Predicting Composition of Genetic Circuits with Resource Competition: Demand and Sensitivity
The design of genetic circuits typically relies on characterization of constituent modules in isolation to predict the behavior of modules' composition. However, it has been shown that the behavior of a genetic module changes when other modules are in the cell due to competition for shared reso...
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Language: | English |
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American Chemical Society (ACS)
2021
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Online Access: | https://hdl.handle.net/1721.1/138591 |
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author | McBride, Cameron D Del Vecchio, Domitilla |
author2 | Massachusetts Institute of Technology. Department of Mechanical Engineering |
author_facet | Massachusetts Institute of Technology. Department of Mechanical Engineering McBride, Cameron D Del Vecchio, Domitilla |
author_sort | McBride, Cameron D |
collection | MIT |
description | The design of genetic circuits typically relies on characterization of constituent modules in isolation to predict the behavior of modules' composition. However, it has been shown that the behavior of a genetic module changes when other modules are in the cell due to competition for shared resources. In order to engineer multimodule circuits that behave as intended, it is thus necessary to predict changes in the behavior of a genetic module when other modules load cellular resources. Here, we introduce two characteristics of circuit modules: the demand for cellular resources and the sensitivity to resource loading. When both are known for every genetic module in a circuit library, they can be used to predict any module's behavior upon addition of any other module to the cell. We develop an experimental approach to measure both characteristics for any circuit module using a resource sensor module. Using the measured resource demand and sensitivity for each module in a library, the outputs of the modules can be accurately predicted when they are inserted in the cell in arbitrary combinations. These resource competition characteristics may be used to inform the design of genetic circuits that perform as predicted despite resource competition. |
first_indexed | 2024-09-23T14:51:33Z |
format | Article |
id | mit-1721.1/138591 |
institution | Massachusetts Institute of Technology |
language | English |
last_indexed | 2024-09-23T14:51:33Z |
publishDate | 2021 |
publisher | American Chemical Society (ACS) |
record_format | dspace |
spelling | mit-1721.1/1385912023-06-20T16:59:07Z Predicting Composition of Genetic Circuits with Resource Competition: Demand and Sensitivity McBride, Cameron D Del Vecchio, Domitilla Massachusetts Institute of Technology. Department of Mechanical Engineering The design of genetic circuits typically relies on characterization of constituent modules in isolation to predict the behavior of modules' composition. However, it has been shown that the behavior of a genetic module changes when other modules are in the cell due to competition for shared resources. In order to engineer multimodule circuits that behave as intended, it is thus necessary to predict changes in the behavior of a genetic module when other modules load cellular resources. Here, we introduce two characteristics of circuit modules: the demand for cellular resources and the sensitivity to resource loading. When both are known for every genetic module in a circuit library, they can be used to predict any module's behavior upon addition of any other module to the cell. We develop an experimental approach to measure both characteristics for any circuit module using a resource sensor module. Using the measured resource demand and sensitivity for each module in a library, the outputs of the modules can be accurately predicted when they are inserted in the cell in arbitrary combinations. These resource competition characteristics may be used to inform the design of genetic circuits that perform as predicted despite resource competition. 2021-12-17T18:28:40Z 2021-12-17T18:28:40Z 2021-11-15 2021-12-17T18:08:10Z Article http://purl.org/eprint/type/JournalArticle https://hdl.handle.net/1721.1/138591 McBride, Cameron D and Del Vecchio, Domitilla. 2021. "Predicting Composition of Genetic Circuits with Resource Competition: Demand and Sensitivity." ACS Synthetic Biology. en 10.1021/acssynbio.1c00281 ACS Synthetic Biology Creative Commons Attribution-Noncommercial-Share Alike http://creativecommons.org/licenses/by-nc-sa/4.0/ application/pdf American Chemical Society (ACS) MIT web domain |
spellingShingle | McBride, Cameron D Del Vecchio, Domitilla Predicting Composition of Genetic Circuits with Resource Competition: Demand and Sensitivity |
title | Predicting Composition of Genetic Circuits with Resource Competition: Demand and Sensitivity |
title_full | Predicting Composition of Genetic Circuits with Resource Competition: Demand and Sensitivity |
title_fullStr | Predicting Composition of Genetic Circuits with Resource Competition: Demand and Sensitivity |
title_full_unstemmed | Predicting Composition of Genetic Circuits with Resource Competition: Demand and Sensitivity |
title_short | Predicting Composition of Genetic Circuits with Resource Competition: Demand and Sensitivity |
title_sort | predicting composition of genetic circuits with resource competition demand and sensitivity |
url | https://hdl.handle.net/1721.1/138591 |
work_keys_str_mv | AT mcbridecamerond predictingcompositionofgeneticcircuitswithresourcecompetitiondemandandsensitivity AT delvecchiodomitilla predictingcompositionofgeneticcircuitswithresourcecompetitiondemandandsensitivity |