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Quantitative estimation of activity and quality for collections of functional genetic elements

Abstract

The practice of engineering biology now depends on the ad hoc reuse of genetic elements whose precise activities vary across changing contexts. Methods are lacking for researchers to affordably coordinate the quantification and analysis of part performance across varied environments, as needed to identify, evaluate and improve problematic part types. We developed an easy-to-use analysis of variance (ANOVA) framework for quantifying the performance of genetic elements. For proof of concept, we assembled and analyzed combinations of prokaryotic transcription and translation initiation elements in Escherichia coli. We determined how estimation of part activity relates to the number of unique element combinations tested, and we show how to estimate expected ensemble-wide part activity from just one or two measurements. We propose a new statistic, biomolecular part 'quality', for tracking quantitative variation in part performance across changing contexts.

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Figure 1: Composition of irregular transcription and translation genetic elements.
Figure 2: Observed variation and correlation of mRNA abundance and protein fluorescence from a full combinatorial library of expression control elements.
Figure 3: Quantification of factors and interactions contributing to variation in mRNA abundance, translation efficiency and gene expression.
Figure 4: Performance and quality scores for transcriptional and translation control elements.
Figure 5: Estimation of part activity with limited measurements.

References

  1. Dubendorff, J.W. & Studier, F.W. Controlling basal expression in an inducible T7 expression system by blocking the target T7 promoter with lac repressor. J. Mol. Biol. 219, 45–59 (1991).

    Article  CAS  PubMed  Google Scholar 

  2. Mertens, N., Remaut, E. & Fiers, W. Tight transcriptional control mechanism ensures stable high-level expression from T7 promoter-based expression plasmids. Bio/Technology 13, 175–179 (1995).

    CAS  Google Scholar 

  3. Xie, Z., Wroblewska, L., Prochazka, L., Weiss, R. & Benenson, Y. Multi-input RNAi-based logic circuit for identification of specific cancer cells. Science 333, 1307–1311 (2011).

    Article  CAS  PubMed  Google Scholar 

  4. Chen, Y.Y., Jensen, M.C. & Smolke, C.D. Genetic control of mammalian T-cell proliferation with synthetic RNA regulatory systems. Proc. Natl. Acad. Sci. USA 107, 8531–8536 (2010).

    Article  PubMed  PubMed Central  Google Scholar 

  5. Anderson, J.C., Clarke, E.J., Arkin, A.P. & Voigt, C.A. Environmentally controlled invasion of cancer cells by engineered bacteria. J. Mol. Biol. 355, 619–627 (2006).

    Article  CAS  PubMed  Google Scholar 

  6. Saeidi, N. et al. Engineering microbes to sense and eradicate Pseudomonas aeruginosa, a human pathogen. Mol. Syst. Biol. 7, 521 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Widmaier, D.M. et al. Engineering the Salmonella type III secretion system to export spider silk monomers. Mol. Syst. Biol. 5, 309 (2009).

    Article  PubMed  PubMed Central  Google Scholar 

  8. Bonnet, J., Subsoontorn, P. & Endy, D. Rewritable digital data storage in live cells via engineered control of recombination directionality. Proc. Natl. Acad. Sci. USA 109, 8884–8889 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Ruder, W.C., Lu, T. & Collins, J.J. Synthetic biology moving into the clinic. Science 333, 1248–1252 (2011).

    Article  CAS  PubMed  Google Scholar 

  10. Sinha, J., Reyes, S.J. & Gallivan, J.P. Reprogramming bacteria to seek and destroy an herbicide. Nat. Chem. Biol. 6, 464–470 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Keasling, J.D. Manufacturing molecules through metabolic engineering. Science 330, 1355–1358 (2010).

    Article  CAS  PubMed  Google Scholar 

  12. Carr, P.A. & Church, G.M. Genome engineering. Nat. Biotechnol. 27, 1151–1162 (2009).

    Article  CAS  PubMed  Google Scholar 

  13. Endy, D. Foundations for engineering biology. Nature 438, 449–453 (2005).

    CAS  PubMed  Google Scholar 

  14. Cambray, G., Mutalik, V.K. & Arkin, A.P. Toward rational design of bacterial genomes. Curr. Opin. Microbiol. 14, 624–630 (2011).

