Analysis of Selenocysteine‐Containing Proteins

Gladyshev, Vadim N.; Hatfield, Dolph L.

doi:10.1002/0471140864.ps0308s20

Cited by 8 publications

(6 citation statements)

References 108 publications

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“…These proteins fall into two classes: those with a covalently bound selenium atom, such as SELENBP1, and the larger group referred to as selenoproteins that contain selenium in the form of the amino acid selenocysteine. While the number of selenoprotein genes varies in the genomes of life forms throughout evolution, there are 25 known in the human genome [ 15 , 16 , 17 , 18 ]. The selenocysteine present in selenoproteins most often resides in the protein’s active site where it facilitates redox reactions at a much faster rate compared to cysteine [ 19 ].…”

Section: Introductionmentioning

confidence: 99%

Distinct Roles of SELENOF in Different Human Cancers

et al. 2023

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SELENOF, previously known as SEP15, is a selenoprotein that contains selenium in the form of the amino acid selenocysteine. Like other selenoproteins, the role for SELENOF in carcinogenesis has been investigated due to its altered expression compared to the corresponding normal tissue, its molecular function, and the association of genetic variations in the SELENOF gene to cancer risk or outcome. This review summarizes SELENOF’s discovery, structure, cellular localization, and expression. SELENOF belongs to a new family of thioredoxin-like proteins. Published data summarized here indicate a likely role for SELENOF in redox protein quality control, and in the regulation of lipids, glucose, and energy metabolism. Current evidence indicates that loss of SELENOF contributes to the development of prostate and breast cancer, while its loss may be protective against colon cancer. Additional investigation into SELENOF’s molecular mechanisms and its impact on cancer is warranted.

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Section: Introductionmentioning

confidence: 99%

Distinct Roles of SELENOF in Different Human Cancers

et al. 2023

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“…Selenium-containing proteins generally fall into three categories [4,5]. One of these classes includes those proteins containing selenomethionine in which selenium, due to its structural similarity to sulfur, incorporates non-specifically into the sulfur-containing amino acid [6]. The most common and best studied class of selenium-containing proteins includes those that contain the amino acid selenocysteine (Sec).…”

Section: Introductionmentioning

confidence: 99%

Selenium-binding protein 1 as a tumor suppressor and a prognostic indicator of clinical outcome

Yang

Diamond

2013

Biomark Res

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Selenium is a trace element that plays a critical role in physiological processes and cancer prevention, whose functions may be through its effects on selenium-containing proteins. Selenium-binding protein 1 (SBP1) is a member of an unusual class of selenium-containing proteins that may function as a tumor suppressor in multiple cancer types and whose levels have been shown to be lower in cancers as compared to corresponding normal tissues. This review is intended to summarize recent advances in gaining an understanding of the significance of SBP1 in carcinogenesis, and suggest that SBP1 could be developed as a potential biomarker for cancer progression and prognosis.

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“…Selenocysteine has been referred to as the 21st amino acid, with no dedicated triplet codon [18, 19]. As such, decoding for selenocysteine is unconventional and requires a “recoding” of the UGA stop codon for incorporation in a process termed stop codon reprogramming [17, 19, 20]. Similar to the yeast Trm9 example noted earlier, stop codon recoding utilizes specifically modified wobble uridine bases, mcm 5 U and 5-methoxycarbonylmethyl-2′-O-methyluridine (mcm 5 Um), to promote optimal anticodon-codon interactions [17, 21, 22], as well as 3'-UTR regulatory sequence and trans-acting factors.…”

Section: Introductionmentioning

confidence: 99%

Gene- and genome-based analysis of significant codon patterns in yeast, rat and mice genomes with the CUT Codon UTilization tool

Doyle

Leonardi

Endres

et al. 2016

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The translation of mRNA in all forms of life uses a three-nucleotide codon and aminoacyl-tRNAs to synthesize a protein. There are 64 possible codons in the genetic code, with codons for the ~20 amino acids and 3 stop codons having 1- to 6-fold degeneracy. Recent studies have shown that families of stress response transcripts, termed modification tunable transcripts (MoTTs), use distinct codon biases that match specifically modified tRNAs to regulate their translation during a stress. Similarly, translational reprogramming of the UGA stop codon to generate selenoproteins or to perform programmed translational read-through (PTR) that results in a longer protein, requires distinct codon bias (i.e., more than one stop codon) and, in the case of selenoproteins, a specifically modified tRNA. In an effort to identify transcripts that have codon usage patterns that could be subject to translational control mechanisms, we have used existing genome and transcript data to develop the gene-specific Codon UTilization (CUT) tool and database, which details all 1-, 2-, 3-, 4- and 5-codon combinations for all genes or transcripts in yeast (Saccharomyces cerevisiae), mice (Mus musculus) and rats (Rattus norvegicus). Here, we describe the use of the CUT tool and database to characterize significant codon usage patterns in specific genes and groups of genes. In yeast, we demonstrate how the CUT database can be used to identify genes that have runs of specific codons (e.g., AGA, GAA, AAG) linked to translational regulation by tRNA methyltransferase 9 (Trm9). We further demonstrate how groups of genes can be analyzed to find significant dicodon patterns, with the 80 Gcn4-regulated transcripts significantly (P < 0.00001) over-represented with the AGA-GAA dicodon. We have also used the CUT database to identify mouse and rat transcripts with internal UGA codons, with the surprising finding of 45 and 120 such transcripts, respectively, which is much larger than expected. The UGA data suggest that there could be many more translationally reprogrammed transcripts than currently reported. CUT thus represents a multi-species codon-counting database that can be used with mRNA-, translation- and proteomics-based results to better understand and model translational control mechanisms.

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Analysis of Selenocysteine‐Containing Proteins

Cited by 8 publications

References 108 publications

Distinct Roles of SELENOF in Different Human Cancers

Distinct Roles of SELENOF in Different Human Cancers

Selenium-binding protein 1 as a tumor suppressor and a prognostic indicator of clinical outcome

Gene- and genome-based analysis of significant codon patterns in yeast, rat and mice genomes with the CUT Codon UTilization tool

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