Dynamic signal processing by ribozyme-mediated RNA circuits to control gene expression

[EN] Organisms have different circuitries that allow converting signal molecule levels to changes in gene expression. An important challenge in synthetic biology involves the de novo design of RNA modules enabling dynamic signal processing in live cells. This requires a scalable methodology for sensing, transmission, and actuation, which could be assembled into larger signaling networks. Here, we present a biochemical strategy to design RNA-mediated signal transduction cascades able to sense small molecules and small RNAs. We design switchable functional RNA domains by using strand-displacement techniques. We experimentally characterize the molecular mechanism underlying our synthetic RNA signaling cascades, show the ability to regulate gene expression with transduced RNA signals, and describe the signal processing response of our systems to periodic forcing in single live cells. The engineered systems integrate RNA-RNA interaction with available ribozyme and aptamer elements, providing new ways to engineer arbitrary complex gene circuits.EVOPROG [FP7-ICT-610730]; PROMYS [FP7-KBBE-613745 to A.J.]; Ministerio de Economia y Competitividad, Spain [BIO2011-26741 to J.-A.D.]; PRES Paris Sud grant (S.S.); EMBO long-term fellowship co-funded by Marie Curie actions [ALTF-1177-2011 A.J., G.R.]; AXA research fund; Ministerio de Educacion, Cultura y Deporte, Spain [AP2012-3751 to E.M.]. Funding for open access charge: EVOPROG [FP7-ICT-610730]; PROMYS [FP7-KBBE-613745].Shen, S.; Rodrigo Tarrega, G.; Prakash, S.; Majer, E.; Landrain, T.; Kirov, B.; Daros Arnau, JA.... (2015). Dynamic signal processing by ribozyme-mediated RNA circuits to control gene expression. Nucleic Acids Research. 43(10):5158-5170. https://doi.org/10.1093/nar/gkv287515851704310Ulrich, L. E., Koonin, E. V., & Zhulin, I. B. (2005). One-component systems dominate signal transduction in prokaryotes. Trends in Microbiology, 13(2), 52-56. doi:10.1016/j.tim.2004.12.006Kiel, C., Yus, E., & Serrano, L. (2010). Engineering Signal Transduction Pathways. Cell, 140(1), 33-47. doi:10.1016/j.cell.2009.12.028Isaacs, F. J., Dwyer, D. J., & Collins, J. J. (2006). RNA synthetic biology. Nature Biotechnology, 24(5), 545-554. doi:10.1038/nbt1208Liang, J. C., Bloom, R. J., & Smolke, C. D. (2011). Engineering Biological Systems with Synthetic RNA Molecules. Molecular Cell, 43(6), 915-926. doi:10.1016/j.molcel.2011.08.023Dueber, J. E. (2003). Reprogramming Control of an Allosteric Signaling Switch Through Modular Recombination. Science, 301(5641), 1904-1908. doi:10.1126/science.1085945Sallee, N. A., Yeh, B. J., & Lim, W. A. (2007). Engineering Modular Protein Interaction Switches by Sequence Overlap. Journal of the American Chemical Society, 129(15), 4606-4611. doi:10.1021/ja0672728Rodrigo, G., Landrain, T. E., Shen, S., & Jaramillo, A. (2013). A new frontier in synthetic biology: automated design of small RNA devices in bacteria. Trends in Genetics, 29(9), 529-536. doi:10.1016/j.tig.2013.06.005Callura, J. M., Dwyer, D. J., Isaacs, F. J., Cantor, C. R., & Collins, J. J. (2010). Tracking, tuning, and terminating microbial physiology using synthetic riboregulators. Proceedings of the National Academy of Sciences, 107(36), 15898-15903. doi:10.1073/pnas.1009747107Callura, J. M., Cantor, C. R., & Collins, J. J. (2012). Genetic switchboard for synthetic biology