Model-based design of RNA hybridization networks implemented in living cells

dc.contributor.affiliationInstituto Universitario Mixto de Biología Molecular y Celular de Plantas
dc.contributor.authorRodrigo, Guillermoes_ES
dc.contributor.authorPrakash, Satyaes_ES
dc.contributor.authorShen, Shensies_ES
dc.contributor.authorMajer, Eszteres_ES
dc.contributor.authorDaròs, José-Antonio
dc.contributor.authorJaramillo, Alfonsoes_ES
dc.contributor.funderUK Research and Innovationes_ES
dc.contributor.funderAXA Research Fundes_ES
dc.contributor.funderMinisterio de Educación, Cultura y Deportees_ES
dc.contributor.funderConsejo Superior de Investigaciones Científicases_ES
dc.contributor.funderBiotechnology and Biological Sciences Research Council, Reino Unidoes_ES
dc.contributor.funderMinisterio de Economía y Competitividades_ES
dc.date.accessioned2020-10-30T04:31:42Z
dc.date.available2020-10-30T04:31:42Z
dc.date.issued2017-09-19es_ES
dc.description.abstract[EN] Synthetic gene circuits allow the behavior of living cells to be reprogrammed, and non-coding small RNAs (sRNAs) are increasingly being used as programmable regulators of gene expression. However, sRNAs (natural or synthetic) are generally used to regulate single target genes, while complex dynamic behaviors would require networks of sRNAs regulating each other. Here, we report a strategy for implementing such networks that exploits hybridization reactions carried out exclusively by multifaceted sRNAs that are both targets of and triggers for other sRNAs. These networks are ultimately coupled to the control of gene expression. We relied on a thermo-dynamic model of the different stable conformational states underlying this system at the nucleotide level. To test our model, we designed five different RNA hybridization networks with a linear architecture, and we implemented them in Escherichia coli. We validated the network architecture at the molecular level by native polyacrylamide gel electrophoresis, as well as the network function at the bacterial population and single-cell levels with a fluorescent reporter. Our results suggest that it is possible to engineer complex cellular programs based on RNA from first principles. Because these networks are mainly based on physical interactions, our designs could be expanded to other organisms as portable regulatory resources or to implement biological computations.en_EN
dc.description.accrualMethodSes_ES
dc.description.bibliographicCitationRodrigo, G.; Prakash, S.; Shen, S.; Majer, E.; Daros Arnau, JA.; Jaramillo, A. (2017). Model-based design of RNA hybridization networks implemented in living cells. Nucleic Acids Research. 45(16):9797-9808. https://doi.org/10.1093/nar/gkx698es_ES
dc.description.issue16es_ES
dc.description.referencesAusländer, S., Ausländer, D., Müller, M., Wieland, M., & Fussenegger, M. (2012). Programmable single-cell mammalian biocomputers. Nature, 487(7405), 123-127. doi:10.1038/nature11149es_ES
dc.description.referencesFriedland, A. E., Lu, T. K., Wang, X., Shi, D., Church, G., & Collins, J. J. (2009). Synthetic Gene Networks That Count. Science, 324(5931), 1199-1202. doi:10.1126/science.1172005es_ES
dc.description.referencesNielsen, A. A. K., Der, B. S., Shin, J., Vaidyanathan, P., Paralanov, V., Strychalski, E. A., … Voigt, C. A. (2016). Genetic circuit design automation. Science, 352(6281), aac7341-aac7341. doi:10.1126/science.aac7341es_ES
dc.description.referencesGreen, A. A., Silver, P. A., Collins, J. J., & Yin, P. (2014). Toehold Switches: De-Novo-Designed Regulators of Gene Expression. Cell, 159(4), 925-939. doi:10.1016/j.cell.2014.10.002es_ES
dc.description.referencesDirks, R. M., & Pierce, N. A. (2004). From The Cover: Triggered amplification by hybridization chain reaction. Proceedings of the National Academy of Sciences, 101(43), 15275-15278. doi:10.1073/pnas.0407024101es_ES
dc.description.referencesChappell, J., Takahashi, M. K., & Lucks, J. B. (2015). Creating small transcription activating RNAs. Nature Chemical Biology, 11(3), 214-220. doi:10.1038/nchembio.1737es_ES
