Abstract
One ultimate goal for synthetic biology is the complete computer-aided design of novel gene circuits. Here, we show how concepts and algorithms from electrical engineering can be exploited to set up a framework for the computational, automatic design of gene Boolean gates and devices. As in electrical engineering, the modular design of digital synthetic gene circuits can be automated via the Karnaugh map algorithm. However, differently from electronics, the circuit scheme corresponding to a Boolean formula is not unique since the wiring between gates can be established by transcription factors or small RNAs. In particular, we discuss a new, simplified version of our previous algorithm that is better tailored to wet-lab circuit implementation.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Andrianantoandro E, Basu S, Karig DK, Weiss R (2006) Synthetic biology: new engineering rules for an emerging discipline. Mol Syst Biol 2:2006.0028. doi:10.1038/msb4100073. http://dx.doi.org/10.1038/msb4100073
Hans-Michael K, Stelling J (2012) Modular analysis of biological networks. Adv Exp Med Biol 736:3–17
Marchisio MA, Stelling J (2011) Automatic design of digital synthetic gene circuits. PLoS Comput Biol 7(2):e1001083. doi:10.1371/journal.pcbi.1001083. http://dx.doi.org/10.1371/journal.pcbi.1001083
Endy D (2005) Foundations for engineering biology. Nature 438(7067):449–453. doi:10.1038/nature04342. http://dx.doi.org/10.1038/nature04342
Marchisio MA, Stelling J (2008) Computational design of synthetic gene circuits with composable parts. Bioinformatics, 24(17):1903–1910. doi:10.1093/bioinformatics/btn330. http://dx.doi.org/10.1093/bioinformatics/btn330
Marchisio MA, Stelling J (2009) Synthetic gene network computational design. In: Proceedings of IEEE international symposium on circuits and systems, ISCAS 2009, pp 309–312
Ginkel M, Kremling A, Nutsch T, Rehner R, Gilles ED (2003) Modular modeling of cellular systems with ProMoT/Diva. Bioinformatics 19(9):1169–1176
Mirschel S, Steinmetz K, Rempel M, Ginkel M, Gilles ED (2009) PROMOT: modular modeling for systems biology. Bioinformatics 25(5):687–689. doi:10.1093/bioinformatics/btp029. http://dx.doi.org/10.1093/bioinformatics/btp029
Alon U (2007) Network motifs: theory and experimental approaches. Nat Rev Genet 8(6):450–461. doi:10.1038/nrg2102. http://dx.doi.org/10.1038/nrg2102
Dasika MS, Maranas CD (2008) OptCircuit: an optimization based method for computational design of genetic circuits. BMC Syst Biol 2:24. doi:10.1186/1752-0509-2-24. http://dx.doi.org/10.1186/1752-0509-2-24
François P, Hakim V (2004) Design of genetic networks with specified functions by evolution in silico. Proc Natl Acad Sci U S A 101(2):580–585. doi:10.1073/pnas.0304532101. http://dx.doi.org/10.1073/pnas.0304532101
Paladugu SR, Chickarmane V, Deckard A, Frumkin JP, McCormack M, Sauro HM (2006) In silico evolution of functional modules in biochemical networks. Syst Biol (Stevenage) 153(4):223–235
Rodrigo G, Carrera J, Jaramillo A (2007) Genetdes: automatic design of transcriptional networks. Bioinformatics 23(14):1857–1858. doi:10.1093/bioinformatics/btm237. http://dx.doi.org/10.1093/bioinformatics/btm237
Maurice K (1953) The map method for synthesis of combinational logic circuits. Trans Am Inst Electr Eng 72(9):593–599
Regot S, Macia J, Conde N, Furukawa K, Kjelln J, Peeters T, Hohmann S, de Nadal EL, Posas F, Sol R (2011) Distributed biological computation with multicellular engineered networks. Nature 469(7329):207–211. doi:10.1038/nature09679. http://dx.doi.org/10.1038/nature09679
