucherie Institut de Biochimie et Génétique Cellulaires, CNRS, Bordeaux, France Search for more papers by this author Manuel A S Santos Corresponding Author Manuel A S Santos Department of Biology and CESAM, University of Aveiro, Aveiro, Portugal Search for more papers by this author Author Information Raquel M Silva1, João A Paredes1, Gabriela R Moura1, Bruno Manadas2, Tatiana Lima-Costa1, Rita Rocha1, Isabel Miranda1, Ana C Gomes1, Marian JG Koerkamp3, Michel Perrot4, Frank CP Holstege3, Hélian Boucherie4 and Manuel A S Santos 1 1Department of Biology and CESAM, University of Aveiro, Aveiro, Portugal 2Centre for Neurosciences and Cell Biology, University of Coimbra, Coimbra, Portugal 3Department of Physiological Chemistry, University Medical Center Utrecht, Utrecht, The Netherlands 4Institut de Biochimie et Génétique Cellulaires, CNRS, Bordeaux, France *Corresponding author. Department of Biology, University of Aveiro, Santiago Campus, Aveiro 3810-193, Portugal. Tel.: +351234370771; Fax: +351234426408; E-mail: [email protected] The EMBO Journal (2007)26:4555-4565https://doi.org/10.1038/sj.emboj.7601876 PDFDownload PDF of article text and main figures. ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinked InMendeleyWechatReddit Figures & Info During the last 30 years, several alterations to the standard genetic code have been discovered in various bacterial and eukaryotic species. Sense and nonsense codons have been reassigned or reprogrammed to expand the genetic code to selenocysteine and pyrrolysine. These discoveries highlight unexpected flexibility in the genetic code, but do not elucidate how the organisms survived the proteome chaos generated by codon identity redefinition. In order to shed new light on this question, we have reconstructed a Candida genetic code alteration in Saccharomyces cerevisiae and used a combination of DNA microarrays, proteomics and genetics approaches to evaluate its impact on gene expression, adaptation and sexual reproduction. This genetic manipulation blocked mating, locked yeast in a diploid state, remodelled gene expression and created stress cross-protection that generated adaptive advantages under environmental challenging conditions. This study highlights unanticipated roles for codon identity redefinition during the evolution of the genus Candida, and strongly suggests that genetic code alterations create genetic barriers that speed up speciation. Introduction The discovery of alterations and expansions to the standard genetic code abolished the hypothesis of a frozen and universal genetic code (Crick, 1968) and raised important new questions, namely '(i) how do organisms survive codon identity redefinition? (ii) how and why do certain codons disappear while others alter their identity? and (iii) what is the evolutionary and physiological impact of codon identity redefinition?' Neutral (Codon Capture) evolutionary mechanisms postulate that highly biased G+C pressure can force codons to disappear and such unassigned codons can be captured by natural or mutant tRNAs from non-cognate codon families (Osawa and Jukes, 1989). This neutral mechanism explains some mitochondrial genetic code changes and unassignment of the CGG and AGA/AUA codons in Mycoplasma capricolum and Micrococcus luteus, which have 25% and 74% GC, respectively (Ohama et al, 1990; Oba et al, 1991). Codon identity redefinition can also be driven by selection through codon misreading (Schultz and Yarus, 1994). This requires structural change of the translational machinery, in particular of tRNAs, aminoacyl-tRNA synthetases and release factors, which decrease codon decoding fidelity and generate codons with more than one identity (Schultz and Yarus, 1994). These selection-driven mechanisms support the expansion of the genetic code to selenocysteine (twenty-first amino acid) and pyrrolysine (twenty-second amino acid) (Chambers et al, 1986; Hao et al, 2002). Selenocysteine is used in both prokaryotic and eukaryotic selenoproteins and its insertion into the genetic code required reprogramming of UGA stop codons by novel translation elongation factors (SelB-prokaryotes; EF-sec and SBP2-eukaryotes), a new tRNA (tRNASec) and a selenocysteine mRNA insertion element (SECIS) (Namy et al, 2004). L-Pyrrolysine is used in the