An algorithm for identification of bacterial selenocysteine insertion sequence elements and selenoprotein genes
- PMID: 15797911
- DOI: 10.1093/bioinformatics/bti400
An algorithm for identification of bacterial selenocysteine insertion sequence elements and selenoprotein genes
Abstract
Motivation: Incorporation of selenocysteine (Sec) into proteins in response to UGA codons requires a cis-acting RNA structure, Sec insertion sequence (SECIS) element. Whereas SECIS elements in Escherichia coli are well characterized, a bacterial SECIS consensus structure is lacking.
Results: We developed a bacterial SECIS consensus model, the key feature of which is a conserved guanosine in a small apical loop of the properly positioned structure. This consensus was used to build a computational tool, bSECISearch, for detection of bacterial SECIS elements and selenoprotein genes in sequence databases. The program identified 96.5% of known selenoprotein genes in completely sequenced bacterial genomes and predicted several new selenoprotein genes. Further analysis revealed that the size of bacterial selenoproteomes varied from 1 to 11 selenoproteins. Formate dehydrogenase was present in most selenoproteomes, often as the only selenoprotein family, whereas the occurrence of other selenoproteins was limited. The availability of the bacterial SECIS consensus and the tool for identification of these structures should help in correct annotation of selenoprotein genes and characterization of bacterial selenoproteomes.
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