dc.description.referencesIsaacs, F. J., Dwyer, D. J., Ding, C., Pervouchine, D. D., Cantor, C. R., & Collins, J. J. (2004). Engineered riboregulators enable post-transcriptional control of gene expression. Nature Biotechnology, 22(7), 841-847. doi:10.1038/nbt986es_ES
dc.description.referencesQi, L., Lucks, J. B., Liu, C. C., Mutalik, V. K., & Arkin, A. P. (2012). Engineering naturally occurring trans -acting non-coding RNAs to sense molecular signals. Nucleic Acids Research, 40(12), 5775-5786. doi:10.1093/nar/gks168es_ES
dc.description.referencesDesai, S. K., & Gallivan, J. P. (2004). Genetic Screens and Selections for Small Molecules Based on a Synthetic Riboswitch That Activates Protein Translation. Journal of the American Chemical Society, 126(41), 13247-13254. doi:10.1021/ja048634jes_ES
dc.description.referencesWachsmuth, M., Findeiss, S., Weissheimer, N., Stadler, P. F., & Morl, M. (2012). De novo design of a synthetic riboswitch that regulates transcription termination. Nucleic Acids Research, 41(4), 2541-2551. doi:10.1093/nar/gks1330es_ES
dc.description.referencesWieland, M., & Hartig, J. S. (2008). Improved Aptazyme Design and In Vivo Screening Enable Riboswitching in Bacteria. Angewandte Chemie International Edition, 47(14), 2604-2607. doi:10.1002/anie.200703700es_ES
dc.description.referencesCarothers, J. M., Goler, J. A., Juminaga, D., & Keasling, J. D. (2011). Model-Driven Engineering of RNA Devices to Quantitatively Program Gene Expression. Science, 334(6063), 1716-1719. doi:10.1126/science.1212209es_ES
dc.description.referencesHochrein, L. M., Schwarzkopf, M., Shahgholi, M., Yin, P., & Pierce, N. A. (2013). Conditional Dicer Substrate Formation via Shape and Sequence Transduction with Small Conditional RNAs. Journal of the American Chemical Society, 135(46), 17322-17330. doi:10.1021/ja404676xes_ES
dc.description.referencesRodrigo, G., Landrain, T. E., Majer, E., Daròs, J.-A., & Jaramillo, A. (2013). Full Design Automation of Multi-State RNA Devices to Program Gene Expression Using Energy-Based Optimization. PLoS Computational Biology, 9(8), e1003172. doi:10.1371/journal.pcbi.1003172es_ES
dc.description.referencesHofacker, I. L., Fontana, W., Stadler, P. F., Bonhoeffer, L. S., Tacker, M., & Schuster, P. (1994). Fast folding and comparison of RNA secondary structures. Monatshefte f�r Chemie Chemical Monthly, 125(2), 167-188. doi:10.1007/bf00818163es_ES
dc.description.referencesMathews, D. H., Disney, M. D., Childs, J. L., Schroeder, S. J., Zuker, M., & Turner, D. H. (2004). Incorporating chemical modification constraints into a dynamic programming algorithm for prediction of RNA secondary structure. Proceedings of the National Academy of Sciences, 101(19), 7287-7292. doi:10.1073/pnas.0401799101es_ES
dc.description.referencesDirks, R. M., Bois, J. S., Schaeffer, J. M., Winfree, E., & Pierce, N. A. (2007). Thermodynamic Analysis of Interacting Nucleic Acid Strands. SIAM Review, 49(1), 65-88. doi:10.1137/060651100es_ES
dc.description.referencesWright, P. R., Georg, J., Mann, M., Sorescu, D. A., Richter, A. S., Lott, S., … Backofen, R. (2014). CopraRNA and IntaRNA: predicting small RNA targets, networks and interaction domains. Nucleic Acids Research, 42(W1), W119-W123. doi:10.1093/nar/gku359es_ES
dc.description.referencesAdleman, L. (1994). Molecular computation of solutions to combinatorial problems. Science, 266(5187), 1021-1024. doi:10.1126/science.7973651es_ES
dc.description.referencesSeelig, G., Soloveichik, D., Zhang, D. Y., & Winfree, E. (2006). Enzyme-Free Nucleic Acid Logic Circuits. Science, 314(5805), 1585-1588. doi:10.1126/science.1132493es_ES
dc.description.referencesYin, P., Choi, H. M. T., Calvert, C. R., & Pierce, N. A. (2008). Programming biomolecular self-assembly pathways. Nature, 451(7176), 318-322. doi:10.1038/nature06451es_ES
dc.description.referencesKirkpatrick, S., Gelatt, C. D., & Vecchi, M. P. (1983). Optimization by Simulated Annealing. Science, 220(4598), 671-680. doi:10.1126/science.220.4598.671es_ES
