Novel structural determinants in human SECIS elements modulate the translational recoding of UGA as selenocysteine

Centre de recherche de Gif-sur-Yvette, FRC 3115, Centre de Génétique Moléculaire, CNRS, FRE 3144, Gif-sur-Yvette, F-75005 Paris, France.
Nucleic Acids Research (Impact Factor: 8.81). 09/2009; 37(17):5868-80. DOI: 10.1093/nar/gkp635
Source: PubMed

ABSTRACT The selenocysteine insertion sequence (SECIS) element directs the translational recoding of UGA as selenocysteine. In eukaryotes, the SECIS is located downstream of the UGA codon in the 3'-UTR of the selenoprotein mRNA. Despite poor sequence conservation, all SECIS elements form a similar stem-loop structure containing a putative kink-turn motif. We functionally characterized the 26 SECIS elements encoded in the human genome. Surprisingly, the SECIS elements displayed a wide range of UGA recoding activities, spanning several 1000-fold in vivo and several 100-fold in vitro. The difference in activity between a representative strong and weak SECIS element was not explained by differential binding affinity of SECIS binding Protein 2, a limiting factor for selenocysteine incorporation. Using chimeric SECIS molecules, we identified the internal loop and helix 2, which flank the kink-turn motif, as critical determinants of UGA recoding activity. The simultaneous presence of a GC base pair in helix 2 and a U in the 5'-side of the internal loop was a statistically significant predictor of weak recoding activity. Thus, the SECIS contains intrinsic information that modulates selenocysteine incorporation efficiency.

  • [Show abstract] [Hide abstract]
    ABSTRACT: Selenium, a micronutrient, is primarily incorporated into human physiology as selenocysteine (Sec). The 25 Sec-containing proteins in humans are known as selenoproteins. Their synthesis depends on the translational recoding of the UGA stop codon to allow Sec insertion. This requires a stem-loop structure in the 3' untranslated region of eukaryotic mRNAs known as the Selenocysteine Insertion Sequence (SECIS). The SECIS is recognized by SECIS-binding protein 2 (SBP2) and this RNA:protein interaction is essential for UGA recoding to occur. Genetic mutations cause SBP2 deficiency in humans, resulting in a broad set of symptoms due to differential effects on individual selenoproteins. Progress on understanding the different phenotypes requires developing robust tools to investigate SBP2 structure and function. In this study we demonstrate that SBP2 protein produced by in vitro translation discriminates among SECIS elements in a competitive UGA recoding assay and has a much higher specific activity than bacterially expressed protein. We also show that a purified recombinant protein encompassing amino acids 517-777 of SBP2 binds to SECIS elements with high affinity and selectivity. The affinity of the SBP2:SECIS interaction correlated with the ability of a SECIS to compete for UGA recoding activity in vitro. The identification of a 250 amino acid sequence that mediates specific, selective SECIS-binding will facilitate future structural studies of the SBP2:SECIS complex. Finally, we identify an evolutionarily conserved core cysteine signature in SBP2 sequences from the vertebrate lineage. Mutation of multiple, but not single, cysteines impaired SECIS-binding but did not affect protein localization in cells.
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: SelenoDB ( aims to provide high-quality annotations of selenoprotein genes, proteins and SECIS elements. Selenoproteins are proteins that contain the amino acid selenocysteine (Sec) and the first release of the database included annotations for eight species. Since the release of SelenoDB 1.0 many new animal genomes have been sequenced. The annotations of selenoproteins in new genomes usually contain many errors in major databases. For this reason, we have now fully annotated selenoprotein genes in 58 animal genomes. We provide manually curated annotations for human selenoproteins, whereas we use an automatic annotation pipeline to annotate selenoprotein genes in other animal genomes. In addition, we annotate the homologous genes containing cysteine (Cys) instead of Sec. Finally, we have surveyed genetic variation in the annotated genes in humans. We use exon capture and resequencing approaches to identify single-nucleotide polymorphisms in more than 50 human populations around the world. We thus present a detailed view of the genetic divergence of Sec- and Cys-containing genes in animals and their diversity in humans. The addition of these datasets into the second release of the database provides a valuable resource for addressing medical and evolutionary questions in selenium biology.
    Nucleic Acids Research 11/2013; 42(Database issue). DOI:10.1093/nar/gkt1045 · 8.81 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Traditional mutation assessment methods generally focus on predicting disruptive changes in protein-coding regions rather than non-coding regulatory regions like untranslated regions (UTRs) of mRNAs. The UTRs, however, are known to have many sequence and structural motifs that can regulate translational and transcriptional efficiency and stability of mRNAs through interaction with RNA-binding proteins and other non-coding RNAs like microRNAs (miRNAs). In a recent study, transcriptomes of tumor cells harboring mutant and wild-type KRAS (V-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog) genes in patients with non-small cell lung cancer (NSCLC) have been sequenced to identify single nucleotide variations (SNVs). About 40% of the total SNVs (73,717) identified were mapped to UTRs, but omitted in the previous analysis. To meet this obvious demand for analysis of the UTRs, we designed a comprehensive pipeline to predict the effect of SNVs on two major regulatory elements, secondary structure and miRNA target sites. Out of 29,290 SNVs in 6462 genes, we predict 472 SNVs (in 408 genes) affecting local RNA secondary structure, 490 SNVs (in 447 genes) affecting miRNA target sites and 48 that do both. Together these disruptive SNVs were present in 803 different genes, out of which 188 (23.4%) were previously known to be cancer-associated. Notably, this ratio is significantly higher (one-sided Fisher's exact test p-value = 0.032) than the ratio (20.8%) of known cancer-associated genes (n = 1347) in our initial data set (n = 6462). Network analysis shows that the genes harboring disruptive SNVs were involved in molecular mechanisms of cancer, and the signaling pathways of LPS-stimulated MAPK, IL-6, iNOS, EIF2 and mTOR. In conclusion, we have found hundreds of SNVs which are highly disruptive with respect to changes in the secondary structure and miRNA target sites within UTRs. These changes hold the potential to alter the expression of known cancer genes or genes linked to cancer-associated pathways.
    PLoS ONE 01/2014; 9(1):e82699. DOI:10.1371/journal.pone.0082699 · 3.53 Impact Factor