Biology subjects

James Chappell

Publications and source records attributed to James Chappell.

3 recordsLinked to original sources

bioRxiv2015

Improving fold activation of small transcription activating RNAs (STARs) with rational RNA engineering strategies.

Engineered RNAs have become integral components of the synthetic biology and bioengineering toolbox for controlling gene expression. We recently expanded this toolbox by creating small transcription activating RNAs (STARs) that act by disrupting the formation of a target transcriptional terminator hairpin placed upstream of a gene. While STARs are a promising addition to the repertoire of RNA regulators, much work remains to be done to optimize the fold activation of these systems. Here we apply rational RNA engineering strategies to improve the fold activation of two STAR regulators. We demonstrate that a combination of promoter strength tuning and multiple RNA stabilization strategies can improve fold activation from 5.4-fold to 13.4-fold for a STAR regulator derived from the pbuE riboswitch terminator. We then validate the generality of our approach and show that these same strategies improve fold activation from 2.1-fold to 14.6-fold for an unrelated STAR regulator. We also establish that the optimizations preserve the orthogonality of these STARs between themselves and a set of antisense RNA transcriptional repressors, enabling these optimized STARs to be used in more sophisticated circuits. These optimization strategies open the door for creating a generation of additional STARs to use in a broad array of biotechnologies.

Synthetic Biology↗

bioRxiv2015

Characterizing and Prototyping Genetic Networks with Cell-Free Transcription-Translation Reactions

A central goal of synthetic biology is to engineer cellular behavior by engineering synthetic gene networks for a variety of biotechnology and medical applications. The process of engineering gene networks often involves an iterative design-build-test cycle, whereby the parts and connections that make up the network are built, characterized and varied until the desired network function is reached. Many advances have been made in the design and build portions of this cycle. However, the slow process of in vivo characterization of network function often limits the timescale of the testing step. Cell-free transcription-translation (TX-TL) systems offer a simple and fast alternative to performing these characterizations in cells. Here we provide an overview of a cell-free TX-TL system that utilizes the native Escherichia coli TX-TL machinery, thereby allowing a large repertoire of parts and networks to be characterized. As a way to demonstrate the utility of cell-free TX-TL, we illustrate the characterization of two genetic networks: an RNA transcriptional cascade and a protein regulated incoherent feed-forward loop. We also provide guidelines for designing TX-TL experiments to characterize new genetic networks. We end with a discussion of current and emerging applications of cell free systems.\n\nAbbreviations

Synthetic Biology↗

bioRxiv2014

Rapidly characterizing the fast dynamics of RNA genetic circuitry with cell-free transcription-translation (TX-TL) systems

RNA regulators are emerging as powerful tools to engineer synthetic genetic networks or rewire existing ones. A potential strength of RNA networks is that they may be able to propagate signals on timescales that are set by the fast degradation rates of RNAs. However, a current bottleneck to verifying this potential is the slow design-build-test cycle of evaluating these networks in vivo. Here we adapt an Escherichia coli-based cell-free transcription-translation (TX-TL) system for rapidly prototyping RNA networks. We used this system to measure the response time of an RNA transcription cascade to be approximately five minutes per step of the cascade. We also show that this response time can be adjusted with temperature and regulator threshold response tuning. Finally we use TX-TL to prototype a new RNA network, an RNA single input module, and show that this network temporally stages the expression of two genes in vivo.

Synthetic Biology↗