    Article  CAS  PubMed  Google Scholar 

  15. Cardinale, S. & Arkin, A.P. Contextualizing context for synthetic biology—identifying causes of failure of synthetic biological systems. Biotechnol. J. 7, 856–866 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Wilkinson, B. & Micklefield, J. Mining and engineering natural-product biosynthetic pathways. Nat. Chem. Biol. 3, 379–386 (2007).

    Article  CAS  PubMed  Google Scholar 

  17. Canton, B., Labno, A. & Endy, D. Refinement and standardization of synthetic biological parts and devices. Nat. Biotechnol. 26, 787–793 (2008).

    Article  CAS  PubMed  Google Scholar 

  18. Smolke, C.D. Building outside of the box: iGEM and the BioBricks Foundation. Nat. Biotechnol. 27, 1099–1102 (2009).

    Article  CAS  PubMed  Google Scholar 

  19. Gulvanessian, H. & Holicky, M. Eurocodes: using reliability analysis to combine action effects. Proceedings of the ICE - Structures and Buildings 158, 243–252 (2005).

    Article  Google Scholar 

  20. Mutalik, V.K., Nonaka, G., Ades, S.E., Rhodius, V.A. & Gross, C.A. Promoter strength properties of the complete sigma E regulon of Escherichia coli and Salmonella enterica. J. Bacteriol. 191, 7279–7287 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Hook-Barnard, I.G. & Hinton, D.M. Transcription initiation by mix and match elements: flexibility for polymerase binding to bacterial promoters. Gene Regul. Syst. Bio. 1, 275–293 (2007).

    PubMed  PubMed Central  Google Scholar 

  22. Shimada, T. et al. Classification and strength measurement of stationary-phase promoters by use of a newly developed promoter cloning vector. J. Bacteriol. 186, 7112–7122 (2004).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Zaslaver, A. et al. A comprehensive library of fluorescent transcriptional reporters for Escherichia coli. Nat. Methods 3, 623–628 (2006).

    Article  CAS  PubMed  Google Scholar 

  24. Babiskin, A.H. & Smolke, C.D. Synthetic RNA modules for fine-tuning gene expression levels in yeast by modulating RNase III activity. Nucleic Acids Res. 39, 8651–8664 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Yarchuk, O., Jacques, N., Guillerez, J. & Dreyfus, M. Interdependence of translation, transcription and mRNA degradation in the lacZ gene. J. Mol. Biol. 226, 581–596 (1992).

    Article  CAS  PubMed  Google Scholar 

  26. Cho, K.O. & Yanofsky, C. Sequence changes preceding a Shine-Dalgarno region influence trpE mRNA translation and decay. J. Mol. Biol. 204, 51–60 (1988).

    Article  CAS  PubMed  Google Scholar 

  27. Telesnitsky, A.P.W. & Chamberlin, M.J. Sequences linked to prokaryotic promoters can affect the efficiency of downstream termination sites. J. Mol. Biol. 205, 315–330 (1989).

    Article  CAS  PubMed  Google Scholar 

  28. Ellinger, T., Behnke, D., Knaus, R., Bujard, H. & Gralla, J.D. Context-dependent effects of upstream A-tracts - stimulation or inhibition of Escherichia coli promoter function. J. Mol. Biol. 239, 466–475 (1994).

    Article  CAS  PubMed  Google Scholar 

  29. Stueber, D. & Bujard, H. Transcription from efficient promoters can interfere with plasmid replication and diminish expression of plasmid specified genes. EMBO J. 1, 1399–1404 (1982).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Barrick, D. et al. Quantitative analysis of ribosome binding sites in E.coli. Nucleic Acids Res. 22, 1287–1295 (1994).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Cox, R.S. III, Surette, M.G. & Elowitz, M.B. Programming gene expression with combinatorial promoters. Mol. Syst. Biol. 3, 145 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Alper, H., Fischer, C., Nevoigt, E. & Stephanopoulos, G. Tuning genetic control through promoter engineering. Proc. Natl. Acad. Sci. USA 102, 12678–12683 (2005).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Ellis, T., Wang, X. & Collins, J.J. Diversity-based, model-guided construction of synthetic gene networks with predicted functions. Nat. Biotechnol. 27, 465–471 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Reynolds, R. & Chamberlin, M.J. Parameters affecting transcription termination by Escherichia coli RNA: II. Construction and analysis of hybrid terminators. J. Mol. Biol. 224, 53–63 (1992).

