Abstract
A central goal of synthetic biology is to achieve multi-signal integration and processing in living cells for diagnostic, therapeutic and biotechnology applications1. Digital logic has been used to build small-scale circuits, but other frameworks may be needed for efficient computation in the resource-limited environments of cells2,3. Here we demonstrate that synthetic analog gene circuits can be engineered to execute sophisticated computational functions in living cells using just three transcription factors. Such synthetic analog gene circuits exploit feedback to implement logarithmically linear sensing, addition, ratiometric and power-law computations. The circuits exhibit Weber’s law behaviour as in natural biological systems4, operate over a wide dynamic range of up to four orders of magnitude and can be designed to have tunable transfer functions. Our circuits can be composed to implement higher-order functions that are well described by both intricate biochemical models and simple mathematical functions. By exploiting analog building-block functions that are already naturally present in cells3,5, this approach efficiently implements arithmetic operations and complex functions in the logarithmic domain. Such circuits may lead to new applications for synthetic biology and biotechnology that require complex computations with limited parts, need wide-dynamic-range biosensing or would benefit from the fine control of gene expression.
This is a preview of subscription content, access via your institution
Access options
Subscribe to this journal
Receive 51 print issues and online access
$199.00 per year
only $3.90 per issue
Buy this article
- Purchase on Springer Link
- Instant access to full article PDF
Prices may be subject to local taxes which are calculated during checkout
Similar content being viewed by others
References
Chen, Y. Y., Galloway, K. E. & Smolke, C. D. Synthetic biology: advancing biological frontiers by building synthetic systems. Genome Biol. 13, 240 (2012)
Cardinale, S. & Arkin, A. P. Contextualizing context for synthetic biology: identifying causes of failure of synthetic biological systems. Biotechnol. J. 7, 856–866 (2012)
Sarpeshkar, R. Analog versus digital: extrapolating from electronics to neurobiology. Neural Comput. 10, 1601–1638 (1998)
Ferrell, J. E. Signaling motifs and Weber’s law. Mol. Cell 36, 724–727 (2009)
Sarpeshkar, R. Ultra Low Power Bioelectronics: Fundamentals, Biomedical Applications, and Bio-Inspired Systems 651–694, 753–786 (Cambridge Univ. Press, 2010)
Sprinzak, D. et al. Cis-interactions between Notch and Delta generate mutually exclusive signalling states. Nature 465, 86–90 (2010)
Canton, B., Labno, A. & Endy, D. Refinement and standardization of synthetic biological parts and devices. Nature Biotechnol. 26, 787–793 (2008)
Giorgetti, L. et al. Noncooperative interactions between transcription factors and clustered DNA binding sites enable graded transcriptional responses to environmental inputs. Mol. Cell 37, 418–428 (2010)
Clark, B. & Hausser, M. Neural coding: hybrid analog and digital signalling in axons. Curr. Biol. 16, R585–R588 (2006)
Daniel, R., Woo, S. S., Turicchia, L. & Sarpeshkar, R. in Biomedical Circuits and Systems Conference (BioCAS 2011) 333–336 (IEEE, 2011)
Tavakoli, M. & Sarpeshkar, R. A sinh resistor and its application to tanh linearization. IEEE J. Solid-State Circuits 40, 536–543 (2005)
Wild, J., Hradecna, Z. & Szybalski, W. Conditionally amplifiable BACs: switching from single-copy to high-copy vectors and genomic clones. Genome Res. 12, 1434–1444 (2002)
Qian, L. & Winfree, E. Scaling up digital circuit computation with DNA strand displacement cascades. Science 332, 1196–1201 (2011)
Stricker, J. et al. A fast, robust and tunable synthetic gene oscillator. Nature 456, 516–519 (2008)
Elowitz, M. B. & Leibler, S. A synthetic oscillatory network of transcriptional regulators. Nature 403, 335–338 (2000)
McMillen, D., Kopell, N., Hasty, J. & Collins, J. J. Synchronizing genetic relaxation oscillators by intercell signaling. Proc. Natl Acad. Sci. USA 99, 679–684 (2002)
