Complex cellular logic computation using ribocomputing devices
Synthetic biology aims to develop engineering-driven approaches to the programming of cellular functions that could yield transformative technologies. Synthetic gene circuits that combine DNA, protein, and RNA components have demonstrated a range of functions such as bistability, oscillation, feedba...
| Hlavní autoři: | , , , , , |
|---|---|
| Další autoři: | |
| Médium: | Článek |
| Jazyk: | en_US |
| Vydáno: |
Nature Publishing Group
2018
|
| On-line přístup: | http://hdl.handle.net/1721.1/119230 https://orcid.org/0000-0002-5560-8246 |
| _version_ | 1826199952464805888 |
|---|---|
| author | Green, Alexander A. Kim, Jongmin Ma, Duo Silver, Pamela A. Yin, Peng Collins, James J. |
| author2 | Institute for Medical Engineering and Science |
| author_facet | Institute for Medical Engineering and Science Green, Alexander A. Kim, Jongmin Ma, Duo Silver, Pamela A. Yin, Peng Collins, James J. |
| author_sort | Green, Alexander A. |
| collection | MIT |
| description | Synthetic biology aims to develop engineering-driven approaches to the programming of cellular functions that could yield transformative technologies. Synthetic gene circuits that combine DNA, protein, and RNA components have demonstrated a range of functions such as bistability, oscillation, feedback, and logic capabilities. However, it remains challenging to scale up these circuits owing to the limited number of designable, orthogonal, high-performance parts, the empirical and often tedious composition rules, and the requirements for substantial resources for encoding and operation. Here, we report a strategy for constructing RNA-only nanodevices to evaluate complex logic in living cells. Our ‘ribocomputing’ systems are composed of de-novo-designed parts and operate through predictable and designable base-pairing rules, allowing the effective in silico design of computing devices with prescribed configurations and functions in complex cellular environments. These devices operate at the post-transcriptional level and use an extended RNA transcript to co-localize all circuit sensing, computation, signal transduction, and output elements in the same self-assembled molecular complex, which reduces diffusion-mediated signal losses, lowers metabolic cost, and improves circuit reliability. We demonstrate that ribocomputing devices in Escherichia coli can evaluate two-input logic with a dynamic range up to 900-fold and scale them to four-input AND, six-input OR, and a complex 12-input expression (A1 AND A2 AND NOT A1*) OR (B1 AND B2 AND NOT B2*) OR (C1 AND C2) OR (D1 AND D2) OR (E1 AND E2). Successful operation of ribocomputing devices based on programmable RNA interactions suggests that systems employing the same design principles could be implemented in other host organisms or in extracellular settings. |
| first_indexed | 2024-09-23T11:28:44Z |
| format | Article |
| id | mit-1721.1/119230 |
| institution | Massachusetts Institute of Technology |
| language | en_US |
| last_indexed | 2024-09-23T11:28:44Z |
| publishDate | 2018 |
| publisher | Nature Publishing Group |
| record_format | dspace |
| spelling | mit-1721.1/1192302022-09-27T19:49:24Z Complex cellular logic computation using ribocomputing devices Green, Alexander A. Kim, Jongmin Ma, Duo Silver, Pamela A. Yin, Peng Collins, James J. Institute for Medical Engineering and Science Massachusetts Institute of Technology. Department of Biological Engineering Massachusetts Institute of Technology. Synthetic Biology Center Collins, James J Collins, James J. Synthetic biology aims to develop engineering-driven approaches to the programming of cellular functions that could yield transformative technologies. Synthetic gene circuits that combine DNA, protein, and RNA components have demonstrated a range of functions such as bistability, oscillation, feedback, and logic capabilities. However, it remains challenging to scale up these circuits owing to the limited number of designable, orthogonal, high-performance parts, the empirical and often tedious composition rules, and the requirements for substantial resources for encoding and operation. Here, we report a strategy for constructing RNA-only nanodevices to evaluate complex logic in living cells. Our ‘ribocomputing’ systems are composed of de-novo-designed parts and operate through predictable and designable base-pairing rules, allowing the effective in silico design of computing devices with prescribed configurations and functions in complex cellular environments. These devices operate at the post-transcriptional level and use an extended RNA transcript to co-localize all circuit sensing, computation, signal transduction, and output elements in the same self-assembled molecular complex, which reduces diffusion-mediated signal losses, lowers metabolic cost, and improves circuit reliability. We demonstrate that ribocomputing devices in Escherichia coli can evaluate two-input logic with a dynamic range up to 900-fold and scale them to four-input AND, six-input OR, and a complex 12-input expression (A1 AND A2 AND NOT A1*) OR (B1 AND B2 AND NOT B2*) OR (C1 AND C2) OR (D1 AND D2) OR (E1 AND E2). Successful operation of ribocomputing devices based on programmable RNA interactions suggests that systems employing the same design principles could be implemented in other host organisms or in extracellular settings. National Institutes of Health (U.S.) (Grant 1DP2OD007292) National Institutes of Health (U.S.) (Grant 1R01EB018659) United States. Office of Naval Research (Award N000141110914) United States. Office of Naval Research (Grant N000141010827) United States. Office of Naval Research (Grant N000141310593) United States. Office of Naval Research (Grant N000141410610) United States. Office of Naval Research (Grant N000141612410) National Science Foundation (U.S.) (Grant CCF1054898) National Science Foundation (U.S.) (Grant CCF1317291) National Science Foundation (U.S.) (Grant CCF1162459) United States. Defense Advanced Research Projects Agency (Grant HR001112C0061) Defense Threat Reduction Agency (DTRA) (Grant HDTRA1-15-1-0040) 2018-11-20T17:23:04Z 2018-11-20T17:23:04Z 2017-07 2016-07 Article http://purl.org/eprint/type/JournalArticle 0028-0836 1476-4687 http://hdl.handle.net/1721.1/119230 Green, Alexander A. et al. “Complex Cellular Logic Computation Using Ribocomputing Devices.” Nature 548, 7665 (July 2017): 117–121 © 2017 Nature Publishing Group https://orcid.org/0000-0002-5560-8246 en_US https://doi.org/10.1038/nature23271 Nature Creative Commons Attribution-Noncommercial-Share Alike http://creativecommons.org/licenses/by-nc-sa/4.0/ application/pdf Nature Publishing Group Prof. Collins via Howard Silver |
| spellingShingle | Green, Alexander A. Kim, Jongmin Ma, Duo Silver, Pamela A. Yin, Peng Collins, James J. Complex cellular logic computation using ribocomputing devices |
| title | Complex cellular logic computation using ribocomputing devices |
| title_full | Complex cellular logic computation using ribocomputing devices |
| title_fullStr | Complex cellular logic computation using ribocomputing devices |
| title_full_unstemmed | Complex cellular logic computation using ribocomputing devices |
| title_short | Complex cellular logic computation using ribocomputing devices |
| title_sort | complex cellular logic computation using ribocomputing devices |
| url | http://hdl.handle.net/1721.1/119230 https://orcid.org/0000-0002-5560-8246 |
| work_keys_str_mv | AT greenalexandera complexcellularlogiccomputationusingribocomputingdevices AT kimjongmin complexcellularlogiccomputationusingribocomputingdevices AT maduo complexcellularlogiccomputationusingribocomputingdevices AT silverpamelaa complexcellularlogiccomputationusingribocomputingdevices AT yinpeng complexcellularlogiccomputationusingribocomputingdevices AT collinsjamesj complexcellularlogiccomputationusingribocomputingdevices |