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Model-based investigation of the relationship between regulation level and pulse property of I1-FFL gene circuits
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Ryan, Jordan, Hong, Seungho, Foo, Mathias, Kim, Jongmin and Tang, Xun (2022) Model-based investigation of the relationship between regulation level and pulse property of I1-FFL gene circuits. ACS Synthetic Biology, 11 (7). pp. 2417-2428. doi:10.1021/acssynbio.2c00109 ISSN 2161-5063.
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Official URL: https://doi.org/10.1021/acssynbio.2c00109
Abstract
Mathematical models are powerful tools in guiding the construction of synthetic biological circuits, given their capability of accurately capturing and predicting circuit dynamics. Recent innovations in RNA technology have enabled the development of a variety of new tools for regulating gene expression at both the transcription and translation levels. However, the effects of different regulation levels on the circuit dynamics remain largely unexplored. In this study, we focus on the Type 1 incoherent feed-forward loop (I1-FFL) gene circuit with four different variations (TX, TL, HY-1, HY-2), to investigate how regulation at the transcription and translation levels affect the circuit dynamics. We develop a mechanistic model for each of the four circuits, and deploy sensitivity analysis to investigate the circuits’ dynamics in terms of pulse generation. Based on the analysis, we observe the repression regulation mechanism dominates the characteristics of the pulse as compared to the activation regulation mechanism, and find that the I1-FFL with transcription repression has a higher chance of generating a pulse meeting the desired criteria. The experimental results in E. coli also confirm our findings from the computational analysis. We expect our findings to facilitate future experimental construction of gene circuits with insights on the selection of appropriate transcription and translation regulation tools.
Item Type: | Journal Article | ||||||||
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Subjects: | Q Science > QH Natural history T Technology > TA Engineering (General). Civil engineering (General) |
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Divisions: | Faculty of Science, Engineering and Medicine > Engineering > Engineering | ||||||||
Library of Congress Subject Headings (LCSH): | Synthetic biology , RNA, Genetic engineering, Synthetic biology -- Mathematical models | ||||||||
Journal or Publication Title: | ACS Synthetic Biology | ||||||||
Publisher: | American Chemical Society | ||||||||
ISSN: | 2161-5063 | ||||||||
Official Date: | 15 July 2022 | ||||||||
Dates: |
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Volume: | 11 | ||||||||
Number: | 7 | ||||||||
Page Range: | pp. 2417-2428 | ||||||||
DOI: | 10.1021/acssynbio.2c00109 | ||||||||
Status: | Peer Reviewed | ||||||||
Publication Status: | Published | ||||||||
Access rights to Published version: | Open Access (Creative Commons) | ||||||||
Date of first compliant deposit: | 23 June 2022 | ||||||||
Date of first compliant Open Access: | 24 June 2022 | ||||||||
RIOXX Funder/Project Grant: |
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