Madar, D., Dekel, E., Bren, A. & Alon, U. Negative auto-regulation increases the input dynamic-range of the arabinose system of Escherichia coli. BMC Syst. Biol. 5, 111 (2011)
Nevozhay, D., Adams, R. M., Murphy, K. F., Josić, K. & Balázsi, G. Negative autoregulation linearizes the dose–response and suppresses the heterogeneity of gene expression. Proc. Natl Acad. Sci. USA 106, 5123–5128 (2009)
Shen-Orr, S. S., Milo, R., Mangan, S. & Alon, U. Network motifs in the transcriptional regulation network of Escherichia coli. Nature Genet. 31, 64–68 (2002)
You, L., Cox, R. S., Weiss, R. & Arnold, F. H. Programmed population control by cell–cell communication and regulated killing. Nature 428, 868–871 (2004)
Tabor, J. J. et al. A synthetic genetic edge detection program. Cell 137, 1272–1281 (2009)
Tamsir, A., Tabor, J. J. & Voigt, C. A. Robust multicellular computing using genetically encoded NOR gates and chemical ‘wires’. Nature 469, 212–215 (2011)
Auslander, S., Auslander, D., Muller, M., Wieland, M. & Fussenegger, M. Programmable single-cell mammalian biocomputers. Nature 487, 123–127 (2012)
Isaacs, F. J. et al. Engineered riboregulators enable post-transcriptional control of gene expression. Nature Biotechnol. 22, 841–847 (2004)
Win, M. N. & Smolke, C. D. Higher-order cellular information processing with synthetic RNA devices. Science 322, 456–460 (2008)
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)
Khalil, A. et al. A synthetic biology framework for programming eukaryotic transcription functions. Cell 150, 647–658 (2012)
Dueber, J. E., Yeh, B. J., Chak, K. & Lim, W. A. Reprogramming control of an allosteric signaling switch through modular recombination. Science 301, 1904–1908 (2003)
Hahnloser, R. H. R., Sarpeshkar, R., Mahowald, M. A., Douglas, R. J. & Seung, H. S. Digital selection and analogue amplification coexist in a cortex-inspired silicon circuit. Nature 405, 947–951 (2000)
Lu, T. K., Khalil, A. S. & Collins, J. J. Next-generation synthetic gene networks. Nature Biotechnol. 27, 1139–1150 (2009)
Acknowledgements
We would like to thank J. Nungesser for assistance with figures and members of the Lu and Sarpeshkar laboratories for discussions. This work was supported in part by a campus collaboration initiative from Lincoln Labs (R.D. and R.S.), the US National Science Foundation (R.D., J.R.R., R.S. and T.K.L.) under grant number 1124247, and the Office of Naval Research (J.R.R. and T.K.L.) under grant number N000141110725.
Author information
Authors and Affiliations
Contributions
R.D., R.S. and T.K.L. designed the study. R.D. and J.R.R. performed experiments and collected data. R.D., J.R.R., R.S. and T.K.L. invented the analog circuit motifs. R.D., R.S. and T.K.L. developed the analog circuit motifs and associated models and simulations. All authors analysed the data, discussed results and wrote the manuscript.
Corresponding authors
Ethics declarations
Competing interests
Massachusetts Institute of Technology, with which all the authors are affiliated, has filed a PCT patent application based on this work.
Supplementary information
Supplementary Information
This file contains Supplementary Text and Data, Supplementary Figures 1-53, Supplementary Tables 1-4, and Supplementary References (see Table of Contents for more details). (PDF 6125 kb)
Rights and permissions
About this article
Cite this article
Daniel, R., Rubens, J., Sarpeshkar, R. et al. Synthetic analog computation in living cells. Nature 497, 619–623 (2013). https://doi.org/10.1038/nature12148
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1038/nature12148
This article is cited by
-
A hybrid transistor with transcriptionally controlled computation and plasticity
Nature Communications (2024)
-
Customizing cellular signal processing by synthetic multi-level regulatory circuits
Nature Communications (2023)
-
Inducible plasmid copy number control for synthetic biology in commonly used E. coli strains
Nature Communications (2022)
-
Low-cost anti-mycobacterial drug discovery using engineered E. coli
Nature Communications (2022)
-
Synthetic neuromorphic computing in living cells
Nature Communications (2022)
Comments
By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.