archeon Methanosarcina barkeri through reprogramming of UAG-stop codons in methylamine methyltransferase genes (Theobald-Dietrich et al, 2005). Codon ambiguity also explains the identity alterations of several sense and non-sense codons in bacteria, mitochondria and in the cytoplasm of eukaryotes. For example, the decoding of leucine CUN (N any nucleotide) codons as threonine in yeast mitochondria and the decoding of leucine CUG codons as serine in the cytoplasm of various Candida species (Schultz and Yarus, 1994; Massey et al, 2003; Miranda et al, 2006). Genetic code alterations driven by codon ambiguity are most interesting because they should block lateral gene transfer and sexual reproduction. The former is highlighted in Candida albicans, where serine CUG decoding prevents the expression of functional wild-type green fluorescent protein (GFP), whose gene contains a single CUG codon, and of many other CUG-containing reporter genes, namely Escherichia coli β-galactosidase, Renilla reniformis luciferase, and Saccharomyces cerevisiae orotidine-5′-phosphate decarboxylase (Ura3p) (Cormack et al, 1997). Additionally, codon identity redefinition reshapes protein primary structure and may create novel protein functionalities, which on one hand may speed up the evolution of new phenotypes, but on the other may generate proteome and genetic incompatibilities to sexual reproduction. The latter is highlighted by the inability of using S. cerevisiae genes to complement C. albicans homologous gene disruptions (Sugiyama et al, 1995). We are using C. albicans as a model system to elucidate the molecular mechanism of evolution of serine CUG decoding in various Candida species and to understand the cellular and evolutionary consequences of altering the genetic code (Santos et al, 1996, 1999; Massey et al, 2003; Silva et al, 2004; Miranda et al, 2006). In C. albicans and other Candida species, the leucine CUG codon is decoded as serine by a novel serine tRNA that appeared 272±25 million years ago in the ancestor of yeasts, before separation of Saccharomyces and Candida genera (Figure 1A; Massey et al, 2003). It originated through the insertion of an adenosine in the intron of a tRNACGASer gene (Massey et al, 2003; Miranda et al, 2006), a mutation that created a hybrid tRNA molecule containing the body of serine and anticodon (5′-CAG-3′) of leucine-tRNAs (tRNACAGSer) (Figure 1B). This unique tRNA could decode leucine CUG codons as serine (Santos and Tuite, 1995; Suzuki et al, 1997) and competed for approximately 100 million years with wild-type tRNACAGLeu for CUG decoding (Figure 1A). It was selected in Candida and eliminated in Saccharomyces lineages (Massey et al, 2003) and its atypical structure was gradually reshaped with functional consequences (Santos et al, 1997; Perreau et al, 1999). In particular, two novel mutations in the anticodon loop changed the conserved uridine at position 33 (U33) to guanosine (G33) and adenosine 37 (A37) to guanosine 37 (G37) (Figure 1B). These two mutations modulate the leucine mischarging and CUG decoding efficiency of tRNACAGSer (Santos et al, 1996; Suzuki et al, 1997; Miranda et al, 2006). Figure 1.Reconstruction model of the Candida genetic code alteration. (A) Redefinition of the identity of the CUG codon from leucine to serine in Candida started with a novel serine tRNA (tRNACAGSer) and evolved gradually over the last 272±25 million years. tRNACAGSer disappeared and the cognate leucine CUG decoder (tRNACAGLeu) was maintained in the S. cerevisiae lineage (standard genetic code), while the converse occurred in the C. albicans lineage (altered genetic code). (B) The tRNACAGSer contains guanosine at position 33 (G33), which is a conserved position occupied by uridine (U33; U-turn) in other tRNAs. (C) The upper panel shows a diagram of the reporter system used to quantify serine misincorporation at CUG codons in vivo in S. cerevisiae. A CUG cassette inserted in the CaPGK gene was flanked by two thrombin cleavage sites to facilitate the purification of the short reporter peptide encoded by the cassette. The recombinant protein was expressed and purified from S. cerevisiae cultures using nickel affinity chromatography, and was then cleaved with thrombin for 16 h at 26°C, in solution. The resulting peptides