dc.description.referencesHersch, G. L., Baker, T. A., & Sauer, R. T. (2004). SspB delivery of substrates for ClpXP proteolysis probed by the design of improved degradation tags. Proceedings of the National Academy of Sciences, 101(33), 12136-12141. doi:10.1073/pnas.0404733101es_ES
dc.description.referencesLutz, R. (1997). Independent and tight regulation of transcriptional units in Escherichia coli via the LacR/O, the TetR/O and AraC/I1-I2 regulatory elements. Nucleic Acids Research, 25(6), 1203-1210. doi:10.1093/nar/25.6.1203es_ES
dc.description.referencesSchindelin, J., Arganda-Carreras, I., Frise, E., Kaynig, V., Longair, M., Pietzsch, T., … Cardona, A. (2012). Fiji: an open-source platform for biological-image analysis. Nature Methods, 9(7), 676-682. doi:10.1038/nmeth.2019es_ES
dc.description.referencesLaidler, K. J., & King, M. C. (1983). Development of transition-state theory. The Journal of Physical Chemistry, 87(15), 2657-2664. doi:10.1021/j100238a002es_ES
dc.description.referencesRodrigo, G., Majer, E., Prakash, S., Daròs, J.-A., Jaramillo, A., & Poyatos, J. F. (2015). Exploring the Dynamics and Mutational Landscape of Riboregulation with a Minimal Synthetic Circuit in Living Cells. Biophysical Journal, 109(5), 1070-1076. doi:10.1016/j.bpj.2015.07.021es_ES
dc.description.referencesSrinivas, N., Ouldridge, T. E., Šulc, P., Schaeffer, J. M., Yurke, B., Louis, A. A., … Winfree, E. (2013). On the biophysics and kinetics of toehold-mediated DNA strand displacement. Nucleic Acids Research, 41(22), 10641-10658. doi:10.1093/nar/gkt801es_ES
dc.description.referencesCuller, S. J., Hoff, K. G., & Smolke, C. D. (2010). Reprogramming Cellular Behavior with RNA Controllers Responsive to Endogenous Proteins. Science, 330(6008), 1251-1255. doi:10.1126/science.1192128es_ES
dc.description.referencesBenenson, Y., Paz-Elizur, T., Adar, R., Keinan, E., Livneh, Z., & Shapiro, E. (2001). Programmable and autonomous computing machine made of biomolecules. Nature, 414(6862), 430-434. doi:10.1038/35106533es_ES
dc.description.sponsorshipThe Consejo Superior de Investigaciones Cientificas (CSIC) Intramural [grant number 201440I017]; the Ministerio de Economia, Industria y Competitividad (MINECO)/FEDER [grant number BFU2015-66894-P]; and the AXA Research Fund Postdoctoral fellowship to G.R. The predoctoral fellowship [grant number AP2012-3751, MECD] to E.M. The Ministerio de Economia, Industria y Competitividad (MINECO) [grant numbers BIO2014-54269-R, AGL2013-49919-EXP] to J.A.D. The 7th Framework Programme [grant numbers 610730 (EVO-PROG), 613745 (PROMYS)]; the Horizon 2020 Marie Sklodowska-Curie [grant number 642738 (MetaRNA)]; the Engineering and Physical Sciences Research Council (EPSRC) and the Biotechnology and Biological Sciences Research Council (BBSRC) [grant number BB/M017982/1 (WISB centre)]; and the School of Life Sciences (U. Warwick) [startup allocation] to A.J. Funding for open access charge: EPSRC/BBSRC [BB/M017982/1 to A.J.].es_ES
dc.description.upvformatpfin9808es_ES
dc.description.upvformatpinicio9797es_ES
dc.description.volume45es_ES
dc.identifier.doi10.1093/nar/gkx698es_ES
dc.identifier.issn0305-1048es_ES
dc.identifier.pmcidPMC5766206es_ES
dc.identifier.pmid28934501es_ES
dc.identifier.urihttps://riunet.upv.es/handle/10251/153674
dc.languageIngléses_ES
dc.publisherOxford University Presses_ES
dc.relation.ispartofNucleic Acids Researches_ES
dc.relation.pasarelaS\356542es_ES
dc.relation.projectIDinfo:eu-repo/grantAgreement/EC/FP7/610730/EU/General-Purpose Programmable Evolution Machine on a Chip/es_ES
dc.relation.projectIDinfo:eu-repo/grantAgreement/UKRI//BB%2FM017982%2F1/GB/Warwick Integrative Synthetic Biology Centre/es_ES
dc.relation.projectIDinfo:eu-repo/grantAgreement/MECD//AP2012-3751/ES/AP2012-3751/es_ES
dc.relation.projectIDinfo:eu-repo/grantAgreement/EC/FP7/613745/EU/Programming synthetic networks for bio-based production of value chemicals/es_ES