    Article  CAS  PubMed  Google Scholar 

  35. Carrier, T.A. & Keasling, J.D. Library of synthetic 5′ secondary structures to manipulate mRNA stability in Escherichia coli. Biotechnol. Prog. 15, 58–64 (1999).

    Article  CAS  PubMed  Google Scholar 

  36. Salis, H.M., Mirsky, E.A. & Voigt, C.A. Automated design of synthetic ribosome binding sites to control protein expression. Nat. Biotechnol. 27, 946–950 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Mutalik, V.K., Qi, L., Guimaraes, J.C., Lucks, J.B. & Arkin, A.P. Rationally designed families of orthogonal RNA regulators of translation. Nat. Chem. Biol. 8, 447–454 (2012).

    Article  CAS  PubMed  Google Scholar 

  38. Khalil, A.S. et al. A synthetic biology framework for programming eukaryotic transcription functions. Cell 150, 647–658 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Purnick, P.E. & Weiss, R. The second wave of synthetic biology: from modules to systems. Nat. Rev. Mol. Cell Biol. 10, 410–422 (2009).

    Article  CAS  PubMed  Google Scholar 

  40. de Smit, M.H. & van Duin, J. Control of translation by mRNA secondary structure in Escherichia coli. A quantitative analysis of literature data. J. Mol. Biol. 244, 144–150 (1994).

    Article  CAS  PubMed  Google Scholar 

  41. Jonsson, J., Norberg, T., Carlsson, L., Gustafsson, C. & Wold, S. Quantitative sequence-activity models (QSAM)—tools for sequence design. Nucleic Acids Res. 21, 733–739 (1993).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Yager, T.D. & von Hippel, P.H. A thermodynamic analysis of RNA transcript elongation and termination in Escherichia coli. Biochemistry 30, 1097–1118 (1991).

    Article  CAS  PubMed  Google Scholar 

  43. Davis, J.H., Rubin, A.J. & Sauer, R.T. Design, construction and characterization of a set of insulated bacterial promoters. Nucleic Acids Res. 39, 1131–1141 (2011).

    Article  CAS  PubMed  Google Scholar 

  44. Qi, L., Haurwitz, R.E., Shao, W., Doudna, J.A. & Arkin, A.P. RNA processing enables predictable programming of gene expression. Nat. Biotechnol. 30, 1002–1006 (2012).

    Article  CAS  PubMed  Google Scholar 

  45. Lou, C., Stanton, B., Chen, Y.J., Munsky, B. & Voigt, C.A. Ribozyme-based insulator parts buffer synthetic circuits from genetic context. Nat. Biotechnol. 30, 1137–1142 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Klumpp, S., Zhang, Z. & Hwa, T. Growth rate-dependent global effects on gene expression in bacteria. Cell 139, 1366–1375 (2009).

    Article  PubMed  PubMed Central  Google Scholar 

  47. Mutalik, V.K. et al. Precise and reliable gene expression via standard transcription and translation initiation elements. Nat. Methods advance online publication, doi:10.1038/nmeth.2404 (10 March 2013).

  48. Kelly, J.R. et al. Measuring the activity of BioBrick promoters using an in vivo reference standard. J. Biol. Eng. 3, 4 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Kittleson, J.T., Wu, G.C. & Anderson, J.C. Successes and failures in modular genetic engineering. Curr. Opin. Chem. Biol. 16, 329–336 (2012).

    Article  CAS  PubMed  Google Scholar 

  50. Wu, C.F.J. & Hamada, M.S. Experiments: Planning, Analysis, and Optimization, 2nd edn (Wiley, Hoboken, New Jersey, USA, 2009).

  51. Ausubel, F.M. Short Protocols in Molecular Biology, 5th edn (Wiley, New York, 2002).

  52. Engler, C., Kandzia, R. & Marillonnet, S. A one pot, one step, precision cloning method with high throughput capability. PLoS ONE 3, e3647 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. Hillson, N.J., Rosengarten, R.D. & Keasling, J.D. j5 DNA assembly design automation software. ACS Synth. Biol. 1, 14–21 (2012).

