Synthetic mixed-signal computation in living cells
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 contra...
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| Format: | Article |
| Language: | en_US |
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Nature Publishing Group
2016
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| Online Access: | http://hdl.handle.net/1721.1/103081 https://orcid.org/0000-0003-1304-0151 https://orcid.org/0000-0002-9999-6690 |
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| author | Rubens, Jacob R. Selvaggio, Gianluca Lu, Timothy K. |
| author2 | Massachusetts Institute of Technology. Synthetic Biology Center |
| author_facet | Massachusetts Institute of Technology. Synthetic Biology Center Rubens, Jacob R. Selvaggio, Gianluca Lu, Timothy K. |
| author_sort | Rubens, Jacob R. |
| collection | MIT |
| description | 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. |
| first_indexed | 2024-09-23T12:16:58Z |
| format | Article |
| id | mit-1721.1/103081 |
| institution | Massachusetts Institute of Technology |
| language | en_US |
| last_indexed | 2024-09-23T12:16:58Z |
| publishDate | 2016 |
| publisher | Nature Publishing Group |
| record_format | dspace |
| spelling | mit-1721.1/1030812024-03-20T20:25:30Z Synthetic mixed-signal computation in living cells Rubens, Jacob R. Selvaggio, Gianluca Lu, Timothy K. Massachusetts Institute of Technology. Synthetic Biology Center Massachusetts Institute of Technology. Department of Biological Engineering Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology. Microbiology Graduate Program Massachusetts Institute of Technology. Research Laboratory of Electronics Rubens, Jacob R. Selvaggio, Gianluca Lu, Timothy K. 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. Fundacao para a Ciencia e a Tecnologia (Fellowship SFRH/BD/51576/2011) National Science Foundation (U.S.) (1350625) National Science Foundation (U.S.) (1124247) United States. Office of Naval Research (N000141310424) National Institutes of Health (U.S.) (New Innovator Award 1DP2OD008435) National Centers for Systems Biology (U.S.) (1P50GM098792) 2016-06-09T15:13:34Z 2016-06-09T15:13:34Z 2016-06 2015-09 Article http://purl.org/eprint/type/JournalArticle 2041-1723 http://hdl.handle.net/1721.1/103081 Rubens, Jacob R., Gianluca Selvaggio, and Timothy K. Lu. “Synthetic Mixed-Signal Computation in Living Cells.” Nature Communications 7 (June 3, 2016): 11658. https://orcid.org/0000-0003-1304-0151 https://orcid.org/0000-0002-9999-6690 en_US http://dx.doi.org/10.1038/ncomms11658 Nature Communications Creative Commons Attribution http://creativecommons.org/licenses/by/4.0/ application/pdf Nature Publishing Group Nature |
| spellingShingle | Rubens, Jacob R. Selvaggio, Gianluca Lu, Timothy K. Synthetic mixed-signal computation in living cells |
| title | Synthetic mixed-signal computation in living cells |
| title_full | Synthetic mixed-signal computation in living cells |
| title_fullStr | Synthetic mixed-signal computation in living cells |
| title_full_unstemmed | Synthetic mixed-signal computation in living cells |
| title_short | Synthetic mixed-signal computation in living cells |
| title_sort | synthetic mixed signal computation in living cells |
| url | http://hdl.handle.net/1721.1/103081 https://orcid.org/0000-0003-1304-0151 https://orcid.org/0000-0002-9999-6690 |
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