Synthetic negative feedback circuits using engineered small RNAs
Negative feedback is known to enable biological and man-made systems to perform reliably in the face of uncertainties and disturbances. To date, synthetic biological feedback circuits have primarily relied upon protein-based, transcriptional regulation to control circuit output. Small RNAs (sRNAs) a...
| Main Authors: | , , , , , |
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| Format: | Journal article |
| Language: | English |
| Published: |
Oxford University Press
2018
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| _version_ | 1826262437333041152 |
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| author | Kelly, C Harris, A Steel, H Hancock, E Heap, J Papachristodoulou, A |
| author_facet | Kelly, C Harris, A Steel, H Hancock, E Heap, J Papachristodoulou, A |
| author_sort | Kelly, C |
| collection | OXFORD |
| description | Negative feedback is known to enable biological and man-made systems to perform reliably in the face of uncertainties and disturbances. To date, synthetic biological feedback circuits have primarily relied upon protein-based, transcriptional regulation to control circuit output. Small RNAs (sRNAs) are non-coding RNA molecules that can inhibit translation of target messenger RNAs (mRNAs). In this work, we modelled, built and validated two synthetic negative feedback circuits that use rationally-designed sRNAs for the first time. The first circuit builds upon the well characterised tet-based autorepressor, incorporating an externally-inducible sRNA to tune the effective feedback strength. This allows more precise fine-tuning of the circuit output in contrast to the sigmoidal, steep input–output response of the autorepressor alone. In the second circuit, the output is a transcription factor that induces expression of an sRNA, which inhibits translation of the mRNA encoding the output, creating direct, closed-loop, negative feedback. Analysis of the noise profiles of both circuits showed that the use of sRNAs did not result in large increases in noise. Stochastic and deterministic modelling of both circuits agreed well with experimental data. Finally, simulations using fitted parameters allowed dynamic attributes of each circuit such as response time and disturbance rejection to be investigated. |
| first_indexed | 2024-03-06T19:36:09Z |
| format | Journal article |
| id | oxford-uuid:1f1cc12e-6d4c-4be6-a29e-8ec9e4057f84 |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-06T19:36:09Z |
| publishDate | 2018 |
| publisher | Oxford University Press |
| record_format | dspace |
| spelling | oxford-uuid:1f1cc12e-6d4c-4be6-a29e-8ec9e4057f842022-03-26T11:20:08ZSynthetic negative feedback circuits using engineered small RNAsJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:1f1cc12e-6d4c-4be6-a29e-8ec9e4057f84EnglishSymplectic Elements at OxfordOxford University Press2018Kelly, CHarris, ASteel, HHancock, EHeap, JPapachristodoulou, ANegative feedback is known to enable biological and man-made systems to perform reliably in the face of uncertainties and disturbances. To date, synthetic biological feedback circuits have primarily relied upon protein-based, transcriptional regulation to control circuit output. Small RNAs (sRNAs) are non-coding RNA molecules that can inhibit translation of target messenger RNAs (mRNAs). In this work, we modelled, built and validated two synthetic negative feedback circuits that use rationally-designed sRNAs for the first time. The first circuit builds upon the well characterised tet-based autorepressor, incorporating an externally-inducible sRNA to tune the effective feedback strength. This allows more precise fine-tuning of the circuit output in contrast to the sigmoidal, steep input–output response of the autorepressor alone. In the second circuit, the output is a transcription factor that induces expression of an sRNA, which inhibits translation of the mRNA encoding the output, creating direct, closed-loop, negative feedback. Analysis of the noise profiles of both circuits showed that the use of sRNAs did not result in large increases in noise. Stochastic and deterministic modelling of both circuits agreed well with experimental data. Finally, simulations using fitted parameters allowed dynamic attributes of each circuit such as response time and disturbance rejection to be investigated. |
| spellingShingle | Kelly, C Harris, A Steel, H Hancock, E Heap, J Papachristodoulou, A Synthetic negative feedback circuits using engineered small RNAs |
| title | Synthetic negative feedback circuits using engineered small RNAs |
| title_full | Synthetic negative feedback circuits using engineered small RNAs |
| title_fullStr | Synthetic negative feedback circuits using engineered small RNAs |
| title_full_unstemmed | Synthetic negative feedback circuits using engineered small RNAs |
| title_short | Synthetic negative feedback circuits using engineered small RNAs |
| title_sort | synthetic negative feedback circuits using engineered small rnas |
| work_keys_str_mv | AT kellyc syntheticnegativefeedbackcircuitsusingengineeredsmallrnas AT harrisa syntheticnegativefeedbackcircuitsusingengineeredsmallrnas AT steelh syntheticnegativefeedbackcircuitsusingengineeredsmallrnas AT hancocke syntheticnegativefeedbackcircuitsusingengineeredsmallrnas AT heapj syntheticnegativefeedbackcircuitsusingengineeredsmallrnas AT papachristodouloua syntheticnegativefeedbackcircuitsusingengineeredsmallrnas |