    Article  CAS  PubMed  Google Scholar 

  54. Pédelacq, J.D., Cabantous, S., Tran, T., Terwilliger, T.C. & Waldo, G.S. Engineering and characterization of a superfolder green fluorescent protein. Nat. Biotechnol. 24, 79–88 (2006).

    Article  CAS  PubMed  Google Scholar 

  55. Campbell, R.E. et al. A monomeric red fluorescent protein. Proc. Natl. Acad. Sci. USA 99, 7877–7882 (2002).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  56. Lee, T.S. et al. BglBrick vectors and datasheets: a synthetic biology platform for gene expression. J. Biol. Eng. 5, 12 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  57. Haldimann, A. & Wanner, B.L. Conditional-replication, integration, excision, and retrieval plasmid-host systems for gene structure-function studies of bacteria. J. Bacteriol. 183, 6384–6393 (2001).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  58. Lutz, R. & Bujard, H. 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 Res. 25, 1203–1210 (1997).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  59. Baba, T. et al. Construction of Escherichia coli K-12 in-frame, single-gene knockout mutants: the Keio collection. Mol. Syst. Biol. 2, 2006.0008 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  60. Leveau, J.H. & Lindow, S.E. Predictive and interpretive simulation of green fluorescent protein expression in reporter bacteria. J. Bacteriol. 183, 6752–6762 (2001).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  61. Iizuka, R., Yamagishi-Shirasaki, M. & Funatsu, T. Kinetic study of de novo chromophore maturation of fluorescent proteins. Anal. Biochem. 414, 173–178 (2011).

    Article  CAS  PubMed  Google Scholar 

  62. Lo, K., Hahne, F., Brinkman, R.R. & Gottardo, R. flowClust: a Bioconductor package for automated gating of flow cytometry data. BMC Bioinformatics 10, 145 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  63. Kerr, M.K. & Churchill, G.A. Experimental design for gene expression microarrays. Biostatistics 2, 183–201 (2001).

    Article  CAS  PubMed  Google Scholar 

  64. Kerr, M.K., Martin, M. & Churchill, G.A. Analysis of variance for gene expression microarray data. J. Comput. Biol. 7, 819–837 (2000).

    Article  CAS  PubMed  Google Scholar 

  65. Ringquist, S. et al. Translation initiation in Escherichia coli: sequences within the ribosome-binding site. Mol. Microbiol. 6, 1219–1229 (1992).

    Article  CAS  PubMed  Google Scholar 

  66. Shearwin, K.E., Callen, B.P. & Egan, J.B. Transcriptional interference—a crash course. Trends Genet. 21, 339–345 (2005).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

We thank N. Hillson, V. Rhodius and C. Smolke for comments and discussion, and F. St-Pierre (Stanford University) for the plasmid pIT-KL-I52002. We acknowledge support from the National Science Foundation to the BIOFAB (award EEC 0946510). G.C. acknowledges support from the Human Frontier Science Program (LT000873/2011-l) and the Bettencourt Schueller foundation. A.P.A. and D.E. acknowledge support from the Synthetic Biology Engineering Research Center under National Science Foundation grant 04-570/0540879. J.C.G. acknowledges financial support from the Portuguese Fundação para a Ciência e a Tecnologia (SFRH/BD/47819/2008). This work was conducted at the Joint BioEnergy Institute supported by the Office of Science, Office of Biological and Environmental Research of the US Department of Energy, under contract DE-AC02-05CH11231.

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V.K.M., D.E. and A.P.A. conceived the study; V.K.M., G.C. and Q.-A.M. designed experiments; V.K.M., G.C., Q.-A.M., L.M., A.Y. and C.L. performed experiments; J.C.G. and G.C. built the computational model; V.K.M., G.C., J.C.G., D.E. and A.P.A. analyzed and interpreted the data; C.R. and M.J.C. provided software tools and database support; G.B. provided critical feedback on the framing the project; and V.K.M., J.C.G., G.C., J.D.K., D.E. and A.P.A. wrote the manuscript. All authors discussed and commented on the manuscript.

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Correspondence to Drew Endy or Adam P Arkin.

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The authors declare no competing financial interests.

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Mutalik, V., Guimaraes, J., Cambray, G. et al. Quantitative estimation of activity and quality for collections of functional genetic elements. Nat Methods 10, 347–353 (2013). https://doi.org/10.1038/nmeth.2403

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