Biology subjects

Julius B Lucks

Publications and source records attributed to Julius B Lucks.

4 recordsLinked to original sources

bioRxiv2016

Achieving large dynamic range control of gene expression with a compact RNA transcription-translation regulator

RNA transcriptional regulators are emerging as versatile components for genetic circuit construction. However, RNA transcriptional regulators suffer from incomplete repression, making their dynamic range less than that of their protein counterparts. This incomplete repression can cause expression leak, which impedes the construction of larger RNA synthetic regulatory networks. Here we demonstrate how naturally derived antisense RNA-mediated transcriptional regulators can be configured to regulate both transcription and translation in a single compact RNA mechanism that functions in Escherichia coli. Using in vivo gene expression assays, we show that a combination of transcriptional termination and RBS sequestration increases repression from 85% to 98% and activation from 10 fold to over 900 fold in response to cognate antisense RNAs. We also show that orthogonal versions of this mechanism can be created through engineering minimal antisense RNAs. Finally, to demonstrate the utility of this dual control mechanism, we use it to reduce circuit leak in an RNA-only transcriptional cascade that activates gene expression as a function of a small molecule input. We anticipate these regulators will find broad use as synthetic biology moves beyond parts engineering to the design and construction of larger and more sophisticated circuits.

Synthetic Biology↗

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

Generating effective models and parameters for RNA genetic circuits

RNA genetic circuitry is emerging as a powerful tool to control gene expression. However, little work has been done to create a theoretical foundation for RNA circuit design. A prerequisite to this is a quantitative modeling framework that accurately describes the dynamics of RNA circuits. In this work, we develop an ordinary differential equation model of transcriptional RNA genetic circuitry, using an RNA cascade as a test case. We show that parameter sensitivity analysis can be used to design a set of four simple experiments that can be performed in parallel using rapid cell-free transcription-translation (TX-TL) reactions to determine the thirteen parameters of the model. The resulting model accurately recapitulates the dynamic behavior of the cascade, and can be easily extended to predict the function of new cascade variants that utilize new elements with limited additional characterization experiments. Interestingly, we show that inconsistencies between model predictions and experiments led to the model-guided discovery of a previously unknown maturation step required for RNA regulator function. We also determine circuit parameters in two different batches of TX-TL, and show that batch-to-batch variation can be attributed to differences in parameters that are directly related to the concentrations of core gene expression machinery. We anticipate the RNA circuit models developed here will inform the creation of computer aided genetic circuit design tools that can incorporate the growing number of RNA regulators, and that the parameterization method will find use in determining functional parameters of a broad array of natural and synthetic regulatory systems.\n\n\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=132 SRC=\"FIGDIR/small/018358_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (17K):\norg.highwire.dtl.DTLVardef@1eace4dorg.highwire.dtl.DTLVardef@8e2757org.highwire.dtl.DTLVardef@b8f454org.highwire.dtl.DTLVardef@b0cfc9_HPS_FORMAT_FIGEXP M_FIG C_FIG

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↗