applications. Proceedings of the National Academy of Sciences, 109(15), 5850-5855. doi:10.1073/pnas.1203808109Werstuck, G. (1998). Controlling Gene Expression in Living Cells Through Small Molecule-RNA Interactions. Science, 282(5387), 296-298. doi:10.1126/science.282.5387.296Wieland, 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.200703700Win, M. N., & Smolke, C. D. (2007). A modular and extensible RNA-based gene-regulatory platform for engineering cellular function. Proceedings of the National Academy of Sciences, 104(36), 14283-14288. doi:10.1073/pnas.0703961104Klauser, B., & Hartig, J. S. (2013). An engineered small RNA-mediated genetic switch based on a ribozyme expression platform. Nucleic Acids Research, 41(10), 5542-5552. doi:10.1093/nar/gkt253Bayer, T. S., & Smolke, C. D. (2005). Programmable ligand-controlled riboregulators of eukaryotic gene expression. Nature Biotechnology, 23(3), 337-343. doi:10.1038/nbt1069Qi, 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/gks168Looger, L. L., Dwyer, M. A., Smith, J. J., & Hellinga, H. W. (2003). Computational design of receptor and sensor proteins with novel functions. Nature, 423(6936), 185-190. doi:10.1038/nature01556Kortemme, T., & Baker, D. (2004). Computational design of protein–protein interactions. Current Opinion in Chemical Biology, 8(1), 91-97. doi:10.1016/j.cbpa.2003.12.008Rodrigo, G., Landrain, T. E., & Jaramillo, A. (2012). De novo automated design of small RNA circuits for engineering synthetic riboregulation in living cells. Proceedings of the National Academy of Sciences, 109(38), 15271-15276. doi:10.1073/pnas.1203831109Isaacs, 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/nbt986Kirkpatrick, S., Gelatt, C. D., & Vecchi, M. P. (1983). Optimization by Simulated Annealing. Science, 220(4598), 671-680. doi:10.1126/science.220.4598.671Hofacker, 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/bf00818163Pédelacq, J.-D., Cabantous, S., Tran, T., Terwilliger, T. C., & Waldo, G. S. (2005). Engineering and characterization of a superfolder green fluorescent protein. Nature Biotechnology, 24(1), 79-88. doi:10.1038/nbt1172Hersch, 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.0404733101Rodrigo, G., Kirov, B., Shen, S., & Jaramillo, A. (2013). Theoretical and experimental analysis of the forced LacI-AraC oscillator with a minimal gene regulatory model. Chaos: An Interdisciplinary Journal of Nonlinear Science, 23(2), 025109. doi:10.1063/1.4809786Danino, T., Mondragón-Palomino, O., Tsimring, L., & Hasty, J. (2010). A synchronized quorum of genetic clocks. Nature, 463(7279), 326-330. doi:10.1038/nature08753Mathews, D. H., Sabina, J., Zuker, M., & Turner, D. H. (1999). Expanded sequence dependence of thermodynamic parameters improves prediction of RNA secondary structure. Journal of Molecular Biology, 288(5), 911-940. doi:10.1006/jmbi.1999.2700Paige, J. S., Nguyen-Duc, T., Song, W., & Jaffrey, S. R. (2012). Fluorescence Imaging of Cellular Metabolites with RNA. Science, 335(6073), 1194-1194. doi:10.1126/science.1218298Chen, X., & Ellington, A. D. (2009). Design Principles for Ligand-Sensing, Conformation-Switching Ribozymes. PLoS Computational Biology, 5(12), e1000620. doi:10.1371/journal.pcbi.1000620Quarta, G., Sin, K., & Schlick, T. (2012). Dynamic Energy Landscapes of Riboswitches Help Interpret Conformational Rearrangements and Function. PLoS Computational Biology, 