were analysed by mass spectrometry. The lower panel shows a 12% SDS–PAGE of the reporter protein. (D) Serine and leucine incorporation at the CUG position (see panel C) was determined by quantitative MRM methodologies using a hybrid quadrupole/linear ion-trap mass spectrometer. Synthetic peptides with sequences identical to those of the serine and leucine peptides shown in panel C were used as external controls and to build the calibration curves used for quantification. Download figure Download PowerPoint In the present study, we have reconstructed the early stages of CUG identity redefinition from leucine to serine in vivo in S. cerevisiae (Figure 1A). Such genetic manipulation was not lethal, but affected sporulation and mating severely and locked yeast in a diploid state. It altered the expression of molecular chaperones, cell wall and membrane proteins, increased proteasome activity and accumulation of glycogen and trehalose. These data support the hypothesis that this genetic code change altered physiology and created a diploid yeast lineage that gave rise to the genus Candida. It highlights unanticipated roles for genetic code alterations in speciation and as a hidden source of genetic and phenotypic diversity. Results Partial CUG identity redefinition affected sexual reproduction We have already shown that the C. albicans tRNACAGSercan be expressed in S. cerevisiae from single-copy plasmids and that it is correctly processed and aminoacylated (Santos et al, 1996). Here, we used these plasmid-transformed strains to elucidate the impact of CUG identity redefinition on S. cerevisiae gene expression and physiology. The tRNACAGSer gene was also integrated into the genome of S. cerevisiae to evaluate the impact of this genetic code alteration on sexual reproduction. These S. cerevisiae clones expressed their own tRNAUAGLeu plus the C. albicans tRNACAGSerand incorporated leucine or serine randomly at CUG positions on a genome-wide scale. This mimicked the CUG ambiguity present in the Candida ancestor, where a cognate tRNALeu plus the novel mutant tRNACAGSer also competed for CUG codons (Figure 1A; Massey et al, 2003). Two versions of the C. albicans tRNACAGSer were used: the C. albicans wild-type tRNACAGSer containing G33, which is an inefficient decoder that appeared late in the evolutionary pathway of the genetic code alteration, plus a mutant tRNACAGSer containing the canonical U at position 33 (U33), which is an efficient decoder and represents the primordial tRNA (Santos et al, 1996; Perreau et al, 1999). The latter allowed us to confirm that the higher decoding efficiency of U33 tRNACAGSer was not an impediment to CUG identity redefinition. The levels of serine misincorporation in vivo at CUG positions were determined by mass spectrometry using a CUG-reporter system (Figure 1C; Supplementary Figures 1–3). In diploid cells, serine incorporation was 1.4% and 2.31% for the G33 and U33 tRNAGCAGSer, respectively (Figure 1D). Considering that background decoding error in vivo in yeast is in the order of 0.001% (Stansfield et al, 1998), those values represent 1400- and 2310-fold increase in decoding error and provide important insight into the level of ambiguity experienced by the Candida ancestor during the initial stages of the CUG identity change (Massey et al, 2003). We have investigated the impact of partial CUG identity redefinition in sexual reproduction using S. cerevisiae clones expressing U33 tRNACAGSer and G33 tRNACAGSer. The inefficient G33 tRNACAGSer decoder decreased sporulation efficiency by 30% (Figure 2A), while clones expressing the efficient U33 tRNACAGSer decoder showed very high sporulation variability; 55% of the clones sporulated normally, 25% did so very poorly and 20% did not sporulate at all (data not shown). The impact of CUG ambiguity on fertility was also tested by germinating spores of dissected asci. In selective media (YEPD–geneticin), 95% and 44% of control and G33 tRNACAGSerspores were viable, respectively, but 42% of G33 tRNACAGSerasci had one viable spore and 23% had two viable spores (Figure 2B and C). In 80% of U33 tRNACAGSer clones that sporulated, 76% of the asci produced spores that did not germinate, 9% had one viable spore and only 15% had two viable spores (data not shown). Since