A quantitative model for the rate-limiting process of UGA alternative assignments to stop and selenocysteine codons

Yen-Fu Chen, Hsiu-Chuan Lin, Kai-Neng Chuang, Chih-Hsu Lin, Hsueh-Chi S Yen and Chen-Hsiang Yeang

PLOS Computational Biology, 2017, vol. 13, issue 2, 1-25

Abstract: Ambiguity in genetic codes exists in cases where certain stop codons are alternatively used to encode non-canonical amino acids. In selenoprotein transcripts, the UGA codon may either represent a translation termination signal or a selenocysteine (Sec) codon. Translating UGA to Sec requires selenium and specialized Sec incorporation machinery such as the interaction between the SECIS element and SBP2 protein, but how these factors quantitatively affect alternative assignments of UGA has not been fully investigated. We developed a model simulating the UGA decoding process. Our model is based on the following assumptions: (1) charged Sec-specific tRNAs (Sec-tRNASec) and release factors compete for a UGA site, (2) Sec-tRNASec abundance is limited by the concentrations of selenium and Sec-specific tRNA (tRNASec) precursors, and (3) all synthesis reactions follow first-order kinetics. We demonstrated that this model captured two prominent characteristics observed from experimental data. First, UGA to Sec decoding increases with elevated selenium availability, but saturates under high selenium supply. Second, the efficiency of Sec incorporation is reduced with increasing selenoprotein synthesis. We measured the expressions of four selenoprotein constructs and estimated their model parameters. Their inferred Sec incorporation efficiencies did not correlate well with their SECIS-SBP2 binding affinities, suggesting the existence of additional factors determining the hierarchy of selenoprotein synthesis under selenium deficiency. This model provides a framework to systematically study the interplay of factors affecting the dual definitions of a genetic codon.Author summary: The “code book” of protein translation maps 43 = 64 triplets of RNA sequences (codons) into 20 canonical amino acids and the stop signal. This code book is universal in almost all organisms on earth. Selenoproteins consist of selenium-containing amino acids–selenocysteines (Sec)–that are not among the 20 canonical amino acids. The cells “borrow” a stop codon UGA to translate selenocysteines. Since UGA maps to two possible outcomes, the translation machinery can synthesize both full-length selenoproteins (when UGA encodes selenocysteine) and truncated peptide chains (when UGA encodes translational termination). Despite extensive study about selenoprotein synthesis mechanisms, a quantitative model for how cells allocate resources to synthesize each species is yet to appear. We propose a quantitative model that can explain the dependency of experimental observables such as protein stability and Sec incorporation efficiency by various factors such as selenium concentration and mRNA levels. Saturation of those quantities implies the existence of limiting factors such as mRNA transcripts and Sec-specific tRNAs. The match between model simulations and experimental data suggests that the cellular decision making of synthesizing the two species of proteins may follow simple first-order kinetics.

Date: 2017
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pcbi00:1005367

DOI: 10.1371/journal.pcbi.1005367

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