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Our enhanced understanding of RNA folding and function has increased the use of small RNA regulators. Among these RNA regulators, synthetic antisense RNA (asRNA) is designed to contain an RNA sequence complementary to the target mRNA sequence, and the formation of double-stranded RNA (dsRNA) facilitates gene repression due to dsRNA degradation or prevention of ribosome access to the mRNA. Despite the simple complementarity rule, however, predictably tunable repression has been challenging when synthetic asRNAs are used. Here, the protocol for model-based asRNA design is described. This model can predict synthetic asRNA-mediated repression efficiency using two parameters: the change in free energy of complex formation (ΔGCF) and percent mismatch of the target binding region (TBR). The model has been experimentally validated in both Gram-positive and Gram-negative bacteria as well as for target genes in both plasmids and chromosomes. These asRNAs can be created by simply replacing the TBR sequence with one that is complementary to the target mRNA sequence of interest. In principle, this protocol can be applied to design and build asRNAs for predictable gene repression in various contexts, including multiple target genes and organisms, making asRNAs predictably tunable regulators for broad applications.
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A portable regulatory RNA array design enables tunable and complex regulation across diverse bacteria
Abstract A lack of composable and tunable gene regulators has hindered efforts to engineer non-model bacteria and consortia. Toward addressing this, we explore the broad-host potential of small transcription activating RNA (STAR) and propose a design strategy to achieve tunable gene control. First, we demonstrate that STARs optimized forE. colifunction across different Gram-negative species and can actuate using phage RNA polymerase, suggesting that RNA systems acting at the level of transcription are portable. Second, we explore an RNA design strategy that uses arrays of tandem and transcriptionally fused RNA regulators to precisely alter regulator concentration from 1 to 8 copies. This provides a simple means to predictably tune output gain across species and does not require access to large regulatory part libraries. Finally, we show RNA arrays can be used to achieve tunable cascading and multiplexing circuits across species, analogous to the motifs used in artificial neural networks.
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- PAR ID:
- 10524037
- Editor(s):
- NA
- Publisher / Repository:
- Nature publishing group
- Date Published:
- Journal Name:
- Nature Communications
- Volume:
- 14
- Issue:
- 1
- ISSN:
- 2041-1723
- Subject(s) / Keyword(s):
- Synthetic biology, RNA regulators, Modularity
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1038/s41467-023-40785-x