CUG ambiguity is toxic and creates genetic instability (see below), the integrity of G33 and U33 tRNACAGSer genes was verified by PCR amplification and resequencing of the respective DNA fragments (8 G33 and 17 U33 in total), isolated from the colonies of germinated spores. Spores expressing G33 tRNACAGSer had the correct tRNA gene sequence, while all the spores expressing U33 tRNACAGSercontained mutations in positions that mapped to the extra-loop and anticodon stem of the mature tRNA (data not shown). That is, U33 tRNACAGSer is lethal in haploid backgrounds, since only cells containing mutations in U33 tRNACAGSer gene could sporulate. These mutations also explained the fast growth of the spores (Figure 2C) and the very high sporulation variability observed in diploid cells expressing U33 tRNACAGSer (see above). It also confirmed previous studies showing that haploid S. cerevisiae cannot be transformed with plasmids carrying U33 tRNACAGSer (Santos et al, 1996). Figure 2.Genetic code alterations act as a barrier for sexual reproduction. The ability of S. cerevisiae cells expressing C. albicans G33 tRNACAGSerto reproduce sexually was determined by their sporulation and mating efficiencies. (A) The number of tetrads produced by diploid ambiguous cells decreased by 30% when compared with control cells, indicating that sporulation efficiency was lower in CUG ambiguous cells. (B) Spore viability was reduced in ambiguous cells, since most tetrads yielded only one (42%) or no viable spores (35%), while tetrads from control cells produced mainly two viable spores (92%). (C) Ambiguous cells produced fewer viable spores and spores grew slower, as shown by growth on solid selective medium. The U33 tRNA spores shown had mutations in the tRNACAGSer gene. (D) Haploid control and ambiguous cells with opposite mating types were mixed and serial dilutions of the mixtures were plated onto selective media. C × C, G × G and C × G indicate the crosses between the control cells, or ambiguous G33 tRNA cells or control and ambiguous G33 tRNA cells, respectively. The reduced amount of diploids produced by crossing ambiguous (G33 tRNA) cell lines showed that mating efficiency was also negatively affected by CUG ambiguity. In all cases, the U33 tRNACAG was lethal in haploid backgrounds. Alternatively, its gene acquired mutations that inactivated the U33 tRNA. Download figure Download PowerPoint Since U33 tRNACAGSer was lethal in haploid backgrounds, the impact of ambiguous CUG decoding on mating was evaluated using clones expressing the G33 tRNACAGSer gene. Crosses of G33 (MATa) × G33 (MATα) displayed low mating efficiency, which increased slightly for G33 (MATa) × control (MATα) crosses (Figure 2D). These mating differences are explained by gene dosage effects because diploids of G33 (MATα) × G33 (MATa) crosses had two copies of the G33 tRNACAGSer gene, while diploids of control (MATα) × G33 (MATa) crosses had a single copy of this tRNA gene and tRNA copy number determines tRNA abundance and CUG ambiguity levels. Interestingly, flow cytometry analysis showed that expression of U33 and G33 tRNACAGSer in S. cerevisiae increased ploidy (Figure 3A and B). G33 tRNACAGSer induced ploidy increase from N to 2N in 56% of the haploid clones, while U33 tRNACAGSerincreased it from 2N to 4N in 50% of diploid clones (Figure 3C). Expression of G33 tRNACAGSer in diploid cells also shifted DNA content peaks slightly, suggesting that the cell population contained a significant number of aneuploid cells. Similar DNA peak shifts were observed in clones expressing U33 tRNACAGSer (Figure 3B). Expression of G33 and U33 tRNACAGSeralso generated highly heterogeneous colony and cell morphologies and increased cell size significantly, which is consistent with ploidy increase (Figure 3D). Nuclear DAPI staining showed the presence of micronuclei and two or more large nuclei in cells expressing G33 and U33 tRNACAGSer. Some daughter cells did not have nuclei, suggesting disruption of chromosome segregation or aberrant nuclear division during mitosis (Figure 3D). Figure 3.Genetic code alterations induce ploidy variation. Flow cytometry analysis of haploid (A) and diploid (B) S. cerevisiae cell lines expressing the C. albicans G33 or U33 tRNACAGSer had a general increase of