A quantitative model for the rate-limiting process of UGA alternative assignments to stop and selenocysteine codons
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...
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description | 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. |
doi_str_mv | 10.1371/journal.pcbi.1005367 |
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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.</description><identifier>ISSN: 1553-7358</identifier><identifier>ISSN: 1553-734X</identifier><identifier>EISSN: 1553-7358</identifier><identifier>DOI: 10.1371/journal.pcbi.1005367</identifier><identifier>PMID: 28178267</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Amino acids ; Biology and life sciences ; Career development planning ; Codon, Initiator - genetics ; Codon, Terminator - genetics ; Codons ; Computer Simulation ; Funding ; Genetic code ; Genomes ; Models, Genetic ; Molecular biology ; Observations ; Physical Sciences ; Physiological aspects ; Protein Biosynthesis - genetics ; Protein synthesis ; Proteins ; Proteins - genetics ; Research and Analysis Methods ; Selenium ; Selenocysteine - genetics ; Selenoproteins - biosynthesis ; Selenoproteins - genetics ; Sequence Analysis, RNA - methods</subject><ispartof>PLoS computational biology, 2017-02, Vol.13 (2), p.e1005367-e1005367</ispartof><rights>COPYRIGHT 2017 Public Library of Science</rights><rights>2017 Public Library of Science. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited: Chen Y-F, Lin H-C, Chuang K-N, Lin C-H, Yen H-CS, Yeang C-H (2017) A quantitative model for the rate-limiting process of UGA alternative assignments to stop and selenocysteine codons. PLoS Comput Biol 13(2): e1005367. doi:10.1371/journal.pcbi.1005367</rights><rights>2017 Chen et al 2017 Chen et al</rights><rights>2017 Public Library of Science. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited: Chen Y-F, Lin H-C, Chuang K-N, Lin C-H, Yen H-CS, Yeang C-H (2017) A quantitative model for the rate-limiting process of UGA alternative assignments to stop and selenocysteine codons. PLoS Comput Biol 13(2): e1005367. doi:10.1371/journal.pcbi.1005367</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c666t-165cc810a3c731e0818e86b6880e747cd772e3d1139df08d42e7ce825535a6503</citedby><cites>FETCH-LOGICAL-c666t-165cc810a3c731e0818e86b6880e747cd772e3d1139df08d42e7ce825535a6503</cites><orcidid>0000-0003-4034-8960 ; 0000-0002-9224-5800</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC5323020/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC5323020/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,860,881,2095,2914,23846,27903,27904,53769,53771,79346,79347</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/28178267$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><contributor>Plotkin, Joshua B.</contributor><creatorcontrib>Chen, Yen-Fu</creatorcontrib><creatorcontrib>Lin, Hsiu-Chuan</creatorcontrib><creatorcontrib>Chuang, Kai-Neng</creatorcontrib><creatorcontrib>Lin, Chih-Hsu</creatorcontrib><creatorcontrib>Yen, Hsueh-Chi S</creatorcontrib><creatorcontrib>Yeang, Chen-Hsiang</creatorcontrib><title>A quantitative model for the rate-limiting process of UGA alternative assignments to stop and selenocysteine codons</title><title>PLoS computational biology</title><addtitle>PLoS Comput Biol</addtitle><description>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.</description><subject>Amino acids</subject><subject>Biology and life sciences</subject><subject>Career development planning</subject><subject>Codon, Initiator - genetics</subject><subject>Codon, Terminator - genetics</subject><subject>Codons</subject><subject>Computer Simulation</subject><subject>Funding</subject><subject>Genetic code</subject><subject>Genomes</subject><subject>Models, Genetic</subject><subject>Molecular biology</subject><subject>Observations</subject><subject>Physical Sciences</subject><subject>Physiological aspects</subject><subject>Protein Biosynthesis - genetics</subject><subject>Protein synthesis</subject><subject>Proteins</subject><subject>Proteins - genetics</subject><subject>Research and Analysis Methods</subject><subject>Selenium</subject><subject>Selenocysteine - genetics</subject><subject>Selenoproteins - biosynthesis</subject><subject>Selenoproteins - genetics</subject><subject>Sequence Analysis, RNA - methods</subject><issn>1553-7358</issn><issn>1553-734X</issn><issn>1553-7358</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2017</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><sourceid>DOA</sourceid><recordid>eNqVkkFv1DAUhCMEoqXwDxBY4gKHXezYsZ1LpVUFZaUKJKBny3FeUq8Se2s7Ff33eLtp1UUcQDnEcb6ZjCevKF4TvCRUkI8bPwWnh-XWNHZJMK4oF0-KY1JVdCFoJZ8-Wh8VL2LcYJyXNX9eHJWSCFlycVzEFbqetEs26WRvAI2-hQF1PqB0BSjoBIvBjjZZ16Nt8AZiRL5Dl-crpIcEOcGdTMdoezeCSxElj2LyW6RdiyIM4Ly5jQmsA2R86118WTzr9BDh1Xw_KS4_f_p59mVx8e18fba6WBjOeVoQXhkjCdbUCEoASyJB8oZLiUEwYVohSqAtIbRuOyxbVoIwIMt86ErzCtOT4u3edzv4qOa-oiJSZFdGS5KJ9Z5ovd6obbCjDrfKa6vuNnzolQ7JmgEUGKFrnZPVHDPMuORd2zRNJ_JDY7TMXqfz16ZmhNbkLoIeDkwP3zh7pXp_oypaUlzu4r6fDYK_niAmNdpoYBi0Az_tcue_VgnG639Ac4N1yTHP6Ls_0L8XsdxTvc5nta7zOaLJVwujNd5BZ_P-itV58hirWRZ8OBBkJsGv1OspRrX-8f0_2K-HLNuzJvgYA3QPBRKsdnN_H1_t5l7Nc59lbx6X_yC6H3T6G5bX_2w</recordid><startdate>20170201</startdate><enddate>20170201</enddate><creator>Chen, Yen-Fu</creator><creator>Lin, Hsiu-Chuan</creator><creator>Chuang, Kai-Neng</creator><creator>Lin, Chih-Hsu</creator><creator>Yen, Hsueh-Chi S</creator><creator>Yeang, Chen-Hsiang</creator><general>Public Library of Science</general><general>Public Library of Science (PLoS)</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>ISN</scope><scope>ISR</scope><scope>3V.