8(2), e1002368. doi:10.1371/journal.pcbi.1002368Freeman, J. B., & Dale, R. (2012). Assessing bimodality to detect the presence of a dual cognitive process. Behavior Research Methods, 45(1), 83-97. doi:10.3758/s13428-012-0225-xWieland, M., Benz, A., Klauser, B., & Hartig, J. S. (2009). Artificial Ribozyme Switches Containing Natural Riboswitch Aptamer Domains. Angewandte Chemie International Edition, 48(15), 2715-2718. doi:10.1002/anie.200805311Penchovsky, R., & Breaker, R. R. (2005). Computational design and experimental validation of oligonucleotide-sensing allosteric ribozymes. Nature Biotechnology, 23(11), 1424-1433. doi:10.1038/nbt1155Chushak, Y., & Stone, M. O. (2009). In silico selection of RNA aptamers. Nucleic Acids Research, 37(12), e87-e87. doi:10.1093/nar/gkp408Bartel, D., & Szostak, J. (1993). Isolation of new ribozymes from a large pool of random sequences [see comment]. Science, 261(5127), 1411-1418. doi:10.1126/science.7690155Lutz, 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/25.6.1203Mutalik, V. K., Qi, L., Guimaraes, J. C., Lucks, J. B., & Arkin, A. P. (2012). Rationally designed families of orthogonal RNA regulators of translation. Nature Chemical Biology, 8(5), 447-454. doi:10.1038/nchembio.919Bennett, M. R., & Hasty, J. (2009). Microfluidic devices for measuring gene network dynamics in single cells. Nature Reviews Genetics, 10(9), 628-638. doi:10.1038/nrg2625Cookson, N. A., Mather, W. H., Danino, T., Mondragón‐Palomino, O., Williams, R. J., Tsimring, L. S., & Hasty, J. (2011). Queueing up for enzymatic processing: correlated signaling through coupled degradation. Molecular Systems Biology, 7(1), 561. doi:10.1038/msb.2011.94Hermann, T. (2000). Adaptive Recognition by Nucleic Acid Aptamers. Science, 287(5454), 820-825. doi:10.1126/science.287.5454.820Lou, C., Stanton, B., Chen, Y.-J., Munsky, B., & Voigt, C. A. (2012). Ribozyme-based insulator parts buffer synthetic circuits from genetic context. Nature Biotechnology, 30(11), 1137-1142. doi:10.1038/nbt.2401Qi, L., Haurwitz, R. E., Shao, W., Doudna, J. A., & Arkin, A. P. (2012). RNA processing enables predictable programming of gene expression. Nature Biotechnology, 30(10), 1002-1006. doi:10.1038/nbt.2355Liu, C. C., Qi, L., Lucks, J. B., Segall-Shapiro, T. H., Wang, D., Mutalik, V. K., & Arkin, A. P. (2012). An adaptor from translational to transcriptional control enables predictable assembly of complex regulation. Nature Methods, 9(11), 1088-1094. doi:10.1038/nmeth.2184Qi, L. S., Larson, M. H., Gilbert, L. A., Doudna, J. A., Weissman, J. S., Arkin, A. P., & Lim, W. A. (2013). Repurposing CRISPR as an RNA-Guided Platform for Sequence-Specific Control of Gene Expression. Cell, 152(5), 1173-1183. doi:10.1016/j.cell.2013.02.022Gilbert, L. A., Larson, M. H., Morsut, L., Liu, Z., Brar, G. A., Torres, S. E., … Qi, L. S. (2013). CRISPR-Mediated Modular RNA-Guided Regulation of Transcription in Eukaryotes. Cell, 154(2), 442-451. doi:10.1016/j.cell.2013.06.044Bashor, C. J., Horwitz, A. A., Peisajovich, S. G., & Lim, W. A. (2010). Rewiring Cells: Synthetic Biology as a Tool to Interrogate the Organizational Principles of Living Systems. Annual Review of Biophysics, 39(1), 515-537. doi:10.1146/annurev.biophys.050708.133652Yen, L., Svendsen, J., Lee, J.-S., Gray, J. T., Magnier, M., Baba, T., … Mulligan, R. C. (2004). Exogenous control of mammalian gene expression through modulation of RNA self-cleavage. Nature, 431(7007), 471-476. doi:10.1038/nature0284