the nuclear DNA content, providing evidence of polyploidy and aneuploidy events in CUG ambiguous cells. (C) Ploidy shift was observed in 56% of the haploid G33 tRNACAGSer clones and 50% of diploid U33 tRNACAGSer clones tested by flow cytometry analysis. (D) Heterogeneity of the ambiguous cell population is shown by the variability in colony, cell and bud size and shape. The increase in cell volume is consistent with polyploidization of the ambiguous clones. DAPI staining highlights ambiguous cells with two nuclei or without nucleus, suggesting the presence of polyploid and aneuploid cells. Download figure Download PowerPoint CUG ambiguity altered gene expression and physiology To shed further light on the impact of codon identity redefinition on physiology and evolution, gene expression was monitored in cells expressing G33 and U33 tRNACAGSer using DNA microarrays. Similar results were obtained for both tRNAs, although differences in the magnitude of changes were observed in some cases (Supplementary Table 1). Overall, DNA microarray profiling uncovered alterations in the expression of genes belonging to the stress response, carbohydrate and amino-acid metabolism, cell wall structure, protein synthesis and degradation (Figure 4A). Figure 4.Genetic code alterations reprogramme gene expression. (A) Transcriptome analysis indicates the percentage of genes with altered expression levels in ambiguous strains. Genes whose expression was both up- and downregulated by CUG ambiguity were grouped according to their functions. The genes that are included in the stress group from the pie-chart were further divided into the functional categories displayed on the adjacent column. (B) Proteome data show the percentage of proteins whose expression was altered in S. cerevisiae cells expressing C. albicans U33 tRNACAGSer, distributed by functional categories. The proteins that are included in the stress group from the pie-chart were further divided into the functional categories displayed on the adjacent column. Both analyses indicate that genetic code ambiguity extensively remodelled gene expression, altered the expression of genes and proteins belonging to the stress response, protein synthesis, folding and degradation pathways, and general metabolism. Download figure Download PowerPoint Expression of 58 genes was upregulated, whereas that of 21 genes was downregulated (Supplementary Table 1). Most upregulated genes were stress-response genes (34%), namely molecular chaperones HSP12 (12.4-fold), HSP26 (5.8-fold), HSP70 (SSA4) (3.9-fold) and HSP104 (2.4-fold). CUG ambiguity also resulted in the upregulation of drug-resistance genes, namely copper-binding metallothionein genes CRS5 (3 fold) and CUP1 (2.9-fold), as well as the membrane ABC (ATP-binding cassette) transporter gene PDR5 (2.2-fold). Other changes involved general stress-response genes, namely the multistress response protein genes DDR2 (9 fold), HSP42 (3.9-fold), HSP30 (3.7-fold), the stress-induced methylglyoxal reductase gene GRE2 (2.1-fold), the GPI-anchored cell-wall glycoprotein genes SED1 and SPI1 (2.8-fold) and the cell-wall genes TIP1 (6.2-fold), and CWP2 (4 fold), which encode major structural mannoproteins (Table I). These gene expression alterations are in line with our previous results showing that CUG ambiguity increases tolerance to arsenite, cadmium, cycloheximide, ethanol, oxidants and salt (Santos et al, 1999). Overexpression of the high-affinity inorganic phosphate transporter (PHO84; 17.6-fold); the acid phosphatases PHO12 (3.4-fold), PHO11 (3.1-fold) and PHO5 (2.9-fold); the hexokinase I (HXK1; 6.2-fold); glucokinase (GLK1; 2.3-fold); glycogen phosphorylase (GPH1; 4.7-fold) and the components of the trehalose-6-phosphate synthetase/phosphatase complex (TSL1 and TPS1; 3.2- and 2.1-fold) indicated that CUG ambiguity affected phosphate, glucose, glycogen and trehalose metabolism (see below). Table 1. Selected genes whose expression was altered by CUG ambiguity Function Gene Fold Function Gene Fold Chaperones HSP12 12.4 Carbohydrate metabolism HXK1 6.2 HSP26 5.8 TSL1 3.2 SSA4 3.9 GLK1 2.3 HSP104 2.4 TPS1 2.1 Stress response CRS5 3.0 Protein synthesis RPL22B −2.1 CUP1 2.9 YDR341C −2.1 PNC1 2.1 RPL9B −2.0 Cell wall and transporters PHO84 17.6 Amino acid metabolism