</scope><scope>7QO</scope><scope>7QP</scope><scope>7TK</scope><scope>7TM</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8AL</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>JQ2</scope><scope>K7-</scope><scope>K9.</scope><scope>LK8</scope><scope>M0N</scope><scope>M0S</scope><scope>M1P</scope><scope>M7P</scope><scope>P5Z</scope><scope>P62</scope><scope>P64</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>Q9U</scope><scope>RC3</scope><scope>7X8</scope><scope>5PM</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0003-4034-8960</orcidid><orcidid>https://orcid.org/0000-0002-9224-5800</orcidid></search><sort><creationdate>20170201</creationdate><title>A quantitative model for the rate-limiting process of UGA alternative assignments to stop and selenocysteine codons</title><author>Chen, Yen-Fu ; Lin, Hsiu-Chuan ; Chuang, Kai-Neng ; Lin, Chih-Hsu ; Yen, Hsueh-Chi S ; Yeang, Chen-Hsiang</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c666t-165cc810a3c731e0818e86b6880e747cd772e3d1139df08d42e7ce825535a6503</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2017</creationdate><topic>Amino acids</topic><topic>Biology and life sciences</topic><topic>Career development planning</topic><topic>Codon, Initiator - genetics</topic><topic>Codon, Terminator - genetics</topic><topic>Codons</topic><topic>Computer Simulation</topic><topic>Funding</topic><topic>Genetic code</topic><topic>Genomes</topic><topic>Models, Genetic</topic><topic>Molecular biology</topic><topic>Observations</topic><topic>Physical Sciences</topic><topic>Physiological aspects</topic><topic>Protein Biosynthesis - genetics</topic><topic>Protein synthesis</topic><topic>Proteins</topic><topic>Proteins - genetics</topic><topic>Research and Analysis Methods</topic><topic>Selenium</topic><topic>Selenocysteine - genetics</topic><topic>Selenoproteins - biosynthesis</topic><topic>Selenoproteins - genetics</topic><topic>Sequence Analysis, RNA - methods</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Chen, Yen-Fu</creatorcontrib><creatorcontrib>Lin, Hsiu-Chuan</creatorcontrib><creatorcontrib>Chuang, Kai-Neng</creatorcontrib><creatorcontrib>Lin, Chih-Hsu</creatorcontrib><creatorcontrib>Yen, Hsueh-Chi S</creatorcontrib><creatorcontrib>Yeang, Chen-Hsiang</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Gale In Context: Canada</collection><collection>Gale In Context: Science</collection><collection>ProQuest Central (Corporate)</collection><collection>Biotechnology Research Abstracts</collection><collection>Calcium & Calcified Tissue Abstracts</collection><collection>Neurosciences Abstracts</collection><collection>Nucleic Acids Abstracts</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>Computing Database (Alumni Edition)</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest One Sustainability</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>Natural Science Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Engineering Research Database</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Computer Science Collection</collection><collection>Computer Science Database</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>ProQuest Biological Science Collection</collection><collection>Computing Database</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Biological Science Database</collection><collection>Advanced Technologies & Aerospace Database</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central Basic</collection><collection>Genetics Abstracts</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>PLoS computational biology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Chen, Yen-Fu</au><au>Lin, Hsiu-Chuan</au><au>Chuang, Kai-Neng</au><au>Lin, Chih-Hsu</au><au>Yen, Hsueh-Chi S</au><au>Yeang, Chen-Hsiang</au><au>Plotkin, Joshua B.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A quantitative model for the rate-limiting process of UGA alternative assignments to stop and selenocysteine codons</atitle><jtitle>PLoS computational biology</jtitle><addtitle>PLoS Comput Biol</addtitle><date>2017-02-01</date><risdate>2017</risdate><volume>13</volume><issue>2</issue><spage>e1005367</spage><epage>e1005367</epage><pages>e1005367-e1005367</pages><issn>1553-7358</issn><issn>1553-734X</issn><eissn>1553-7358</eissn><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.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>28178267</pmid><doi>10.1371/journal.pcbi.1005367</doi><orcidid>https://orcid.org/0000-0003-4034-8960</orcidid><orcidid>https://orcid.org/0000-0002-9224-5800</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Amino acids Biology and life sciences Career development planning Codon, Initiator - genetics Codon, Terminator - genetics Codons Computer Simulation Funding Genetic code Genomes Models, Genetic Molecular biology Observations Physical Sciences Physiological aspects Protein Biosynthesis - genetics Protein synthesis Proteins Proteins - genetics Research and Analysis Methods Selenium Selenocysteine - genetics Selenoproteins - biosynthesis Selenoproteins - genetics Sequence Analysis, RNA - methods |
title | A quantitative model for the rate-limiting process of UGA alternative assignments to stop and selenocysteine codons |
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