dc.relation.projectIDinfo:eu-repo/grantAgreement/EC/H2020/642738/EU/RNA-based technologies for single-cell metabolite analysis/es_ES
dc.relation.projectIDinfo:eu-repo/grantAgreement/MINECO//AGL2013-49919-EXP/ES/DETECCION DE PATOGENOS Y BIOCOMPUTACION MEDIANTE CIRCUITOS REGULADORES EN PLANTAS/es_ES
dc.relation.projectIDinfo:eu-repo/grantAgreement/MINECO//BIO2014-54269-R/ES/INSTRUMENTOS BIOTECNOLOGICOS DERIVADOS DE VIRUS DE PLANTAS/es_ES
dc.relation.projectIDinfo:eu-repo/grantAgreement/CSIC//201440I017/es_ES
dc.relation.projectIDinfo:eu-repo/grantAgreement/MINECO//BFU2015-66894-P /ES/MODELADO, DISEÑO DE NOVO E INGENIERIA DE INTERRUPTORES DE RNA QUE RESPONDEN A SEÑALES GENETICAS/es_ES
dc.relation.publisherversionhttps://doi.org/10.1093/nar/gkx698es_ES
dc.relation.references10.1038/nature11149es_ES
dc.relation.references10.1126/science.1172005es_ES
dc.relation.references10.1126/science.aac7341es_ES
dc.relation.references10.1073/pnas.1203831109es_ES
dc.relation.references10.1016/j.cell.2014.10.002es_ES
dc.relation.references10.1073/pnas.0407024101es_ES
dc.relation.references10.1038/nchembio.1737es_ES
dc.relation.references10.1038/nbt986es_ES
dc.relation.references10.1038/nbt1069es_ES
dc.relation.references10.1073/pnas.1015741108es_ES
dc.relation.references10.1038/nbt.2461es_ES
dc.relation.references10.1038/nmeth.2184es_ES
dc.relation.references10.1093/nar/gks168es_ES
dc.relation.references10.1021/ja048634jes_ES
dc.relation.references10.1093/nar/gks1330es_ES
dc.relation.references10.1002/anie.200703700es_ES
dc.relation.references10.1126/science.1212209es_ES
dc.relation.references10.1093/nar/gkt253es_ES
dc.relation.references10.1093/nar/gkv287es_ES
dc.relation.references10.1021/nl501593res_ES
dc.relation.references10.1021/ja404676xes_ES
dc.relation.references10.1371/journal.pcbi.1003172es_ES
dc.relation.references10.1007/BF00818163es_ES
dc.relation.references10.1073/pnas.0401799101es_ES
dc.relation.references10.1137/060651100es_ES
dc.relation.references10.1093/nar/gku359es_ES
dc.relation.references10.1126/science.7973651es_ES
dc.relation.references10.1126/science.1132493es_ES
dc.relation.references10.1038/nature06451es_ES
dc.relation.references10.1126/science.220.4598.671es_ES
dc.relation.references10.1073/pnas.0404733101es_ES
dc.relation.references10.1093/nar/25.6.1203es_ES
dc.relation.references10.1038/nnano.2011.105es_ES
dc.relation.references10.1038/nmeth.2019es_ES
dc.relation.references10.1063/1.4809786es_ES
dc.relation.references10.1021/j100238a002es_ES
dc.relation.references10.1128/JB.183.23.6752-6762.2001es_ES
dc.relation.references10.1371/journal.pbio.0050229es_ES
dc.relation.references10.1021/sb4000959es_ES
dc.relation.references10.1038/nrmicro2615es_ES
dc.relation.references10.1038/srep36196es_ES
dc.relation.references10.1016/j.bpj.2015.07.021es_ES
dc.relation.references10.1093/nar/gkt801es_ES
dc.relation.references10.1073/pnas.2133841100es_ES
dc.relation.references10.1021/sb5002196es_ES
dc.relation.references10.1126/science.1192128es_ES
dc.relation.references10.1038/35106533es_ES
dc.rightsReserva de todos los derechoses_ES
dc.rights.accessRightsAbiertoes_ES
dc.titleModel-based design of RNA hybridization networks implemented in living cellses_ES
dc.typeArtículoes_ES
dc.type.versioninfo:eu-repo/semantics/publishedVersiones_ES
dspace.entity.typePublication
person.identifier192869
person.identifier.orcid0000-0002-6535-2889
relation.isAuthorOfPublication7ef79024-3a2e-4918-a833-4e2ebfe9e289
relation.isAuthorOfPublication.latestForDiscovery7ef79024-3a2e-4918-a833-4e2ebfe9e289
relation.isOrgUnitOfPublicatione7a4640e-8a10-48bc-8661-bb4fb3481bd0
relation.isOrgUnitOfPublication.latestForDiscoverye7a4640e-8a10-48bc-8661-bb4fb3481bd0
upv.uuidbbffdaae-5dfd-4414-8b39-fe38d87d75a7es_ES

Archivos

Bloque original

Mostrando 1 - 1 de 1
Cargando...
Miniatura
Nombre:
Rodrigo;Prakash;Shen - Model-based design of RNA hybridization networks implemented in living cells.pdf
Tamaño:
2.99 MB
Formato:
Adobe Portable Document Format
Descripción:
Versión editorial