PUT1 3.7 PIR3 7.5 LYS9 −2.4 TIP1 6.2 SAM4 −2.0 CWP2 4.0 PDR5 2.2 Genes induced in ambiguous cells display positive fold variation and genes repressed are indicated by negative fold variation (FDR=0.001). Since expression of G33 and U33 tRNACAGSer generated highly heterogeneous cell populations (Figure 3) and induced the stress response, which altered gene expression at the post-transcriptional level (DiDomenico et al, 1982), we wondered whether DNA microarray profiling was providing a complete view of the gene expression alterations induced by ambiguous CUG decoding. To clarify this question, quantification of protein expression was carried out using phosphorimaging of [35S]methionine-labelled proteins fractionated onto 2D-PAGE (Figure 4B; Supplementary Figure 4 and Table 2). Up-regulation of 43 proteins belonging to the stress response and protein degradation, and down-regulation of 34 proteins involved in amino-acid metabolism and protein synthesis was observed (Figure 4B). These data confirmed the DNA microarray data, but fold-induction differences were observed for several genes (Table II). For example, Hsp104p and Pnc1p were up-regulated 13.1- and 29.5-fold (Table II), while their mRNAs increased 2.4- and 2.1-fold only, respectively (Tables I and II). Two additional differences were found between the microarray and proteomics data. The latter, but not the former, showed up-regulation of several proteasome subunits, namely Rpn10p, Rpn12p, Pup2p and Scl1p (Table II), which was confirmed by increased proteasome activity (3.6-fold) in ambiguous cells (Figure 5A and B). Figure 5.Genetic code alterations reprogramme the stress response. (A) Proteasome activity increased 3.6-fold in S. cerevisiae cells expressing C. albicans tRNACAGSer (U33), as shown by enhanced proteolysis of the chymotrypsin-like substrate SucLLVY-AMC. The results are expressed as mean±s.d. of 4–6 independent experiments (**P<0.01 by Student's t-test). Fluorescence intensity (FIU) is shown in arbitrary units. (B) Expression of proteasome subunits (Supplementary Table 3) was threefold induced by CUG ambiguity, as measured by proteome analysis. Control (C) and ambiguous (U33) cells were grown at 25°C (25), 37°C (37) or heat shocked (HS). Proteins were labelled in vivo with L-[35S]methionine and separated by 2D-PAGE as described in Materials and methods. The medium expression level of the selected proteins was calculated and normalized to the control to deduce general folds. (C) Ambiguity pre-adapted cells to tolerate adverse growth conditions. Expression of stress proteins (Supplementary Tables 3 and 4) increased twofold in control cells at 37°C, but not in ambiguous cells that already had increased amounts (3 fold) of these stress-protective proteins. (D) Ambiguous cells retained the capacity to respond to additional stress. Expression of stress proteins (Supplementary Tables 3 and 4) was induced in both strains under heat-shock (8- and 13-fold for the control and ambiguous cells, respectively). Download figure Download PowerPoint Table 2. Selected proteins whose expression was altered by CUG ambiguity Function Protein Fold P-value Function Protein Fold P-value Chaperones Hsp104 13.1 — Amino-acid metabolism Met17 −5.3 0.0004 Ssa1 4.7 0.0007 Aro8 −5.1 0.000007 Ssa2 2.5 0.0091 Arg1 −3.4 0.005 Ssa4 N — Lys9 −2.8 0.006 Stress Pnc1 29.5 0.0154 Leu2 −2.3 0.0001 Response Ahp1 3.4 0.0021 Carbohydrate metabolism Glk1 5.0 0.0091 Protein synthesis Krs1 −2.7 0.0011 Hxk1 N — Ssb1 −2.1 0.0167 Hor2 N — Ssb2 −2.1 0.0052 Protein degradation Rpn12 5.2 0.0230 Rpn10 3.6 0.0065 Pup2 3.6 0.0010 Scl1 3.6 0.0228 Proteins whose expression was altered in ambiguous cells, indicating the respective fold variation and statistical significance. Proteins induced display positive fold variation and proteins repressed are represented by negative fold variation; N stands for new spots (proteins that were not expressed in the control condition and, therefore, their fold variation could not be accurately determined). An average fold represents proteins that are present in the 2D gel by more than one spot. Strong up-regulation (29.5-fold) of the enzyme nicotinamidase (PNC1), which converts nicotinamide into nicotinic acid in the NAD+ salvage pathway (Anderson et al, 2003), was
Referência(s)