Kuphaldt TR (2007) Lessons in electric circuits ,Vol 4(Digital). http://www.ibiblio.org/obp/electricCircuits
Terzer M, Jovanovic M, Choutko A, Nikolayeva O, Korn A, Brockhoff D, Zurcher F, Friedmann M, Schutz R, Zitzler E, Stelling J, Panke S (2007) Design of a biological half adder. IET Synth Biol 1(1–2):53–58
Bintu L, Buchler NE, Garcia HG, Gerland U, Hwa T, Kondev J, Kuhlman T, Phillips R (2005) Transcriptional regulation by the numbers: applications. Curr Opin Genet Dev 15(2):125–135. doi:10.1016/j.gde.2005.02.006. http://dx.doi.org/10.1016/j.gde.2005.02.006
Silva-Rocha R, de Lorenzo V (2008) Mining logic gates in prokaryotic transcriptional regulation networks. FEBS Lett 582(8):1237–1244. doi:10.1016/j.febslet.2008.01.060. http://dx.doi.org/10.1016/j.febslet.2008.01.060
Win MN, Smolke CD (2008) Higher-order cellular information processing with synthetic RNA devices. Science 322(5900):456–460. doi:10.1126/science.1160311. http://dx.doi.org/10.1126/science.1160311
Lucks JB, Qi L, Mutalik VK, Wang D, Arkin AP (2011) Versatile RNA-sensing transcriptional regulators for engineering genetic networks. Proc Natl Acad Sci U S A 108(21):8617–8622. doi:10.1073/pnas.1015741108. http://dx.doi.org/10.1073/pnas.1015741108
Rinaudo K, Bleris L, Maddamsetti R, Subramanian S, Weiss R, Benenson Y (2007) A universal RNAi-based logic evaluator that operates in mammalian cells. Nat Biotechnol 25(7):795–801. doi:10.1038/nbt1307. http://dx.doi.org/10.1038/nbt1307
Lewin B (2000) Genes VII. Oxford University Press, New York
Isaacs FJ, Dwyer DJ, Collins JJ (2006) RNA synthetic biology. Nat Biotechnol 24(5):545–554. doi:10.1038/nbt1208. http://dx.doi.org/10.1038/nbt1208
Purnick PEM, Weiss R (2009) The second wave of synthetic biology: from modules to systems. Nat Rev Mol Cell Biol 10(6):410–422. doi:10.1038/nrm2698. http://dx.doi.org/10.1038/nrm2698
Lohmueller JJ, Armel TZ, Silver PA (2012) A tunable zinc finger-based framework for Boolean logic computation in mammalian cells. Nucleic Acids Res. doi:10.1093/nar/gks142. http://dx.doi.org/10.1093/nar/gks142
Bogdanove AJ, Voytas DF (2011) TAL effectors: customizable proteins for DNA targeting. Science 333(6051):1843–1846. doi:10.1126/science.1204094. http://dx.doi.org/10.1126/science.1204094
Hucka M et al (Mar 2003) The systems biology markup language (SBML): a medium for representation and exchange of biochemical network models. Bioinformatics 19(4):524–531
Benenson Y (2012) Biomolecular computing systems: principles, progress and potential. Nat Rev Genet 13(7):455–468. doi:10.1038/nrg3197. http://dx.doi.org/10.1038/nrg3197
Marchisio MA, Rudolf F (2011) Synthetic biosensing systems. Int J Biochem Cell Biol 43(3):310–319. doi:10.1016/j.biocel.2010.11.012. http://dx.doi.org/10.1016/j.biocel.2010.11.012
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer Science+Business Media Dordrecht
About this chapter
Cite this chapter
Marchisio, M.A., Stelling, J. (2014). Simplified Computational Design of Digital Synthetic Gene Circuits. In: Kulkarni, V., Stan, GB., Raman, K. (eds) A Systems Theoretic Approach to Systems and Synthetic Biology II: Analysis and Design of Cellular Systems. Springer, Dordrecht. https://doi.org/10.1007/978-94-017-9047-5_11
Download citation
DOI: https://doi.org/10.1007/978-94-017-9047-5_11
Published:
Publisher Name: Springer, Dordrecht
Print ISBN: 978-94-017-9046-8
Online ISBN: 978-94-017-9047-5
eBook Packages: Biomedical and Life SciencesBiomedical and Life Sciences (R0)