Synthetic mixed-signal computation in living cells
Jacob R. Rubens, Gianluca Selvaggio & Timothy K. Lu
Nature Communications 7, Article number: 11658 (2016)
Download Citation
Biological techniques Computational biology and bioinformatics
Received: 04 September 2015 Accepted: 18 April 2016 Published online: 03 June 2016
Source/Fonte: MIT - Liang Zong and Yan Liang
Abstract
Living cells implement complex computations on the continuous environmental signals that they encounter. These computations involve both analogue- and digital-like processing of signals to give rise to complex developmental programs, context-dependent behaviours and homeostatic activities. In contrast to natural biological systems, synthetic biological systems have largely focused on either digital or analogue computation separately. Here we integrate analogue and digital computation to implement complex hybrid synthetic genetic programs in living cells. We present a framework for building comparator gene circuits to digitize analogue inputs based on different thresholds. We then demonstrate that comparators can be predictably composed together to build band-pass filters, ternary logic systems and multi-level analogue-to-digital converters. In addition, we interface these analogue-to-digital circuits with other digital gene circuits to enable concentration-dependent logic. We expect that this hybrid computational paradigm will enable new industrial, diagnostic and therapeutic applications with engineered cells.
Acknowledgements
We would like to thank members of the Lu Lab, the MIT Microbiology Program and the MIT Synthetic Biology Center for their feedback. We thank the staff at the Koch Institute Flow Cytometry Core for their assistance in flow cytometry and Quintara Biosciences for DNA sequencing service. J.R.R. was supported by an NSF Graduate Research Fellowship. G.S. was supported by a ‘FCT, Fundação para a Ciência e a Tecnologia’ fellowship (#SFRH/BD/51576/2011). This work was supported by the National Science Foundation (#1350625 and #1124247), the Office of Naval Research (#N000141310424), an NIH New Innovator Award (#1DP2OD008435) and the NIH National Centers for Systems Biology (#1P50GM098792).
Author information
Affiliations
1Synthetic Biology Group, MIT Synthetic Biology Center, Research Laboratory of Electronics, Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA
Jacob R. Rubens, Gianluca Selvaggio & Timothy K. Lu
Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA
Jacob R. Rubens, Gianluca Selvaggio & Timothy K. Lu
Microbiology Program, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA
Jacob R. Rubens & Timothy K. Lu
Computational and System Biology Group, Centre for Neuroscience and Cell Biology, University of Coimbra, 3004-517 Coimbra, Portugal
Gianluca Selvaggio
The Center for Microbiome Informatics and Therapeutics, Cambridge, Massachusetts 02139, USA
Timothy K. Lu
Contributions
J.R.R. and T.K.L. conceived the study. J.R.R. and G.S. performed the experiments and collected the data. All authors analysed the data, discussed the results and wrote the manuscript.
Competing interests
J.R.R., G.S. and T.K.L. have filed a provisional patent application based on this work (‘Analogue to Digital Computations in Biological Systems’, PCT/US2015/067381).
Corresponding author
Correspondence to Timothy K. Lu.
