The prokaryotic selenoproteome.
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ABSTRACT:
SUBMITTER: Kryukov GV
PROVIDER: S-EPMC1299047 | biostudies-literature | 2004 May
REPOSITORIES: biostudies-literature
Publications
In the genetic code, the UGA codon has a dual function as it encodes selenocysteine (Sec) and serves as a stop signal. However, only the translation terminator function is used in gene annotation programs, resulting in misannotation of selenoprotein genes. Here, we applied two independent bioinformatics approaches to characterize a selenoprotein set in prokaryotic genomes. One method searched for selenoprotein genes by identifying RNA stem-loop structures, selenocysteine insertion sequence eleme ...[more]
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Project description:The use of selenocysteine (Sec) as the 21st amino acid in the genetic code has been described in all three major domains of life. However, within eukaryotes, selenoproteins are only known in animals and algae. In this study, we characterized selenoproteomes and Sec insertion systems in protozoan Apicomplexa parasites. We found that among these organisms, Plasmodium and Toxoplasma utilized Sec, whereas Cryptosporidium did not. However, Plasmodium had no homologs of known selenoproteins. By searching computationally for evolutionarily conserved selenocysteine insertion sequence (SECIS) elements, which are RNA structures involved in Sec insertion, we identified four unique Plasmodium falciparum selenoprotein genes. These selenoproteins were incorrectly annotated in PlasmoDB, were conserved in other Plasmodia and had no detectable homologs in other species. We provide evidence that two Plasmodium SECIS elements supported Sec insertion into parasite and endogenous selenoproteins when they were expressed in mammalian cells, demonstrating that the Plasmodium SECIS elements are functional and indicating conservation of Sec insertion between Apicomplexa and animals. Dependence of the plasmodial parasites on selenium suggests possible strategies for antimalarial drug development.
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Project description:The role of the selenoproteome, which is the collection of all proteins containing selenium in an organism, in cancer development, growth and progression requires further investigation, due to the importance of selenium in both cancer and immune system function. Data about the selenoproteome, including its differential expression, single nucleotide variations, copy number variations, methylation, pathways and overall survival (OS) in five leading types of cancer are available from the GSCALite website. Subsequent to the analysis of these datasets, it was revealed that there was increased expression of GPX3 in stomach adenocarcinoma and lung squamous cell carcinoma, SELENOV in oesophageal carcinoma, GPX8 and GPX4 in colon adenocarcinoma, TXNRD1 and SEPHS1 in hepatocellular carcinoma and GPX8 in lung adenocarcinoma were associated with poor survival. Decreased gene expression of SELENOP was indicated in liver hepatocellular carcinoma and GPX3, and SELENOW, SELENOK, SELENBP1 and SECISBP2 in lung adenocarcinoma were associated with a poor prognosis. OS data suggested that hypermethylation of GPX4 in colon adenocarcinoma, GPX8 in lung squamous cell carcinoma, GPX1 in stomach adenocarcinoma and GPX3 in lung adenocarcinoma was associated with low survival, as is hypomethylation of GPX5 in lung adenocarcinoma. The selenoproteome is heterogeneous, especially in its effect on the OS of patients with cancer. The present study demonstrated that the roles of GPX4 in colon adenocarcinoma, SCLY and SELENOV in oesophageal carcinoma, SEPHS1 in liver hepatocellular carcinoma, SELENOK in lung cancer, as well as SELENOM and SELENOW in stomach adenocarcinoma requires further research. The present study may lead to the identification of novel biomarkers or potential therapeutic targets for use in the treatment of cancers, such as colon adenocarcinoma, oesophageal carcinoma, liver hepatocellular carcinoma, lung cancer and stomach adenocarcinoma.
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Project description:BackgroundSelenocysteine (Sec) is a rare amino acid which occurs in proteins in major domains of life. It is encoded by TGA, which also serves as the signal for termination of translation, precluding identification of selenoprotein genes by available annotation tools. Information on full sets of selenoproteins (selenoproteomes) is essential for understanding the biology of selenium. Herein, we characterized the selenoproteome of the largest microbial sequence dataset, the Sargasso Sea environmental genome project.ResultsWe identified 310 selenoprotein genes that clustered into 25 families, including 101 new selenoprotein genes that belonged to 15 families. Most of these proteins were predicted redox proteins containing catalytic selenocysteines. Several bacterial selenoproteins previously thought to be restricted to eukaryotes were detected by analyzing eukaryotic and bacterial SECIS elements, suggesting that eukaryotic and bacterial selenoprotein sets partially overlapped. The Sargasso Sea microbial selenoproteome was rich in selenoproteins and its composition was different from that observed in the combined set of completely sequenced genomes, suggesting that these genomes do not accurately represent the microbial selenoproteome. Most detected selenoproteins occurred sporadically compared to the widespread presence of their cysteine homologs, suggesting that many selenoproteins recently evolved from cysteine-containing homologs.ConclusionsThis study yielded the largest selenoprotein dataset to date, doubled the number of prokaryotic selenoprotein families and provided insights into forces that drive selenocysteine evolution.
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Project description:BACKGROUND: Computational methods for identifying selenoproteins have been developed rapidly in recent years. However, it is still difficult to identify the open reading frame (ORF) of eukaryotic selenoprotein gene, because the TGA codon for a selenocysteine (Sec) residue in the active centre of selenoprotein is traditionally a terminal signal of protein translation. Although the identification of selenoproteins from genomes through bioinformatics methods has been conducted in bacteria, unicellular eukaryotes, insects and several vertebrates, only a few results have been reported on the ancient chordate selenoproteins. RESULTS: A gene assembly algorithm SelGenAmic has been constructed and presented in this study for identifying selenoprotein genes from eukaryotic genomes. A method based on this algorithm was developed to build an optimal TGA-containing-ORF for each TGA in a genome, followed by protein similarity analysis through conserved sequence alignments to screen out selenoprotein genes form these ORFs. This method improved the sensitivity of detecting selenoproteins from a genome due to the design that all TGAs in the genome were investigated for its possibility of decoding as a Sec residue. Using this method, eighteen selenoprotein genes were identified from the genome of Ciona intestinalis, leading to its member of selenoproteome up to 19. Among them a selenoprotein W gene was found to have two SECIS elements in the 3'-untranslated region. Additionally, the disulfide bond formation protein A (DsbA) was firstly identified as a selenoprotein in the ancient chordates of Ciona intestinalis, Ciona savignyi and Branchiostoma floridae, while selenoprotein DsbAs had only been found in bacteria and green algae before. CONCLUSION: The method based on SelGenAmic algorithm is capable of identifying eukaryotic selenoprotein genes from their genomes. Application of this method to Ciona intestinalis proves its successes in finding Sec-decoding TGA from large-scale eukaryotic genome sequences, which fills the gap in our knowledge on the ancient chordate selenoproteins.
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