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Rationally designed families of orthogonal RNA regulators of translation

Nature Chemical Biology volume 8, pages 447–454 (2012)Cite this article

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Abstract

Our ability to routinely engineer genetic networks for applications is limited by the scarcity of highly specific and non–cross-reacting (orthogonal) gene regulators with predictable behavior. Though antisense RNAs are attractive contenders for this purpose, quantitative understanding of their specificity and sequence-function relationship sufficient for their design has been limited. Here, we use rationally designed variants of the RNA-IN–RNA-OUT antisense RNA–mediated translation system from the insertion sequence IS10 to quantify >500 RNA-RNA interactions in Escherichia coli and integrate the data set with sequence-activity modeling to identify the thermodynamic stability of the duplex and the seed region as the key determinants of specificity. Applying this model, we predict the performance of an additional ∼2,600 antisense-regulator pairs, forecast the possibility of large families of orthogonal mutants, and forward engineer and experimentally validate two RNA pairs orthogonal to an existing group of five from the training data set. We discuss the potential use of these regulators in next-generation synthetic biology applications.

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Figure 1: Schematic of sense RNA-IN and antisense RNA-OUT interaction.
Figure 2: A rationally designed library for finding orthogonal mutants in the RNA-IN/OUT system.
Figure 3: Repression characteristics and estimation of total number of orthogonal pairs in the experimental data set.
Figure 4: The sequence-activity PLSR model and experimental validation of model predictions.

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Acknowledgements

The authors would like to thank G. Cambray, E. Gogol, C. Liu and J. Skerker for comments on the manuscript. V.K.M. was supported by British Petroleum under contract number LB08004883 at the Joint BioEnergy Institute. A.P.A. and L.Q. acknowledge support from the Synthetic Biology Engineering Research Center under US National Science Foundation grant number 04-570/0540879. J.C.G. acknowledges financial support by the Portuguese Fundação para a Ciência e a Tecnologia (SFRH/BD/47819/2008). J.B.L. acknowledges the financial support of the Miller Institute for Basic Scientific Research. This work conducted by the Joint BioEnergy Institute was supported by the Office of Science, Office of Biological and Environmental Research, of the US Department of Energy under Contract No. DE-AC02-05CH11231.

Author information

Author notes

  1. Vivek K Mutalik & Julius B Lucks

    Present address: Present addresses: BioFAB, Joint BioEnergy Institute, Emeryville, California, USA (V.K.M.); School of Chemical and Biomolecular Engineering, Cornell University, Ithaca, New York, USA (J.B.L.).,

  2. Vivek K Mutalik and Lei Qi: These authors contributed equally to this work.

Authors and Affiliations

  1. Physical Biosciences Division, Lawrence Berkeley National Laboratory, Berkeley, California, USA

    Vivek K Mutalik & Adam P Arkin

  2. Joint Bioenergy Institute, Emeryville, California, USA

    Vivek K Mutalik & Adam P Arkin

  3. QB3–California Institute for Quantitative Sciences, Berkeley, California, USA

    Vivek K Mutalik & Adam P Arkin

  4. Department of Bioengineering, University of California, Berkeley, California, USA

    Lei Qi, Joao C Guimaraes, Julius B Lucks & Adam P Arkin

  5. Department of Informatics–Computer Science and Technology Center, University of Minho, Campus de Gualtar, Braga, Portugal.,

    Joao C Guimaraes

  6. Miller Institute for Basic Scientific Research, Berkeley, California, USA

    Julius B Lucks

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Contributions

V.K.M. conceived of the study, designed and performed experiments, built the computational model. L.Q. designed and performed experiments. J.C.G. designed and built the computational model. J.B.L. provided reagents and key insights. A.P.A advised at all levels of the project. V.K.M. and A.P.A. wrote the manuscript. V.K.M., L.Q., J.C.G., J.B.L. and A.P.A. interpreted results, discussed and commented on the manuscript.

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Correspondence to Adam P Arkin.

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The authors declare no competing financial interests.

Supplementary information

Supplementary Text and Figures

Supplementary Methods and Supplementary Results (PDF 13048 kb)

Supplementary Data Set 1

Strains used in this work (XLSX 39 kb)

Supplementary Data Set 2

RNA In / RNA Out, etc. (PDF 3912 kb)

Supplementary Data Set 3

PLS Model input for 23*23 dataset (XLSX 104 kb)

Supplementary Data Set 4

PLS Model input for 56*56 dataset (XLSX 225 kb)

Supplementary Data Set 5

Predicted mutually orthogonal families of translation regulators from predicted repression dataset presented in Supplementary Table 10 (XLSX 240 kb)

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Mutalik, V., Qi, L., Guimaraes, J. et al. Rationally designed families of orthogonal RNA regulators of translation. Nat Chem Biol 8, 447–454 (2012). https://doi.org/10.1038/nchembio.919

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